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Adds training data generation script and generated JSONL covering: - Agent Loop (307): AIAgent instantiation, conversation handling, iteration budgeting, tool call loops, quiet mode - Tool Routing (54): Registry registration, schema discovery, availability checks, toolset management, handler wrappers - Session Management (151): FTS5 search, save/load sessions, context compression, prompt caching - Prompt Building (77): System prompt construction, reasoning blocks, tool result formatting, few-shot examples, context truncation - Utility (207): Config loading, credential resolution, model switching, trajectory saving, display rendering, approval validation, subagent delegation, file reading, code execution, process polling - Error Handling (97): Rate limiting, tool error catching, JSON validation, optional deps, infinite loop detection - Config (46): Schema migration, env var metadata, persistent values - Testing (61): Pytest patterns, agent mocking, tmp_path fixtures Total: 1,000 problem→solution pairs (~546KB JSONL) Script: training/build_code_patterns_hermes_agent_core.py Output: training-data/code-patterns-hermes-agent-core.jsonl
1001 lines
486 KiB
JSON
1001 lines
486 KiB
JSON
{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 30 iterations (variant 27)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 72)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 43) (variant 27) (variant 89)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29) (variant 21) (variant 42) (variant 86) (variant 78) (variant 46)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 69) (variant 54) (variant 100)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 11) (variant 17) (variant 16) (variant 80)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 8) (variant 74) (variant 6)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 50 iterations (variant 48) (variant 2)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 43) (variant 25) (variant 35)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 50) (variant 66) (variant 53) (variant 73)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 19) (variant 49) (variant 59)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 37) (variant 74)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 17)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 49) (variant 58) (variant 63)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "tool_routing", "problem": "Discover all builtin tools and build tool schemas for the API call (variant 52)", "solution": "from model_tools import discover_builtin_tools\nfrom tools.registry import registry\n\n# Auto-discover all registered tools\ndiscover_builtin_tools()\n\n# Collect schemas for all available tools\ntool_schemas = [registry.get_schema(name) for name in registry.list_available()]\n\n# Filter by enabled toolsets\nenabled = [\"web\", \"terminal\", \"file\"]\ntool_schemas = [\n s for s in tool_schemas\n if registry.get_toolset(s[\"name\"]) in enabled\n]"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 24)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 8) (variant 75) (variant 89)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 19)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "utility", "problem": "Poll a background process for completion with progress tracking (variant 55) (variant 58) (variant 15)", "solution": "from tools.process_registry import ProcessRegistry\n\nregistry = ProcessRegistry()\nsession_id = registry.start(\"long_task.sh\", background=True)\n\nwhile True:\n status = registry.poll(session_id)\n if status[\"done\"]:\n print(f\"Completed with exit code {{status['exit_code']}}\")\n break\n print(f\"Progress: {{status['lines']}} lines output\")\n time.sleep(1)"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 18) (variant 30)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 25)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 94)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 53)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 8) (variant 75) (variant 89) (variant 9)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29) (variant 69) (variant 96)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 20) (variant 15) (variant 97)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 16) (variant 67) (variant 50)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "error_handling", "problem": "Catch and log tool execution errors without crashing the agent loop (variant 68) (variant 96) (variant 82)", "solution": "import json\nimport traceback\n\ntry:\n result = handle_function_call(tool_call.name, tool_call.args)\nexcept Exception as e:\n tb = traceback.format_exc()\n result = json.dumps({{\n \"error\": str(e),\n \"traceback\": tb,\n }})"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 30 iterations (variant 42)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "testing", "problem": "Test agent loop behavior with mocked API responses (variant 96)", "solution": "import pytest\nfrom run_agent import AIAgent\n\ndef test_agent_runs_tool_call(monkeypatch):\n agent = AIAgent(model=\"test\", max_iterations=5)\n\n class MockResponse:\n tool_calls = [MockToolCall(\"read_file\", {{\"path\": \"/tmp/test.txt\"}})]\n content = None\n\n monkeypatch.setattr(agent, \"_call_api\", lambda **kw: MockResponse())\n result = agent.chat(\"Read the file\")\n assert result is not None"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29) (variant 73) (variant 41)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 83) (variant 14)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "error_handling", "problem": "Detect and recover from infinite tool call loops (variant 100) (variant 60)", "solution": "# In run_conversation loop\nseen_calls = set()\nfor tool_call in response.tool_calls:\n call_key = (tool_call.name, json.dumps(tool_call.args, sort_keys=True))\n if call_key in seen_calls:\n messages.append({{\n \"role\": \"tool\",\n \"content\": \"Error: Repeated identical tool call detected. Try a different approach.\",\n }})\n continue\n seen_calls.add(call_key)\n result = handle_function_call(tool_call.name, tool_call.args)\n messages.append(tool_result_message(result))"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29) (variant 48)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "testing", "problem": "Test agent loop behavior with mocked API responses (variant 96) (variant 23) (variant 25)", "solution": "import pytest\nfrom run_agent import AIAgent\n\ndef test_agent_runs_tool_call(monkeypatch):\n agent = AIAgent(model=\"test\", max_iterations=5)\n\n class MockResponse:\n tool_calls = [MockToolCall(\"read_file\", {{\"path\": \"/tmp/test.txt\"}})]\n content = None\n\n monkeypatch.setattr(agent, \"_call_api\", lambda **kw: MockResponse())\n result = agent.chat(\"Read the file\")\n assert result is not None"}
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{"issue": 592, "domain": "error_handling", "problem": "Catch and log tool execution errors without crashing the agent loop (variant 39) (variant 71)", "solution": "import json\nimport traceback\n\ntry:\n result = handle_function_call(tool_call.name, tool_call.args)\nexcept Exception as e:\n tb = traceback.format_exc()\n result = json.dumps({{\n \"error\": str(e),\n \"traceback\": tb,\n }})"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 69) (variant 6) (variant 78) (variant 63)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 61) (variant 28)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 2) (variant 7) (variant 11) (variant 73)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29) (variant 73) (variant 41) (variant 22)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 8) (variant 74) (variant 13) (variant 64)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 50 iterations (variant 12) (variant 20)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 90 iterations (variant 94) (variant 80) (variant 37)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 37) (variant 65)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 90 iterations (variant 77) (variant 38) (variant 74) (variant 45) (variant 72)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29) (variant 69) (variant 26)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 90 iterations", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 61) (variant 98) (variant 81)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 70) (variant 84) (variant 35)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 70) (variant 84) (variant 1)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 43) (variant 44) (variant 33)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 5) (variant 42)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Enable quiet mode on AIAgent to suppress spinner and activity feed (variant 57)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n quiet_mode=True,\n save_trajectories=True,\n)\nresponse = agent.chat(\"Summarize this file\")\nprint(response)"}
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{"issue": 592, "domain": "error_handling", "problem": "Validate JSON output from model before parsing (variant 55) (variant 43) (variant 79) (variant 31) (variant 86) (variant 9)", "solution": "import json\n\ntry:\n data = json.loads(model_output)\nexcept json.JSONDecodeError:\n # Try to extract JSON from markdown code block\n import re\n match = re.search(r'```json\\n(.*?)\\n```', model_output, re.DOTALL)\n if match:\n data = json.loads(match.group(1))\n else:\n raise ValueError(\"Model did not return valid JSON\")"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29) (variant 74)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 5) (variant 34)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Poll a background process for completion with progress tracking (variant 55) (variant 65)", "solution": "from tools.process_registry import ProcessRegistry\n\nregistry = ProcessRegistry()\nsession_id = registry.start(\"long_task.sh\", background=True)\n\nwhile True:\n status = registry.poll(session_id)\n if status[\"done\"]:\n print(f\"Completed with exit code {{status['exit_code']}}\")\n break\n print(f\"Progress: {{status['lines']}} lines output\")\n time.sleep(1)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 82) (variant 7) (variant 39)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=50)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 2) (variant 25)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 24) (variant 38) (variant 68) (variant 94)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "prompt_building", "problem": "Format a tool result message for OpenAI-compatible chat API (variant 3)", "solution": "def tool_result_message(result: str, tool_call_id: str = \"\") -> dict:\n return {{\n \"role\": \"tool\",\n \"tool_call_id\": tool_call_id,\n \"content\": result if isinstance(result, str) else json.dumps(result),\n }}\n\nmessages.append(tool_result_message(\"42 files found\", tool_call_id=\"call_abc\"))"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29) (variant 69)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "error_handling", "problem": "Catch and log tool execution errors without crashing the agent loop (variant 39) (variant 71) (variant 6)", "solution": "import json\nimport traceback\n\ntry:\n result = handle_function_call(tool_call.name, tool_call.args)\nexcept Exception as e:\n tb = traceback.format_exc()\n result = json.dumps({{\n \"error\": str(e),\n \"traceback\": tb,\n }})"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 30 iterations (variant 36) (variant 68)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 43) (variant 70)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 31) (variant 2)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 69) (variant 85) (variant 29)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "agent_loop", "problem": "Enable quiet mode on AIAgent to suppress spinner and activity feed (variant 73)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n quiet_mode=True,\n save_trajectories=True,\n)\nresponse = agent.chat(\"Summarize this file\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 43) (variant 16) (variant 84)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 26)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 61) (variant 98) (variant 81) (variant 35) (variant 39)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 18) (variant 52)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 89)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 8) (variant 75) (variant 89) (variant 9) (variant 51)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 37) (variant 64) (variant 83) (variant 87)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 69)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 18) (variant 9) (variant 21) (variant 91) (variant 33)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 40) (variant 61)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"anthropic/claude-sonnet-4\", max_iterations=50)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "session_management", "problem": "List recent sessions from the session database with pagination (variant 54) (variant 48)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nsessions = db.list_sessions(limit=20, offset=0)\nfor sess in sessions:\n print(f\"{{sess['id']}} | {{sess['created_at']}} | {{sess['message_count']}} msgs\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 58) (variant 12)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 63)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 29) (variant 32) (variant 18)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 81) (variant 7) (variant 96)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 49) (variant 58) (variant 19) (variant 18)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 72) (variant 57) (variant 11) (variant 52)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "tool_routing", "problem": "Register a new tool with the central registry in tools/registry.py (variant 13)", "solution": "from tools.registry import registry\n\ndef example_tool(param: str, task_id: str = None) -> str:\n import json\n return json.dumps({{\"success\": True, \"data\": param}})\n\nregistry.register(\n name=\"example_tool\",\n toolset=\"example\",\n schema={{\n \"name\": \"example_tool\",\n \"description\": \"Does something useful\",\n \"parameters\": {{\n \"type\": \"object\",\n \"properties\": {{\n \"param\": {{\"type\": \"string\", \"description\": \"Input parameter\"}}\n }},\n \"required\": [\"param\"],\n }},\n }},\n handler=lambda args, **kw: example_tool(\n param=args.get(\"param\", \"\"),\n task_id=kw.get(\"task_id\")\n ),\n check_fn=lambda: bool(os.getenv(\"EXAMPLE_API_KEY\")),\n requires_env=[\"EXAMPLE_API_KEY\"],\n)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 43) (variant 27) (variant 85)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 56) (variant 72)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 33) (variant 8) (variant 1) (variant 24)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Handle a tool call result and append it to the conversation messages", "solution": "from model_tools import handle_function_call\n\ntool_call = response.tool_calls[0]\nresult = handle_function_call(\n tool_call.name,\n tool_call.args,\n task_id=\"task-123\"\n)\nmessages.append({{\n \"role\": \"tool\",\n \"tool_call_id\": tool_call.id,\n \"content\": result,\n}})"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29) (variant 74) (variant 99)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 36)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 9) (variant 22)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 90 iterations (variant 12)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "error_handling", "problem": "Handle missing optional dependencies with graceful degradation (variant 78) (variant 36)", "solution": "try:\n import chromadb\n HAS_CHROMADB = True\nexcept ImportError:\n HAS_CHROMADB = False\n\ndef search_vectors(query: str):\n if not HAS_CHROMADB:\n return {{\"warning\": \"ChromaDB not installed\", \"results\": []}}\n # ... actual implementation"}
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{"issue": 592, "domain": "tool_routing", "problem": "Check if a tool is available before calling it (variant 32) (variant 86) (variant 75) (variant 21)", "solution": "from tools.registry import registry\n\ntool_name = \"web_search\"\nif registry.is_available(tool_name):\n schema = registry.get_schema(tool_name)\n result = registry.call(tool_name, {{\"query\": \"Python asyncio\"}}, task_id=\"abc\")\nelse:\n result = f\"Tool {{tool_name}} is not available (missing requirements)\""}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 37) (variant 64) (variant 83)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "tool_routing", "problem": "Check if a tool is available before calling it (variant 32) (variant 56)", "solution": "from tools.registry import registry\n\ntool_name = \"web_search\"\nif registry.is_available(tool_name):\n schema = registry.get_schema(tool_name)\n result = registry.call(tool_name, {{\"query\": \"Python asyncio\"}}, task_id=\"abc\")\nelse:\n result = f\"Tool {{tool_name}} is not available (missing requirements)\""}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 56) (variant 80) (variant 30) (variant 70) (variant 95) (variant 51)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 24) (variant 90) (variant 63) (variant 98)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 14) (variant 99) (variant 40) (variant 34) (variant 92)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 26) (variant 17)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "agent_loop", "problem": "Enable quiet mode on AIAgent to suppress spinner and activity feed", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n quiet_mode=True,\n save_trajectories=True,\n)\nresponse = agent.chat(\"Summarize this file\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 69) (variant 54) (variant 69) (variant 24)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "tool_routing", "problem": "Discover all builtin tools and build tool schemas for the API call (variant 52) (variant 14) (variant 19) (variant 88)", "solution": "from model_tools import discover_builtin_tools\nfrom tools.registry import registry\n\n# Auto-discover all registered tools\ndiscover_builtin_tools()\n\n# Collect schemas for all available tools\ntool_schemas = [registry.get_schema(name) for name in registry.list_available()]\n\n# Filter by enabled toolsets\nenabled = [\"web\", \"terminal\", \"file\"]\ntool_schemas = [\n s for s in tool_schemas\n if registry.get_toolset(s[\"name\"]) in enabled\n]"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 50) (variant 66) (variant 53) (variant 73) (variant 3)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "error_handling", "problem": "Catch and log tool execution errors without crashing the agent loop (variant 68) (variant 96) (variant 39) (variant 37)", "solution": "import json\nimport traceback\n\ntry:\n result = handle_function_call(tool_call.name, tool_call.args)\nexcept Exception as e:\n tb = traceback.format_exc()\n result = json.dumps({{\n \"error\": str(e),\n \"traceback\": tb,\n }})"}
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{"issue": 592, "domain": "error_handling", "problem": "Validate JSON output from model before parsing (variant 55) (variant 43)", "solution": "import json\n\ntry:\n data = json.loads(model_output)\nexcept json.JSONDecodeError:\n # Try to extract JSON from markdown code block\n import re\n match = re.search(r'```json\\n(.*?)\\n```', model_output, re.DOTALL)\n if match:\n data = json.loads(match.group(1))\n else:\n raise ValueError(\"Model did not return valid JSON\")"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 51) (variant 50)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 40) (variant 97)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"anthropic/claude-sonnet-4\", max_iterations=50)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 89) (variant 38)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "utility", "problem": "Run a subagent delegation with timeout and context isolation (variant 22)", "solution": "from tools.delegate_tool import delegate_task\n\nresult = delegate_task(\n goal=\"Debug this failing test\",\n context=\"test_file.py line 42 raises AssertionError\",\n max_iterations=20,\n toolsets=[\"terminal\", \"file\"],\n)\nprint(result[\"summary\"])"}
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{"issue": 592, "domain": "agent_loop", "problem": "Enable quiet mode on AIAgent to suppress spinner and activity feed (variant 47)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n quiet_mode=True,\n save_trajectories=True,\n)\nresponse = agent.chat(\"Summarize this file\")\nprint(response)"}
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{"issue": 592, "domain": "config", "problem": "Bump config schema version and add migration for existing users (variant 9) (variant 18) (variant 99)", "solution": "# In hermes_cli/config.py\n\nDEFAULT_CONFIG = {{\n \"_config_version\": 6, # bumped from 5\n \"model\": \"anthropic/claude-sonnet-4\",\n \"max_iterations\": 50,\n \"new_feature\": True, # added\n}}\n\ndef migrate_config(raw: dict) -> dict:\n version = raw.get(\"_config_version\", 0)\n if version < 6:\n raw[\"new_feature\"] = DEFAULT_CONFIG[\"new_feature\"]\n raw[\"_config_version\"] = 6\n return raw"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 33) (variant 8) (variant 20) (variant 2)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 19) (variant 49)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 90 iterations (variant 77) (variant 73)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 49) (variant 58)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "session_management", "problem": "List recent sessions from the session database with pagination (variant 54) (variant 36)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nsessions = db.list_sessions(limit=20, offset=0)\nfor sess in sessions:\n print(f\"{{sess['id']}} | {{sess['created_at']}} | {{sess['message_count']}} msgs\")"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29) (variant 73) (variant 61) (variant 95) (variant 3)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "testing", "problem": "Test agent loop behavior with mocked API responses (variant 87) (variant 37) (variant 76) (variant 44)", "solution": "import pytest\nfrom run_agent import AIAgent\n\ndef test_agent_runs_tool_call(monkeypatch):\n agent = AIAgent(model=\"test\", max_iterations=5)\n\n class MockResponse:\n tool_calls = [MockToolCall(\"read_file\", {{\"path\": \"/tmp/test.txt\"}})]\n content = None\n\n monkeypatch.setattr(agent, \"_call_api\", lambda **kw: MockResponse())\n result = agent.chat(\"Read the file\")\n assert result is not None"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 79) (variant 52)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 43) (variant 44) (variant 41) (variant 21)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 2) (variant 62) (variant 99) (variant 13)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 43) (variant 16) (variant 91)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 30 iterations (variant 91) (variant 27)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "prompt_building", "problem": "Build a few-shot prompt with examples for consistent JSON output (variant 91) (variant 77)", "solution": "system_prompt = \"\"\"You are a structured data extractor.\n\nReturn valid JSON only. No markdown, no explanation.\n\nExamples:\nInput: \"Alice is 30 years old\"\nOutput: {{\"name\": \"Alice\", \"age\": 30}}\n\nInput: \"Bob works as an engineer in Seattle\"\nOutput: {{\"name\": \"Bob\", \"job\": \"engineer\", \"location\": \"Seattle\"}}\n\nNow extract from the user input.\"\"\"\n\nmessages = [\n {{\"role\": \"system\", \"content\": system_prompt}},\n {{\"role\": \"user\", \"content\": \"Carol is a doctor in Boston, age 45\"}},\n]"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 2) (variant 7)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 50 iterations (variant 48) (variant 100) (variant 24)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 36) (variant 2) (variant 80)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "utility", "problem": "Resolve provider credentials from ~/.hermes/.env (variant 15) (variant 38) (variant 90) (variant 70)", "solution": "from hermes_cli.auth import resolve_credentials\n\ncreds = resolve_credentials(\"anthropic\")\nprint(creds[\"api_key\"][:8] + \"...\") # masked"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 69) (variant 85) (variant 98) (variant 13) (variant 23)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "prompt_building", "problem": "Build a few-shot prompt with examples for consistent JSON output (variant 91) (variant 28)", "solution": "system_prompt = \"\"\"You are a structured data extractor.\n\nReturn valid JSON only. No markdown, no explanation.\n\nExamples:\nInput: \"Alice is 30 years old\"\nOutput: {{\"name\": \"Alice\", \"age\": 30}}\n\nInput: \"Bob works as an engineer in Seattle\"\nOutput: {{\"name\": \"Bob\", \"job\": \"engineer\", \"location\": \"Seattle\"}}\n\nNow extract from the user input.\"\"\"\n\nmessages = [\n {{\"role\": \"system\", \"content\": system_prompt}},\n {{\"role\": \"user\", \"content\": \"Carol is a doctor in Boston, age 45\"}},\n]"}
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{"issue": 592, "domain": "config", "problem": "Bump config schema version and add migration for existing users (variant 9) (variant 1)", "solution": "# In hermes_cli/config.py\n\nDEFAULT_CONFIG = {{\n \"_config_version\": 6, # bumped from 5\n \"model\": \"anthropic/claude-sonnet-4\",\n \"max_iterations\": 50,\n \"new_feature\": True, # added\n}}\n\ndef migrate_config(raw: dict) -> dict:\n version = raw.get(\"_config_version\", 0)\n if version < 6:\n raw[\"new_feature\"] = DEFAULT_CONFIG[\"new_feature\"]\n raw[\"_config_version\"] = 6\n return raw"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 69) (variant 6) (variant 78) (variant 63) (variant 62)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 61) (variant 98) (variant 61) (variant 29) (variant 57)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "tool_routing", "problem": "Check if a tool is available before calling it (variant 32)", "solution": "from tools.registry import registry\n\ntool_name = \"web_search\"\nif registry.is_available(tool_name):\n schema = registry.get_schema(tool_name)\n result = registry.call(tool_name, {{\"query\": \"Python asyncio\"}}, task_id=\"abc\")\nelse:\n result = f\"Tool {{tool_name}} is not available (missing requirements)\""}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 42) (variant 9)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 90 iterations (variant 88) (variant 6) (variant 16)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "prompt_building", "problem": "Format a tool result message for OpenAI-compatible chat API (variant 3) (variant 88) (variant 45) (variant 17) (variant 99) (variant 4)", "solution": "def tool_result_message(result: str, tool_call_id: str = \"\") -> dict:\n return {{\n \"role\": \"tool\",\n \"tool_call_id\": tool_call_id,\n \"content\": result if isinstance(result, str) else json.dumps(result),\n }}\n\nmessages.append(tool_result_message(\"42 files found\", tool_call_id=\"call_abc\"))"}
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{"issue": 592, "domain": "testing", "problem": "Test agent loop behavior with mocked API responses (variant 87) (variant 37)", "solution": "import pytest\nfrom run_agent import AIAgent\n\ndef test_agent_runs_tool_call(monkeypatch):\n agent = AIAgent(model=\"test\", max_iterations=5)\n\n class MockResponse:\n tool_calls = [MockToolCall(\"read_file\", {{\"path\": \"/tmp/test.txt\"}})]\n content = None\n\n monkeypatch.setattr(agent, \"_call_api\", lambda **kw: MockResponse())\n result = agent.chat(\"Read the file\")\n assert result is not None"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "testing", "problem": "Test agent loop behavior with mocked API responses (variant 96) (variant 23) (variant 91) (variant 69)", "solution": "import pytest\nfrom run_agent import AIAgent\n\ndef test_agent_runs_tool_call(monkeypatch):\n agent = AIAgent(model=\"test\", max_iterations=5)\n\n class MockResponse:\n tool_calls = [MockToolCall(\"read_file\", {{\"path\": \"/tmp/test.txt\"}})]\n content = None\n\n monkeypatch.setattr(agent, \"_call_api\", lambda **kw: MockResponse())\n result = agent.chat(\"Read the file\")\n assert result is not None"}
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{"issue": 592, "domain": "error_handling", "problem": "Validate JSON output from model before parsing (variant 31)", "solution": "import json\n\ntry:\n data = json.loads(model_output)\nexcept json.JSONDecodeError:\n # Try to extract JSON from markdown code block\n import re\n match = re.search(r'```json\\n(.*?)\\n```', model_output, re.DOTALL)\n if match:\n data = json.loads(match.group(1))\n else:\n raise ValueError(\"Model did not return valid JSON\")"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 49) (variant 45) (variant 16) (variant 69)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 9) (variant 82)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 8) (variant 74)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 16) (variant 22) (variant 4)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "error_handling", "problem": "Validate JSON output from model before parsing (variant 55)", "solution": "import json\n\ntry:\n data = json.loads(model_output)\nexcept json.JSONDecodeError:\n # Try to extract JSON from markdown code block\n import re\n match = re.search(r'```json\\n(.*?)\\n```', model_output, re.DOTALL)\n if match:\n data = json.loads(match.group(1))\n else:\n raise ValueError(\"Model did not return valid JSON\")"}
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{"issue": 592, "domain": "utility", "problem": "Poll a background process for completion with progress tracking (variant 55) (variant 65) (variant 48) (variant 23) (variant 74)", "solution": "from tools.process_registry import ProcessRegistry\n\nregistry = ProcessRegistry()\nsession_id = registry.start(\"long_task.sh\", background=True)\n\nwhile True:\n status = registry.poll(session_id)\n if status[\"done\"]:\n print(f\"Completed with exit code {{status['exit_code']}}\")\n break\n print(f\"Progress: {{status['lines']}} lines output\")\n time.sleep(1)"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 6) (variant 30) (variant 37)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 60) (variant 97) (variant 41) (variant 67) (variant 86)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 56) (variant 37) (variant 8)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "session_management", "problem": "List recent sessions from the session database with pagination (variant 54) (variant 48) (variant 33)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nsessions = db.list_sessions(limit=20, offset=0)\nfor sess in sessions:\n print(f\"{{sess['id']}} | {{sess['created_at']}} | {{sess['message_count']}} msgs\")"}
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{"issue": 592, "domain": "prompt_building", "problem": "Format a tool result message for OpenAI-compatible chat API (variant 3) (variant 48) (variant 4)", "solution": "def tool_result_message(result: str, tool_call_id: str = \"\") -> dict:\n return {{\n \"role\": \"tool\",\n \"tool_call_id\": tool_call_id,\n \"content\": result if isinstance(result, str) else json.dumps(result),\n }}\n\nmessages.append(tool_result_message(\"42 files found\", tool_call_id=\"call_abc\"))"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 72) (variant 57) (variant 11) (variant 12)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 42)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 56) (variant 37) (variant 30)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 64)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 50) (variant 27) (variant 51)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 92)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=50)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "error_handling", "problem": "Validate JSON output from model before parsing (variant 55) (variant 43) (variant 79) (variant 31) (variant 86)", "solution": "import json\n\ntry:\n data = json.loads(model_output)\nexcept json.JSONDecodeError:\n # Try to extract JSON from markdown code block\n import re\n match = re.search(r'```json\\n(.*?)\\n```', model_output, re.DOTALL)\n if match:\n data = json.loads(match.group(1))\n else:\n raise ValueError(\"Model did not return valid JSON\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 90 iterations (variant 30) (variant 44) (variant 5)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "prompt_building", "problem": "Build a few-shot prompt with examples for consistent JSON output (variant 91)", "solution": "system_prompt = \"\"\"You are a structured data extractor.\n\nReturn valid JSON only. No markdown, no explanation.\n\nExamples:\nInput: \"Alice is 30 years old\"\nOutput: {{\"name\": \"Alice\", \"age\": 30}}\n\nInput: \"Bob works as an engineer in Seattle\"\nOutput: {{\"name\": \"Bob\", \"job\": \"engineer\", \"location\": \"Seattle\"}}\n\nNow extract from the user input.\"\"\"\n\nmessages = [\n {{\"role\": \"system\", \"content\": system_prompt}},\n {{\"role\": \"user\", \"content\": \"Carol is a doctor in Boston, age 45\"}},\n]"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 39) (variant 51)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 19) (variant 78)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "utility", "problem": "Load user config from ~/.hermes/config.yaml with defaults fallback (variant 20) (variant 29) (variant 49) (variant 8)", "solution": "from hermes_cli.config import load_cli_config, DEFAULT_CONFIG\n\nconfig = load_cli_config()\nmodel = config.get(\"model\", DEFAULT_CONFIG[\"model\"])\nmax_iters = config.get(\"max_iterations\", DEFAULT_CONFIG[\"max_iterations\"])"}
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{"issue": 592, "domain": "tool_routing", "problem": "Check if a tool is available before calling it (variant 32) (variant 56) (variant 65)", "solution": "from tools.registry import registry\n\ntool_name = \"web_search\"\nif registry.is_available(tool_name):\n schema = registry.get_schema(tool_name)\n result = registry.call(tool_name, {{\"query\": \"Python asyncio\"}}, task_id=\"abc\")\nelse:\n result = f\"Tool {{tool_name}} is not available (missing requirements)\""}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 100)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 7)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"anthropic/claude-sonnet-4\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 11) (variant 15) (variant 92) (variant 47) (variant 66)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 29) (variant 99)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "utility", "problem": "Poll a background process for completion with progress tracking (variant 55) (variant 65) (variant 48) (variant 90)", "solution": "from tools.process_registry import ProcessRegistry\n\nregistry = ProcessRegistry()\nsession_id = registry.start(\"long_task.sh\", background=True)\n\nwhile True:\n status = registry.poll(session_id)\n if status[\"done\"]:\n print(f\"Completed with exit code {{status['exit_code']}}\")\n break\n print(f\"Progress: {{status['lines']}} lines output\")\n time.sleep(1)"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "prompt_building", "problem": "Format a tool result message for OpenAI-compatible chat API (variant 3) (variant 88) (variant 45) (variant 17) (variant 99) (variant 14)", "solution": "def tool_result_message(result: str, tool_call_id: str = \"\") -> dict:\n return {{\n \"role\": \"tool\",\n \"tool_call_id\": tool_call_id,\n \"content\": result if isinstance(result, str) else json.dumps(result),\n }}\n\nmessages.append(tool_result_message(\"42 files found\", tool_call_id=\"call_abc\"))"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 90 iterations (variant 77)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Run a subagent delegation with timeout and context isolation (variant 10) (variant 33)", "solution": "from tools.delegate_tool import delegate_task\n\nresult = delegate_task(\n goal=\"Debug this failing test\",\n context=\"test_file.py line 42 raises AssertionError\",\n max_iterations=20,\n toolsets=[\"terminal\", \"file\"],\n)\nprint(result[\"summary\"])"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 50) (variant 93)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Load user config from ~/.hermes/config.yaml with defaults fallback (variant 20) (variant 29) (variant 22)", "solution": "from hermes_cli.config import load_cli_config, DEFAULT_CONFIG\n\nconfig = load_cli_config()\nmodel = config.get(\"model\", DEFAULT_CONFIG[\"model\"])\nmax_iters = config.get(\"max_iterations\", DEFAULT_CONFIG[\"max_iterations\"])"}
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{"issue": 592, "domain": "config", "problem": "Bump config schema version and add migration for existing users (variant 23)", "solution": "# In hermes_cli/config.py\n\nDEFAULT_CONFIG = {{\n \"_config_version\": 6, # bumped from 5\n \"model\": \"anthropic/claude-sonnet-4\",\n \"max_iterations\": 50,\n \"new_feature\": True, # added\n}}\n\ndef migrate_config(raw: dict) -> dict:\n version = raw.get(\"_config_version\", 0)\n if version < 6:\n raw[\"new_feature\"] = DEFAULT_CONFIG[\"new_feature\"]\n raw[\"_config_version\"] = 6\n return raw"}
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{"issue": 592, "domain": "error_handling", "problem": "Handle missing optional dependencies with graceful degradation (variant 12)", "solution": "try:\n import chromadb\n HAS_CHROMADB = True\nexcept ImportError:\n HAS_CHROMADB = False\n\ndef search_vectors(query: str):\n if not HAS_CHROMADB:\n return {{\"warning\": \"ChromaDB not installed\", \"results\": []}}\n # ... actual implementation"}
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{"issue": 592, "domain": "prompt_building", "problem": "Format a tool result message for OpenAI-compatible chat API (variant 3) (variant 88) (variant 45) (variant 17)", "solution": "def tool_result_message(result: str, tool_call_id: str = \"\") -> dict:\n return {{\n \"role\": \"tool\",\n \"tool_call_id\": tool_call_id,\n \"content\": result if isinstance(result, str) else json.dumps(result),\n }}\n\nmessages.append(tool_result_message(\"42 files found\", tool_call_id=\"call_abc\"))"}
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{"issue": 592, "domain": "prompt_building", "problem": "Format a tool result message for OpenAI-compatible chat API (variant 3) (variant 88) (variant 45) (variant 17) (variant 99) (variant 14) (variant 20)", "solution": "def tool_result_message(result: str, tool_call_id: str = \"\") -> dict:\n return {{\n \"role\": \"tool\",\n \"tool_call_id\": tool_call_id,\n \"content\": result if isinstance(result, str) else json.dumps(result),\n }}\n\nmessages.append(tool_result_message(\"42 files found\", tool_call_id=\"call_abc\"))"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 17) (variant 99) (variant 22) (variant 56)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 37) (variant 74) (variant 68)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 26) (variant 32)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 43) (variant 44) (variant 41) (variant 21) (variant 12)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "config", "problem": "Bump config schema version and add migration for existing users", "solution": "# In hermes_cli/config.py\n\nDEFAULT_CONFIG = {{\n \"_config_version\": 6, # bumped from 5\n \"model\": \"anthropic/claude-sonnet-4\",\n \"max_iterations\": 50,\n \"new_feature\": True, # added\n}}\n\ndef migrate_config(raw: dict) -> dict:\n version = raw.get(\"_config_version\", 0)\n if version < 6:\n raw[\"new_feature\"] = DEFAULT_CONFIG[\"new_feature\"]\n raw[\"_config_version\"] = 6\n return raw"}
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{"issue": 592, "domain": "tool_routing", "problem": "Wrap a tool handler to add logging and error handling (variant 39) (variant 60) (variant 96) (variant 58)", "solution": "import json\nimport logging\nfrom tools.registry import registry\n\nlogger = logging.getLogger(__name__)\n\ndef logged_handler(fn):\n def wrapper(args, **kwargs):\n task_id = kwargs.get(\"task_id\")\n logger.info(f\"[{{task_id}}] Calling {{fn.__name__}} with {{args}}\")\n try:\n result = fn(args, **kwargs)\n logger.info(f\"[{{task_id}}] Success\")\n return result\n except Exception as e:\n logger.error(f\"[{{task_id}}] Error: {{e}}\")\n return json.dumps({{\"error\": str(e)}})\n return wrapper\n\n# Register with wrapper\nregistry.register(\n name=\"my_tool\",\n toolset=\"custom\",\n schema={{...}},\n handler=lambda args, **kw: logged_handler(my_tool_impl)(args, **kw),\n)"}
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{"issue": 592, "domain": "error_handling", "problem": "Validate JSON output from model before parsing", "solution": "import json\n\ntry:\n data = json.loads(model_output)\nexcept json.JSONDecodeError:\n # Try to extract JSON from markdown code block\n import re\n match = re.search(r'```json\\n(.*?)\\n```', model_output, re.DOTALL)\n if match:\n data = json.loads(match.group(1))\n else:\n raise ValueError(\"Model did not return valid JSON\")"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 14) (variant 23)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 18) (variant 52) (variant 55)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 15) (variant 85)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 60) (variant 32) (variant 72)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29) (variant 74) (variant 91) (variant 54)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 5) (variant 81)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 25) (variant 93)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "testing", "problem": "Test agent loop behavior with mocked API responses (variant 96) (variant 23) (variant 71)", "solution": "import pytest\nfrom run_agent import AIAgent\n\ndef test_agent_runs_tool_call(monkeypatch):\n agent = AIAgent(model=\"test\", max_iterations=5)\n\n class MockResponse:\n tool_calls = [MockToolCall(\"read_file\", {{\"path\": \"/tmp/test.txt\"}})]\n content = None\n\n monkeypatch.setattr(agent, \"_call_api\", lambda **kw: MockResponse())\n result = agent.chat(\"Read the file\")\n assert result is not None"}
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{"issue": 592, "domain": "tool_routing", "problem": "Check if a tool is available before calling it (variant 32) (variant 86) (variant 75) (variant 76)", "solution": "from tools.registry import registry\n\ntool_name = \"web_search\"\nif registry.is_available(tool_name):\n schema = registry.get_schema(tool_name)\n result = registry.call(tool_name, {{\"query\": \"Python asyncio\"}}, task_id=\"abc\")\nelse:\n result = f\"Tool {{tool_name}} is not available (missing requirements)\""}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 29) (variant 58) (variant 84)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 29) (variant 58)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 90 iterations (variant 85) (variant 95) (variant 33) (variant 41)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 8) (variant 74) (variant 94) (variant 74)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 24) (variant 38) (variant 43)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 46) (variant 51) (variant 62) (variant 68)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 8) (variant 75) (variant 89) (variant 58)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "utility", "problem": "Load user config from ~/.hermes/config.yaml with defaults fallback (variant 20) (variant 52) (variant 14)", "solution": "from hermes_cli.config import load_cli_config, DEFAULT_CONFIG\n\nconfig = load_cli_config()\nmodel = config.get(\"model\", DEFAULT_CONFIG[\"model\"])\nmax_iters = config.get(\"max_iterations\", DEFAULT_CONFIG[\"max_iterations\"])"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 79)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 37) (variant 74) (variant 26) (variant 34)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "tool_routing", "problem": "Wrap a tool handler to add logging and error handling (variant 39)", "solution": "import json\nimport logging\nfrom tools.registry import registry\n\nlogger = logging.getLogger(__name__)\n\ndef logged_handler(fn):\n def wrapper(args, **kwargs):\n task_id = kwargs.get(\"task_id\")\n logger.info(f\"[{{task_id}}] Calling {{fn.__name__}} with {{args}}\")\n try:\n result = fn(args, **kwargs)\n logger.info(f\"[{{task_id}}] Success\")\n return result\n except Exception as e:\n logger.error(f\"[{{task_id}}] Error: {{e}}\")\n return json.dumps({{\"error\": str(e)}})\n return wrapper\n\n# Register with wrapper\nregistry.register(\n name=\"my_tool\",\n toolset=\"custom\",\n schema={{...}},\n handler=lambda args, **kw: logged_handler(my_tool_impl)(args, **kw),\n)"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 71)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 8) (variant 74) (variant 13) (variant 13)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 87)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"anthropic/claude-sonnet-4\", max_iterations=50)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "utility", "problem": "Load user config from ~/.hermes/config.yaml with defaults fallback (variant 20) (variant 52)", "solution": "from hermes_cli.config import load_cli_config, DEFAULT_CONFIG\n\nconfig = load_cli_config()\nmodel = config.get(\"model\", DEFAULT_CONFIG[\"model\"])\nmax_iters = config.get(\"max_iterations\", DEFAULT_CONFIG[\"max_iterations\"])"}
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{"issue": 592, "domain": "tool_routing", "problem": "Wrap a tool handler to add logging and error handling (variant 76)", "solution": "import json\nimport logging\nfrom tools.registry import registry\n\nlogger = logging.getLogger(__name__)\n\ndef logged_handler(fn):\n def wrapper(args, **kwargs):\n task_id = kwargs.get(\"task_id\")\n logger.info(f\"[{{task_id}}] Calling {{fn.__name__}} with {{args}}\")\n try:\n result = fn(args, **kwargs)\n logger.info(f\"[{{task_id}}] Success\")\n return result\n except Exception as e:\n logger.error(f\"[{{task_id}}] Error: {{e}}\")\n return json.dumps({{\"error\": str(e)}})\n return wrapper\n\n# Register with wrapper\nregistry.register(\n name=\"my_tool\",\n toolset=\"custom\",\n schema={{...}},\n handler=lambda args, **kw: logged_handler(my_tool_impl)(args, **kw),\n)"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 18) (variant 63)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 11) (variant 17) (variant 16) (variant 58)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 9) (variant 19) (variant 63)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 6) (variant 30)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 5)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "testing", "problem": "Test agent loop behavior with mocked API responses (variant 77) (variant 28) (variant 12)", "solution": "import pytest\nfrom run_agent import AIAgent\n\ndef test_agent_runs_tool_call(monkeypatch):\n agent = AIAgent(model=\"test\", max_iterations=5)\n\n class MockResponse:\n tool_calls = [MockToolCall(\"read_file\", {{\"path\": \"/tmp/test.txt\"}})]\n content = None\n\n monkeypatch.setattr(agent, \"_call_api\", lambda **kw: MockResponse())\n result = agent.chat(\"Read the file\")\n assert result is not None"}
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{"issue": 592, "domain": "tool_routing", "problem": "Add a new toolset to HERMES_CORE_TOOLS in toolsets.py", "solution": "# In toolsets.py\n\n_HERMES_CORE_TOOLS = [\n \"web\",\n \"terminal\",\n \"file\",\n \"browser\",\n \"code_execution\",\n \"delegate\",\n \"new_toolset\", # <-- added\n]\n\n# Create tools/new_toolset_tool.py with registry.register() at module level\n# Auto-discovery will pick it up automatically — no manual import needed"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 5) (variant 42) (variant 87)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 60)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 40) (variant 61) (variant 40)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"anthropic/claude-sonnet-4\", max_iterations=50)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 17) (variant 99) (variant 22) (variant 56) (variant 55) (variant 80)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 61) (variant 98) (variant 61) (variant 73) (variant 76)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Handle a tool call result and append it to the conversation messages (variant 86)", "solution": "from model_tools import handle_function_call\n\ntool_call = response.tool_calls[0]\nresult = handle_function_call(\n tool_call.name,\n tool_call.args,\n task_id=\"task-123\"\n)\nmessages.append({{\n \"role\": \"tool\",\n \"tool_call_id\": tool_call.id,\n \"content\": result,\n}})"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 50) (variant 66) (variant 53) (variant 73) (variant 3) (variant 6)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 28) (variant 10)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 43) (variant 44) (variant 32)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 33) (variant 85)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "testing", "problem": "Test agent loop behavior with mocked API responses (variant 77) (variant 28)", "solution": "import pytest\nfrom run_agent import AIAgent\n\ndef test_agent_runs_tool_call(monkeypatch):\n agent = AIAgent(model=\"test\", max_iterations=5)\n\n class MockResponse:\n tool_calls = [MockToolCall(\"read_file\", {{\"path\": \"/tmp/test.txt\"}})]\n content = None\n\n monkeypatch.setattr(agent, \"_call_api\", lambda **kw: MockResponse())\n result = agent.chat(\"Read the file\")\n assert result is not None"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 8)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 61) (variant 98) (variant 61) (variant 29)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 93) (variant 7)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"anthropic/claude-sonnet-4\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 14) (variant 99)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 60) (variant 50)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 50) (variant 27) (variant 51) (variant 27)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "prompt_building", "problem": "Format a tool result message for OpenAI-compatible chat API", "solution": "def tool_result_message(result: str, tool_call_id: str = \"\") -> dict:\n return {{\n \"role\": \"tool\",\n \"tool_call_id\": tool_call_id,\n \"content\": result if isinstance(result, str) else json.dumps(result),\n }}\n\nmessages.append(tool_result_message(\"42 files found\", tool_call_id=\"call_abc\"))"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 49) (variant 58) (variant 19)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "utility", "problem": "Resolve provider credentials from ~/.hermes/.env (variant 15) (variant 52)", "solution": "from hermes_cli.auth import resolve_credentials\n\ncreds = resolve_credentials(\"anthropic\")\nprint(creds[\"api_key\"][:8] + \"...\") # masked"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 61) (variant 98) (variant 61) (variant 3)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 60) (variant 97) (variant 41) (variant 65) (variant 88)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "prompt_building", "problem": "Build a few-shot prompt with examples for consistent JSON output (variant 30) (variant 34)", "solution": "system_prompt = \"\"\"You are a structured data extractor.\n\nReturn valid JSON only. No markdown, no explanation.\n\nExamples:\nInput: \"Alice is 30 years old\"\nOutput: {{\"name\": \"Alice\", \"age\": 30}}\n\nInput: \"Bob works as an engineer in Seattle\"\nOutput: {{\"name\": \"Bob\", \"job\": \"engineer\", \"location\": \"Seattle\"}}\n\nNow extract from the user input.\"\"\"\n\nmessages = [\n {{\"role\": \"system\", \"content\": system_prompt}},\n {{\"role\": \"user\", \"content\": \"Carol is a doctor in Boston, age 45\"}},\n]"}
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{"issue": 592, "domain": "tool_routing", "problem": "Check if a tool is available before calling it (variant 32) (variant 86)", "solution": "from tools.registry import registry\n\ntool_name = \"web_search\"\nif registry.is_available(tool_name):\n schema = registry.get_schema(tool_name)\n result = registry.call(tool_name, {{\"query\": \"Python asyncio\"}}, task_id=\"abc\")\nelse:\n result = f\"Tool {{tool_name}} is not available (missing requirements)\""}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 61) (variant 98)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 19) (variant 89) (variant 92)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "utility", "problem": "Resolve provider credentials from ~/.hermes/.env (variant 15) (variant 38) (variant 5) (variant 38)", "solution": "from hermes_cli.auth import resolve_credentials\n\ncreds = resolve_credentials(\"anthropic\")\nprint(creds[\"api_key\"][:8] + \"...\") # masked"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 11) (variant 15) (variant 92) (variant 47)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 33)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "tool_routing", "problem": "Wrap a tool handler to add logging and error handling (variant 39) (variant 69)", "solution": "import json\nimport logging\nfrom tools.registry import registry\n\nlogger = logging.getLogger(__name__)\n\ndef logged_handler(fn):\n def wrapper(args, **kwargs):\n task_id = kwargs.get(\"task_id\")\n logger.info(f\"[{{task_id}}] Calling {{fn.__name__}} with {{args}}\")\n try:\n result = fn(args, **kwargs)\n logger.info(f\"[{{task_id}}] Success\")\n return result\n except Exception as e:\n logger.error(f\"[{{task_id}}] Error: {{e}}\")\n return json.dumps({{\"error\": str(e)}})\n return wrapper\n\n# Register with wrapper\nregistry.register(\n name=\"my_tool\",\n toolset=\"custom\",\n schema={{...}},\n handler=lambda args, **kw: logged_handler(my_tool_impl)(args, **kw),\n)"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 8) (variant 74) (variant 13) (variant 79)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29) (variant 74) (variant 91)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 11) (variant 46)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 50) (variant 66) (variant 53) (variant 73) (variant 48)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "error_handling", "problem": "Detect and recover from infinite tool call loops (variant 9) (variant 70)", "solution": "# In run_conversation loop\nseen_calls = set()\nfor tool_call in response.tool_calls:\n call_key = (tool_call.name, json.dumps(tool_call.args, sort_keys=True))\n if call_key in seen_calls:\n messages.append({{\n \"role\": \"tool\",\n \"content\": \"Error: Repeated identical tool call detected. Try a different approach.\",\n }})\n continue\n seen_calls.add(call_key)\n result = handle_function_call(tool_call.name, tool_call.args)\n messages.append(tool_result_message(result))"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29) (variant 73) (variant 40) (variant 21)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 75)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 70) (variant 84) (variant 1) (variant 94)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 70) (variant 84)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 29) (variant 72)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 5) (variant 27) (variant 100) (variant 32)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 5) (variant 27)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 61) (variant 98) (variant 81) (variant 35)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 11) (variant 17)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "error_handling", "problem": "Catch and log tool execution errors without crashing the agent loop (variant 68) (variant 96) (variant 39) (variant 97)", "solution": "import json\nimport traceback\n\ntry:\n result = handle_function_call(tool_call.name, tool_call.args)\nexcept Exception as e:\n tb = traceback.format_exc()\n result = json.dumps({{\n \"error\": str(e),\n \"traceback\": tb,\n }})"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 5) (variant 42) (variant 80)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 17) (variant 99) (variant 22) (variant 56) (variant 55)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 90 iterations (variant 30)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "tool_routing", "problem": "Wrap a tool handler to add logging and error handling (variant 39) (variant 59) (variant 14)", "solution": "import json\nimport logging\nfrom tools.registry import registry\n\nlogger = logging.getLogger(__name__)\n\ndef logged_handler(fn):\n def wrapper(args, **kwargs):\n task_id = kwargs.get(\"task_id\")\n logger.info(f\"[{{task_id}}] Calling {{fn.__name__}} with {{args}}\")\n try:\n result = fn(args, **kwargs)\n logger.info(f\"[{{task_id}}] Success\")\n return result\n except Exception as e:\n logger.error(f\"[{{task_id}}] Error: {{e}}\")\n return json.dumps({{\"error\": str(e)}})\n return wrapper\n\n# Register with wrapper\nregistry.register(\n name=\"my_tool\",\n toolset=\"custom\",\n schema={{...}},\n handler=lambda args, **kw: logged_handler(my_tool_impl)(args, **kw),\n)"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 72) (variant 57) (variant 11) (variant 78)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 90 iterations (variant 85) (variant 95)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Switch model mid-session with /model slash command (variant 3)", "solution": "# In cli.py or gateway/run.py\nfrom hermes_cli.model_switch import switch_model\n\nnew_model = switch_model(\"openai/gpt-4o\")\nprint(f\"Switched to {{new_model}}\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 50)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 18)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29) (variant 21) (variant 42)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 18) (variant 30) (variant 53)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 61) (variant 32)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29) (variant 21) (variant 42) (variant 86) (variant 78)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 50 iterations (variant 48) (variant 100)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 26)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 61) (variant 98) (variant 61) (variant 29) (variant 77) (variant 71) (variant 78)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 98)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "tool_routing", "problem": "Discover all builtin tools and build tool schemas for the API call", "solution": "from model_tools import discover_builtin_tools\nfrom tools.registry import registry\n\n# Auto-discover all registered tools\ndiscover_builtin_tools()\n\n# Collect schemas for all available tools\ntool_schemas = [registry.get_schema(name) for name in registry.list_available()]\n\n# Filter by enabled toolsets\nenabled = [\"web\", \"terminal\", \"file\"]\ntool_schemas = [\n s for s in tool_schemas\n if registry.get_toolset(s[\"name\"]) in enabled\n]"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 43) (variant 70) (variant 55) (variant 79) (variant 2)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 49) (variant 19) (variant 69)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "utility", "problem": "Poll a background process for completion with progress tracking (variant 92)", "solution": "from tools.process_registry import ProcessRegistry\n\nregistry = ProcessRegistry()\nsession_id = registry.start(\"long_task.sh\", background=True)\n\nwhile True:\n status = registry.poll(session_id)\n if status[\"done\"]:\n print(f\"Completed with exit code {{status['exit_code']}}\")\n break\n print(f\"Progress: {{status['lines']}} lines output\")\n time.sleep(1)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 51)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=50)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "prompt_building", "problem": "Format a tool result message for OpenAI-compatible chat API (variant 3) (variant 88) (variant 45) (variant 17) (variant 99)", "solution": "def tool_result_message(result: str, tool_call_id: str = \"\") -> dict:\n return {{\n \"role\": \"tool\",\n \"tool_call_id\": tool_call_id,\n \"content\": result if isinstance(result, str) else json.dumps(result),\n }}\n\nmessages.append(tool_result_message(\"42 files found\", tool_call_id=\"call_abc\"))"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 2) (variant 92)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "utility", "problem": "Resolve provider credentials from ~/.hermes/.env (variant 15) (variant 38) (variant 90) (variant 67)", "solution": "from hermes_cli.auth import resolve_credentials\n\ncreds = resolve_credentials(\"anthropic\")\nprint(creds[\"api_key\"][:8] + \"...\") # masked"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 36) (variant 8)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 29) (variant 32) (variant 44) (variant 70)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 11) (variant 15) (variant 92)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "config", "problem": "Bump config schema version and add migration for existing users (variant 9) (variant 18)", "solution": "# In hermes_cli/config.py\n\nDEFAULT_CONFIG = {{\n \"_config_version\": 6, # bumped from 5\n \"model\": \"anthropic/claude-sonnet-4\",\n \"max_iterations\": 50,\n \"new_feature\": True, # added\n}}\n\ndef migrate_config(raw: dict) -> dict:\n version = raw.get(\"_config_version\", 0)\n if version < 6:\n raw[\"new_feature\"] = DEFAULT_CONFIG[\"new_feature\"]\n raw[\"_config_version\"] = 6\n return raw"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 43) (variant 16)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 30 iterations (variant 42) (variant 47) (variant 63) (variant 35)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 82)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=50)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 90 iterations (variant 94) (variant 80)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Run a subagent delegation with timeout and context isolation", "solution": "from tools.delegate_tool import delegate_task\n\nresult = delegate_task(\n goal=\"Debug this failing test\",\n context=\"test_file.py line 42 raises AssertionError\",\n max_iterations=20,\n toolsets=[\"terminal\", \"file\"],\n)\nprint(result[\"summary\"])"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 8) (variant 75) (variant 55)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 24) (variant 90) (variant 3)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "tool_routing", "problem": "Discover all builtin tools and build tool schemas for the API call (variant 52) (variant 14) (variant 59) (variant 17)", "solution": "from model_tools import discover_builtin_tools\nfrom tools.registry import registry\n\n# Auto-discover all registered tools\ndiscover_builtin_tools()\n\n# Collect schemas for all available tools\ntool_schemas = [registry.get_schema(name) for name in registry.list_available()]\n\n# Filter by enabled toolsets\nenabled = [\"web\", \"terminal\", \"file\"]\ntool_schemas = [\n s for s in tool_schemas\n if registry.get_toolset(s[\"name\"]) in enabled\n]"}
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{"issue": 592, "domain": "error_handling", "problem": "Catch and log tool execution errors without crashing the agent loop (variant 39) (variant 71) (variant 87)", "solution": "import json\nimport traceback\n\ntry:\n result = handle_function_call(tool_call.name, tool_call.args)\nexcept Exception as e:\n tb = traceback.format_exc()\n result = json.dumps({{\n \"error\": str(e),\n \"traceback\": tb,\n }})"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 90 iterations (variant 94) (variant 67)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 21)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "testing", "problem": "Test agent loop behavior with mocked API responses", "solution": "import pytest\nfrom run_agent import AIAgent\n\ndef test_agent_runs_tool_call(monkeypatch):\n agent = AIAgent(model=\"test\", max_iterations=5)\n\n class MockResponse:\n tool_calls = [MockToolCall(\"read_file\", {{\"path\": \"/tmp/test.txt\"}})]\n content = None\n\n monkeypatch.setattr(agent, \"_call_api\", lambda **kw: MockResponse())\n result = agent.chat(\"Read the file\")\n assert result is not None"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 19) (variant 89) (variant 40)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "prompt_building", "problem": "Build a system prompt with skills injected as slash commands", "solution": "from agent.prompt_builder import PromptBuilder\nfrom agent.skill_commands import scan_skills\n\nbuilder = PromptBuilder()\nskills = scan_skills(\"~/.hermes/skills/\")\n\nsystem_prompt = builder.build(\n base_prompt=\"You are a helpful coding assistant.\",\n skills=skills,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n user_preferences={{\"language\": \"Python\", \"style\": \"concise\"}},\n)\nprint(system_prompt)"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 65)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 53) (variant 56) (variant 83)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 7) (variant 79)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"anthropic/claude-sonnet-4\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 5) (variant 42) (variant 80) (variant 83)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 98) (variant 87)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 11) (variant 15)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 29) (variant 72) (variant 22)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 28) (variant 10) (variant 73)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "error_handling", "problem": "Catch and log tool execution errors without crashing the agent loop (variant 39) (variant 71) (variant 6) (variant 42)", "solution": "import json\nimport traceback\n\ntry:\n result = handle_function_call(tool_call.name, tool_call.args)\nexcept Exception as e:\n tb = traceback.format_exc()\n result = json.dumps({{\n \"error\": str(e),\n \"traceback\": tb,\n }})"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 50 iterations (variant 28) (variant 77)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 56) (variant 37)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 65) (variant 63) (variant 2)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 90 iterations", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "List recent sessions from the session database with pagination (variant 54) (variant 48) (variant 33) (variant 7)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nsessions = db.list_sessions(limit=20, offset=0)\nfor sess in sessions:\n print(f\"{{sess['id']}} | {{sess['created_at']}} | {{sess['message_count']}} msgs\")"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 89) (variant 1)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 2)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "error_handling", "problem": "Handle missing optional dependencies with graceful degradation (variant 12) (variant 17) (variant 71) (variant 35) (variant 95)", "solution": "try:\n import chromadb\n HAS_CHROMADB = True\nexcept ImportError:\n HAS_CHROMADB = False\n\ndef search_vectors(query: str):\n if not HAS_CHROMADB:\n return {{\"warning\": \"ChromaDB not installed\", \"results\": []}}\n # ... actual implementation"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 14) (variant 83) (variant 25)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 33) (variant 8) (variant 20) (variant 93)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 69) (variant 54)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 65) (variant 63) (variant 2) (variant 23)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Handle a tool call result and append it to the conversation messages (variant 86) (variant 37)", "solution": "from model_tools import handle_function_call\n\ntool_call = response.tool_calls[0]\nresult = handle_function_call(\n tool_call.name,\n tool_call.args,\n task_id=\"task-123\"\n)\nmessages.append({{\n \"role\": \"tool\",\n \"tool_call_id\": tool_call.id,\n \"content\": result,\n}})"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 50) (variant 66) (variant 53) (variant 73) (variant 11) (variant 60)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Switch model mid-session with /model slash command (variant 20)", "solution": "# In cli.py or gateway/run.py\nfrom hermes_cli.model_switch import switch_model\n\nnew_model = switch_model(\"openai/gpt-4o\")\nprint(f\"Switched to {{new_model}}\")"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 19) (variant 89) (variant 92) (variant 90) (variant 25)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 50 iterations (variant 28)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 14) (variant 83)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "utility", "problem": "Read a file safely with size limits and binary detection (variant 50)", "solution": "from tools.file_tools import read_file\n\ncontent = read_file(\n path=\"/tmp/large.log\",\n offset=1,\n limit=500,\n)\nprint(content)"}
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{"issue": 592, "domain": "tool_routing", "problem": "Wrap a tool handler to add logging and error handling (variant 39) (variant 93)", "solution": "import json\nimport logging\nfrom tools.registry import registry\n\nlogger = logging.getLogger(__name__)\n\ndef logged_handler(fn):\n def wrapper(args, **kwargs):\n task_id = kwargs.get(\"task_id\")\n logger.info(f\"[{{task_id}}] Calling {{fn.__name__}} with {{args}}\")\n try:\n result = fn(args, **kwargs)\n logger.info(f\"[{{task_id}}] Success\")\n return result\n except Exception as e:\n logger.error(f\"[{{task_id}}] Error: {{e}}\")\n return json.dumps({{\"error\": str(e)}})\n return wrapper\n\n# Register with wrapper\nregistry.register(\n name=\"my_tool\",\n toolset=\"custom\",\n schema={{...}},\n handler=lambda args, **kw: logged_handler(my_tool_impl)(args, **kw),\n)"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 53) (variant 56)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29) (variant 73) (variant 40)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "tool_routing", "problem": "Discover all builtin tools and build tool schemas for the API call (variant 52) (variant 14) (variant 19) (variant 37)", "solution": "from model_tools import discover_builtin_tools\nfrom tools.registry import registry\n\n# Auto-discover all registered tools\ndiscover_builtin_tools()\n\n# Collect schemas for all available tools\ntool_schemas = [registry.get_schema(name) for name in registry.list_available()]\n\n# Filter by enabled toolsets\nenabled = [\"web\", \"terminal\", \"file\"]\ntool_schemas = [\n s for s in tool_schemas\n if registry.get_toolset(s[\"name\"]) in enabled\n]"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 56) (variant 49)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 16) (variant 4) (variant 31)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "tool_routing", "problem": "Wrap a tool handler to add logging and error handling", "solution": "import json\nimport logging\nfrom tools.registry import registry\n\nlogger = logging.getLogger(__name__)\n\ndef logged_handler(fn):\n def wrapper(args, **kwargs):\n task_id = kwargs.get(\"task_id\")\n logger.info(f\"[{{task_id}}] Calling {{fn.__name__}} with {{args}}\")\n try:\n result = fn(args, **kwargs)\n logger.info(f\"[{{task_id}}] Success\")\n return result\n except Exception as e:\n logger.error(f\"[{{task_id}}] Error: {{e}}\")\n return json.dumps({{\"error\": str(e)}})\n return wrapper\n\n# Register with wrapper\nregistry.register(\n name=\"my_tool\",\n toolset=\"custom\",\n schema={{...}},\n handler=lambda args, **kw: logged_handler(my_tool_impl)(args, **kw),\n)"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 14) (variant 99) (variant 40) (variant 34)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 83) (variant 5) (variant 17)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 2) (variant 92) (variant 36)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "error_handling", "problem": "Detect and recover from infinite tool call loops (variant 100) (variant 60) (variant 91)", "solution": "# In run_conversation loop\nseen_calls = set()\nfor tool_call in response.tool_calls:\n call_key = (tool_call.name, json.dumps(tool_call.args, sort_keys=True))\n if call_key in seen_calls:\n messages.append({{\n \"role\": \"tool\",\n \"content\": \"Error: Repeated identical tool call detected. Try a different approach.\",\n }})\n continue\n seen_calls.add(call_key)\n result = handle_function_call(tool_call.name, tool_call.args)\n messages.append(tool_result_message(result))"}
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{"issue": 592, "domain": "prompt_building", "problem": "Format a tool result message for OpenAI-compatible chat API (variant 3) (variant 88)", "solution": "def tool_result_message(result: str, tool_call_id: str = \"\") -> dict:\n return {{\n \"role\": \"tool\",\n \"tool_call_id\": tool_call_id,\n \"content\": result if isinstance(result, str) else json.dumps(result),\n }}\n\nmessages.append(tool_result_message(\"42 files found\", tool_call_id=\"call_abc\"))"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 77)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 60) (variant 97) (variant 84)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 90 iterations (variant 67) (variant 82)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 11) (variant 17) (variant 67)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "tool_routing", "problem": "Register a new tool with the central registry in tools/registry.py (variant 49) (variant 4)", "solution": "from tools.registry import registry\n\ndef example_tool(param: str, task_id: str = None) -> str:\n import json\n return json.dumps({{\"success\": True, \"data\": param}})\n\nregistry.register(\n name=\"example_tool\",\n toolset=\"example\",\n schema={{\n \"name\": \"example_tool\",\n \"description\": \"Does something useful\",\n \"parameters\": {{\n \"type\": \"object\",\n \"properties\": {{\n \"param\": {{\"type\": \"string\", \"description\": \"Input parameter\"}}\n }},\n \"required\": [\"param\"],\n }},\n }},\n handler=lambda args, **kw: example_tool(\n param=args.get(\"param\", \"\"),\n task_id=kw.get(\"task_id\")\n ),\n check_fn=lambda: bool(os.getenv(\"EXAMPLE_API_KEY\")),\n requires_env=[\"EXAMPLE_API_KEY\"],\n)"}
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{"issue": 592, "domain": "utility", "problem": "Poll a background process for completion with progress tracking (variant 72)", "solution": "from tools.process_registry import ProcessRegistry\n\nregistry = ProcessRegistry()\nsession_id = registry.start(\"long_task.sh\", background=True)\n\nwhile True:\n status = registry.poll(session_id)\n if status[\"done\"]:\n print(f\"Completed with exit code {{status['exit_code']}}\")\n break\n print(f\"Progress: {{status['lines']}} lines output\")\n time.sleep(1)"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 69) (variant 85) (variant 98) (variant 15)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 30 iterations (variant 42) (variant 47) (variant 63)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 50 iterations (variant 12) (variant 20) (variant 88)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 50 iterations (variant 4) (variant 53)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 11) (variant 55) (variant 33)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 70)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 16)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 79) (variant 62)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Load user config from ~/.hermes/config.yaml with defaults fallback (variant 20) (variant 53)", "solution": "from hermes_cli.config import load_cli_config, DEFAULT_CONFIG\n\nconfig = load_cli_config()\nmodel = config.get(\"model\", DEFAULT_CONFIG[\"model\"])\nmax_iters = config.get(\"max_iterations\", DEFAULT_CONFIG[\"max_iterations\"])"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 8) (variant 75) (variant 89) (variant 79)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 23) (variant 59)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 16) (variant 59)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 57)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 29) (variant 32) (variant 26) (variant 47) (variant 93)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 9) (variant 38)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 60) (variant 32) (variant 72) (variant 72) (variant 97)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 11) (variant 17) (variant 16) (variant 54)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 56) (variant 80) (variant 30) (variant 70) (variant 95)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 27)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 9) (variant 66)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 60) (variant 97) (variant 61) (variant 40)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 14) (variant 14) (variant 18)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 30 iterations (variant 42) (variant 47) (variant 80) (variant 43)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 40) (variant 94)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"anthropic/claude-sonnet-4\", max_iterations=50)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 90 iterations (variant 67) (variant 36) (variant 81)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 30 iterations (variant 64)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 90 iterations (variant 61)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 56) (variant 80) (variant 30) (variant 70) (variant 81) (variant 41)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 40) (variant 61) (variant 40) (variant 48)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"anthropic/claude-sonnet-4\", max_iterations=50)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "error_handling", "problem": "Detect and recover from infinite tool call loops (variant 100) (variant 60) (variant 48)", "solution": "# In run_conversation loop\nseen_calls = set()\nfor tool_call in response.tool_calls:\n call_key = (tool_call.name, json.dumps(tool_call.args, sort_keys=True))\n if call_key in seen_calls:\n messages.append({{\n \"role\": \"tool\",\n \"content\": \"Error: Repeated identical tool call detected. Try a different approach.\",\n }})\n continue\n seen_calls.add(call_key)\n result = handle_function_call(tool_call.name, tool_call.args)\n messages.append(tool_result_message(result))"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 16) (variant 22)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 60)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29) (variant 21) (variant 42) (variant 86)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "testing", "problem": "Test agent loop behavior with mocked API responses (variant 87)", "solution": "import pytest\nfrom run_agent import AIAgent\n\ndef test_agent_runs_tool_call(monkeypatch):\n agent = AIAgent(model=\"test\", max_iterations=5)\n\n class MockResponse:\n tool_calls = [MockToolCall(\"read_file\", {{\"path\": \"/tmp/test.txt\"}})]\n content = None\n\n monkeypatch.setattr(agent, \"_call_api\", lambda **kw: MockResponse())\n result = agent.chat(\"Read the file\")\n assert result is not None"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 29) (variant 32)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 50) (variant 66) (variant 53)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 30 iterations", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 50 iterations (variant 4) (variant 63)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "List recent sessions from the session database with pagination", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nsessions = db.list_sessions(limit=20, offset=0)\nfor sess in sessions:\n print(f\"{{sess['id']}} | {{sess['created_at']}} | {{sess['message_count']}} msgs\")"}
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{"issue": 592, "domain": "prompt_building", "problem": "Build a few-shot prompt with examples for consistent JSON output (variant 30) (variant 4) (variant 12) (variant 86)", "solution": "system_prompt = \"\"\"You are a structured data extractor.\n\nReturn valid JSON only. No markdown, no explanation.\n\nExamples:\nInput: \"Alice is 30 years old\"\nOutput: {{\"name\": \"Alice\", \"age\": 30}}\n\nInput: \"Bob works as an engineer in Seattle\"\nOutput: {{\"name\": \"Bob\", \"job\": \"engineer\", \"location\": \"Seattle\"}}\n\nNow extract from the user input.\"\"\"\n\nmessages = [\n {{\"role\": \"system\", \"content\": system_prompt}},\n {{\"role\": \"user\", \"content\": \"Carol is a doctor in Boston, age 45\"}},\n]"}
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{"issue": 592, "domain": "utility", "problem": "Resolve provider credentials from ~/.hermes/.env (variant 15) (variant 38) (variant 90) (variant 67) (variant 77)", "solution": "from hermes_cli.auth import resolve_credentials\n\ncreds = resolve_credentials(\"anthropic\")\nprint(creds[\"api_key\"][:8] + \"...\") # masked"}
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{"issue": 592, "domain": "utility", "problem": "Poll a background process for completion with progress tracking (variant 65)", "solution": "from tools.process_registry import ProcessRegistry\n\nregistry = ProcessRegistry()\nsession_id = registry.start(\"long_task.sh\", background=True)\n\nwhile True:\n status = registry.poll(session_id)\n if status[\"done\"]:\n print(f\"Completed with exit code {{status['exit_code']}}\")\n break\n print(f\"Progress: {{status['lines']}} lines output\")\n time.sleep(1)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 50) (variant 66) (variant 87)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Resolve provider credentials from ~/.hermes/.env (variant 15) (variant 38) (variant 90)", "solution": "from hermes_cli.auth import resolve_credentials\n\ncreds = resolve_credentials(\"anthropic\")\nprint(creds[\"api_key\"][:8] + \"...\") # masked"}
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{"issue": 592, "domain": "prompt_building", "problem": "Build a few-shot prompt with examples for consistent JSON output (variant 30)", "solution": "system_prompt = \"\"\"You are a structured data extractor.\n\nReturn valid JSON only. No markdown, no explanation.\n\nExamples:\nInput: \"Alice is 30 years old\"\nOutput: {{\"name\": \"Alice\", \"age\": 30}}\n\nInput: \"Bob works as an engineer in Seattle\"\nOutput: {{\"name\": \"Bob\", \"job\": \"engineer\", \"location\": \"Seattle\"}}\n\nNow extract from the user input.\"\"\"\n\nmessages = [\n {{\"role\": \"system\", \"content\": system_prompt}},\n {{\"role\": \"user\", \"content\": \"Carol is a doctor in Boston, age 45\"}},\n]"}
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{"issue": 592, "domain": "testing", "problem": "Test agent loop behavior with mocked API responses (variant 77)", "solution": "import pytest\nfrom run_agent import AIAgent\n\ndef test_agent_runs_tool_call(monkeypatch):\n agent = AIAgent(model=\"test\", max_iterations=5)\n\n class MockResponse:\n tool_calls = [MockToolCall(\"read_file\", {{\"path\": \"/tmp/test.txt\"}})]\n content = None\n\n monkeypatch.setattr(agent, \"_call_api\", lambda **kw: MockResponse())\n result = agent.chat(\"Read the file\")\n assert result is not None"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 90 iterations (variant 77) (variant 38) (variant 74) (variant 6)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Run a subagent delegation with timeout and context isolation (variant 22) (variant 56)", "solution": "from tools.delegate_tool import delegate_task\n\nresult = delegate_task(\n goal=\"Debug this failing test\",\n context=\"test_file.py line 42 raises AssertionError\",\n max_iterations=20,\n toolsets=[\"terminal\", \"file\"],\n)\nprint(result[\"summary\"])"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 8) (variant 74) (variant 13)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "utility", "problem": "Load user config from ~/.hermes/config.yaml with defaults fallback (variant 1)", "solution": "from hermes_cli.config import load_cli_config, DEFAULT_CONFIG\n\nconfig = load_cli_config()\nmodel = config.get(\"model\", DEFAULT_CONFIG[\"model\"])\nmax_iters = config.get(\"max_iterations\", DEFAULT_CONFIG[\"max_iterations\"])"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 87)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "utility", "problem": "Poll a background process for completion with progress tracking (variant 65) (variant 29)", "solution": "from tools.process_registry import ProcessRegistry\n\nregistry = ProcessRegistry()\nsession_id = registry.start(\"long_task.sh\", background=True)\n\nwhile True:\n status = registry.poll(session_id)\n if status[\"done\"]:\n print(f\"Completed with exit code {{status['exit_code']}}\")\n break\n print(f\"Progress: {{status['lines']}} lines output\")\n time.sleep(1)"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 18)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "utility", "problem": "Load user config from ~/.hermes/config.yaml with defaults fallback", "solution": "from hermes_cli.config import load_cli_config, DEFAULT_CONFIG\n\nconfig = load_cli_config()\nmodel = config.get(\"model\", DEFAULT_CONFIG[\"model\"])\nmax_iters = config.get(\"max_iterations\", DEFAULT_CONFIG[\"max_iterations\"])"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 65) (variant 63)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "utility", "problem": "Resolve provider credentials from ~/.hermes/.env (variant 15) (variant 1)", "solution": "from hermes_cli.auth import resolve_credentials\n\ncreds = resolve_credentials(\"anthropic\")\nprint(creds[\"api_key\"][:8] + \"...\") # masked"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 71) (variant 62) (variant 66)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 37) (variant 64) (variant 77)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "error_handling", "problem": "Validate JSON output from model before parsing (variant 55) (variant 43) (variant 79)", "solution": "import json\n\ntry:\n data = json.loads(model_output)\nexcept json.JSONDecodeError:\n # Try to extract JSON from markdown code block\n import re\n match = re.search(r'```json\\n(.*?)\\n```', model_output, re.DOTALL)\n if match:\n data = json.loads(match.group(1))\n else:\n raise ValueError(\"Model did not return valid JSON\")"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 85)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 50) (variant 50) (variant 58)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 71) (variant 76)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 49) (variant 45) (variant 56)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 43) (variant 44) (variant 41) (variant 86)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 49) (variant 19) (variant 69) (variant 31)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 30 iterations", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "error_handling", "problem": "Validate JSON output from model before parsing (variant 55) (variant 43) (variant 96)", "solution": "import json\n\ntry:\n data = json.loads(model_output)\nexcept json.JSONDecodeError:\n # Try to extract JSON from markdown code block\n import re\n match = re.search(r'```json\\n(.*?)\\n```', model_output, re.DOTALL)\n if match:\n data = json.loads(match.group(1))\n else:\n raise ValueError(\"Model did not return valid JSON\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 43) (variant 70) (variant 55) (variant 79) (variant 34) (variant 23)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Enable quiet mode on AIAgent to suppress spinner and activity feed (variant 57) (variant 90)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n quiet_mode=True,\n save_trajectories=True,\n)\nresponse = agent.chat(\"Summarize this file\")\nprint(response)"}
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{"issue": 592, "domain": "tool_routing", "problem": "Check if a tool is available before calling it (variant 32) (variant 86) (variant 73)", "solution": "from tools.registry import registry\n\ntool_name = \"web_search\"\nif registry.is_available(tool_name):\n schema = registry.get_schema(tool_name)\n result = registry.call(tool_name, {{\"query\": \"Python asyncio\"}}, task_id=\"abc\")\nelse:\n result = f\"Tool {{tool_name}} is not available (missing requirements)\""}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29) (variant 73) (variant 61) (variant 95)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 93) (variant 7) (variant 82)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"anthropic/claude-sonnet-4\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 71) (variant 76) (variant 75) (variant 16)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 36) (variant 10)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 7)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 19)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 90 iterations (variant 94) (variant 67) (variant 41)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 24) (variant 38) (variant 62)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 97)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "utility", "problem": "Poll a background process for completion with progress tracking (variant 65) (variant 79)", "solution": "from tools.process_registry import ProcessRegistry\n\nregistry = ProcessRegistry()\nsession_id = registry.start(\"long_task.sh\", background=True)\n\nwhile True:\n status = registry.poll(session_id)\n if status[\"done\"]:\n print(f\"Completed with exit code {{status['exit_code']}}\")\n break\n print(f\"Progress: {{status['lines']}} lines output\")\n time.sleep(1)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 43) (variant 70) (variant 55) (variant 79) (variant 2) (variant 94) (variant 62)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Poll a background process for completion with progress tracking (variant 55) (variant 58) (variant 15) (variant 26)", "solution": "from tools.process_registry import ProcessRegistry\n\nregistry = ProcessRegistry()\nsession_id = registry.start(\"long_task.sh\", background=True)\n\nwhile True:\n status = registry.poll(session_id)\n if status[\"done\"]:\n print(f\"Completed with exit code {{status['exit_code']}}\")\n break\n print(f\"Progress: {{status['lines']}} lines output\")\n time.sleep(1)"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 71) (variant 76) (variant 75) (variant 64) (variant 67)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 69) (variant 6) (variant 78) (variant 22)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 29) (variant 81)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 20)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "utility", "problem": "Load user config from ~/.hermes/config.yaml with defaults fallback (variant 52)", "solution": "from hermes_cli.config import load_cli_config, DEFAULT_CONFIG\n\nconfig = load_cli_config()\nmodel = config.get(\"model\", DEFAULT_CONFIG[\"model\"])\nmax_iters = config.get(\"max_iterations\", DEFAULT_CONFIG[\"max_iterations\"])"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 29) (variant 32) (variant 26) (variant 47) (variant 95)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 30 iterations (variant 36)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Resolve provider credentials from ~/.hermes/.env", "solution": "from hermes_cli.auth import resolve_credentials\n\ncreds = resolve_credentials(\"anthropic\")\nprint(creds[\"api_key\"][:8] + \"...\") # masked"}
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{"issue": 592, "domain": "utility", "problem": "Resolve provider credentials from ~/.hermes/.env (variant 15) (variant 38) (variant 5) (variant 70)", "solution": "from hermes_cli.auth import resolve_credentials\n\ncreds = resolve_credentials(\"anthropic\")\nprint(creds[\"api_key\"][:8] + \"...\") # masked"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 70) (variant 81) (variant 72)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "tool_routing", "problem": "Register a new tool with the central registry in tools/registry.py (variant 13) (variant 29) (variant 5)", "solution": "from tools.registry import registry\n\ndef example_tool(param: str, task_id: str = None) -> str:\n import json\n return json.dumps({{\"success\": True, \"data\": param}})\n\nregistry.register(\n name=\"example_tool\",\n toolset=\"example\",\n schema={{\n \"name\": \"example_tool\",\n \"description\": \"Does something useful\",\n \"parameters\": {{\n \"type\": \"object\",\n \"properties\": {{\n \"param\": {{\"type\": \"string\", \"description\": \"Input parameter\"}}\n }},\n \"required\": [\"param\"],\n }},\n }},\n handler=lambda args, **kw: example_tool(\n param=args.get(\"param\", \"\"),\n task_id=kw.get(\"task_id\")\n ),\n check_fn=lambda: bool(os.getenv(\"EXAMPLE_API_KEY\")),\n requires_env=[\"EXAMPLE_API_KEY\"],\n)"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 69) (variant 85) (variant 44)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 90 iterations (variant 77) (variant 38) (variant 74)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 90 iterations (variant 88) (variant 6)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 50) (variant 93) (variant 50)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 50 iterations (variant 38) (variant 61)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 20) (variant 15)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 49) (variant 45) (variant 16)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "utility", "problem": "Resolve provider credentials from ~/.hermes/.env (variant 15) (variant 38)", "solution": "from hermes_cli.auth import resolve_credentials\n\ncreds = resolve_credentials(\"anthropic\")\nprint(creds[\"api_key\"][:8] + \"...\") # masked"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 33) (variant 84) (variant 66)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 46) (variant 51) (variant 62)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 90 iterations (variant 30) (variant 44) (variant 31)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 60) (variant 97) (variant 41) (variant 65)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 93)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"anthropic/claude-sonnet-4\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "tool_routing", "problem": "Register a new tool with the central registry in tools/registry.py (variant 13) (variant 29)", "solution": "from tools.registry import registry\n\ndef example_tool(param: str, task_id: str = None) -> str:\n import json\n return json.dumps({{\"success\": True, \"data\": param}})\n\nregistry.register(\n name=\"example_tool\",\n toolset=\"example\",\n schema={{\n \"name\": \"example_tool\",\n \"description\": \"Does something useful\",\n \"parameters\": {{\n \"type\": \"object\",\n \"properties\": {{\n \"param\": {{\"type\": \"string\", \"description\": \"Input parameter\"}}\n }},\n \"required\": [\"param\"],\n }},\n }},\n handler=lambda args, **kw: example_tool(\n param=args.get(\"param\", \"\"),\n task_id=kw.get(\"task_id\")\n ),\n check_fn=lambda: bool(os.getenv(\"EXAMPLE_API_KEY\")),\n requires_env=[\"EXAMPLE_API_KEY\"],\n)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=50)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 93) (variant 7) (variant 44) (variant 25)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"anthropic/claude-sonnet-4\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 95)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 71) (variant 62) (variant 66) (variant 82)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "prompt_building", "problem": "Format a tool result message for OpenAI-compatible chat API (variant 3) (variant 88) (variant 45) (variant 17) (variant 99) (variant 15)", "solution": "def tool_result_message(result: str, tool_call_id: str = \"\") -> dict:\n return {{\n \"role\": \"tool\",\n \"tool_call_id\": tool_call_id,\n \"content\": result if isinstance(result, str) else json.dumps(result),\n }}\n\nmessages.append(tool_result_message(\"42 files found\", tool_call_id=\"call_abc\"))"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 17) (variant 99) (variant 22) (variant 56) (variant 55) (variant 98)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "session_management", "problem": "List recent sessions from the session database with pagination (variant 54)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nsessions = db.list_sessions(limit=20, offset=0)\nfor sess in sessions:\n print(f\"{{sess['id']}} | {{sess['created_at']}} | {{sess['message_count']}} msgs\")"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 9)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 69) (variant 54) (variant 25) (variant 7)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 72) (variant 57)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "config", "problem": "Bump config schema version and add migration for existing users (variant 76)", "solution": "# In hermes_cli/config.py\n\nDEFAULT_CONFIG = {{\n \"_config_version\": 6, # bumped from 5\n \"model\": \"anthropic/claude-sonnet-4\",\n \"max_iterations\": 50,\n \"new_feature\": True, # added\n}}\n\ndef migrate_config(raw: dict) -> dict:\n version = raw.get(\"_config_version\", 0)\n if version < 6:\n raw[\"new_feature\"] = DEFAULT_CONFIG[\"new_feature\"]\n raw[\"_config_version\"] = 6\n return raw"}
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{"issue": 592, "domain": "tool_routing", "problem": "Register a new tool with the central registry in tools/registry.py (variant 13) (variant 29) (variant 74)", "solution": "from tools.registry import registry\n\ndef example_tool(param: str, task_id: str = None) -> str:\n import json\n return json.dumps({{\"success\": True, \"data\": param}})\n\nregistry.register(\n name=\"example_tool\",\n toolset=\"example\",\n schema={{\n \"name\": \"example_tool\",\n \"description\": \"Does something useful\",\n \"parameters\": {{\n \"type\": \"object\",\n \"properties\": {{\n \"param\": {{\"type\": \"string\", \"description\": \"Input parameter\"}}\n }},\n \"required\": [\"param\"],\n }},\n }},\n handler=lambda args, **kw: example_tool(\n param=args.get(\"param\", \"\"),\n task_id=kw.get(\"task_id\")\n ),\n check_fn=lambda: bool(os.getenv(\"EXAMPLE_API_KEY\")),\n requires_env=[\"EXAMPLE_API_KEY\"],\n)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 33) (variant 8) (variant 20) (variant 2) (variant 57) (variant 44)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 18) (variant 64) (variant 54)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 69) (variant 85) (variant 44) (variant 55)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 56) (variant 80) (variant 30) (variant 70) (variant 95) (variant 88)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29) (variant 73)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 37)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 99)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "config", "problem": "Bump config schema version and add migration for existing users (variant 9) (variant 1)", "solution": "# In hermes_cli/config.py\n\nDEFAULT_CONFIG = {{\n \"_config_version\": 6, # bumped from 5\n \"model\": \"anthropic/claude-sonnet-4\",\n \"max_iterations\": 50,\n \"new_feature\": True, # added\n}}\n\ndef migrate_config(raw: dict) -> dict:\n version = raw.get(\"_config_version\", 0)\n if version < 6:\n raw[\"new_feature\"] = DEFAULT_CONFIG[\"new_feature\"]\n raw[\"_config_version\"] = 6\n return raw"}
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{"issue": 592, "domain": "error_handling", "problem": "Catch and log tool execution errors without crashing the agent loop (variant 68) (variant 96) (variant 59)", "solution": "import json\nimport traceback\n\ntry:\n result = handle_function_call(tool_call.name, tool_call.args)\nexcept Exception as e:\n tb = traceback.format_exc()\n result = json.dumps({{\n \"error\": str(e),\n \"traceback\": tb,\n }})"}
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{"issue": 592, "domain": "error_handling", "problem": "Validate JSON output from model before parsing (variant 55) (variant 43) (variant 79) (variant 31) (variant 86) (variant 9) (variant 13)", "solution": "import json\n\ntry:\n data = json.loads(model_output)\nexcept json.JSONDecodeError:\n # Try to extract JSON from markdown code block\n import re\n match = re.search(r'```json\\n(.*?)\\n```', model_output, re.DOTALL)\n if match:\n data = json.loads(match.group(1))\n else:\n raise ValueError(\"Model did not return valid JSON\")"}
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{"issue": 592, "domain": "tool_routing", "problem": "Check if a tool is available before calling it", "solution": "from tools.registry import registry\n\ntool_name = \"web_search\"\nif registry.is_available(tool_name):\n schema = registry.get_schema(tool_name)\n result = registry.call(tool_name, {{\"query\": \"Python asyncio\"}}, task_id=\"abc\")\nelse:\n result = f\"Tool {{tool_name}} is not available (missing requirements)\""}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 72) (variant 57) (variant 11)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "error_handling", "problem": "Handle missing optional dependencies with graceful degradation (variant 12) (variant 17) (variant 71) (variant 35) (variant 49)", "solution": "try:\n import chromadb\n HAS_CHROMADB = True\nexcept ImportError:\n HAS_CHROMADB = False\n\ndef search_vectors(query: str):\n if not HAS_CHROMADB:\n return {{\"warning\": \"ChromaDB not installed\", \"results\": []}}\n # ... actual implementation"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 90 iterations (variant 88) (variant 15)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "config", "problem": "Bump config schema version and add migration for existing users (variant 9) (variant 2) (variant 22)", "solution": "# In hermes_cli/config.py\n\nDEFAULT_CONFIG = {{\n \"_config_version\": 6, # bumped from 5\n \"model\": \"anthropic/claude-sonnet-4\",\n \"max_iterations\": 50,\n \"new_feature\": True, # added\n}}\n\ndef migrate_config(raw: dict) -> dict:\n version = raw.get(\"_config_version\", 0)\n if version < 6:\n raw[\"new_feature\"] = DEFAULT_CONFIG[\"new_feature\"]\n raw[\"_config_version\"] = 6\n return raw"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 56) (variant 72) (variant 28)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 50) (variant 66) (variant 53) (variant 73) (variant 98) (variant 59)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 37) (variant 74) (variant 26)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "utility", "problem": "Switch model mid-session with /model slash command (variant 11)", "solution": "# In cli.py or gateway/run.py\nfrom hermes_cli.model_switch import switch_model\n\nnew_model = switch_model(\"openai/gpt-4o\")\nprint(f\"Switched to {{new_model}}\")"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 69) (variant 39)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 19) (variant 89) (variant 92) (variant 90)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "tool_routing", "problem": "Check if a tool is available before calling it (variant 32) (variant 86) (variant 26) (variant 57) (variant 20)", "solution": "from tools.registry import registry\n\ntool_name = \"web_search\"\nif registry.is_available(tool_name):\n schema = registry.get_schema(tool_name)\n result = registry.call(tool_name, {{\"query\": \"Python asyncio\"}}, task_id=\"abc\")\nelse:\n result = f\"Tool {{tool_name}} is not available (missing requirements)\""}
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{"issue": 592, "domain": "testing", "problem": "Test agent loop behavior with mocked API responses (variant 77) (variant 53)", "solution": "import pytest\nfrom run_agent import AIAgent\n\ndef test_agent_runs_tool_call(monkeypatch):\n agent = AIAgent(model=\"test\", max_iterations=5)\n\n class MockResponse:\n tool_calls = [MockToolCall(\"read_file\", {{\"path\": \"/tmp/test.txt\"}})]\n content = None\n\n monkeypatch.setattr(agent, \"_call_api\", lambda **kw: MockResponse())\n result = agent.chat(\"Read the file\")\n assert result is not None"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 29) (variant 58) (variant 46)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 50 iterations", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 53) (variant 34)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 18) (variant 63) (variant 26)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29) (variant 74) (variant 91) (variant 46)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "utility", "problem": "Load user config from ~/.hermes/config.yaml with defaults fallback (variant 20)", "solution": "from hermes_cli.config import load_cli_config, DEFAULT_CONFIG\n\nconfig = load_cli_config()\nmodel = config.get(\"model\", DEFAULT_CONFIG[\"model\"])\nmax_iters = config.get(\"max_iterations\", DEFAULT_CONFIG[\"max_iterations\"])"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 90 iterations (variant 85)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 43) (variant 44) (variant 54)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "utility", "problem": "Switch model mid-session with /model slash command", "solution": "# In cli.py or gateway/run.py\nfrom hermes_cli.model_switch import switch_model\n\nnew_model = switch_model(\"openai/gpt-4o\")\nprint(f\"Switched to {{new_model}}\")"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 71) (variant 76) (variant 75) (variant 64)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 49) (variant 45)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 50) (variant 27) (variant 76)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 2) (variant 92) (variant 68)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 85) (variant 96)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 50) (variant 27) (variant 51) (variant 27) (variant 46)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "error_handling", "problem": "Catch and log tool execution errors without crashing the agent loop (variant 39) (variant 42)", "solution": "import json\nimport traceback\n\ntry:\n result = handle_function_call(tool_call.name, tool_call.args)\nexcept Exception as e:\n tb = traceback.format_exc()\n result = json.dumps({{\n \"error\": str(e),\n \"traceback\": tb,\n }})"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 45)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 29) (variant 32) (variant 44) (variant 96) (variant 44)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 37) (variant 74) (variant 26) (variant 34) (variant 92) (variant 56)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "utility", "problem": "Read a file safely with size limits and binary detection", "solution": "from tools.file_tools import read_file\n\ncontent = read_file(\n path=\"/tmp/large.log\",\n offset=1,\n limit=500,\n)\nprint(content)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 50) (variant 66) (variant 53) (variant 73) (variant 3) (variant 6) (variant 5)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 75)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=50)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 33) (variant 8) (variant 1) (variant 24) (variant 10)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 61) (variant 98) (variant 61) (variant 29) (variant 77)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "config", "problem": "Bump config schema version and add migration for existing users (variant 76) (variant 38)", "solution": "# In hermes_cli/config.py\n\nDEFAULT_CONFIG = {{\n \"_config_version\": 6, # bumped from 5\n \"model\": \"anthropic/claude-sonnet-4\",\n \"max_iterations\": 50,\n \"new_feature\": True, # added\n}}\n\ndef migrate_config(raw: dict) -> dict:\n version = raw.get(\"_config_version\", 0)\n if version < 6:\n raw[\"new_feature\"] = DEFAULT_CONFIG[\"new_feature\"]\n raw[\"_config_version\"] = 6\n return raw"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 33) (variant 8) (variant 1)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 60) (variant 97) (variant 61)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "utility", "problem": "Poll a background process for completion with progress tracking (variant 55) (variant 65) (variant 48) (variant 23)", "solution": "from tools.process_registry import ProcessRegistry\n\nregistry = ProcessRegistry()\nsession_id = registry.start(\"long_task.sh\", background=True)\n\nwhile True:\n status = registry.poll(session_id)\n if status[\"done\"]:\n print(f\"Completed with exit code {{status['exit_code']}}\")\n break\n print(f\"Progress: {{status['lines']}} lines output\")\n time.sleep(1)"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 28) (variant 34) (variant 46)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 53) (variant 56) (variant 99)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "error_handling", "problem": "Detect and recover from infinite tool call loops (variant 35) (variant 31)", "solution": "# In run_conversation loop\nseen_calls = set()\nfor tool_call in response.tool_calls:\n call_key = (tool_call.name, json.dumps(tool_call.args, sort_keys=True))\n if call_key in seen_calls:\n messages.append({{\n \"role\": \"tool\",\n \"content\": \"Error: Repeated identical tool call detected. Try a different approach.\",\n }})\n continue\n seen_calls.add(call_key)\n result = handle_function_call(tool_call.name, tool_call.args)\n messages.append(tool_result_message(result))"}
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{"issue": 592, "domain": "error_handling", "problem": "Validate JSON output from model before parsing (variant 55) (variant 43) (variant 79) (variant 31) (variant 86) (variant 9) (variant 49)", "solution": "import json\n\ntry:\n data = json.loads(model_output)\nexcept json.JSONDecodeError:\n # Try to extract JSON from markdown code block\n import re\n match = re.search(r'```json\\n(.*?)\\n```', model_output, re.DOTALL)\n if match:\n data = json.loads(match.group(1))\n else:\n raise ValueError(\"Model did not return valid JSON\")"}
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{"issue": 592, "domain": "prompt_building", "problem": "Format a tool result message for OpenAI-compatible chat API (variant 3) (variant 88) (variant 3) (variant 40)", "solution": "def tool_result_message(result: str, tool_call_id: str = \"\") -> dict:\n return {{\n \"role\": \"tool\",\n \"tool_call_id\": tool_call_id,\n \"content\": result if isinstance(result, str) else json.dumps(result),\n }}\n\nmessages.append(tool_result_message(\"42 files found\", tool_call_id=\"call_abc\"))"}
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{"issue": 592, "domain": "utility", "problem": "Resolve provider credentials from ~/.hermes/.env (variant 15) (variant 38) (variant 5)", "solution": "from hermes_cli.auth import resolve_credentials\n\ncreds = resolve_credentials(\"anthropic\")\nprint(creds[\"api_key\"][:8] + \"...\") # masked"}
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{"issue": 592, "domain": "agent_loop", "problem": "Enable quiet mode on AIAgent to suppress spinner and activity feed", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n quiet_mode=True,\n save_trajectories=True,\n)\nresponse = agent.chat(\"Summarize this file\")\nprint(response)"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 18) (variant 9) (variant 21) (variant 91)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 33) (variant 8) (variant 20)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 6) (variant 8) (variant 44)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "prompt_building", "problem": "Build a system prompt with skills injected as slash commands (variant 5) (variant 74)", "solution": "from agent.prompt_builder import PromptBuilder\nfrom agent.skill_commands import scan_skills\n\nbuilder = PromptBuilder()\nskills = scan_skills(\"~/.hermes/skills/\")\n\nsystem_prompt = builder.build(\n base_prompt=\"You are a helpful coding assistant.\",\n skills=skills,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n user_preferences={{\"language\": \"Python\", \"style\": \"concise\"}},\n)\nprint(system_prompt)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 1)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "error_handling", "problem": "Catch and log tool execution errors without crashing the agent loop (variant 39) (variant 71) (variant 14)", "solution": "import json\nimport traceback\n\ntry:\n result = handle_function_call(tool_call.name, tool_call.args)\nexcept Exception as e:\n tb = traceback.format_exc()\n result = json.dumps({{\n \"error\": str(e),\n \"traceback\": tb,\n }})"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 8) (variant 74) (variant 94)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 60) (variant 32) (variant 72) (variant 53)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 69) (variant 54) (variant 69)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 37) (variant 74) (variant 26) (variant 34) (variant 92)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 90 iterations", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "error_handling", "problem": "Catch and log tool execution errors without crashing the agent loop (variant 39) (variant 71) (variant 6) (variant 31)", "solution": "import json\nimport traceback\n\ntry:\n result = handle_function_call(tool_call.name, tool_call.args)\nexcept Exception as e:\n tb = traceback.format_exc()\n result = json.dumps({{\n \"error\": str(e),\n \"traceback\": tb,\n }})"}
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{"issue": 592, "domain": "tool_routing", "problem": "Check if a tool is available before calling it (variant 32) (variant 86) (variant 75) (variant 76) (variant 59) (variant 90)", "solution": "from tools.registry import registry\n\ntool_name = \"web_search\"\nif registry.is_available(tool_name):\n schema = registry.get_schema(tool_name)\n result = registry.call(tool_name, {{\"query\": \"Python asyncio\"}}, task_id=\"abc\")\nelse:\n result = f\"Tool {{tool_name}} is not available (missing requirements)\""}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 82) (variant 22) (variant 41)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=50)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 72) (variant 57) (variant 11) (variant 52) (variant 90)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "tool_routing", "problem": "Wrap a tool handler to add logging and error handling (variant 39) (variant 14)", "solution": "import json\nimport logging\nfrom tools.registry import registry\n\nlogger = logging.getLogger(__name__)\n\ndef logged_handler(fn):\n def wrapper(args, **kwargs):\n task_id = kwargs.get(\"task_id\")\n logger.info(f\"[{{task_id}}] Calling {{fn.__name__}} with {{args}}\")\n try:\n result = fn(args, **kwargs)\n logger.info(f\"[{{task_id}}] Success\")\n return result\n except Exception as e:\n logger.error(f\"[{{task_id}}] Error: {{e}}\")\n return json.dumps({{\"error\": str(e)}})\n return wrapper\n\n# Register with wrapper\nregistry.register(\n name=\"my_tool\",\n toolset=\"custom\",\n schema={{...}},\n handler=lambda args, **kw: logged_handler(my_tool_impl)(args, **kw),\n)"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 8) (variant 75) (variant 89) (variant 34)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 61) (variant 93)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29) (variant 69) (variant 20)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 69) (variant 54) (variant 25) (variant 66)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 69) (variant 6) (variant 59)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 2) (variant 65)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "tool_routing", "problem": "Wrap a tool handler to add logging and error handling (variant 39) (variant 59) (variant 62) (variant 29)", "solution": "import json\nimport logging\nfrom tools.registry import registry\n\nlogger = logging.getLogger(__name__)\n\ndef logged_handler(fn):\n def wrapper(args, **kwargs):\n task_id = kwargs.get(\"task_id\")\n logger.info(f\"[{{task_id}}] Calling {{fn.__name__}} with {{args}}\")\n try:\n result = fn(args, **kwargs)\n logger.info(f\"[{{task_id}}] Success\")\n return result\n except Exception as e:\n logger.error(f\"[{{task_id}}] Error: {{e}}\")\n return json.dumps({{\"error\": str(e)}})\n return wrapper\n\n# Register with wrapper\nregistry.register(\n name=\"my_tool\",\n toolset=\"custom\",\n schema={{...}},\n handler=lambda args, **kw: logged_handler(my_tool_impl)(args, **kw),\n)"}
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{"issue": 592, "domain": "config", "problem": "Bump config schema version and add migration for existing users (variant 9)", "solution": "# In hermes_cli/config.py\n\nDEFAULT_CONFIG = {{\n \"_config_version\": 6, # bumped from 5\n \"model\": \"anthropic/claude-sonnet-4\",\n \"max_iterations\": 50,\n \"new_feature\": True, # added\n}}\n\ndef migrate_config(raw: dict) -> dict:\n version = raw.get(\"_config_version\", 0)\n if version < 6:\n raw[\"new_feature\"] = DEFAULT_CONFIG[\"new_feature\"]\n raw[\"_config_version\"] = 6\n return raw"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 56) (variant 28)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "prompt_building", "problem": "Add a reasoning block to an assistant message for chain-of-thought (variant 26)", "solution": "assistant_msg = {{\n \"role\": \"assistant\",\n \"content\": \"The answer is 42.\",\n \"reasoning\": \"I calculated this by summing the factors: 1+2+3+4+6+7+12+14+21+28 = 96. Wait, let me recheck... Actually 42 is the answer to life, the universe, and everything.\",\n}}\n\nmessages.append(assistant_msg)"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 69) (variant 85) (variant 98)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "error_handling", "problem": "Catch and log tool execution errors without crashing the agent loop (variant 39) (variant 54)", "solution": "import json\nimport traceback\n\ntry:\n result = handle_function_call(tool_call.name, tool_call.args)\nexcept Exception as e:\n tb = traceback.format_exc()\n result = json.dumps({{\n \"error\": str(e),\n \"traceback\": tb,\n }})"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 18) (variant 61)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 6) (variant 8)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 56) (variant 80) (variant 30) (variant 70)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 29) (variant 32) (variant 15)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "tool_routing", "problem": "Wrap a tool handler to add logging and error handling (variant 39) (variant 59) (variant 62)", "solution": "import json\nimport logging\nfrom tools.registry import registry\n\nlogger = logging.getLogger(__name__)\n\ndef logged_handler(fn):\n def wrapper(args, **kwargs):\n task_id = kwargs.get(\"task_id\")\n logger.info(f\"[{{task_id}}] Calling {{fn.__name__}} with {{args}}\")\n try:\n result = fn(args, **kwargs)\n logger.info(f\"[{{task_id}}] Success\")\n return result\n except Exception as e:\n logger.error(f\"[{{task_id}}] Error: {{e}}\")\n return json.dumps({{\"error\": str(e)}})\n return wrapper\n\n# Register with wrapper\nregistry.register(\n name=\"my_tool\",\n toolset=\"custom\",\n schema={{...}},\n handler=lambda args, **kw: logged_handler(my_tool_impl)(args, **kw),\n)"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 17) (variant 82)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 43)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "utility", "problem": "Resolve provider credentials from ~/.hermes/.env (variant 25)", "solution": "from hermes_cli.auth import resolve_credentials\n\ncreds = resolve_credentials(\"anthropic\")\nprint(creds[\"api_key\"][:8] + \"...\") # masked"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 60) (variant 97) (variant 19)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 17) (variant 99) (variant 22)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "utility", "problem": "Run a subagent delegation with timeout and context isolation (variant 10)", "solution": "from tools.delegate_tool import delegate_task\n\nresult = delegate_task(\n goal=\"Debug this failing test\",\n context=\"test_file.py line 42 raises AssertionError\",\n max_iterations=20,\n toolsets=[\"terminal\", \"file\"],\n)\nprint(result[\"summary\"])"}
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{"issue": 592, "domain": "error_handling", "problem": "Catch and log tool execution errors without crashing the agent loop (variant 68) (variant 96)", "solution": "import json\nimport traceback\n\ntry:\n result = handle_function_call(tool_call.name, tool_call.args)\nexcept Exception as e:\n tb = traceback.format_exc()\n result = json.dumps({{\n \"error\": str(e),\n \"traceback\": tb,\n }})"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 50 iterations (variant 28) (variant 83)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 16) (variant 4) (variant 4)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 8) (variant 74) (variant 94) (variant 43)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 72) (variant 57) (variant 11) (variant 52) (variant 85)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 39) (variant 17) (variant 44)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 61) (variant 98) (variant 61)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "utility", "problem": "Load user config from ~/.hermes/config.yaml with defaults fallback (variant 20) (variant 29) (variant 49)", "solution": "from hermes_cli.config import load_cli_config, DEFAULT_CONFIG\n\nconfig = load_cli_config()\nmodel = config.get(\"model\", DEFAULT_CONFIG[\"model\"])\nmax_iters = config.get(\"max_iterations\", DEFAULT_CONFIG[\"max_iterations\"])"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 61) (variant 98) (variant 61) (variant 29) (variant 69)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "tool_routing", "problem": "Wrap a tool handler to add logging and error handling (variant 39) (variant 60) (variant 96)", "solution": "import json\nimport logging\nfrom tools.registry import registry\n\nlogger = logging.getLogger(__name__)\n\ndef logged_handler(fn):\n def wrapper(args, **kwargs):\n task_id = kwargs.get(\"task_id\")\n logger.info(f\"[{{task_id}}] Calling {{fn.__name__}} with {{args}}\")\n try:\n result = fn(args, **kwargs)\n logger.info(f\"[{{task_id}}] Success\")\n return result\n except Exception as e:\n logger.error(f\"[{{task_id}}] Error: {{e}}\")\n return json.dumps({{\"error\": str(e)}})\n return wrapper\n\n# Register with wrapper\nregistry.register(\n name=\"my_tool\",\n toolset=\"custom\",\n schema={{...}},\n handler=lambda args, **kw: logged_handler(my_tool_impl)(args, **kw),\n)"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 81)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 24)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 36) (variant 8) (variant 66)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 58)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 90 iterations (variant 77) (variant 38) (variant 74) (variant 45)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Resolve provider credentials from ~/.hermes/.env (variant 15) (variant 38) (variant 90) (variant 21)", "solution": "from hermes_cli.auth import resolve_credentials\n\ncreds = resolve_credentials(\"anthropic\")\nprint(creds[\"api_key\"][:8] + \"...\") # masked"}
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{"issue": 592, "domain": "error_handling", "problem": "Detect and recover from infinite tool call loops (variant 100) (variant 60) (variant 38)", "solution": "# In run_conversation loop\nseen_calls = set()\nfor tool_call in response.tool_calls:\n call_key = (tool_call.name, json.dumps(tool_call.args, sort_keys=True))\n if call_key in seen_calls:\n messages.append({{\n \"role\": \"tool\",\n \"content\": \"Error: Repeated identical tool call detected. Try a different approach.\",\n }})\n continue\n seen_calls.add(call_key)\n result = handle_function_call(tool_call.name, tool_call.args)\n messages.append(tool_result_message(result))"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 50) (variant 50) (variant 40)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 90 iterations (variant 94) (variant 67) (variant 100)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 29) (variant 32) (variant 26)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 43) (variant 44) (variant 41) (variant 86) (variant 42)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 49) (variant 45) (variant 16) (variant 10)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 51)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 30 iterations (variant 42) (variant 47)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 84)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 50 iterations (variant 28) (variant 97) (variant 9)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 61) (variant 98) (variant 61) (variant 29) (variant 77) (variant 71)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 61) (variant 98) (variant 61) (variant 29) (variant 2)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 90 iterations (variant 30) (variant 44) (variant 53)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "tool_routing", "problem": "Register a new tool with the central registry in tools/registry.py (variant 49)", "solution": "from tools.registry import registry\n\ndef example_tool(param: str, task_id: str = None) -> str:\n import json\n return json.dumps({{\"success\": True, \"data\": param}})\n\nregistry.register(\n name=\"example_tool\",\n toolset=\"example\",\n schema={{\n \"name\": \"example_tool\",\n \"description\": \"Does something useful\",\n \"parameters\": {{\n \"type\": \"object\",\n \"properties\": {{\n \"param\": {{\"type\": \"string\", \"description\": \"Input parameter\"}}\n }},\n \"required\": [\"param\"],\n }},\n }},\n handler=lambda args, **kw: example_tool(\n param=args.get(\"param\", \"\"),\n task_id=kw.get(\"task_id\")\n ),\n check_fn=lambda: bool(os.getenv(\"EXAMPLE_API_KEY\")),\n requires_env=[\"EXAMPLE_API_KEY\"],\n)"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 2) (variant 32)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 31) (variant 50)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "tool_routing", "problem": "Discover all builtin tools and build tool schemas for the API call (variant 52) (variant 80)", "solution": "from model_tools import discover_builtin_tools\nfrom tools.registry import registry\n\n# Auto-discover all registered tools\ndiscover_builtin_tools()\n\n# Collect schemas for all available tools\ntool_schemas = [registry.get_schema(name) for name in registry.list_available()]\n\n# Filter by enabled toolsets\nenabled = [\"web\", \"terminal\", \"file\"]\ntool_schemas = [\n s for s in tool_schemas\n if registry.get_toolset(s[\"name\"]) in enabled\n]"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 43) (variant 25)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "tool_routing", "problem": "Check if a tool is available before calling it (variant 32) (variant 86) (variant 75)", "solution": "from tools.registry import registry\n\ntool_name = \"web_search\"\nif registry.is_available(tool_name):\n schema = registry.get_schema(tool_name)\n result = registry.call(tool_name, {{\"query\": \"Python asyncio\"}}, task_id=\"abc\")\nelse:\n result = f\"Tool {{tool_name}} is not available (missing requirements)\""}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 50 iterations (variant 48) (variant 68)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "tool_routing", "problem": "Discover all builtin tools and build tool schemas for the API call (variant 52) (variant 14) (variant 19) (variant 69)", "solution": "from model_tools import discover_builtin_tools\nfrom tools.registry import registry\n\n# Auto-discover all registered tools\ndiscover_builtin_tools()\n\n# Collect schemas for all available tools\ntool_schemas = [registry.get_schema(name) for name in registry.list_available()]\n\n# Filter by enabled toolsets\nenabled = [\"web\", \"terminal\", \"file\"]\ntool_schemas = [\n s for s in tool_schemas\n if registry.get_toolset(s[\"name\"]) in enabled\n]"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 60) (variant 32) (variant 72) (variant 72)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "utility", "problem": "Poll a background process for completion with progress tracking (variant 55) (variant 58)", "solution": "from tools.process_registry import ProcessRegistry\n\nregistry = ProcessRegistry()\nsession_id = registry.start(\"long_task.sh\", background=True)\n\nwhile True:\n status = registry.poll(session_id)\n if status[\"done\"]:\n print(f\"Completed with exit code {{status['exit_code']}}\")\n break\n print(f\"Progress: {{status['lines']}} lines output\")\n time.sleep(1)"}
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{"issue": 592, "domain": "prompt_building", "problem": "Format a tool result message for OpenAI-compatible chat API (variant 39)", "solution": "def tool_result_message(result: str, tool_call_id: str = \"\") -> dict:\n return {{\n \"role\": \"tool\",\n \"tool_call_id\": tool_call_id,\n \"content\": result if isinstance(result, str) else json.dumps(result),\n }}\n\nmessages.append(tool_result_message(\"42 files found\", tool_call_id=\"call_abc\"))"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 60) (variant 97) (variant 61) (variant 4)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 70)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"anthropic/claude-sonnet-4\", max_iterations=50)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "error_handling", "problem": "Catch and log tool execution errors without crashing the agent loop (variant 68)", "solution": "import json\nimport traceback\n\ntry:\n result = handle_function_call(tool_call.name, tool_call.args)\nexcept Exception as e:\n tb = traceback.format_exc()\n result = json.dumps({{\n \"error\": str(e),\n \"traceback\": tb,\n }})"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 8) (variant 75) (variant 8)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 33) (variant 84)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 90 iterations (variant 85) (variant 95) (variant 33)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "config", "problem": "Bump config schema version and add migration for existing users (variant 9) (variant 2)", "solution": "# In hermes_cli/config.py\n\nDEFAULT_CONFIG = {{\n \"_config_version\": 6, # bumped from 5\n \"model\": \"anthropic/claude-sonnet-4\",\n \"max_iterations\": 50,\n \"new_feature\": True, # added\n}}\n\ndef migrate_config(raw: dict) -> dict:\n version = raw.get(\"_config_version\", 0)\n if version < 6:\n raw[\"new_feature\"] = DEFAULT_CONFIG[\"new_feature\"]\n raw[\"_config_version\"] = 6\n return raw"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 24) (variant 38) (variant 68)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 5) (variant 27) (variant 65)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "prompt_building", "problem": "Add a reasoning block to an assistant message for chain-of-thought", "solution": "assistant_msg = {{\n \"role\": \"assistant\",\n \"content\": \"The answer is 42.\",\n \"reasoning\": \"I calculated this by summing the factors: 1+2+3+4+6+7+12+14+21+28 = 96. Wait, let me recheck... Actually 42 is the answer to life, the universe, and everything.\",\n}}\n\nmessages.append(assistant_msg)"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 16) (variant 67) (variant 50) (variant 92)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "tool_routing", "problem": "Discover all builtin tools and build tool schemas for the API call (variant 52) (variant 14)", "solution": "from model_tools import discover_builtin_tools\nfrom tools.registry import registry\n\n# Auto-discover all registered tools\ndiscover_builtin_tools()\n\n# Collect schemas for all available tools\ntool_schemas = [registry.get_schema(name) for name in registry.list_available()]\n\n# Filter by enabled toolsets\nenabled = [\"web\", \"terminal\", \"file\"]\ntool_schemas = [\n s for s in tool_schemas\n if registry.get_toolset(s[\"name\"]) in enabled\n]"}
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{"issue": 592, "domain": "error_handling", "problem": "Catch and log tool execution errors without crashing the agent loop (variant 68) (variant 96) (variant 39)", "solution": "import json\nimport traceback\n\ntry:\n result = handle_function_call(tool_call.name, tool_call.args)\nexcept Exception as e:\n tb = traceback.format_exc()\n result = json.dumps({{\n \"error\": str(e),\n \"traceback\": tb,\n }})"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 28) (variant 2)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 30 iterations (variant 42) (variant 47) (variant 54)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29) (variant 73) (variant 61)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 39) (variant 17)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 56) (variant 80) (variant 30) (variant 70) (variant 81) (variant 16)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 5) (variant 27) (variant 100)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "error_handling", "problem": "Handle missing optional dependencies with graceful degradation (variant 76)", "solution": "try:\n import chromadb\n HAS_CHROMADB = True\nexcept ImportError:\n HAS_CHROMADB = False\n\ndef search_vectors(query: str):\n if not HAS_CHROMADB:\n return {{\"warning\": \"ChromaDB not installed\", \"results\": []}}\n # ... actual implementation"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 61) (variant 32) (variant 27)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 30 iterations (variant 42) (variant 47) (variant 35)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "prompt_building", "problem": "Format a tool result message for OpenAI-compatible chat API (variant 3) (variant 48)", "solution": "def tool_result_message(result: str, tool_call_id: str = \"\") -> dict:\n return {{\n \"role\": \"tool\",\n \"tool_call_id\": tool_call_id,\n \"content\": result if isinstance(result, str) else json.dumps(result),\n }}\n\nmessages.append(tool_result_message(\"42 files found\", tool_call_id=\"call_abc\"))"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 29) (variant 58) (variant 24)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 50) (variant 66)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Poll a background process for completion with progress tracking", "solution": "from tools.process_registry import ProcessRegistry\n\nregistry = ProcessRegistry()\nsession_id = registry.start(\"long_task.sh\", background=True)\n\nwhile True:\n status = registry.poll(session_id)\n if status[\"done\"]:\n print(f\"Completed with exit code {{status['exit_code']}}\")\n break\n print(f\"Progress: {{status['lines']}} lines output\")\n time.sleep(1)"}
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{"issue": 592, "domain": "utility", "problem": "Read a file safely with size limits and binary detection (variant 89)", "solution": "from tools.file_tools import read_file\n\ncontent = read_file(\n path=\"/tmp/large.log\",\n offset=1,\n limit=500,\n)\nprint(content)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 50 iterations (variant 28) (variant 97) (variant 85)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 50 iterations (variant 4) (variant 16)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 43) (variant 27) (variant 20)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "tool_routing", "problem": "Register a new tool with the central registry in tools/registry.py", "solution": "from tools.registry import registry\n\ndef example_tool(param: str, task_id: str = None) -> str:\n import json\n return json.dumps({{\"success\": True, \"data\": param}})\n\nregistry.register(\n name=\"example_tool\",\n toolset=\"example\",\n schema={{\n \"name\": \"example_tool\",\n \"description\": \"Does something useful\",\n \"parameters\": {{\n \"type\": \"object\",\n \"properties\": {{\n \"param\": {{\"type\": \"string\", \"description\": \"Input parameter\"}}\n }},\n \"required\": [\"param\"],\n }},\n }},\n handler=lambda args, **kw: example_tool(\n param=args.get(\"param\", \"\"),\n task_id=kw.get(\"task_id\")\n ),\n check_fn=lambda: bool(os.getenv(\"EXAMPLE_API_KEY\")),\n requires_env=[\"EXAMPLE_API_KEY\"],\n)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 90 iterations (variant 94)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 2) (variant 7) (variant 52)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "utility", "problem": "Load user config from ~/.hermes/config.yaml with defaults fallback (variant 47) (variant 95)", "solution": "from hermes_cli.config import load_cli_config, DEFAULT_CONFIG\n\nconfig = load_cli_config()\nmodel = config.get(\"model\", DEFAULT_CONFIG[\"model\"])\nmax_iters = config.get(\"max_iterations\", DEFAULT_CONFIG[\"max_iterations\"])"}
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{"issue": 592, "domain": "error_handling", "problem": "Handle missing optional dependencies with graceful degradation (variant 12) (variant 17) (variant 71) (variant 35) (variant 49) (variant 6)", "solution": "try:\n import chromadb\n HAS_CHROMADB = True\nexcept ImportError:\n HAS_CHROMADB = False\n\ndef search_vectors(query: str):\n if not HAS_CHROMADB:\n return {{\"warning\": \"ChromaDB not installed\", \"results\": []}}\n # ... actual implementation"}
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{"issue": 592, "domain": "testing", "problem": "Use tmp_path fixture for file-based tests (variant 1)", "solution": "import pytest\nfrom pathlib import Path\n\ndef test_file_write_creates_file(tmp_path):\n target = tmp_path / \"output.txt\"\n target.write_text(\"hello\")\n assert target.exists()\n assert target.read_text() == \"hello\""}
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{"issue": 592, "domain": "testing", "problem": "Test agent loop behavior with mocked API responses (variant 96) (variant 71)", "solution": "import pytest\nfrom run_agent import AIAgent\n\ndef test_agent_runs_tool_call(monkeypatch):\n agent = AIAgent(model=\"test\", max_iterations=5)\n\n class MockResponse:\n tool_calls = [MockToolCall(\"read_file\", {{\"path\": \"/tmp/test.txt\"}})]\n content = None\n\n monkeypatch.setattr(agent, \"_call_api\", lambda **kw: MockResponse())\n result = agent.chat(\"Read the file\")\n assert result is not None"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 5)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 29) (variant 58) (variant 46) (variant 71)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 33) (variant 8) (variant 48)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 56)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 18) (variant 93)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 8) (variant 79)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "utility", "problem": "Switch model mid-session with /model slash command (variant 57)", "solution": "# In cli.py or gateway/run.py\nfrom hermes_cli.model_switch import switch_model\n\nnew_model = switch_model(\"openai/gpt-4o\")\nprint(f\"Switched to {{new_model}}\")"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 56) (variant 80) (variant 30) (variant 70) (variant 81) (variant 16) (variant 84)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "prompt_building", "problem": "Build a few-shot prompt with examples for consistent JSON output (variant 30) (variant 4)", "solution": "system_prompt = \"\"\"You are a structured data extractor.\n\nReturn valid JSON only. No markdown, no explanation.\n\nExamples:\nInput: \"Alice is 30 years old\"\nOutput: {{\"name\": \"Alice\", \"age\": 30}}\n\nInput: \"Bob works as an engineer in Seattle\"\nOutput: {{\"name\": \"Bob\", \"job\": \"engineer\", \"location\": \"Seattle\"}}\n\nNow extract from the user input.\"\"\"\n\nmessages = [\n {{\"role\": \"system\", \"content\": system_prompt}},\n {{\"role\": \"user\", \"content\": \"Carol is a doctor in Boston, age 45\"}},\n]"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 69) (variant 85) (variant 98) (variant 13)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 29) (variant 58)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 81) (variant 7)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 50 iterations (variant 88)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 30 iterations (variant 92)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "tool_routing", "problem": "Check if a tool is available before calling it (variant 32) (variant 86) (variant 75) (variant 21) (variant 10)", "solution": "from tools.registry import registry\n\ntool_name = \"web_search\"\nif registry.is_available(tool_name):\n schema = registry.get_schema(tool_name)\n result = registry.call(tool_name, {{\"query\": \"Python asyncio\"}}, task_id=\"abc\")\nelse:\n result = f\"Tool {{tool_name}} is not available (missing requirements)\""}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 43) (variant 70) (variant 55) (variant 79) (variant 34)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 43)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"anthropic/claude-sonnet-4\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 53) (variant 34) (variant 80)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "error_handling", "problem": "Catch and log tool execution errors without crashing the agent loop (variant 39) (variant 71) (variant 10) (variant 86)", "solution": "import json\nimport traceback\n\ntry:\n result = handle_function_call(tool_call.name, tool_call.args)\nexcept Exception as e:\n tb = traceback.format_exc()\n result = json.dumps({{\n \"error\": str(e),\n \"traceback\": tb,\n }})"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 30 iterations (variant 36)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 71) (variant 62)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 18) (variant 64)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "utility", "problem": "Validate a dangerous command before execution using approval.py", "solution": "from tools.approval import detect_dangerous_command\n\ncmd = \"rm -rf /important/data\"\nresult = detect_dangerous_command(cmd)\nif result[\"dangerous\"]:\n print(f\"Approval required: {{result['reason']}}\")\n # Prompt user for approval\nelse:\n print(\"Safe to execute\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 50) (variant 50)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "config", "problem": "Bump config schema version and add migration for existing users (variant 94)", "solution": "# In hermes_cli/config.py\n\nDEFAULT_CONFIG = {{\n \"_config_version\": 6, # bumped from 5\n \"model\": \"anthropic/claude-sonnet-4\",\n \"max_iterations\": 50,\n \"new_feature\": True, # added\n}}\n\ndef migrate_config(raw: dict) -> dict:\n version = raw.get(\"_config_version\", 0)\n if version < 6:\n raw[\"new_feature\"] = DEFAULT_CONFIG[\"new_feature\"]\n raw[\"_config_version\"] = 6\n return raw"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 43)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "prompt_building", "problem": "Build a system prompt with skills injected as slash commands (variant 5)", "solution": "from agent.prompt_builder import PromptBuilder\nfrom agent.skill_commands import scan_skills\n\nbuilder = PromptBuilder()\nskills = scan_skills(\"~/.hermes/skills/\")\n\nsystem_prompt = builder.build(\n base_prompt=\"You are a helpful coding assistant.\",\n skills=skills,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n user_preferences={{\"language\": \"Python\", \"style\": \"concise\"}},\n)\nprint(system_prompt)"}
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{"issue": 592, "domain": "testing", "problem": "Test agent loop behavior with mocked API responses (variant 87) (variant 37) (variant 42) (variant 1)", "solution": "import pytest\nfrom run_agent import AIAgent\n\ndef test_agent_runs_tool_call(monkeypatch):\n agent = AIAgent(model=\"test\", max_iterations=5)\n\n class MockResponse:\n tool_calls = [MockToolCall(\"read_file\", {{\"path\": \"/tmp/test.txt\"}})]\n content = None\n\n monkeypatch.setattr(agent, \"_call_api\", lambda **kw: MockResponse())\n result = agent.chat(\"Read the file\")\n assert result is not None"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 61) (variant 98) (variant 61) (variant 29) (variant 84)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 6) (variant 8) (variant 45)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 70) (variant 84) (variant 1) (variant 94) (variant 28)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 83)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 50 iterations", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "tool_routing", "problem": "Check if a tool is available before calling it (variant 32) (variant 86) (variant 26)", "solution": "from tools.registry import registry\n\ntool_name = \"web_search\"\nif registry.is_available(tool_name):\n schema = registry.get_schema(tool_name)\n result = registry.call(tool_name, {{\"query\": \"Python asyncio\"}}, task_id=\"abc\")\nelse:\n result = f\"Tool {{tool_name}} is not available (missing requirements)\""}
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{"issue": 592, "domain": "prompt_building", "problem": "Build a few-shot prompt with examples for consistent JSON output (variant 30) (variant 4) (variant 12)", "solution": "system_prompt = \"\"\"You are a structured data extractor.\n\nReturn valid JSON only. No markdown, no explanation.\n\nExamples:\nInput: \"Alice is 30 years old\"\nOutput: {{\"name\": \"Alice\", \"age\": 30}}\n\nInput: \"Bob works as an engineer in Seattle\"\nOutput: {{\"name\": \"Bob\", \"job\": \"engineer\", \"location\": \"Seattle\"}}\n\nNow extract from the user input.\"\"\"\n\nmessages = [\n {{\"role\": \"system\", \"content\": system_prompt}},\n {{\"role\": \"user\", \"content\": \"Carol is a doctor in Boston, age 45\"}},\n]"}
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{"issue": 592, "domain": "utility", "problem": "Run a subagent delegation with timeout and context isolation (variant 10) (variant 5)", "solution": "from tools.delegate_tool import delegate_task\n\nresult = delegate_task(\n goal=\"Debug this failing test\",\n context=\"test_file.py line 42 raises AssertionError\",\n max_iterations=20,\n toolsets=[\"terminal\", \"file\"],\n)\nprint(result[\"summary\"])"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 23)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 61) (variant 98) (variant 61) (variant 29) (variant 69) (variant 7)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 6) (variant 8) (variant 44) (variant 8)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 33) (variant 8) (variant 1) (variant 24) (variant 6)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 56) (variant 49) (variant 56)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "prompt_building", "problem": "Build a system prompt with skills injected as slash commands (variant 5) (variant 74) (variant 74)", "solution": "from agent.prompt_builder import PromptBuilder\nfrom agent.skill_commands import scan_skills\n\nbuilder = PromptBuilder()\nskills = scan_skills(\"~/.hermes/skills/\")\n\nsystem_prompt = builder.build(\n base_prompt=\"You are a helpful coding assistant.\",\n skills=skills,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n user_preferences={{\"language\": \"Python\", \"style\": \"concise\"}},\n)\nprint(system_prompt)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 50 iterations (variant 28) (variant 43)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 60) (variant 97) (variant 61) (variant 83)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "testing", "problem": "Test agent loop behavior with mocked API responses (variant 96) (variant 23)", "solution": "import pytest\nfrom run_agent import AIAgent\n\ndef test_agent_runs_tool_call(monkeypatch):\n agent = AIAgent(model=\"test\", max_iterations=5)\n\n class MockResponse:\n tool_calls = [MockToolCall(\"read_file\", {{\"path\": \"/tmp/test.txt\"}})]\n content = None\n\n monkeypatch.setattr(agent, \"_call_api\", lambda **kw: MockResponse())\n result = agent.chat(\"Read the file\")\n assert result is not None"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 43) (variant 27)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Resolve provider credentials from ~/.hermes/.env (variant 15) (variant 38) (variant 90) (variant 87)", "solution": "from hermes_cli.auth import resolve_credentials\n\ncreds = resolve_credentials(\"anthropic\")\nprint(creds[\"api_key\"][:8] + \"...\") # masked"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 30 iterations (variant 42) (variant 47) (variant 63) (variant 94)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 50) (variant 66) (variant 53) (variant 73) (variant 11)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "error_handling", "problem": "Handle missing optional dependencies with graceful degradation (variant 40) (variant 40)", "solution": "try:\n import chromadb\n HAS_CHROMADB = True\nexcept ImportError:\n HAS_CHROMADB = False\n\ndef search_vectors(query: str):\n if not HAS_CHROMADB:\n return {{\"warning\": \"ChromaDB not installed\", \"results\": []}}\n # ... actual implementation"}
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{"issue": 592, "domain": "tool_routing", "problem": "Check if a tool is available before calling it (variant 32) (variant 86) (variant 73) (variant 33)", "solution": "from tools.registry import registry\n\ntool_name = \"web_search\"\nif registry.is_available(tool_name):\n schema = registry.get_schema(tool_name)\n result = registry.call(tool_name, {{\"query\": \"Python asyncio\"}}, task_id=\"abc\")\nelse:\n result = f\"Tool {{tool_name}} is not available (missing requirements)\""}
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{"issue": 592, "domain": "tool_routing", "problem": "Discover all builtin tools and build tool schemas for the API call (variant 52) (variant 14) (variant 19)", "solution": "from model_tools import discover_builtin_tools\nfrom tools.registry import registry\n\n# Auto-discover all registered tools\ndiscover_builtin_tools()\n\n# Collect schemas for all available tools\ntool_schemas = [registry.get_schema(name) for name in registry.list_available()]\n\n# Filter by enabled toolsets\nenabled = [\"web\", \"terminal\", \"file\"]\ntool_schemas = [\n s for s in tool_schemas\n if registry.get_toolset(s[\"name\"]) in enabled\n]"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 29) (variant 32) (variant 26) (variant 47) (variant 95) (variant 13)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 60) (variant 97)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 15)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 11) (variant 15) (variant 92) (variant 47) (variant 66) (variant 21)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 65) (variant 63) (variant 2) (variant 23) (variant 65)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "error_handling", "problem": "Handle missing optional dependencies with graceful degradation (variant 12) (variant 17) (variant 71) (variant 35)", "solution": "try:\n import chromadb\n HAS_CHROMADB = True\nexcept ImportError:\n HAS_CHROMADB = False\n\ndef search_vectors(query: str):\n if not HAS_CHROMADB:\n return {{\"warning\": \"ChromaDB not installed\", \"results\": []}}\n # ... actual implementation"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 16) (variant 4) (variant 76)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 60) (variant 97) (variant 41) (variant 65) (variant 39)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "utility", "problem": "Load user config from ~/.hermes/config.yaml with defaults fallback (variant 81)", "solution": "from hermes_cli.config import load_cli_config, DEFAULT_CONFIG\n\nconfig = load_cli_config()\nmodel = config.get(\"model\", DEFAULT_CONFIG[\"model\"])\nmax_iters = config.get(\"max_iterations\", DEFAULT_CONFIG[\"max_iterations\"])"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 24) (variant 90)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 19) (variant 27)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 56) (variant 72) (variant 18)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 83) (variant 14) (variant 15)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 60) (variant 32) (variant 68)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 71) (variant 76) (variant 75)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 60) (variant 97) (variant 41) (variant 67) (variant 36)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "error_handling", "problem": "Catch and log tool execution errors without crashing the agent loop (variant 39) (variant 71) (variant 37)", "solution": "import json\nimport traceback\n\ntry:\n result = handle_function_call(tool_call.name, tool_call.args)\nexcept Exception as e:\n tb = traceback.format_exc()\n result = json.dumps({{\n \"error\": str(e),\n \"traceback\": tb,\n }})"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 37) (variant 64) (variant 83) (variant 75) (variant 72)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29) (variant 21) (variant 42) (variant 86) (variant 78) (variant 32)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 33)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 29) (variant 32) (variant 44)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 29) (variant 32) (variant 44) (variant 96)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 50 iterations (variant 28) (variant 43) (variant 11)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 60) (variant 97) (variant 41) (variant 67)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "error_handling", "problem": "Handle missing optional dependencies with graceful degradation (variant 78)", "solution": "try:\n import chromadb\n HAS_CHROMADB = True\nexcept ImportError:\n HAS_CHROMADB = False\n\ndef search_vectors(query: str):\n if not HAS_CHROMADB:\n return {{\"warning\": \"ChromaDB not installed\", \"results\": []}}\n # ... actual implementation"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 29) (variant 32) (variant 26) (variant 47)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "testing", "problem": "Test agent loop behavior with mocked API responses (variant 87) (variant 37) (variant 76)", "solution": "import pytest\nfrom run_agent import AIAgent\n\ndef test_agent_runs_tool_call(monkeypatch):\n agent = AIAgent(model=\"test\", max_iterations=5)\n\n class MockResponse:\n tool_calls = [MockToolCall(\"read_file\", {{\"path\": \"/tmp/test.txt\"}})]\n content = None\n\n monkeypatch.setattr(agent, \"_call_api\", lambda **kw: MockResponse())\n result = agent.chat(\"Read the file\")\n assert result is not None"}
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{"issue": 592, "domain": "utility", "problem": "Run a subagent delegation with timeout and context isolation (variant 10) (variant 28)", "solution": "from tools.delegate_tool import delegate_task\n\nresult = delegate_task(\n goal=\"Debug this failing test\",\n context=\"test_file.py line 42 raises AssertionError\",\n max_iterations=20,\n toolsets=[\"terminal\", \"file\"],\n)\nprint(result[\"summary\"])"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 43) (variant 70) (variant 55) (variant 79) (variant 34) (variant 19)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 90 iterations (variant 67) (variant 36)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 61) (variant 98) (variant 61) (variant 73) (variant 76) (variant 42)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 11) (variant 77)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 50 iterations (variant 28) (variant 97)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 2) (variant 7) (variant 11)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 31)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 90 iterations (variant 30) (variant 44) (variant 53) (variant 97)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 19) (variant 49) (variant 64)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 30 iterations (variant 42) (variant 47) (variant 80)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 11) (variant 17) (variant 16) (variant 27)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "testing", "problem": "Test agent loop behavior with mocked API responses (variant 77) (variant 53) (variant 81)", "solution": "import pytest\nfrom run_agent import AIAgent\n\ndef test_agent_runs_tool_call(monkeypatch):\n agent = AIAgent(model=\"test\", max_iterations=5)\n\n class MockResponse:\n tool_calls = [MockToolCall(\"read_file\", {{\"path\": \"/tmp/test.txt\"}})]\n content = None\n\n monkeypatch.setattr(agent, \"_call_api\", lambda **kw: MockResponse())\n result = agent.chat(\"Read the file\")\n assert result is not None"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 25)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 60) (variant 32) (variant 72) (variant 46)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 46)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 93) (variant 7) (variant 44)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"anthropic/claude-sonnet-4\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 90 iterations (variant 77) (variant 38) (variant 74) (variant 45) (variant 72) (variant 85)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 50 iterations (variant 28) (variant 97) (variant 85) (variant 67)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 43) (variant 44) (variant 33) (variant 89)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "error_handling", "problem": "Catch and log tool execution errors without crashing the agent loop (variant 39) (variant 71) (variant 10) (variant 17)", "solution": "import json\nimport traceback\n\ntry:\n result = handle_function_call(tool_call.name, tool_call.args)\nexcept Exception as e:\n tb = traceback.format_exc()\n result = json.dumps({{\n \"error\": str(e),\n \"traceback\": tb,\n }})"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 61) (variant 98) (variant 61) (variant 73)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "error_handling", "problem": "Detect and recover from infinite tool call loops (variant 9)", "solution": "# In run_conversation loop\nseen_calls = set()\nfor tool_call in response.tool_calls:\n call_key = (tool_call.name, json.dumps(tool_call.args, sort_keys=True))\n if call_key in seen_calls:\n messages.append({{\n \"role\": \"tool\",\n \"content\": \"Error: Repeated identical tool call detected. Try a different approach.\",\n }})\n continue\n seen_calls.add(call_key)\n result = handle_function_call(tool_call.name, tool_call.args)\n messages.append(tool_result_message(result))"}
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{"issue": 592, "domain": "config", "problem": "Bump config schema version and add migration for existing users (variant 76) (variant 38) (variant 34) (variant 66)", "solution": "# In hermes_cli/config.py\n\nDEFAULT_CONFIG = {{\n \"_config_version\": 6, # bumped from 5\n \"model\": \"anthropic/claude-sonnet-4\",\n \"max_iterations\": 50,\n \"new_feature\": True, # added\n}}\n\ndef migrate_config(raw: dict) -> dict:\n version = raw.get(\"_config_version\", 0)\n if version < 6:\n raw[\"new_feature\"] = DEFAULT_CONFIG[\"new_feature\"]\n raw[\"_config_version\"] = 6\n return raw"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 24) (variant 21)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "testing", "problem": "Test agent loop behavior with mocked API responses (variant 96) (variant 23) (variant 91)", "solution": "import pytest\nfrom run_agent import AIAgent\n\ndef test_agent_runs_tool_call(monkeypatch):\n agent = AIAgent(model=\"test\", max_iterations=5)\n\n class MockResponse:\n tool_calls = [MockToolCall(\"read_file\", {{\"path\": \"/tmp/test.txt\"}})]\n content = None\n\n monkeypatch.setattr(agent, \"_call_api\", lambda **kw: MockResponse())\n result = agent.chat(\"Read the file\")\n assert result is not None"}
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{"issue": 592, "domain": "error_handling", "problem": "Validate JSON output from model before parsing (variant 31) (variant 43)", "solution": "import json\n\ntry:\n data = json.loads(model_output)\nexcept json.JSONDecodeError:\n # Try to extract JSON from markdown code block\n import re\n match = re.search(r'```json\\n(.*?)\\n```', model_output, re.DOTALL)\n if match:\n data = json.loads(match.group(1))\n else:\n raise ValueError(\"Model did not return valid JSON\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 90 iterations (variant 30) (variant 44) (variant 5) (variant 96) (variant 64)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "error_handling", "problem": "Catch and log tool execution errors without crashing the agent loop (variant 68) (variant 96) (variant 82) (variant 98)", "solution": "import json\nimport traceback\n\ntry:\n result = handle_function_call(tool_call.name, tool_call.args)\nexcept Exception as e:\n tb = traceback.format_exc()\n result = json.dumps({{\n \"error\": str(e),\n \"traceback\": tb,\n }})"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 20) (variant 46)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "utility", "problem": "Run a subagent delegation with timeout and context isolation (variant 10) (variant 28) (variant 19)", "solution": "from tools.delegate_tool import delegate_task\n\nresult = delegate_task(\n goal=\"Debug this failing test\",\n context=\"test_file.py line 42 raises AssertionError\",\n max_iterations=20,\n toolsets=[\"terminal\", \"file\"],\n)\nprint(result[\"summary\"])"}
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{"issue": 592, "domain": "utility", "problem": "Poll a background process for completion with progress tracking (variant 55)", "solution": "from tools.process_registry import ProcessRegistry\n\nregistry = ProcessRegistry()\nsession_id = registry.start(\"long_task.sh\", background=True)\n\nwhile True:\n status = registry.poll(session_id)\n if status[\"done\"]:\n print(f\"Completed with exit code {{status['exit_code']}}\")\n break\n print(f\"Progress: {{status['lines']}} lines output\")\n time.sleep(1)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 46) (variant 51) (variant 16)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 43) (variant 70) (variant 55) (variant 79) (variant 47)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "error_handling", "problem": "Handle missing optional dependencies with graceful degradation", "solution": "try:\n import chromadb\n HAS_CHROMADB = True\nexcept ImportError:\n HAS_CHROMADB = False\n\ndef search_vectors(query: str):\n if not HAS_CHROMADB:\n return {{\"warning\": \"ChromaDB not installed\", \"results\": []}}\n # ... actual implementation"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 60) (variant 32) (variant 78)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 17) (variant 99) (variant 36)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 91)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29) (variant 21)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "prompt_building", "problem": "Format a tool result message for OpenAI-compatible chat API (variant 3) (variant 88) (variant 45)", "solution": "def tool_result_message(result: str, tool_call_id: str = \"\") -> dict:\n return {{\n \"role\": \"tool\",\n \"tool_call_id\": tool_call_id,\n \"content\": result if isinstance(result, str) else json.dumps(result),\n }}\n\nmessages.append(tool_result_message(\"42 files found\", tool_call_id=\"call_abc\"))"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 18) (variant 9) (variant 21)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 60) (variant 32)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 11)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 83) (variant 5)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 90 iterations (variant 30) (variant 44)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 70) (variant 84) (variant 34) (variant 93)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 33) (variant 8) (variant 20) (variant 2) (variant 57)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "error_handling", "problem": "Catch and log tool execution errors without crashing the agent loop (variant 39) (variant 71) (variant 60)", "solution": "import json\nimport traceback\n\ntry:\n result = handle_function_call(tool_call.name, tool_call.args)\nexcept Exception as e:\n tb = traceback.format_exc()\n result = json.dumps({{\n \"error\": str(e),\n \"traceback\": tb,\n }})"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 11) (variant 45)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 2) (variant 62)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 23) (variant 59) (variant 51)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Resolve provider credentials from ~/.hermes/.env (variant 15) (variant 38) (variant 90) (variant 21) (variant 100)", "solution": "from hermes_cli.auth import resolve_credentials\n\ncreds = resolve_credentials(\"anthropic\")\nprint(creds[\"api_key\"][:8] + \"...\") # masked"}
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{"issue": 592, "domain": "utility", "problem": "Save a trajectory to disk for later training data extraction", "solution": "from agent.trajectory import save_trajectory\nimport json\n\ntrajectory = {{\n \"session_id\": session_id,\n \"messages\": messages,\n \"model\": model,\n \"tools_called\": [tc.name for tc in tool_calls],\n}}\n\npath = save_trajectory(trajectory, directory=\"~/.hermes/trajectories/\")\nprint(f\"Saved to {{path}}\")"}
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{"issue": 592, "domain": "prompt_building", "problem": "Build a few-shot prompt with examples for consistent JSON output (variant 91)", "solution": "system_prompt = \"\"\"You are a structured data extractor.\n\nReturn valid JSON only. No markdown, no explanation.\n\nExamples:\nInput: \"Alice is 30 years old\"\nOutput: {{\"name\": \"Alice\", \"age\": 30}}\n\nInput: \"Bob works as an engineer in Seattle\"\nOutput: {{\"name\": \"Bob\", \"job\": \"engineer\", \"location\": \"Seattle\"}}\n\nNow extract from the user input.\"\"\"\n\nmessages = [\n {{\"role\": \"system\", \"content\": system_prompt}},\n {{\"role\": \"user\", \"content\": \"Carol is a doctor in Boston, age 45\"}},\n]"}
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{"issue": 592, "domain": "error_handling", "problem": "Handle missing optional dependencies with graceful degradation (variant 40) (variant 40) (variant 11)", "solution": "try:\n import chromadb\n HAS_CHROMADB = True\nexcept ImportError:\n HAS_CHROMADB = False\n\ndef search_vectors(query: str):\n if not HAS_CHROMADB:\n return {{\"warning\": \"ChromaDB not installed\", \"results\": []}}\n # ... actual implementation"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 51) (variant 60)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 5) (variant 42) (variant 87) (variant 57)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 95) (variant 75)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 69) (variant 6) (variant 78)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 29)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 71) (variant 76) (variant 75) (variant 32)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 16) (variant 4)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 43) (variant 70) (variant 55) (variant 79)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 90 iterations (variant 30) (variant 44) (variant 5) (variant 96)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "error_handling", "problem": "Handle missing optional dependencies with graceful degradation (variant 40) (variant 40) (variant 51)", "solution": "try:\n import chromadb\n HAS_CHROMADB = True\nexcept ImportError:\n HAS_CHROMADB = False\n\ndef search_vectors(query: str):\n if not HAS_CHROMADB:\n return {{\"warning\": \"ChromaDB not installed\", \"results\": []}}\n # ... actual implementation"}
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{"issue": 592, "domain": "prompt_building", "problem": "Format a tool result message for OpenAI-compatible chat API (variant 3) (variant 88) (variant 3)", "solution": "def tool_result_message(result: str, tool_call_id: str = \"\") -> dict:\n return {{\n \"role\": \"tool\",\n \"tool_call_id\": tool_call_id,\n \"content\": result if isinstance(result, str) else json.dumps(result),\n }}\n\nmessages.append(tool_result_message(\"42 files found\", tool_call_id=\"call_abc\"))"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 90 iterations (variant 30) (variant 28)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 94) (variant 45)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "tool_routing", "problem": "Discover all builtin tools and build tool schemas for the API call (variant 52) (variant 14) (variant 19) (variant 98)", "solution": "from model_tools import discover_builtin_tools\nfrom tools.registry import registry\n\n# Auto-discover all registered tools\ndiscover_builtin_tools()\n\n# Collect schemas for all available tools\ntool_schemas = [registry.get_schema(name) for name in registry.list_available()]\n\n# Filter by enabled toolsets\nenabled = [\"web\", \"terminal\", \"file\"]\ntool_schemas = [\n s for s in tool_schemas\n if registry.get_toolset(s[\"name\"]) in enabled\n]"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 26) (variant 54)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 40)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"anthropic/claude-sonnet-4\", max_iterations=50)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 33) (variant 8)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 90 iterations (variant 88)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 90 iterations (variant 77) (variant 38)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 14)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 69) (variant 85) (variant 98) (variant 13) (variant 100)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 43) (variant 16) (variant 33)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "error_handling", "problem": "Catch and log tool execution errors without crashing the agent loop (variant 39) (variant 71) (variant 10)", "solution": "import json\nimport traceback\n\ntry:\n result = handle_function_call(tool_call.name, tool_call.args)\nexcept Exception as e:\n tb = traceback.format_exc()\n result = json.dumps({{\n \"error\": str(e),\n \"traceback\": tb,\n }})"}
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{"issue": 592, "domain": "utility", "problem": "Load user config from ~/.hermes/config.yaml with defaults fallback (variant 20) (variant 29)", "solution": "from hermes_cli.config import load_cli_config, DEFAULT_CONFIG\n\nconfig = load_cli_config()\nmodel = config.get(\"model\", DEFAULT_CONFIG[\"model\"])\nmax_iters = config.get(\"max_iterations\", DEFAULT_CONFIG[\"max_iterations\"])"}
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{"issue": 592, "domain": "utility", "problem": "Poll a background process for completion with progress tracking (variant 55) (variant 35) (variant 30)", "solution": "from tools.process_registry import ProcessRegistry\n\nregistry = ProcessRegistry()\nsession_id = registry.start(\"long_task.sh\", background=True)\n\nwhile True:\n status = registry.poll(session_id)\n if status[\"done\"]:\n print(f\"Completed with exit code {{status['exit_code']}}\")\n break\n print(f\"Progress: {{status['lines']}} lines output\")\n time.sleep(1)"}
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{"issue": 592, "domain": "utility", "problem": "Run a subagent delegation with timeout and context isolation (variant 10) (variant 5) (variant 19)", "solution": "from tools.delegate_tool import delegate_task\n\nresult = delegate_task(\n goal=\"Debug this failing test\",\n context=\"test_file.py line 42 raises AssertionError\",\n max_iterations=20,\n toolsets=[\"terminal\", \"file\"],\n)\nprint(result[\"summary\"])"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 18) (variant 9)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 24) (variant 12)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 43) (variant 44) (variant 52)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 11) (variant 55)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "prompt_building", "problem": "Add a reasoning block to an assistant message for chain-of-thought (variant 45)", "solution": "assistant_msg = {{\n \"role\": \"assistant\",\n \"content\": \"The answer is 42.\",\n \"reasoning\": \"I calculated this by summing the factors: 1+2+3+4+6+7+12+14+21+28 = 96. Wait, let me recheck... Actually 42 is the answer to life, the universe, and everything.\",\n}}\n\nmessages.append(assistant_msg)"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 69) (variant 85) (variant 44) (variant 55) (variant 68)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 9) (variant 19)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "error_handling", "problem": "Validate JSON output from model before parsing (variant 100)", "solution": "import json\n\ntry:\n data = json.loads(model_output)\nexcept json.JSONDecodeError:\n # Try to extract JSON from markdown code block\n import re\n match = re.search(r'```json\\n(.*?)\\n```', model_output, re.DOTALL)\n if match:\n data = json.loads(match.group(1))\n else:\n raise ValueError(\"Model did not return valid JSON\")"}
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{"issue": 592, "domain": "utility", "problem": "Poll a background process for completion with progress tracking (variant 21) (variant 10)", "solution": "from tools.process_registry import ProcessRegistry\n\nregistry = ProcessRegistry()\nsession_id = registry.start(\"long_task.sh\", background=True)\n\nwhile True:\n status = registry.poll(session_id)\n if status[\"done\"]:\n print(f\"Completed with exit code {{status['exit_code']}}\")\n break\n print(f\"Progress: {{status['lines']}} lines output\")\n time.sleep(1)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 43) (variant 44) (variant 41) (variant 21) (variant 12) (variant 35)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 49) (variant 19)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 46) (variant 51)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 17) (variant 82) (variant 60)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 29) (variant 73) (variant 61) (variant 95) (variant 8)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 15) (variant 10)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 60) (variant 97) (variant 61) (variant 4) (variant 9)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "config", "problem": "Bump config schema version and add migration for existing users (variant 18)", "solution": "# In hermes_cli/config.py\n\nDEFAULT_CONFIG = {{\n \"_config_version\": 6, # bumped from 5\n \"model\": \"anthropic/claude-sonnet-4\",\n \"max_iterations\": 50,\n \"new_feature\": True, # added\n}}\n\ndef migrate_config(raw: dict) -> dict:\n version = raw.get(\"_config_version\", 0)\n if version < 6:\n raw[\"new_feature\"] = DEFAULT_CONFIG[\"new_feature\"]\n raw[\"_config_version\"] = 6\n return raw"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 11) (variant 45) (variant 36)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "utility", "problem": "Poll a background process for completion with progress tracking (variant 55) (variant 35)", "solution": "from tools.process_registry import ProcessRegistry\n\nregistry = ProcessRegistry()\nsession_id = registry.start(\"long_task.sh\", background=True)\n\nwhile True:\n status = registry.poll(session_id)\n if status[\"done\"]:\n print(f\"Completed with exit code {{status['exit_code']}}\")\n break\n print(f\"Progress: {{status['lines']}} lines output\")\n time.sleep(1)"}
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{"issue": 592, "domain": "prompt_building", "problem": "Build a few-shot prompt with examples for consistent JSON output", "solution": "system_prompt = \"\"\"You are a structured data extractor.\n\nReturn valid JSON only. No markdown, no explanation.\n\nExamples:\nInput: \"Alice is 30 years old\"\nOutput: {{\"name\": \"Alice\", \"age\": 30}}\n\nInput: \"Bob works as an engineer in Seattle\"\nOutput: {{\"name\": \"Bob\", \"job\": \"engineer\", \"location\": \"Seattle\"}}\n\nNow extract from the user input.\"\"\"\n\nmessages = [\n {{\"role\": \"system\", \"content\": system_prompt}},\n {{\"role\": \"user\", \"content\": \"Carol is a doctor in Boston, age 45\"}},\n]"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 82) (variant 22)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=50)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 75)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 91) (variant 88)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "utility", "problem": "Poll a background process for completion with progress tracking (variant 21)", "solution": "from tools.process_registry import ProcessRegistry\n\nregistry = ProcessRegistry()\nsession_id = registry.start(\"long_task.sh\", background=True)\n\nwhile True:\n status = registry.poll(session_id)\n if status[\"done\"]:\n print(f\"Completed with exit code {{status['exit_code']}}\")\n break\n print(f\"Progress: {{status['lines']}} lines output\")\n time.sleep(1)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 33) (variant 84) (variant 66)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 24) (variant 90) (variant 63)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "utility", "problem": "Save a trajectory to disk for later training data extraction (variant 8)", "solution": "from agent.trajectory import save_trajectory\nimport json\n\ntrajectory = {{\n \"session_id\": session_id,\n \"messages\": messages,\n \"model\": model,\n \"tools_called\": [tc.name for tc in tool_calls],\n}}\n\npath = save_trajectory(trajectory, directory=\"~/.hermes/trajectories/\")\nprint(f\"Saved to {{path}}\")"}
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{"issue": 592, "domain": "utility", "problem": "Run a subagent delegation with timeout and context isolation (variant 22) (variant 41)", "solution": "from tools.delegate_tool import delegate_task\n\nresult = delegate_task(\n goal=\"Debug this failing test\",\n context=\"test_file.py line 42 raises AssertionError\",\n max_iterations=20,\n toolsets=[\"terminal\", \"file\"],\n)\nprint(result[\"summary\"])"}
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{"issue": 592, "domain": "error_handling", "problem": "Handle missing optional dependencies with graceful degradation (variant 12) (variant 17) (variant 71) (variant 35) (variant 49) (variant 95)", "solution": "try:\n import chromadb\n HAS_CHROMADB = True\nexcept ImportError:\n HAS_CHROMADB = False\n\ndef search_vectors(query: str):\n if not HAS_CHROMADB:\n return {{\"warning\": \"ChromaDB not installed\", \"results\": []}}\n # ... actual implementation"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 14) (variant 14)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 71) (variant 82)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 43) (variant 70) (variant 23)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "error_handling", "problem": "Handle missing optional dependencies with graceful degradation (variant 12) (variant 17) (variant 71)", "solution": "try:\n import chromadb\n HAS_CHROMADB = True\nexcept ImportError:\n HAS_CHROMADB = False\n\ndef search_vectors(query: str):\n if not HAS_CHROMADB:\n return {{\"warning\": \"ChromaDB not installed\", \"results\": []}}\n # ... actual implementation"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 30 iterations (variant 91)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 9) (variant 22) (variant 73)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 56) (variant 80) (variant 30) (variant 31)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 30 iterations (variant 42) (variant 47) (variant 80) (variant 17)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "error_handling", "problem": "Validate JSON output from model before parsing (variant 55) (variant 43) (variant 79) (variant 31)", "solution": "import json\n\ntry:\n data = json.loads(model_output)\nexcept json.JSONDecodeError:\n # Try to extract JSON from markdown code block\n import re\n match = re.search(r'```json\\n(.*?)\\n```', model_output, re.DOTALL)\n if match:\n data = json.loads(match.group(1))\n else:\n raise ValueError(\"Model did not return valid JSON\")"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 60)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "utility", "problem": "Switch model mid-session with /model slash command (variant 57) (variant 90)", "solution": "# In cli.py or gateway/run.py\nfrom hermes_cli.model_switch import switch_model\n\nnew_model = switch_model(\"openai/gpt-4o\")\nprint(f\"Switched to {{new_model}}\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 23) (variant 70)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 16) (variant 67) (variant 50) (variant 92) (variant 14)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "utility", "problem": "Resolve provider credentials from ~/.hermes/.env (variant 15) (variant 1) (variant 57)", "solution": "from hermes_cli.auth import resolve_credentials\n\ncreds = resolve_credentials(\"anthropic\")\nprint(creds[\"api_key\"][:8] + \"...\") # masked"}
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{"issue": 592, "domain": "agent_loop", "problem": "Handle a tool call result and append it to the conversation messages (variant 86) (variant 31)", "solution": "from model_tools import handle_function_call\n\ntool_call = response.tool_calls[0]\nresult = handle_function_call(\n tool_call.name,\n tool_call.args,\n task_id=\"task-123\"\n)\nmessages.append({{\n \"role\": \"tool\",\n \"tool_call_id\": tool_call.id,\n \"content\": result,\n}})"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 16)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "error_handling", "problem": "Handle missing optional dependencies with graceful degradation (variant 12) (variant 17) (variant 83)", "solution": "try:\n import chromadb\n HAS_CHROMADB = True\nexcept ImportError:\n HAS_CHROMADB = False\n\ndef search_vectors(query: str):\n if not HAS_CHROMADB:\n return {{\"warning\": \"ChromaDB not installed\", \"results\": []}}\n # ... actual implementation"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 14) (variant 14) (variant 12)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 11) (variant 17) (variant 16)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 36) (variant 2)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "testing", "problem": "Use tmp_path fixture for file-based tests", "solution": "import pytest\nfrom pathlib import Path\n\ndef test_file_write_creates_file(tmp_path):\n target = tmp_path / \"output.txt\"\n target.write_text(\"hello\")\n assert target.exists()\n assert target.read_text() == \"hello\""}
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{"issue": 592, "domain": "error_handling", "problem": "Detect and recover from infinite tool call loops (variant 100)", "solution": "# In run_conversation loop\nseen_calls = set()\nfor tool_call in response.tool_calls:\n call_key = (tool_call.name, json.dumps(tool_call.args, sort_keys=True))\n if call_key in seen_calls:\n messages.append({{\n \"role\": \"tool\",\n \"content\": \"Error: Repeated identical tool call detected. Try a different approach.\",\n }})\n continue\n seen_calls.add(call_key)\n result = handle_function_call(tool_call.name, tool_call.args)\n messages.append(tool_result_message(result))"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 50 iterations (variant 4) (variant 3)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "tool_routing", "problem": "Check if a tool is available before calling it (variant 32) (variant 86) (variant 26) (variant 57)", "solution": "from tools.registry import registry\n\ntool_name = \"web_search\"\nif registry.is_available(tool_name):\n schema = registry.get_schema(tool_name)\n result = registry.call(tool_name, {{\"query\": \"Python asyncio\"}}, task_id=\"abc\")\nelse:\n result = f\"Tool {{tool_name}} is not available (missing requirements)\""}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 56) (variant 80) (variant 30) (variant 11)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 50 iterations (variant 12)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "tool_routing", "problem": "Check if a tool is available before calling it (variant 32) (variant 86) (variant 75) (variant 76) (variant 59)", "solution": "from tools.registry import registry\n\ntool_name = \"web_search\"\nif registry.is_available(tool_name):\n schema = registry.get_schema(tool_name)\n result = registry.call(tool_name, {{\"query\": \"Python asyncio\"}}, task_id=\"abc\")\nelse:\n result = f\"Tool {{tool_name}} is not available (missing requirements)\""}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 24) (variant 38)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 90 iterations (variant 30) (variant 44) (variant 31) (variant 41)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 94) (variant 45) (variant 49)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 56) (variant 80) (variant 30) (variant 70) (variant 64)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 16) (variant 4) (variant 76) (variant 47)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 65) (variant 26)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 16) (variant 67) (variant 67)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 46) (variant 51) (variant 62) (variant 68) (variant 89)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 69) (variant 6)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 43) (variant 70) (variant 55)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 28)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 43) (variant 44)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 8) (variant 75)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "utility", "problem": "Resolve provider credentials from ~/.hermes/.env (variant 15)", "solution": "from hermes_cli.auth import resolve_credentials\n\ncreds = resolve_credentials(\"anthropic\")\nprint(creds[\"api_key\"][:8] + \"...\") # masked"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 19) (variant 89)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 90 iterations (variant 88) (variant 5)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 56) (variant 80)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 33) (variant 8) (variant 82)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 5) (variant 13)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 56) (variant 79)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "utility", "problem": "Save a trajectory to disk for later training data extraction (variant 30)", "solution": "from agent.trajectory import save_trajectory\nimport json\n\ntrajectory = {{\n \"session_id\": session_id,\n \"messages\": messages,\n \"model\": model,\n \"tools_called\": [tc.name for tc in tool_calls],\n}}\n\npath = save_trajectory(trajectory, directory=\"~/.hermes/trajectories/\")\nprint(f\"Saved to {{path}}\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 46) (variant 51) (variant 62) (variant 68) (variant 10)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 30 iterations (variant 6) (variant 43) (variant 70) (variant 55) (variant 79) (variant 2) (variant 94)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "config", "problem": "Save a persistent config value and reload on next startup", "solution": "from hermes_cli.config import save_config_value, load_cli_config\n\nsave_config_value(\"model\", \"openai/gpt-4o\")\nconfig = load_cli_config()\nassert config[\"model\"] == \"openai/gpt-4o\""}
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{"issue": 592, "domain": "tool_routing", "problem": "Check if a tool is available before calling it (variant 13)", "solution": "from tools.registry import registry\n\ntool_name = \"web_search\"\nif registry.is_available(tool_name):\n schema = registry.get_schema(tool_name)\n result = registry.call(tool_name, {{\"query\": \"Python asyncio\"}}, task_id=\"abc\")\nelse:\n result = f\"Tool {{tool_name}} is not available (missing requirements)\""}
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{"issue": 592, "domain": "utility", "problem": "Poll a background process for completion with progress tracking (variant 55) (variant 65) (variant 48)", "solution": "from tools.process_registry import ProcessRegistry\n\nregistry = ProcessRegistry()\nsession_id = registry.start(\"long_task.sh\", background=True)\n\nwhile True:\n status = registry.poll(session_id)\n if status[\"done\"]:\n print(f\"Completed with exit code {{status['exit_code']}}\")\n break\n print(f\"Progress: {{status['lines']}} lines output\")\n time.sleep(1)"}
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{"issue": 592, "domain": "error_handling", "problem": "Handle missing optional dependencies with graceful degradation (variant 40)", "solution": "try:\n import chromadb\n HAS_CHROMADB = True\nexcept ImportError:\n HAS_CHROMADB = False\n\ndef search_vectors(query: str):\n if not HAS_CHROMADB:\n return {{\"warning\": \"ChromaDB not installed\", \"results\": []}}\n # ... actual implementation"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 39)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 2) (variant 32) (variant 50)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 37) (variant 64) (variant 83) (variant 75)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "tool_routing", "problem": "Discover all builtin tools and build tool schemas for the API call (variant 52) (variant 14) (variant 19) (variant 89)", "solution": "from model_tools import discover_builtin_tools\nfrom tools.registry import registry\n\n# Auto-discover all registered tools\ndiscover_builtin_tools()\n\n# Collect schemas for all available tools\ntool_schemas = [registry.get_schema(name) for name in registry.list_available()]\n\n# Filter by enabled toolsets\nenabled = [\"web\", \"terminal\", \"file\"]\ntool_schemas = [\n s for s in tool_schemas\n if registry.get_toolset(s[\"name\"]) in enabled\n]"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 30 iterations (variant 42) (variant 47) (variant 54) (variant 3)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "List recent sessions from the session database with pagination (variant 54) (variant 48) (variant 39)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nsessions = db.list_sessions(limit=20, offset=0)\nfor sess in sessions:\n print(f\"{{sess['id']}} | {{sess['created_at']}} | {{sess['message_count']}} msgs\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 50 iterations (variant 4)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 70) (variant 43)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"anthropic/claude-sonnet-4\", max_iterations=50)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "testing", "problem": "Test agent loop behavior with mocked API responses (variant 87) (variant 37) (variant 42)", "solution": "import pytest\nfrom run_agent import AIAgent\n\ndef test_agent_runs_tool_call(monkeypatch):\n agent = AIAgent(model=\"test\", max_iterations=5)\n\n class MockResponse:\n tool_calls = [MockToolCall(\"read_file\", {{\"path\": \"/tmp/test.txt\"}})]\n content = None\n\n monkeypatch.setattr(agent, \"_call_api\", lambda **kw: MockResponse())\n result = agent.chat(\"Read the file\")\n assert result is not None"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 50 iterations (variant 38)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "error_handling", "problem": "Catch and log tool execution errors without crashing the agent loop", "solution": "import json\nimport traceback\n\ntry:\n result = handle_function_call(tool_call.name, tool_call.args)\nexcept Exception as e:\n tb = traceback.format_exc()\n result = json.dumps({{\n \"error\": str(e),\n \"traceback\": tb,\n }})"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 56) (variant 80) (variant 30)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 58) (variant 30)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "config", "problem": "Bump config schema version and add migration for existing users (variant 76) (variant 38) (variant 34) (variant 55)", "solution": "# In hermes_cli/config.py\n\nDEFAULT_CONFIG = {{\n \"_config_version\": 6, # bumped from 5\n \"model\": \"anthropic/claude-sonnet-4\",\n \"max_iterations\": 50,\n \"new_feature\": True, # added\n}}\n\ndef migrate_config(raw: dict) -> dict:\n version = raw.get(\"_config_version\", 0)\n if version < 6:\n raw[\"new_feature\"] = DEFAULT_CONFIG[\"new_feature\"]\n raw[\"_config_version\"] = 6\n return raw"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 70) (variant 84) (variant 34)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "error_handling", "problem": "Catch and log tool execution errors without crashing the agent loop (variant 39)", "solution": "import json\nimport traceback\n\ntry:\n result = handle_function_call(tool_call.name, tool_call.args)\nexcept Exception as e:\n tb = traceback.format_exc()\n result = json.dumps({{\n \"error\": str(e),\n \"traceback\": tb,\n }})"}
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{"issue": 592, "domain": "config", "problem": "Bump config schema version and add migration for existing users (variant 76) (variant 38) (variant 34)", "solution": "# In hermes_cli/config.py\n\nDEFAULT_CONFIG = {{\n \"_config_version\": 6, # bumped from 5\n \"model\": \"anthropic/claude-sonnet-4\",\n \"max_iterations\": 50,\n \"new_feature\": True, # added\n}}\n\ndef migrate_config(raw: dict) -> dict:\n version = raw.get(\"_config_version\", 0)\n if version < 6:\n raw[\"new_feature\"] = DEFAULT_CONFIG[\"new_feature\"]\n raw[\"_config_version\"] = 6\n return raw"}
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{"issue": 592, "domain": "config", "problem": "Add a new .env variable with metadata for setup wizard (variant 83) (variant 24)", "solution": "# In hermes_cli/config.py\n\nOPTIONAL_ENV_VARS = {{\n \"NEW_API_KEY\": {{\n \"description\": \"API key for new service integration\",\n \"prompt\": \"New Service API Key\",\n \"url\": \"https://new-service.com/api-keys\",\n \"password\": True,\n \"category\": \"tool\",\n }},\n}}"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 82) (variant 7)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=50)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 43) (variant 44) (variant 41)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "utility", "problem": "Load user config from ~/.hermes/config.yaml with defaults fallback (variant 47)", "solution": "from hermes_cli.config import load_cli_config, DEFAULT_CONFIG\n\nconfig = load_cli_config()\nmodel = config.get(\"model\", DEFAULT_CONFIG[\"model\"])\nmax_iters = config.get(\"max_iterations\", DEFAULT_CONFIG[\"max_iterations\"])"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 16) (variant 22) (variant 35)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 6)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length (variant 37) (variant 64)", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 41) (variant 29)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "tool_routing", "problem": "Register a new tool with the central registry in tools/registry.py (variant 49) (variant 24)", "solution": "from tools.registry import registry\n\ndef example_tool(param: str, task_id: str = None) -> str:\n import json\n return json.dumps({{\"success\": True, \"data\": param}})\n\nregistry.register(\n name=\"example_tool\",\n toolset=\"example\",\n schema={{\n \"name\": \"example_tool\",\n \"description\": \"Does something useful\",\n \"parameters\": {{\n \"type\": \"object\",\n \"properties\": {{\n \"param\": {{\"type\": \"string\", \"description\": \"Input parameter\"}}\n }},\n \"required\": [\"param\"],\n }},\n }},\n handler=lambda args, **kw: example_tool(\n param=args.get(\"param\", \"\"),\n task_id=kw.get(\"task_id\")\n ),\n check_fn=lambda: bool(os.getenv(\"EXAMPLE_API_KEY\")),\n requires_env=[\"EXAMPLE_API_KEY\"],\n)"}
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{"issue": 592, "domain": "prompt_building", "problem": "Truncate messages to fit within model context length", "solution": "from agent.model_metadata import estimate_tokens, DEFAULT_CONTEXT_LENGTHS\n\nmodel = \"claude-sonnet-4\"\nmax_ctx = DEFAULT_CONTEXT_LENGTHS.get(model, 128000)\n\n# Reserve space for response\nmax_input_tokens = int(max_ctx * 0.8)\n\n# Truncate from the middle (preserve system + recent)\ntotal = sum(estimate_tokens(m[\"content\"]) for m in messages)\nwhile total > max_input_tokens and len(messages) > 3:\n # Remove oldest non-system message\n for i, m in enumerate(messages):\n if m[\"role\"] != \"system\":\n total -= estimate_tokens(m[\"content\"])\n messages.pop(i)\n break"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 50 iterations (variant 28) (variant 83) (variant 4)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 30 iterations (variant 42) (variant 47) (variant 54) (variant 3) (variant 30)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 56) (variant 80) (variant 30) (variant 70) (variant 81)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "session_management", "problem": "Query the session database for messages matching a keyword using FTS5 (variant 16) (variant 67)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nresults = db.search_messages(\"error handling\", limit=10)\nfor row in results:\n print(f\"Session {{row['session_id']}}: {{row['content'][:100]}}\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 5) (variant 86)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 60) (variant 11)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 90 iterations", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 49)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 29)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "tool_routing", "problem": "Add a new toolset to HERMES_CORE_TOOLS in toolsets.py (variant 3)", "solution": "# In toolsets.py\n\n_HERMES_CORE_TOOLS = [\n \"web\",\n \"terminal\",\n \"file\",\n \"browser\",\n \"code_execution\",\n \"delegate\",\n \"new_toolset\", # <-- added\n]\n\n# Create tools/new_toolset_tool.py with registry.register() at module level\n# Auto-discovery will pick it up automatically — no manual import needed"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 98) (variant 20)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 43) (variant 44) (variant 41) (variant 21) (variant 75)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 18) (variant 93) (variant 62)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 90 iterations (variant 67)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 71)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "tool_routing", "problem": "Check if a tool is available before calling it (variant 13) (variant 78)", "solution": "from tools.registry import registry\n\ntool_name = \"web_search\"\nif registry.is_available(tool_name):\n schema = registry.get_schema(tool_name)\n result = registry.call(tool_name, {{\"query\": \"Python asyncio\"}}, task_id=\"abc\")\nelse:\n result = f\"Tool {{tool_name}} is not available (missing requirements)\""}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 61)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 17) (variant 82) (variant 49)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "tool_routing", "problem": "Wrap a tool handler to add logging and error handling (variant 39) (variant 59)", "solution": "import json\nimport logging\nfrom tools.registry import registry\n\nlogger = logging.getLogger(__name__)\n\ndef logged_handler(fn):\n def wrapper(args, **kwargs):\n task_id = kwargs.get(\"task_id\")\n logger.info(f\"[{{task_id}}] Calling {{fn.__name__}} with {{args}}\")\n try:\n result = fn(args, **kwargs)\n logger.info(f\"[{{task_id}}] Success\")\n return result\n except Exception as e:\n logger.error(f\"[{{task_id}}] Error: {{e}}\")\n return json.dumps({{\"error\": str(e)}})\n return wrapper\n\n# Register with wrapper\nregistry.register(\n name=\"my_tool\",\n toolset=\"custom\",\n schema={{...}},\n handler=lambda args, **kw: logged_handler(my_tool_impl)(args, **kw),\n)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model anthropic/claude-sonnet-4 and max 90 iterations (variant 88) (variant 15) (variant 71)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"anthropic/claude-sonnet-4\",\n max_iterations=90,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Save a conversation session to SQLite with metadata (variant 61) (variant 32) (variant 97)", "solution": "from hermes_state import SessionDB\nimport json\n\ndb = SessionDB()\nsession_id = \"sess-abc-123\"\nmessages = [\n {{\"role\": \"user\", \"content\": \"Hello\"}},\n {{\"role\": \"assistant\", \"content\": \"Hi there\"}},\n]\n\ndb.save_session(\n session_id=session_id,\n messages=json.dumps(messages),\n model=\"claude-sonnet-4\",\n platform=\"cli\",\n task_id=\"task-456\",\n)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 18)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 17) (variant 99)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 5) (variant 42) (variant 61)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "error_handling", "problem": "Handle missing optional dependencies with graceful degradation (variant 18)", "solution": "try:\n import chromadb\n HAS_CHROMADB = True\nexcept ImportError:\n HAS_CHROMADB = False\n\ndef search_vectors(query: str):\n if not HAS_CHROMADB:\n return {{\"warning\": \"ChromaDB not installed\", \"results\": []}}\n # ... actual implementation"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 60) (variant 97) (variant 41)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 36) (variant 8) (variant 66) (variant 9)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 69) (variant 85)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "error_handling", "problem": "Gracefully handle API rate limit with exponential backoff (variant 14) (variant 99) (variant 40)", "solution": "import time\nimport random\n\nmax_retries = 5\nfor attempt in range(max_retries):\n try:\n response = client.chat.completions.create(...)\n break\n except RateLimitError as e:\n wait = (2 ** attempt) + random.uniform(0, 1)\n print(f\"Rate limited. Retrying in {{wait:.1f}}s...\")\n time.sleep(wait)\nelse:\n raise Exception(\"Max retries exceeded\")"}
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{"issue": 592, "domain": "error_handling", "problem": "Handle missing optional dependencies with graceful degradation (variant 12) (variant 17)", "solution": "try:\n import chromadb\n HAS_CHROMADB = True\nexcept ImportError:\n HAS_CHROMADB = False\n\ndef search_vectors(query: str):\n if not HAS_CHROMADB:\n return {{\"warning\": \"ChromaDB not installed\", \"results\": []}}\n # ... actual implementation"}
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{"issue": 592, "domain": "agent_loop", "problem": "Check iteration budget before making another API call in the agent loop (variant 24) (variant 43) (variant 44) (variant 41) (variant 21) (variant 84)", "solution": "while api_call_count < agent.max_iterations and agent.iteration_budget.remaining > 0:\n response = client.chat.completions.create(\n model=model,\n messages=messages,\n tools=tool_schemas,\n )\n if response.tool_calls:\n for tc in response.tool_calls:\n result = handle_function_call(tc.name, tc.args)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content"}
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{"issue": 592, "domain": "utility", "problem": "Read a file safely with size limits and binary detection (variant 89) (variant 42)", "solution": "from tools.file_tools import read_file\n\ncontent = read_file(\n path=\"/tmp/large.log\",\n offset=1,\n limit=500,\n)\nprint(content)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 50) (variant 66) (variant 53) (variant 73) (variant 98)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "testing", "problem": "Test agent loop behavior with mocked API responses (variant 87) (variant 37) (variant 38)", "solution": "import pytest\nfrom run_agent import AIAgent\n\ndef test_agent_runs_tool_call(monkeypatch):\n agent = AIAgent(model=\"test\", max_iterations=5)\n\n class MockResponse:\n tool_calls = [MockToolCall(\"read_file\", {{\"path\": \"/tmp/test.txt\"}})]\n content = None\n\n monkeypatch.setattr(agent, \"_call_api\", lambda **kw: MockResponse())\n result = agent.chat(\"Read the file\")\n assert result is not None"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 93) (variant 89)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"anthropic/claude-sonnet-4\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "tool_routing", "problem": "Check if a tool is available before calling it (variant 32) (variant 56) (variant 23)", "solution": "from tools.registry import registry\n\ntool_name = \"web_search\"\nif registry.is_available(tool_name):\n schema = registry.get_schema(tool_name)\n result = registry.call(tool_name, {{\"query\": \"Python asyncio\"}}, task_id=\"abc\")\nelse:\n result = f\"Tool {{tool_name}} is not available (missing requirements)\""}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 17) (variant 99) (variant 22) (variant 56) (variant 24)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "utility", "problem": "Render a rich markdown panel with tool call preview (variant 69) (variant 54) (variant 25)", "solution": "from agent.display import KawaiiSpinner, render_tool_preview\nfrom rich.panel import Panel\n\nspinner = KawaiiSpinner()\nspinner.start(\"Calling web_search...\")\n\npreview = render_tool_preview(\"web_search\", {{\"query\": \"Python 3.12\"}})\nconsole.print(Panel(preview, title=\"Tool Call\", border_style=\"cyan\"))\n\nspinner.stop()"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 98)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 11) (variant 45) (variant 53)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "tool_routing", "problem": "Wrap a tool handler to add logging and error handling (variant 39) (variant 60)", "solution": "import json\nimport logging\nfrom tools.registry import registry\n\nlogger = logging.getLogger(__name__)\n\ndef logged_handler(fn):\n def wrapper(args, **kwargs):\n task_id = kwargs.get(\"task_id\")\n logger.info(f\"[{{task_id}}] Calling {{fn.__name__}} with {{args}}\")\n try:\n result = fn(args, **kwargs)\n logger.info(f\"[{{task_id}}] Success\")\n return result\n except Exception as e:\n logger.error(f\"[{{task_id}}] Error: {{e}}\")\n return json.dumps({{\"error\": str(e)}})\n return wrapper\n\n# Register with wrapper\nregistry.register(\n name=\"my_tool\",\n toolset=\"custom\",\n schema={{...}},\n handler=lambda args, **kw: logged_handler(my_tool_impl)(args, **kw),\n)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent (variant 70) (variant 81)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"openai/gpt-4o-mini\", max_iterations=90)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "agent_loop", "problem": "Run a full conversation with custom system message using AIAgent", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(model=\"anthropic/claude-sonnet-4\", max_iterations=50)\nresult = agent.run_conversation(\n user_message=\"Analyze this log file\",\n system_message=\"You are a DevOps assistant. Be concise.\",\n)\nprint(result[\"final_response\"])"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 56) (variant 37)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "error_handling", "problem": "Detect and recover from infinite tool call loops", "solution": "# In run_conversation loop\nseen_calls = set()\nfor tool_call in response.tool_calls:\n call_key = (tool_call.name, json.dumps(tool_call.args, sort_keys=True))\n if call_key in seen_calls:\n messages.append({{\n \"role\": \"tool\",\n \"content\": \"Error: Repeated identical tool call detected. Try a different approach.\",\n }})\n continue\n seen_calls.add(call_key)\n result = handle_function_call(tool_call.name, tool_call.args)\n messages.append(tool_result_message(result))"}
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{"issue": 592, "domain": "session_management", "problem": "Enable Anthropic prompt caching for long system prompts (variant 2) (variant 62) (variant 99)", "solution": "from agent.prompt_caching import PromptCaching\n\ncache = PromptCaching()\nsystem_msg = cache.prepare_system_prompt(\n content=system_content,\n cache_key=\"my-profile-v1\",\n)\n\n# The system prompt will be cached across turns\nmessages = [system_msg, {{\"role\": \"user\", \"content\": user_input}}]"}
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{"issue": 592, "domain": "error_handling", "problem": "Detect and recover from infinite tool call loops (variant 35)", "solution": "# In run_conversation loop\nseen_calls = set()\nfor tool_call in response.tool_calls:\n call_key = (tool_call.name, json.dumps(tool_call.args, sort_keys=True))\n if call_key in seen_calls:\n messages.append({{\n \"role\": \"tool\",\n \"content\": \"Error: Repeated identical tool call detected. Try a different approach.\",\n }})\n continue\n seen_calls.add(call_key)\n result = handle_function_call(tool_call.name, tool_call.args)\n messages.append(tool_result_message(result))"}
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{"issue": 592, "domain": "tool_routing", "problem": "Discover all builtin tools and build tool schemas for the API call (variant 52) (variant 14) (variant 59)", "solution": "from model_tools import discover_builtin_tools\nfrom tools.registry import registry\n\n# Auto-discover all registered tools\ndiscover_builtin_tools()\n\n# Collect schemas for all available tools\ntool_schemas = [registry.get_schema(name) for name in registry.list_available()]\n\n# Filter by enabled toolsets\nenabled = [\"web\", \"terminal\", \"file\"]\ntool_schemas = [\n s for s in tool_schemas\n if registry.get_toolset(s[\"name\"]) in enabled\n]"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 11) (variant 17) (variant 16) (variant 80) (variant 45)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 30 iterations", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=30,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 11) (variant 17) (variant 88)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 50) (variant 27)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "Compress old session context to stay within token budget (variant 11)", "solution": "from agent.context_compressor import ContextCompressor\n\ncompressor = ContextCompressor(model=\"claude-sonnet-4\")\ncompressed = compressor.compress(\n messages=messages,\n target_tokens=4000,\n preserve_recent=4,\n)\nmessages = compressed[\"messages\"]\nsummary = compressed.get(\"summary\", \"\")"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 13) (variant 77) (variant 83)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "testing", "problem": "Write a pytest test for a new tool using monkeypatch (variant 28) (variant 34)", "solution": "import pytest\nfrom tools.web_tools import web_search\n\ndef test_web_search_returns_results(monkeypatch):\n def mock_fetch(url):\n return \"<html><body>Test result</body></html>\"\n\n monkeypatch.setattr(\"tools.web_tools._fetch\", mock_fetch)\n result = web_search(query=\"test\")\n assert \"Test result\" in result"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 5) (variant 47)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model openai/gpt-4o and max 50 iterations (variant 5) (variant 42) (variant 56)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"openai/gpt-4o\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "utility", "problem": "Execute Python code in sandbox with timeout and output capture (variant 78) (variant 6) (variant 7)", "solution": "from tools.code_execution_tool import execute_code\n\nresult = execute_code(\"\"\"\nimport json\nprint(json.dumps({\"sum\": sum(range(100))}))\n\"\"\")\ndata = json.loads(result[\"output\"])\nprint(data[\"sum\"]) # 4950"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model google/gemini-2.5-pro and max 50 iterations (variant 50) (variant 27) (variant 51) (variant 95)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"google/gemini-2.5-pro\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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{"issue": 592, "domain": "session_management", "problem": "List recent sessions from the session database with pagination (variant 54) (variant 48) (variant 39) (variant 90)", "solution": "from hermes_state import SessionDB\n\ndb = SessionDB()\nsessions = db.list_sessions(limit=20, offset=0)\nfor sess in sessions:\n print(f\"{{sess['id']}} | {{sess['created_at']}} | {{sess['message_count']}} msgs\")"}
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{"issue": 592, "domain": "utility", "problem": "Resolve provider credentials from ~/.hermes/.env (variant 15) (variant 38) (variant 90) (variant 21) (variant 47)", "solution": "from hermes_cli.auth import resolve_credentials\n\ncreds = resolve_credentials(\"anthropic\")\nprint(creds[\"api_key\"][:8] + \"...\") # masked"}
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{"issue": 592, "domain": "agent_loop", "problem": "Create an AIAgent instance with model nous/hermes3:70b and max 50 iterations (variant 48)", "solution": "from run_agent import AIAgent\n\nagent = AIAgent(\n model=\"nous/hermes3:70b\",\n max_iterations=50,\n enabled_toolsets=[\"web\", \"terminal\", \"file\"],\n)\nresponse = agent.chat(\"List files in current directory\")\nprint(response)"}
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