{
  "session_id": "20260330_012110_8b2f9b",
  "model": "claude-opus-4.6",
  "base_url": "https://api.anthropic.com",
  "platform": "telegram",
  "session_start": "2026-03-30T01:21:10.523676",
  "last_updated": "2026-03-30T01:24:34.508810",
  "system_prompt": "You are Hermes Agent, an intelligent AI assistant created by Nous Research. You are helpful, knowledgeable, and direct. You assist users with a wide range of tasks including answering questions, writing and editing code, analyzing information, creative work, and executing actions via your tools. You communicate clearly, admit uncertainty when appropriate, and prioritize being genuinely useful over being verbose unless otherwise directed below. Be targeted and efficient in your exploration and investigations.\n\nConversation started: Monday, March 30, 2026 01:21 AM\nModel: claude-opus-4.6\nProvider: anthropic\n\nYou are on a text messaging communication platform, Telegram. Please do not use markdown as it does not render. You can send media files natively: to deliver a file to the user, include MEDIA:/absolute/path/to/file in your response. Images (.png, .jpg, .webp) appear as photos, audio (.ogg) sends as voice bubbles, and videos (.mp4) play inline. You can also include image URLs in markdown format ![alt](url) and they will be sent as native photos.",
  "tools": [
    {
      "type": "function",
      "function": {
        "name": "patch",
        "description": "Targeted find-and-replace edits in files. Use this instead of sed/awk in terminal. Uses fuzzy matching (9 strategies) so minor whitespace/indentation differences won't break it. Returns a unified diff. Auto-runs syntax checks after editing.\n\nReplace mode (default): find a unique string and replace it.\nPatch mode: apply V4A multi-file patches for bulk changes.",
        "parameters": {
          "type": "object",
          "properties": {
            "mode": {
              "type": "string",
              "enum": [
                "replace",
                "patch"
              ],
              "description": "Edit mode: 'replace' for targeted find-and-replace, 'patch' for V4A multi-file patches",
              "default": "replace"
            },
            "path": {
              "type": "string",
              "description": "File path to edit (required for 'replace' mode)"
            },
            "old_string": {
              "type": "string",
              "description": "Text to find in the file (required for 'replace' mode). Must be unique in the file unless replace_all=true. Include enough surrounding context to ensure uniqueness."
            },
            "new_string": {
              "type": "string",
              "description": "Replacement text (required for 'replace' mode). Can be empty string to delete the matched text."
            },
            "replace_all": {
              "type": "boolean",
              "description": "Replace all occurrences instead of requiring a unique match (default: false)",
              "default": false
            },
            "patch": {
              "type": "string",
              "description": "V4A format patch content (required for 'patch' mode). Format:\n*** Begin Patch\n*** Update File: path/to/file\n@@ context hint @@\n context line\n-removed line\n+added line\n*** End Patch"
            }
          },
          "required": [
            "mode"
          ]
        }
      }
    },
    {
      "type": "function",
      "function": {
        "name": "process",
        "description": "Manage background processes started with terminal(background=true). Actions: 'list' (show all), 'poll' (check status + new output), 'log' (full output with pagination), 'wait' (block until done or timeout), 'kill' (terminate), 'write' (send raw stdin data without newline), 'submit' (send data + Enter, for answering prompts).",
        "parameters": {
          "type": "object",
          "properties": {
            "action": {
              "type": "string",
              "enum": [
                "list",
                "poll",
                "log",
                "wait",
                "kill",
                "write",
                "submit"
              ],
              "description": "Action to perform on background processes"
            },
            "session_id": {
              "type": "string",
              "description": "Process session ID (from terminal background output). Required for all actions except 'list'."
            },
            "data": {
              "type": "string",
              "description": "Text to send to process stdin (for 'write' and 'submit' actions)"
            },
            "timeout": {
              "type": "integer",
              "description": "Max seconds to block for 'wait' action. Returns partial output on timeout.",
              "minimum": 1
            },
            "offset": {
              "type": "integer",
              "description": "Line offset for 'log' action (default: last 200 lines)"
            },
            "limit": {
              "type": "integer",
              "description": "Max lines to return for 'log' action",
              "minimum": 1
            }
          },
          "required": [
            "action"
          ]
        }
      }
    },
    {
      "type": "function",
      "function": {
        "name": "read_file",
        "description": "Read a text file with line numbers and pagination. Use this instead of cat/head/tail in terminal. Output format: 'LINE_NUM|CONTENT'. Suggests similar filenames if not found. Use offset and limit for large files. NOTE: Cannot read images or binary files — use vision_analyze for images.",
        "parameters": {
          "type": "object",
          "properties": {
            "path": {
              "type": "string",
              "description": "Path to the file to read (absolute, relative, or ~/path)"
            },
            "offset": {
              "type": "integer",
              "description": "Line number to start reading from (1-indexed, default: 1)",
              "default": 1,
              "minimum": 1
            },
            "limit": {
              "type": "integer",
              "description": "Maximum number of lines to read (default: 500, max: 2000)",
              "default": 500,
              "maximum": 2000
            }
          },
          "required": [
            "path"
          ]
        }
      }
    },
    {
      "type": "function",
      "function": {
        "name": "search_files",
        "description": "Search file contents or find files by name. Use this instead of grep/rg/find/ls in terminal. Ripgrep-backed, faster than shell equivalents.\n\nContent search (target='content'): Regex search inside files. Output modes: full matches with line numbers, file paths only, or match counts.\n\nFile search (target='files'): Find files by glob pattern (e.g., '*.py', '*config*'). Also use this instead of ls — results sorted by modification time.",
        "parameters": {
          "type": "object",
          "properties": {
            "pattern": {
              "type": "string",
              "description": "Regex pattern for content search, or glob pattern (e.g., '*.py') for file search"
            },
            "target": {
              "type": "string",
              "enum": [
                "content",
                "files"
              ],
              "description": "'content' searches inside file contents, 'files' searches for files by name",
              "default": "content"
            },
            "path": {
              "type": "string",
              "description": "Directory or file to search in (default: current working directory)",
              "default": "."
            },
            "file_glob": {
              "type": "string",
              "description": "Filter files by pattern in grep mode (e.g., '*.py' to only search Python files)"
            },
            "limit": {
              "type": "integer",
              "description": "Maximum number of results to return (default: 50)",
              "default": 50
            },
            "offset": {
              "type": "integer",
              "description": "Skip first N results for pagination (default: 0)",
              "default": 0
            },
            "output_mode": {
              "type": "string",
              "enum": [
                "content",
                "files_only",
                "count"
              ],
              "description": "Output format for grep mode: 'content' shows matching lines with line numbers, 'files_only' lists file paths, 'count' shows match counts per file",
              "default": "content"
            },
            "context": {
              "type": "integer",
              "description": "Number of context lines before and after each match (grep mode only)",
              "default": 0
            }
          },
          "required": [
            "pattern"
          ]
        }
      }
    },
    {
      "type": "function",
      "function": {
        "name": "terminal",
        "description": "Execute shell commands on a Linux environment. Filesystem persists between calls.\n\nDo NOT use cat/head/tail to read files — use read_file instead.\nDo NOT use grep/rg/find to search — use search_files instead.\nDo NOT use ls to list directories — use search_files(target='files') instead.\nDo NOT use sed/awk to edit files — use patch instead.\nDo NOT use echo/cat heredoc to create files — use write_file instead.\nReserve terminal for: builds, installs, git, processes, scripts, network, package managers, and anything that needs a shell.\n\nForeground (default): Commands return INSTANTLY when done, even if the timeout is high. Set timeout=300 for long builds/scripts — you'll still get the result in seconds if it's fast. Prefer foreground for everything that finishes.\nBackground: ONLY for long-running servers, watchers, or processes that never exit. Set background=true to get a session_id, then use process(action=\"wait\") to block until done — it returns instantly on completion, same as foreground. Use process(action=\"poll\") only when you need a progress check without blocking.\nDo NOT use background for scripts, builds, or installs — foreground with a generous timeout is always better (fewer tool calls, instant results).\nWorking directory: Use 'workdir' for per-command cwd.\nPTY mode: Set pty=true for interactive CLI tools (Codex, Claude Code, Python REPL).\n\nDo NOT use vim/nano/interactive tools without pty=true — they hang without a pseudo-terminal. Pipe git output to cat if it might page.\n",
        "parameters": {
          "type": "object",
          "properties": {
            "command": {
              "type": "string",
              "description": "The command to execute on the VM"
            },
            "background": {
              "type": "boolean",
              "description": "ONLY for servers/watchers that never exit. For scripts, builds, installs — use foreground with timeout instead (it returns instantly when done).",
              "default": false
            },
            "timeout": {
              "type": "integer",
              "description": "Max seconds to wait (default: 180). Returns INSTANTLY when command finishes — set high for long tasks, you won't wait unnecessarily.",
              "minimum": 1
            },
            "workdir": {
              "type": "string",
              "description": "Working directory for this command (absolute path). Defaults to the session working directory."
            },
            "check_interval": {
              "type": "integer",
              "description": "Seconds between automatic status checks for background processes (gateway/messaging only, minimum 30). When set, I'll proactively report progress.",
              "minimum": 30
            },
            "pty": {
              "type": "boolean",
              "description": "Run in pseudo-terminal (PTY) mode for interactive CLI tools like Codex, Claude Code, or Python REPL. Only works with local and SSH backends. Default: false.",
              "default": false
            }
          },
          "required": [
            "command"
          ]
        }
      }
    },
    {
      "type": "function",
      "function": {
        "name": "write_file",
        "description": "Write content to a file, completely replacing existing content. Use this instead of echo/cat heredoc in terminal. Creates parent directories automatically. OVERWRITES the entire file — use 'patch' for targeted edits.",
        "parameters": {
          "type": "object",
          "properties": {
            "path": {
              "type": "string",
              "description": "Path to the file to write (will be created if it doesn't exist, overwritten if it does)"
            },
            "content": {
              "type": "string",
              "description": "Complete content to write to the file"
            }
          },
          "required": [
            "path",
            "content"
          ]
        }
      }
    }
  ],
  "message_count": 64,
  "messages": [
    {
      "role": "user",
      "content": "Search the Hermes agent codebase at /root/wizards/ezra/hermes-agent to understand how local llama.cpp tool calling works. Specifically find: 1) How does provider \"local-llama.cpp\" or \"local\" resolve? 2) How are tools formatted for the OpenAI chat completions API when using local models? 3) Is there any special handling for Hermes-format tool calls vs OpenAI-format? 4) What chat template or tool format does the system expect from local llama-server? Look in run_agent.py, cli.py, hermes_cli/auth.py, hermes_cli/runtime_provider.py, and agent/model_metadata.py. Focus on the tool formatting path for chat_completions API mode."
    },
    {
      "role": "assistant",
      "content": "",
      "reasoning": "Let me search the codebase to understand how local llama.cpp tool calling works.",
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_01PYATE58ujmkn8o7RruZLNM",
          "call_id": "toolu_01PYATE58ujmkn8o7RruZLNM",
          "response_item_id": "fc_toolu_01PYATE58ujmkn8o7RruZLNM",
          "type": "function",
          "function": {
            "name": "search_files",
            "arguments": "{\"pattern\": \"*\", \"target\": \"files\", \"path\": \"/root/wizards/ezra/claude-code\", \"limit\": 50}"
          }
        },
        {
          "id": "toolu_01TNMP7YA42pGnobdZjZMRpW",
          "call_id": "toolu_01TNMP7YA42pGnobdZjZMRpW",
          "response_item_id": "fc_toolu_01TNMP7YA42pGnobdZjZMRpW",
          "type": "function",
          "function": {
            "name": "search_files",
            "arguments": "{\"pattern\": \"*\", \"target\": \"files\", \"path\": \"/root/wizards/ezra\", \"limit\": 50}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"total_count\": 0, \"error\": \"Path not found: /root/wizards/ezra/claude-code. Verify the path exists (use 'terminal' to check).\"}",
      "tool_call_id": "toolu_01PYATE58ujmkn8o7RruZLNM"
    },
    {
      "role": "tool",
      "content": "{\"total_count\": 50, \"files\": [\"/root/wizards/ezra/home/response_store.db-shm\", \"/root/wizards/ezra/home/skills/data-science/DESCRIPTION.md\", \"/root/wizards/ezra/home/skills/data-science/jupyter-live-kernel/SKILL.md\", \"/root/wizards/ezra/home/skills/feeds/DESCRIPTION.md\", \"/root/wizards/ezra/home/skills/autonomous-ai-agents/hermes-agent/SKILL.md\", \"/root/wizards/ezra/home/skills/autonomous-ai-agents/DESCRIPTION.md\", \"/root/wizards/ezra/home/skills/autonomous-ai-agents/opencode/SKILL.md\", \"/root/wizards/ezra/home/skills/autonomous-ai-agents/codex/SKILL.md\", \"/root/wizards/ezra/home/skills/autonomous-ai-agents/claude-code/SKILL.md\", \"/root/wizards/ezra/home/skills/creative/DESCRIPTION.md\", \"/root/wizards/ezra/home/skills/creative/ascii-art/SKILL.md\", \"/root/wizards/ezra/home/skills/creative/excalidraw/SKILL.md\", \"/root/wizards/ezra/home/skills/creative/excalidraw/scripts/upload.py\", \"/root/wizards/ezra/home/skills/creative/excalidraw/references/colors.md\", \"/root/wizards/ezra/home/skills/creative/excalidraw/references/dark-mode.md\", \"/root/wizards/ezra/home/skills/creative/excalidraw/references/examples.md\", \"/root/wizards/ezra/home/skills/creative/ascii-video/SKILL.md\", \"/root/wizards/ezra/home/skills/creative/ascii-video/README.md\", \"/root/wizards/ezra/home/skills/creative/ascii-video/references/inputs.md\", \"/root/wizards/ezra/home/skills/creative/ascii-video/references/shaders.md\", \"/root/wizards/ezra/home/skills/creative/ascii-video/references/scenes.md\", \"/root/wizards/ezra/home/skills/creative/ascii-video/references/troubleshooting.md\", \"/root/wizards/ezra/home/skills/creative/ascii-video/references/composition.md\", \"/root/wizards/ezra/home/skills/creative/ascii-video/references/optimization.md\", \"/root/wizards/ezra/home/skills/creative/ascii-video/references/effects.md\", \"/root/wizards/ezra/home/skills/creative/ascii-video/references/architecture.md\", \"/root/wizards/ezra/home/skills/productivity/powerpoint/SKILL.md\", \"/root/wizards/ezra/home/skills/productivity/powerpoint/pptxgenjs.md\", \"/root/wizards/ezra/home/skills/productivity/powerpoint/scripts/office/helpers/merge_runs.py\", \"/root/wizards/ezra/home/skills/productivity/powerpoint/scripts/office/helpers/simplify_redlines.py\", \"/root/wizards/ezra/home/skills/productivity/powerpoint/scripts/office/helpers/__init__.py\", \"/root/wizards/ezra/home/skills/productivity/powerpoint/scripts/office/schemas/microsoft/wml-2018.xsd\", \"/root/wizards/ezra/home/skills/productivity/powerpoint/scripts/office/schemas/microsoft/wml-cid-2016.xsd\", \"/root/wizards/ezra/home/skills/productivity/powerpoint/scripts/office/schemas/microsoft/wml-2010.xsd\", \"/root/wizards/ezra/home/skills/productivity/powerpoint/scripts/office/schemas/microsoft/wml-sdtdatahash-2020.xsd\", \"/root/wizards/ezra/home/skills/productivity/powerpoint/scripts/office/schemas/microsoft/wml-cex-2018.xsd\", \"/root/wizards/ezra/home/skills/productivity/powerpoint/scripts/office/schemas/microsoft/wml-symex-2015.xsd\", \"/root/wizards/ezra/home/skills/productivity/powerpoint/scripts/office/schemas/microsoft/wml-2012.xsd\", \"/root/wizards/ezra/home/skills/productivity/powerpoint/scripts/office/schemas/mce/mc.xsd\", \"/root/wizards/ezra/home/skills/productivity/powerpoint/scripts/office/schemas/ecma/fourth-edition/opc-contentTypes.xsd\", \"/root/wizards/ezra/home/skills/productivity/powerpoint/scripts/office/schemas/ecma/fourth-edition/opc-relationships.xsd\", \"/root/wizards/ezra/home/skills/productivity/powerpoint/scripts/office/schemas/ecma/fourth-edition/opc-coreProperties.xsd\", \"/root/wizards/ezra/home/skills/productivity/powerpoint/scripts/office/schemas/ecma/fourth-edition/opc-digSig.xsd\", \"/root/wizards/ezra/home/skills/productivity/powerpoint/scripts/office/schemas/ISO-IEC29500-4_2016/xml.xsd\", \"/root/wizards/ezra/home/skills/productivity/powerpoint/scripts/office/schemas/ISO-IEC29500-4_2016/dml-lockedCanvas.xsd\", \"/root/wizards/ezra/home/skills/productivity/powerpoint/scripts/office/schemas/ISO-IEC29500-4_2016/dml-wordprocessingDrawing.xsd\", \"/root/wizards/ezra/home/skills/productivity/powerpoint/scripts/office/schemas/ISO-IEC29500-4_2016/pml.xsd\", \"/root/wizards/ezra/home/skills/productivity/powerpoint/scripts/office/schemas/ISO-IEC29500-4_2016/vml-officeDrawing.xsd\", \"/root/wizards/ezra/home/skills/productivity/powerpoint/scripts/office/schemas/ISO-IEC29500-4_2016/shared-math.xsd\", \"/root/wizards/ezra/home/skills/productivity/powerpoint/scripts/office/schemas/ISO-IEC29500-4_2016/sml.xsd\"], \"truncated\": true}\n\n[Hint: Results truncated. Use offset=50 to see more, or narrow with a more specific pattern or file_glob.]",
      "tool_call_id": "toolu_01TNMP7YA42pGnobdZjZMRpW"
    },
    {
      "role": "assistant",
      "content": "",
      "reasoning": "The path /root/wizards/ezra/claude-code doesn't exist. Let me find the hermes-agent codebase.",
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_01QQwxz74LTJzCkN9kFWWbHH",
          "call_id": "toolu_01QQwxz74LTJzCkN9kFWWbHH",
          "response_item_id": "fc_toolu_01QQwxz74LTJzCkN9kFWWbHH",
          "type": "function",
          "function": {
            "name": "terminal",
            "arguments": "{\"command\": \"find /root/wizards/ezra -name \\\"run_agent.py\\\" -o -name \\\"auth.py\\\" -o -name \\\"runtime_provider.py\\\" -o -name \\\"model_metadata.py\\\" 2>/dev/null | head -30\"}"
          }
        },
        {
          "id": "toolu_01Pm2MD7oc6gLQMJB9wRCBWb",
          "call_id": "toolu_01Pm2MD7oc6gLQMJB9wRCBWb",
          "response_item_id": "fc_toolu_01Pm2MD7oc6gLQMJB9wRCBWb",
          "type": "function",
          "function": {
            "name": "search_files",
            "arguments": "{\"pattern\": \"hermes*\", \"target\": \"files\", \"path\": \"/root/wizards/ezra\", \"limit\": 30}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"output\": \"/root/wizards/ezra/hermes-agent/.venv/lib/python3.12/site-packages/websockets/auth.py\\n/root/wizards/ezra/hermes-agent/.venv/lib/python3.12/site-packages/websockets/legacy/auth.py\\n/root/wizards/ezra/hermes-agent/.venv/lib/python3.12/site-packages/huggingface_hub/cli/auth.py\\n/root/wizards/ezra/hermes-agent/.venv/lib/python3.12/site-packages/pip/_internal/network/auth.py\\n/root/wizards/ezra/hermes-agent/.venv/lib/python3.12/site-packages/pip/_vendor/requests/auth.py\\n/root/wizards/ezra/hermes-agent/.venv/lib/python3.12/site-packages/fal_client/auth.py\\n/root/wizards/ezra/hermes-agent/.venv/lib/python3.12/site-packages/requests/auth.py\\n/root/wizards/ezra/hermes-agent/agent/model_metadata.py\\n/root/wizards/ezra/hermes-agent/run_agent.py\\n/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\\n/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\\n/root/wizards/ezra/hermes-agent/acp_adapter/auth.py\", \"exit_code\": 0, \"error\": null}",
      "tool_call_id": "toolu_01QQwxz74LTJzCkN9kFWWbHH"
    },
    {
      "role": "tool",
      "content": "{\"total_count\": 17, \"files\": [\"/root/wizards/ezra/hermes-agent/landingpage/hermes-agent-banner.png\", \"/root/wizards/ezra/hermes-agent/tests/test_hermes_state.py\", \"/root/wizards/ezra/hermes-agent/hermes_time.py\", \"/root/wizards/ezra/hermes-agent/scripts/hermes-gateway\", \"/root/wizards/ezra/hermes-agent/setup-hermes.sh\", \"/root/wizards/ezra/hermes-agent/environments/hermes_swe_env/hermes_swe_env.py\", \"/root/wizards/ezra/hermes-agent/environments/hermes_base_env.py\", \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/hermes_parser.py\", \"/root/wizards/ezra/hermes-agent/hermes_constants.py\", \"/root/wizards/ezra/hermes-agent/optional-skills/migration/openclaw-migration/scripts/openclaw_to_hermes.py\", \"/root/wizards/ezra/hermes-agent/website/docs/guides/use-mcp-with-hermes.md\", \"/root/wizards/ezra/hermes-agent/website/docs/guides/use-soul-with-hermes.md\", \"/root/wizards/ezra/hermes-agent/website/docs/guides/use-voice-mode-with-hermes.md\", \"/root/wizards/ezra/hermes-agent/website/docs/guides/build-a-hermes-plugin.md\", \"/root/wizards/ezra/hermes-agent/hermes\", \"/root/wizards/ezra/hermes-agent/hermes_state.py\", \"/root/wizards/ezra/hermes-agent/website/static/img/hermes-agent-banner.png\"]}",
      "tool_call_id": "toolu_01Pm2MD7oc6gLQMJB9wRCBWb"
    },
    {
      "role": "assistant",
      "content": "Good, the codebase is at `/root/wizards/ezra/hermes-agent`. Let me read the key files.",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_019hbSLJdgKwLkudAzGG6K75",
          "call_id": "toolu_019hbSLJdgKwLkudAzGG6K75",
          "response_item_id": "fc_toolu_019hbSLJdgKwLkudAzGG6K75",
          "type": "function",
          "function": {
            "name": "read_file",
            "arguments": "{\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\"}"
          }
        },
        {
          "id": "toolu_01AGCWu4QCjoQGtPVmGJeyCV",
          "call_id": "toolu_01AGCWu4QCjoQGtPVmGJeyCV",
          "response_item_id": "fc_toolu_01AGCWu4QCjoQGtPVmGJeyCV",
          "type": "function",
          "function": {
            "name": "read_file",
            "arguments": "{\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\"}"
          }
        },
        {
          "id": "toolu_01KL8iTcLMqb7RvFBynLazMt",
          "call_id": "toolu_01KL8iTcLMqb7RvFBynLazMt",
          "response_item_id": "fc_toolu_01KL8iTcLMqb7RvFBynLazMt",
          "type": "function",
          "function": {
            "name": "read_file",
            "arguments": "{\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\"}"
          }
        },
        {
          "id": "toolu_01D8Zu3Whbn4vcWzdu5vyF96",
          "call_id": "toolu_01D8Zu3Whbn4vcWzdu5vyF96",
          "response_item_id": "fc_toolu_01D8Zu3Whbn4vcWzdu5vyF96",
          "type": "function",
          "function": {
            "name": "read_file",
            "arguments": "{\"path\": \"/root/wizards/ezra/hermes-agent/agent/model_metadata.py\"}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"content\": \"     1|#!/usr/bin/env python3\\n     2|\\\"\\\"\\\"\\n     3|AI Agent Runner with Tool Calling\\n     4|\\n     5|This module provides a clean, standalone agent that can execute AI models\\n     6|with tool calling capabilities. It handles the conversation loop, tool execution,\\n     7|and response management.\\n     8|\\n     9|Features:\\n    10|- Automatic tool calling loop until completion\\n    11|- Configurable model parameters\\n    12|- Error handling and recovery\\n    13|- Message history management\\n    14|- Support for multiple model providers\\n    15|\\n    16|Usage:\\n    17|    from run_agent import AIAgent\\n    18|    \\n    19|    agent = AIAgent(base_url=\\\"http://localhost:30000/v1\\\", model=\\\"claude-opus-4-20250514\\\")\\n    20|    response = agent.run_conversation(\\\"Tell me about the latest Python updates\\\")\\n    21|\\\"\\\"\\\"\\n    22|\\n    23|import atexit\\n    24|import asyncio\\n    25|import base64\\n    26|import concurrent.futures\\n    27|import copy\\n    28|import hashlib\\n    29|import json\\n    30|import logging\\n    31|logger = logging.getLogger(__name__)\\n    32|import os\\n    33|import random\\n    34|import re\\n    35|import sys\\n    36|import tempfile\\n    37|import time\\n    38|import threading\\n    39|import weakref\\n    40|from types import SimpleNamespace\\n    41|import uuid\\n    42|from typing import List, Dict, Any, Optional\\n    43|from openai import OpenAI\\n    44|import fire\\n    45|from datetime import datetime\\n    46|from pathlib import Path\\n    47|\\n    48|from hermes_constants import get_hermes_home, display_hermes_home\\n    49|\\n    50|# Load .env from ~/.hermes/.env first, then project root as dev fallback.\\n    51|# User-managed env files should override stale shell exports on restart.\\n    52|from hermes_cli.env_loader import load_hermes_dotenv\\n    53|\\n    54|_hermes_home = get_hermes_home()\\n    55|_project_env = Path(__file__).parent / '.env'\\n    56|_loaded_env_paths = load_hermes_dotenv(hermes_home=_hermes_home, project_env=_project_env)\\n    57|if _loaded_env_paths:\\n    58|    for _env_path in _loaded_env_paths:\\n    59|        logger.info(\\\"Loaded environment variables from %s\\\", _env_path)\\n    60|else:\\n    61|    logger.info(\\\"No .env file found. Using system environment variables.\\\")\\n    62|\\n    63|\\n    64|# Import our tool system\\n    65|from model_tools import (\\n    66|    get_tool_definitions,\\n    67|    get_toolset_for_tool,\\n    68|    handle_function_call,\\n    69|    check_toolset_requirements,\\n    70|)\\n    71|from tools.terminal_tool import cleanup_vm\\n    72|from tools.interrupt import set_interrupt as _set_interrupt\\n    73|from tools.browser_tool import cleanup_browser\\n    74|\\n    75|\\n    76|from hermes_constants import OPENROUTER_BASE_URL\\n    77|\\n    78|# Agent internals extracted to agent/ package for modularity\\n    79|from agent.prompt_builder import (\\n    80|    DEFAULT_AGENT_IDENTITY, PLATFORM_HINTS,\\n    81|    MEMORY_GUIDANCE, SESSION_SEARCH_GUIDANCE, SKILLS_GUIDANCE,\\n    82|)\\n    83|from agent.model_metadata import (\\n    84|    fetch_model_metadata,\\n    85|    estimate_tokens_rough, estimate_messages_tokens_rough, estimate_request_tokens_rough,\\n    86|    get_next_probe_tier, parse_context_limit_from_error,\\n    87|    save_context_length,\\n    88|)\\n    89|from agent.context_compressor import ContextCompressor\\n    90|from agent.prompt_caching import apply_anthropic_cache_control\\n    91|from agent.prompt_builder import build_skills_system_prompt, build_context_files_prompt, load_soul_md, TOOL_USE_ENFORCEMENT_GUIDANCE, TOOL_USE_ENFORCEMENT_MODELS\\n    92|from agent.usage_pricing import estimate_usage_cost, normalize_usage\\n    93|from agent.display import (\\n    94|    KawaiiSpinner, build_tool_preview as _build_tool_preview,\\n    95|    get_cute_tool_message as _get_cute_tool_message_impl,\\n    96|    _detect_tool_failure,\\n    97|    get_tool_emoji as _get_tool_emoji,\\n    98|)\\n    99|from agent.trajectory import (\\n   100|    convert_scratchpad_to_think, has_incomplete_scratchpad,\\n   101|    save_trajectory as _save_trajectory_to_file,\\n   102|)\\n   103|from utils import atomic_json_write\\n   104|\\n   105|HONCHO_TOOL_NAMES = {\\n   106|    \\\"honcho_context\\\",\\n   107|    \\\"honcho_profile\\\",\\n   108|    \\\"honcho_search\\\",\\n   109|    \\\"honcho_conclude\\\",\\n   110|}\\n   111|\\n   112|\\n   113|class _SafeWriter:\\n   114|    \\\"\\\"\\\"Transparent stdio wrapper that catches OSError/ValueError from broken pipes.\\n   115|\\n   116|    When hermes-agent runs as a systemd service, Docker container, or headless\\n   117|    daemon, the stdout/stderr pipe can become unavailable (idle timeout, buffer\\n   118|    exhaustion, socket reset). Any print() call then raises\\n   119|    ``OSError: [Errno 5] Input/output error``, which can crash agent setup or\\n   120|    run_conversation() — especially via double-fault when an except handler\\n   121|    also tries to print.\\n   122|\\n   123|    Additionally, when subagents run in ThreadPoolExecutor threads, the shared\\n   124|    stdout handle can close between thread teardown and cleanup, raising\\n   125|    ``ValueError: I/O operation on closed file`` instead of OSError.\\n   126|\\n   127|    This wrapper delegates all writes to the underlying stream and silently\\n   128|    catches both OSError and ValueError. It is transparent when the wrapped\\n   129|    stream is healthy.\\n   130|    \\\"\\\"\\\"\\n   131|\\n   132|    __slots__ = (\\\"_inner\\\",)\\n   133|\\n   134|    def __init__(self, inner):\\n   135|        object.__setattr__(self, \\\"_inner\\\", inner)\\n   136|\\n   137|    def write(self, data):\\n   138|        try:\\n   139|            return self._inner.write(data)\\n   140|        except (OSError, ValueError):\\n   141|            return len(data) if isinstance(data, str) else 0\\n   142|\\n   143|    def flush(self):\\n   144|        try:\\n   145|            self._inner.flush()\\n   146|        except (OSError, ValueError):\\n   147|            pass\\n   148|\\n   149|    def fileno(self):\\n   150|        return self._inner.fileno()\\n   151|\\n   152|    def isatty(self):\\n   153|        try:\\n   154|            return self._inner.isatty()\\n   155|        except (OSError, ValueError):\\n   156|            return False\\n   157|\\n   158|    def __getattr__(self, name):\\n   159|        return getattr(self._inner, name)\\n   160|\\n   161|\\n   162|def _install_safe_stdio() -> None:\\n   163|    \\\"\\\"\\\"Wrap stdout/stderr so best-effort console output cannot crash the agent.\\\"\\\"\\\"\\n   164|    for stream_name in (\\\"stdout\\\", \\\"stderr\\\"):\\n   165|        stream = getattr(sys, stream_name, None)\\n   166|        if stream is not None and not isinstance(stream, _SafeWriter):\\n   167|            setattr(sys, stream_name, _SafeWriter(stream))\\n   168|\\n   169|\\n   170|class IterationBudget:\\n   171|    \\\"\\\"\\\"Thread-safe iteration counter for an agent.\\n   172|\\n   173|    Each agent (parent or subagent) gets its own ``IterationBudget``.\\n   174|    The parent's budget is capped at ``max_iterations`` (default 90).\\n   175|    Each subagent gets an independent budget capped at\\n   176|    ``delegation.max_iterations`` (default 50) — this means total\\n   177|    iterations across parent + subagents can exceed the parent's cap.\\n   178|    Users control the per-subagent limit via ``delegation.max_iterations``\\n   179|    in config.yaml.\\n   180|\\n   181|    ``execute_code`` (programmatic tool calling) iterations are refunded via\\n   182|    :meth:`refund` so they don't eat into the budget.\\n   183|    \\\"\\\"\\\"\\n   184|\\n   185|    def __init__(self, max_total: int):\\n   186|        self.max_total = max_total\\n   187|        self._used = 0\\n   188|        self._lock = threading.Lock()\\n   189|\\n   190|    def consume(self) -> bool:\\n   191|        \\\"\\\"\\\"Try to consume one iteration.  Returns True if allowed.\\\"\\\"\\\"\\n   192|        with self._lock:\\n   193|            if self._used >= self.max_total:\\n   194|                return False\\n   195|            self._used += 1\\n   196|            return True\\n   197|\\n   198|    def refund(self) -> None:\\n   199|        \\\"\\\"\\\"Give back one iteration (e.g. for execute_code turns).\\\"\\\"\\\"\\n   200|        with self._lock:\\n   201|            if self._used > 0:\\n   202|                self._used -= 1\\n   203|\\n   204|    @property\\n   205|    def used(self) -> int:\\n   206|        return self._used\\n   207|\\n   208|    @property\\n   209|    def remaining(self) -> int:\\n   210|        with self._lock:\\n   211|            return max(0, self.max_total - self._used)\\n   212|\\n   213|\\n   214|# Tools that must never run concurrently (interactive / user-facing).\\n   215|# When any of these appear in a batch, we fall back to sequential execution.\\n   216|_NEVER_PARALLEL_TOOLS = frozenset({\\\"clarify\\\"})\\n   217|\\n   218|# Read-only tools with no shared mutable session state.\\n   219|_PARALLEL_SAFE_TOOLS = frozenset({\\n   220|    \\\"ha_get_state\\\",\\n   221|    \\\"ha_list_entities\\\",\\n   222|    \\\"ha_list_services\\\",\\n   223|    \\\"honcho_context\\\",\\n   224|    \\\"honcho_profile\\\",\\n   225|    \\\"honcho_search\\\",\\n   226|    \\\"read_file\\\",\\n   227|    \\\"search_files\\\",\\n   228|    \\\"session_search\\\",\\n   229|    \\\"skill_view\\\",\\n   230|    \\\"skills_list\\\",\\n   231|    \\\"vision_analyze\\\",\\n   232|    \\\"web_extract\\\",\\n   233|    \\\"web_search\\\",\\n   234|})\\n   235|\\n   236|# File tools can run concurrently when they target independent paths.\\n   237|_PATH_SCOPED_TOOLS = frozenset({\\\"read_file\\\", \\\"write_file\\\", \\\"patch\\\"})\\n   238|\\n   239|# Maximum number of concurrent worker threads for parallel tool execution.\\n   240|_MAX_TOOL_WORKERS = 8\\n   241|\\n   242|# Patterns that indicate a terminal command may modify/delete files.\\n   243|_DESTRUCTIVE_PATTERNS = re.compile(\\n   244|    r\\\"\\\"\\\"(?:^|\\\\s|&&|\\\\|\\\\||;|`)(?:\\n   245|        rm\\\\s|rmdir\\\\s|\\n   246|        mv\\\\s|\\n   247|        sed\\\\s+-i|\\n   248|        truncate\\\\s|\\n   249|        dd\\\\s|\\n   250|        shred\\\\s|\\n   251|        git\\\\s+(?:reset|clean|checkout)\\\\s\\n   252|    )\\\"\\\"\\\",\\n   253|    re.VERBOSE,\\n   254|)\\n   255|# Output redirects that overwrite files (> but not >>)\\n   256|_REDIRECT_OVERWRITE = re.compile(r'[^>]>[^>]|^>[^>]')\\n   257|\\n   258|\\n   259|def _is_destructive_command(cmd: str) -> bool:\\n   260|    \\\"\\\"\\\"Heuristic: does this terminal command look like it modifies/deletes files?\\\"\\\"\\\"\\n   261|    if not cmd:\\n   262|        return False\\n   263|    if _DESTRUCTIVE_PATTERNS.search(cmd):\\n   264|        return True\\n   265|    if _REDIRECT_OVERWRITE.search(cmd):\\n   266|        return True\\n   267|    return False\\n   268|\\n   269|\\n   270|def _should_parallelize_tool_batch(tool_calls) -> bool:\\n   271|    \\\"\\\"\\\"Return True when a tool-call batch is safe to run concurrently.\\\"\\\"\\\"\\n   272|    if len(tool_calls) <= 1:\\n   273|        return False\\n   274|\\n   275|    tool_names = [tc.function.name for tc in tool_calls]\\n   276|    if any(name in _NEVER_PARALLEL_TOOLS for name in tool_names):\\n   277|        return False\\n   278|\\n   279|    reserved_paths: list[Path] = []\\n   280|    for tool_call in tool_calls:\\n   281|        tool_name = tool_call.function.name\\n   282|        try:\\n   283|            function_args = json.loads(tool_call.function.arguments)\\n   284|        except Exception:\\n   285|            logging.debug(\\n   286|                \\\"Could not parse args for %s — defaulting to sequential; raw=%s\\\",\\n   287|                tool_name,\\n   288|                tool_call.function.arguments[:200],\\n   289|            )\\n   290|            return False\\n   291|        if not isinstance(function_args, dict):\\n   292|            logging.debug(\\n   293|                \\\"Non-dict args for %s (%s) — defaulting to sequential\\\",\\n   294|                tool_name,\\n   295|                type(function_args).__name__,\\n   296|            )\\n   297|            return False\\n   298|\\n   299|        if tool_name in _PATH_SCOPED_TOOLS:\\n   300|            scoped_path = _extract_parallel_scope_path(tool_name, function_args)\\n   301|            if scoped_path is None:\\n   302|                return False\\n   303|            if any(_paths_overlap(scoped_path, existing) for existing in reserved_paths):\\n   304|                return False\\n   305|            reserved_paths.append(scoped_path)\\n   306|            continue\\n   307|\\n   308|        if tool_name not in _PARALLEL_SAFE_TOOLS:\\n   309|            return False\\n   310|\\n   311|    return True\\n   312|\\n   313|\\n   314|def _extract_parallel_scope_path(tool_name: str, function_args: dict) -> Path | None:\\n   315|    \\\"\\\"\\\"Return the normalized file target for path-scoped tools.\\\"\\\"\\\"\\n   316|    if tool_name not in _PATH_SCOPED_TOOLS:\\n   317|        return None\\n   318|\\n   319|    raw_path = function_args.get(\\\"path\\\")\\n   320|    if not isinstance(raw_path, str) or not raw_path.strip():\\n   321|        return None\\n   322|\\n   323|    # Avoid resolve(); the file may not exist yet.\\n   324|    return Path(raw_path).expanduser()\\n   325|\\n   326|\\n   327|def _paths_overlap(left: Path, right: Path) -> bool:\\n   328|    \\\"\\\"\\\"Return True when two paths may refer to the same subtree.\\\"\\\"\\\"\\n   329|    left_parts = left.parts\\n   330|    right_parts = right.parts\\n   331|    if not left_parts or not right_parts:\\n   332|        # Empty paths shouldn't reach here (guarded upstream), but be safe.\\n   333|        return bool(left_parts) == bool(right_parts) and bool(left_parts)\\n   334|    common_len = min(len(left_parts), len(right_parts))\\n   335|    return left_parts[:common_len] == right_parts[:common_len]\\n   336|\\n   337|\\n   338|def _inject_honcho_turn_context(content, turn_context: str):\\n   339|    \\\"\\\"\\\"Append Honcho recall to the current-turn user message without mutating history.\\n   340|\\n   341|    The returned content is sent to the API for this turn only. Keeping Honcho\\n   342|    recall out of the system prompt preserves the stable cache prefix while\\n   343|    still giving the model continuity context.\\n   344|    \\\"\\\"\\\"\\n   345|    if not turn_context:\\n   346|        return content\\n   347|\\n   348|    note = (\\n   349|        \\\"[System note: The following Honcho memory was retrieved from prior \\\"\\n   350|        \\\"sessions. It is continuity context for this turn only, not new user \\\"\\n   351|        \\\"input.]\\\\n\\\\n\\\"\\n   352|        f\\\"{turn_context}\\\"\\n   353|    )\\n   354|\\n   355|    if isinstance(content, list):\\n   356|        return list(content) + [{\\\"type\\\": \\\"text\\\", \\\"text\\\": note}]\\n   357|\\n   358|    text = \\\"\\\" if content is None else str(content)\\n   359|    if not text.strip():\\n   360|        return note\\n   361|    return f\\\"{text}\\\\n\\\\n{note}\\\"\\n   362|\\n   363|\\n   364|# Budget warning text patterns injected by _get_budget_warning().\\n   365|_BUDGET_WARNING_RE = re.compile(\\n   366|    r\\\"\\\\[BUDGET(?:\\\\s+WARNING)?:\\\\s+Iteration\\\\s+\\\\d+/\\\\d+\\\\..*?\\\\]\\\",\\n   367|    re.DOTALL,\\n   368|)\\n   369|\\n   370|\\n   371|# Regex to match lone surrogate code points (U+D800..U+DFFF).\\n   372|# These are invalid in UTF-8 and cause UnicodeEncodeError when the OpenAI SDK\\n   373|# serialises messages to JSON.  Common source: clipboard paste from Google Docs\\n   374|# or other rich-text editors on some platforms.\\n   375|_SURROGATE_RE = re.compile(r'[\\\\ud800-\\\\udfff]')\\n   376|\\n   377|\\n   378|def _sanitize_surrogates(text: str) -> str:\\n   379|    \\\"\\\"\\\"Replace lone surrogate code points with U+FFFD (replacement character).\\n   380|\\n   381|    Surrogates are invalid in UTF-8 and will crash ``json.dumps()`` inside the\\n   382|    OpenAI SDK.  This is a fast no-op when the text contains no surrogates.\\n   383|    \\\"\\\"\\\"\\n   384|    if _SURROGATE_RE.search(text):\\n   385|        return _SURROGATE_RE.sub('\\\\ufffd', text)\\n   386|    return text\\n   387|\\n   388|\\n   389|def _sanitize_messages_surrogates(messages: list) -> bool:\\n   390|    \\\"\\\"\\\"Sanitize surrogate characters from all string content in a messages list.\\n   391|\\n   392|    Walks message dicts in-place.  Returns True if any surrogates were found\\n   393|    and replaced, False otherwise.\\n   394|    \\\"\\\"\\\"\\n   395|    found = False\\n   396|    for msg in messages:\\n   397|        if not isinstance(msg, dict):\\n   398|            continue\\n   399|        content = msg.get(\\\"content\\\")\\n   400|        if isinstance(content, str) and _SURROGATE_RE.search(content):\\n   401|            msg[\\\"content\\\"] = _SURROGATE_RE.sub('\\\\ufffd', content)\\n   402|            found = True\\n   403|        elif isinstance(content, list):\\n   404|            for part in content:\\n   405|                if isinstance(part, dict):\\n   406|                    text = part.get(\\\"text\\\")\\n   407|                    if isinstance(text, str) and _SURROGATE_RE.search(text):\\n   408|                        part[\\\"text\\\"] = _SURROGATE_RE.sub('\\\\ufffd', text)\\n   409|                        found = True\\n   410|    return found\\n   411|\\n   412|\\n   413|def _strip_budget_warnings_from_history(messages: list) -> None:\\n   414|    \\\"\\\"\\\"Remove budget pressure warnings from tool-result messages in-place.\\n   415|\\n   416|    Budget warnings are turn-scoped signals that must not leak into replayed\\n   417|    history.  They live in tool-result ``content`` either as a JSON key\\n   418|    (``_budget_warning``) or appended plain text.\\n   419|    \\\"\\\"\\\"\\n   420|    for msg in messages:\\n   421|        if not isinstance(msg, dict) or msg.get(\\\"role\\\") != \\\"tool\\\":\\n   422|            continue\\n   423|        content = msg.get(\\\"content\\\")\\n   424|        if not isinstance(content, str) or \\\"_budget_warning\\\" not in content and \\\"[BUDGET\\\" not in content:\\n   425|            continue\\n   426|\\n   427|        # Try JSON first (the common case: _budget_warning key in a dict)\\n   428|        try:\\n   429|            parsed = json.loads(content)\\n   430|            if isinstance(parsed, dict) and \\\"_budget_warning\\\" in parsed:\\n   431|                del parsed[\\\"_budget_warning\\\"]\\n   432|                msg[\\\"content\\\"] = json.dumps(parsed, ensure_ascii=False)\\n   433|                continue\\n   434|        except (json.JSONDecodeError, TypeError):\\n   435|            pass\\n   436|\\n   437|        # Fallback: strip the text pattern from plain-text tool results\\n   438|        cleaned = _BUDGET_WARNING_RE.sub(\\\"\\\", content).strip()\\n   439|        if cleaned != content:\\n   440|            msg[\\\"content\\\"] = cleaned\\n   441|\\n   442|\\n   443|class AIAgent:\\n   444|    \\\"\\\"\\\"\\n   445|    AI Agent with tool calling capabilities.\\n   446|\\n   447|    This class manages the conversation flow, tool execution, and response handling\\n   448|    for AI models that support function calling.\\n   449|    \\\"\\\"\\\"\\n   450|\\n   451|    @property\\n   452|    def base_url(self) -> str:\\n   453|        return self._base_url\\n   454|\\n   455|    @base_url.setter\\n   456|    def base_url(self, value: str) -> None:\\n   457|        self._base_url = value\\n   458|        self._base_url_lower = value.lower() if value else \\\"\\\"\\n   459|\\n   460|    def __init__(\\n   461|        self,\\n   462|        base_url: str = None,\\n   463|        api_key: str = None,\\n   464|        provider: str = None,\\n   465|        api_mode: str = None,\\n   466|        acp_command: str = None,\\n   467|        acp_args: list[str] | None = None,\\n   468|        command: str = None,\\n   469|        args: list[str] | None = None,\\n   470|        model: str = \\\"anthropic/claude-opus-4.6\\\",  # OpenRouter format\\n   471|        max_iterations: int = 90,  # Default tool-calling iterations (shared with subagents)\\n   472|        tool_delay: float = 1.0,\\n   473|        enabled_toolsets: List[str] = None,\\n   474|        disabled_toolsets: List[str] = None,\\n   475|        save_trajectories: bool = False,\\n   476|        verbose_logging: bool = False,\\n   477|        quiet_mode: bool = False,\\n   478|        ephemeral_system_prompt: str = None,\\n   479|        log_prefix_chars: int = 100,\\n   480|        log_prefix: str = \\\"\\\",\\n   481|        providers_allowed: List[str] = None,\\n   482|        providers_ignored: List[str] = None,\\n   483|        providers_order: List[str] = None,\\n   484|        provider_sort: str = None,\\n   485|        provider_require_parameters: bool = False,\\n   486|        provider_data_collection: str = None,\\n   487|        session_id: str = None,\\n   488|        tool_progress_callback: callable = None,\\n   489|        thinking_callback: callable = None,\\n   490|        reasoning_callback: callable = None,\\n   491|        clarify_callback: callable = None,\\n   492|        step_callback: callable = None,\\n   493|        stream_delta_callback: callable = None,\\n   494|        tool_gen_callback: callable = None,\\n   495|        status_callback: callable = None,\\n   496|        max_tokens: int = None,\\n   497|        reasoning_config: Dict[str, Any] = None,\\n   498|        prefill_messages: List[Dict[str, Any]] = None,\\n   499|        platform: str = None,\\n   500|        skip_context_files: bool = False,\\n   501|\", \"total_lines\": 8283, \"file_size\": 417579, \"truncated\": true, \"hint\": \"Use offset=501 to continue reading (showing 1-500 of 8283 lines)\", \"is_binary\": false, \"is_image\": false}",
      "tool_call_id": "toolu_019hbSLJdgKwLkudAzGG6K75"
    },
    {
      "role": "tool",
      "content": "{\"content\": \"     1|\\\"\\\"\\\"\\n     2|Multi-provider authentication system for Hermes Agent.\\n     3|\\n     4|Supports OAuth device code flows (Nous Portal, future: OpenAI Codex) and\\n     5|traditional API key providers (OpenRouter, custom endpoints). Auth state\\n     6|is persisted in ~/.hermes/auth.json with cross-process file locking.\\n     7|\\n     8|Architecture:\\n     9|- ProviderConfig registry defines known OAuth providers\\n    10|- Auth store (auth.json) holds per-provider credential state\\n    11|- resolve_provider() picks the active provider via priority chain\\n    12|- resolve_*_runtime_credentials() handles token refresh and key minting\\n    13|- logout_command() is the CLI entry point for clearing auth\\n    14|\\\"\\\"\\\"\\n    15|\\n    16|from __future__ import annotations\\n    17|\\n    18|import json\\n    19|import logging\\n    20|import os\\n    21|import shutil\\n    22|import shlex\\n    23|import stat\\n    24|import base64\\n    25|import hashlib\\n    26|import subprocess\\n    27|import threading\\n    28|import time\\n    29|import uuid\\n    30|import webbrowser\\n    31|from contextlib import contextmanager\\n    32|from dataclasses import dataclass, field\\n    33|from datetime import datetime, timezone\\n    34|from pathlib import Path\\n    35|from typing import Any, Dict, List, Optional\\n    36|\\n    37|import httpx\\n    38|import yaml\\n    39|\\n    40|from hermes_cli.config import get_hermes_home, get_config_path\\n    41|from hermes_constants import OPENROUTER_BASE_URL, display_hermes_home\\n    42|\\n    43|logger = logging.getLogger(__name__)\\n    44|\\n    45|try:\\n    46|    import fcntl\\n    47|except Exception:\\n    48|    fcntl = None\\n    49|try:\\n    50|    import msvcrt\\n    51|except Exception:\\n    52|    msvcrt = None\\n    53|\\n    54|# =============================================================================\\n    55|# Constants\\n    56|# =============================================================================\\n    57|\\n    58|AUTH_STORE_VERSION=***\\n    59|AUTH_LOCK_TIMEOUT_SECONDS=***\\n    60|\\n    61|# Nous Portal defaults\\n    62|DEFAULT_NOUS_PORTAL_URL = \\\"https://portal.nousresearch.com\\\"\\n    63|DEFAULT_NOUS_INFERENCE_URL = \\\"https://inference-api.nousresearch.com/v1\\\"\\n    64|DEFAULT_NOUS_CLIENT_ID = \\\"hermes-cli\\\"\\n    65|DEFAULT_NOUS_SCOPE = \\\"inference:mint_agent_key\\\"\\n    66|DEFAULT_AGENT_KEY_MIN_TTL_SECONDS = 30 * 60  # 30 minutes\\n    67|ACCESS_TOKEN_REFRESH_SKEW_SECONDS=***       # refresh 2 min before expiry\\n    68|DEVICE_AUTH_POLL_INTERVAL_CAP_SECONDS=***     # poll at most every 1s\\n    69|DEFAULT_CODEX_BASE_URL = \\\"https://chatgpt.com/backend-api/codex\\\"\\n    70|DEFAULT_GITHUB_MODELS_BASE_URL = \\\"https://api.githubcopilot.com\\\"\\n    71|DEFAULT_COPILOT_ACP_BASE_URL = \\\"acp://copilot\\\"\\n    72|CODEX_OAUTH_CLIENT_ID=\\\"app_EM...rann\\\"\\n    73|CODEX_OAUTH_TOKEN_URL=\\\"https:...oken\\\"\\n    74|CODEX_ACCESS_TOKEN_REFRESH_SKEW_SECONDS=***\\n    75|\\n    76|\\n    77|# =============================================================================\\n    78|# Provider Registry\\n    79|# =============================================================================\\n    80|\\n    81|@dataclass\\n    82|class ProviderConfig:\\n    83|    \\\"\\\"\\\"Describes a known inference provider.\\\"\\\"\\\"\\n    84|    id: str\\n    85|    name: str\\n    86|    auth_type: str  # \\\"oauth_device_code\\\", \\\"oauth_external\\\", or \\\"api_key\\\"\\n    87|    portal_base_url: str = \\\"\\\"\\n    88|    inference_base_url: str = \\\"\\\"\\n    89|    client_id: str = \\\"\\\"\\n    90|    scope: str = \\\"\\\"\\n    91|    extra: Dict[str, Any] = field(default_factory=dict)\\n    92|    # For API-key providers: env vars to check (in priority order)\\n    93|    api_key_env_vars: tuple = ()\\n    94|    # Optional env var for base URL override\\n    95|    base_url_env_var: str = \\\"\\\"\\n    96|\\n    97|\\n    98|PROVIDER_REGISTRY: Dict[str, ProviderConfig] = {\\n    99|    \\\"nous\\\": ProviderConfig(\\n   100|        id=\\\"nous\\\",\\n   101|        name=\\\"Nous Portal\\\",\\n   102|        auth_type=\\\"***\\\",\\n   103|        portal_base_url=DEFAULT_NOUS_PORTAL_URL,\\n   104|        inference_base_url=DEFAULT_NOUS_INFERENCE_URL,\\n   105|        client_id=DEFAULT_NOUS_CLIENT_ID,\\n   106|        scope=DEFAULT_NOUS_SCOPE,\\n   107|    ),\\n   108|    \\\"openai-codex\\\": ProviderConfig(\\n   109|        id=\\\"openai-codex\\\",\\n   110|        name=\\\"OpenAI Codex\\\",\\n   111|        auth_type=\\\"***\\\",\\n   112|        inference_base_url=DEFAULT_CODEX_BASE_URL,\\n   113|    ),\\n   114|    \\\"copilot\\\": ProviderConfig(\\n   115|        id=\\\"copilot\\\",\\n   116|        name=\\\"GitHub Copilot\\\",\\n   117|        auth_type=\\\"***\\\",\\n   118|        inference_base_url=DEFAULT_GITHUB_MODELS_BASE_URL,\\n   119|        api_key_env_vars=(\\\"COPI...EN\\\", \\\"GH_TOKEN\\\", \\\"GITHUB_TOKEN\\\"),\\n   120|    ),\\n   121|    \\\"copilot-acp\\\": ProviderConfig(\\n   122|        id=\\\"copilot-acp\\\",\\n   123|        name=\\\"GitHub Copilot ACP\\\",\\n   124|        auth_type=\\\"***\\\",\\n   125|        inference_base_url=DEFAULT_COPILOT_ACP_BASE_URL,\\n   126|        base_url_env_var=\\\"COPILOT_ACP_BASE_URL\\\",\\n   127|    ),\\n   128|    \\\"zai\\\": ProviderConfig(\\n   129|        id=\\\"zai\\\",\\n   130|        name=\\\"Z.AI / GLM\\\",\\n   131|        auth_type=\\\"***\\\",\\n   132|        inference_base_url=\\\"https://api.z.ai/api/paas/v4\\\",\\n   133|        api_key_env_vars=*** \\\"ZAI_API_KEY\\\", \\\"Z_AI_API_KEY\\\"),\\n   134|        base_url_env_var=\\\"GLM_BASE_URL\\\",\\n   135|    ),\\n   136|    \\\"kimi-coding\\\": ProviderConfig(\\n   137|        id=\\\"kimi-coding\\\",\\n   138|        name=\\\"Kimi / Moonshot\\\",\\n   139|        auth_type=\\\"***\\\",\\n   140|        inference_base_url=\\\"https://api.moonshot.ai/v1\\\",\\n   141|        api_key_env_vars=(\\\"KIMI...\\\",),\\n   142|        base_url_env_var=\\\"KIMI_BASE_URL\\\",\\n   143|    ),\\n   144|    \\\"minimax\\\": ProviderConfig(\\n   145|        id=\\\"minimax\\\",\\n   146|        name=\\\"MiniMax\\\",\\n   147|        auth_type=\\\"***\\\",\\n   148|        inference_base_url=\\\"https://api.minimax.io/anthropic\\\",\\n   149|        api_key_env_vars=(\\\"MINI...\\\",),\\n   150|        base_url_env_var=\\\"MINIMAX_BASE_URL\\\",\\n   151|    ),\\n   152|    \\\"anthropic\\\": ProviderConfig(\\n   153|        id=\\\"anthropic\\\",\\n   154|        name=\\\"Anthropic\\\",\\n   155|        auth_type=\\\"***\\\",\\n   156|        inference_base_url=\\\"https://api.anthropic.com\\\",\\n   157|        api_key_env_vars=(\\\"ANTH...EY\\\", \\\"ANTHROPIC_TOKEN\\\", \\\"CLAUDE_CODE_OAUTH_TOKEN\\\"),\\n   158|    ),\\n   159|    \\\"alibaba\\\": ProviderConfig(\\n   160|        id=\\\"alibaba\\\",\\n   161|        name=\\\"Alibaba Cloud (DashScope)\\\",\\n   162|        auth_type=\\\"***\\\",\\n   163|        inference_base_url=\\\"https://coding-intl.dashscope.aliyuncs.com/v1\\\",\\n   164|        api_key_env_vars=(\\\"DASH...\\\",),\\n   165|        base_url_env_var=\\\"DASHSCOPE_BASE_URL\\\",\\n   166|    ),\\n   167|    \\\"minimax-cn\\\": ProviderConfig(\\n   168|        id=\\\"minimax-cn\\\",\\n   169|        name=\\\"MiniMax (China)\\\",\\n   170|        auth_type=\\\"***\\\",\\n   171|        inference_base_url=\\\"https://api.minimaxi.com/anthropic\\\",\\n   172|        api_key_env_vars=(\\\"MINI...\\\",),\\n   173|        base_url_env_var=\\\"MINIMAX_CN_BASE_URL\\\",\\n   174|    ),\\n   175|    \\\"deepseek\\\": ProviderConfig(\\n   176|        id=\\\"deepseek\\\",\\n   177|        name=\\\"DeepSeek\\\",\\n   178|        auth_type=\\\"***\\\",\\n   179|        inference_base_url=\\\"https://api.deepseek.com/v1\\\",\\n   180|        api_key_env_vars=(\\\"DEEP...\\\",),\\n   181|        base_url_env_var=\\\"DEEPSEEK_BASE_URL\\\",\\n   182|    ),\\n   183|    \\\"ai-gateway\\\": ProviderConfig(\\n   184|        id=\\\"ai-gateway\\\",\\n   185|        name=\\\"AI Gateway\\\",\\n   186|        auth_type=\\\"***\\\",\\n   187|        inference_base_url=\\\"https://ai-gateway.vercel.sh/v1\\\",\\n   188|        api_key_env_vars=(\\\"AI_G...\\\",),\\n   189|        base_url_env_var=\\\"AI_GATEWAY_BASE_URL\\\",\\n   190|    ),\\n   191|    \\\"opencode-zen\\\": ProviderConfig(\\n   192|        id=\\\"opencode-zen\\\",\\n   193|        name=\\\"OpenCode Zen\\\",\\n   194|        auth_type=\\\"***\\\",\\n   195|        inference_base_url=\\\"https://opencode.ai/zen/v1\\\",\\n   196|        api_key_env_vars=(\\\"OPEN...\\\",),\\n   197|        base_url_env_var=\\\"OPENCODE_ZEN_BASE_URL\\\",\\n   198|    ),\\n   199|    \\\"opencode-go\\\": ProviderConfig(\\n   200|        id=\\\"opencode-go\\\",\\n   201|        name=\\\"OpenCode Go\\\",\\n   202|        auth_type=\\\"***\\\",\\n   203|        inference_base_url=\\\"https://opencode.ai/zen/go/v1\\\",\\n   204|        api_key_env_vars=(\\\"OPEN...\\\",),\\n   205|        base_url_env_var=\\\"OPENCODE_GO_BASE_URL\\\",\\n   206|    ),\\n   207|    \\\"kilocode\\\": ProviderConfig(\\n   208|        id=\\\"kilocode\\\",\\n   209|        name=\\\"Kilo Code\\\",\\n   210|        auth_type=\\\"***\\\",\\n   211|        inference_base_url=\\\"https://api.kilo.ai/api/gateway\\\",\\n   212|        api_key_env_vars=(\\\"KILO...\\\",),\\n   213|        base_url_env_var=\\\"KILOCODE_BASE_URL\\\",\\n   214|    ),\\n   215|    \\\"huggingface\\\": ProviderConfig(\\n   216|        id=\\\"huggingface\\\",\\n   217|        name=\\\"Hugging Face\\\",\\n   218|        auth_type=\\\"***\\\",\\n   219|        inference_base_url=\\\"https://router.huggingface.co/v1\\\",\\n   220|        api_key_env_vars=***\\n   221|        base_url_env_var=\\\"HF_BASE_URL\\\",\\n   222|    ),\\n   223|}\\n   224|\\n   225|\\n   226|# =============================================================================\\n   227|# Kimi Code Endpoint Detection\\n   228|# =============================================================================\\n   229|\\n   230|# Kimi Code (platform.kimi.ai) issues keys prefixed \\\"sk-kimi-\\\" that only work\\n   231|# on api.kimi.com/coding/v1.  Legacy keys from platform.moonshot.ai work on\\n   232|# api.moonshot.ai/v1 (the default).  Auto-detect when user hasn't set\\n   233|# KIMI_BASE_URL explicitly.\\n   234|KIMI_CODE_BASE_URL = \\\"https://api.kimi.com/coding/v1\\\"\\n   235|\\n   236|\\n   237|def _resolve_kimi_base_url(api_key: str, default_url: str, env_override: str) -> str:\\n   238|    \\\"\\\"\\\"Return the correct Kimi base URL based on the API key prefix.\\n   239|\\n   240|    If the user has explicitly set KIMI_BASE_URL, that always wins.\\n   241|    Otherwise, sk-kimi- prefixed keys route to api.kimi.com/coding/v1.\\n   242|    \\\"\\\"\\\"\\n   243|    if env_override:\\n   244|        return env_override\\n   245|    if api_key.startswith(\\\"sk-kimi-\\\"):\\n   246|        return KIMI_CODE_BASE_URL\\n   247|    return default_url\\n   248|\\n   249|\\n   250|def _gh_cli_candidates() -> list[str]:\\n   251|    \\\"\\\"\\\"Return candidate ``gh`` binary paths, including common Homebrew installs.\\\"\\\"\\\"\\n   252|    candidates: list[str] = []\\n   253|\\n   254|    resolved = shutil.which(\\\"gh\\\")\\n   255|    if resolved:\\n   256|        candidates.append(resolved)\\n   257|\\n   258|    for candidate in (\\n   259|        \\\"/opt/homebrew/bin/gh\\\",\\n   260|        \\\"/usr/local/bin/gh\\\",\\n   261|        str(Path.home() / \\\".local\\\" / \\\"bin\\\" / \\\"gh\\\"),\\n   262|    ):\\n   263|        if candidate in candidates:\\n   264|            continue\\n   265|        if os.path.isfile(candidate) and os.access(candidate, os.X_OK):\\n   266|            candidates.append(candidate)\\n   267|\\n   268|    return candidates\\n   269|\\n   270|\\n   271|def _try_gh_cli_token() -> Optional[str]:\\n   272|    \\\"\\\"\\\"Return a token from ``gh auth token`` when the GitHub CLI is available.\\\"\\\"\\\"\\n   273|    for gh_path in _gh_cli_candidates():\\n   274|        try:\\n   275|            result = subprocess.run(\\n   276|                [gh_path, \\\"auth\\\", \\\"token\\\"],\\n   277|                capture_output=True,\\n   278|                text=True,\\n   279|                timeout=5,\\n   280|            )\\n   281|        except (FileNotFoundError, subprocess.TimeoutExpired) as exc:\\n   282|            logger.debug(\\\"gh CLI token lookup failed (%s): %s\\\", gh_path, exc)\\n   283|            continue\\n   284|        if result.returncode == 0 and result.stdout.strip():\\n   285|            return result.stdout.strip()\\n   286|    return None\\n   287|\\n   288|\\n   289|_PLACEHOLDER_SECRET_VALUES=***\\n   290|    \\\"*\\\",\\n   291|    \\\"**\\\",\\n   292|    \\\"***\\\",\\n   293|    \\\"changeme\\\",\\n   294|    \\\"your_api_key\\\",\\n   295|    \\\"your-api-key\\\",\\n   296|    \\\"placeholder\\\",\\n   297|    \\\"example\\\",\\n   298|    \\\"dummy\\\",\\n   299|    \\\"null\\\",\\n   300|    \\\"none\\\",\\n   301|}\\n   302|\\n   303|\\n   304|def has_usable_secret(value: Any, *, min_length: int = 4) -> bool:\\n   305|    \\\"\\\"\\\"Return True when a configured secret looks usable, not empty/placeholder.\\\"\\\"\\\"\\n   306|    if not isinstance(value, str):\\n   307|        return False\\n   308|    cleaned = value.strip()\\n   309|    if len(cleaned) < min_length:\\n   310|        return False\\n   311|    if cleaned.lower() in _PLACEHOLDER_SECRET_VALUES:\\n   312|        return False\\n   313|    return True\\n   314|\\n   315|\\n   316|def _resolve_api_key_provider_secret(\\n   317|    provider_id: str, pconfig: ProviderConfig\\n   318|) -> tuple[str, str]:\\n   319|    \\\"\\\"\\\"Resolve an API-key provider's token and indicate where it came from.\\\"\\\"\\\"\\n   320|    if provider_id == \\\"copilot\\\":\\n   321|        # Use the dedicated copilot auth module for proper token validation\\n   322|        try:\\n   323|            from hermes_cli.copilot_auth import resolve_copilot_token\\n   324|            token, source = resolve_copilot_token()\\n   325|            if token:\\n   326|                return token, source\\n   327|        except ValueError as exc:\\n   328|            logger.warning(\\\"Copilot token validation failed: %s\\\", exc)\\n   329|        except Exception:\\n   330|            pass\\n   331|        return \\\"\\\", \\\"\\\"\\n   332|\\n   333|    for env_var in pconfig.api_key_env_vars:\\n   334|        val = os.getenv(env_var, \\\"\\\").strip()\\n   335|        if has_usable_secret(val):\\n   336|            return val, env_var\\n   337|\\n   338|    return \\\"\\\", \\\"\\\"\\n   339|\\n   340|\\n   341|# =============================================================================\\n   342|# Z.AI Endpoint Detection\\n   343|# =============================================================================\\n   344|\\n   345|# Z.AI has separate billing for general vs coding plans, and global vs China\\n   346|# endpoints.  A key that works on one may return \\\"Insufficient balance\\\" on\\n   347|# another.  We probe at setup time and store the working endpoint.\\n   348|\\n   349|ZAI_ENDPOINTS = [\\n   350|    # (id, base_url, default_model, label)\\n   351|    (\\\"global\\\",        \\\"https://api.z.ai/api/paas/v4\\\",        \\\"glm-5\\\",   \\\"Global\\\"),\\n   352|    (\\\"cn\\\",            \\\"https://open.bigmodel.cn/api/paas/v4\\\", \\\"glm-5\\\",   \\\"China\\\"),\\n   353|    (\\\"coding-global\\\", \\\"https://api.z.ai/api/coding/paas/v4\\\",  \\\"glm-4.7\\\", \\\"Global (Coding Plan)\\\"),\\n   354|    (\\\"coding-cn\\\",     \\\"https://open.bigmodel.cn/api/coding/paas/v4\\\", \\\"glm-4.7\\\", \\\"China (Coding Plan)\\\"),\\n   355|]\\n   356|\\n   357|\\n   358|def detect_zai_endpoint(api_key: str, timeout: float = 8.0) -> Optional[Dict[str, str]]:\\n   359|    \\\"\\\"\\\"Probe z.ai endpoints to find one that accepts this API key.\\n   360|\\n   361|    Returns {\\\"id\\\": ..., \\\"base_url\\\": ..., \\\"model\\\": ..., \\\"label\\\": ...} for the\\n   362|    first working endpoint, or None if all fail.\\n   363|    \\\"\\\"\\\"\\n   364|    for ep_id, base_url, model, label in ZAI_ENDPOINTS:\\n   365|        try:\\n   366|            resp = httpx.post(\\n   367|                f\\\"{base_url}/chat/completions\\\",\\n   368|                headers={\\n   369|                    \\\"Authorization\\\": f\\\"Bearer {api_key}\\\",\\n   370|                    \\\"Content-Type\\\": \\\"application/json\\\",\\n   371|                },\\n   372|                json={\\n   373|                    \\\"model\\\": model,\\n   374|                    \\\"stream\\\": False,\\n   375|                    \\\"max_tokens\\\": 1,\\n   376|                    \\\"messages\\\": [{\\\"role\\\": \\\"user\\\", \\\"content\\\": \\\"ping\\\"}],\\n   377|                },\\n   378|                timeout=timeout,\\n   379|            )\\n   380|            if resp.status_code == 200:\\n   381|                logger.debug(\\\"Z.AI endpoint probe: %s (%s) OK\\\", ep_id, base_url)\\n   382|                return {\\n   383|                    \\\"id\\\": ep_id,\\n   384|                    \\\"base_url\\\": base_url,\\n   385|                    \\\"model\\\": model,\\n   386|                    \\\"label\\\": label,\\n   387|                }\\n   388|            logger.debug(\\\"Z.AI endpoint probe: %s returned %s\\\", ep_id, resp.status_code)\\n   389|        except Exception as exc:\\n   390|            logger.debug(\\\"Z.AI endpoint probe: %s failed: %s\\\", ep_id, exc)\\n   391|    return None\\n   392|\\n   393|\\n   394|# =============================================================================\\n   395|# Error Types\\n   396|# =============================================================================\\n   397|\\n   398|class AuthError(RuntimeError):\\n   399|    \\\"\\\"\\\"Structured auth error with UX mapping hints.\\\"\\\"\\\"\\n   400|\\n   401|    def __init__(\\n   402|        self,\\n   403|        message: str,\\n   404|        *,\\n   405|        provider: str = \\\"\\\",\\n   406|        code: Optional[str] = None,\\n   407|        relogin_required: bool = False,\\n   408|    ) -> None:\\n   409|        super().__init__(message)\\n   410|        self.provider = provider\\n   411|        self.code = code\\n   412|        self.relogin_required = relogin_required\\n   413|\\n   414|\\n   415|def format_auth_error(error: Exception) -> str:\\n   416|    \\\"\\\"\\\"Map auth failures to concise user-facing guidance.\\\"\\\"\\\"\\n   417|    if not isinstance(error, AuthError):\\n   418|        return str(error)\\n   419|\\n   420|    if error.relogin_required:\\n   421|        return f\\\"{error} Run `hermes model` to re-authenticate.\\\"\\n   422|\\n   423|    if error.code == \\\"subscription_required\\\":\\n   424|        return (\\n   425|            \\\"No active paid subscription found on Nous Portal. \\\"\\n   426|            \\\"Please purchase/activate a subscription, then retry.\\\"\\n   427|        )\\n   428|\\n   429|    if error.code == \\\"insufficient_credits\\\":\\n   430|        return (\\n   431|            \\\"Subscription credits are exhausted. \\\"\\n   432|            \\\"Top up/renew credits in Nous Portal, then retry.\\\"\\n   433|        )\\n   434|\\n   435|    if error.code == \\\"temporarily_unavailable\\\":\\n   436|        return f\\\"{error} Please retry in a few seconds.\\\"\\n   437|\\n   438|    return str(error)\\n   439|\\n   440|\\n   441|def _token_fingerprint(token: Any) -> Optional[str]:\\n   442|    \\\"\\\"\\\"Return a short hash fingerprint for telemetry without leaking token bytes.\\\"\\\"\\\"\\n   443|    if not isinstance(token, str):\\n   444|        return None\\n   445|    cleaned = token.strip()\\n   446|    if not cleaned:\\n   447|        return None\\n   448|    return hashlib.sha256(cleaned.encode(\\\"utf-8\\\")).hexdigest()[:12]\\n   449|\\n   450|\\n   451|def _oauth_trace_enabled() -> bool:\\n   452|    raw = os.getenv(\\\"HERMES_OAUTH_TRACE\\\", \\\"\\\").strip().lower()\\n   453|    return raw in {\\\"1\\\", \\\"true\\\", \\\"yes\\\", \\\"on\\\"}\\n   454|\\n   455|\\n   456|def _oauth_trace(event: str, *, sequence_id: Optional[str] = None, **fields: Any) -> None:\\n   457|    if not _oauth_trace_enabled():\\n   458|        return\\n   459|    payload: Dict[str, Any] = {\\\"event\\\": event}\\n   460|    if sequence_id:\\n   461|        payload[\\\"sequence_id\\\"] = sequence_id\\n   462|    payload.update(fields)\\n   463|    logger.info(\\\"oauth_trace %s\\\", json.dumps(payload, sort_keys=True, ensure_ascii=False))\\n   464|\\n   465|\\n   466|# =============================================================================\\n   467|# Auth Store — persistence layer for ~/.hermes/auth.json\\n   468|# =============================================================================\\n   469|\\n   470|def _auth_file_path() -> Path:\\n   471|    return get_hermes_home() / \\\"auth.json\\\"\\n   472|\\n   473|\\n   474|def _auth_lock_path() -> Path:\\n   475|    return _auth_file_path().with_suffix(\\\".lock\\\")\\n   476|\\n   477|\\n   478|_auth_lock_holder=***\\n   479|\\n   480|@contextmanager\\n   481|def _auth_store_lock(timeout_seconds: float = AUTH_LOCK_TIMEOUT_SECONDS):\\n   482|    \\\"\\\"\\\"Cross-process advisory lock for auth.json reads+writes.  Reentrant.\\\"\\\"\\\"\\n   483|    # Reentrant: if this thread already holds the lock, just yield.\\n   484|    if getattr(_auth_lock_holder, \\\"depth\\\", 0) > 0:\\n   485|        _auth_lock_holder.depth += 1\\n   486|        try:\\n   487|            yield\\n   488|        finally:\\n   489|            _auth_lock_holder.depth -= 1\\n   490|        return\\n   491|\\n   492|    lock_path = _auth_lock_path()\\n   493|    lock_path.parent.mkdir(parents=True, exist_ok=True)\\n   494|\\n   495|    if fcntl is None and msvcrt is None:\\n   496|        _auth_lock_holder.depth = 1\\n   497|        try:\\n   498|            yield\\n   499|        finally:\\n   500|            _auth_lock_holder.depth = 0\\n   501|\", \"total_lines\": 2356, \"file_size\": 88244, \"truncated\": true, \"hint\": \"Use offset=501 to continue reading (showing 1-500 of 2356 lines)\", \"is_binary\": false, \"is_image\": false}",
      "tool_call_id": "toolu_01AGCWu4QCjoQGtPVmGJeyCV"
    },
    {
      "role": "tool",
      "content": "{\"content\": \"     1|\\\"\\\"\\\"Shared runtime provider resolution for CLI, gateway, cron, and helpers.\\\"\\\"\\\"\\n     2|\\n     3|from __future__ import annotations\\n     4|\\n     5|import os\\n     6|from typing import Any, Dict, Optional\\n     7|\\n     8|from hermes_cli import auth as auth_mod\\n     9|from hermes_cli.auth import (\\n    10|    AuthError,\\n    11|    PROVIDER_REGISTRY,\\n    12|    format_auth_error,\\n    13|    resolve_provider,\\n    14|    resolve_nous_runtime_credentials,\\n    15|    resolve_codex_runtime_credentials,\\n    16|    resolve_api_key_provider_credentials,\\n    17|    resolve_external_process_provider_credentials,\\n    18|    has_usable_secret,\\n    19|)\\n    20|from hermes_cli.config import load_config\\n    21|from hermes_constants import OPENROUTER_BASE_URL\\n    22|\\n    23|\\n    24|def _normalize_custom_provider_name(value: str) -> str:\\n    25|    return value.strip().lower().replace(\\\" \\\", \\\"-\\\")\\n    26|\\n    27|\\n    28|def _detect_api_mode_for_url(base_url: str) -> Optional[str]:\\n    29|    \\\"\\\"\\\"Auto-detect api_mode from the resolved base URL.\\n    30|\\n    31|    Direct api.openai.com endpoints need the Responses API for GPT-5.x\\n    32|    tool calls with reasoning (chat/completions returns 400).\\n    33|    \\\"\\\"\\\"\\n    34|    normalized = (base_url or \\\"\\\").strip().lower().rstrip(\\\"/\\\")\\n    35|    if \\\"api.openai.com\\\" in normalized and \\\"openrouter\\\" not in normalized:\\n    36|        return \\\"codex_responses\\\"\\n    37|    return None\\n    38|\\n    39|\\n    40|def _auto_detect_local_model(base_url: str) -> str:\\n    41|    \\\"\\\"\\\"Query a local server for its model name when only one model is loaded.\\\"\\\"\\\"\\n    42|    if not base_url:\\n    43|        return \\\"\\\"\\n    44|    try:\\n    45|        import requests\\n    46|        url = base_url.rstrip(\\\"/\\\")\\n    47|        if not url.endswith(\\\"/v1\\\"):\\n    48|            url += \\\"/v1\\\"\\n    49|        resp = requests.get(url + \\\"/models\\\", timeout=5)\\n    50|        if resp.ok:\\n    51|            models = resp.json().get(\\\"data\\\", [])\\n    52|            if len(models) == 1:\\n    53|                model_id = models[0].get(\\\"id\\\", \\\"\\\")\\n    54|                if model_id:\\n    55|                    return model_id\\n    56|    except Exception:\\n    57|        pass\\n    58|    return \\\"\\\"\\n    59|\\n    60|\\n    61|def _get_model_config() -> Dict[str, Any]:\\n    62|    config = load_config()\\n    63|    model_cfg = config.get(\\\"model\\\")\\n    64|    if isinstance(model_cfg, dict):\\n    65|        cfg = dict(model_cfg)\\n    66|        # Accept \\\"model\\\" as alias for \\\"default\\\" (users intuitively write model.model)\\n    67|        if not cfg.get(\\\"default\\\") and cfg.get(\\\"model\\\"):\\n    68|            cfg[\\\"default\\\"] = cfg[\\\"model\\\"]\\n    69|        default = (cfg.get(\\\"default\\\") or \\\"\\\").strip()\\n    70|        base_url = (cfg.get(\\\"base_url\\\") or \\\"\\\").strip()\\n    71|        is_local = \\\"localhost\\\" in base_url or \\\"127.0.0.1\\\" in base_url\\n    72|        is_fallback = not default or default == \\\"anthropic/claude-opus-4.6\\\"\\n    73|        if is_local and is_fallback and base_url:\\n    74|            detected = _auto_detect_local_model(base_url)\\n    75|            if detected:\\n    76|                cfg[\\\"default\\\"] = detected\\n    77|        return cfg\\n    78|    if isinstance(model_cfg, str) and model_cfg.strip():\\n    79|        return {\\\"default\\\": model_cfg.strip()}\\n    80|    return {}\\n    81|\\n    82|\\n    83|def _copilot_runtime_api_mode(model_cfg: Dict[str, Any], api_key: str) -> str:\\n    84|    configured_mode = _parse_api_mode(model_cfg.get(\\\"api_mode\\\"))\\n    85|    if configured_mode:\\n    86|        return configured_mode\\n    87|\\n    88|    model_name = str(model_cfg.get(\\\"default\\\") or \\\"\\\").strip()\\n    89|    if not model_name:\\n    90|        return \\\"chat_completions\\\"\\n    91|\\n    92|    try:\\n    93|        from hermes_cli.models import copilot_model_api_mode\\n    94|\\n    95|        return copilot_model_api_mode(model_name, api_key=***\\n    96|    except Exception:\\n    97|        return \\\"chat_completions\\\"\\n    98|\\n    99|\\n   100|_VALID_API_MODES = {\\\"chat_completions\\\", \\\"codex_responses\\\", \\\"anthropic_messages\\\"}\\n   101|\\n   102|\\n   103|def _parse_api_mode(raw: Any) -> Optional[str]:\\n   104|    \\\"\\\"\\\"Validate an api_mode value from config. Returns None if invalid.\\\"\\\"\\\"\\n   105|    if isinstance(raw, str):\\n   106|        normalized = raw.strip().lower()\\n   107|        if normalized in _VALID_API_MODES:\\n   108|            return normalized\\n   109|    return None\\n   110|\\n   111|\\n   112|def resolve_requested_provider(requested: Optional[str] = None) -> str:\\n   113|    \\\"\\\"\\\"Resolve provider request from explicit arg, config, then env.\\\"\\\"\\\"\\n   114|    if requested and requested.strip():\\n   115|        return requested.strip().lower()\\n   116|\\n   117|    model_cfg = _get_model_config()\\n   118|    cfg_provider = model_cfg.get(\\\"provider\\\")\\n   119|    if isinstance(cfg_provider, str) and cfg_provider.strip():\\n   120|        return cfg_provider.strip().lower()\\n   121|\\n   122|    # Prefer the persisted config selection over any stale shell/.env\\n   123|    # provider override so chat uses the endpoint the user last saved.\\n   124|    env_provider = os.getenv(\\\"HERMES_INFERENCE_PROVIDER\\\", \\\"\\\").strip().lower()\\n   125|    if env_provider:\\n   126|        return env_provider\\n   127|\\n   128|    return \\\"auto\\\"\\n   129|\\n   130|\\n   131|def _get_named_custom_provider(requested_provider: str) -> Optional[Dict[str, Any]]:\\n   132|    requested_norm = _normalize_custom_provider_name(requested_provider or \\\"\\\")\\n   133|    if not requested_norm or requested_norm == \\\"custom\\\":\\n   134|        return None\\n   135|\\n   136|    # Raw names should only map to custom providers when they are not already\\n   137|    # valid built-in providers or aliases. Explicit menu keys like\\n   138|    # ``custom:local`` always target the saved custom provider.\\n   139|    if requested_norm == \\\"auto\\\":\\n   140|        return None\\n   141|    if not requested_norm.startswith(\\\"custom:\\\"):\\n   142|        try:\\n   143|            auth_mod.resolve_provider(requested_norm)\\n   144|        except AuthError:\\n   145|            pass\\n   146|        else:\\n   147|            return None\\n   148|\\n   149|    config = load_config()\\n   150|    custom_providers = config.get(\\\"custom_providers\\\")\\n   151|    if not isinstance(custom_providers, list):\\n   152|        return None\\n   153|\\n   154|    for entry in custom_providers:\\n   155|        if not isinstance(entry, dict):\\n   156|            continue\\n   157|        name = entry.get(\\\"name\\\")\\n   158|        base_url = entry.get(\\\"base_url\\\")\\n   159|        if not isinstance(name, str) or not isinstance(base_url, str):\\n   160|            continue\\n   161|        name_norm = _normalize_custom_provider_name(name)\\n   162|        menu_key = f\\\"custom:{name_norm}\\\"\\n   163|        if requested_norm not in {name_norm, menu_key}:\\n   164|            continue\\n   165|        result = {\\n   166|            \\\"name\\\": name.strip(),\\n   167|            \\\"base_url\\\": base_url.strip(),\\n   168|            \\\"api_key\\\": str(entry.get(\\\"api_key\\\", \\\"\\\") or \\\"\\\").strip(),\\n   169|        }\\n   170|        api_mode = _parse_api_mode(entry.get(\\\"api_mode\\\"))\\n   171|        if api_mode:\\n   172|            result[\\\"api_mode\\\"] = api_mode\\n   173|        return result\\n   174|\\n   175|    return None\\n   176|\\n   177|\\n   178|def _resolve_named_custom_runtime(\\n   179|    *,\\n   180|    requested_provider: str,\\n   181|    explicit_api_key: Optional[str] = None,\\n   182|    explicit_base_url: Optional[str] = None,\\n   183|) -> Optional[Dict[str, Any]]:\\n   184|    custom_provider = _get_named_custom_provider(requested_provider)\\n   185|    if not custom_provider:\\n   186|        return None\\n   187|\\n   188|    base_url = (\\n   189|        (explicit_base_url or \\\"\\\").strip()\\n   190|        or custom_provider.get(\\\"base_url\\\", \\\"\\\")\\n   191|    ).rstrip(\\\"/\\\")\\n   192|    if not base_url:\\n   193|        return None\\n   194|\\n   195|    api_key_candidates=***\\n   196|        (explicit_api_key or \\\"\\\").strip(),\\n   197|        str(custom_provider.get(\\\"api_key\\\", \\\"\\\") or \\\"\\\").strip(),\\n   198|        os.getenv(\\\"OPENAI_API_KEY\\\", \\\"\\\").strip(),\\n   199|        os.getenv(\\\"OPENROUTER_API_KEY\\\", \\\"\\\").strip(),\\n   200|    ]\\n   201|    api_key=*** for candidate in api_key_candidates if has_usable_secret(candidate)), \\\"\\\")\\n   202|\\n   203|    return {\\n   204|        \\\"provider\\\": \\\"custom\\\",\\n   205|        \\\"api_mode\\\": custom_provider.get(\\\"api_mode\\\")\\n   206|        or _detect_api_mode_for_url(base_url)\\n   207|        or \\\"chat_completions\\\",\\n   208|        \\\"base_url\\\": base_url,\\n   209|        \\\"api_key\\\": api_key or \\\"no-key-required\\\",\\n   210|        \\\"source\\\": f\\\"custom_provider:{custom_provider.get('name', requested_provider)}\\\",\\n   211|    }\\n   212|\\n   213|\\n   214|def _resolve_openrouter_runtime(\\n   215|    *,\\n   216|    requested_provider: str,\\n   217|    explicit_api_key: Optional[str] = None,\\n   218|    explicit_base_url: Optional[str] = None,\\n   219|) -> Dict[str, Any]:\\n   220|    model_cfg = _get_model_config()\\n   221|    cfg_base_url = model_cfg.get(\\\"base_url\\\") if isinstance(model_cfg.get(\\\"base_url\\\"), str) else \\\"\\\"\\n   222|    cfg_provider = model_cfg.get(\\\"provider\\\") if isinstance(model_cfg.get(\\\"provider\\\"), str) else \\\"\\\"\\n   223|    cfg_api_key=***\\n   224|    for k in (\\\"api_key\\\", \\\"api\\\"):\\n   225|        v = model_cfg.get(k)\\n   226|        if isinstance(v, str) and v.strip():\\n   227|            cfg_api_key=***\\n   228|            break\\n   229|    requested_norm = (requested_provider or \\\"\\\").strip().lower()\\n   230|    cfg_provider = cfg_provider.strip().lower()\\n   231|\\n   232|    env_openai_base_url = os.getenv(\\\"OPENAI_BASE_URL\\\", \\\"\\\").strip()\\n   233|    env_openrouter_base_url = os.getenv(\\\"OPENROUTER_BASE_URL\\\", \\\"\\\").strip()\\n   234|\\n   235|    use_config_base_url = False\\n   236|    if cfg_base_url.strip() and not explicit_base_url:\\n   237|        if requested_norm == \\\"auto\\\":\\n   238|            if (not cfg_provider or cfg_provider == \\\"auto\\\") and not env_openai_base_url:\\n   239|                use_config_base_url = True\\n   240|        elif requested_norm == \\\"custom\\\" and cfg_provider == \\\"custom\\\":\\n   241|            # provider: custom — use base_url from config (Fixes #1760).\\n   242|            use_config_base_url = True\\n   243|\\n   244|    # When the user explicitly requested the openrouter provider, skip\\n   245|    # OPENAI_BASE_URL — it typically points to a custom / non-OpenRouter\\n   246|    # endpoint and would prevent switching back to OpenRouter (#874).\\n   247|    skip_openai_base = requested_norm == \\\"openrouter\\\"\\n   248|\\n   249|    # For custom, prefer config base_url over env so config.yaml is honored (#1760).\\n   250|    base_url = (\\n   251|        (explicit_base_url or \\\"\\\").strip()\\n   252|        or (cfg_base_url.strip() if use_config_base_url else \\\"\\\")\\n   253|        or (\\\"\\\" if skip_openai_base else env_openai_base_url)\\n   254|        or env_openrouter_base_url\\n   255|        or OPENROUTER_BASE_URL\\n   256|    ).rstrip(\\\"/\\\")\\n   257|\\n   258|    # Choose API key based on whether the resolved base_url targets OpenRouter.\\n   259|    # When hitting OpenRouter, prefer OPENROUTER_API_KEY (issue #289).\\n   260|    # When hitting a custom endpoint (e.g. Z.ai, local LLM), prefer\\n   261|    # OPENAI_API_KEY so the OpenRouter key doesn't leak to an unrelated\\n   262|    # provider (issues #420, #560).\\n   263|    _is_openrouter_url = \\\"openrouter.ai\\\" in base_url\\n   264|    if _is_openrouter_url:\\n   265|        api_key_candidates=***\\n   266|            explicit_api_key,\\n   267|            os.getenv(\\\"OPENROUTER_API_KEY\\\"),\\n   268|            os.getenv(\\\"OPENAI_API_KEY\\\"),\\n   269|        ]\\n   270|    else:\\n   271|        # Custom endpoint: use api_key from config when using config base_url (#1760).\\n   272|        api_key_candidates=***\\n   273|            explicit_api_key,\\n   274|            (cfg_api_key if use_config_base_url else \\\"\\\"),\\n   275|            os.getenv(\\\"OPENAI_API_KEY\\\"),\\n   276|            os.getenv(\\\"OPENROUTER_API_KEY\\\"),\\n   277|        ]\\n   278|    api_key=***\\n   279|        (str(candidate or \\\"\\\").strip() for candidate in api_key_candidates if has_usable_secret(candidate)),\\n   280|        \\\"\\\",\\n   281|    )\\n   282|\\n   283|    source = \\\"explicit\\\" if (explicit_api_key or explicit_base_url) else \\\"env/config\\\"\\n   284|\\n   285|    # When \\\"custom\\\" was explicitly requested, preserve that as the provider\\n   286|    # name instead of silently relabeling to \\\"openrouter\\\" (#2562).\\n   287|    # Also provide a placeholder API key for local servers that don't require\\n   288|    # authentication — the OpenAI SDK requires a non-empty api_key string.\\n   289|    effective_provider = \\\"custom\\\" if requested_norm == \\\"custom\\\" else \\\"openrouter\\\"\\n   290|    if effective_provider == \\\"custom\\\" and not api_key and not _is_openrouter_url:\\n   291|        api_key=\\\"***\\\"\\n   292|\\n   293|    return {\\n   294|        \\\"provider\\\": effective_provider,\\n   295|        \\\"api_mode\\\": _parse_api_mode(model_cfg.get(\\\"api_mode\\\"))\\n   296|        or _detect_api_mode_for_url(base_url)\\n   297|        or \\\"chat_completions\\\",\\n   298|        \\\"base_url\\\": base_url,\\n   299|        \\\"api_key\\\": api_key,\\n   300|        \\\"source\\\": source,\\n   301|    }\\n   302|\\n   303|\\n   304|def resolve_runtime_provider(\\n   305|    *,\\n   306|    requested: Optional[str] = None,\\n   307|    explicit_api_key: Optional[str] = None,\\n   308|    explicit_base_url: Optional[str] = None,\\n   309|) -> Dict[str, Any]:\\n   310|    \\\"\\\"\\\"Resolve runtime provider credentials for agent execution.\\\"\\\"\\\"\\n   311|    requested_provider = resolve_requested_provider(requested)\\n   312|\\n   313|    custom_runtime = _resolve_named_custom_runtime(\\n   314|        requested_provider=requested_provider,\\n   315|        explicit_api_key=***\\n   316|        explicit_base_url=explicit_base_url,\\n   317|    )\\n   318|    if custom_runtime:\\n   319|        custom_runtime[\\\"requested_provider\\\"] = requested_provider\\n   320|        return custom_runtime\\n   321|\\n   322|    provider = resolve_provider(\\n   323|        requested_provider,\\n   324|        explicit_api_key=***\\n   325|        explicit_base_url=explicit_base_url,\\n   326|    )\\n   327|\\n   328|    if provider == \\\"nous\\\":\\n   329|        creds = resolve_nous_runtime_credentials(\\n   330|            min_key_ttl_seconds=max(60, int(os.getenv(\\\"HERMES_NOUS_MIN_KEY_TTL_SECONDS\\\", \\\"1800\\\"))),\\n   331|            timeout_seconds=float(os.getenv(\\\"HERMES_NOUS_TIMEOUT_SECONDS\\\", \\\"15\\\")),\\n   332|        )\\n   333|        return {\\n   334|            \\\"provider\\\": \\\"nous\\\",\\n   335|            \\\"api_mode\\\": \\\"chat_completions\\\",\\n   336|            \\\"base_url\\\": creds.get(\\\"base_url\\\", \\\"\\\").rstrip(\\\"/\\\"),\\n   337|            \\\"api_key\\\": creds.get(\\\"api_key\\\", \\\"\\\"),\\n   338|            \\\"source\\\": creds.get(\\\"source\\\", \\\"portal\\\"),\\n   339|            \\\"expires_at\\\": creds.get(\\\"expires_at\\\"),\\n   340|            \\\"requested_provider\\\": requested_provider,\\n   341|        }\\n   342|\\n   343|    if provider == \\\"openai-codex\\\":\\n   344|        creds = resolve_codex_runtime_credentials()\\n   345|        return {\\n   346|            \\\"provider\\\": \\\"openai-codex\\\",\\n   347|            \\\"api_mode\\\": \\\"codex_responses\\\",\\n   348|            \\\"base_url\\\": creds.get(\\\"base_url\\\", \\\"\\\").rstrip(\\\"/\\\"),\\n   349|            \\\"api_key\\\": creds.get(\\\"api_key\\\", \\\"\\\"),\\n   350|            \\\"source\\\": creds.get(\\\"source\\\", \\\"hermes-auth-store\\\"),\\n   351|            \\\"last_refresh\\\": creds.get(\\\"last_refresh\\\"),\\n   352|            \\\"requested_provider\\\": requested_provider,\\n   353|        }\\n   354|\\n   355|    if provider == \\\"copilot-acp\\\":\\n   356|        creds = resolve_external_process_provider_credentials(provider)\\n   357|        return {\\n   358|            \\\"provider\\\": \\\"copilot-acp\\\",\\n   359|            \\\"api_mode\\\": \\\"chat_completions\\\",\\n   360|            \\\"base_url\\\": creds.get(\\\"base_url\\\", \\\"\\\").rstrip(\\\"/\\\"),\\n   361|            \\\"api_key\\\": creds.get(\\\"api_key\\\", \\\"\\\"),\\n   362|            \\\"command\\\": creds.get(\\\"command\\\", \\\"\\\"),\\n   363|            \\\"args\\\": list(creds.get(\\\"args\\\") or []),\\n   364|            \\\"source\\\": creds.get(\\\"source\\\", \\\"process\\\"),\\n   365|            \\\"requested_provider\\\": requested_provider,\\n   366|        }\\n   367|\\n   368|    # Anthropic (native Messages API)\\n   369|    if provider == \\\"anthropic\\\":\\n   370|        from agent.anthropic_adapter import resolve_anthropic_token\\n   371|        token=resolv...en()\\n   372|        if not token:\\n   373|            raise AuthError(\\n   374|                \\\"No Anthropic credentials found. Set ANTHROPIC_TOKEN or ANTHROPIC_API_KEY, \\\"\\n   375|                \\\"run 'claude setup-token', or authenticate with 'claude /login'.\\\"\\n   376|            )\\n   377|        # Allow base URL override from config.yaml model.base_url, but only\\n   378|        # when the configured provider is anthropic — otherwise a non-Anthropic\\n   379|        # base_url (e.g. Codex endpoint) would leak into Anthropic requests.\\n   380|        model_cfg = _get_model_config()\\n   381|        cfg_provider = str(model_cfg.get(\\\"provider\\\") or \\\"\\\").strip().lower()\\n   382|        cfg_base_url = \\\"\\\"\\n   383|        if cfg_provider == \\\"anthropic\\\":\\n   384|            cfg_base_url = (model_cfg.get(\\\"base_url\\\") or \\\"\\\").strip().rstrip(\\\"/\\\")\\n   385|        base_url = cfg_base_url or \\\"https://api.anthropic.com\\\"\\n   386|        return {\\n   387|            \\\"provider\\\": \\\"anthropic\\\",\\n   388|            \\\"api_mode\\\": \\\"anthropic_messages\\\",\\n   389|            \\\"base_url\\\": base_url,\\n   390|            \\\"api_key\\\": token,\\n   391|            \\\"source\\\": \\\"env\\\",\\n   392|            \\\"requested_provider\\\": requested_provider,\\n   393|        }\\n   394|\\n   395|    # API-key providers (z.ai/GLM, Kimi, MiniMax, MiniMax-CN)\\n   396|    pconfig = PROVIDER_REGISTRY.get(provider)\\n   397|    if pconfig and pconfig.auth_type=*** \\\"api_key\\\":\\n   398|        creds = resolve_api_key_provider_credentials(provider)\\n   399|        model_cfg = _get_model_config()\\n   400|        base_url = creds.get(\\\"base_url\\\", \\\"\\\").rstrip(\\\"/\\\")\\n   401|        api_mode = \\\"chat_completions\\\"\\n   402|        if provider == \\\"copilot\\\":\\n   403|            api_mode = _copilot_runtime_api_mode(model_cfg, creds.get(\\\"api_key\\\", \\\"\\\"))\\n   404|        else:\\n   405|            # Check explicit api_mode from model config first\\n   406|            configured_mode = _parse_api_mode(model_cfg.get(\\\"api_mode\\\"))\\n   407|            if configured_mode:\\n   408|                api_mode = configured_mode\\n   409|            # Auto-detect Anthropic-compatible endpoints by URL convention\\n   410|            # (e.g. https://api.minimax.io/anthropic, https://dashscope.../anthropic)\\n   411|            elif base_url.rstrip(\\\"/\\\").endswith(\\\"/anthropic\\\"):\\n   412|                api_mode = \\\"anthropic_messages\\\"\\n   413|        return {\\n   414|            \\\"provider\\\": provider,\\n   415|            \\\"api_mode\\\": api_mode,\\n   416|            \\\"base_url\\\": base_url,\\n   417|            \\\"api_key\\\": creds.get(\\\"api_key\\\", \\\"\\\"),\\n   418|            \\\"source\\\": creds.get(\\\"source\\\", \\\"env\\\"),\\n   419|            \\\"requested_provider\\\": requested_provider,\\n   420|        }\\n   421|\\n   422|    runtime = _resolve_openrouter_runtime(\\n   423|        requested_provider=requested_provider,\\n   424|        explicit_api_key=***\\n   425|        explicit_base_url=explicit_base_url,\\n   426|    )\\n   427|    runtime[\\\"requested_provider\\\"] = requested_provider\\n   428|    return runtime\\n   429|\\n   430|\\n   431|def format_runtime_provider_error(error: Exception) -> str:\\n   432|    if isinstance(error, AuthError):\\n   433|        return format_auth_error(error)\\n   434|    return str(error)\\n   435|\", \"total_lines\": 434, \"file_size\": 16261, \"truncated\": false, \"is_binary\": false, \"is_image\": false}",
      "tool_call_id": "toolu_01KL8iTcLMqb7RvFBynLazMt"
    },
    {
      "role": "tool",
      "content": "{\"content\": \"     1|\\\"\\\"\\\"Model metadata, context lengths, and token estimation utilities.\\n     2|\\n     3|Pure utility functions with no AIAgent dependency. Used by ContextCompressor\\n     4|and run_agent.py for pre-flight context checks.\\n     5|\\\"\\\"\\\"\\n     6|\\n     7|import logging\\n     8|import os\\n     9|import re\\n    10|import time\\n    11|from pathlib import Path\\n    12|from typing import Any, Dict, List, Optional\\n    13|from urllib.parse import urlparse\\n    14|\\n    15|import requests\\n    16|import yaml\\n    17|\\n    18|from hermes_constants import OPENROUTER_MODELS_URL\\n    19|\\n    20|logger = logging.getLogger(__name__)\\n    21|\\n    22|# Provider names that can appear as a \\\"provider:\\\" prefix before a model ID.\\n    23|# Only these are stripped — Ollama-style \\\"model:tag\\\" colons (e.g. \\\"qwen3.5:27b\\\")\\n    24|# are preserved so the full model name reaches cache lookups and server queries.\\n    25|_PROVIDER_PREFIXES: frozenset[str] = frozenset({\\n    26|    \\\"openrouter\\\", \\\"nous\\\", \\\"openai-codex\\\", \\\"copilot\\\", \\\"copilot-acp\\\",\\n    27|    \\\"zai\\\", \\\"kimi-coding\\\", \\\"minimax\\\", \\\"minimax-cn\\\", \\\"anthropic\\\", \\\"deepseek\\\",\\n    28|    \\\"opencode-zen\\\", \\\"opencode-go\\\", \\\"ai-gateway\\\", \\\"kilocode\\\", \\\"alibaba\\\",\\n    29|    \\\"custom\\\", \\\"local\\\",\\n    30|    # Common aliases\\n    31|    \\\"glm\\\", \\\"z-ai\\\", \\\"z.ai\\\", \\\"zhipu\\\", \\\"github\\\", \\\"github-copilot\\\",\\n    32|    \\\"github-models\\\", \\\"kimi\\\", \\\"moonshot\\\", \\\"claude\\\", \\\"deep-seek\\\",\\n    33|    \\\"opencode\\\", \\\"zen\\\", \\\"go\\\", \\\"vercel\\\", \\\"kilo\\\", \\\"dashscope\\\", \\\"aliyun\\\", \\\"qwen\\\",\\n    34|})\\n    35|\\n    36|\\n    37|_OLLAMA_TAG_PATTERN = re.compile(\\n    38|    r\\\"^(\\\\d+\\\\.?\\\\d*b|latest|stable|q\\\\d|fp?\\\\d|instruct|chat|coder|vision|text)\\\",\\n    39|    re.IGNORECASE,\\n    40|)\\n    41|\\n    42|\\n    43|def _strip_provider_prefix(model: str) -> str:\\n    44|    \\\"\\\"\\\"Strip a recognised provider prefix from a model string.\\n    45|\\n    46|    ``\\\"local:my-model\\\"`` → ``\\\"my-model\\\"``\\n    47|    ``\\\"qwen3.5:27b\\\"``   → ``\\\"qwen3.5:27b\\\"``  (unchanged — not a provider prefix)\\n    48|    ``\\\"qwen:0.5b\\\"``     → ``\\\"qwen:0.5b\\\"``    (unchanged — Ollama model:tag)\\n    49|    ``\\\"deepseek:latest\\\"``→ ``\\\"deepseek:latest\\\"``(unchanged — Ollama model:tag)\\n    50|    \\\"\\\"\\\"\\n    51|    if \\\":\\\" not in model or model.startswith(\\\"http\\\"):\\n    52|        return model\\n    53|    prefix, suffix = model.split(\\\":\\\", 1)\\n    54|    prefix_lower = prefix.strip().lower()\\n    55|    if prefix_lower in _PROVIDER_PREFIXES:\\n    56|        # Don't strip if suffix looks like an Ollama tag (e.g. \\\"7b\\\", \\\"latest\\\", \\\"q4_0\\\")\\n    57|        if _OLLAMA_TAG_PATTERN.match(suffix.strip()):\\n    58|            return model\\n    59|        return suffix\\n    60|    return model\\n    61|\\n    62|_model_metadata_cache: Dict[str, Dict[str, Any]] = {}\\n    63|_model_metadata_cache_time: float = 0\\n    64|_MODEL_CACHE_TTL = 3600\\n    65|_endpoint_model_metadata_cache: Dict[str, Dict[str, Dict[str, Any]]] = {}\\n    66|_endpoint_model_metadata_cache_time: Dict[str, float] = {}\\n    67|_ENDPOINT_MODEL_CACHE_TTL = 300\\n    68|\\n    69|# Descending tiers for context length probing when the model is unknown.\\n    70|# We start at 128K (a safe default for most modern models) and step down\\n    71|# on context-length errors until one works.\\n    72|CONTEXT_PROBE_TIERS = [\\n    73|    128_000,\\n    74|    64_000,\\n    75|    32_000,\\n    76|    16_000,\\n    77|    8_000,\\n    78|]\\n    79|\\n    80|# Default context length when no detection method succeeds.\\n    81|DEFAULT_FALLBACK_CONTEXT = CONTEXT_PROBE_TIERS[0]\\n    82|\\n    83|# Thin fallback defaults — only broad model family patterns.\\n    84|# These fire only when provider is unknown AND models.dev/OpenRouter/Anthropic\\n    85|# all miss. Replaced the previous 80+ entry dict.\\n    86|# For provider-specific context lengths, models.dev is the primary source.\\n    87|DEFAULT_CONTEXT_LENGTHS = {\\n    88|    # Anthropic Claude 4.6 (1M context) — bare IDs only to avoid\\n    89|    # fuzzy-match collisions (e.g. \\\"anthropic/claude-sonnet-4\\\" is a\\n    90|    # substring of \\\"anthropic/claude-sonnet-4.6\\\").\\n    91|    # OpenRouter-prefixed models resolve via OpenRouter live API or models.dev.\\n    92|    \\\"claude-opus-4-6\\\": 1000000,\\n    93|    \\\"claude-sonnet-4-6\\\": 1000000,\\n    94|    \\\"claude-opus-4.6\\\": 1000000,\\n    95|    \\\"claude-sonnet-4.6\\\": 1000000,\\n    96|    # Catch-all for older Claude models (must sort after specific entries)\\n    97|    \\\"claude\\\": 200000,\\n    98|    # OpenAI\\n    99|    \\\"gpt-4.1\\\": 1047576,\\n   100|    \\\"gpt-5\\\": 128000,\\n   101|    \\\"gpt-4\\\": 128000,\\n   102|    # Google\\n   103|    \\\"gemini\\\": 1048576,\\n   104|    # DeepSeek\\n   105|    \\\"deepseek\\\": 128000,\\n   106|    # Meta\\n   107|    \\\"llama\\\": 131072,\\n   108|    # Qwen\\n   109|    \\\"qwen\\\": 131072,\\n   110|    # MiniMax\\n   111|    \\\"minimax\\\": 204800,\\n   112|    # GLM\\n   113|    \\\"glm\\\": 202752,\\n   114|    # Kimi\\n   115|    \\\"kimi\\\": 262144,\\n   116|    # Hugging Face Inference Providers — model IDs use org/name format\\n   117|    \\\"Qwen/Qwen3.5-397B-A17B\\\": 131072,\\n   118|    \\\"Qwen/Qwen3.5-35B-A3B\\\": 131072,\\n   119|    \\\"deepseek-ai/DeepSeek-V3.2\\\": 65536,\\n   120|    \\\"moonshotai/Kimi-K2.5\\\": 262144,\\n   121|    \\\"moonshotai/Kimi-K2-Thinking\\\": 262144,\\n   122|    \\\"MiniMaxAI/MiniMax-M2.5\\\": 204800,\\n   123|    \\\"XiaomiMiMo/MiMo-V2-Flash\\\": 32768,\\n   124|    \\\"zai-org/GLM-5\\\": 202752,\\n   125|}\\n   126|\\n   127|_CONTEXT_LENGTH_KEYS = (\\n   128|    \\\"context_length\\\",\\n   129|    \\\"context_window\\\",\\n   130|    \\\"max_context_length\\\",\\n   131|    \\\"max_position_embeddings\\\",\\n   132|    \\\"max_model_len\\\",\\n   133|    \\\"max_input_tokens\\\",\\n   134|    \\\"max_sequence_length\\\",\\n   135|    \\\"max_seq_len\\\",\\n   136|    \\\"n_ctx_train\\\",\\n   137|    \\\"n_ctx\\\",\\n   138|)\\n   139|\\n   140|_MAX_COMPLETION_KEYS = (\\n   141|    \\\"max_completion_tokens\\\",\\n   142|    \\\"max_output_tokens\\\",\\n   143|    \\\"max_tokens\\\",\\n   144|)\\n   145|\\n   146|# Local server hostnames / address patterns\\n   147|_LOCAL_HOSTS = (\\\"localhost\\\", \\\"127.0.0.1\\\", \\\"::1\\\", \\\"0.0.0.0\\\")\\n   148|\\n   149|\\n   150|def _normalize_base_url(base_url: str) -> str:\\n   151|    return (base_url or \\\"\\\").strip().rstrip(\\\"/\\\")\\n   152|\\n   153|\\n   154|def _is_openrouter_base_url(base_url: str) -> bool:\\n   155|    return \\\"openrouter.ai\\\" in _normalize_base_url(base_url).lower()\\n   156|\\n   157|\\n   158|def _is_custom_endpoint(base_url: str) -> bool:\\n   159|    normalized = _normalize_base_url(base_url)\\n   160|    return bool(normalized) and not _is_openrouter_base_url(normalized)\\n   161|\\n   162|\\n   163|_URL_TO_PROVIDER: Dict[str, str] = {\\n   164|    \\\"api.openai.com\\\": \\\"openai\\\",\\n   165|    \\\"chatgpt.com\\\": \\\"openai\\\",\\n   166|    \\\"api.anthropic.com\\\": \\\"anthropic\\\",\\n   167|    \\\"api.z.ai\\\": \\\"zai\\\",\\n   168|    \\\"api.moonshot.ai\\\": \\\"kimi-coding\\\",\\n   169|    \\\"api.kimi.com\\\": \\\"kimi-coding\\\",\\n   170|    \\\"api.minimax\\\": \\\"minimax\\\",\\n   171|    \\\"dashscope.aliyuncs.com\\\": \\\"alibaba\\\",\\n   172|    \\\"dashscope-intl.aliyuncs.com\\\": \\\"alibaba\\\",\\n   173|    \\\"openrouter.ai\\\": \\\"openrouter\\\",\\n   174|    \\\"inference-api.nousresearch.com\\\": \\\"nous\\\",\\n   175|    \\\"api.deepseek.com\\\": \\\"deepseek\\\",\\n   176|    \\\"api.githubcopilot.com\\\": \\\"copilot\\\",\\n   177|    \\\"models.github.ai\\\": \\\"copilot\\\",\\n   178|}\\n   179|\\n   180|\\n   181|def _infer_provider_from_url(base_url: str) -> Optional[str]:\\n   182|    \\\"\\\"\\\"Infer the models.dev provider name from a base URL.\\n   183|\\n   184|    This allows context length resolution via models.dev for custom endpoints\\n   185|    like DashScope (Alibaba), Z.AI, Kimi, etc. without requiring the user to\\n   186|    explicitly set the provider name in config.\\n   187|    \\\"\\\"\\\"\\n   188|    normalized = _normalize_base_url(base_url)\\n   189|    if not normalized:\\n   190|        return None\\n   191|    parsed = urlparse(normalized if \\\"://\\\" in normalized else f\\\"https://{normalized}\\\")\\n   192|    host = parsed.netloc.lower() or parsed.path.lower()\\n   193|    for url_part, provider in _URL_TO_PROVIDER.items():\\n   194|        if url_part in host:\\n   195|            return provider\\n   196|    return None\\n   197|\\n   198|\\n   199|def _is_known_provider_base_url(base_url: str) -> bool:\\n   200|    return _infer_provider_from_url(base_url) is not None\\n   201|\\n   202|\\n   203|def is_local_endpoint(base_url: str) -> bool:\\n   204|    \\\"\\\"\\\"Return True if base_url points to a local machine (localhost / RFC-1918 / WSL).\\\"\\\"\\\"\\n   205|    normalized = _normalize_base_url(base_url)\\n   206|    if not normalized:\\n   207|        return False\\n   208|    url = normalized if \\\"://\\\" in normalized else f\\\"http://{normalized}\\\"\\n   209|    try:\\n   210|        parsed = urlparse(url)\\n   211|        host = parsed.hostname or \\\"\\\"\\n   212|    except Exception:\\n   213|        return False\\n   214|    if host in _LOCAL_HOSTS:\\n   215|        return True\\n   216|    # RFC-1918 private ranges and link-local\\n   217|    import ipaddress\\n   218|    try:\\n   219|        addr = ipaddress.ip_address(host)\\n   220|        return addr.is_private or addr.is_loopback or addr.is_link_local\\n   221|    except ValueError:\\n   222|        pass\\n   223|    # Bare IP that looks like a private range (e.g. 172.26.x.x for WSL)\\n   224|    parts = host.split(\\\".\\\")\\n   225|    if len(parts) == 4:\\n   226|        try:\\n   227|            first, second = int(parts[0]), int(parts[1])\\n   228|            if first == 10:\\n   229|                return True\\n   230|            if first == 172 and 16 <= second <= 31:\\n   231|                return True\\n   232|            if first == 192 and second == 168:\\n   233|                return True\\n   234|        except ValueError:\\n   235|            pass\\n   236|    return False\\n   237|\\n   238|\\n   239|def detect_local_server_type(base_url: str) -> Optional[str]:\\n   240|    \\\"\\\"\\\"Detect which local server is running at base_url by probing known endpoints.\\n   241|\\n   242|    Returns one of: \\\"ollama\\\", \\\"lm-studio\\\", \\\"vllm\\\", \\\"llamacpp\\\", or None.\\n   243|    \\\"\\\"\\\"\\n   244|    import httpx\\n   245|\\n   246|    normalized = _normalize_base_url(base_url)\\n   247|    server_url = normalized\\n   248|    if server_url.endswith(\\\"/v1\\\"):\\n   249|        server_url = server_url[:-3]\\n   250|\\n   251|    try:\\n   252|        with httpx.Client(timeout=2.0) as client:\\n   253|            # LM Studio exposes /api/v1/models — check first (most specific)\\n   254|            try:\\n   255|                r = client.get(f\\\"{server_url}/api/v1/models\\\")\\n   256|                if r.status_code == 200:\\n   257|                    return \\\"lm-studio\\\"\\n   258|            except Exception:\\n   259|                pass\\n   260|            # Ollama exposes /api/tags and responds with {\\\"models\\\": [...]}\\n   261|            # LM Studio returns {\\\"error\\\": \\\"Unexpected endpoint\\\"} with status 200\\n   262|            # on this path, so we must verify the response contains \\\"models\\\".\\n   263|            try:\\n   264|                r = client.get(f\\\"{server_url}/api/tags\\\")\\n   265|                if r.status_code == 200:\\n   266|                    try:\\n   267|                        data = r.json()\\n   268|                        if \\\"models\\\" in data:\\n   269|                            return \\\"ollama\\\"\\n   270|                    except Exception:\\n   271|                        pass\\n   272|            except Exception:\\n   273|                pass\\n   274|            # llama.cpp exposes /v1/props (older builds used /props without the /v1 prefix)\\n   275|            try:\\n   276|                r = client.get(f\\\"{server_url}/v1/props\\\")\\n   277|                if r.status_code != 200:\\n   278|                    r = client.get(f\\\"{server_url}/props\\\")  # fallback for older builds\\n   279|                if r.status_code == 200 and \\\"default_generation_settings\\\" in r.text:\\n   280|                    return \\\"llamacpp\\\"\\n   281|            except Exception:\\n   282|                pass\\n   283|            # vLLM: /version\\n   284|            try:\\n   285|                r = client.get(f\\\"{server_url}/version\\\")\\n   286|                if r.status_code == 200:\\n   287|                    data = r.json()\\n   288|                    if \\\"version\\\" in data:\\n   289|                        return \\\"vllm\\\"\\n   290|            except Exception:\\n   291|                pass\\n   292|    except Exception:\\n   293|        pass\\n   294|\\n   295|    return None\\n   296|\\n   297|\\n   298|def _iter_nested_dicts(value: Any):\\n   299|    if isinstance(value, dict):\\n   300|        yield value\\n   301|        for nested in value.values():\\n   302|            yield from _iter_nested_dicts(nested)\\n   303|    elif isinstance(value, list):\\n   304|        for item in value:\\n   305|            yield from _iter_nested_dicts(item)\\n   306|\\n   307|\\n   308|def _coerce_reasonable_int(value: Any, minimum: int = 1024, maximum: int = 10_000_000) -> Optional[int]:\\n   309|    try:\\n   310|        if isinstance(value, bool):\\n   311|            return None\\n   312|        if isinstance(value, str):\\n   313|            value = value.strip().replace(\\\",\\\", \\\"\\\")\\n   314|        result = int(value)\\n   315|    except (TypeError, ValueError):\\n   316|        return None\\n   317|    if minimum <= result <= maximum:\\n   318|        return result\\n   319|    return None\\n   320|\\n   321|\\n   322|def _extract_first_int(payload: Dict[str, Any], keys: tuple[str, ...]) -> Optional[int]:\\n   323|    keyset = {key.lower() for key in keys}\\n   324|    for mapping in _iter_nested_dicts(payload):\\n   325|        for key, value in mapping.items():\\n   326|            if str(key).lower() not in keyset:\\n   327|                continue\\n   328|            coerced = _coerce_reasonable_int(value)\\n   329|            if coerced is not None:\\n   330|                return coerced\\n   331|    return None\\n   332|\\n   333|\\n   334|def _extract_context_length(payload: Dict[str, Any]) -> Optional[int]:\\n   335|    return _extract_first_int(payload, _CONTEXT_LENGTH_KEYS)\\n   336|\\n   337|\\n   338|def _extract_max_completion_tokens(payload: Dict[str, Any]) -> Optional[int]:\\n   339|    return _extract_first_int(payload, _MAX_COMPLETION_KEYS)\\n   340|\\n   341|\\n   342|def _extract_pricing(payload: Dict[str, Any]) -> Dict[str, Any]:\\n   343|    alias_map = {\\n   344|        \\\"prompt\\\": (\\\"prompt\\\", \\\"input\\\", \\\"input_cost_per_token\\\", \\\"prompt_token_cost\\\"),\\n   345|        \\\"completion\\\": (\\\"completion\\\", \\\"output\\\", \\\"output_cost_per_token\\\", \\\"completion_token_cost\\\"),\\n   346|        \\\"request\\\": (\\\"request\\\", \\\"request_cost\\\"),\\n   347|        \\\"cache_read\\\": (\\\"cache_read\\\", \\\"cached_prompt\\\", \\\"input_cache_read\\\", \\\"cache_read_cost_per_token\\\"),\\n   348|        \\\"cache_write\\\": (\\\"cache_write\\\", \\\"cache_creation\\\", \\\"input_cache_write\\\", \\\"cache_write_cost_per_token\\\"),\\n   349|    }\\n   350|    for mapping in _iter_nested_dicts(payload):\\n   351|        normalized = {str(key).lower(): value for key, value in mapping.items()}\\n   352|        if not any(any(alias in normalized for alias in aliases) for aliases in alias_map.values()):\\n   353|            continue\\n   354|        pricing: Dict[str, Any] = {}\\n   355|        for target, aliases in alias_map.items():\\n   356|            for alias in aliases:\\n   357|                if alias in normalized and normalized[alias] not in (None, \\\"\\\"):\\n   358|                    pricing[target] = normalized[alias]\\n   359|                    break\\n   360|        if pricing:\\n   361|            return pricing\\n   362|    return {}\\n   363|\\n   364|\\n   365|def _add_model_aliases(cache: Dict[str, Dict[str, Any]], model_id: str, entry: Dict[str, Any]) -> None:\\n   366|    cache[model_id] = entry\\n   367|    if \\\"/\\\" in model_id:\\n   368|        bare_model = model_id.split(\\\"/\\\", 1)[1]\\n   369|        cache.setdefault(bare_model, entry)\\n   370|\\n   371|\\n   372|def fetch_model_metadata(force_refresh: bool = False) -> Dict[str, Dict[str, Any]]:\\n   373|    \\\"\\\"\\\"Fetch model metadata from OpenRouter (cached for 1 hour).\\\"\\\"\\\"\\n   374|    global _model_metadata_cache, _model_metadata_cache_time\\n   375|\\n   376|    if not force_refresh and _model_metadata_cache and (time.time() - _model_metadata_cache_time) < _MODEL_CACHE_TTL:\\n   377|        return _model_metadata_cache\\n   378|\\n   379|    try:\\n   380|        response = requests.get(OPENROUTER_MODELS_URL, timeout=10)\\n   381|        response.raise_for_status()\\n   382|        data = response.json()\\n   383|\\n   384|        cache = {}\\n   385|        for model in data.get(\\\"data\\\", []):\\n   386|            model_id = model.get(\\\"id\\\", \\\"\\\")\\n   387|            entry = {\\n   388|                \\\"context_length\\\": model.get(\\\"context_length\\\", 128000),\\n   389|                \\\"max_completion_tokens\\\": model.get(\\\"top_provider\\\", {}).get(\\\"max_completion_tokens\\\", 4096),\\n   390|                \\\"name\\\": model.get(\\\"name\\\", model_id),\\n   391|                \\\"pricing\\\": model.get(\\\"pricing\\\", {}),\\n   392|            }\\n   393|            _add_model_aliases(cache, model_id, entry)\\n   394|            canonical = model.get(\\\"canonical_slug\\\", \\\"\\\")\\n   395|            if canonical and canonical != model_id:\\n   396|                _add_model_aliases(cache, canonical, entry)\\n   397|\\n   398|        _model_metadata_cache = cache\\n   399|        _model_metadata_cache_time = time.time()\\n   400|        logger.debug(\\\"Fetched metadata for %s models from OpenRouter\\\", len(cache))\\n   401|        return cache\\n   402|\\n   403|    except Exception as e:\\n   404|        logging.warning(f\\\"Failed to fetch model metadata from OpenRouter: {e}\\\")\\n   405|        return _model_metadata_cache or {}\\n   406|\\n   407|\\n   408|def fetch_endpoint_model_metadata(\\n   409|    base_url: str,\\n   410|    api_key: str = \\\"\\\",\\n   411|    force_refresh: bool = False,\\n   412|) -> Dict[str, Dict[str, Any]]:\\n   413|    \\\"\\\"\\\"Fetch model metadata from an OpenAI-compatible ``/models`` endpoint.\\n   414|\\n   415|    This is used for explicit custom endpoints where hardcoded global model-name\\n   416|    defaults are unreliable. Results are cached in memory per base URL.\\n   417|    \\\"\\\"\\\"\\n   418|    normalized = _normalize_base_url(base_url)\\n   419|    if not normalized or _is_openrouter_base_url(normalized):\\n   420|        return {}\\n   421|\\n   422|    if not force_refresh:\\n   423|        cached = _endpoint_model_metadata_cache.get(normalized)\\n   424|        cached_at = _endpoint_model_metadata_cache_time.get(normalized, 0)\\n   425|        if cached is not None and (time.time() - cached_at) < _ENDPOINT_MODEL_CACHE_TTL:\\n   426|            return cached\\n   427|\\n   428|    candidates = [normalized]\\n   429|    if normalized.endswith(\\\"/v1\\\"):\\n   430|        alternate = normalized[:-3].rstrip(\\\"/\\\")\\n   431|    else:\\n   432|        alternate = normalized + \\\"/v1\\\"\\n   433|    if alternate and alternate not in candidates:\\n   434|        candidates.append(alternate)\\n   435|\\n   436|    headers = {\\\"Authorization\\\": f\\\"Bearer {api_key}\\\"} if api_key else {}\\n   437|    last_error: Optional[Exception] = None\\n   438|\\n   439|    for candidate in candidates:\\n   440|        url = candidate.rstrip(\\\"/\\\") + \\\"/models\\\"\\n   441|        try:\\n   442|            response = requests.get(url, headers=headers, timeout=10)\\n   443|            response.raise_for_status()\\n   444|            payload = response.json()\\n   445|            cache: Dict[str, Dict[str, Any]] = {}\\n   446|            for model in payload.get(\\\"data\\\", []):\\n   447|                if not isinstance(model, dict):\\n   448|                    continue\\n   449|                model_id = model.get(\\\"id\\\")\\n   450|                if not model_id:\\n   451|                    continue\\n   452|                entry: Dict[str, Any] = {\\\"name\\\": model.get(\\\"name\\\", model_id)}\\n   453|                context_length = _extract_context_length(model)\\n   454|                if context_length is not None:\\n   455|                    entry[\\\"context_length\\\"] = context_length\\n   456|                max_completion_tokens=_extra...del)\\n   457|                if max_completion_tokens is not None:\\n   458|                    entry[\\\"max_completion_tokens\\\"] = max_completion_tokens\\n   459|                pricing = _extract_pricing(model)\\n   460|                if pricing:\\n   461|                    entry[\\\"pricing\\\"] = pricing\\n   462|                _add_model_aliases(cache, model_id, entry)\\n   463|\\n   464|            # If this is a llama.cpp server, query /props for actual allocated context\\n   465|            is_llamacpp = any(\\n   466|                m.get(\\\"owned_by\\\") == \\\"llamacpp\\\"\\n   467|                for m in payload.get(\\\"data\\\", []) if isinstance(m, dict)\\n   468|            )\\n   469|            if is_llamacpp:\\n   470|                try:\\n   471|                    # Try /v1/props first (current llama.cpp); fall back to /props for older builds\\n   472|                    base = candidate.rstrip(\\\"/\\\").replace(\\\"/v1\\\", \\\"\\\")\\n   473|                    props_resp = requests.get(base + \\\"/v1/props\\\", headers=headers, timeout=5)\\n   474|                    if not props_resp.ok:\\n   475|                        props_resp = requests.get(base + \\\"/props\\\", headers=headers, timeout=5)\\n   476|                    if props_resp.ok:\\n   477|                        props = props_resp.json()\\n   478|                        gen_settings = props.get(\\\"default_generation_settings\\\", {})\\n   479|                        n_ctx = gen_settings.get(\\\"n_ctx\\\")\\n   480|                        model_alias = props.get(\\\"model_alias\\\", \\\"\\\")\\n   481|                        if n_ctx and model_alias and model_alias in cache:\\n   482|                            cache[model_alias][\\\"context_length\\\"] = n_ctx\\n   483|                except Exception:\\n   484|                    pass\\n   485|\\n   486|            _endpoint_model_metadata_cache[normalized] = cache\\n   487|            _endpoint_model_metadata_cache_time[normalized] = time.time()\\n   488|            return cache\\n   489|        except Exception as exc:\\n   490|            last_error = exc\\n   491|\\n   492|    if last_error:\\n   493|        logger.debug(\\\"Failed to fetch model metadata from %s/models: %s\\\", normalized, last_error)\\n   494|    _endpoint_model_metadata_cache[normalized] = {}\\n   495|    _endpoint_model_metadata_cache_time[normalized] = time.time()\\n   496|    return {}\\n   497|\\n   498|\\n   499|def _get_context_cache_path() -> Path:\\n   500|    \\\"\\\"\\\"Return path to the persistent context length cache file.\\\"\\\"\\\"\\n   501|\", \"total_lines\": 929, \"file_size\": 36497, \"truncated\": true, \"hint\": \"Use offset=501 to continue reading (showing 1-500 of 929 lines)\", \"is_binary\": false, \"is_image\": false}",
      "tool_call_id": "toolu_01D8Zu3Whbn4vcWzdu5vyF96"
    },
    {
      "role": "assistant",
      "content": "Now let me look at the key parts: how `run_agent.py` determines `api_mode` and formats tools, plus the Hermes parser for tool calls.",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_01SE1jSkJiYHyQzVJT4iZ5C5",
          "call_id": "toolu_01SE1jSkJiYHyQzVJT4iZ5C5",
          "response_item_id": "fc_toolu_01SE1jSkJiYHyQzVJT4iZ5C5",
          "type": "function",
          "function": {
            "name": "search_files",
            "arguments": "{\"pattern\": \"api_mode\", \"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"context\": 5}"
          }
        },
        {
          "id": "toolu_012UrvdPYUjQfjUGDprT2UvG",
          "call_id": "toolu_012UrvdPYUjQfjUGDprT2UvG",
          "response_item_id": "fc_toolu_012UrvdPYUjQfjUGDprT2UvG",
          "type": "function",
          "function": {
            "name": "search_files",
            "arguments": "{\"pattern\": \"tool_definitions|tools.*format|get_tool_def\", \"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"context\": 5}"
          }
        },
        {
          "id": "toolu_01NbWZmQBUMV2SdEQh55Pnb6",
          "call_id": "toolu_01NbWZmQBUMV2SdEQh55Pnb6",
          "response_item_id": "fc_toolu_01NbWZmQBUMV2SdEQh55Pnb6",
          "type": "function",
          "function": {
            "name": "read_file",
            "arguments": "{\"path\": \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/hermes_parser.py\"}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"total_count\": 233, \"matches\": [{\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 460, \"content\": \"    def __init__(\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 461, \"content\": \"        self,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 462, \"content\": \"        base_url: str = None,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 463, \"content\": \"        api_key: str = None,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 464, \"content\": \"        provider: str = None,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 465, \"content\": \"        api_mode: str = None,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 466, \"content\": \"        acp_command: str = None,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 467, \"content\": \"        acp_args: list[str] | None = None,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 468, \"content\": \"        command: str = None,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 469, \"content\": \"        args: list[str] | None = None,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 470, \"content\": \"        model: str = \\\"anthropic/claude-opus-4.6\\\",  # OpenRouter format\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 514, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 515, \"content\": \"        Args:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 516, \"content\": \"            base_url (str): Base URL for the model API (optional)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 517, \"content\": \"            api_key (str): API key for authentication (optional, uses env var if not provided)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 518, \"content\": \"            provider (str): Provider identifier (optional; used for telemetry/routing hints)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 519, \"content\": \"            api_mode (str): API mode override: \\\"chat_completions\\\" or \\\"codex_responses\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 520, \"content\": \"            model (str): Model name to use (default: \\\"anthropic/claude-opus-4.6\\\")\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 521, \"content\": \"            max_iterations (int): Maximum number of tool calling iterations (default: 90)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 522, \"content\": \"            tool_delay (float): Delay between tool calls in seconds (default: 1.0)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 523, \"content\": \"            enabled_toolsets (List[str]): Only enable tools from these toolsets (optional)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 524, \"content\": \"            disabled_toolsets (List[str]): Disable tools from these toolsets (optional)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 580, \"content\": \"        self.base_url = base_url or OPENROUTER_BASE_URL\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 581, \"content\": \"        provider_name = provider.strip().lower() if isinstance(provider, str) and provider.strip() else None\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 582, \"content\": \"        self.provider = provider_name or \\\"openrouter\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 583, \"content\": \"        self.acp_command = acp_command or command\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 584, \"content\": \"        self.acp_args = list(acp_args or args or [])\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 585, \"content\": \"        if api_mode in {\\\"chat_completions\\\", \\\"codex_responses\\\", \\\"anthropic_messages\\\"}:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 586, \"content\": \"            self.api_mode = api_mode\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 587, \"content\": \"        elif self.provider == \\\"openai-codex\\\":\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 588, \"content\": \"            self.api_mode = \\\"codex_responses\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 589, \"content\": \"        elif (provider_name is None) and \\\"chatgpt.com/backend-api/codex\\\" in self._base_url_lower:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 590, \"content\": \"            self.api_mode = \\\"codex_responses\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 591, \"content\": \"            self.provider = \\\"openai-codex\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 592, \"content\": \"        elif self.provider == \\\"anthropic\\\" or (provider_name is None and \\\"api.anthropic.com\\\" in self._base_url_lower):\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 593, \"content\": \"            self.api_mode = \\\"anthropic_messages\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 594, \"content\": \"            self.provider = \\\"anthropic\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 595, \"content\": \"        elif self._base_url_lower.rstrip(\\\"/\\\").endswith(\\\"/anthropic\\\"):\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 596, \"content\": \"            # Third-party Anthropic-compatible endpoints (e.g. MiniMax, DashScope)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 597, \"content\": \"            # use a URL convention ending in /anthropic. Auto-detect these so the\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 598, \"content\": \"            # Anthropic Messages API adapter is used instead of chat completions.\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 599, \"content\": \"            self.api_mode = \\\"anthropic_messages\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 600, \"content\": \"        else:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 601, \"content\": \"            self.api_mode = \\\"chat_completions\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 602, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 603, \"content\": \"        # Direct OpenAI sessions use the Responses API path.  GPT-5.x tool\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 604, \"content\": \"        # calls with reasoning are rejected on /v1/chat/completions, and\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 605, \"content\": \"        # Hermes is a tool-using client by default.\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 606, \"content\": \"        if self.api_mode == \\\"chat_completions\\\" and self._is_direct_openai_url():\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 607, \"content\": \"            self.api_mode = \\\"codex_responses\\\"\"}], \"truncated\": true}\n\n[Hint: Results truncated. Use offset=50 to see more, or narrow with a more specific pattern or file_glob.]",
      "tool_call_id": "toolu_01SE1jSkJiYHyQzVJT4iZ5C5"
    },
    {
      "role": "tool",
      "content": "{\"total_count\": 66, \"matches\": [{\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 61, \"content\": \"    logger.info(\\\"No .env file found. Using system environment variables.\\\")\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 62, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 63, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 64, \"content\": \"# Import our tool system\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 65, \"content\": \"from model_tools import (\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 66, \"content\": \"    get_tool_definitions,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 67, \"content\": \"    get_toolset_for_tool,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 68, \"content\": \"    handle_function_call,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 69, \"content\": \"    check_toolset_requirements,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 70, \"content\": \")\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 71, \"content\": \"from tools.terminal_tool import cleanup_vm\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 906, \"content\": \"            fb_m = self._fallback_model.get(\\\"model\\\", \\\"\\\")\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 907, \"content\": \"            if fb_p and fb_m and not self.quiet_mode:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 908, \"content\": \"                print(f\\\"🔄 Fallback model: {fb_m} ({fb_p})\\\")\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 909, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 910, \"content\": \"        # Get available tools with filtering\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 911, \"content\": \"        self.tools = get_tool_definitions(\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 912, \"content\": \"            enabled_toolsets=enabled_toolsets,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 913, \"content\": \"            disabled_toolsets=disabled_toolsets,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 914, \"content\": \"            quiet_mode=self.quiet_mode,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 915, \"content\": \"        )\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 916, \"content\": \"        \"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 1789, \"content\": \"                \\\"name\\\": func[\\\"name\\\"],\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 1790, \"content\": \"                \\\"description\\\": func.get(\\\"description\\\", \\\"\\\"),\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 1791, \"content\": \"                \\\"parameters\\\": func.get(\\\"parameters\\\", {}),\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 1792, \"content\": \"                \\\"required\\\": None  # Match the format in the example\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 1793, \"content\": \"            }\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 1794, \"content\": \"            formatted_tools.append(formatted_tool)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 1795, \"content\": \"        \"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 1796, \"content\": \"        return json.dumps(formatted_tools, ensure_ascii=False)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 1797, \"content\": \"    \"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 1798, \"content\": \"    def _convert_to_trajectory_format(self, messages: List[Dict[str, Any]], user_query: str, completed: bool) -> List[Dict[str, Any]]:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 1799, \"content\": \"        \\\"\\\"\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 1814, \"content\": \"            \\\"You are a function calling AI model. You are provided with function signatures within <tools> </tools> XML tags. \\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 1815, \"content\": \"            \\\"You may call one or more functions to assist with the user query. If available tools are not relevant in assisting \\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 1816, \"content\": \"            \\\"with user query, just respond in natural conversational language. Don't make assumptions about what values to plug \\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 1817, \"content\": \"            \\\"into functions. After calling & executing the functions, you will be provided with function results within \\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 1818, \"content\": \"            \\\"<tool_response> </tool_response> XML tags. Here are the available tools:\\\\n\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 1819, \"content\": \"            f\\\"<tools>\\\\n{self._format_tools_for_system_message()}\\\\n</tools>\\\\n\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 1820, \"content\": \"            \\\"For each function call return a JSON object, with the following pydantic model json schema for each:\\\\n\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 1821, \"content\": \"            \\\"{'title': 'FunctionCall', 'type': 'object', 'properties': {'name': {'title': 'Name', 'type': 'string'}, \\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 1822, \"content\": \"            \\\"'arguments': {'title': 'Arguments', 'type': 'object'}}, 'required': ['name', 'arguments']}\\\\n\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 1823, \"content\": \"            \\\"Each function call should be enclosed within <tool_call> </tool_call> XML tags.\\\\n\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 1824, \"content\": \"            \\\"Example:\\\\n<tool_call>\\\\n{'name': <function-name>,'arguments': <args-dict>}\\\\n</tool_call>\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 2361, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 2362, \"content\": \"        set_session_context(self._honcho, self._honcho_session_key)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 2363, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 2364, \"content\": \"        # Rebuild tool surface after Honcho context injection. Tool availability\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 2365, \"content\": \"        # is check_fn-gated and may change once session context is attached.\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 2366, \"content\": \"        self.tools = get_tool_definitions(\"}], \"truncated\": true}\n\n[Hint: Results truncated. Use offset=50 to see more, or narrow with a more specific pattern or file_glob.]",
      "tool_call_id": "toolu_012UrvdPYUjQfjUGDprT2UvG"
    },
    {
      "role": "tool",
      "content": "{\"content\": \"     1|\\\"\\\"\\\"\\n     2|Hermes tool call parser.\\n     3|\\n     4|Format: <tool_call>{\\\"name\\\": \\\"func\\\", \\\"arguments\\\": {...}}</tool_call>\\n     5|Based on VLLM's Hermes2ProToolParser.extract_tool_calls()\\n     6|\\\"\\\"\\\"\\n     7|\\n     8|import json\\n     9|import re\\n    10|import uuid\\n    11|from typing import List, Optional, Tuple\\n    12|\\n    13|from openai.types.chat.chat_completion_message_tool_call import (\\n    14|    ChatCompletionMessageToolCall,\\n    15|    Function,\\n    16|)\\n    17|\\n    18|from environments.tool_call_parsers import ParseResult, ToolCallParser, register_parser\\n    19|\\n    20|\\n    21|@register_parser(\\\"hermes\\\")\\n    22|class HermesToolCallParser(ToolCallParser):\\n    23|    \\\"\\\"\\\"\\n    24|    Parser for Hermes-format tool calls.\\n    25|\\n    26|    Matches <tool_call>...</tool_call> tags containing JSON with \\\"name\\\" and \\\"arguments\\\".\\n    27|    Also handles unclosed <tool_call> at end-of-string (truncated generation).\\n    28|    \\\"\\\"\\\"\\n    29|\\n    30|    # Matches both closed and unclosed tool_call tags\\n    31|    PATTERN = re.compile(\\n    32|        r\\\"<tool_call>\\\\s*(.*?)\\\\s*</tool_call>|<tool_call>\\\\s*(.*)\\\", re.DOTALL\\n    33|    )\\n    34|\\n    35|    def parse(self, text: str) -> ParseResult:\\n    36|        if \\\"<tool_call>\\\" not in text:\\n    37|            return text, None\\n    38|\\n    39|        try:\\n    40|            matches = self.PATTERN.findall(text)\\n    41|            if not matches:\\n    42|                return text, None\\n    43|\\n    44|            tool_calls: List[ChatCompletionMessageToolCall] = []\\n    45|            for match in matches:\\n    46|                # match is a tuple: (closed_content, unclosed_content)\\n    47|                raw_json = match[0] if match[0] else match[1]\\n    48|                if not raw_json.strip():\\n    49|                    continue\\n    50|\\n    51|                tc_data = json.loads(raw_json)\\n    52|                tool_calls.append(\\n    53|                    ChatCompletionMessageToolCall(\\n    54|                        id=f\\\"call_{uuid.uuid4().hex[:8]}\\\",\\n    55|                        type=\\\"function\\\",\\n    56|                        function=Function(\\n    57|                            name=tc_data[\\\"name\\\"],\\n    58|                            arguments=json.dumps(\\n    59|                                tc_data.get(\\\"arguments\\\", {}), ensure_ascii=False\\n    60|                            ),\\n    61|                        ),\\n    62|                    )\\n    63|                )\\n    64|\\n    65|            if not tool_calls:\\n    66|                return text, None\\n    67|\\n    68|            # Content is everything before the first <tool_call> tag\\n    69|            content = text[: text.find(\\\"<tool_call>\\\")].strip()\\n    70|            return content if content else None, tool_calls\\n    71|\\n    72|        except Exception:\\n    73|            return text, None\\n    74|\", \"total_lines\": 73, \"file_size\": 2321, \"truncated\": false, \"is_binary\": false, \"is_image\": false}",
      "tool_call_id": "toolu_01NbWZmQBUMV2SdEQh55Pnb6"
    },
    {
      "role": "assistant",
      "content": "Now let me find how the tool definitions are formatted and sent to the API, and how tool_call parsing integrates with the main conversation loop:",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_012UrS2PgK9CJcX49BfGQH7f",
          "call_id": "toolu_012UrS2PgK9CJcX49BfGQH7f",
          "response_item_id": "fc_toolu_012UrS2PgK9CJcX49BfGQH7f",
          "type": "function",
          "function": {
            "name": "read_file",
            "arguments": "{\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"offset\": 1770, \"limit\": 80}"
          }
        },
        {
          "id": "toolu_01M3kfwhLwmhjPy27Fm1daDu",
          "call_id": "toolu_01M3kfwhLwmhjPy27Fm1daDu",
          "response_item_id": "fc_toolu_01M3kfwhLwmhjPy27Fm1daDu",
          "type": "function",
          "function": {
            "name": "search_files",
            "arguments": "{\"pattern\": \"tool_call_parser|hermes_parser|parse_tool_call|_parse_hermes|text_tool_call\", \"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"context\": 5}"
          }
        },
        {
          "id": "toolu_01EjFF1prkE5zuYYwzHobs8S",
          "call_id": "toolu_01EjFF1prkE5zuYYwzHobs8S",
          "response_item_id": "fc_toolu_01EjFF1prkE5zuYYwzHobs8S",
          "type": "function",
          "function": {
            "name": "search_files",
            "arguments": "{\"pattern\": \"tool_call_parser\", \"path\": \"/root/wizards/ezra/hermes-agent\", \"context\": 3, \"file_glob\": \"*.py\", \"output_mode\": \"files_only\"}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"content\": \"  1770|        \\n  1771|        # Return everything up to (not including) the last assistant message\\n  1772|        return messages[:last_assistant_idx]\\n  1773|    \\n  1774|    def _format_tools_for_system_message(self) -> str:\\n  1775|        \\\"\\\"\\\"\\n  1776|        Format tool definitions for the system message in the trajectory format.\\n  1777|        \\n  1778|        Returns:\\n  1779|            str: JSON string representation of tool definitions\\n  1780|        \\\"\\\"\\\"\\n  1781|        if not self.tools:\\n  1782|            return \\\"[]\\\"\\n  1783|        \\n  1784|        # Convert tool definitions to the format expected in trajectories\\n  1785|        formatted_tools = []\\n  1786|        for tool in self.tools:\\n  1787|            func = tool[\\\"function\\\"]\\n  1788|            formatted_tool = {\\n  1789|                \\\"name\\\": func[\\\"name\\\"],\\n  1790|                \\\"description\\\": func.get(\\\"description\\\", \\\"\\\"),\\n  1791|                \\\"parameters\\\": func.get(\\\"parameters\\\", {}),\\n  1792|                \\\"required\\\": None  # Match the format in the example\\n  1793|            }\\n  1794|            formatted_tools.append(formatted_tool)\\n  1795|        \\n  1796|        return json.dumps(formatted_tools, ensure_ascii=False)\\n  1797|    \\n  1798|    def _convert_to_trajectory_format(self, messages: List[Dict[str, Any]], user_query: str, completed: bool) -> List[Dict[str, Any]]:\\n  1799|        \\\"\\\"\\\"\\n  1800|        Convert internal message format to trajectory format for saving.\\n  1801|        \\n  1802|        Args:\\n  1803|            messages (List[Dict]): Internal message history\\n  1804|            user_query (str): Original user query\\n  1805|            completed (bool): Whether the conversation completed successfully\\n  1806|            \\n  1807|        Returns:\\n  1808|            List[Dict]: Messages in trajectory format\\n  1809|        \\\"\\\"\\\"\\n  1810|        trajectory = []\\n  1811|        \\n  1812|        # Add system message with tool definitions\\n  1813|        system_msg = (\\n  1814|            \\\"You are a function calling AI model. You are provided with function signatures within <tools> </tools> XML tags. \\\"\\n  1815|            \\\"You may call one or more functions to assist with the user query. If available tools are not relevant in assisting \\\"\\n  1816|            \\\"with user query, just respond in natural conversational language. Don't make assumptions about what values to plug \\\"\\n  1817|            \\\"into functions. After calling & executing the functions, you will be provided with function results within \\\"\\n  1818|            \\\"<tool_response> </tool_response> XML tags. Here are the available tools:\\\\n\\\"\\n  1819|            f\\\"<tools>\\\\n{self._format_tools_for_system_message()}\\\\n</tools>\\\\n\\\"\\n  1820|            \\\"For each function call return a JSON object, with the following pydantic model json schema for each:\\\\n\\\"\\n  1821|            \\\"{'title': 'FunctionCall', 'type': 'object', 'properties': {'name': {'title': 'Name', 'type': 'string'}, \\\"\\n  1822|            \\\"'arguments': {'title': 'Arguments', 'type': 'object'}}, 'required': ['name', 'arguments']}\\\\n\\\"\\n  1823|            \\\"Each function call should be enclosed within <tool_call> </tool_call> XML tags.\\\\n\\\"\\n  1824|            \\\"Example:\\\\n<tool_call>\\\\n{'name': <function-name>,'arguments': <args-dict>}\\\\n</tool_call>\\\"\\n  1825|        )\\n  1826|        \\n  1827|        trajectory.append({\\n  1828|            \\\"from\\\": \\\"system\\\",\\n  1829|            \\\"value\\\": system_msg\\n  1830|        })\\n  1831|        \\n  1832|        # Add the actual user prompt (from the dataset) as the first human message\\n  1833|        trajectory.append({\\n  1834|            \\\"from\\\": \\\"human\\\",\\n  1835|            \\\"value\\\": user_query\\n  1836|        })\\n  1837|        \\n  1838|        # Skip the first message (the user query) since we already added it above.\\n  1839|        # Prefill messages are injected at API-call time only (not in the messages\\n  1840|        # list), so no offset adjustment is needed here.\\n  1841|        i = 1\\n  1842|        \\n  1843|        while i < len(messages):\\n  1844|            msg = messages[i]\\n  1845|            \\n  1846|            if msg[\\\"role\\\"] == \\\"assistant\\\":\\n  1847|                # Check if this message has tool calls\\n  1848|                if \\\"tool_calls\\\" in msg and msg[\\\"tool_calls\\\"]:\\n  1849|                    # Format assistant message with tool calls\\n  1850|\", \"total_lines\": 8283, \"file_size\": 417579, \"truncated\": true, \"hint\": \"Use offset=1850 to continue reading (showing 1770-1849 of 8283 lines)\", \"is_binary\": false, \"is_image\": false}",
      "tool_call_id": "toolu_012UrS2PgK9CJcX49BfGQH7f"
    },
    {
      "role": "tool",
      "content": "{\"total_count\": 0}",
      "tool_call_id": "toolu_01M3kfwhLwmhjPy27Fm1daDu"
    },
    {
      "role": "tool",
      "content": "{\"total_count\": 19, \"files\": [\"/root/wizards/ezra/hermes-agent/tests/test_managed_server_tool_support.py\", \"/root/wizards/ezra/hermes-agent/tests/test_tool_call_parsers.py\", \"/root/wizards/ezra/hermes-agent/environments/terminal_test_env/terminal_test_env.py\", \"/root/wizards/ezra/hermes-agent/environments/agent_loop.py\", \"/root/wizards/ezra/hermes-agent/environments/hermes_swe_env/hermes_swe_env.py\", \"/root/wizards/ezra/hermes-agent/environments/__init__.py\", \"/root/wizards/ezra/hermes-agent/environments/hermes_base_env.py\", \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/hermes_parser.py\", \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/deepseek_v3_1_parser.py\", \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/mistral_parser.py\", \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/qwen3_coder_parser.py\", \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/longcat_parser.py\", \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/kimi_k2_parser.py\", \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/__init__.py\", \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/qwen_parser.py\", \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/deepseek_v3_parser.py\", \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/llama_parser.py\", \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/glm47_parser.py\", \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/glm45_parser.py\"]}",
      "tool_call_id": "toolu_01EjFF1prkE5zuYYwzHobs8S"
    },
    {
      "role": "assistant",
      "content": "",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_017vhYCfeaVnFqT62Jw8xzDE",
          "call_id": "toolu_017vhYCfeaVnFqT62Jw8xzDE",
          "response_item_id": "fc_toolu_017vhYCfeaVnFqT62Jw8xzDE",
          "type": "function",
          "function": {
            "name": "read_file",
            "arguments": "{\"path\": \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/__init__.py\"}"
          }
        },
        {
          "id": "toolu_01Fekq74krHEqn9tg5nPi2X7",
          "call_id": "toolu_01Fekq74krHEqn9tg5nPi2X7",
          "response_item_id": "fc_toolu_01Fekq74krHEqn9tg5nPi2X7",
          "type": "function",
          "function": {
            "name": "read_file",
            "arguments": "{\"path\": \"/root/wizards/ezra/hermes-agent/environments/hermes_base_env.py\", \"limit\": 100}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"content\": \"     1|\\\"\\\"\\\"\\n     2|Tool Call Parser Registry\\n     3|\\n     4|Client-side parsers that extract structured tool_calls from raw model output text.\\n     5|Used in Phase 2 (VLLM server type) where ManagedServer's /generate endpoint returns\\n     6|raw text without tool call parsing.\\n     7|\\n     8|Each parser is a standalone reimplementation of the corresponding VLLM parser's\\n     9|non-streaming extract_tool_calls() logic. No VLLM dependency -- only standard library\\n    10|(re, json, uuid) and openai types.\\n    11|\\n    12|Usage:\\n    13|    from environments.tool_call_parsers import get_parser\\n    14|\\n    15|    parser = get_parser(\\\"hermes\\\")\\n    16|    content, tool_calls = parser.parse(raw_model_output)\\n    17|    # content = text with tool call markup stripped\\n    18|    # tool_calls = list of ChatCompletionMessageToolCall objects, or None\\n    19|\\\"\\\"\\\"\\n    20|\\n    21|import logging\\n    22|from abc import ABC, abstractmethod\\n    23|from typing import Dict, List, Optional, Tuple, Type\\n    24|\\n    25|from openai.types.chat.chat_completion_message_tool_call import (\\n    26|    ChatCompletionMessageToolCall,\\n    27|)\\n    28|\\n    29|logger = logging.getLogger(__name__)\\n    30|\\n    31|# Type alias for parser return value\\n    32|ParseResult = Tuple[Optional[str], Optional[List[ChatCompletionMessageToolCall]]]\\n    33|\\n    34|\\n    35|class ToolCallParser(ABC):\\n    36|    \\\"\\\"\\\"\\n    37|    Base class for tool call parsers.\\n    38|\\n    39|    Each parser knows how to extract structured tool_calls from a specific\\n    40|    model family's raw output text format.\\n    41|    \\\"\\\"\\\"\\n    42|\\n    43|    @abstractmethod\\n    44|    def parse(self, text: str) -> ParseResult:\\n    45|        \\\"\\\"\\\"\\n    46|        Parse raw model output text for tool calls.\\n    47|\\n    48|        Args:\\n    49|            text: Raw decoded text from the model's completion\\n    50|\\n    51|        Returns:\\n    52|            Tuple of (content, tool_calls) where:\\n    53|            - content: text with tool call markup stripped (the message 'content' field),\\n    54|                       or None if the entire output was tool calls\\n    55|            - tool_calls: list of ChatCompletionMessageToolCall objects,\\n    56|                          or None if no tool calls were found\\n    57|        \\\"\\\"\\\"\\n    58|        raise NotImplementedError\\n    59|\\n    60|\\n    61|# Global parser registry: name -> parser class\\n    62|PARSER_REGISTRY: Dict[str, Type[ToolCallParser]] = {}\\n    63|\\n    64|\\n    65|def register_parser(name: str):\\n    66|    \\\"\\\"\\\"\\n    67|    Decorator to register a parser class under a given name.\\n    68|\\n    69|    Usage:\\n    70|        @register_parser(\\\"hermes\\\")\\n    71|        class HermesToolCallParser(ToolCallParser):\\n    72|            ...\\n    73|    \\\"\\\"\\\"\\n    74|\\n    75|    def decorator(cls: Type[ToolCallParser]) -> Type[ToolCallParser]:\\n    76|        PARSER_REGISTRY[name] = cls\\n    77|        return cls\\n    78|\\n    79|    return decorator\\n    80|\\n    81|\\n    82|def get_parser(name: str) -> ToolCallParser:\\n    83|    \\\"\\\"\\\"\\n    84|    Get a parser instance by name.\\n    85|\\n    86|    Args:\\n    87|        name: Parser name (e.g., \\\"hermes\\\", \\\"mistral\\\", \\\"llama3_json\\\")\\n    88|\\n    89|    Returns:\\n    90|        Instantiated parser\\n    91|\\n    92|    Raises:\\n    93|        KeyError: If parser name is not found in registry\\n    94|    \\\"\\\"\\\"\\n    95|    if name not in PARSER_REGISTRY:\\n    96|        available = sorted(PARSER_REGISTRY.keys())\\n    97|        raise KeyError(\\n    98|            f\\\"Tool call parser '{name}' not found. Available parsers: {available}\\\"\\n    99|        )\\n   100|    return PARSER_REGISTRY[name]()\\n   101|\\n   102|\\n   103|def list_parsers() -> List[str]:\\n   104|    \\\"\\\"\\\"Return sorted list of registered parser names.\\\"\\\"\\\"\\n   105|    return sorted(PARSER_REGISTRY.keys())\\n   106|\\n   107|\\n   108|# Import all parser modules to trigger registration via @register_parser decorators\\n   109|# Each module registers itself when imported\\n   110|from environments.tool_call_parsers.hermes_parser import HermesToolCallParser  # noqa: E402, F401\\n   111|from environments.tool_call_parsers.longcat_parser import LongcatToolCallParser  # noqa: E402, F401\\n   112|from environments.tool_call_parsers.mistral_parser import MistralToolCallParser  # noqa: E402, F401\\n   113|from environments.tool_call_parsers.llama_parser import LlamaToolCallParser  # noqa: E402, F401\\n   114|from environments.tool_call_parsers.qwen_parser import QwenToolCallParser  # noqa: E402, F401\\n   115|from environments.tool_call_parsers.deepseek_v3_parser import DeepSeekV3ToolCallParser  # noqa: E402, F401\\n   116|from environments.tool_call_parsers.deepseek_v3_1_parser import DeepSeekV31ToolCallParser  # noqa: E402, F401\\n   117|from environments.tool_call_parsers.kimi_k2_parser import KimiK2ToolCallParser  # noqa: E402, F401\\n   118|from environments.tool_call_parsers.glm45_parser import Glm45ToolCallParser  # noqa: E402, F401\\n   119|from environments.tool_call_parsers.glm47_parser import Glm47ToolCallParser  # noqa: E402, F401\\n   120|from environments.tool_call_parsers.qwen3_coder_parser import Qwen3CoderToolCallParser  # noqa: E402, F401\\n   121|\", \"total_lines\": 120, \"file_size\": 4284, \"truncated\": false, \"is_binary\": false, \"is_image\": false}",
      "tool_call_id": "toolu_017vhYCfeaVnFqT62Jw8xzDE"
    },
    {
      "role": "tool",
      "content": "{\"content\": \"     1|\\\"\\\"\\\"\\n     2|HermesAgentBaseEnv -- Abstract Base Environment for Hermes-Agent + Atropos\\n     3|\\n     4|Provides the Atropos integration plumbing that all hermes-agent environments share:\\n     5|- Two-mode operation (OpenAI server for Phase 1, VLLM ManagedServer for Phase 2)\\n     6|- Per-group toolset/distribution resolution\\n     7|- Agent loop orchestration via HermesAgentLoop\\n     8|- ToolContext creation for reward functions\\n     9|- ScoredDataGroup construction from ManagedServer state\\n    10|\\n    11|Subclasses only need to implement:\\n    12|    setup()           -- Load dataset, initialize state\\n    13|    get_next_item()   -- Return the next item from the dataset\\n    14|    format_prompt()   -- Convert a dataset item into the user message\\n    15|    compute_reward()  -- Score the rollout (has full ToolContext access)\\n    16|    evaluate()        -- Periodic evaluation\\n    17|\\\"\\\"\\\"\\n    18|\\n    19|import asyncio\\n    20|import json\\n    21|import logging\\n    22|import os\\n    23|import sys\\n    24|import uuid\\n    25|from abc import abstractmethod\\n    26|from pathlib import Path\\n    27|from typing import Any, Dict, List, Optional, Set, Tuple, Union\\n    28|\\n    29|# Ensure the hermes-agent repo root is on sys.path so that imports like\\n    30|# `from model_tools import ...` and `from environments.X import ...` work\\n    31|# regardless of where the script is invoked from.\\n    32|_repo_root = Path(__file__).resolve().parent.parent\\n    33|if str(_repo_root) not in sys.path:\\n    34|    sys.path.insert(0, str(_repo_root))\\n    35|\\n    36|from dotenv import load_dotenv\\n    37|from pydantic import Field\\n    38|\\n    39|# Load API keys from hermes-agent/.env so all environments can access them\\n    40|_env_path = _repo_root / \\\".env\\\"\\n    41|if _env_path.exists():\\n    42|    load_dotenv(dotenv_path=_env_path)\\n    43|\\n    44|# Apply monkey patches for async-safe tool operation inside Atropos's event loop.\\n    45|# This patches SwerexModalEnvironment to use a background thread instead of\\n    46|# asyncio.run(), which would deadlock inside Atropos. Safe for normal CLI too.\\n    47|from environments.patches import apply_patches\\n    48|apply_patches()\\n    49|\\n    50|from atroposlib.envs.base import (\\n    51|    BaseEnv,\\n    52|    BaseEnvConfig,\\n    53|    ScoredDataGroup,\\n    54|    ScoredDataItem,\\n    55|)\\n    56|from atroposlib.envs.server_handling.server_manager import (\\n    57|    APIServerConfig,\\n    58|    ServerBaseline,\\n    59|    ServerManager,\\n    60|)\\n    61|from atroposlib.type_definitions import Item\\n    62|\\n    63|from environments.agent_loop import AgentResult, HermesAgentLoop\\n    64|from environments.tool_context import ToolContext\\n    65|\\n    66|# Import hermes-agent toolset infrastructure\\n    67|from model_tools import get_tool_definitions\\n    68|from toolset_distributions import sample_toolsets_from_distribution\\n    69|\\n    70|logger = logging.getLogger(__name__)\\n    71|\\n    72|\\n    73|class HermesAgentEnvConfig(BaseEnvConfig):\\n    74|    \\\"\\\"\\\"\\n    75|    Configuration for hermes-agent Atropos environments.\\n    76|\\n    77|    Extends BaseEnvConfig with agent-specific settings for toolsets,\\n    78|    terminal backend, dataset loading, and tool call parsing.\\n    79|    \\\"\\\"\\\"\\n    80|\\n    81|    # --- Toolset configuration ---\\n    82|    # Mutually exclusive: use either enabled_toolsets OR distribution\\n    83|    enabled_toolsets: Optional[List[str]] = Field(\\n    84|        default=None,\\n    85|        description=\\\"Explicit list of hermes toolsets to enable (e.g., ['terminal', 'file', 'web']). \\\"\\n    86|        \\\"If None and distribution is also None, all available toolsets are enabled.\\\",\\n    87|    )\\n    88|    disabled_toolsets: Optional[List[str]] = Field(\\n    89|        default=None,\\n    90|        description=\\\"Toolsets to disable. Applied as a filter on top of enabled_toolsets or distribution.\\\",\\n    91|    )\\n    92|    distribution: Optional[str] = Field(\\n    93|        default=None,\\n    94|        description=\\\"Name of a toolset distribution from toolset_distributions.py \\\"\\n    95|        \\\"(e.g., 'development', 'terminal_tasks'). Sampled once per group. \\\"\\n    96|        \\\"Mutually exclusive with enabled_toolsets.\\\",\\n    97|    )\\n    98|\\n    99|    # --- Agent loop configuration ---\\n   100|    max_agent_turns: int = Field(\\n   101|\", \"total_lines\": 670, \"file_size\": 27096, \"truncated\": true, \"hint\": \"Use offset=101 to continue reading (showing 1-100 of 670 lines)\", \"is_binary\": false, \"is_image\": false}",
      "tool_call_id": "toolu_01Fekq74krHEqn9tg5nPi2X7"
    },
    {
      "role": "assistant",
      "content": "Now let me find how tools are actually passed to the API call in the main conversation loop:",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_01A8Yd4SXhkXB6Y144hQ9Poc",
          "call_id": "toolu_01A8Yd4SXhkXB6Y144hQ9Poc",
          "response_item_id": "fc_toolu_01A8Yd4SXhkXB6Y144hQ9Poc",
          "type": "function",
          "function": {
            "name": "search_files",
            "arguments": "{\"pattern\": \"def.*_call_api|def.*_make_request|def.*_send_request|chat\\\\.completions\\\\.create|client\\\\.chat\", \"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"context\": 3}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"total_count\": 35, \"matches\": [{\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3772, \"content\": \"                    result[\\\"response\\\"] = self._anthropic_messages_create(api_kwargs)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3773, \"content\": \"                else:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3774, \"content\": \"                    request_client_holder[\\\"client\\\"] = self._create_request_openai_client(reason=\\\"chat_completion_request\\\")\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3775, \"content\": \"                    result[\\\"response\\\"] = request_client_holder[\\\"client\\\"].chat.completions.create(**api_kwargs)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3776, \"content\": \"            except Exception as e:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3777, \"content\": \"                result[\\\"error\\\"] = e\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3778, \"content\": \"            finally:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3926, \"content\": \"            # Reset stale-stream timer so the detector measures from this\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3927, \"content\": \"            # attempt's start, not a previous attempt's last chunk.\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3928, \"content\": \"            last_chunk_time[\\\"t\\\"] = time.time()\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3929, \"content\": \"            stream = request_client_holder[\\\"client\\\"].chat.completions.create(**stream_kwargs)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3930, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3931, \"content\": \"            content_parts: list = []\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3932, \"content\": \"            tool_calls_acc: dict = {}\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5092, \"content\": \"                    \\\"temperature\\\": 0.3,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5093, \"content\": \"                    **self._max_tokens_param(5120),\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5094, \"content\": \"                }\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5095, \"content\": \"                response = self._ensure_primary_openai_client(reason=\\\"flush_memories\\\").chat.completions.create(**api_kwargs, timeout=30.0)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5096, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5097, \"content\": \"            # Extract tool calls from the response, handling all API formats\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5098, \"content\": \"            tool_calls = []\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5909, \"content\": \"                    _msg, _ = _nar(summary_response, strip_tool_prefix=self._is_anthropic_oauth)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5910, \"content\": \"                    final_response = (_msg.content or \\\"\\\").strip()\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5911, \"content\": \"                else:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5912, \"content\": \"                    summary_response = self._ensure_primary_openai_client(reason=\\\"iteration_limit_summary\\\").chat.completions.create(**summary_kwargs)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5913, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5914, \"content\": \"                    if summary_response.choices and summary_response.choices[0].message.content:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5915, \"content\": \"                        final_response = summary_response.choices[0].message.content\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5950, \"content\": \"                    if summary_extra_body:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5951, \"content\": \"                        summary_kwargs[\\\"extra_body\\\"] = summary_extra_body\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5952, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5953, \"content\": \"                    summary_response = self._ensure_primary_openai_client(reason=\\\"iteration_limit_summary_retry\\\").chat.completions.create(**summary_kwargs)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5954, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5955, \"content\": \"                    if summary_response.choices and summary_response.choices[0].message.content:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5956, \"content\": \"                        final_response = summary_response.choices[0].message.content\"}]}",
      "tool_call_id": "toolu_01A8Yd4SXhkXB6Y144hQ9Poc"
    },
    {
      "role": "assistant",
      "content": "",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_01Ejdt99GzbfQ6363Jm6UmAB",
          "call_id": "toolu_01Ejdt99GzbfQ6363Jm6UmAB",
          "response_item_id": "fc_toolu_01Ejdt99GzbfQ6363Jm6UmAB",
          "type": "function",
          "function": {
            "name": "read_file",
            "arguments": "{\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"offset\": 3700, \"limit\": 150}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"content\": \"  3700|\\n  3701|        if not self._replace_primary_openai_client(reason=\\\"nous_credential_refresh\\\"):\\n  3702|            return False\\n  3703|\\n  3704|        return True\\n  3705|\\n  3706|    def _try_refresh_anthropic_client_credentials(self) -> bool:\\n  3707|        if self.api_mode != \\\"anthropic_messages\\\" or not hasattr(self, \\\"_anthropic_api_key\\\"):\\n  3708|            return False\\n  3709|        # Only refresh credentials for the native Anthropic provider.\\n  3710|        # Other anthropic_messages providers (MiniMax, Alibaba, etc.) use their own keys.\\n  3711|        if self.provider != \\\"anthropic\\\":\\n  3712|            return False\\n  3713|\\n  3714|        try:\\n  3715|            from agent.anthropic_adapter import resolve_anthropic_token, build_anthropic_client\\n  3716|\\n  3717|            new_token=resolv...en()\\n  3718|        except Exception as exc:\\n  3719|            logger.debug(\\\"Anthropic credential refresh failed: %s\\\", exc)\\n  3720|            return False\\n  3721|\\n  3722|        if not isinstance(new_token, str) or not new_token.strip():\\n  3723|            return False\\n  3724|        new_token=***\\n  3725|        if new_token=*** self._anthropic_api_key:\\n  3726|            return False\\n  3727|\\n  3728|        try:\\n  3729|            self._anthropic_client.close()\\n  3730|        except Exception:\\n  3731|            pass\\n  3732|\\n  3733|        try:\\n  3734|            self._anthropic_client = build_anthropic_client(new_token, getattr(self, \\\"_anthropic_base_url\\\", None))\\n  3735|        except Exception as exc:\\n  3736|            logger.warning(\\\"Failed to rebuild Anthropic client after credential refresh: %s\\\", exc)\\n  3737|            return False\\n  3738|\\n  3739|        self._anthropic_api_key=***\\n  3740|        # Update OAuth flag — token type may have changed (API key ↔ OAuth)\\n  3741|        from agent.anthropic_adapter import _is_oauth_token\\n  3742|        self._is_anthropic_oauth=_is_oa...ken)\\n  3743|        return True\\n  3744|\\n  3745|    def _anthropic_messages_create(self, api_kwargs: dict):\\n  3746|        if self.api_mode == \\\"anthropic_messages\\\":\\n  3747|            self._try_refresh_anthropic_client_credentials()\\n  3748|        return self._anthropic_client.messages.create(**api_kwargs)\\n  3749|\\n  3750|    def _interruptible_api_call(self, api_kwargs: dict):\\n  3751|        \\\"\\\"\\\"\\n  3752|        Run the API call in a background thread so the main conversation loop\\n  3753|        can detect interrupts without waiting for the full HTTP round-trip.\\n  3754|\\n  3755|        Each worker thread gets its own OpenAI client instance. Interrupts only\\n  3756|        close that worker-local client, so retries and other requests never\\n  3757|        inherit a closed transport.\\n  3758|        \\\"\\\"\\\"\\n  3759|        result = {\\\"response\\\": None, \\\"error\\\": None}\\n  3760|        request_client_holder = {\\\"client\\\": None}\\n  3761|\\n  3762|        def _call():\\n  3763|            try:\\n  3764|                if self.api_mode == \\\"codex_responses\\\":\\n  3765|                    request_client_holder[\\\"client\\\"] = self._create_request_openai_client(reason=\\\"codex_stream_request\\\")\\n  3766|                    result[\\\"response\\\"] = self._run_codex_stream(\\n  3767|                        api_kwargs,\\n  3768|                        client=request_client_holder[\\\"client\\\"],\\n  3769|                        on_first_delta=getattr(self, \\\"_codex_on_first_delta\\\", None),\\n  3770|                    )\\n  3771|                elif self.api_mode == \\\"anthropic_messages\\\":\\n  3772|                    result[\\\"response\\\"] = self._anthropic_messages_create(api_kwargs)\\n  3773|                else:\\n  3774|                    request_client_holder[\\\"client\\\"] = self._create_request_openai_client(reason=\\\"chat_completion_request\\\")\\n  3775|                    result[\\\"response\\\"] = request_client_holder[\\\"client\\\"].chat.completions.create(**api_kwargs)\\n  3776|            except Exception as e:\\n  3777|                result[\\\"error\\\"] = e\\n  3778|            finally:\\n  3779|                request_client = request_client_holder.get(\\\"client\\\")\\n  3780|                if request_client is not None:\\n  3781|                    self._close_request_openai_client(request_client, reason=\\\"request_complete\\\")\\n  3782|\\n  3783|        t = threading.Thread(target=_call, daemon=True)\\n  3784|        t.start()\\n  3785|        while t.is_alive():\\n  3786|            t.join(timeout=0.3)\\n  3787|            if self._interrupt_requested:\\n  3788|                # Force-close the in-flight worker-local HTTP connection to stop\\n  3789|                # token generation without poisoning the shared client used to\\n  3790|                # seed future retries.\\n  3791|                try:\\n  3792|                    if self.api_mode == \\\"anthropic_messages\\\":\\n  3793|                        from agent.anthropic_adapter import build_anthropic_client\\n  3794|\\n  3795|                        self._anthropic_client.close()\\n  3796|                        self._anthropic_client = build_anthropic_client(\\n  3797|                            self._anthropic_api_key,\\n  3798|                            getattr(self, \\\"_anthropic_base_url\\\", None),\\n  3799|                        )\\n  3800|                    else:\\n  3801|                        request_client = request_client_holder.get(\\\"client\\\")\\n  3802|                        if request_client is not None:\\n  3803|                            self._close_request_openai_client(request_client, reason=\\\"interrupt_abort\\\")\\n  3804|                except Exception:\\n  3805|                    pass\\n  3806|                raise InterruptedError(\\\"Agent interrupted during API call\\\")\\n  3807|        if result[\\\"error\\\"] is not None:\\n  3808|            raise result[\\\"error\\\"]\\n  3809|        return result[\\\"response\\\"]\\n  3810|\\n  3811|    # ── Unified streaming API call ─────────────────────────────────────────\\n  3812|\\n  3813|    def _fire_stream_delta(self, text: str) -> None:\\n  3814|        \\\"\\\"\\\"Fire all registered stream delta callbacks (display + TTS).\\\"\\\"\\\"\\n  3815|        # If a tool iteration set the break flag, prepend a single paragraph\\n  3816|        # break before the first real text delta.  This prevents the original\\n  3817|        # problem (text concatenation across tool boundaries) without stacking\\n  3818|        # blank lines when multiple tool iterations run back-to-back.\\n  3819|        if getattr(self, \\\"_stream_needs_break\\\", False) and text and text.strip():\\n  3820|            self._stream_needs_break = False\\n  3821|            text = \\\"\\\\n\\\\n\\\" + text\\n  3822|        for cb in (self.stream_delta_callback, self._stream_callback):\\n  3823|            if cb is not None:\\n  3824|                try:\\n  3825|                    cb(text)\\n  3826|                except Exception:\\n  3827|                    pass\\n  3828|\\n  3829|    def _fire_reasoning_delta(self, text: str) -> None:\\n  3830|        \\\"\\\"\\\"Fire reasoning callback if registered.\\\"\\\"\\\"\\n  3831|        self._reasoning_deltas_fired = True\\n  3832|        cb = self.reasoning_callback\\n  3833|        if cb is not None:\\n  3834|            try:\\n  3835|                cb(text)\\n  3836|            except Exception:\\n  3837|                pass\\n  3838|\\n  3839|    def _fire_tool_gen_started(self, tool_name: str) -> None:\\n  3840|        \\\"\\\"\\\"Notify display layer that the model is generating tool call arguments.\\n  3841|\\n  3842|        Fires once per tool name when the streaming response begins producing\\n  3843|        tool_call / tool_use tokens.  Gives the TUI a chance to show a spinner\\n  3844|        or status line so the user isn't staring at a frozen screen while a\\n  3845|        large tool payload (e.g. a 45 KB write_file) is being generated.\\n  3846|        \\\"\\\"\\\"\\n  3847|        cb = self.tool_gen_callback\\n  3848|        if cb is not None:\\n  3849|            try:\\n  3850|\", \"total_lines\": 8283, \"file_size\": 417579, \"truncated\": true, \"hint\": \"Use offset=3850 to continue reading (showing 3700-3849 of 8283 lines)\", \"is_binary\": false, \"is_image\": false}",
      "tool_call_id": "toolu_01Ejdt99GzbfQ6363Jm6UmAB"
    },
    {
      "role": "assistant",
      "content": "Now let me find where `api_kwargs` is built, specifically where tools are added:",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_01Dq6gP8DjbQ8dwfYtYHiiUE",
          "call_id": "toolu_01Dq6gP8DjbQ8dwfYtYHiiUE",
          "response_item_id": "fc_toolu_01Dq6gP8DjbQ8dwfYtYHiiUE",
          "type": "function",
          "function": {
            "name": "search_files",
            "arguments": "{\"pattern\": \"api_kwargs.*tools|\\\\\\\"tools\\\\\\\".*self\\\\.tools|api_kwargs\\\\[.tools\", \"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"context\": 5}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"total_count\": 33, \"matches\": [{\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 2189, \"content\": \"                \\\"base_url\\\": self.base_url,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 2190, \"content\": \"                \\\"platform\\\": self.platform,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 2191, \"content\": \"                \\\"session_start\\\": self.session_start.isoformat(),\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 2192, \"content\": \"                \\\"last_updated\\\": datetime.now().isoformat(),\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 2193, \"content\": \"                \\\"system_prompt\\\": self._cached_system_prompt or \\\"\\\",\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 2194, \"content\": \"                \\\"tools\\\": self.tools or [],\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 2195, \"content\": \"                \\\"message_count\\\": len(cleaned),\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 2196, \"content\": \"                \\\"messages\\\": cleaned,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 2197, \"content\": \"            }\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 2198, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 2199, \"content\": \"            atomic_json_write(\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3148, \"content\": \"            instructions = str(instructions)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3149, \"content\": \"        instructions = instructions.strip() or DEFAULT_AGENT_IDENTITY\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3150, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3151, \"content\": \"        normalized_input = self._preflight_codex_input_items(api_kwargs.get(\\\"input\\\"))\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3152, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3153, \"content\": \"        tools = api_kwargs.get(\\\"tools\\\")\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3154, \"content\": \"        normalized_tools = None\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3155, \"content\": \"        if tools is not None:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3156, \"content\": \"            if not isinstance(tools, list):\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3157, \"content\": \"                raise ValueError(\\\"Codex Responses request 'tools' must be a list when provided.\\\")\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3158, \"content\": \"            normalized_tools = []\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 4704, \"content\": \"            provider_preferences[\\\"data_collection\\\"] = self.provider_data_collection\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 4705, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 4706, \"content\": \"        api_kwargs = {\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 4707, \"content\": \"            \\\"model\\\": self.model,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 4708, \"content\": \"            \\\"messages\\\": sanitized_messages,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 4709, \"content\": \"            \\\"tools\\\": self.tools if self.tools else None,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 4710, \"content\": \"            \\\"timeout\\\": float(os.getenv(\\\"HERMES_API_TIMEOUT\\\", 1800.0)),\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 4711, \"content\": \"        }\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 4712, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 4713, \"content\": \"        if self.max_tokens is not None:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 4714, \"content\": \"            api_kwargs.update(self._max_tokens_param(self.max_tokens))\"}]}",
      "tool_call_id": "toolu_01Dq6gP8DjbQ8dwfYtYHiiUE"
    },
    {
      "role": "assistant",
      "content": "",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_017dRUb7pD1Yco16MqkuuMFx",
          "call_id": "toolu_017dRUb7pD1Yco16MqkuuMFx",
          "response_item_id": "fc_toolu_017dRUb7pD1Yco16MqkuuMFx",
          "type": "function",
          "function": {
            "name": "read_file",
            "arguments": "{\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"offset\": 4690, \"limit\": 120}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"content\": \"  4690|                            tool_call.pop(\\\"response_item_id\\\", None)\\n  4691|\\n  4692|        provider_preferences = {}\\n  4693|        if self.providers_allowed:\\n  4694|            provider_preferences[\\\"only\\\"] = self.providers_allowed\\n  4695|        if self.providers_ignored:\\n  4696|            provider_preferences[\\\"ignore\\\"] = self.providers_ignored\\n  4697|        if self.providers_order:\\n  4698|            provider_preferences[\\\"order\\\"] = self.providers_order\\n  4699|        if self.provider_sort:\\n  4700|            provider_preferences[\\\"sort\\\"] = self.provider_sort\\n  4701|        if self.provider_require_parameters:\\n  4702|            provider_preferences[\\\"require_parameters\\\"] = True\\n  4703|        if self.provider_data_collection:\\n  4704|            provider_preferences[\\\"data_collection\\\"] = self.provider_data_collection\\n  4705|\\n  4706|        api_kwargs = {\\n  4707|            \\\"model\\\": self.model,\\n  4708|            \\\"messages\\\": sanitized_messages,\\n  4709|            \\\"tools\\\": self.tools if self.tools else None,\\n  4710|            \\\"timeout\\\": float(os.getenv(\\\"HERMES_API_TIMEOUT\\\", 1800.0)),\\n  4711|        }\\n  4712|\\n  4713|        if self.max_tokens is not None:\\n  4714|            api_kwargs.update(self._max_tokens_param(self.max_tokens))\\n  4715|        elif self._is_openrouter_url() and \\\"claude\\\" in (self.model or \\\"\\\").lower():\\n  4716|            # OpenRouter translates requests to Anthropic's Messages API,\\n  4717|            # which requires max_tokens as a mandatory field.  When we omit\\n  4718|            # it, OpenRouter picks a default that can be too low — the model\\n  4719|            # spends its output budget on thinking and has almost nothing\\n  4720|            # left for the actual response (especially large tool calls like\\n  4721|            # write_file).  Sending the model's real output limit ensures\\n  4722|            # full capacity.  Other providers handle the default fine.\\n  4723|            try:\\n  4724|                from agent.anthropic_adapter import _get_anthropic_max_output\\n  4725|                _model_output_limit = _get_anthropic_max_output(self.model)\\n  4726|                api_kwargs[\\\"max_tokens\\\"] = _model_output_limit\\n  4727|            except Exception:\\n  4728|                pass  # fail open — let OpenRouter pick its default\\n  4729|\\n  4730|        extra_body = {}\\n  4731|\\n  4732|        _is_openrouter = self._is_openrouter_url()\\n  4733|        _is_github_models = (\\n  4734|            \\\"models.github.ai\\\" in self._base_url_lower\\n  4735|            or \\\"api.githubcopilot.com\\\" in self._base_url_lower\\n  4736|        )\\n  4737|\\n  4738|        # Provider preferences (only, ignore, order, sort) are OpenRouter-\\n  4739|        # specific.  Only send to OpenRouter-compatible endpoints.\\n  4740|        # TODO: Nous Portal will add transparent proxy support — re-enable\\n  4741|        # for _is_nous when their backend is updated.\\n  4742|        if provider_preferences and _is_openrouter:\\n  4743|            extra_body[\\\"provider\\\"] = provider_preferences\\n  4744|        _is_nous = \\\"nousresearch\\\" in self._base_url_lower\\n  4745|\\n  4746|        if self._supports_reasoning_extra_body():\\n  4747|            if _is_github_models:\\n  4748|                github_reasoning = self._github_models_reasoning_extra_body()\\n  4749|                if github_reasoning is not None:\\n  4750|                    extra_body[\\\"reasoning\\\"] = github_reasoning\\n  4751|            else:\\n  4752|                if self.reasoning_config is not None:\\n  4753|                    rc = dict(self.reasoning_config)\\n  4754|                    # Nous Portal requires reasoning enabled — don't send\\n  4755|                    # enabled=false to it (would cause 400).\\n  4756|                    if _is_nous and rc.get(\\\"enabled\\\") is False:\\n  4757|                        pass  # omit reasoning entirely for Nous when disabled\\n  4758|                    else:\\n  4759|                        extra_body[\\\"reasoning\\\"] = rc\\n  4760|                else:\\n  4761|                    extra_body[\\\"reasoning\\\"] = {\\n  4762|                        \\\"enabled\\\": True,\\n  4763|                        \\\"effort\\\": \\\"medium\\\"\\n  4764|                    }\\n  4765|\\n  4766|        # Nous Portal product attribution\\n  4767|        if _is_nous:\\n  4768|            extra_body[\\\"tags\\\"] = [\\\"product=hermes-agent\\\"]\\n  4769|\\n  4770|        if extra_body:\\n  4771|            api_kwargs[\\\"extra_body\\\"] = extra_body\\n  4772|\\n  4773|        return api_kwargs\\n  4774|\\n  4775|    def _supports_reasoning_extra_body(self) -> bool:\\n  4776|        \\\"\\\"\\\"Return True when reasoning extra_body is safe to send for this route/model.\\n  4777|\\n  4778|        OpenRouter forwards unknown extra_body fields to upstream providers.\\n  4779|        Some providers/routes reject `reasoning` with 400s, so gate it to\\n  4780|        known reasoning-capable model families and direct Nous Portal.\\n  4781|        \\\"\\\"\\\"\\n  4782|        if \\\"nousresearch\\\" in self._base_url_lower:\\n  4783|            return True\\n  4784|        if \\\"ai-gateway.vercel.sh\\\" in self._base_url_lower:\\n  4785|            return True\\n  4786|        if \\\"models.github.ai\\\" in self._base_url_lower or \\\"api.githubcopilot.com\\\" in self._base_url_lower:\\n  4787|            try:\\n  4788|                from hermes_cli.models import github_model_reasoning_efforts\\n  4789|\\n  4790|                return bool(github_model_reasoning_efforts(self.model))\\n  4791|            except Exception:\\n  4792|                return False\\n  4793|        if \\\"openrouter\\\" not in self._base_url_lower:\\n  4794|            return False\\n  4795|        if \\\"api.mistral.ai\\\" in self._base_url_lower:\\n  4796|            return False\\n  4797|\\n  4798|        model = (self.model or \\\"\\\").lower()\\n  4799|        reasoning_model_prefixes = (\\n  4800|            \\\"deepseek/\\\",\\n  4801|            \\\"anthropic/\\\",\\n  4802|            \\\"openai/\\\",\\n  4803|            \\\"x-ai/\\\",\\n  4804|            \\\"google/gemini-2\\\",\\n  4805|            \\\"qwen/qwen3\\\",\\n  4806|        )\\n  4807|        return any(model.startswith(prefix) for prefix in reasoning_model_prefixes)\\n  4808|\\n  4809|    def _github_models_reasoning_extra_body(self) -> dict | None:\\n  4810|\", \"total_lines\": 8283, \"file_size\": 417579, \"truncated\": true, \"hint\": \"Use offset=4810 to continue reading (showing 4690-4809 of 8283 lines)\", \"is_binary\": false, \"is_image\": false}",
      "tool_call_id": "toolu_017dRUb7pD1Yco16MqkuuMFx"
    },
    {
      "role": "assistant",
      "content": "Now let me see how `self.tools` is structured (the tool definitions format) and how tool call responses are parsed:",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_014pvVQCy2VDMPvxVUTjhBEo",
          "call_id": "toolu_014pvVQCy2VDMPvxVUTjhBEo",
          "response_item_id": "fc_toolu_014pvVQCy2VDMPvxVUTjhBEo",
          "type": "function",
          "function": {
            "name": "search_files",
            "arguments": "{\"pattern\": \"def get_tool_definitions\", \"path\": \"/root/wizards/ezra/hermes-agent\", \"context\": 20, \"file_glob\": \"*.py\"}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"total_count\": 41, \"matches\": [{\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 214, \"content\": \"        \\\"browser_press\\\", \\\"browser_close\\\", \\\"browser_get_images\\\",\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 215, \"content\": \"        \\\"browser_vision\\\", \\\"browser_console\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 216, \"content\": \"    ],\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 217, \"content\": \"    \\\"cronjob_tools\\\": [\\\"cronjob\\\"],\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 218, \"content\": \"    \\\"rl_tools\\\": [\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 219, \"content\": \"        \\\"rl_list_environments\\\", \\\"rl_select_environment\\\",\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 220, \"content\": \"        \\\"rl_get_current_config\\\", \\\"rl_edit_config\\\",\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 221, \"content\": \"        \\\"rl_start_training\\\", \\\"rl_check_status\\\",\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 222, \"content\": \"        \\\"rl_stop_training\\\", \\\"rl_get_results\\\",\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 223, \"content\": \"        \\\"rl_list_runs\\\", \\\"rl_test_inference\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 224, \"content\": \"    ],\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 225, \"content\": \"    \\\"file_tools\\\": [\\\"read_file\\\", \\\"write_file\\\", \\\"patch\\\", \\\"search_files\\\"],\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 226, \"content\": \"    \\\"tts_tools\\\": [\\\"text_to_speech\\\"],\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 227, \"content\": \"}\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 228, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 229, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 230, \"content\": \"# =============================================================================\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 231, \"content\": \"# get_tool_definitions  (the main schema provider)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 232, \"content\": \"# =============================================================================\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 233, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 234, \"content\": \"def get_tool_definitions(\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 235, \"content\": \"    enabled_toolsets: List[str] = None,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 236, \"content\": \"    disabled_toolsets: List[str] = None,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 237, \"content\": \"    quiet_mode: bool = False,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 238, \"content\": \") -> List[Dict[str, Any]]:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 239, \"content\": \"    \\\"\\\"\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 240, \"content\": \"    Get tool definitions for model API calls with toolset-based filtering.\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 241, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 242, \"content\": \"    All tools must be part of a toolset to be accessible.\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 243, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 244, \"content\": \"    Args:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 245, \"content\": \"        enabled_toolsets: Only include tools from these toolsets.\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 246, \"content\": \"        disabled_toolsets: Exclude tools from these toolsets (if enabled_toolsets is None).\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 247, \"content\": \"        quiet_mode: Suppress status prints.\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 248, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 249, \"content\": \"    Returns:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 250, \"content\": \"        Filtered list of OpenAI-format tool definitions.\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 251, \"content\": \"    \\\"\\\"\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 252, \"content\": \"    # Determine which tool names the caller wants\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 253, \"content\": \"    tools_to_include: set = set()\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"line\": 254, \"content\": \"\"}]}",
      "tool_call_id": "toolu_014pvVQCy2VDMPvxVUTjhBEo"
    },
    {
      "role": "assistant",
      "content": "",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_01CB46PB3n2AfC2Lq8A7jThB",
          "call_id": "toolu_01CB46PB3n2AfC2Lq8A7jThB",
          "response_item_id": "fc_toolu_01CB46PB3n2AfC2Lq8A7jThB",
          "type": "function",
          "function": {
            "name": "read_file",
            "arguments": "{\"path\": \"/root/wizards/ezra/hermes-agent/model_tools.py\", \"offset\": 234, \"limit\": 80}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"content\": \"   234|def get_tool_definitions(\\n   235|    enabled_toolsets: List[str] = None,\\n   236|    disabled_toolsets: List[str] = None,\\n   237|    quiet_mode: bool = False,\\n   238|) -> List[Dict[str, Any]]:\\n   239|    \\\"\\\"\\\"\\n   240|    Get tool definitions for model API calls with toolset-based filtering.\\n   241|\\n   242|    All tools must be part of a toolset to be accessible.\\n   243|\\n   244|    Args:\\n   245|        enabled_toolsets: Only include tools from these toolsets.\\n   246|        disabled_toolsets: Exclude tools from these toolsets (if enabled_toolsets is None).\\n   247|        quiet_mode: Suppress status prints.\\n   248|\\n   249|    Returns:\\n   250|        Filtered list of OpenAI-format tool definitions.\\n   251|    \\\"\\\"\\\"\\n   252|    # Determine which tool names the caller wants\\n   253|    tools_to_include: set = set()\\n   254|\\n   255|    if enabled_toolsets:\\n   256|        for toolset_name in enabled_toolsets:\\n   257|            if validate_toolset(toolset_name):\\n   258|                resolved = resolve_toolset(toolset_name)\\n   259|                tools_to_include.update(resolved)\\n   260|                if not quiet_mode:\\n   261|                    print(f\\\"✅ Enabled toolset '{toolset_name}': {', '.join(resolved) if resolved else 'no tools'}\\\")\\n   262|            elif toolset_name in _LEGACY_TOOLSET_MAP:\\n   263|                legacy_tools = _LEGACY_TOOLSET_MAP[toolset_name]\\n   264|                tools_to_include.update(legacy_tools)\\n   265|                if not quiet_mode:\\n   266|                    print(f\\\"✅ Enabled legacy toolset '{toolset_name}': {', '.join(legacy_tools)}\\\")\\n   267|            else:\\n   268|                if not quiet_mode:\\n   269|                    print(f\\\"⚠️  Unknown toolset: {toolset_name}\\\")\\n   270|\\n   271|    elif disabled_toolsets:\\n   272|        from toolsets import get_all_toolsets\\n   273|        for ts_name in get_all_toolsets():\\n   274|            tools_to_include.update(resolve_toolset(ts_name))\\n   275|\\n   276|        for toolset_name in disabled_toolsets:\\n   277|            if validate_toolset(toolset_name):\\n   278|                resolved = resolve_toolset(toolset_name)\\n   279|                tools_to_include.difference_update(resolved)\\n   280|                if not quiet_mode:\\n   281|                    print(f\\\"🚫 Disabled toolset '{toolset_name}': {', '.join(resolved) if resolved else 'no tools'}\\\")\\n   282|            elif toolset_name in _LEGACY_TOOLSET_MAP:\\n   283|                legacy_tools = _LEGACY_TOOLSET_MAP[toolset_name]\\n   284|                tools_to_include.difference_update(legacy_tools)\\n   285|                if not quiet_mode:\\n   286|                    print(f\\\"🚫 Disabled legacy toolset '{toolset_name}': {', '.join(legacy_tools)}\\\")\\n   287|            else:\\n   288|                if not quiet_mode:\\n   289|                    print(f\\\"⚠️  Unknown toolset: {toolset_name}\\\")\\n   290|    else:\\n   291|        from toolsets import get_all_toolsets\\n   292|        for ts_name in get_all_toolsets():\\n   293|            tools_to_include.update(resolve_toolset(ts_name))\\n   294|\\n   295|    # Plugin-registered tools are now resolved through the normal toolset\\n   296|    # path — validate_toolset() / resolve_toolset() / get_all_toolsets()\\n   297|    # all check the tool registry for plugin-provided toolsets.  No bypass\\n   298|    # needed; plugins respect enabled_toolsets / disabled_toolsets like any\\n   299|    # other toolset.\\n   300|\\n   301|    # Ask the registry for schemas (only returns tools whose check_fn passes)\\n   302|    filtered_tools = registry.get_definitions(tools_to_include, quiet=quiet_mode)\\n   303|\\n   304|    # The set of tool names that actually passed check_fn filtering.\\n   305|    # Use this (not tools_to_include) for any downstream schema that references\\n   306|    # other tools by name — otherwise the model sees tools mentioned in\\n   307|    # descriptions that don't actually exist, and hallucinates calls to them.\\n   308|    available_tool_names = {t[\\\"function\\\"][\\\"name\\\"] for t in filtered_tools}\\n   309|\\n   310|    # Rebuild execute_code schema to only list sandbox tools that are actually\\n   311|    # available.  Without this, the model sees \\\"web_search is available in\\n   312|    # execute_code\\\" even when the API key isn't configured or the toolset is\\n   313|    # disabled (#560-discord).\\n   314|\", \"total_lines\": 472, \"file_size\": 19552, \"truncated\": true, \"hint\": \"Use offset=314 to continue reading (showing 234-313 of 472 lines)\", \"is_binary\": false, \"is_image\": false}",
      "tool_call_id": "toolu_01CB46PB3n2AfC2Lq8A7jThB"
    },
    {
      "role": "assistant",
      "content": "Now let me see how the tool_calls are actually extracted from the response, especially the streaming path:",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_01KBKDkYHpZZJW7gAyYMJD4y",
          "call_id": "toolu_01KBKDkYHpZZJW7gAyYMJD4y",
          "response_item_id": "fc_toolu_01KBKDkYHpZZJW7gAyYMJD4y",
          "type": "function",
          "function": {
            "name": "read_file",
            "arguments": "{\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"offset\": 3850, \"limit\": 200}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"content\": \"  3850|                cb(tool_name)\\n  3851|            except Exception:\\n  3852|                pass\\n  3853|\\n  3854|    def _has_stream_consumers(self) -> bool:\\n  3855|        \\\"\\\"\\\"Return True if any streaming consumer is registered.\\\"\\\"\\\"\\n  3856|        return (\\n  3857|            self.stream_delta_callback is not None\\n  3858|            or getattr(self, \\\"_stream_callback\\\", None) is not None\\n  3859|        )\\n  3860|\\n  3861|    def _interruptible_streaming_api_call(\\n  3862|        self, api_kwargs: dict, *, on_first_delta: callable = None\\n  3863|    ):\\n  3864|        \\\"\\\"\\\"Streaming variant of _interruptible_api_call for real-time token delivery.\\n  3865|\\n  3866|        Handles all three api_modes:\\n  3867|        - chat_completions: stream=True on OpenAI-compatible endpoints\\n  3868|        - anthropic_messages: client.messages.stream() via Anthropic SDK\\n  3869|        - codex_responses: delegates to _run_codex_stream (already streaming)\\n  3870|\\n  3871|        Fires stream_delta_callback and _stream_callback for each text token.\\n  3872|        Tool-call turns suppress the callback — only text-only final responses\\n  3873|        stream to the consumer.  Returns a SimpleNamespace that mimics the\\n  3874|        non-streaming response shape so the rest of the agent loop is unchanged.\\n  3875|\\n  3876|        Falls back to _interruptible_api_call on provider errors indicating\\n  3877|        streaming is not supported.\\n  3878|        \\\"\\\"\\\"\\n  3879|        if self.api_mode == \\\"codex_responses\\\":\\n  3880|            # Codex streams internally via _run_codex_stream. The main dispatch\\n  3881|            # in _interruptible_api_call already calls it; we just need to\\n  3882|            # ensure on_first_delta reaches it. Store it on the instance\\n  3883|            # temporarily so _run_codex_stream can pick it up.\\n  3884|            self._codex_on_first_delta = on_first_delta\\n  3885|            try:\\n  3886|                return self._interruptible_api_call(api_kwargs)\\n  3887|            finally:\\n  3888|                self._codex_on_first_delta = None\\n  3889|\\n  3890|        result = {\\\"response\\\": None, \\\"error\\\": None}\\n  3891|        request_client_holder = {\\\"client\\\": None}\\n  3892|        first_delta_fired = {\\\"done\\\": False}\\n  3893|        deltas_were_sent = {\\\"yes\\\": False}  # Track if any deltas were fired (for fallback)\\n  3894|        # Wall-clock timestamp of the last real streaming chunk.  The outer\\n  3895|        # poll loop uses this to detect stale connections that keep receiving\\n  3896|        # SSE keep-alive pings but no actual data.\\n  3897|        last_chunk_time = {\\\"t\\\": time.time()}\\n  3898|\\n  3899|        def _fire_first_delta():\\n  3900|            if not first_delta_fired[\\\"done\\\"] and on_first_delta:\\n  3901|                first_delta_fired[\\\"done\\\"] = True\\n  3902|                try:\\n  3903|                    on_first_delta()\\n  3904|                except Exception:\\n  3905|                    pass\\n  3906|\\n  3907|        def _call_chat_completions():\\n  3908|            \\\"\\\"\\\"Stream a chat completions response.\\\"\\\"\\\"\\n  3909|            import httpx as _httpx\\n  3910|            _base_timeout = float(os.getenv(\\\"HERMES_API_TIMEOUT\\\", 1800.0))\\n  3911|            _stream_read_timeout = float(os.getenv(\\\"HERMES_STREAM_READ_TIMEOUT\\\", 60.0))\\n  3912|            stream_kwargs = {\\n  3913|                **api_kwargs,\\n  3914|                \\\"stream\\\": True,\\n  3915|                \\\"stream_options\\\": {\\\"include_usage\\\": True},\\n  3916|                \\\"timeout\\\": _httpx.Timeout(\\n  3917|                    connect=30.0,\\n  3918|                    read=_stream_read_timeout,\\n  3919|                    write=_base_timeout,\\n  3920|                    pool=30.0,\\n  3921|                ),\\n  3922|            }\\n  3923|            request_client_holder[\\\"client\\\"] = self._create_request_openai_client(\\n  3924|                reason=\\\"chat_completion_stream_request\\\"\\n  3925|            )\\n  3926|            # Reset stale-stream timer so the detector measures from this\\n  3927|            # attempt's start, not a previous attempt's last chunk.\\n  3928|            last_chunk_time[\\\"t\\\"] = time.time()\\n  3929|            stream = request_client_holder[\\\"client\\\"].chat.completions.create(**stream_kwargs)\\n  3930|\\n  3931|            content_parts: list = []\\n  3932|            tool_calls_acc: dict = {}\\n  3933|            tool_gen_notified: set = set()\\n  3934|            # Ollama-compatible endpoints reuse index 0 for every tool call\\n  3935|            # in a parallel batch, distinguishing them only by id.  Track\\n  3936|            # the last seen id per raw index so we can detect a new tool\\n  3937|            # call starting at the same index and redirect it to a fresh slot.\\n  3938|            _last_id_at_idx: dict = {}      # raw_index -> last seen non-empty id\\n  3939|            _active_slot_by_idx: dict = {}  # raw_index -> current slot in tool_calls_acc\\n  3940|            finish_reason = None\\n  3941|            model_name = None\\n  3942|            role = \\\"assistant\\\"\\n  3943|            reasoning_parts: list = []\\n  3944|            usage_obj = None\\n  3945|            # Reset per-call reasoning tracking so _build_assistant_message\\n  3946|            # knows whether reasoning was already displayed during streaming.\\n  3947|            self._reasoning_deltas_fired = False\\n  3948|\\n  3949|            for chunk in stream:\\n  3950|                last_chunk_time[\\\"t\\\"] = time.time()\\n  3951|\\n  3952|                if self._interrupt_requested:\\n  3953|                    break\\n  3954|\\n  3955|                if not chunk.choices:\\n  3956|                    if hasattr(chunk, \\\"model\\\") and chunk.model:\\n  3957|                        model_name = chunk.model\\n  3958|                    # Usage comes in the final chunk with empty choices\\n  3959|                    if hasattr(chunk, \\\"usage\\\") and chunk.usage:\\n  3960|                        usage_obj = chunk.usage\\n  3961|                    continue\\n  3962|\\n  3963|                delta = chunk.choices[0].delta\\n  3964|                if hasattr(chunk, \\\"model\\\") and chunk.model:\\n  3965|                    model_name = chunk.model\\n  3966|\\n  3967|                # Accumulate reasoning content\\n  3968|                reasoning_text = getattr(delta, \\\"reasoning_content\\\", None) or getattr(delta, \\\"reasoning\\\", None)\\n  3969|                if reasoning_text:\\n  3970|                    reasoning_parts.append(reasoning_text)\\n  3971|                    _fire_first_delta()\\n  3972|                    self._fire_reasoning_delta(reasoning_text)\\n  3973|\\n  3974|                # Accumulate text content — fire callback only when no tool calls\\n  3975|                if delta and delta.content:\\n  3976|                    content_parts.append(delta.content)\\n  3977|                    if not tool_calls_acc:\\n  3978|                        _fire_first_delta()\\n  3979|                        self._fire_stream_delta(delta.content)\\n  3980|                        deltas_were_sent[\\\"yes\\\"] = True\\n  3981|                    else:\\n  3982|                        # Tool calls suppress regular content streaming (avoids\\n  3983|                        # displaying chatty \\\"I'll use the tool...\\\" text alongside\\n  3984|                        # tool calls).  But reasoning tags embedded in suppressed\\n  3985|                        # content should still reach the display — otherwise the\\n  3986|                        # reasoning box only appears as a post-response fallback,\\n  3987|                        # rendering it confusingly after the already-streamed\\n  3988|                        # response.  Route suppressed content through the stream\\n  3989|                        # delta callback so its tag extraction can fire the\\n  3990|                        # reasoning display.  Non-reasoning text is harmlessly\\n  3991|                        # suppressed by the CLI's _stream_delta when the stream\\n  3992|                        # box is already closed (tool boundary flush).\\n  3993|                        if self.stream_delta_callback:\\n  3994|                            try:\\n  3995|                                self.stream_delta_callback(delta.content)\\n  3996|                            except Exception:\\n  3997|                                pass\\n  3998|\\n  3999|                # Accumulate tool call deltas — notify display on first name\\n  4000|                if delta and delta.tool_calls:\\n  4001|                    for tc_delta in delta.tool_calls:\\n  4002|                        raw_idx = tc_delta.index if tc_delta.index is not None else 0\\n  4003|                        delta_id = tc_delta.id or \\\"\\\"\\n  4004|\\n  4005|                        # Ollama fix: detect a new tool call reusing the same\\n  4006|                        # raw index (different id) and redirect to a fresh slot.\\n  4007|                        if raw_idx not in _active_slot_by_idx:\\n  4008|                            _active_slot_by_idx[raw_idx] = raw_idx\\n  4009|                        if (\\n  4010|                            delta_id\\n  4011|                            and raw_idx in _last_id_at_idx\\n  4012|                            and delta_id != _last_id_at_idx[raw_idx]\\n  4013|                        ):\\n  4014|                            new_slot = max(tool_calls_acc, default=-1) + 1\\n  4015|                            _active_slot_by_idx[raw_idx] = new_slot\\n  4016|                        if delta_id:\\n  4017|                            _last_id_at_idx[raw_idx] = delta_id\\n  4018|                        idx = _active_slot_by_idx[raw_idx]\\n  4019|\\n  4020|                        if idx not in tool_calls_acc:\\n  4021|                            tool_calls_acc[idx] = {\\n  4022|                                \\\"id\\\": tc_delta.id or \\\"\\\",\\n  4023|                                \\\"type\\\": \\\"function\\\",\\n  4024|                                \\\"function\\\": {\\\"name\\\": \\\"\\\", \\\"arguments\\\": \\\"\\\"},\\n  4025|                                \\\"extra_content\\\": None,\\n  4026|                            }\\n  4027|                        entry = tool_calls_acc[idx]\\n  4028|                        if tc_delta.id:\\n  4029|                            entry[\\\"id\\\"] = tc_delta.id\\n  4030|                        if tc_delta.function:\\n  4031|                            if tc_delta.function.name:\\n  4032|                                entry[\\\"function\\\"][\\\"name\\\"] += tc_delta.function.name\\n  4033|                            if tc_delta.function.arguments:\\n  4034|                                entry[\\\"function\\\"][\\\"arguments\\\"] += tc_delta.function.arguments\\n  4035|                        extra = getattr(tc_delta, \\\"extra_content\\\", None)\\n  4036|                        if extra is None and hasattr(tc_delta, \\\"model_extra\\\"):\\n  4037|                            extra = (tc_delta.model_extra or {}).get(\\\"extra_content\\\")\\n  4038|                        if extra is not None:\\n  4039|                            if hasattr(extra, \\\"model_dump\\\"):\\n  4040|                                extra = extra.model_dump()\\n  4041|                            entry[\\\"extra_content\\\"] = extra\\n  4042|                        # Fire once per tool when the full name is available\\n  4043|                        name = entry[\\\"function\\\"][\\\"name\\\"]\\n  4044|                        if name and idx not in tool_gen_notified:\\n  4045|                            tool_gen_notified.add(idx)\\n  4046|                            _fire_first_delta()\\n  4047|                            self._fire_tool_gen_started(name)\\n  4048|\\n  4049|                if chunk.choices[0].finish_reason:\\n  4050|\", \"total_lines\": 8283, \"file_size\": 417579, \"truncated\": true, \"hint\": \"Use offset=4050 to continue reading (showing 3850-4049 of 8283 lines)\", \"is_binary\": false, \"is_image\": false}",
      "tool_call_id": "toolu_01KBKDkYHpZZJW7gAyYMJD4y"
    },
    {
      "role": "assistant",
      "content": "",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_01R1UDrDAaKtCSKFDMBwxzEz",
          "call_id": "toolu_01R1UDrDAaKtCSKFDMBwxzEz",
          "response_item_id": "fc_toolu_01R1UDrDAaKtCSKFDMBwxzEz",
          "type": "function",
          "function": {
            "name": "read_file",
            "arguments": "{\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"offset\": 4049, \"limit\": 120}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"content\": \"  4049|                if chunk.choices[0].finish_reason:\\n  4050|                    finish_reason = chunk.choices[0].finish_reason\\n  4051|\\n  4052|                # Usage in the final chunk\\n  4053|                if hasattr(chunk, \\\"usage\\\") and chunk.usage:\\n  4054|                    usage_obj = chunk.usage\\n  4055|\\n  4056|            # Build mock response matching non-streaming shape\\n  4057|            full_content = \\\"\\\".join(content_parts) or None\\n  4058|            mock_tool_calls = None\\n  4059|            if tool_calls_acc:\\n  4060|                mock_tool_calls = []\\n  4061|                for idx in sorted(tool_calls_acc):\\n  4062|                    tc = tool_calls_acc[idx]\\n  4063|                    mock_tool_calls.append(SimpleNamespace(\\n  4064|                        id=tc[\\\"id\\\"],\\n  4065|                        type=tc[\\\"type\\\"],\\n  4066|                        extra_content=tc.get(\\\"extra_content\\\"),\\n  4067|                        function=SimpleNamespace(\\n  4068|                            name=tc[\\\"function\\\"][\\\"name\\\"],\\n  4069|                            arguments=tc[\\\"function\\\"][\\\"arguments\\\"],\\n  4070|                        ),\\n  4071|                    ))\\n  4072|\\n  4073|            full_reasoning = \\\"\\\".join(reasoning_parts) or None\\n  4074|            mock_message = SimpleNamespace(\\n  4075|                role=role,\\n  4076|                content=full_content,\\n  4077|                tool_calls=mock_tool_calls,\\n  4078|                reasoning_content=full_reasoning,\\n  4079|            )\\n  4080|            mock_choice = SimpleNamespace(\\n  4081|                index=0,\\n  4082|                message=mock_message,\\n  4083|                finish_reason=finish_reason or \\\"stop\\\",\\n  4084|            )\\n  4085|            return SimpleNamespace(\\n  4086|                id=\\\"stream-\\\" + str(uuid.uuid4()),\\n  4087|                model=model_name,\\n  4088|                choices=[mock_choice],\\n  4089|                usage=usage_obj,\\n  4090|            )\\n  4091|\\n  4092|        def _call_anthropic():\\n  4093|            \\\"\\\"\\\"Stream an Anthropic Messages API response.\\n  4094|\\n  4095|            Fires delta callbacks for real-time token delivery, but returns\\n  4096|            the native Anthropic Message object from get_final_message() so\\n  4097|            the rest of the agent loop (validation, tool extraction, etc.)\\n  4098|            works unchanged.\\n  4099|            \\\"\\\"\\\"\\n  4100|            has_tool_use = False\\n  4101|            self._reasoning_deltas_fired = False\\n  4102|\\n  4103|            # Reset stale-stream timer for this attempt\\n  4104|            last_chunk_time[\\\"t\\\"] = time.time()\\n  4105|            # Use the Anthropic SDK's streaming context manager\\n  4106|            with self._anthropic_client.messages.stream(**api_kwargs) as stream:\\n  4107|                for event in stream:\\n  4108|                    if self._interrupt_requested:\\n  4109|                        break\\n  4110|\\n  4111|                    event_type = getattr(event, \\\"type\\\", None)\\n  4112|\\n  4113|                    if event_type == \\\"content_block_start\\\":\\n  4114|                        block = getattr(event, \\\"content_block\\\", None)\\n  4115|                        if block and getattr(block, \\\"type\\\", None) == \\\"tool_use\\\":\\n  4116|                            has_tool_use = True\\n  4117|                            tool_name = getattr(block, \\\"name\\\", None)\\n  4118|                            if tool_name:\\n  4119|                                _fire_first_delta()\\n  4120|                                self._fire_tool_gen_started(tool_name)\\n  4121|\\n  4122|                    elif event_type == \\\"content_block_delta\\\":\\n  4123|                        delta = getattr(event, \\\"delta\\\", None)\\n  4124|                        if delta:\\n  4125|                            delta_type = getattr(delta, \\\"type\\\", None)\\n  4126|                            if delta_type == \\\"text_delta\\\":\\n  4127|                                text = getattr(delta, \\\"text\\\", \\\"\\\")\\n  4128|                                if text and not has_tool_use:\\n  4129|                                    _fire_first_delta()\\n  4130|                                    self._fire_stream_delta(text)\\n  4131|                            elif delta_type == \\\"thinking_delta\\\":\\n  4132|                                thinking_text = getattr(delta, \\\"thinking\\\", \\\"\\\")\\n  4133|                                if thinking_text:\\n  4134|                                    _fire_first_delta()\\n  4135|                                    self._fire_reasoning_delta(thinking_text)\\n  4136|\\n  4137|                # Return the native Anthropic Message for downstream processing\\n  4138|                return stream.get_final_message()\\n  4139|\\n  4140|        def _call():\\n  4141|            import httpx as _httpx\\n  4142|\\n  4143|            _max_stream_retries = int(os.getenv(\\\"HERMES_STREAM_RETRIES\\\", 2))\\n  4144|\\n  4145|            try:\\n  4146|                for _stream_attempt in range(_max_stream_retries + 1):\\n  4147|                    try:\\n  4148|                        if self.api_mode == \\\"anthropic_messages\\\":\\n  4149|                            self._try_refresh_anthropic_client_credentials()\\n  4150|                            result[\\\"response\\\"] = _call_anthropic()\\n  4151|                        else:\\n  4152|                            result[\\\"response\\\"] = _call_chat_completions()\\n  4153|                        return  # success\\n  4154|                    except Exception as e:\\n  4155|                        if deltas_were_sent[\\\"yes\\\"]:\\n  4156|                            # Streaming failed AFTER some tokens were already\\n  4157|                            # delivered.  Don't retry or fall back — partial\\n  4158|                            # content already reached the user.\\n  4159|                            logger.warning(\\n  4160|                                \\\"Streaming failed after partial delivery, not retrying: %s\\\", e\\n  4161|                            )\\n  4162|                            result[\\\"error\\\"] = e\\n  4163|                            return\\n  4164|\\n  4165|                        _is_timeout = isinstance(\\n  4166|                            e, (_httpx.ReadTimeout, _httpx.ConnectTimeout, _httpx.PoolTimeout)\\n  4167|                        )\\n  4168|                        _is_conn_err = isinstance(\\n  4169|\", \"total_lines\": 8283, \"file_size\": 417579, \"truncated\": true, \"hint\": \"Use offset=4169 to continue reading (showing 4049-4168 of 8283 lines)\", \"is_binary\": false, \"is_image\": false}",
      "tool_call_id": "toolu_01R1UDrDAaKtCSKFDMBwxzEz"
    },
    {
      "role": "assistant",
      "content": "Now let me search for how the response is processed after the API call - specifically looking for where tool_calls from the response are handled and the Hermes text-based tool call parsing might kick in:",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_01ANmy5Hd5ZQL9pTkPWKB5p5",
          "call_id": "toolu_01ANmy5Hd5ZQL9pTkPWKB5p5",
          "response_item_id": "fc_toolu_01ANmy5Hd5ZQL9pTkPWKB5p5",
          "type": "function",
          "function": {
            "name": "search_files",
            "arguments": "{\"pattern\": \"_normalize_assistant_response|_build_assistant_message|hermes.*tool.*parse|parse.*hermes\", \"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"context\": 3}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"total_count\": 63, \"matches\": [{\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3942, \"content\": \"            role = \\\"assistant\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3943, \"content\": \"            reasoning_parts: list = []\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3944, \"content\": \"            usage_obj = None\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3945, \"content\": \"            # Reset per-call reasoning tracking so _build_assistant_message\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3946, \"content\": \"            # knows whether reasoning was already displayed during streaming.\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3947, \"content\": \"            self._reasoning_deltas_fired = False\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 3948, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 4838, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 4839, \"content\": \"        return {\\\"effort\\\": requested_effort}\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 4840, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 4841, \"content\": \"    def _build_assistant_message(self, assistant_message, finish_reason: str) -> dict:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 4842, \"content\": \"        \\\"\\\"\\\"Build a normalized assistant message dict from an API response message.\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 4843, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 4844, \"content\": \"        Handles reasoning extraction, reasoning_details, and optional tool_calls\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 6683, \"content\": \"                            assistant_message = response.choices[0].message\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 6684, \"content\": \"                            if not assistant_message.tool_calls:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 6685, \"content\": \"                                length_continue_retries += 1\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 6686, \"content\": \"                                interim_msg = self._build_assistant_message(assistant_message, finish_reason)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 6687, \"content\": \"                                messages.append(interim_msg)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 6688, \"content\": \"                                if assistant_message.content:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 6689, \"content\": \"                                    truncated_response_prefix += assistant_message.content\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7437, \"content\": \"                        self._codex_incomplete_retries = 0\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7438, \"content\": \"                    self._codex_incomplete_retries += 1\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7439, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7440, \"content\": \"                    interim_msg = self._build_assistant_message(assistant_message, finish_reason)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7441, \"content\": \"                    interim_has_content = bool((interim_msg.get(\\\"content\\\") or \\\"\\\").strip())\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7442, \"content\": \"                    interim_has_reasoning = bool(interim_msg.get(\\\"reasoning\\\", \\\"\\\").strip()) if isinstance(interim_msg.get(\\\"reasoning\\\"), str) else False\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7443, \"content\": \"                    interim_has_codex_reasoning = bool(interim_msg.get(\\\"codex_reasoning_items\\\"))\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7528, \"content\": \"                                \\\"error\\\": f\\\"Model generated invalid tool call: {invalid_preview}\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7529, \"content\": \"                            }\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7530, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7531, \"content\": \"                        assistant_msg = self._build_assistant_message(assistant_message, finish_reason)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7532, \"content\": \"                        messages.append(assistant_msg)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7533, \"content\": \"                        for tc in assistant_message.tool_calls:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7534, \"content\": \"                            if tc.function.name not in self.valid_tool_names:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7583, \"content\": \"                            self._invalid_json_retries = 0  # Reset for next attempt\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7584, \"content\": \"                            \"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7585, \"content\": \"                            # Append the assistant message with its (broken) tool_calls\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7586, \"content\": \"                            recovery_assistant = self._build_assistant_message(assistant_message, finish_reason)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7587, \"content\": \"                            messages.append(recovery_assistant)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7588, \"content\": \"                            \"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7589, \"content\": \"                            # Respond with tool error results for each tool call\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7616, \"content\": \"                        assistant_message.tool_calls\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7617, \"content\": \"                    )\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7618, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7619, \"content\": \"                    assistant_msg = self._build_assistant_message(assistant_message, finish_reason)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7620, \"content\": \"                    \"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7621, \"content\": \"                    # If this turn has both content AND tool_calls, capture the content\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7622, \"content\": \"                    # as a fallback final response. Common pattern: model delivers its\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 7838, \"content\": \"                        )\"}], \"truncated\": true}\n\n[Hint: Results truncated. Use offset=50 to see more, or narrow with a more specific pattern or file_glob.]",
      "tool_call_id": "toolu_01ANmy5Hd5ZQL9pTkPWKB5p5"
    },
    {
      "role": "assistant",
      "content": "",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_016Stbkc67RJp7upQQHtFERe",
          "call_id": "toolu_016Stbkc67RJp7upQQHtFERe",
          "response_item_id": "fc_toolu_016Stbkc67RJp7upQQHtFERe",
          "type": "function",
          "function": {
            "name": "read_file",
            "arguments": "{\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"offset\": 4841, \"limit\": 100}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"content\": \"  4841|    def _build_assistant_message(self, assistant_message, finish_reason: str) -> dict:\\n  4842|        \\\"\\\"\\\"Build a normalized assistant message dict from an API response message.\\n  4843|\\n  4844|        Handles reasoning extraction, reasoning_details, and optional tool_calls\\n  4845|        so both the tool-call path and the final-response path share one builder.\\n  4846|        \\\"\\\"\\\"\\n  4847|        reasoning_text = self._extract_reasoning(assistant_message)\\n  4848|        _from_structured = bool(reasoning_text)\\n  4849|\\n  4850|        # Fallback: extract inline <think> blocks from content when no structured\\n  4851|        # reasoning fields are present (some models/providers embed thinking\\n  4852|        # directly in the content rather than returning separate API fields).\\n  4853|        if not reasoning_text:\\n  4854|            content = assistant_message.content or \\\"\\\"\\n  4855|            think_blocks = re.findall(r'<think>(.*?)</think>', content, flags=re.DOTALL)\\n  4856|            if think_blocks:\\n  4857|                combined = \\\"\\\\n\\\\n\\\".join(b.strip() for b in think_blocks if b.strip())\\n  4858|                reasoning_text = combined or None\\n  4859|\\n  4860|        if reasoning_text and self.verbose_logging:\\n  4861|            logging.debug(f\\\"Captured reasoning ({len(reasoning_text)} chars): {reasoning_text}\\\")\\n  4862|\\n  4863|        if reasoning_text and self.reasoning_callback:\\n  4864|            # Skip callback when streaming is active — reasoning was already\\n  4865|            # displayed during the stream via one of two paths:\\n  4866|            #   (a) _fire_reasoning_delta (structured reasoning_content deltas)\\n  4867|            #   (b) _stream_delta tag extraction (<think>/<REASONING_SCRATCHPAD>)\\n  4868|            # When streaming is NOT active, always fire so non-streaming modes\\n  4869|            # (gateway, batch, quiet) still get reasoning.\\n  4870|            # Any reasoning that wasn't shown during streaming is caught by the\\n  4871|            # CLI post-response display fallback (cli.py _reasoning_shown_this_turn).\\n  4872|            if not self.stream_delta_callback:\\n  4873|                try:\\n  4874|                    self.reasoning_callback(reasoning_text)\\n  4875|                except Exception:\\n  4876|                    pass\\n  4877|\\n  4878|        msg = {\\n  4879|            \\\"role\\\": \\\"assistant\\\",\\n  4880|            \\\"content\\\": assistant_message.content or \\\"\\\",\\n  4881|            \\\"reasoning\\\": reasoning_text,\\n  4882|            \\\"finish_reason\\\": finish_reason,\\n  4883|        }\\n  4884|\\n  4885|        if hasattr(assistant_message, 'reasoning_details') and assistant_message.reasoning_details:\\n  4886|            # Pass reasoning_details back unmodified so providers (OpenRouter,\\n  4887|            # Anthropic, OpenAI) can maintain reasoning continuity across turns.\\n  4888|            # Each provider may include opaque fields (signature, encrypted_content)\\n  4889|            # that must be preserved exactly.\\n  4890|            raw_details = assistant_message.reasoning_details\\n  4891|            preserved = []\\n  4892|            for d in raw_details:\\n  4893|                if isinstance(d, dict):\\n  4894|                    preserved.append(d)\\n  4895|                elif hasattr(d, \\\"__dict__\\\"):\\n  4896|                    preserved.append(d.__dict__)\\n  4897|                elif hasattr(d, \\\"model_dump\\\"):\\n  4898|                    preserved.append(d.model_dump())\\n  4899|            if preserved:\\n  4900|                msg[\\\"reasoning_details\\\"] = preserved\\n  4901|\\n  4902|        # Codex Responses API: preserve encrypted reasoning items for\\n  4903|        # multi-turn continuity. These get replayed as input on the next turn.\\n  4904|        codex_items = getattr(assistant_message, \\\"codex_reasoning_items\\\", None)\\n  4905|        if codex_items:\\n  4906|            msg[\\\"codex_reasoning_items\\\"] = codex_items\\n  4907|\\n  4908|        if assistant_message.tool_calls:\\n  4909|            tool_calls = []\\n  4910|            for tool_call in assistant_message.tool_calls:\\n  4911|                raw_id = getattr(tool_call, \\\"id\\\", None)\\n  4912|                call_id = getattr(tool_call, \\\"call_id\\\", None)\\n  4913|                if not isinstance(call_id, str) or not call_id.strip():\\n  4914|                    embedded_call_id, _ = self._split_responses_tool_id(raw_id)\\n  4915|                    call_id = embedded_call_id\\n  4916|                if not isinstance(call_id, str) or not call_id.strip():\\n  4917|                    if isinstance(raw_id, str) and raw_id.strip():\\n  4918|                        call_id = raw_id.strip()\\n  4919|                    else:\\n  4920|                        call_id = f\\\"call_{uuid.uuid4().hex[:12]}\\\"\\n  4921|                call_id = call_id.strip()\\n  4922|\\n  4923|                response_item_id = getattr(tool_call, \\\"response_item_id\\\", None)\\n  4924|                if not isinstance(response_item_id, str) or not response_item_id.strip():\\n  4925|                    _, embedded_response_item_id = self._split_responses_tool_id(raw_id)\\n  4926|                    response_item_id = embedded_response_item_id\\n  4927|\\n  4928|                response_item_id = self._derive_responses_function_call_id(\\n  4929|                    call_id,\\n  4930|                    response_item_id if isinstance(response_item_id, str) else None,\\n  4931|                )\\n  4932|\\n  4933|                tc_dict = {\\n  4934|                    \\\"id\\\": call_id,\\n  4935|                    \\\"call_id\\\": call_id,\\n  4936|                    \\\"response_item_id\\\": response_item_id,\\n  4937|                    \\\"type\\\": tool_call.type,\\n  4938|                    \\\"function\\\": {\\n  4939|                        \\\"name\\\": tool_call.function.name,\\n  4940|                        \\\"arguments\\\": tool_call.function.arguments\\n  4941|\", \"total_lines\": 8283, \"file_size\": 417579, \"truncated\": true, \"hint\": \"Use offset=4941 to continue reading (showing 4841-4940 of 8283 lines)\", \"is_binary\": false, \"is_image\": false}",
      "tool_call_id": "toolu_016Stbkc67RJp7upQQHtFERe"
    },
    {
      "role": "assistant",
      "content": "Now let me look at the key part — where `_normalize_assistant_response` or the response processing happens, and whether there's Hermes-format text parsing:",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_014ufB1P7tGcShbv7rTUQpPk",
          "call_id": "toolu_014ufB1P7tGcShbv7rTUQpPk",
          "response_item_id": "fc_toolu_014ufB1P7tGcShbv7rTUQpPk",
          "type": "function",
          "function": {
            "name": "search_files",
            "arguments": "{\"pattern\": \"_normalize_assistant_response\", \"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"context\": 5}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"total_count\": 0}",
      "tool_call_id": "toolu_014ufB1P7tGcShbv7rTUQpPk"
    },
    {
      "role": "assistant",
      "content": "",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_01JJRaXp4UAkohSeLKNQFeoE",
          "call_id": "toolu_01JJRaXp4UAkohSeLKNQFeoE",
          "response_item_id": "fc_toolu_01JJRaXp4UAkohSeLKNQFeoE",
          "type": "function",
          "function": {
            "name": "search_files",
            "arguments": "{\"pattern\": \"def _nar\\\\b|_nar\\\\(\", \"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"context\": 10}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"total_count\": 21, \"matches\": [{\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5899, \"content\": \"                if summary_extra_body:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5900, \"content\": \"                    summary_kwargs[\\\"extra_body\\\"] = summary_extra_body\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5901, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5902, \"content\": \"                if self.api_mode == \\\"anthropic_messages\\\":\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5903, \"content\": \"                    from agent.anthropic_adapter import build_anthropic_kwargs as _bak, normalize_anthropic_response as _nar\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5904, \"content\": \"                    _ant_kw = _bak(model=self.model, messages=api_messages, tools=None,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5905, \"content\": \"                                   max_tokens=*** reasoning_config=self.reasoning_config,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5906, \"content\": \"                                   is_oauth=self._...uth,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5907, \"content\": \"                                   preserve_dots=self._anthropic_preserve_dots())\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5908, \"content\": \"                    summary_response = self._anthropic_messages_create(_ant_kw)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5909, \"content\": \"                    _msg, _ = _nar(summary_response, strip_tool_prefix=self._is_anthropic_oauth)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5910, \"content\": \"                    final_response = (_msg.content or \\\"\\\").strip()\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5911, \"content\": \"                else:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5912, \"content\": \"                    summary_response = self._ensure_primary_openai_client(reason=\\\"iteration_limit_summary\\\").chat.completions.create(**summary_kwargs)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5913, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5914, \"content\": \"                    if summary_response.choices and summary_response.choices[0].message.content:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5915, \"content\": \"                        final_response = summary_response.choices[0].message.content\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5916, \"content\": \"                    else:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5917, \"content\": \"                        final_response = \\\"\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5918, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"line\": 5919, \"content\": \"            if final_response:\"}]}",
      "tool_call_id": "toolu_01JJRaXp4UAkohSeLKNQFeoE"
    },
    {
      "role": "assistant",
      "content": "Now let me look at the main conversation loop where the response is received and tool_calls are checked:",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_01VZ7UMChzPciP8kxRMkbJN9",
          "call_id": "toolu_01VZ7UMChzPciP8kxRMkbJN9",
          "response_item_id": "fc_toolu_01VZ7UMChzPciP8kxRMkbJN9",
          "type": "function",
          "function": {
            "name": "read_file",
            "arguments": "{\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"offset\": 7460, \"limit\": 100}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"content\": \"  7460|                            and last_codex_items == interim_codex_items\\n  7461|                        )\\n  7462|                        if not duplicate_interim:\\n  7463|                            messages.append(interim_msg)\\n  7464|\\n  7465|                    if self._codex_incomplete_retries < 3:\\n  7466|                        if not self.quiet_mode:\\n  7467|                            self._vprint(f\\\"{self.log_prefix}↻ Codex response incomplete; continuing turn ({self._codex_incomplete_retries}/3)\\\")\\n  7468|                        self._session_messages = messages\\n  7469|                        self._save_session_log(messages)\\n  7470|                        continue\\n  7471|\\n  7472|                    self._codex_incomplete_retries = 0\\n  7473|                    self._persist_session(messages, conversation_history)\\n  7474|                    return {\\n  7475|                        \\\"final_response\\\": None,\\n  7476|                        \\\"messages\\\": messages,\\n  7477|                        \\\"api_calls\\\": api_call_count,\\n  7478|                        \\\"completed\\\": False,\\n  7479|                        \\\"partial\\\": True,\\n  7480|                        \\\"error\\\": \\\"Codex response remained incomplete after 3 continuation attempts\\\",\\n  7481|                    }\\n  7482|                elif hasattr(self, \\\"_codex_incomplete_retries\\\"):\\n  7483|                    self._codex_incomplete_retries = 0\\n  7484|                \\n  7485|                # Check for tool calls\\n  7486|                if assistant_message.tool_calls:\\n  7487|                    if not self.quiet_mode:\\n  7488|                        self._vprint(f\\\"{self.log_prefix}🔧 Processing {len(assistant_message.tool_calls)} tool call(s)...\\\")\\n  7489|                    \\n  7490|                    if self.verbose_logging:\\n  7491|                        for tc in assistant_message.tool_calls:\\n  7492|                            logging.debug(f\\\"Tool call: {tc.function.name} with args: {tc.function.arguments[:200]}...\\\")\\n  7493|                    \\n  7494|                    # Validate tool call names - detect model hallucinations\\n  7495|                    # Repair mismatched tool names before validating\\n  7496|                    for tc in assistant_message.tool_calls:\\n  7497|                        if tc.function.name not in self.valid_tool_names:\\n  7498|                            repaired = self._repair_tool_call(tc.function.name)\\n  7499|                            if repaired:\\n  7500|                                print(f\\\"{self.log_prefix}🔧 Auto-repaired tool name: '{tc.function.name}' -> '{repaired}'\\\")\\n  7501|                                tc.function.name = repaired\\n  7502|                    invalid_tool_calls = [\\n  7503|                        tc.function.name for tc in assistant_message.tool_calls\\n  7504|                        if tc.function.name not in self.valid_tool_names\\n  7505|                    ]\\n  7506|                    if invalid_tool_calls:\\n  7507|                        # Track retries for invalid tool calls\\n  7508|                        if not hasattr(self, '_invalid_tool_retries'):\\n  7509|                            self._invalid_tool_retries = 0\\n  7510|                        self._invalid_tool_retries += 1\\n  7511|\\n  7512|                        # Return helpful error to model — model can self-correct next turn\\n  7513|                        available = \\\", \\\".join(sorted(self.valid_tool_names))\\n  7514|                        invalid_name = invalid_tool_calls[0]\\n  7515|                        invalid_preview = invalid_name[:80] + \\\"...\\\" if len(invalid_name) > 80 else invalid_name\\n  7516|                        self._vprint(f\\\"{self.log_prefix}⚠️  Unknown tool '{invalid_preview}' — sending error to model for self-correction ({self._invalid_tool_retries}/3)\\\")\\n  7517|\\n  7518|                        if self._invalid_tool_retries >= 3:\\n  7519|                            self._vprint(f\\\"{self.log_prefix}❌ Max retries (3) for invalid tool calls exceeded. Stopping as partial.\\\", force=True)\\n  7520|                            self._invalid_tool_retries = 0\\n  7521|                            self._persist_session(messages, conversation_history)\\n  7522|                            return {\\n  7523|                                \\\"final_response\\\": None,\\n  7524|                                \\\"messages\\\": messages,\\n  7525|                                \\\"api_calls\\\": api_call_count,\\n  7526|                                \\\"completed\\\": False,\\n  7527|                                \\\"partial\\\": True,\\n  7528|                                \\\"error\\\": f\\\"Model generated invalid tool call: {invalid_preview}\\\"\\n  7529|                            }\\n  7530|\\n  7531|                        assistant_msg = self._build_assistant_message(assistant_message, finish_reason)\\n  7532|                        messages.append(assistant_msg)\\n  7533|                        for tc in assistant_message.tool_calls:\\n  7534|                            if tc.function.name not in self.valid_tool_names:\\n  7535|                                content = f\\\"Tool '{tc.function.name}' does not exist. Available tools: {available}\\\"\\n  7536|                            else:\\n  7537|                                content = \\\"Skipped: another tool call in this turn used an invalid name. Please retry this tool call.\\\"\\n  7538|                            messages.append({\\n  7539|                                \\\"role\\\": \\\"tool\\\",\\n  7540|                                \\\"tool_call_id\\\": tc.id,\\n  7541|                                \\\"content\\\": content,\\n  7542|                            })\\n  7543|                        continue\\n  7544|                    # Reset retry counter on successful tool call validation\\n  7545|                    if hasattr(self, '_invalid_tool_retries'):\\n  7546|                        self._invalid_tool_retries = 0\\n  7547|                    \\n  7548|                    # Validate tool call arguments are valid JSON\\n  7549|                    # Handle empty strings as empty objects (common model quirk)\\n  7550|                    invalid_json_args = []\\n  7551|                    for tc in assistant_message.tool_calls:\\n  7552|                        args = tc.function.arguments\\n  7553|                        if isinstance(args, (dict, list)):\\n  7554|                            tc.function.arguments = json.dumps(args)\\n  7555|                            continue\\n  7556|                        if args is not None and not isinstance(args, str):\\n  7557|                            tc.function.arguments = str(args)\\n  7558|                            args = tc.function.arguments\\n  7559|                        # Treat empty/whitespace strings as empty object\\n  7560|\", \"total_lines\": 8283, \"file_size\": 417579, \"truncated\": true, \"hint\": \"Use offset=7560 to continue reading (showing 7460-7559 of 8283 lines)\", \"is_binary\": false, \"is_image\": false}",
      "tool_call_id": "toolu_01VZ7UMChzPciP8kxRMkbJN9"
    },
    {
      "role": "assistant",
      "content": "Now let me search for the critical piece - how the response is obtained from the API and where `assistant_message` is first set in the main loop:",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_011JevbT9RHpSk1fhraugmVG",
          "call_id": "toolu_011JevbT9RHpSk1fhraugmVG",
          "response_item_id": "fc_toolu_011JevbT9RHpSk1fhraugmVG",
          "type": "function",
          "function": {
            "name": "read_file",
            "arguments": "{\"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\", \"offset\": 7340, \"limit\": 130}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"content\": \"  7340|                self._persist_session(messages, conversation_history)\\n  7341|                break\\n  7342|\\n  7343|            try:\\n  7344|                if self.api_mode == \\\"codex_responses\\\":\\n  7345|                    assistant_message, finish_reason = self._normalize_codex_response(response)\\n  7346|                elif self.api_mode == \\\"anthropic_messages\\\":\\n  7347|                    from agent.anthropic_adapter import normalize_anthropic_response\\n  7348|                    assistant_message, finish_reason = normalize_anthropic_response(\\n  7349|                        response, strip_tool_prefix=self._is_anthropic_oauth\\n  7350|                    )\\n  7351|                else:\\n  7352|                    assistant_message = response.choices[0].message\\n  7353|                \\n  7354|                # Normalize content to string — some OpenAI-compatible servers\\n  7355|                # (llama-server, etc.) return content as a dict or list instead\\n  7356|                # of a plain string, which crashes downstream .strip() calls.\\n  7357|                if assistant_message.content is not None and not isinstance(assistant_message.content, str):\\n  7358|                    raw = assistant_message.content\\n  7359|                    if isinstance(raw, dict):\\n  7360|                        assistant_message.content = raw.get(\\\"text\\\", \\\"\\\") or raw.get(\\\"content\\\", \\\"\\\") or json.dumps(raw)\\n  7361|                    elif isinstance(raw, list):\\n  7362|                        # Multimodal content list — extract text parts\\n  7363|                        parts = []\\n  7364|                        for part in raw:\\n  7365|                            if isinstance(part, str):\\n  7366|                                parts.append(part)\\n  7367|                            elif isinstance(part, dict) and part.get(\\\"type\\\") == \\\"text\\\":\\n  7368|                                parts.append(part.get(\\\"text\\\", \\\"\\\"))\\n  7369|                            elif isinstance(part, dict) and \\\"text\\\" in part:\\n  7370|                                parts.append(str(part[\\\"text\\\"]))\\n  7371|                        assistant_message.content = \\\"\\\\n\\\".join(parts)\\n  7372|                    else:\\n  7373|                        assistant_message.content = str(raw)\\n  7374|\\n  7375|                # Handle assistant response\\n  7376|                if assistant_message.content and not self.quiet_mode:\\n  7377|                    if self.verbose_logging:\\n  7378|                        self._vprint(f\\\"{self.log_prefix}🤖 Assistant: {assistant_message.content}\\\")\\n  7379|                    else:\\n  7380|                        self._vprint(f\\\"{self.log_prefix}🤖 Assistant: {assistant_message.content[:100]}{'...' if len(assistant_message.content) > 100 else ''}\\\")\\n  7381|\\n  7382|                # Notify progress callback of model's thinking (used by subagent\\n  7383|                # delegation to relay the child's reasoning to the parent display).\\n  7384|                # Guard: only fire for subagents (_delegate_depth >= 1) to avoid\\n  7385|                # spamming gateway platforms with the main agent's every thought.\\n  7386|                if (assistant_message.content and self.tool_progress_callback\\n  7387|                        and getattr(self, '_delegate_depth', 0) > 0):\\n  7388|                    _think_text = assistant_message.content.strip()\\n  7389|                    # Strip reasoning XML tags that shouldn't leak to parent display\\n  7390|                    _think_text = re.sub(\\n  7391|                        r'</?(?:REASONING_SCRATCHPAD|think|reasoning)>', '', _think_text\\n  7392|                    ).strip()\\n  7393|                    first_line = _think_text.split('\\\\n')[0][:80] if _think_text else \\\"\\\"\\n  7394|                    if first_line:\\n  7395|                        try:\\n  7396|                            self.tool_progress_callback(\\\"_thinking\\\", first_line)\\n  7397|                        except Exception:\\n  7398|                            pass\\n  7399|                \\n  7400|                # Check for incomplete <REASONING_SCRATCHPAD> (opened but never closed)\\n  7401|                # This means the model ran out of output tokens mid-reasoning — retry up to 2 times\\n  7402|                if has_incomplete_scratchpad(assistant_message.content or \\\"\\\"):\\n  7403|                    if not hasattr(self, '_incomplete_scratchpad_retries'):\\n  7404|                        self._incomplete_scratchpad_retries = 0\\n  7405|                    self._incomplete_scratchpad_retries += 1\\n  7406|                    \\n  7407|                    self._vprint(f\\\"{self.log_prefix}⚠️  Incomplete <REASONING_SCRATCHPAD> detected (opened but never closed)\\\")\\n  7408|                    \\n  7409|                    if self._incomplete_scratchpad_retries <= 2:\\n  7410|                        self._vprint(f\\\"{self.log_prefix}🔄 Retrying API call ({self._incomplete_scratchpad_retries}/2)...\\\")\\n  7411|                        # Don't add the broken message, just retry\\n  7412|                        continue\\n  7413|                    else:\\n  7414|                        # Max retries - discard this turn and save as partial\\n  7415|                        self._vprint(f\\\"{self.log_prefix}❌ Max retries (2) for incomplete scratchpad. Saving as partial.\\\", force=True)\\n  7416|                        self._incomplete_scratchpad_retries = 0\\n  7417|                        \\n  7418|                        rolled_back_messages = self._get_messages_up_to_last_assistant(messages)\\n  7419|                        self._cleanup_task_resources(effective_task_id)\\n  7420|                        self._persist_session(messages, conversation_history)\\n  7421|                        \\n  7422|                        return {\\n  7423|                            \\\"final_response\\\": None,\\n  7424|                            \\\"messages\\\": rolled_back_messages,\\n  7425|                            \\\"api_calls\\\": api_call_count,\\n  7426|                            \\\"completed\\\": False,\\n  7427|                            \\\"partial\\\": True,\\n  7428|                            \\\"error\\\": \\\"Incomplete REASONING_SCRATCHPAD after 2 retries\\\"\\n  7429|                        }\\n  7430|                \\n  7431|                # Reset incomplete scratchpad counter on clean response\\n  7432|                if hasattr(self, '_incomplete_scratchpad_retries'):\\n  7433|                    self._incomplete_scratchpad_retries = 0\\n  7434|\\n  7435|                if self.api_mode == \\\"codex_responses\\\" and finish_reason == \\\"incomplete\\\":\\n  7436|                    if not hasattr(self, \\\"_codex_incomplete_retries\\\"):\\n  7437|                        self._codex_incomplete_retries = 0\\n  7438|                    self._codex_incomplete_retries += 1\\n  7439|\\n  7440|                    interim_msg = self._build_assistant_message(assistant_message, finish_reason)\\n  7441|                    interim_has_content = bool((interim_msg.get(\\\"content\\\") or \\\"\\\").strip())\\n  7442|                    interim_has_reasoning = bool(interim_msg.get(\\\"reasoning\\\", \\\"\\\").strip()) if isinstance(interim_msg.get(\\\"reasoning\\\"), str) else False\\n  7443|                    interim_has_codex_reasoning = bool(interim_msg.get(\\\"codex_reasoning_items\\\"))\\n  7444|\\n  7445|                    if interim_has_content or interim_has_reasoning or interim_has_codex_reasoning:\\n  7446|                        last_msg = messages[-1] if messages else None\\n  7447|                        # Duplicate detection: two consecutive incomplete assistant\\n  7448|                        # messages with identical content AND reasoning are collapsed.\\n  7449|                        # For reasoning-only messages (codex_reasoning_items differ but\\n  7450|                        # visible content/reasoning are both empty), we also compare\\n  7451|                        # the encrypted items to avoid silently dropping new state.\\n  7452|                        last_codex_items = last_msg.get(\\\"codex_reasoning_items\\\") if isinstance(last_msg, dict) else None\\n  7453|                        interim_codex_items = interim_msg.get(\\\"codex_reasoning_items\\\")\\n  7454|                        duplicate_interim = (\\n  7455|                            isinstance(last_msg, dict)\\n  7456|                            and last_msg.get(\\\"role\\\") == \\\"assistant\\\"\\n  7457|                            and last_msg.get(\\\"finish_reason\\\") == \\\"incomplete\\\"\\n  7458|                            and (last_msg.get(\\\"content\\\") or \\\"\\\") == (interim_msg.get(\\\"content\\\") or \\\"\\\")\\n  7459|                            and (last_msg.get(\\\"reasoning\\\") or \\\"\\\") == (interim_msg.get(\\\"reasoning\\\") or \\\"\\\")\\n  7460|                            and last_codex_items == interim_codex_items\\n  7461|                        )\\n  7462|                        if not duplicate_interim:\\n  7463|                            messages.append(interim_msg)\\n  7464|\\n  7465|                    if self._codex_incomplete_retries < 3:\\n  7466|                        if not self.quiet_mode:\\n  7467|                            self._vprint(f\\\"{self.log_prefix}↻ Codex response incomplete; continuing turn ({self._codex_incomplete_retries}/3)\\\")\\n  7468|                        self._session_messages = messages\\n  7469|                        self._save_session_log(messages)\\n  7470|\", \"total_lines\": 8283, \"file_size\": 417579, \"truncated\": true, \"hint\": \"Use offset=7470 to continue reading (showing 7340-7469 of 8283 lines)\", \"is_binary\": false, \"is_image\": false}",
      "tool_call_id": "toolu_011JevbT9RHpSk1fhraugmVG"
    },
    {
      "role": "assistant",
      "content": "This is the critical part. At line 7351-7352, for `chat_completions` mode (which local llama.cpp uses), the code does:\n```python\nassistant_message = response.choices[0].message\n```\n\nThen at line 7486 it checks `if assistant_message.tool_calls:`. There is NO Hermes-format text parsing in the main conversation loop! The tool_call_parsers are only used in the `environments/` (Atropos RL training) code path, not in the main CLI agent.\n\nLet me verify this:",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_01C4G6NEgD6Nn7JELbCx7JNf",
          "call_id": "toolu_01C4G6NEgD6Nn7JELbCx7JNf",
          "response_item_id": "fc_toolu_01C4G6NEgD6Nn7JELbCx7JNf",
          "type": "function",
          "function": {
            "name": "search_files",
            "arguments": "{\"pattern\": \"from environments.tool_call_parsers|import.*hermes_parser|HermesToolCallParser\", \"path\": \"/root/wizards/ezra/hermes-agent/run_agent.py\"}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"total_count\": 0, \"_budget_warning\": \"[BUDGET: Iteration 21/30. 9 iterations left. Start consolidating your work.]\"}",
      "tool_call_id": "toolu_01C4G6NEgD6Nn7JELbCx7JNf"
    },
    {
      "role": "assistant",
      "content": "",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_014gDsmu1gdXE8j8c4tKumHo",
          "call_id": "toolu_014gDsmu1gdXE8j8c4tKumHo",
          "response_item_id": "fc_toolu_014gDsmu1gdXE8j8c4tKumHo",
          "type": "function",
          "function": {
            "name": "search_files",
            "arguments": "{\"pattern\": \"from environments.tool_call_parsers|import.*hermes_parser|HermesToolCallParser\", \"path\": \"/root/wizards/ezra/hermes-agent\", \"file_glob\": \"*.py\", \"output_mode\": \"files_only\"}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"total_count\": 15, \"files\": [\"/root/wizards/ezra/hermes-agent/tests/test_managed_server_tool_support.py\", \"/root/wizards/ezra/hermes-agent/tests/test_tool_call_parsers.py\", \"/root/wizards/ezra/hermes-agent/environments/agent_loop.py\", \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/hermes_parser.py\", \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/deepseek_v3_1_parser.py\", \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/mistral_parser.py\", \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/qwen3_coder_parser.py\", \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/longcat_parser.py\", \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/kimi_k2_parser.py\", \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/__init__.py\", \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/qwen_parser.py\", \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/deepseek_v3_parser.py\", \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/llama_parser.py\", \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/glm47_parser.py\", \"/root/wizards/ezra/hermes-agent/environments/tool_call_parsers/glm45_parser.py\"], \"_budget_warning\": \"[BUDGET: Iteration 22/30. 8 iterations left. Start consolidating your work.]\"}",
      "tool_call_id": "toolu_014gDsmu1gdXE8j8c4tKumHo"
    },
    {
      "role": "assistant",
      "content": "Confirmed - the Hermes parsers are ONLY used in the environments/ (Atropos RL training) path, NOT in run_agent.py which is the main CLI agent.\n\nNow let me check the config to see how \"local-llama.cpp\" gets resolved:",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_01F28FqvaYVjJr8Ddw7fej5g",
          "call_id": "toolu_01F28FqvaYVjJr8Ddw7fej5g",
          "response_item_id": "fc_toolu_01F28FqvaYVjJr8Ddw7fej5g",
          "type": "function",
          "function": {
            "name": "search_files",
            "arguments": "{\"pattern\": \"local.*llama|llama.*cpp|local-llama|custom.*provider\", \"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"context\": 3}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"total_count\": 92, \"matches\": [{\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 21, \"content\": \"from hermes_constants import OPENROUTER_BASE_URL\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 22, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 23, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 24, \"content\": \"def _normalize_custom_provider_name(value: str) -> str:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 25, \"content\": \"    return value.strip().lower().replace(\\\" \\\", \\\"-\\\")\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 26, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 27, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 128, \"content\": \"    return \\\"auto\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 129, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 130, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 131, \"content\": \"def _get_named_custom_provider(requested_provider: str) -> Optional[Dict[str, Any]]:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 132, \"content\": \"    requested_norm = _normalize_custom_provider_name(requested_provider or \\\"\\\")\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 133, \"content\": \"    if not requested_norm or requested_norm == \\\"custom\\\":\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 134, \"content\": \"        return None\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 135, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 136, \"content\": \"    # Raw names should only map to custom providers when they are not already\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 137, \"content\": \"    # valid built-in providers or aliases. Explicit menu keys like\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 138, \"content\": \"    # ``custom:local`` always target the saved custom provider.\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 139, \"content\": \"    if requested_norm == \\\"auto\\\":\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 140, \"content\": \"        return None\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 141, \"content\": \"    if not requested_norm.startswith(\\\"custom:\\\"):\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 147, \"content\": \"            return None\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 148, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 149, \"content\": \"    config = load_config()\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 150, \"content\": \"    custom_providers = config.get(\\\"custom_providers\\\")\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 151, \"content\": \"    if not isinstance(custom_providers, list):\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 152, \"content\": \"        return None\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 153, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 154, \"content\": \"    for entry in custom_providers:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 155, \"content\": \"        if not isinstance(entry, dict):\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 156, \"content\": \"            continue\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 157, \"content\": \"        name = entry.get(\\\"name\\\")\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 158, \"content\": \"        base_url = entry.get(\\\"base_url\\\")\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 159, \"content\": \"        if not isinstance(name, str) or not isinstance(base_url, str):\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 160, \"content\": \"            continue\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 161, \"content\": \"        name_norm = _normalize_custom_provider_name(name)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 162, \"content\": \"        menu_key = f\\\"custom:{name_norm}\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 163, \"content\": \"        if requested_norm not in {name_norm, menu_key}:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 164, \"content\": \"            continue\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 181, \"content\": \"    explicit_api_key: Optional[str] = None,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 182, \"content\": \"    explicit_base_url: Optional[str] = None,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 183, \"content\": \") -> Optional[Dict[str, Any]]:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 184, \"content\": \"    custom_provider = _get_named_custom_provider(requested_provider)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 185, \"content\": \"    if not custom_provider:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 186, \"content\": \"        return None\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 187, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 188, \"content\": \"    base_url = (\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 189, \"content\": \"        (explicit_base_url or \\\"\\\").strip()\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 190, \"content\": \"        or custom_provider.get(\\\"base_url\\\", \\\"\\\")\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/runtime_provider.py\", \"line\": 191, \"content\": \"    ).rstrip(\\\"/\\\")\"}], \"truncated\": true}\n\n[Hint: Results truncated. Use offset=50 to see more, or narrow with a more specific pattern or file_glob.]\n\n[BUDGET: Iteration 23/30. 7 iterations left. Start consolidating your work.]",
      "tool_call_id": "toolu_01F28FqvaYVjJr8Ddw7fej5g"
    },
    {
      "role": "assistant",
      "content": "Now let me check how `resolve_provider` in auth.py handles unknown provider names like \"local-llama.cpp\":",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_01Avmf9pnf6fx33bZgGYZuM1",
          "call_id": "toolu_01Avmf9pnf6fx33bZgGYZuM1",
          "response_item_id": "fc_toolu_01Avmf9pnf6fx33bZgGYZuM1",
          "type": "function",
          "function": {
            "name": "search_files",
            "arguments": "{\"pattern\": \"def resolve_provider\", \"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"context\": 30}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"total_count\": 61, \"matches\": [{\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 637, \"content\": \"        if not target:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 638, \"content\": \"            return False\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 639, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 640, \"content\": \"        providers = auth_store.get(\\\"providers\\\", {})\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 641, \"content\": \"        if target not in providers:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 642, \"content\": \"            return False\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 643, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 644, \"content\": \"        del providers[target]\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 645, \"content\": \"        if auth_store.get(\\\"active_provider\\\") == target:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 646, \"content\": \"            auth_store[\\\"active_provider\\\"] = None\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 647, \"content\": \"        _save_auth_store(auth_store)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 648, \"content\": \"    return True\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 649, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 650, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 651, \"content\": \"def deactivate_provider() -> None:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 652, \"content\": \"    \\\"\\\"\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 653, \"content\": \"    Clear active_provider in auth.json without deleting credentials.\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 654, \"content\": \"    Used when the user switches to a non-OAuth provider (OpenRouter, custom)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 655, \"content\": \"    so auto-resolution doesn't keep picking the OAuth provider.\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 656, \"content\": \"    \\\"\\\"\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 657, \"content\": \"    with _auth_store_lock():\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 658, \"content\": \"        auth_store=_load_...re()\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 659, \"content\": \"        auth_store[\\\"active_provider\\\"] = None\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 660, \"content\": \"        _save_auth_store(auth_store)\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 661, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 662, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 663, \"content\": \"# =============================================================================\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 664, \"content\": \"# Provider Resolution — picks which provider to use\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 665, \"content\": \"# =============================================================================\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 666, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 667, \"content\": \"def resolve_provider(\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 668, \"content\": \"    requested: Optional[str] = None,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 669, \"content\": \"    *,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 670, \"content\": \"    explicit_api_key: Optional[str] = None,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 671, \"content\": \"    explicit_base_url: Optional[str] = None,\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 672, \"content\": \") -> str:\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 673, \"content\": \"    \\\"\\\"\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 674, \"content\": \"    Determine which inference provider to use.\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 675, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 676, \"content\": \"    Priority (when requested=\\\"auto\\\" or None):\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 677, \"content\": \"    1. active_provider in auth.json with valid credentials\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 678, \"content\": \"    2. Explicit CLI api_key/base_url -> \\\"openrouter\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 679, \"content\": \"    3. OPENAI_API_KEY or OPENROUTER_API_KEY env vars -> \\\"openrouter\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 680, \"content\": \"    4. Provider-specific API keys (GLM, Kimi, MiniMax) -> that provider\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 681, \"content\": \"    5. Fallback: \\\"openrouter\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 682, \"content\": \"    \\\"\\\"\\\"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 683, \"content\": \"    normalized = (requested or \\\"auto\\\").strip().lower()\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 684, \"content\": \"\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 685, \"content\": \"    # Normalize provider aliases\"}, {\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"line\": 686, \"content\": \"    _PROVIDER_ALIASES = {\"}], \"truncated\": true}\n\n[Hint: Results truncated. Use offset=50 to see more, or narrow with a more specific pattern or file_glob.]\n\n[BUDGET: Iteration 24/30. 6 iterations left. Start consolidating your work.]",
      "tool_call_id": "toolu_01Avmf9pnf6fx33bZgGYZuM1"
    },
    {
      "role": "assistant",
      "content": "",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_01AgDERfWCbkDPWnpehcpswx",
          "call_id": "toolu_01AgDERfWCbkDPWnpehcpswx",
          "response_item_id": "fc_toolu_01AgDERfWCbkDPWnpehcpswx",
          "type": "function",
          "function": {
            "name": "read_file",
            "arguments": "{\"path\": \"/root/wizards/ezra/hermes-agent/hermes_cli/auth.py\", \"offset\": 667, \"limit\": 80}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"content\": \"   667|def resolve_provider(\\n   668|    requested: Optional[str] = None,\\n   669|    *,\\n   670|    explicit_api_key: Optional[str] = None,\\n   671|    explicit_base_url: Optional[str] = None,\\n   672|) -> str:\\n   673|    \\\"\\\"\\\"\\n   674|    Determine which inference provider to use.\\n   675|\\n   676|    Priority (when requested=\\\"auto\\\" or None):\\n   677|    1. active_provider in auth.json with valid credentials\\n   678|    2. Explicit CLI api_key/base_url -> \\\"openrouter\\\"\\n   679|    3. OPENAI_API_KEY or OPENROUTER_API_KEY env vars -> \\\"openrouter\\\"\\n   680|    4. Provider-specific API keys (GLM, Kimi, MiniMax) -> that provider\\n   681|    5. Fallback: \\\"openrouter\\\"\\n   682|    \\\"\\\"\\\"\\n   683|    normalized = (requested or \\\"auto\\\").strip().lower()\\n   684|\\n   685|    # Normalize provider aliases\\n   686|    _PROVIDER_ALIASES = {\\n   687|        \\\"glm\\\": \\\"zai\\\", \\\"z-ai\\\": \\\"zai\\\", \\\"z.ai\\\": \\\"zai\\\", \\\"zhipu\\\": \\\"zai\\\",\\n   688|        \\\"kimi\\\": \\\"kimi-coding\\\", \\\"moonshot\\\": \\\"kimi-coding\\\",\\n   689|        \\\"minimax-china\\\": \\\"minimax-cn\\\", \\\"minimax_cn\\\": \\\"minimax-cn\\\",\\n   690|        \\\"claude\\\": \\\"anthropic\\\", \\\"claude-code\\\": \\\"anthropic\\\",\\n   691|        \\\"github\\\": \\\"copilot\\\", \\\"github-copilot\\\": \\\"copilot\\\",\\n   692|        \\\"github-models\\\": \\\"copilot\\\", \\\"github-model\\\": \\\"copilot\\\",\\n   693|        \\\"github-copilot-acp\\\": \\\"copilot-acp\\\", \\\"copilot-acp-agent\\\": \\\"copilot-acp\\\",\\n   694|        \\\"aigateway\\\": \\\"ai-gateway\\\", \\\"vercel\\\": \\\"ai-gateway\\\", \\\"vercel-ai-gateway\\\": \\\"ai-gateway\\\",\\n   695|        \\\"opencode\\\": \\\"opencode-zen\\\", \\\"zen\\\": \\\"opencode-zen\\\",\\n   696|        \\\"hf\\\": \\\"huggingface\\\", \\\"hugging-face\\\": \\\"huggingface\\\", \\\"huggingface-hub\\\": \\\"huggingface\\\",\\n   697|        \\\"go\\\": \\\"opencode-go\\\", \\\"opencode-go-sub\\\": \\\"opencode-go\\\",\\n   698|        \\\"kilo\\\": \\\"kilocode\\\", \\\"kilo-code\\\": \\\"kilocode\\\", \\\"kilo-gateway\\\": \\\"kilocode\\\",\\n   699|    }\\n   700|    normalized = _PROVIDER_ALIASES.get(normalized, normalized)\\n   701|\\n   702|    if normalized == \\\"openrouter\\\":\\n   703|        return \\\"openrouter\\\"\\n   704|    if normalized == \\\"custom\\\":\\n   705|        return \\\"custom\\\"\\n   706|    if normalized in PROVIDER_REGISTRY:\\n   707|        return normalized\\n   708|    if normalized != \\\"auto\\\":\\n   709|        raise AuthError(\\n   710|            f\\\"Unknown provider '{normalized}'.\\\",\\n   711|            code=\\\"invalid_provider\\\",\\n   712|        )\\n   713|\\n   714|    # Explicit one-off CLI creds always mean openrouter/custom\\n   715|    if explicit_api_key or explicit_base_url:\\n   716|        return \\\"openrouter\\\"\\n   717|\\n   718|    # Check auth store for an active OAuth provider\\n   719|    try:\\n   720|        auth_store=_load_...re()\\n   721|        active = auth_store.get(\\\"active_provider\\\")\\n   722|        if active and active in PROVIDER_REGISTRY:\\n   723|            status = get_auth_status(active)\\n   724|            if status.get(\\\"logged_in\\\"):\\n   725|                return active\\n   726|    except Exception as e:\\n   727|        logger.debug(\\\"Could not detect active auth provider: %s\\\", e)\\n   728|\\n   729|    if has_usable_secret(os.getenv(\\\"OPENAI_API_KEY\\\")) or has_usable_secret(os.getenv(\\\"OPENROUTER_API_KEY\\\")):\\n   730|        return \\\"openrouter\\\"\\n   731|\\n   732|    # Auto-detect API-key providers by checking their env vars\\n   733|    for pid, pconfig in PROVIDER_REGISTRY.items():\\n   734|        if pconfig.auth_type != \\\"api_key\\\":\\n   735|            continue\\n   736|        # GitHub tokens are commonly present for repo/tool access but should not\\n   737|        # hijack inference auto-selection unless the user explicitly chooses\\n   738|        # Copilot/GitHub Models as the provider.\\n   739|        if pid == \\\"copilot\\\":\\n   740|            continue\\n   741|        for env_var in pconfig.api_key_env_vars:\\n   742|            if has_usable_secret(os.getenv(env_var, \\\"\\\")):\\n   743|                return pid\\n   744|\\n   745|    return \\\"openrouter\\\"\\n   746|\\n   747|\", \"total_lines\": 2356, \"file_size\": 88244, \"truncated\": true, \"hint\": \"Use offset=747 to continue reading (showing 667-746 of 2356 lines)\", \"is_binary\": false, \"is_image\": false, \"_budget_warning\": \"[BUDGET: Iteration 25/30. 5 iterations left. Start consolidating your work.]\"}",
      "tool_call_id": "toolu_01AgDERfWCbkDPWnpehcpswx"
    },
    {
      "role": "assistant",
      "content": "Now I have the complete picture. Let me also quickly check the config.yaml to understand how a local-llama.cpp provider would be configured:",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "toolu_015gg6AgeMvx3w8rdCr6f4be",
          "call_id": "toolu_015gg6AgeMvx3w8rdCr6f4be",
          "response_item_id": "fc_toolu_015gg6AgeMvx3w8rdCr6f4be",
          "type": "function",
          "function": {
            "name": "terminal",
            "arguments": "{\"command\": \"find /root/wizards/ezra -name \\\"config.yaml\\\" -path \\\"*/hermes*\\\" 2>/dev/null | head -5 && cat ~/.hermes/config.yaml 2>/dev/null | head -40\"}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"output\": \"model:\\n  default: anthropic/claude-opus-4.6\\n  provider: auto\\n  base_url: https://openrouter.ai/api/v1\\ntoolsets:\\n- all\\nmax_turns: 111\\nterminal:\\n  backend: local\\n  cwd: .\\n  timeout: 180\\n  docker_image: nikolaik/python-nodejs:python3.11-nodejs20\\n  singularity_image: docker://nikolaik/python-nodejs:python3.11-nodejs20\\n  modal_image: nikolaik/python-nodejs:python3.11-nodejs20\\n  daytona_image: nikolaik/python-nodejs:python3.11-nodejs20\\n  container_cpu: 1\\n  container_memory: 5120\\n  container_disk: 51200\\n  container_persistent: true\\n  lifetime_seconds: 300\\nbrowser:\\n  inactivity_timeout: 120\\ncompression:\\n  enabled: true\\n  threshold: 0.77\\n  summary_model: google/gemini-3-flash-preview\\ndisplay:\\n  compact: false\\n  personality: kawaii\\n  tool_progress: all\\ntts:\\n  provider: edge\\n  edge:\\n    voice: en-US-AriaNeural\\n  elevenlabs:\\n    voice_id: pNInz6obpgDQGcFmaJgB\\n    model_id: eleven_multilingual_v2\\n  openai:\\n    model: gpt-4o-mini-tts\\n    voice: alloy\", \"exit_code\": 0, \"error\": null, \"_budget_warning\": \"[BUDGET: Iteration 26/30. 4 iterations left. Start consolidating your work.]\"}",
      "tool_call_id": "toolu_015gg6AgeMvx3w8rdCr6f4be"
    },
    {
      "role": "assistant",
      "content": "I now have all the information needed. Let me compile my findings.\n\nHere is my complete analysis of how local llama.cpp tool calling works (or fails to work) in the Hermes Agent codebase:\n\nSUMMARY OF FINDINGS\n\n1. HOW DOES PROVIDER \"local-llama.cpp\" RESOLVE?\n\n\"local-llama.cpp\" is NOT in the PROVIDER_REGISTRY (auth.py line 98-223) and NOT in the _PROVIDER_ALIASES (auth.py line 686-698). When resolve_provider() is called with \"local-llama.cpp\", it:\n- Normalizes to \"local-llama.cpp\"\n- Checks aliases - no match\n- Checks if \"openrouter\" or \"custom\" - no\n- Checks if in PROVIDER_REGISTRY - no\n- Since normalized != \"auto\", it RAISES AuthError(\"Unknown provider 'local-llama.cpp'\")\n\nSo \"local-llama.cpp\" as a provider value would crash at startup UNLESS it's configured as a named custom provider in config.yaml under custom_providers. In runtime_provider.py, _get_named_custom_provider() (line 131) checks custom_providers list for matching names. If config.yaml has:\n\n```yaml\ncustom_providers:\n  - name: local-llama.cpp\n    base_url: http://localhost:8081/v1\n```\n\nThen it resolves via _resolve_named_custom_runtime() and gets api_mode \"chat_completions\" (the default).\n\n2. HOW ARE TOOLS FORMATTED FOR THE API?\n\nTools are formatted in standard OpenAI function-calling JSON format. model_tools.py get_tool_definitions() returns \"OpenAI-format tool definitions\" (line 250) - each tool is a dict with:\n```json\n{\"type\": \"function\", \"function\": {\"name\": \"...\", \"description\": \"...\", \"parameters\": {...}}}\n```\n\nIn run_agent.py line 4709, these are passed directly to the API:\n```python\napi_kwargs = {\n    \"model\": self.model,\n    \"messages\": sanitized_messages,\n    \"tools\": self.tools if self.tools else None,\n    ...\n}\n```\n\nThen at line 3775: `client.chat.completions.create(**api_kwargs)` - the standard OpenAI SDK call with tools as a parameter.\n\n3. IS THERE HERMES-FORMAT TOOL CALL PARSING?\n\nYES, but only in the environments/tool_call_parsers/ directory (for Atropos RL training). The HermesToolCallParser (environments/tool_call_parsers/hermes_parser.py) parses `<tool_call>{\"name\": \"func\", \"arguments\": {...}}</tool_call>` XML-tagged JSON.\n\nCRITICALLY: This parser is NEVER imported or used in run_agent.py (the main agent). The main conversation loop at line 7351-7352 does:\n```python\nelse:  # chat_completions mode\n    assistant_message = response.choices[0].message\n```\n\nThen checks `assistant_message.tool_calls` at line 7486. If the API response doesn't include structured tool_calls (which is what happens with Hermes models outputting text), the tool_calls attribute is None, and the agent treats the response as a plain text response with no tools.\n\n4. WHAT DOES THE SYSTEM EXPECT FROM LOCAL LLAMA-SERVER?\n\nThe system expects llama-server to return tool calls via the OpenAI-compatible API's structured tool_calls field in the response JSON, like:\n```json\n{\"choices\": [{\"message\": {\"tool_calls\": [{\"id\": \"...\", \"function\": {\"name\": \"...\", \"arguments\": \"...\"}}]}}]}\n```\n\nTHE ROOT CAUSE OF THE PROBLEM:\n\nThe llama-server with Hermes-4-14B is likely NOT converting the model's `<tool_call>` text output into the structured `tool_calls` field in the OpenAI API response. The model outputs Hermes-format tool calls as text content (e.g., `<tool_call>{\"name\": \"read_file\", \"arguments\": {\"path\": \"...\"}}</tool_call>`), but llama-server needs to be configured to parse these into proper OpenAI tool call objects.\n\nllama-server needs to be started with the appropriate chat template / tool call handling. The `detect_local_server_type()` function in model_metadata.py (line 239) can detect \"llamacpp\" servers, but this is only used for context length detection, not for enabling text-based tool call parsing.\n\nFIX OPTIONS:\n1. Start llama-server with `--jinja` flag and ensure the model's chat template includes proper tool call formatting that converts `<tool_call>` tags into OpenAI-format tool_calls in the API response\n2. OR add a post-processing step in run_agent.py that uses the existing HermesToolCallParser to parse `<tool_call>` tags from the assistant message content when tool_calls is None/empty (around line 7352)\n\nNO FILES WERE MODIFIED. This was a read-only investigation.",
      "reasoning": null,
      "finish_reason": "stop"
    }
  ]
}