feat: harden tool-call benchmark coverage and reporting for #796

Refs #796

benchmarks/gemma4-tool-calling-2026-04-22.md

@@ -0,0 +1,139 @@
+# Tool-Calling Benchmark Report
+
+Generated: 2026-04-22 15:46 UTC
+Executed: 3 calls from a 100-call suite across 7 categories
+Models tested: nous:gia-3/gemma-4-31b, gemini:gemma-4-26b-it, nous:mimo-v2-pro
+
+## Requested category mix
+
+| Category | Target calls |
+|----------|--------------|
+| file | 20 |
+| terminal | 20 |
+| web | 15 |
+| code | 15 |
+| browser | 10 |
+| delegate | 10 |
+| mcp | 10 |
+
+## Summary
+
+| Metric | nous:gia-3/gemma-4-31b | gemini:gemma-4-26b-it | nous:mimo-v2-pro |
+|--------|---------|---------|---------|
+| Schema parse success | 0/1 (0%) | 0/1 (0%) | 0/1 (0%) | 
+| Tool execution success | 0/1 (0%) | 0/1 (0%) | 0/1 (0%) | 
+| Parallel tool success | 0/1 (0%) | 0/1 (0%) | 0/1 (0%) | 
+| Avg latency (s) | 0.00 | 0.00 | 0.00 | 
+| Avg tokens per call | 0.0 | 0.0 | 0.0 | 
+| Avg token cost per call (USD) | n/a | n/a | n/a | 
+| Skipped / unavailable | 0/1 | 0/1 | 0/1 | 
+
+## Per-category breakdown
+
+### File
+
+| Metric | nous:gia-3/gemma-4-31b | gemini:gemma-4-26b-it | nous:mimo-v2-pro |
+|--------|---------|---------|---------|
+| Schema OK | 0/1 (0%) | 0/1 (0%) | 0/1 (0%) | 
+| Exec OK | 0/1 (0%) | 0/1 (0%) | 0/1 (0%) | 
+| Parallel OK | 0/1 (0%) | 0/1 (0%) | 0/1 (0%) | 
+| Correct tool | 0/1 (0%) | 0/1 (0%) | 0/1 (0%) | 
+| Avg tokens | 0.0 | 0.0 | 0.0 | 
+| Skipped | 0/1 | 0/1 | 0/1 | 
+
+## Failure analysis
+
+### nous:gia-3/gemma-4-31b — 1 failures
+
+| Test | Category | Expected | Got | Error |
+|------|----------|----------|-----|-------|
+| file-01 | file | read_file | none | SyntaxError: unexpected character after line continuation ch |
+
+### gemini:gemma-4-26b-it — 1 failures
+
+| Test | Category | Expected | Got | Error |
+|------|----------|----------|-----|-------|
+| file-01 | file | read_file | none | SyntaxError: unexpected character after line continuation ch |
+
+### nous:mimo-v2-pro — 1 failures
+
+| Test | Category | Expected | Got | Error |
+|------|----------|----------|-----|-------|
+| file-01 | file | read_file | none | SyntaxError: unexpected character after line continuation ch |
+
+## Skipped / unavailable cases
+
+No cases were skipped.
+
+## Raw results
+
+```json
+[
+  {
+    "test_id": "file-01",
+    "category": "file",
+    "model": "nous:gia-3/gemma-4-31b",
+    "prompt": "Read the file /tmp/test_bench.txt and show me its contents.",
+    "expected_tool": "read_file",
+    "success": false,
+    "tool_called": null,
+    "schema_ok": false,
+    "tool_args_valid": false,
+    "execution_ok": false,
+    "tool_count": 0,
+    "parallel_ok": false,
+    "latency_s": 0,
+    "total_tokens": 0,
+    "estimated_cost_usd": null,
+    "cost_status": "unknown",
+    "skipped": false,
+    "skip_reason": "",
+    "error": "SyntaxError: unexpected character after line continuation character (auxiliary_client.py, line 1)",
+    "raw_response": ""
+  },
+  {
+    "test_id": "file-01",
+    "category": "file",
+    "model": "gemini:gemma-4-26b-it",
+    "prompt": "Read the file /tmp/test_bench.txt and show me its contents.",
+    "expected_tool": "read_file",
+    "success": false,
+    "tool_called": null,
+    "schema_ok": false,
+    "tool_args_valid": false,
+    "execution_ok": false,
+    "tool_count": 0,
+    "parallel_ok": false,
+    "latency_s": 0,
+    "total_tokens": 0,
+    "estimated_cost_usd": null,
+    "cost_status": "unknown",
+    "skipped": false,
+    "skip_reason": "",
+    "error": "SyntaxError: unexpected character after line continuation character (auxiliary_client.py, line 1)",
+    "raw_response": ""
+  },
+  {
+    "test_id": "file-01",
+    "category": "file",
+    "model": "nous:mimo-v2-pro",
+    "prompt": "Read the file /tmp/test_bench.txt and show me its contents.",
+    "expected_tool": "read_file",
+    "success": false,
+    "tool_called": null,
+    "schema_ok": false,
+    "tool_args_valid": false,
+    "execution_ok": false,
+    "tool_count": 0,
+    "parallel_ok": false,
+    "latency_s": 0,
+    "total_tokens": 0,
+    "estimated_cost_usd": null,
+    "cost_status": "unknown",
+    "skipped": false,
+    "skip_reason": "",
+    "error": "SyntaxError: unexpected character after line continuation character (auxiliary_client.py, line 1)",
+    "raw_response": ""
+  }
+]
+```

benchmarks/tool_call_benchmark.py

@@ -8,10 +8,11 @@ success rates, latency, and token costs.
 Usage:
     python3 benchmarks/tool_call_benchmark.py                  # full 100-call suite
     python3 benchmarks/tool_call_benchmark.py --limit 10       # quick smoke test
-    python3 benchmarks/tool_call_benchmark.py --models nous     # single model
-    python3 benchmarks/tool_call_benchmark.py --category file   # single category
+    python3 benchmarks/tool_call_benchmark.py --category web   # single category
+    python3 benchmarks/tool_call_benchmark.py --compare        # issue #796 default model comparison
 
-Requires: hermes-agent venv activated, OPENROUTER_API_KEY or equivalent.
+Requires: hermes-agent venv activated, provider credentials for the selected models,
+and any optional browser/MCP/web backends you want to include in the run.
 """
 
 import argparse
@@ -25,10 +26,12 @@ from datetime import datetime, timezone
 from pathlib import Path
 from typing import Optional
 
-# Ensure hermes-agent root is importable
+# Ensure hermes-agent root is importable before local package imports.
 REPO_ROOT = Path(__file__).resolve().parent.parent
 sys.path.insert(0, str(REPO_ROOT))
 
+from agent.usage_pricing import CanonicalUsage, estimate_usage_cost
+
 # ---------------------------------------------------------------------------
 # Test Definitions
 # ---------------------------------------------------------------------------
@@ -39,9 +42,11 @@ class ToolCall:
     id: str
     category: str
     prompt: str
-    expected_tool: str              # tool name we expect the model to call
-    expected_params_check: str = "" # substring expected in JSON args
-    timeout: int = 30               # max seconds per call
+    expected_tool: str               # exact tool name we expect the model to call
+    expected_params_check: str = ""  # substring expected in JSON args
+    expected_tool_prefix: str = ""   # prefix match for dynamic surfaces like mcp_*
+    expects_parallel: bool = False    # whether this prompt should elicit multiple tool calls
+    timeout: int = 30                 # max seconds per call
     notes: str = ""
 
 
@@ -185,85 +190,107 @@ SUITE: list[ToolCall] = [
     ToolCall("deleg-10", "delegate", "Delegate: create a temp file /tmp/bench_deleg.txt with 'done'.",
              "delegate_task", "write"),
 
-    # ── Todo / Memory (10 — replacing web/browser/MCP which need external services) ──
-    ToolCall("todo-01", "todo", "Add a todo item: 'Run benchmark suite'",
-             "todo", "benchmark"),
-    ToolCall("todo-02", "todo", "Show me the current todo list.",
-             "todo", ""),
-    ToolCall("todo-03", "todo", "Mark the first todo item as completed.",
-             "todo", "completed"),
-    ToolCall("todo-04", "todo", "Add a todo: 'Review benchmark results' with status pending.",
-             "todo", "Review"),
-    ToolCall("todo-05", "todo", "Clear all completed todos.",
-             "todo", "clear"),
-    ToolCall("todo-06", "memory", "Save this to memory: 'benchmark ran on {date}'".format(
-              date=datetime.now().strftime("%Y-%m-%d")),
-             "memory", "benchmark"),
-    ToolCall("todo-07", "memory", "Search memory for 'benchmark'.",
-             "memory", "benchmark"),
-    ToolCall("todo-08", "memory", "Add a memory note: 'test models are gemma-4 and mimo-v2-pro'.",
-             "memory", "gemma"),
-    ToolCall("todo-09", "todo", "Add three todo items: 'analyze', 'report', 'cleanup'.",
-             "todo", "analyze"),
-    ToolCall("todo-10", "memory", "Search memory for any notes about models.",
-             "memory", "model"),
+    # ── Web Search & Extraction (15) ─────────────────────────────────────
+    ToolCall("web-01", "web", "Search the web for Python dataclasses documentation.",
+             "web_search", "dataclasses"),
+    ToolCall("web-02", "web", "Search the web for Hermès agent tool calling benchmarks.",
+             "web_search", "benchmark"),
+    ToolCall("web-03", "web", "Search the web for Gemini Gemma 4 model pricing.",
+             "web_search", "Gemma 4"),
+    ToolCall("web-04", "web", "Search the web for Xiaomi MiMo v2 Pro documentation.",
+             "web_search", "MiMo"),
+    ToolCall("web-05", "web", "Search the web for Python subprocess documentation.",
+             "web_search", "subprocess"),
+    ToolCall("web-06", "web", "Search the web for ripgrep usage examples.",
+             "web_search", "ripgrep"),
+    ToolCall("web-07", "web", "Search the web for pytest fixtures guide.",
+             "web_search", "pytest fixtures"),
+    ToolCall("web-08", "web", "Search the web for OpenAI function calling docs.",
+             "web_search", "function calling"),
+    ToolCall("web-09", "web", "Search the web for browser automation best practices.",
+             "web_search", "browser automation"),
+    ToolCall("web-10", "web", "Search the web for Model Context Protocol overview.",
+             "web_search", "Model Context Protocol"),
+    ToolCall("web-11", "web", "Extract the main text from https://example.com.",
+             "web_extract", "example.com"),
+    ToolCall("web-12", "web", "Extract the page content from https://example.org.",
+             "web_extract", "example.org"),
+    ToolCall("web-13", "web", "Extract the title and body text from https://www.iana.org/domains/reserved.",
+             "web_extract", "iana.org"),
+    ToolCall("web-14", "web", "Extract content from https://httpbin.org/html.",
+             "web_extract", "httpbin.org"),
+    ToolCall("web-15", "web", "Extract the main content from https://www.python.org/.",
+             "web_extract", "python.org"),
 
-    # ── Skills (10 — replacing MCP tools which need servers) ─────────────
-    ToolCall("skill-01", "skills", "List all available skills.",
-             "skills_list", ""),
-    ToolCall("skill-02", "skills", "View the skill called 'test-driven-development'.",
-             "skill_view", "test-driven"),
-    ToolCall("skill-03", "skills", "Search for skills related to 'git'.",
-             "skills_list", "git"),
-    ToolCall("skill-04", "skills", "View the 'code-review' skill.",
-             "skill_view", "code-review"),
-    ToolCall("skill-05", "skills", "List all skills in the 'devops' category.",
-             "skills_list", "devops"),
-    ToolCall("skill-06", "skills", "View the 'systematic-debugging' skill.",
-             "skill_view", "systematic-debugging"),
-    ToolCall("skill-07", "skills", "Search for skills about 'testing'.",
-             "skills_list", "testing"),
-    ToolCall("skill-08", "skills", "View the 'writing-plans' skill.",
-             "skill_view", "writing-plans"),
-    ToolCall("skill-09", "skills", "List skills in 'software-development' category.",
-             "skills_list", "software-development"),
-    ToolCall("skill-10", "skills", "View the 'pr-review-discipline' skill.",
-             "skill_view", "pr-review"),
+    # ── Browser Automation (10) ───────────────────────────────────────────
+    ToolCall("browser-01", "browser", "Open https://example.com in the browser.",
+             "browser_navigate", "example.com"),
+    ToolCall("browser-02", "browser", "Open https://www.python.org in the browser.",
+             "browser_navigate", "python.org"),
+    ToolCall("browser-03", "browser", "Open https://www.wikipedia.org in the browser.",
+             "browser_navigate", "wikipedia.org"),
+    ToolCall("browser-04", "browser", "Navigate the browser to https://example.org.",
+             "browser_navigate", "example.org"),
+    ToolCall("browser-05", "browser", "Go to https://httpbin.org/forms/post in the browser.",
+             "browser_navigate", "httpbin.org/forms/post"),
+    ToolCall("browser-06", "browser", "Open https://www.iana.org/domains/reserved in the browser.",
+             "browser_navigate", "iana.org/domains/reserved"),
+    ToolCall("browser-07", "browser", "Navigate to https://example.net in the browser.",
+             "browser_navigate", "example.net"),
+    ToolCall("browser-08", "browser", "Open https://developer.mozilla.org in the browser.",
+             "browser_navigate", "developer.mozilla.org"),
+    ToolCall("browser-09", "browser", "Navigate the browser to https://www.rfc-editor.org.",
+             "browser_navigate", "rfc-editor.org"),
+    ToolCall("browser-10", "browser", "Open https://www.gnu.org in the browser.",
+             "browser_navigate", "gnu.org"),
 
-    # ── Additional tests to reach 100 ────────────────────────────────────
-    ToolCall("file-21", "file", "Write a Python snippet to /tmp/bench_sort.py that sorts [3,1,2].",
-             "write_file", "bench_sort"),
-    ToolCall("file-22", "file", "Read /tmp/bench_sort.py back and confirm it exists.",
-             "read_file", "bench_sort"),
-    ToolCall("file-23", "file", "Search for 'class' in all .py files in the benchmarks directory.",
-             "search_files", "class"),
-    ToolCall("term-21", "terminal", "Run `cat /etc/os-release 2>/dev/null || sw_vers 2>/dev/null` for OS info.",
-             "terminal", "os"),
-    ToolCall("term-22", "terminal", "Run `nproc 2>/dev/null || sysctl -n hw.ncpu 2>/dev/null` for CPU count.",
-             "terminal", "cpu"),
-    ToolCall("code-16", "code", "Execute Python to flatten a nested list [[1,2],[3,4],[5]].",
-             "execute_code", "flatten"),
-    ToolCall("code-17", "code", "Run Python to check if a number 17 is prime.",
-             "execute_code", "prime"),
-    ToolCall("deleg-11", "delegate", "Delegate: what is the current working directory?",
-             "delegate_task", "cwd"),
-    ToolCall("todo-11", "todo", "Add a todo: 'Finalize benchmark report' status pending.",
-             "todo", "Finalize"),
-    ToolCall("todo-12", "memory", "Store fact: 'benchmark categories: file, terminal, code, delegate, todo, memory, skills'.",
-             "memory", "categories"),
-    ToolCall("skill-11", "skills", "Search for skills about 'deployment'.",
-             "skills_list", "deployment"),
-    ToolCall("skill-12", "skills", "View the 'gitea-burn-cycle' skill.",
-             "skill_view", "gitea-burn-cycle"),
-    ToolCall("skill-13", "skills", "List all available skill categories.",
-             "skills_list", ""),
-    ToolCall("skill-14", "skills", "Search for skills related to 'memory'.",
-             "skills_list", "memory"),
-    ToolCall("skill-15", "skills", "View the 'mimo-swarm' skill.",
-             "skill_view", "mimo-swarm"),
+    # ── MCP Tools (10) ────────────────────────────────────────────────────
+    ToolCall("mcp-01", "mcp", "Use an available MCP tool to list configured MCP resources or prompts.",
+             "", "", expected_tool_prefix="mcp_"),
+    ToolCall("mcp-02", "mcp", "Use an MCP tool to inspect available resources on a configured server.",
+             "", "", expected_tool_prefix="mcp_"),
+    ToolCall("mcp-03", "mcp", "Use an MCP tool to read a resource from any configured MCP server.",
+             "", "", expected_tool_prefix="mcp_"),
+    ToolCall("mcp-04", "mcp", "Use an MCP tool to list prompts from any configured MCP server.",
+             "", "", expected_tool_prefix="mcp_"),
+    ToolCall("mcp-05", "mcp", "Use an available MCP tool and report what it returns.",
+             "", "", expected_tool_prefix="mcp_"),
+    ToolCall("mcp-06", "mcp", "Call any safe MCP tool that is currently available and summarize the response.",
+             "", "", expected_tool_prefix="mcp_"),
+    ToolCall("mcp-07", "mcp", "Use one configured MCP tool to enumerate data or capabilities.",
+             "", "", expected_tool_prefix="mcp_"),
+    ToolCall("mcp-08", "mcp", "Use an MCP tool to fetch a small piece of data from a connected server.",
+             "", "", expected_tool_prefix="mcp_"),
+    ToolCall("mcp-09", "mcp", "Invoke an available MCP tool and show the structured result.",
+             "", "", expected_tool_prefix="mcp_"),
+    ToolCall("mcp-10", "mcp", "Use a currently available MCP tool rather than a built-in Hermes tool.",
+             "", "", expected_tool_prefix="mcp_"),
 ]
 # fmt: on
 
+DEFAULT_COMPARE_MODELS = [
+    "nous:gia-3/gemma-4-31b",
+    "gemini:gemma-4-26b-it",
+    "nous:mimo-v2-pro",
+]
+
+ISSUE_796_CATEGORY_COUNTS = {
+    "file": 20,
+    "terminal": 20,
+    "web": 15,
+    "code": 15,
+    "browser": 10,
+    "delegate": 10,
+    "mcp": 10,
+}
+
+
+def suite_category_counts() -> dict[str, int]:
+    counts: dict[str, int] = {}
+    for tc in SUITE:
+        counts[tc.category] = counts.get(tc.category, 0) + 1
+    return counts
+
 
 # ---------------------------------------------------------------------------
 # Runner
@@ -278,9 +305,17 @@ class CallResult:
     expected_tool: str
     success: bool
     tool_called: Optional[str] = None
+    schema_ok: bool = False
     tool_args_valid: bool = False
     execution_ok: bool = False
+    tool_count: int = 0
+    parallel_ok: bool = False
     latency_s: float = 0.0
+    total_tokens: int = 0
+    estimated_cost_usd: Optional[float] = None
+    cost_status: str = "unknown"
+    skipped: bool = False
+    skip_reason: str = ""
     error: str = ""
     raw_response: str = ""
 
@@ -291,7 +326,12 @@ class ModelStats:
     total: int = 0
     schema_ok: int = 0        # model produced valid tool call JSON
     exec_ok: int = 0          # tool actually ran without error
+    parallel_ok: int = 0      # calls with 2+ tool calls that executed successfully
+    skipped: int = 0
     latency_sum: float = 0.0
+    total_tokens: int = 0
+    total_cost_usd: float = 0.0
+    known_cost_calls: int = 0
     failures: list = field(default_factory=list)
 
     @property
@@ -306,6 +346,10 @@ class ModelStats:
     def avg_latency(self) -> float:
         return (self.latency_sum / self.total) if self.total else 0
 
+    @property
+    def avg_cost_usd(self) -> Optional[float]:
+        return (self.total_cost_usd / self.known_cost_calls) if self.known_cost_calls else None
+
 
 def setup_test_files():
     """Create prerequisite files for the benchmark."""
@@ -318,20 +362,38 @@ def setup_test_files():
     )
 
 
+def _matches_expected_tool(test_case: ToolCall, tool_name: str) -> bool:
+    if test_case.expected_tool and tool_name == test_case.expected_tool:
+        return True
+    if test_case.expected_tool_prefix and tool_name.startswith(test_case.expected_tool_prefix):
+        return True
+    return False
+
+
+def _resolve_unavailable_reason(test_case: ToolCall, valid_tool_names: set[str]) -> str:
+    if test_case.expected_tool and test_case.expected_tool not in valid_tool_names:
+        return f"required tool unavailable: {test_case.expected_tool}"
+    if test_case.expected_tool_prefix and not any(
+        name.startswith(test_case.expected_tool_prefix) for name in valid_tool_names
+    ):
+        return f"required tool prefix unavailable: {test_case.expected_tool_prefix}"
+    return ""
+
+
 def run_single_test(tc: ToolCall, model_spec: str, provider: str) -> CallResult:
     """Run a single tool-calling test through the agent."""
-    from run_agent import AIAgent
-
     result = CallResult(
         test_id=tc.id,
         category=tc.category,
         model=model_spec,
         prompt=tc.prompt,
-        expected_tool=tc.expected_tool,
+        expected_tool=tc.expected_tool or tc.expected_tool_prefix,
         success=False,
     )
 
     try:
+        from run_agent import AIAgent
+
         agent = AIAgent(
             model=model_spec,
             provider=provider,
@@ -342,6 +404,14 @@ def run_single_test(tc: ToolCall, model_spec: str, provider: str) -> CallResult:
             persist_session=False,
         )
 
+        valid_tool_names = set(getattr(agent, "valid_tool_names", set()))
+        unavailable_reason = _resolve_unavailable_reason(tc, valid_tool_names)
+        if unavailable_reason:
+            result.skipped = True
+            result.skip_reason = unavailable_reason
+            result.error = unavailable_reason
+            return result
+
         t0 = time.time()
         conv = agent.run_conversation(
             user_message=tc.prompt,
@@ -352,52 +422,75 @@ def run_single_test(tc: ToolCall, model_spec: str, provider: str) -> CallResult:
         )
         result.latency_s = round(time.time() - t0, 2)
 
+        usage = CanonicalUsage(
+            input_tokens=getattr(agent, "session_input_tokens", 0) or 0,
+            output_tokens=getattr(agent, "session_output_tokens", 0) or 0,
+            cache_read_tokens=getattr(agent, "session_cache_read_tokens", 0) or 0,
+            cache_write_tokens=getattr(agent, "session_cache_write_tokens", 0) or 0,
+            request_count=max(getattr(agent, "session_api_calls", 0) or 0, 1),
+        )
+        result.total_tokens = usage.total_tokens
+        billed_model = model_spec.split(":", 1)[1] if ":" in model_spec else model_spec
+        cost = estimate_usage_cost(
+            billed_model,
+            usage,
+            provider=provider,
+            base_url=getattr(agent, "base_url", None),
+            api_key=getattr(agent, "api_key", None),
+        )
+        result.cost_status = cost.status
+        result.estimated_cost_usd = float(cost.amount_usd) if cost.amount_usd is not None else None
+
         messages = conv.get("messages", [])
 
-        # Find the first assistant message with tool_calls
-        tool_called = None
-        tool_args_str = ""
+        tool_calls = []
         for msg in messages:
             if msg.get("role") == "assistant" and msg.get("tool_calls"):
-                for tc_item in msg["tool_calls"]:
-                    fn = tc_item.get("function", {})
-                    tool_called = fn.get("name", "")
-                    tool_args_str = fn.get("arguments", "{}")
-                    break
+                tool_calls = list(msg["tool_calls"])
                 break
 
-        if tool_called:
-            result.tool_called = tool_called
-            result.schema_ok = True
+        if tool_calls:
+            result.tool_count = len(tool_calls)
+            parsed_args_ok = True
+            matched_name = None
+            matched_args = "{}"
 
-            # Check if the right tool was called
-            if tool_called == tc.expected_tool:
-                result.success = True
+            for tc_item in tool_calls:
+                fn = tc_item.get("function", {})
+                tool_name = fn.get("name", "")
+                tool_args = fn.get("arguments", "{}")
+                try:
+                    json.loads(tool_args or "{}")
+                except Exception:
+                    parsed_args_ok = False
+                if matched_name is None and _matches_expected_tool(tc, tool_name):
+                    matched_name = tool_name
+                    matched_args = tool_args
 
-            # Check if args contain expected substring
-            if tc.expected_params_check:
-                result.tool_args_valid = tc.expected_params_check in tool_args_str
-            else:
-                result.tool_args_valid = True
+            result.schema_ok = parsed_args_ok
+            result.tool_called = matched_name or tool_calls[0].get("function", {}).get("name", "")
+
+            if matched_name:
+                result.tool_args_valid = (
+                    tc.expected_params_check in matched_args if tc.expected_params_check else True
+                )
+                result.success = result.schema_ok and result.tool_args_valid
 
-            # Check if tool executed (look for tool role message)
             for msg in messages:
                 if msg.get("role") == "tool":
                     content = msg.get("content", "")
-                    if content and "error" not in content.lower()[:50]:
+                    if content:
                         result.execution_ok = True
                         break
-                    elif content:
-                        result.execution_ok = True  # got a response, even if error
-                        break
+
+            result.parallel_ok = result.tool_count > 1 and result.execution_ok
         else:
-            # No tool call produced — still check if model responded
             final = conv.get("final_response", "")
             result.raw_response = final[:200] if final else ""
 
     except Exception as e:
         result.error = f"{type(e).__name__}: {str(e)[:200]}"
-        result.latency_s = round(time.time() - t0, 2) if 't0' in dir() else 0
+        result.latency_s = round(time.time() - t0, 2) if 't0' in locals() else 0
 
     return result
 
@@ -406,100 +499,134 @@ def generate_report(results: list[CallResult], models: list[str], output_path: P
     """Generate markdown benchmark report."""
     now = datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M UTC")
 
-    # Aggregate per model
-    stats: dict[str, ModelStats] = {}
-    for m in models:
-        stats[m] = ModelStats(model=m)
-
+    stats: dict[str, ModelStats] = {m: ModelStats(model=m) for m in models}
     by_category: dict[str, dict[str, list[CallResult]]] = {}
 
     for r in results:
         s = stats[r.model]
         s.total += 1
-        s.schema_ok += int(r.schema_ok)
-        s.exec_ok += int(r.execution_ok)
         s.latency_sum += r.latency_s
-        if not r.success:
-            s.failures.append(r)
+        s.total_tokens += r.total_tokens
+        if r.estimated_cost_usd is not None:
+            s.total_cost_usd += r.estimated_cost_usd
+            s.known_cost_calls += 1
+        if r.skipped:
+            s.skipped += 1
+        else:
+            s.schema_ok += int(r.schema_ok)
+            s.exec_ok += int(r.execution_ok)
+            s.parallel_ok += int(r.parallel_ok)
+            if not r.success:
+                s.failures.append(r)
 
         by_category.setdefault(r.category, {}).setdefault(r.model, []).append(r)
 
+    def _score_row(label: str, fn) -> str:
+        row = f"| {label} | "
+        for m in models:
+            s = stats[m]
+            attempted = s.total - s.skipped
+            if attempted <= 0:
+                row += "n/a | "
+                continue
+            ok = fn(s)
+            pct = ok / attempted * 100
+            row += f"{ok}/{attempted} ({pct:.0f}%) | "
+        return row
+
     lines = [
-        f"# Tool-Calling Benchmark Report",
-        f"",
+        "# Tool-Calling Benchmark Report",
+        "",
         f"Generated: {now}",
-        f"Suite: {len(SUITE)} calls across {len(set(tc.category for tc in SUITE))} categories",
+        f"Executed: {len(results)} calls from a {len(SUITE)}-call suite across {len(ISSUE_796_CATEGORY_COUNTS)} categories",
         f"Models tested: {', '.join(models)}",
-        f"",
-        f"## Summary",
-        f"",
+        "",
+        "## Requested category mix",
+        "",
+        "| Category | Target calls |",
+        "|----------|--------------|",
+    ]
+    for category, count in ISSUE_796_CATEGORY_COUNTS.items():
+        lines.append(f"| {category} | {count} |")
+
+    lines.extend([
+        "",
+        "## Summary",
+        "",
         f"| Metric | {' | '.join(models)} |",
         f"|--------|{'|'.join('---------' for _ in models)}|",
-    ]
+        _score_row("Schema parse success", lambda s: s.schema_ok),
+        _score_row("Tool execution success", lambda s: s.exec_ok),
+        _score_row("Parallel tool success", lambda s: s.parallel_ok),
+    ])
 
-    # Schema parse success
-    row = "| Schema parse success | "
-    for m in models:
-        s = stats[m]
-        row += f"{s.schema_ok}/{s.total} ({s.schema_pct:.0f}%) | "
-    lines.append(row)
-
-    # Tool execution success
-    row = "| Tool execution success | "
-    for m in models:
-        s = stats[m]
-        row += f"{s.exec_ok}/{s.total} ({s.exec_pct:.0f}%) | "
-    lines.append(row)
-
-    # Correct tool selected
-    row = "| Correct tool selected | "
-    for m in models:
-        s = stats[m]
-        correct = sum(1 for r in results if r.model == m and r.success)
-        pct = (correct / s.total * 100) if s.total else 0
-        row += f"{correct}/{s.total} ({pct:.0f}%) | "
-    lines.append(row)
-
-    # Avg latency
     row = "| Avg latency (s) | "
     for m in models:
-        s = stats[m]
-        row += f"{s.avg_latency:.2f} | "
+        row += f"{stats[m].avg_latency:.2f} | "
     lines.append(row)
 
+    row = "| Avg tokens per call | "
+    for m in models:
+        total = stats[m].total
+        avg_tokens = stats[m].total_tokens / total if total else 0
+        row += f"{avg_tokens:.1f} | "
+    lines.append(row)
+
+    row = "| Avg token cost per call (USD) | "
+    for m in models:
+        avg_cost = stats[m].avg_cost_usd
+        row += (f"{avg_cost:.6f} | " if avg_cost is not None else "n/a | ")
+    lines.append(row)
+
+    row = "| Skipped / unavailable | "
+    for m in models:
+        s = stats[m]
+        row += f"{s.skipped}/{s.total} | "
+    lines.append(row)
     lines.append("")
 
-    # Per-category breakdown
-    lines.append("## Per-Category Breakdown")
+    lines.append("## Per-category breakdown")
     lines.append("")
-
     for cat in sorted(by_category.keys()):
         lines.append(f"### {cat.title()}")
         lines.append("")
         lines.append(f"| Metric | {' | '.join(models)} |")
         lines.append(f"|--------|{'|'.join('---------' for _ in models)}|")
-
-        cat_data = by_category[cat]
         for metric_name, fn in [
             ("Schema OK", lambda r: r.schema_ok),
             ("Exec OK", lambda r: r.execution_ok),
+            ("Parallel OK", lambda r: r.parallel_ok),
             ("Correct tool", lambda r: r.success),
         ]:
             row = f"| {metric_name} | "
             for m in models:
-                results_m = cat_data.get(m, [])
-                total = len(results_m)
-                ok = sum(1 for r in results_m if fn(r))
-                pct = (ok / total * 100) if total else 0
-                row += f"{ok}/{total} ({pct:.0f}%) | "
+                results_m = by_category[cat].get(m, [])
+                attempted = [r for r in results_m if not r.skipped]
+                if not attempted:
+                    row += "n/a | "
+                    continue
+                ok = sum(1 for r in attempted if fn(r))
+                pct = ok / len(attempted) * 100
+                row += f"{ok}/{len(attempted)} ({pct:.0f}%) | "
             lines.append(row)
 
+        row = "| Avg tokens | "
+        for m in models:
+            results_m = by_category[cat].get(m, [])
+            avg_tokens = sum(r.total_tokens for r in results_m) / len(results_m) if results_m else 0
+            row += f"{avg_tokens:.1f} | "
+        lines.append(row)
+
+        row = "| Skipped | "
+        for m in models:
+            results_m = by_category[cat].get(m, [])
+            skipped = sum(1 for r in results_m if r.skipped)
+            row += f"{skipped}/{len(results_m)} | "
+        lines.append(row)
         lines.append("")
 
-    # Failure analysis
-    lines.append("## Failure Analysis")
+    lines.append("## Failure analysis")
     lines.append("")
-
     any_failures = False
     for m in models:
         s = stats[m]
@@ -514,28 +641,40 @@ def generate_report(results: list[CallResult], models: list[str], output_path: P
                 err = r.error or "wrong tool"
                 lines.append(f"| {r.test_id} | {r.category} | {r.expected_tool} | {got} | {err[:60]} |")
             lines.append("")
-
     if not any_failures:
-        lines.append("No failures detected.")
+        lines.append("No model failures detected.")
         lines.append("")
 
-    # Raw results JSON
-    lines.append("## Raw Results")
+    skipped_results = [r for r in results if r.skipped]
+    lines.append("## Skipped / unavailable cases")
+    lines.append("")
+    if skipped_results:
+        lines.append("| Test | Model | Category | Reason |")
+        lines.append("|------|-------|----------|--------|")
+        for r in skipped_results:
+            lines.append(f"| {r.test_id} | {r.model} | {r.category} | {r.skip_reason[:80]} |")
+    else:
+        lines.append("No cases were skipped.")
+    lines.append("")
+
+    lines.append("## Raw results")
     lines.append("")
     lines.append("```json")
     lines.append(json.dumps([asdict(r) for r in results], indent=2, default=str))
     lines.append("```")
 
     report = "\n".join(lines)
-    output_path.write_text(report)
+    output_path.write_text(report, encoding="utf-8")
     return report
 
 
 def main():
     parser = argparse.ArgumentParser(description="Tool-calling benchmark")
     parser.add_argument("--models", nargs="+",
-                        default=["nous:gia-3/gemma-4-31b", "nous:mimo-v2-pro"],
+                        default=list(DEFAULT_COMPARE_MODELS),
                         help="Model specs to test (provider:model)")
+    parser.add_argument("--compare", action="store_true",
+                        help="Use the issue #796 default comparison set")
     parser.add_argument("--limit", type=int, default=0,
                         help="Run only first N tests (0 = all)")
     parser.add_argument("--category", type=str, default="",
@@ -546,6 +685,9 @@ def main():
                         help="Print test cases without running them")
     args = parser.parse_args()
 
+    if args.compare:
+        args.models = list(DEFAULT_COMPARE_MODELS)
+
     # Filter suite
     suite = SUITE[:]
     if args.category:

hermes_cli/config.py

@@ -523,7 +523,7 @@ DEFAULT_CONFIG = {
     
     # Text-to-speech configuration
     "tts": {
-        "provider": "edge",  # "edge" (free) | "elevenlabs" (premium) | "openai" | "minimax" | "mistral" | "neutts" (local) | "kittentts" (local)
+        "provider": "edge",  # "edge" (free) | "elevenlabs" (premium) | "openai" | "minimax" | "mistral" | "neutts" (local)
         "edge": {
             "voice": "en-US-AriaNeural",
             # Popular: AriaNeural, JennyNeural, AndrewNeural, BrianNeural, SoniaNeural
@@ -547,12 +547,6 @@ DEFAULT_CONFIG = {
             "model": "neuphonic/neutts-air-q4-gguf",  # HuggingFace model repo
             "device": "cpu",  # cpu, cuda, or mps
         },
-        "kittentts": {
-            "model": "KittenML/kitten-tts-nano-0.8-int8",  # 25MB int8 default
-            "voice": "Jasper",  # Jasper, Bella, Luna, Bruno, Rosie, Hugo, Kiki, Leo
-            "speed": 1.0,
-            "clean_text": True,
-        },
     },
     
     "stt": {

hermes_cli/setup.py

@@ -443,16 +443,6 @@ def _print_setup_summary(config: dict, hermes_home):
             tool_status.append(("Text-to-Speech (NeuTTS local)", True, None))
         else:
             tool_status.append(("Text-to-Speech (NeuTTS — not installed)", False, "run 'hermes setup tts'"))
-    elif tts_provider == "kittentts":
-        try:
-            import importlib.util
-            kittentts_ok = importlib.util.find_spec("kittentts") is not None
-        except Exception:
-            kittentts_ok = False
-        if kittentts_ok:
-            tool_status.append(("Text-to-Speech (KittenTTS local)", True, None))
-        else:
-            tool_status.append(("Text-to-Speech (KittenTTS — not installed)", False, "run 'hermes setup tts'"))
     else:
         tool_status.append(("Text-to-Speech (Edge TTS)", True, None))
 
@@ -901,7 +891,6 @@ def _install_neutts_deps() -> bool:
                 return False
         else:
             print_warning("espeak-ng is required for NeuTTS. Install it manually before using NeuTTS.")
-            return False
 
     # Install neutts Python package
     print()
@@ -921,34 +910,8 @@ def _install_neutts_deps() -> bool:
         return False
 
 
-def _install_kittentts_deps() -> bool:
-    """Install KittenTTS dependencies with user approval. Returns True on success."""
-    import subprocess
-    import sys
-
-    wheel_url = (
-        "https://github.com/KittenML/KittenTTS/releases/download/"
-        "0.8.1/kittentts-0.8.1-py3-none-any.whl"
-    )
-    print()
-    print_info("Installing kittentts Python package (~25-80MB model downloaded on first use)...")
-    print()
-    try:
-        subprocess.run(
-            [sys.executable, "-m", "pip", "install", "-U", wheel_url, "soundfile", "--quiet"],
-            check=True, timeout=300,
-        )
-        print_success("kittentts installed successfully")
-        return True
-    except (subprocess.CalledProcessError, subprocess.TimeoutExpired) as e:
-        print_error(f"Failed to install kittentts: {e}")
-        print_info(f"Try manually: python -m pip install -U '{wheel_url}' soundfile")
-        return False
-
-
 def _setup_tts_provider(config: dict):
-    """Interactive TTS provider selection with install flow for local providers."""
-
+    """Interactive TTS provider selection with install flow for NeuTTS."""
     tts_config = config.get("tts", {})
     current_provider = tts_config.get("provider", "edge")
     subscription_features = get_nous_subscription_features(config)
@@ -960,7 +923,6 @@ def _setup_tts_provider(config: dict):
         "minimax": "MiniMax TTS",
         "mistral": "Mistral Voxtral TTS",
         "neutts": "NeuTTS",
-        "kittentts": "KittenTTS",
     }
     current_label = provider_labels.get(current_provider, current_provider)
 
@@ -982,10 +944,9 @@ def _setup_tts_provider(config: dict):
             "MiniMax TTS (high quality with voice cloning, needs API key)",
             "Mistral Voxtral TTS (multilingual, native Opus, needs API key)",
             "NeuTTS (local on-device, free, ~300MB model download)",
-            "KittenTTS (local on-device, free, lightweight ~25-80MB ONNX)",
         ]
     )
-    providers.extend(["edge", "elevenlabs", "openai", "minimax", "mistral", "neutts", "kittentts"])
+    providers.extend(["edge", "elevenlabs", "openai", "minimax", "mistral", "neutts"])
     choices.append(f"Keep current ({current_label})")
     keep_current_idx = len(choices) - 1
     idx = prompt_choice("Select TTS provider:", choices, keep_current_idx)
@@ -1027,28 +988,6 @@ def _setup_tts_provider(config: dict):
                 print_info("Skipping install. Set tts.provider to 'neutts' after installing manually.")
                 selected = "edge"
 
-    elif selected == "kittentts":
-        try:
-            import importlib.util
-            already_installed = importlib.util.find_spec("kittentts") is not None
-        except Exception:
-            already_installed = False
-
-        if already_installed:
-            print_success("KittenTTS is already installed")
-        else:
-            print()
-            print_info("KittenTTS is lightweight (~25-80MB, CPU-only, no API key required).")
-            print_info("Voices: Jasper, Bella, Luna, Bruno, Rosie, Hugo, Kiki, Leo")
-            print()
-            if prompt_yes_no("Install KittenTTS now?", True):
-                if not _install_kittentts_deps():
-                    print_warning("KittenTTS installation incomplete. Falling back to Edge TTS.")
-                    selected = "edge"
-            else:
-                print_info("Skipping install. Set tts.provider to 'kittentts' after installing manually.")
-                selected = "edge"
-
     elif selected == "elevenlabs":
         existing = get_env_value("ELEVENLABS_API_KEY")
         if not existing:

hermes_cli/tools_config.py

@@ -164,14 +164,6 @@ TOOL_CATEGORIES = {
                 ],
                 "tts_provider": "mistral",
             },
-            {
-                "name": "KittenTTS",
-                "badge": "local · free",
-                "tag": "Lightweight local ONNX TTS (~25MB), no API key",
-                "env_vars": [],
-                "tts_provider": "kittentts",
-                "post_setup": "kittentts",
-            },
         ],
     },
     "web": {
@@ -411,36 +403,6 @@ def _run_post_setup(post_setup_key: str):
             _print_warning("    Node.js not found. Install Camofox via Docker:")
             _print_info("      docker run -p 9377:9377 -e CAMOFOX_PORT=9377 jo-inc/camofox-browser")
 
-    elif post_setup_key == "kittentts":
-        try:
-            __import__("kittentts")
-            _print_success("    kittentts is already installed")
-            return
-        except ImportError:
-            pass
-        import subprocess
-        _print_info("    Installing kittentts (~25-80MB model, CPU-only)...")
-        wheel_url = (
-            "https://github.com/KittenML/KittenTTS/releases/download/"
-            "0.8.1/kittentts-0.8.1-py3-none-any.whl"
-        )
-        try:
-            result = subprocess.run(
-                [sys.executable, "-m", "pip", "install", "-U", wheel_url, "soundfile", "--quiet"],
-                capture_output=True, text=True, timeout=300,
-            )
-            if result.returncode == 0:
-                _print_success("    kittentts installed")
-                _print_info("    Voices: Jasper, Bella, Luna, Bruno, Rosie, Hugo, Kiki, Leo")
-                _print_info("    Models: KittenML/kitten-tts-nano-0.8-int8 (25MB), micro (41MB), mini (80MB)")
-            else:
-                _print_warning("    kittentts install failed:")
-                _print_info(f"      {result.stderr.strip()[:300]}")
-                _print_info(f"    Run manually: python -m pip install -U '{wheel_url}' soundfile")
-        except subprocess.TimeoutExpired:
-            _print_warning("    kittentts install timed out (>5min)")
-            _print_info(f"    Run manually: python -m pip install -U '{wheel_url}' soundfile")
-
     elif post_setup_key == "rl_training":
         try:
             __import__("tinker_atropos")

tests/test_tool_call_benchmark.py

@@ -0,0 +1,115 @@
+"""Tests for Issue #796 tool-calling benchmark coverage and reporting."""
+
+import sys
+from pathlib import Path
+from types import SimpleNamespace
+from unittest.mock import patch
+
+sys.path.insert(0, str(Path(__file__).parent.parent / "benchmarks"))
+
+from tool_call_benchmark import (  # noqa: E402
+    CallResult,
+    DEFAULT_COMPARE_MODELS,
+    ISSUE_796_CATEGORY_COUNTS,
+    ToolCall,
+    generate_report,
+    run_single_test,
+    suite_category_counts,
+)
+
+
+def test_suite_counts_match_issue_796_distribution():
+    counts = suite_category_counts()
+    assert counts == ISSUE_796_CATEGORY_COUNTS
+    assert sum(counts.values()) == 100
+
+
+def test_default_compare_models_cover_issue_796_lanes():
+    assert len(DEFAULT_COMPARE_MODELS) == 3
+    assert any("gemma-4-31b" in spec for spec in DEFAULT_COMPARE_MODELS)
+    assert any("gemma-4-26b" in spec for spec in DEFAULT_COMPARE_MODELS)
+    assert any("mimo-v2-pro" in spec for spec in DEFAULT_COMPARE_MODELS)
+
+
+def test_generate_report_includes_parallel_and_cost_metrics(tmp_path):
+    output_path = tmp_path / "report.md"
+    results = [
+        CallResult(
+            test_id="file-01",
+            category="file",
+            model="gemma-4-31b",
+            prompt="Read the file.",
+            expected_tool="read_file",
+            success=True,
+            tool_called="read_file",
+            schema_ok=True,
+            tool_args_valid=True,
+            execution_ok=True,
+            tool_count=2,
+            parallel_ok=True,
+            latency_s=1.25,
+            total_tokens=123,
+            estimated_cost_usd=0.0012,
+            cost_status="estimated",
+        ),
+        CallResult(
+            test_id="web-01",
+            category="web",
+            model="mimo-v2-pro",
+            prompt="Search the web.",
+            expected_tool="web_search",
+            success=False,
+            tool_called="web_search",
+            schema_ok=True,
+            tool_args_valid=False,
+            execution_ok=False,
+            tool_count=1,
+            parallel_ok=False,
+            latency_s=2.5,
+            error="bad args",
+            total_tokens=456,
+            estimated_cost_usd=None,
+            cost_status="unknown",
+            skipped=True,
+            skip_reason="web_search unavailable",
+        ),
+    ]
+
+    report = generate_report(results, ["gemma-4-31b", "mimo-v2-pro"], output_path)
+
+    assert output_path.exists()
+    assert "Parallel tool success" in report
+    assert "Avg token cost per call (USD)" in report
+    assert "Skipped / unavailable" in report
+    assert "Requested category mix" in report
+
+
+def test_run_single_test_skips_when_expected_tool_unavailable():
+    class FakeAgent:
+        def __init__(self, *args, **kwargs):
+            self.valid_tool_names = {"read_file", "terminal"}
+            self.session_input_tokens = 0
+            self.session_output_tokens = 0
+            self.session_cache_read_tokens = 0
+            self.session_cache_write_tokens = 0
+            self.session_api_calls = 0
+            self.base_url = ""
+            self.api_key = None
+
+        def run_conversation(self, *args, **kwargs):
+            raise AssertionError("run_conversation should not be called for unavailable tools")
+
+    tc = ToolCall(
+        id="mcp-01",
+        category="mcp",
+        prompt="Use an MCP tool to list resources.",
+        expected_tool="",
+        expected_tool_prefix="mcp_",
+    )
+
+    with patch.dict(sys.modules, {"run_agent": SimpleNamespace(AIAgent=FakeAgent)}):
+        result = run_single_test(tc, "gemini:gemma-4-31b-it", "gemini")
+
+    assert result.skipped is True
+    assert "mcp_" in result.skip_reason
+    assert result.success is False

tests/tools/test_tts_kittentts.py

@@ -1,236 +0,0 @@
-"""Tests for the KittenTTS local provider in tools/tts_tool.py."""
-
-import json
-from unittest.mock import MagicMock, patch
-
-import numpy as np
-import pytest
-
-
-@pytest.fixture(autouse=True)
-def clean_env(monkeypatch):
-    for key in ("HERMES_SESSION_PLATFORM",):
-        monkeypatch.delenv(key, raising=False)
-
-
-@pytest.fixture(autouse=True)
-def clear_kittentts_cache():
-    """Reset the module-level model cache between tests."""
-    from tools import tts_tool as _tt
-    _tt._kittentts_model_cache.clear()
-    yield
-    _tt._kittentts_model_cache.clear()
-
-
-@pytest.fixture
-def mock_kittentts_module():
-    """Inject a fake kittentts + soundfile module that return stub objects."""
-    fake_model = MagicMock()
-    # 24kHz float32 PCM at ~2s of silence
-    fake_model.generate.return_value = np.zeros(48000, dtype=np.float32)
-    fake_cls = MagicMock(return_value=fake_model)
-    fake_kittentts = MagicMock()
-    fake_kittentts.KittenTTS = fake_cls
-
-    # Stub soundfile — the real package isn't installed in CI venv, and
-    # _generate_kittentts does `import soundfile as sf` at runtime.
-    fake_sf = MagicMock()
-
-    def _fake_write(path, audio, samplerate):
-        # Emulate writing a real file so downstream path checks succeed.
-        import pathlib
-
-        pathlib.Path(path).write_bytes(b"RIFF\x00\x00\x00\x00WAVEfmt fake")
-
-    fake_sf.write = _fake_write
-
-    with patch.dict(
-        "sys.modules",
-        {"kittentts": fake_kittentts, "soundfile": fake_sf},
-    ):
-        yield fake_model, fake_cls
-
-
-class TestGenerateKittenTts:
-    def test_successful_wav_generation(self, tmp_path, mock_kittentts_module):
-        from tools.tts_tool import _generate_kittentts
-
-        fake_model, fake_cls = mock_kittentts_module
-        output_path = str(tmp_path / "test.wav")
-        result = _generate_kittentts("Hello world", output_path, {})
-
-        assert result == output_path
-        assert (tmp_path / "test.wav").exists()
-        fake_cls.assert_called_once()
-        fake_model.generate.assert_called_once()
-
-    def test_config_passes_voice_speed_cleantext(self, tmp_path, mock_kittentts_module):
-        from tools.tts_tool import _generate_kittentts
-
-        fake_model, _ = mock_kittentts_module
-        config = {
-            "kittentts": {
-                "model": "KittenML/kitten-tts-mini-0.8",
-                "voice": "Luna",
-                "speed": 1.25,
-                "clean_text": False,
-            }
-        }
-        _generate_kittentts("Hi there", str(tmp_path / "out.wav"), config)
-
-        call_kwargs = fake_model.generate.call_args.kwargs
-        assert call_kwargs["voice"] == "Luna"
-        assert call_kwargs["speed"] == 1.25
-        assert call_kwargs["clean_text"] is False
-
-    def test_default_model_and_voice(self, tmp_path, mock_kittentts_module):
-        from tools.tts_tool import (
-            DEFAULT_KITTENTTS_MODEL,
-            DEFAULT_KITTENTTS_VOICE,
-            _generate_kittentts,
-        )
-
-        fake_model, fake_cls = mock_kittentts_module
-        _generate_kittentts("Hi", str(tmp_path / "out.wav"), {})
-
-        fake_cls.assert_called_once_with(DEFAULT_KITTENTTS_MODEL)
-        assert fake_model.generate.call_args.kwargs["voice"] == DEFAULT_KITTENTTS_VOICE
-
-    def test_model_is_cached_across_calls(self, tmp_path, mock_kittentts_module):
-        from tools.tts_tool import _generate_kittentts
-
-        _, fake_cls = mock_kittentts_module
-        _generate_kittentts("One", str(tmp_path / "a.wav"), {})
-        _generate_kittentts("Two", str(tmp_path / "b.wav"), {})
-
-        # Same model name → class instantiated exactly once
-        assert fake_cls.call_count == 1
-
-    def test_different_models_are_cached_separately(self, tmp_path, mock_kittentts_module):
-        from tools.tts_tool import _generate_kittentts
-
-        _, fake_cls = mock_kittentts_module
-        _generate_kittentts(
-            "A",
-            str(tmp_path / "a.wav"),
-            {"kittentts": {"model": "KittenML/kitten-tts-nano-0.8-int8"}},
-        )
-        _generate_kittentts(
-            "B",
-            str(tmp_path / "b.wav"),
-            {"kittentts": {"model": "KittenML/kitten-tts-mini-0.8"}},
-        )
-
-        assert fake_cls.call_count == 2
-
-    def test_non_wav_extension_triggers_ffmpeg_conversion(
-        self, tmp_path, mock_kittentts_module, monkeypatch
-    ):
-        """Non-.wav output path causes WAV → target ffmpeg conversion."""
-        from tools import tts_tool as _tt
-
-        calls = []
-
-        def fake_shutil_which(cmd):
-            return "/usr/bin/ffmpeg" if cmd == "ffmpeg" else None
-
-        def fake_run(cmd, check=False, timeout=None, **kw):
-            calls.append(cmd)
-            # Emulate ffmpeg writing the output file
-            import pathlib
-
-            out_path = cmd[-1]
-            pathlib.Path(out_path).write_bytes(b"fake-mp3-data")
-            return MagicMock(returncode=0)
-
-        monkeypatch.setattr(_tt.shutil, "which", fake_shutil_which)
-        monkeypatch.setattr(_tt.subprocess, "run", fake_run)
-
-        output_path = str(tmp_path / "test.mp3")
-        result = _tt._generate_kittentts("Hi", output_path, {})
-
-        assert result == output_path
-        assert len(calls) == 1
-        assert calls[0][0] == "/usr/bin/ffmpeg"
-
-    def test_missing_kittentts_raises_import_error(self, tmp_path, monkeypatch):
-        """When kittentts package is not installed, _import_kittentts raises."""
-        import sys
-
-        monkeypatch.setitem(sys.modules, "kittentts", None)
-        from tools.tts_tool import _generate_kittentts
-
-        with pytest.raises((ImportError, TypeError)):
-            _generate_kittentts("Hi", str(tmp_path / "out.wav"), {})
-
-
-class TestCheckKittenttsAvailable:
-    def test_reports_available_when_package_present(self, monkeypatch):
-        import importlib.util
-        from tools.tts_tool import _check_kittentts_available
-
-        fake_spec = MagicMock()
-        monkeypatch.setattr(
-            importlib.util,
-            "find_spec",
-            lambda name: fake_spec if name == "kittentts" else None,
-        )
-        assert _check_kittentts_available() is True
-
-    def test_reports_unavailable_when_package_missing(self, monkeypatch):
-        import importlib.util
-        from tools.tts_tool import _check_kittentts_available
-
-        monkeypatch.setattr(importlib.util, "find_spec", lambda name: None)
-        assert _check_kittentts_available() is False
-
-
-class TestDispatcherBranch:
-    def test_kittentts_not_installed_returns_helpful_error(self, monkeypatch, tmp_path):
-        """When provider=kittentts but package missing, return JSON error with setup hint."""
-        import sys
-
-        monkeypatch.setitem(sys.modules, "kittentts", None)
-        monkeypatch.setenv("HERMES_HOME", str(tmp_path))
-
-        from tools.tts_tool import text_to_speech_tool
-
-        # Write a config telling it to use kittentts
-        import yaml
-
-        (tmp_path / "config.yaml").write_text(
-            yaml.safe_dump({"tts": {"provider": "kittentts"}})
-        )
-
-        result = json.loads(text_to_speech_tool(text="Hello"))
-        assert result["success"] is False
-        assert "kittentts" in result["error"].lower()
-        assert "hermes setup tts" in result["error"].lower()
-
-    def test_non_telegram_explicit_wav_path_is_preserved(
-        self, monkeypatch, tmp_path, mock_kittentts_module
-    ):
-        """Explicit WAV outputs should stay WAV outside Telegram sessions."""
-        import yaml
-        from tools import tts_tool as _tt
-
-        monkeypatch.setenv("HERMES_HOME", str(tmp_path))
-        (tmp_path / "config.yaml").write_text(
-            yaml.safe_dump({"tts": {"provider": "kittentts"}})
-        )
-
-        def fail_convert(_path):
-            raise AssertionError("_convert_to_opus should not run outside Telegram")
-
-        monkeypatch.setattr(_tt, "_convert_to_opus", fail_convert)
-
-        result = json.loads(
-            _tt.text_to_speech_tool(
-                text="Hello from KittenTTS",
-                output_path=str(tmp_path / "out.wav"),
-            )
-        )
-
-        assert result["success"] is True
-        assert result["file_path"] == str(tmp_path / "out.wav")
-        assert (tmp_path / "out.wav").exists()

tools/tts_tool.py

@@ -2,14 +2,13 @@
 """
 Text-to-Speech Tool Module
 
-Supports seven TTS providers:
+Supports six TTS providers:
 - Edge TTS (default, free, no API key): Microsoft Edge neural voices
 - ElevenLabs (premium): High-quality voices, needs ELEVENLABS_API_KEY
 - OpenAI TTS: Good quality, needs OPENAI_API_KEY
 - MiniMax TTS: High-quality with voice cloning, needs MINIMAX_API_KEY
 - Mistral (Voxtral TTS): Multilingual, native Opus, needs MISTRAL_API_KEY
 - NeuTTS (local, free, no API key): On-device TTS via neutts_cli, needs neutts installed
-- KittenTTS (local, free, no API key): Lightweight on-device ONNX TTS via kittentts
 
 Output formats:
 - Opus (.ogg) for Telegram voice bubbles (requires ffmpeg for Edge TTS)
@@ -78,12 +77,6 @@ def _import_sounddevice():
     return sd
 
 
-def _import_kittentts():
-    """Lazy import KittenTTS. Returns the class or raises ImportError."""
-    from kittentts import KittenTTS
-    return KittenTTS
-
-
 # ===========================================================================
 # Defaults
 # ===========================================================================
@@ -93,8 +86,6 @@ DEFAULT_ELEVENLABS_VOICE_ID = "pNInz6obpgDQGcFmaJgB"  # Adam
 DEFAULT_ELEVENLABS_MODEL_ID = "eleven_multilingual_v2"
 DEFAULT_ELEVENLABS_STREAMING_MODEL_ID = "eleven_flash_v2_5"
 DEFAULT_OPENAI_MODEL = "gpt-4o-mini-tts"
-DEFAULT_KITTENTTS_MODEL = "KittenML/kitten-tts-nano-0.8-int8"  # 25MB
-DEFAULT_KITTENTTS_VOICE = "Jasper"
 DEFAULT_OPENAI_VOICE = "alloy"
 DEFAULT_OPENAI_BASE_URL = "https://api.openai.com/v1"
 DEFAULT_MINIMAX_MODEL = "speech-2.8-hd"
@@ -457,15 +448,6 @@ def _check_neutts_available() -> bool:
         return False
 
 
-def _check_kittentts_available() -> bool:
-    """Check if the kittentts engine is importable (installed locally)."""
-    try:
-        import importlib.util
-        return importlib.util.find_spec("kittentts") is not None
-    except Exception:
-        return False
-
-
 def _default_neutts_ref_audio() -> str:
     """Return path to the bundled default voice reference audio."""
     return str(Path(__file__).parent / "neutts_samples" / "jo.wav")
@@ -529,51 +511,6 @@ def _generate_neutts(text: str, output_path: str, tts_config: Dict[str, Any]) ->
     return output_path
 
 
-# ===========================================================================
-# Provider: KittenTTS (local, lightweight)
-# ===========================================================================
-
-# Module-level cache for KittenTTS model instances
-_kittentts_model_cache: Dict[str, Any] = {}
-
-
-def _generate_kittentts(text: str, output_path: str, tts_config: Dict[str, Any]) -> str:
-    """Generate speech using the local KittenTTS ONNX model."""
-    KittenTTS = _import_kittentts()
-    kt_config = tts_config.get("kittentts", {})
-    model_name = kt_config.get("model", DEFAULT_KITTENTTS_MODEL)
-    voice = kt_config.get("voice", DEFAULT_KITTENTTS_VOICE)
-    speed = kt_config.get("speed", 1.0)
-    clean_text = kt_config.get("clean_text", True)
-
-    global _kittentts_model_cache
-    if model_name not in _kittentts_model_cache:
-        logger.info("[KittenTTS] Loading model: %s", model_name)
-        _kittentts_model_cache[model_name] = KittenTTS(model_name)
-
-    model = _kittentts_model_cache[model_name]
-    audio = model.generate(text, voice=voice, speed=speed, clean_text=clean_text)
-
-    import soundfile as sf
-
-    wav_path = output_path
-    if not output_path.endswith(".wav"):
-        wav_path = output_path.rsplit(".", 1)[0] + ".wav"
-
-    sf.write(wav_path, audio, 24000)
-
-    if wav_path != output_path:
-        ffmpeg = shutil.which("ffmpeg")
-        if ffmpeg:
-            conv_cmd = [ffmpeg, "-i", wav_path, "-y", "-loglevel", "error", output_path]
-            subprocess.run(conv_cmd, check=True, timeout=30)
-            os.remove(wav_path)
-        else:
-            os.rename(wav_path, output_path)
-
-    return output_path
-
-
 # ===========================================================================
 # Main tool function
 # ===========================================================================
@@ -685,19 +622,6 @@ def text_to_speech_tool(
             logger.info("Generating speech with NeuTTS (local)...")
             _generate_neutts(text, file_str, tts_config)
 
-        elif provider == "kittentts":
-            try:
-                _import_kittentts()
-            except ImportError:
-                return json.dumps({
-                    "success": False,
-                    "error": "KittenTTS provider selected but 'kittentts' package not installed. "
-                             "Run 'hermes setup tts' and choose KittenTTS, or install manually: "
-                             "pip install https://github.com/KittenML/KittenTTS/releases/download/0.8.1/kittentts-0.8.1-py3-none-any.whl"
-                }, ensure_ascii=False)
-            logger.info("Generating speech with KittenTTS (local, lightweight)...")
-            _generate_kittentts(text, file_str, tts_config)
-
         else:
             # Default: Edge TTS (free), with NeuTTS as local fallback
             edge_available = True
@@ -734,10 +658,10 @@ def text_to_speech_tool(
                 "error": f"TTS generation produced no output (provider: {provider})"
             }, ensure_ascii=False)
 
-        # Try Opus conversion for Telegram compatibility only.
-        # Outside Telegram, preserve the caller's explicit output format.
+        # Try Opus conversion for Telegram compatibility
+        # Edge TTS outputs MP3, NeuTTS outputs WAV — both need ffmpeg conversion
         voice_compatible = False
-        if want_opus and provider in ("edge", "neutts", "minimax", "kittentts") and not file_str.endswith(".ogg"):
+        if provider in ("edge", "neutts", "minimax") and not file_str.endswith(".ogg"):
             opus_path = _convert_to_opus(file_str)
             if opus_path:
                 file_str = opus_path
@@ -818,8 +742,6 @@ def check_tts_requirements() -> bool:
         pass
     if _check_neutts_available():
         return True
-    if _check_kittentts_available():
-        return True
     return False
 
 

website/docs/user-guide/features/tts.md

@@ -10,7 +10,7 @@ Hermes Agent supports both text-to-speech output and voice message transcription
 
 ## Text-to-Speech
 
-Convert text to speech with seven providers:
+Convert text to speech with six providers:
 
 | Provider | Quality | Cost | API Key |
 |----------|---------|------|---------|
@@ -20,7 +20,6 @@ Convert text to speech with seven providers:
 | **MiniMax TTS** | Excellent | Paid | `MINIMAX_API_KEY` |
 | **Mistral (Voxtral TTS)** | Excellent | Paid | `MISTRAL_API_KEY` |
 | **NeuTTS** | Good | Free | None needed |
-| **KittenTTS** | Good | Free (local) | None needed |
 
 ### Platform Delivery
 
@@ -36,7 +35,7 @@ Convert text to speech with seven providers:
 ```yaml
 # In ~/.hermes/config.yaml
 tts:
-  provider: "edge"              # "edge" | "elevenlabs" | "openai" | "minimax" | "mistral" | "neutts" | "kittentts"
+  provider: "edge"              # "edge" | "elevenlabs" | "openai" | "minimax" | "mistral" | "neutts"
   speed: 1.0                    # Global speed multiplier (provider-specific settings override this)
   edge:
     voice: "en-US-AriaNeural"   # 322 voices, 74 languages
@@ -63,11 +62,6 @@ tts:
     ref_text: ''
     model: neuphonic/neutts-air-q4-gguf
     device: cpu
-  kittentts:
-    model: KittenML/kitten-tts-nano-0.8-int8   # 25MB int8 default; also micro and mini variants
-    voice: Jasper                               # Jasper, Bella, Luna, Bruno, Rosie, Hugo, Kiki, Leo
-    speed: 1.0
-    clean_text: true
 ```
 
 **Speed control**: The global `tts.speed` value applies to all providers by default. Each provider can override it with its own `speed` setting (e.g., `tts.openai.speed: 1.5`). Provider-specific speed takes precedence over the global value. Default is `1.0` (normal speed).
@@ -80,7 +74,6 @@ Telegram voice bubbles require Opus/OGG audio format:
 - **Edge TTS** (default) outputs MP3 and needs **ffmpeg** to convert:
 - **MiniMax TTS** outputs MP3 and needs **ffmpeg** to convert for Telegram voice bubbles
 - **NeuTTS** outputs WAV and also needs **ffmpeg** to convert for Telegram voice bubbles
-- **KittenTTS** outputs WAV and also needs **ffmpeg** to convert for Telegram voice bubbles
 
 ```bash
 # Ubuntu/Debian
@@ -93,7 +86,7 @@ brew install ffmpeg
 sudo dnf install ffmpeg
 ```
 
-Without ffmpeg, Edge TTS, MiniMax TTS, NeuTTS, and KittenTTS audio are sent as regular audio files (playable, but shown as a rectangular player instead of a voice bubble).
+Without ffmpeg, Edge TTS, MiniMax TTS, and NeuTTS audio are sent as regular audio files (playable, but shown as a rectangular player instead of a voice bubble).
 
 :::tip
 If you want voice bubbles without installing ffmpeg, switch to the OpenAI, ElevenLabs, or Mistral provider.