feat(agent): Ollama tool-call adapter with parameterized timeouts (fixes #205) - #210
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feat(agent): Ollama tool-call adapter with parameterized timeouts (fixes #205)#210mike-011 wants to merge 5 commits into
mike-011 wants to merge 5 commits into
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Add openkb/agent/ollama_adapter.py — a resilient wrapper that catches ModelBehaviorError when Ollama models hallucinate tool names and retries with a corrective message listing the actual available tools. - is_ollama_backend(): detect Ollama models (ollama/ and litellm/ollama/ prefixes) - arun_with_retry(): wraps Runner.run() with retry on ModelBehaviorError - run_streamed_with_retry(): wraps Runner.run_streamed() with retry - _RetryableStreamResult: seamless stream retry via generator - 26 new tests in tests/test_ollama_adapter.py (all passing) - query.py patched to use retry wrapper for Ollama backends only - Non-Ollama path unchanged Issue: VectifyAI#205
Key improvements over v1: 1. rewrite_ollama_model(): convert ollama/ → ollama_chat/ so LiteLLM uses native Ollama Chat API with tool support (primary fix). Without this, LiteLLM falls back to prompt injection and tool calls never work through the SDK. 2. Configurable timeout: _ensure_ollama_timeout() injects 300s default into ModelSettings.extra_args for Ollama models, preventing premature timeouts on slow local hardware. 3. Updated query.py: rewrite applied in build_query_agent() and build_run_config_from_bundle(). 4. 41 tests (up from 26), all passing. 5. 1116 existing tests, all passing. 6. Live test: gemma4:12b full tool-loop completes in 132s. Issue: VectifyAI#205
Fixes for the full add+query pipeline with Ollama: 1. Module-level OLLAMA_API_BASE propagation in ollama_adapter.py: - OPENAI_API_BASE → OLLAMA_API_BASE (env var) - litellm.api_base module setting So ollama_chat LiteLLM provider finds the endpoint on all paths. 2. compiler.py: pass api_base from env when bundle is None (CLI path) so litellm.completion/acompletion reaches Ollama for add/concepts. 3. cli.py: rewrite_ollama_model applied to all model resolutions (12 sites) so ollama/ → ollama_chat/ everywhere, not just query. 4. add_coordinator.py: import ollama_adapter for side effects. 5. drop_params=True set in _ensure_ollama_settings for ollama_chat (rejects parallel_tool_calls). Tests: 1116 passed, 0 failed. Live: add summary=77s OK; query tool-loop=132s OK (SDK E2E verified). Issue: VectifyAI#205
Add resolve_ollama_settings() to read the 'ollama:' config block:
ollama:
timeout: 300 # per-request timeout (s), default 300
tool_call_retries: 3 # max retries on hallucinated tool names
Timeout precedence: ollama.timeout > litellm.timeout > top-level timeout > 300
Retry precedence: ollama.tool_call_retries > default 3
Changes:
- ollama_adapter.py: resolve_ollama_settings() + all retry/timeout
functions now resolve from config when not explicitly passed
- config.yaml.example: documented ollama: section
- docs/ollama_tool_call_adapter.md: full configuration documentation
- tests/test_ollama_adapter.py: 15 new tests for resolve_ollama_settings
(56 total, all passing; 1131 total suite, 0 failures)
Issue: VectifyAI#205
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Summary
Fixes #205
When using Ollama models with
openkb queryandopenkb chat, the openai-agents SDK tool-calling loop fails in three ways:ollama/prefix causes LiteLLM to strip tools and inject them into prompt text withformat: json. Model returns tool-call JSON incontentinstead oftool_calls.ModelBehaviorError.Fix
1. Model rewrite:
ollama/toollama_chat/Primary fix — LiteLLM uses native Ollama Chat API with tool support.
2. Retry on hallucination
Catches
ModelBehaviorError, appends corrective message, retries (configurable, default 3).3. Parameterized timeouts and retries
New
ollama:config block inconfig.yaml:4. drop_params + api_base propagation
Testing
See
docs/ollama_tool_call_adapter.mdfor full documentation.