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Implements a comprehensive recording and replay system for inference API calls that eliminates dependency on online inference providers during testing. The system treats inference as deterministic by recording real API responses and replaying them in subsequent test runs. Applies to OpenAI clients (which should cover many inference requests) as well as OpenAI AsyncClient. For storing, we use a hybrid system: Sqlite for fast lookups and JSON files for easy greppability / debuggability. As expected, tests become much much faster (more than 3x in just inference testing.) ```bash LLAMA_STACK_INFERENCE_MODE=record uv run pytest -s -v tests/integration/inference \ --stack-config=starter \ -k "not( builtin_tool or safety_with_image or code_interpreter or test_rag )" \ --text-model="ollama/llama3.2:3b-instruct-fp16" \ --embedding-model=sentence-transformers/all-MiniLM-L6-v2 ``` ```bash LLAMA_STACK_INFERENCE_MODE=replay LLAMA_STACK_TEST_ID=<test_id> uv run pytest -s -v tests/integration/inference \ --stack-config=starter \ -k "not( builtin_tool or safety_with_image or code_interpreter or test_rag )" \ --text-model="ollama/llama3.2:3b-instruct-fp16" \ --embedding-model=sentence-transformers/all-MiniLM-L6-v2 ``` - `LLAMA_STACK_INFERENCE_MODE`: `live` (default), `record`, or `replay` - `LLAMA_STACK_TEST_ID`: Specify recording directory (auto-generated if not set) - `LLAMA_STACK_RECORDING_DIR`: Storage location (default: ~/.llama/recordings/) |
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| .. | ||
| client-sdk/post_training | ||
| common | ||
| external | ||
| integration | ||
| unit | ||
| verifications | ||
| __init__.py | ||
| Containerfile | ||
| README.md | ||
Llama Stack Tests
Llama Stack has multiple layers of testing done to ensure continuous functionality and prevent regressions to the codebase.
| Testing Type | Details |
|---|---|
| Unit | unit/README.md |
| Integration | integration/README.md |
| Verification | verifications/README.md |