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Akram Ben Aissi 5e74bc7fcf Add dynamic authentication token forwarding support for vLLM provider 
This enables per-request authentication tokens for vLLM providers, supporting use cases like RAG operations where different requests may need different authentication tokens. The implementation follows the same pattern as other providers like Together AI, Fireworks, and Passthrough.

- Add LiteLLMOpenAIMixin that manages the vllm_api_token properly

Usage:

- Static: VLLM_API_TOKEN env var or config.api_token
- Dynamic: X-LlamaStack-Provider-Data header with vllm_api_token
All existing functionality is preserved while adding new dynamic capabilities.

Signed-off-by: Akram Ben Aissi <akram.benaissi@gmail.com>
2025-09-15 13:01:12 +01:00
..
cli chore(rename): move llama_stack.distribution to llama_stack.core (#2975) 2025-07-30 23:30:53 -07:00
distribution chore(recorder): add support for NOT_GIVEN (#3430) 2025-09-13 11:11:38 -07:00
files chore(files tests): update files integration tests and fix inline::localfs (#3195) 2025-08-20 14:22:40 -04:00
models chore(test): migrate unit tests from unittest to pytest for system prompt (#2789) 2025-07-18 11:54:02 +02:00
prompts/prompts feat: Adding OpenAI Prompts API (#3319) 2025-09-08 11:05:13 -04:00
providers Add dynamic authentication token forwarding support for vLLM provider 2025-09-15 13:01:12 +01:00
rag fix: pre-commit issues: non executable shebang file and removal of @pytest.mark.asyncio decorator (#3397) 2025-09-10 15:27:35 +02:00
registry chore(rename): move llama_stack.distribution to llama_stack.core (#2975) 2025-07-30 23:30:53 -07:00
server feat: Add Kubernetes auth provider to use SelfSubjectReview and kubernetes api server (#2559) 2025-09-08 11:25:10 +02:00
utils chore: introduce write queue for inference_store (#3383) 2025-09-10 11:57:42 -07:00
__init__.py chore: Add fixtures to conftest.py (#2067) 2025-05-06 13:57:48 +02:00
conftest.py chore: block network access from unit tests (#2732) 2025-07-12 16:53:54 -07:00
fixtures.py chore(rename): move llama_stack.distribution to llama_stack.core (#2975) 2025-07-30 23:30:53 -07:00
README.md test: Measure and track code coverage (#2636) 2025-07-18 18:08:36 +02:00

README.md

Llama Stack Unit Tests

Unit Tests

Unit tests verify individual components and functions in isolation. They are fast, reliable, and don't require external services.

Prerequisites

  1. Python Environment: Ensure you have Python 3.12+ installed
  2. uv Package Manager: Install uv if not already installed

You can run the unit tests by running:

./scripts/unit-tests.sh [PYTEST_ARGS]

Any additional arguments are passed to pytest. For example, you can specify a test directory, a specific test file, or any pytest flags (e.g., -vvv for verbosity). If no test directory is specified, it defaults to "tests/unit", e.g:

./scripts/unit-tests.sh tests/unit/registry/test_registry.py -vvv

If you'd like to run for a non-default version of Python (currently 3.12), pass PYTHON_VERSION variable as follows:

source .venv/bin/activate
PYTHON_VERSION=3.13 ./scripts/unit-tests.sh

Test Configuration

  • Test Discovery: Tests are automatically discovered in the tests/unit/ directory
  • Async Support: Tests use --asyncio-mode=auto for automatic async test handling
  • Coverage: Tests generate coverage reports in htmlcov/ directory
  • Python Version: Defaults to Python 3.12, but can be overridden with PYTHON_VERSION environment variable

Coverage Reports

After running tests, you can view coverage reports:

# Open HTML coverage report in browser
open htmlcov/index.html  # macOS
xdg-open htmlcov/index.html  # Linux
start htmlcov/index.html  # Windows