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https://github.com/meta-llama/llama-stack.git
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928a39d17b
Groq has never supported raw completions anyhow. So this makes it easier to switch it to LiteLLM. All our test suite passes. I also updated all the openai-compat providers so they work with api keys passed from headers. `provider_data` ## Test Plan ```bash LLAMA_STACK_CONFIG=groq \ pytest -s -v tests/client-sdk/inference/test_text_inference.py \ --inference-model=groq/llama-3.3-70b-versatile --vision-inference-model="" ``` Also tested (openai, anthropic, gemini) providers. No regressions. |
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| .. | ||
| agents | ||
| inference | ||
| safety | ||
| tool_runtime | ||
| vector_io | ||
| __init__.py | ||
| conftest.py | ||
| metadata.py | ||
| README.md | ||
| report.py | ||
Llama Stack Integration Tests
You can run llama stack integration tests on either a Llama Stack Library or a Llama Stack endpoint.
To test on a Llama Stack library with certain configuration, run
LLAMA_STACK_CONFIG=./llama_stack/templates/cerebras/run.yaml pytest -s -v tests/client-sdk/inference/
or just the template name
LLAMA_STACK_CONFIG=together pytest -s -v tests/client-sdk/inference/
To test on a Llama Stack endpoint, run
LLAMA_STACK_BASE_URL=http://localhost:8089 pytest -s -v tests/client-sdk/inference
Report Generation
To generate a report, run with --report option
LLAMA_STACK_CONFIG=together pytest -s -v report.md tests/client-sdk/ --report
Common options
Depending on the API, there are custom options enabled
- For tests in
inference/andagents/, we support--inference-model(to be used in text inference tests) and--vision-inference-model` (only used in image inference tests) overrides - For tests in
vector_io/, we support--embedding-modeloverride - For tests in
safety/, we support--safety-shieldoverride - The param can be
--reportor--report <path>If path is not provided, we do a best effort to infer based on the config / template name. For url endpoints, path is required.