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You now run the integration tests with these options: ```bash Custom options: --stack-config=STACK_CONFIG a 'pointer' to the stack. this can be either be: (a) a template name like `fireworks`, or (b) a path to a run.yaml file, or (c) an adhoc config spec, e.g. `inference=fireworks,safety=llama-guard,agents=meta- reference` --env=ENV Set environment variables, e.g. --env KEY=value --text-model=TEXT_MODEL comma-separated list of text models. Fixture name: text_model_id --vision-model=VISION_MODEL comma-separated list of vision models. Fixture name: vision_model_id --embedding-model=EMBEDDING_MODEL comma-separated list of embedding models. Fixture name: embedding_model_id --safety-shield=SAFETY_SHIELD comma-separated list of safety shields. Fixture name: shield_id --judge-model=JUDGE_MODEL comma-separated list of judge models. Fixture name: judge_model_id --embedding-dimension=EMBEDDING_DIMENSION Output dimensionality of the embedding model to use for testing. Default: 384 --record-responses Record new API responses instead of using cached ones. --report=REPORT Path where the test report should be written, e.g. --report=/path/to/report.md ``` Importantly, if you don't specify any of the models (text-model, vision-model, etc.) the relevant tests will get **skipped!** This will make running tests somewhat more annoying since all options will need to be specified. We will make this easier by adding some easy wrapper yaml configs. ## Test Plan Example: ```bash ashwin@ashwin-mbp ~/local/llama-stack/tests/integration (unify_tests) $ LLAMA_STACK_CONFIG=fireworks pytest -s -v inference/test_text_inference.py \ --text-model meta-llama/Llama-3.2-3B-Instruct ``` |
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.. | ||
apis | ||
cli | ||
distribution | ||
models/llama | ||
providers | ||
scripts | ||
strong_typing | ||
templates | ||
__init__.py | ||
env.py | ||
logcat.py | ||
schema_utils.py |