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114 lines
4.3 KiB
Markdown
114 lines
4.3 KiB
Markdown
# Llama Stack Integration Tests
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We use `pytest` for parameterizing and running tests. You can see all options with:
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```bash
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cd tests/integration
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# this will show a long list of options, look for "Custom options:"
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pytest --help
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```
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Here are the most important options:
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- `--stack-config`: specify the stack config to use. You have four ways to point to a stack:
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- **`server:<config>`** - automatically start a server with the given config (e.g., `server:fireworks`). This provides one-step testing by auto-starting the server if the port is available, or reusing an existing server if already running.
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- **`server:<config>:<port>`** - same as above but with a custom port (e.g., `server:together:8322`)
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- a URL which points to a Llama Stack distribution server
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- a template (e.g., `starter`) or a path to a `run.yaml` file
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- a comma-separated list of api=provider pairs, e.g. `inference=fireworks,safety=llama-guard,agents=meta-reference`. This is most useful for testing a single API surface.
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- `--env`: set environment variables, e.g. --env KEY=value. this is a utility option to set environment variables required by various providers.
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Model parameters can be influenced by the following options:
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- `--text-model`: comma-separated list of text models.
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- `--vision-model`: comma-separated list of vision models.
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- `--embedding-model`: comma-separated list of embedding models.
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- `--safety-shield`: comma-separated list of safety shields.
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- `--judge-model`: comma-separated list of judge models.
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- `--embedding-dimension`: output dimensionality of the embedding model to use for testing. Default: 384
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Each of these are comma-separated lists and can be used to generate multiple parameter combinations. Note that tests will be skipped
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if no model is specified.
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## Examples
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### Testing against a Server
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Run all text inference tests by auto-starting a server with the `fireworks` config:
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```bash
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pytest -s -v tests/integration/inference/test_text_inference.py \
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--stack-config=server:fireworks \
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--text-model=meta-llama/Llama-3.1-8B-Instruct
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```
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Run tests with auto-server startup on a custom port:
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```bash
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pytest -s -v tests/integration/inference/ \
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--stack-config=server:together:8322 \
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--text-model=meta-llama/Llama-3.1-8B-Instruct
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```
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Run multiple test suites with auto-server (eliminates manual server management):
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```bash
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# Auto-start server and run all integration tests
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export FIREWORKS_API_KEY=<your_key>
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pytest -s -v tests/integration/inference/ tests/integration/safety/ tests/integration/agents/ \
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--stack-config=server:fireworks \
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--text-model=meta-llama/Llama-3.1-8B-Instruct
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```
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### Testing with Library Client
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Run all text inference tests with the `starter` distribution using the `together` provider:
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```bash
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ENABLE_TOGETHER=together pytest -s -v tests/integration/inference/test_text_inference.py \
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--stack-config=starter \
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--text-model=meta-llama/Llama-3.1-8B-Instruct
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```
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Run all text inference tests with the `starter` distribution using the `together` provider and `meta-llama/Llama-3.1-8B-Instruct`:
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```bash
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ENABLE_TOGETHER=together pytest -s -v tests/integration/inference/test_text_inference.py \
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--stack-config=starter \
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--text-model=meta-llama/Llama-3.1-8B-Instruct
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```
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Running all inference tests for a number of models using the `together` provider:
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```bash
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TEXT_MODELS=meta-llama/Llama-3.1-8B-Instruct,meta-llama/Llama-3.1-70B-Instruct
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VISION_MODELS=meta-llama/Llama-3.2-11B-Vision-Instruct
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EMBEDDING_MODELS=all-MiniLM-L6-v2
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ENABLE_TOGETHER=together
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export TOGETHER_API_KEY=<together_api_key>
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pytest -s -v tests/integration/inference/ \
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--stack-config=together \
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--text-model=$TEXT_MODELS \
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--vision-model=$VISION_MODELS \
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--embedding-model=$EMBEDDING_MODELS
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```
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Same thing but instead of using the distribution, use an adhoc stack with just one provider (`fireworks` for inference):
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```bash
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export FIREWORKS_API_KEY=<fireworks_api_key>
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pytest -s -v tests/integration/inference/ \
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--stack-config=inference=fireworks \
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--text-model=$TEXT_MODELS \
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--vision-model=$VISION_MODELS \
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--embedding-model=$EMBEDDING_MODELS
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```
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Running Vector IO tests for a number of embedding models:
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```bash
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uv run pytest -sv --stack-config="inference=inline::sentence-transformers,vector_io=inline::sqlite-vec,files=localfs" \
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tests/integration/vector_io --embedding-model \
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sentence-transformers/all-MiniLM-L6-v2
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```
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