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https://github.com/meta-llama/llama-stack.git
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c3fc859257
add new overwrite_completion_id feature to OpenAIMixin to deal with TGI always returning id="" test with - tgi: `docker run --gpus all --shm-size 1g -p 8080:80 -v /data:/data ghcr.io/huggingface/text-generation-inference --model-id Qwen/Qwen3-0.6B` stack: `TGI_URL=http://localhost:8080 uv run llama stack build --image-type venv --distro ci-tests --run` test: `./scripts/integration-tests.sh --stack-config http://localhost:8321 --setup tgi --subdirs inference --pattern openai`
129 lines
3.7 KiB
Python
129 lines
3.7 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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# Central definition of integration test suites. You can use these suites by passing --suite=name to pytest.
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# For example:
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#
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# ```bash
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# pytest tests/integration/ --suite=vision --setup=ollama
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# ```
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#
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"""
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Each suite defines what to run (roots). Suites can be run with different global setups defined in setups.py.
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Setups provide environment variables and model defaults that can be reused across multiple suites.
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CLI examples:
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pytest tests/integration --suite=responses --setup=gpt
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pytest tests/integration --suite=vision --setup=ollama
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pytest tests/integration --suite=base --setup=vllm
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"""
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from pathlib import Path
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from pydantic import BaseModel, Field
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this_dir = Path(__file__).parent
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class Suite(BaseModel):
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name: str
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roots: list[str]
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default_setup: str | None = None
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class Setup(BaseModel):
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"""A reusable test configuration with environment and CLI defaults."""
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name: str
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description: str
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defaults: dict[str, str] = Field(default_factory=dict)
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env: dict[str, str] = Field(default_factory=dict)
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# Global setups - can be used with any suite "technically" but in reality, some setups might work
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# only for specific test suites.
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SETUP_DEFINITIONS: dict[str, Setup] = {
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"ollama": Setup(
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name="ollama",
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description="Local Ollama provider with text + safety models",
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env={
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"OLLAMA_URL": "http://0.0.0.0:11434",
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"SAFETY_MODEL": "ollama/llama-guard3:1b",
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},
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defaults={
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"text_model": "ollama/llama3.2:3b-instruct-fp16",
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"embedding_model": "sentence-transformers/all-MiniLM-L6-v2",
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"safety_model": "ollama/llama-guard3:1b",
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"safety_shield": "llama-guard",
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},
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),
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"ollama-vision": Setup(
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name="ollama",
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description="Local Ollama provider with a vision model",
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env={
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"OLLAMA_URL": "http://0.0.0.0:11434",
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},
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defaults={
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"vision_model": "ollama/llama3.2-vision:11b",
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"embedding_model": "sentence-transformers/all-MiniLM-L6-v2",
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},
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),
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"vllm": Setup(
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name="vllm",
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description="vLLM provider with a text model",
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env={
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"VLLM_URL": "http://localhost:8000/v1",
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},
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defaults={
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"text_model": "vllm/meta-llama/Llama-3.2-1B-Instruct",
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"embedding_model": "sentence-transformers/all-MiniLM-L6-v2",
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},
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),
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"gpt": Setup(
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name="gpt",
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description="OpenAI GPT models for high-quality responses and tool calling",
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defaults={
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"text_model": "openai/gpt-4o",
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"embedding_model": "sentence-transformers/all-MiniLM-L6-v2",
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},
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),
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"tgi": Setup(
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name="tgi",
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description="Text Generation Inference (TGI) provider with a text model",
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env={
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"TGI_URL": "http://localhost:8080",
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},
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defaults={
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"text_model": "tgi/Qwen/Qwen3-0.6B",
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},
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),
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}
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base_roots = [
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str(p)
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for p in this_dir.glob("*")
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if p.is_dir()
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and p.name not in ("__pycache__", "fixtures", "test_cases", "recordings", "responses", "post_training")
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]
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SUITE_DEFINITIONS: dict[str, Suite] = {
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"base": Suite(
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name="base",
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roots=base_roots,
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default_setup="ollama",
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),
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"responses": Suite(
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name="responses",
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roots=["tests/integration/responses"],
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default_setup="gpt",
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),
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"vision": Suite(
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name="vision",
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roots=["tests/integration/inference/test_vision_inference.py"],
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default_setup="ollama-vision",
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),
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}
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