llama-stack-mirror/tests/unit
Ben Browning 2d9fd041eb
fix: annotations list and web_search_preview in Responses (#2520)
# What does this PR do?


These are a couple of fixes to get an example LangChain app working with
our OpenAI Responses API implementation.

The Responses API spec requires an annotations array in
`output[*].content[*].annotations` and we were not providing one. So,
this adds that as an empty list, even though we don't do anything to
populate it yet. This prevents an error from client libraries like
Langchain that expect this field to always exist, even if an empty list.

The other fix is `web_search_preview` is a valid name for the web search
tool in the Responses API, but we only responded to `web_search` or
`web_search_preview_2025_03_11`.


## Test Plan


The existing Responses unit tests were expanded to test these cases,
via:

```
pytest -sv tests/unit/providers/agents/meta_reference/test_openai_responses.py
```

The existing test_openai_responses.py integration tests still pass with
this change, tested as below with Fireworks:

```
uv run llama stack run llama_stack/templates/starter/run.yaml

LLAMA_STACK_CONFIG=http://localhost:8321 \
uv run pytest -sv tests/integration/agents/test_openai_responses.py \
  --text-model accounts/fireworks/models/llama4-scout-instruct-basic
```

Lastly, this example LangChain app now works with Llama stack (tested
with Ollama in the starter template in this case). This LangChain code
is using the example snippets for using Responses API at
https://python.langchain.com/docs/integrations/chat/openai/#responses-api

```python
from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
    base_url="http://localhost:8321/v1/openai/v1",
    api_key="fake",
    model="ollama/meta-llama/Llama-3.2-3B-Instruct",
)

tool = {"type": "web_search_preview"}
llm_with_tools = llm.bind_tools([tool])

response = llm_with_tools.invoke("What was a positive news story from today?")

print(response.content)
```

Signed-off-by: Ben Browning <bbrownin@redhat.com>
2025-06-26 07:59:33 +05:30
..
cli chore: enable pyupgrade fixes (#1806) 2025-05-01 14:23:50 -07:00
distribution feat: fine grained access control policy (#2264) 2025-06-03 14:51:12 -07:00
files feat: support pagination in inference/responses stores (#2397) 2025-06-16 22:43:35 -07:00
models chore: remove usage of load_tiktoken_bpe (#2276) 2025-06-02 07:33:37 -07:00
providers fix: annotations list and web_search_preview in Responses (#2520) 2025-06-26 07:59:33 +05:30
rag feat: Add ChunkMetadata to Chunk (#2497) 2025-06-25 15:55:23 -04:00
registry feat: fine grained access control policy (#2264) 2025-06-03 14:51:12 -07:00
server feat: Add url field to PaginatedResponse and populate it using route … (#2419) 2025-06-16 11:19:48 +02:00
utils feat: support auth attributes in inference/responses stores (#2389) 2025-06-20 10:24:45 -07:00
__init__.py chore: Add fixtures to conftest.py (#2067) 2025-05-06 13:57:48 +02:00
conftest.py chore: Add fixtures to conftest.py (#2067) 2025-05-06 13:57:48 +02:00
fixtures.py chore: Add fixtures to conftest.py (#2067) 2025-05-06 13:57:48 +02:00
README.md chore: bump python supported version to 3.12 (#2475) 2025-06-24 09:22:04 +05:30

Llama Stack Unit Tests

You can run the unit tests by running:

source .venv/bin/activate
./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