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4 commits

Author SHA1 Message Date
Xi Yan
66d7e15c93
perf: ensure ToolCall in ChatCompletionResponse is subset of ChatCompletionRequest.tools (#1041)
# What does this PR do?

**Problem**
- Using script:
https://gist.github.com/thoraxe/6163b2145ce7b1c24c6026b64cf90085

- This hits an issue on server with `code_interpreter` not found, as we
do not pass "builtin::code_interpreter" in AgentConfig's `toolgroups`.

This is a general issue where model always tries to output
`code_interpreter` in `ToolCall` even when we do not have
`code_interpreter` available for execution.

**Reproduce Deeper Problem in chat-completion**
- Use script:
https://gist.github.com/yanxi0830/163a9ad7b5db10556043fbfc7ecd7603

1. We currently always populate `code_interpreter` in `ToolCall` in
ChatCompletionResponse if the model's response begins with
`<|python_tag|>`. See
c5f5958498/models/llama3/api/chat_format.py (L200-L213)

<img width="913" alt="image"
src="https://github.com/user-attachments/assets/328d313d-0a0b-495c-8715-61cca9ccc4a6"
/>

2. This happens even if we do not pass the `code_interpreter` as a
`tools` in ChatCompletionRequest.

**This PR**

Explicitly make sure that the tools returned in
`ChatCompletionResponse.tool_calls` is always a tool requested by
`ChatCompletionRequest.tools`.

[//]: # (If resolving an issue, uncomment and update the line below)
[//]: # (Closes #[issue-number])

## Test Plan

**Before**
<img width="913" alt="image"
src="https://github.com/user-attachments/assets/328d313d-0a0b-495c-8715-61cca9ccc4a6"
/>
<img width="997" alt="image"
src="https://github.com/user-attachments/assets/d3e82b62-b142-4939-954c-62843bec7110"
/>


**After**
<img width="856" alt="image"
src="https://github.com/user-attachments/assets/2c70ce55-c8d0-45ea-b10f-f70adc50d3d9"
/>
<img width="1000" alt="image"
src="https://github.com/user-attachments/assets/b5e81826-c35b-4052-bf81-7afff93ce2ef"
/>



**Unit Test**
```
LLAMA_STACK_BASE_URL=http://localhost:8321 pytest -v tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_tool_calling_tools_not_in_request --inference-model "meta-llama/Llama-3.3-70B-Instruct"
```

```
LLAMA_STACK_BASE_URL=http://localhost:8321 pytest -v tests/client-sdk/agents/
```
<img width="1002" alt="image"
src="https://github.com/user-attachments/assets/04808517-eded-4122-97f5-7e5142de9779"
/>



**Streaming**
- Chat Completion
<img width="902" alt="image"
src="https://github.com/user-attachments/assets/f477bc86-bd38-4729-b49e-a0a6ed3f835a"
/>

- Agent
<img width="916" alt="image"
src="https://github.com/user-attachments/assets/f4cc3417-23cd-46b1-953d-3a2271e79bbb"
/>


[//]: # (## Documentation)
[//]: # (- [ ] Added a Changelog entry if the change is significant)
2025-02-11 18:31:35 -08:00
Yuan Tang
b981b49bfa
test: Use JSON tool prompt format for remote::vllm provider (#1019)
# What does this PR do?

This PR removes the warnings when running tests for `remote::vllm`
provider:
```
Detected the chat template content format to be 'openai'. You can set `--chat-template-content-format` to override this.
```

## Test Plan

All tests passed without the warning messages shown above.

Signed-off-by: Yuan Tang <terrytangyuan@gmail.com>
2025-02-08 20:42:57 -08:00
Yuan Tang
413099ef6a
test: Make text-based chat completion tests run 10x faster (#1016)
# What does this PR do?

This significantly shortens the test time (about 10x faster) since most
of the time is spent on outputing the tokens "there are several planets
in our solar system that have...". We want to have an answer quicker,
especially when testing even larger models.

## Test Plan

```
LLAMA_STACK_BASE_URL=http://localhost:5002 pytest -v tests/client-sdk/inference/test_text_inference.py -k "test_text_chat_completion_non_streaming or test_text_chat_completion_streaming"
================================================================== test session starts ===================================================================
platform linux -- Python 3.10.16, pytest-8.3.4, pluggy-1.5.0 -- /home/yutang/.conda/envs/myenv/bin/python3.10
cachedir: .pytest_cache
rootdir: /home/yutang/repos/llama-stack
configfile: pyproject.toml
plugins: anyio-4.7.0
collected 12 items / 8 deselected / 4 selected                                                                                                           

tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_non_streaming[meta-llama/Llama-3.1-8B-Instruct-Which planet do humans live on?-Earth] PASSED [ 25%]
tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_non_streaming[meta-llama/Llama-3.1-8B-Instruct-Which planet has rings around it with a name starting with letter S?-Saturn] PASSED [ 50%]
tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_streaming[meta-llama/Llama-3.1-8B-Instruct-What's the name of the Sun in latin?-Sol] PASSED [ 75%]
tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_streaming[meta-llama/Llama-3.1-8B-Instruct-What is the name of the US captial?-Washington] PASSED [100%]


```

---------

Signed-off-by: Yuan Tang <terrytangyuan@gmail.com>
2025-02-08 11:49:46 -08:00
Yuan Tang
c97e05f75e
test: Split inference tests to text and vision (#1008)
# What does this PR do?

This PR splits the inference tests into text and vision to make testing
on vLLM provider easier as mentioned in
https://github.com/meta-llama/llama-stack/pull/951 since serving
multiple models (e.g. Llama-3.2-11B-Vision-Instruct and
Llama-3.1-8B-Instruct) on a single port using the OpenAI API is [not
supported yet](https://docs.vllm.ai/en/v0.5.5/serving/faq.html) so it's
a bit tricky to test both at the same time.

## Test Plan

All previously passing tests related to text still pass:
`LLAMA_STACK_BASE_URL=http://localhost:5002 pytest -v
tests/client-sdk/inference/test_text_inference.py`

All vision tests passed via `LLAMA_STACK_BASE_URL=http://localhost:5002
pytest -v tests/client-sdk/inference/test_vision_inference.py`.

Signed-off-by: Yuan Tang <terrytangyuan@gmail.com>
2025-02-07 09:35:49 -08:00
Renamed from tests/client-sdk/inference/test_inference.py (Browse further)