forked from phoenix-oss/llama-stack-mirror
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)
This commit is contained in:
Xi Yan
GitHub
parent
dd37e58868
commit
66d7e15c93
14 changed files with 164 additions and 33 deletions
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@ -158,7 +158,10 @@ def test_text_completion_structured_output(llama_stack_client, text_model_id, in
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"question,expected",
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[
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("Which planet do humans live on?", "Earth"),
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("Which planet has rings around it with a name starting with letter S?", "Saturn"),
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(
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"Which planet has rings around it with a name starting with letter S?",
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"Saturn",
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),
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],
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)
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def test_text_chat_completion_non_streaming(llama_stack_client, text_model_id, question, expected):
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@ -280,3 +283,82 @@ def test_text_chat_completion_structured_output(llama_stack_client, text_model_i
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assert answer.last_name == "Jordan"
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assert answer.year_of_birth == 1963
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assert answer.num_seasons_in_nba == 15
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@pytest.mark.parametrize(
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"streaming",
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[
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True,
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False,
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],
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)
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def test_text_chat_completion_tool_calling_tools_not_in_request(llama_stack_client, text_model_id, streaming):
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# TODO: more dynamic lookup on tool_prompt_format for model family
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tool_prompt_format = "json" if "3.1" in text_model_id else "python_list"
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request = {
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"model_id": text_model_id,
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"messages": [
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{"role": "system", "content": "You are a helpful assistant."},
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{
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"role": "user",
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"content": "What pods are in the namespace openshift-lightspeed?",
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},
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{
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"role": "assistant",
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"content": "",
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"stop_reason": "end_of_turn",
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"tool_calls": [
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{
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"call_id": "1",
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"tool_name": "get_object_namespace_list",
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"arguments": {
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"kind": "pod",
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"namespace": "openshift-lightspeed",
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},
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}
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],
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},
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{
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"role": "tool",
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"call_id": "1",
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"tool_name": "get_object_namespace_list",
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"content": "the objects are pod1, pod2, pod3",
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},
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],
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"tools": [
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{
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"tool_name": "get_object_namespace_list",
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"description": "Get the list of objects in a namespace",
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"parameters": {
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"kind": {
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"param_type": "string",
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"description": "the type of object",
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"required": True,
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},
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"namespace": {
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"param_type": "string",
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"description": "the name of the namespace",
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"required": True,
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},
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},
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}
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],
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"tool_choice": "auto",
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"tool_prompt_format": tool_prompt_format,
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"stream": streaming,
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}
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response = llama_stack_client.inference.chat_completion(**request)
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if streaming:
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for chunk in response:
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delta = chunk.event.delta
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if delta.type == "tool_call" and delta.parse_status == "succeeded":
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assert delta.tool_call.tool_name == "get_object_namespace_list"
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if delta.type == "tool_call" and delta.parse_status == "failed":
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# expect raw message that failed to parse in tool_call
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assert type(delta.tool_call) == str
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assert len(delta.tool_call) > 0
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else:
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for tc in response.completion_message.tool_calls:
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assert tc.tool_name == "get_object_namespace_list"
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