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fix(test): update client-sdk tests to handle tool format parametrization better (#1287)

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# What does this PR do?

Tool format depends on the model. @ehhuang introduced a
`get_default_tool_prompt_format` function for this purpose. We should
use that instead of hacky model ID matching we had before.

Secondly, non llama models don't have this concept so testing with those
models should work as is.

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

## Test Plan

```bash
for distro in fireworks ollama; do
  LLAMA_STACK_CONFIG=$distro \
    pytest -s -v tests/client-sdk/inference/test_text_inference.py \
       --inference-model=meta-llama/Llama-3.2-3B-Instruct \
       --vision-inference-model=""
done

LLAMA_STACK_CONFIG=dev \
   pytest -s -v tests/client-sdk/inference/test_text_inference.py \
       --inference-model=openai/gpt-4o \
       --vision-inference-model=""

```

[//]: # (## Documentation)
This commit is contained in:
Ashwin Bharambe 2025-02-26 21:16:00 -08:00 • committed by GitHub
parent 30ef1c3680
commit 23b65b6cee
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3 changed files with 64 additions and 63 deletions
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52
llama_stack/providers/utils/inference/openai_compat.py
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@ -518,40 +518,44 @@ async def convert_message_to_openai_dict_new(message: Message | Dict) -> OpenAIC
# {"type": "image", "image": {"url": {"uri": ...}}} -> {"type": "image_url", "image_url": {"url": ...}}
# {"type": "image", "image": {"data": ...}} -> {"type": "image_url", "image_url": {"url": "data:image/?;base64,..."}}
# List[...] -> List[...]
async def _convert_user_message_content(
async def _convert_message_content(
content: InterleavedContent,
) -> Union[str, Iterable[OpenAIChatCompletionContentPartParam]]:
# Llama Stack and OpenAI spec match for str and text input
if isinstance(content, str):
return OpenAIChatCompletionContentPartTextParam(
type="text",
text=content,
)
elif isinstance(content, TextContentItem):
return OpenAIChatCompletionContentPartTextParam(
type="text",
text=content.text,
)
elif isinstance(content, ImageContentItem):
return OpenAIChatCompletionContentPartImageParam(
type="image_url",
image_url=OpenAIImageURL(url=await convert_image_content_to_url(content)),
)
elif isinstance(content, List):
return [await _convert_user_message_content(item) for item in content]
async def impl():
# Llama Stack and OpenAI spec match for str and text input
if isinstance(content, str):
return content
elif isinstance(content, TextContentItem):
return OpenAIChatCompletionContentPartTextParam(
type="text",
text=content.text,
)
elif isinstance(content, ImageContentItem):
return OpenAIChatCompletionContentPartImageParam(
type="image_url",
image_url=OpenAIImageURL(url=await convert_image_content_to_url(content)),
)
elif isinstance(content, list):
return [await _convert_message_content(item) for item in content]
else:
raise ValueError(f"Unsupported content type: {type(content)}")
ret = await impl()
if isinstance(ret, str) or isinstance(ret, list):
return ret
else:
raise ValueError(f"Unsupported content type: {type(content)}")
return [ret]
out: OpenAIChatCompletionMessage = None
if isinstance(message, UserMessage):
out = OpenAIChatCompletionUserMessage(
role="user",
content=await _convert_user_message_content(message.content),
content=await _convert_message_content(message.content),
)
elif isinstance(message, CompletionMessage):
out = OpenAIChatCompletionAssistantMessage(
role="assistant",
content=message.content,
content=await _convert_message_content(message.content),
tool_calls=[
OpenAIChatCompletionMessageToolCall(
id=tool.call_id,
@ -568,12 +572,12 @@ async def convert_message_to_openai_dict_new(message: Message | Dict) -> OpenAIC
out = OpenAIChatCompletionToolMessage(
role="tool",
tool_call_id=message.call_id,
content=message.content,
content=await _convert_message_content(message.content),
)
elif isinstance(message, SystemMessage):
out = OpenAIChatCompletionSystemMessage(
role="system",
content=message.content,
content=await _convert_message_content(message.content),
)
else:
raise ValueError(f"Unsupported message type: {type(message)}")