Public helper for recombining ChatCompletionChunks into ChatCompletion

[jackmpcollins]

Confirm this is a feature request for the Python library and not the underlying OpenAI API.

• This is a feature request for the Python library

Describe the feature or improvement you're requesting

After streaming a chat completion response it is often necessary to recombine the streamed chunks into a message. Two examples are

• in the https://github.com/pydantic/logfire observability platform, when a streamed response has ended the final Assistant message could be displayed nicely in the UI.
  • issue: LLM tool call not shown for streamed response pydantic/logfire#542
• in https://github.com/jackmpcollins/magentic , parallel tool calls are streamed to call these during the generation, and inserting the outputs back into messages requires also creating an Assistant message from the streamed chunks.

Currently the internal class ChatCompletionStreamState makes this easy, but it is private which indicates it should not be relied on. Would it be possible to make this or similar functionality a supported part of the public API?

The current feature set of ChatCompletionStreamState is ideal:

• get a ChatCompletion at any point during the stream (current_completion_snapshot). This allows logging a partial stream response in case of error, including if max_tokens was reached.
• parse the chunks into correct pydantic BaseModels for the tools/response_format (get_final_completion())

Example usage of the existing class

import openai
from openai.lib.streaming.chat._completions import ChatCompletionStreamState

state = ChatCompletionStreamState(
    input_tools=openai.NOT_GIVEN,
    response_format=openai.NOT_GIVEN,
)

response = client.chat.completions.create(...)
for chunk in response:
    state.handle_chunk(chunk)

print(state.current_completion_snapshot)
print(state.get_final_completion())

Additional context

No response

[RobertCraigie]

Thanks for the suggestion, I think this is a good idea!