[Bug] Fix gpt-oss missing tool content

[levunet]

Purpose

This PR requires the following PRs to be merged first: #24768 and the harmony lib PR (openai/harmony#76).

The changes include adding 'with_recipient' and the Assistant's 'analysis' content.
Without adding this content, there was an issue where the gpt-oss model had a higher probability of outputting abnormal tokens when calling tools.

Test Plan

gpt-oss_test.py
messages.txt

Run python3 gpt-oss_test.py about 10 times.

Test Result

(before)

(after applying the harmony lib changes)

[gemini-code-assist]

Code Review

This pull request aims to fix a bug in gpt-oss model tool calls by adding 'analysis' content and with_recipient. The changes are logical and align with the stated purpose. However, I've identified a high-severity issue where the handling of 'analysis' content is not robust for multimodal inputs, which could lead to a runtime crash. I have provided a code suggestion to address this.

[gemini-code-assist]

The logic to extract content is not robust. The content of an assistant message can be a list of parts (e.g., for multimodal inputs), not just a string. The current implementation content = chat_msg.get("content") or "" will cause a runtime error if content is a non-empty list, as Message.from_role_and_content expects a string. The code should handle the case where content is a list by extracting the text parts, similar to how it's handled for other message types in this file.

        content = chat_msg.get("content")
        if isinstance(content, list):
            # Extract text from multimodal content
            content = "\n".join(
                p.get("text", "") for p in content
                if isinstance(p, dict) and p.get("type") == "text")
        elif not isinstance(content, str):
            content = ""

        analysis_msg = Message.from_role_and_content(Role.ASSISTANT, content)
        analysis_msg = analysis_msg.with_channel("analysis")
        msgs.append(analysis_msg)

[levunet]

@alecsolder
In the harmony library, the ' to' value should have been encoded as id 316, but occasionally it was incorrectly encoded as a mixture of 220+935 id values, which caused the model to output incorrect tokens.

[alecsolder]

In your test script, I see you're using the streaming completions endpoint, which I don't think uses the harmony_utils method you modified? I just want to double check I'm reading it right

[alecsolder]

Also, thanks for mentioning that huggingface tokenizer change, I hadn't seen it and my snapshot was out of date!

[levunet]

Thank you for checking. I've double-checked the part you mentioned.
I can confirm that the parse_chat_input I modified in the harmony_utils.py file is being used without any issues through the flow: /v1/chat/completions -> def create_chat_completion -> def _make_request_with_harmony -> def parse_chat_input to parse request.messages.
The streaming endpoint is also correctly using this modified method.