def _parse_response_update_from_openai(self, chunk: ChatCompletionChunk) -> ChatResponseUpdate:
    chunk_metadata = self._get_metadata_from_streaming_chat_response(chunk)
    if chunk.usage:
        return ChatResponseUpdate(  # ← Early return!
            role=Role.ASSISTANT,
            contents=[Content.from_usage(...)],
            ...
        )
    # Text parsing below is never reached when usage is present
    contents: list[Content] = []
    for choice in chunk.choices:
        if text_content := self._parse_text_from_openai(choice):
            contents.append(text_content)
    ...

import asyncio
import os
from dotenv import load_dotenv
from agent_framework.openai import OpenAIChatClient

load_dotenv()

async def test_streaming():
    client = OpenAIChatClient(
        model_id="gemini-2.0-flash-lite",
        api_key=os.getenv("GEMINI_API_KEY"),
        base_url="https://generativelanguage.googleapis.com/v1beta/openai/",
    )

    agent = client.as_agent(
        name="test_agent",
        instructions="You are a helpful assistant."
    )

    async for update in agent.run_stream("Count from 1 to 3"):
        print(f"Text: '{update.text}'")  # Always empty!
        print(f"Contents: {update.contents}")  # Only usage

asyncio.run(test_streaming())

def _parse_response_update_from_openai(self, chunk: ChatCompletionChunk) -> ChatResponseUpdate:
    chunk_metadata = self._get_metadata_from_streaming_chat_response(chunk)
    contents: list[Content] = []
    finish_reason: FinishReason | None = None

    # Process usage alongside text (no early return)
    if chunk.usage:
        contents.append(
            Content.from_usage(
                usage_details=self._parse_usage_from_openai(chunk.usage),
                raw_representation=chunk
            )
        )

    # Process text and tool calls
    for choice in chunk.choices:
        chunk_metadata.update(self._get_metadata_from_chat_choice(choice))
        contents.extend(self._parse_tool_calls_from_openai(choice))
        if choice.finish_reason:
            finish_reason = FinishReason(value=choice.finish_reason)
        if text_content := self._parse_text_from_openai(choice):
            contents.append(text_content)
        if reasoning_details := getattr(choice.delta, "reasoning_details", None):
            contents.append(Content.from_text_reasoning(protected_data=json.dumps(reasoning_details)))

    return ChatResponseUpdate(
        created_at=datetime.fromtimestamp(chunk.created, tz=timezone.utc).strftime("%Y-%m-%dT%H:%M:%S.%fZ"),
        contents=contents,
        role=Role.ASSISTANT,
        model_id=chunk.model,
        additional_properties=chunk_metadata,
        finish_reason=finish_reason,
        raw_representation=chunk,
        response_id=chunk.id,
        message_id=chunk.id,
    )