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fix(provider): preserve streamed Codex output when response.completed.output is empty (#1928)
* fix: preserve streamed Codex output items * fix: prefer completed Codex output over streamed placeholders
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@ -216,18 +216,48 @@ class CodexChatModel(BaseChatModel):
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def _stream_response(self, headers: dict, payload: dict) -> dict:
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"""Stream SSE from Codex API and collect the final response."""
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completed_response = None
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streamed_output_items: dict[int, dict[str, Any]] = {}
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with httpx.Client(timeout=300) as client:
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with client.stream("POST", f"{CODEX_BASE_URL}/responses", headers=headers, json=payload) as resp:
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resp.raise_for_status()
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for line in resp.iter_lines():
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data = self._parse_sse_data_line(line)
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if data and data.get("type") == "response.completed":
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if not data:
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continue
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event_type = data.get("type")
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if event_type == "response.output_item.done":
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output_index = data.get("output_index")
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output_item = data.get("item")
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if isinstance(output_index, int) and isinstance(output_item, dict):
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streamed_output_items[output_index] = output_item
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elif event_type == "response.completed":
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completed_response = data["response"]
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if not completed_response:
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raise RuntimeError("Codex API stream ended without response.completed event")
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# ChatGPT Codex can emit the final assistant content only in stream events.
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# When response.completed arrives, response.output may still be empty.
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if streamed_output_items:
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merged_output = []
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response_output = completed_response.get("output")
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if isinstance(response_output, list):
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merged_output = list(response_output)
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max_index = max(max(streamed_output_items), len(merged_output) - 1)
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if max_index >= 0 and len(merged_output) <= max_index:
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merged_output.extend([None] * (max_index + 1 - len(merged_output)))
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for output_index, output_item in streamed_output_items.items():
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existing_item = merged_output[output_index]
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if not isinstance(existing_item, dict):
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merged_output[output_index] = output_item
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completed_response = dict(completed_response)
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completed_response["output"] = [item for item in merged_output if isinstance(item, dict)]
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return completed_response
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@staticmethod
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@ -5,6 +5,7 @@ import json
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import pytest
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from langchain_core.messages import HumanMessage, SystemMessage
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from deerflow.models import openai_codex_provider as codex_provider_module
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from deerflow.models.claude_provider import ClaudeChatModel
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from deerflow.models.credential_loader import CodexCliCredential
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from deerflow.models.openai_codex_provider import CodexChatModel
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@ -147,3 +148,124 @@ def test_codex_provider_parses_valid_tool_arguments(monkeypatch):
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)
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assert result.generations[0].message.tool_calls == [{"name": "bash", "args": {"cmd": "pwd"}, "id": "tc-1", "type": "tool_call"}]
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class _FakeResponseStream:
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def __init__(self, lines: list[str]):
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self._lines = lines
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def __enter__(self):
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return self
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def __exit__(self, exc_type, exc, tb):
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return False
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def raise_for_status(self):
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return None
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def iter_lines(self):
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yield from self._lines
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class _FakeHttpxClient:
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def __init__(self, lines: list[str], *_args, **_kwargs):
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self._lines = lines
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def __enter__(self):
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return self
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def __exit__(self, exc_type, exc, tb):
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return False
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def stream(self, *_args, **_kwargs):
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return _FakeResponseStream(self._lines)
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def test_codex_provider_merges_streamed_output_items_when_completed_output_is_empty(monkeypatch):
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monkeypatch.setattr(
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CodexChatModel,
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"_load_codex_auth",
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lambda self: CodexCliCredential(access_token="token", account_id="acct"),
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)
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lines = [
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'data: {"type":"response.output_item.done","output_index":0,"item":{"type":"message","content":[{"type":"output_text","text":"Hello from stream"}]}}',
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'data: {"type":"response.completed","response":{"model":"gpt-5.4","output":[],"usage":{"input_tokens":1,"output_tokens":2,"total_tokens":3}}}',
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]
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monkeypatch.setattr(
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codex_provider_module.httpx,
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"Client",
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lambda *args, **kwargs: _FakeHttpxClient(lines, *args, **kwargs),
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)
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model = CodexChatModel()
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response = model._stream_response(headers={}, payload={})
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parsed = model._parse_response(response)
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assert response["output"] == [
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{
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"type": "message",
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"content": [{"type": "output_text", "text": "Hello from stream"}],
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}
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]
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assert parsed.generations[0].message.content == "Hello from stream"
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def test_codex_provider_orders_streamed_output_items_by_output_index(monkeypatch):
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monkeypatch.setattr(
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CodexChatModel,
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"_load_codex_auth",
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lambda self: CodexCliCredential(access_token="token", account_id="acct"),
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)
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lines = [
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'data: {"type":"response.output_item.done","output_index":1,"item":{"type":"message","content":[{"type":"output_text","text":"Second"}]}}',
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'data: {"type":"response.output_item.done","output_index":0,"item":{"type":"message","content":[{"type":"output_text","text":"First"}]}}',
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'data: {"type":"response.completed","response":{"model":"gpt-5.4","output":[],"usage":{}}}',
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]
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monkeypatch.setattr(
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codex_provider_module.httpx,
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"Client",
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lambda *args, **kwargs: _FakeHttpxClient(lines, *args, **kwargs),
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)
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model = CodexChatModel()
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response = model._stream_response(headers={}, payload={})
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assert [item["content"][0]["text"] for item in response["output"]] == [
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"First",
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"Second",
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]
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def test_codex_provider_preserves_completed_output_when_stream_only_has_placeholder(monkeypatch):
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monkeypatch.setattr(
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CodexChatModel,
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"_load_codex_auth",
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lambda self: CodexCliCredential(access_token="token", account_id="acct"),
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)
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lines = [
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'data: {"type":"response.output_item.added","output_index":0,"item":{"type":"message","status":"in_progress","content":[]}}',
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'data: {"type":"response.completed","response":{"model":"gpt-5.4","output":[{"type":"message","content":[{"type":"output_text","text":"Final from completed"}]}],"usage":{}}}',
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]
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monkeypatch.setattr(
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codex_provider_module.httpx,
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"Client",
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lambda *args, **kwargs: _FakeHttpxClient(lines, *args, **kwargs),
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)
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model = CodexChatModel()
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response = model._stream_response(headers={}, payload={})
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parsed = model._parse_response(response)
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assert response["output"] == [
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{
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"type": "message",
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"content": [{"type": "output_text", "text": "Final from completed"}],
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}
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]
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assert parsed.generations[0].message.content == "Final from completed"
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