fix(agent): preserve Codex message items for replay
This commit is contained in:
@@ -227,6 +227,23 @@ def _responses_tools(tools: Optional[List[Dict[str, Any]]] = None) -> Optional[L
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# Message format conversion
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# ---------------------------------------------------------------------------
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_RESPONSE_MESSAGE_STATUSES = {"completed", "incomplete", "in_progress"}
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def _normalize_responses_message_status(value: Any, *, default: str = "completed") -> str:
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"""Normalize a Responses assistant message status for replay.
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The API accepts completed/incomplete/in_progress on replayed assistant
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output messages. Preserve those exactly (modulo case/hyphen spelling) so
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incomplete Codex continuation turns don't get falsely marked completed.
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"""
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if isinstance(value, str):
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status = value.strip().lower().replace("-", "_").replace(" ", "_")
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if status in _RESPONSE_MESSAGE_STATUSES:
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return status
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return default
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def _chat_messages_to_responses_input(messages: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
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"""Convert internal chat-style messages to Responses input items."""
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items: List[Dict[str, Any]] = []
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@@ -272,7 +289,57 @@ def _chat_messages_to_responses_input(messages: List[Dict[str, Any]]) -> List[Di
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seen_item_ids.add(item_id)
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has_codex_reasoning = True
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if content_parts:
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# Replay exact assistant message items (with id/phase) from
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# previous turns so the API can maintain prefix-cache hits.
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# OpenAI docs: "preserve and resend phase on all assistant
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# messages — dropping it can degrade performance."
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codex_message_items = msg.get("codex_message_items")
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replayed_message_items = 0
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if isinstance(codex_message_items, list):
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for raw_item in codex_message_items:
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if not isinstance(raw_item, dict):
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continue
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if raw_item.get("type") != "message" or raw_item.get("role") != "assistant":
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continue
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raw_content_parts = raw_item.get("content")
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if not isinstance(raw_content_parts, list):
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continue
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normalized_content_parts = []
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for part in raw_content_parts:
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if not isinstance(part, dict):
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continue
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part_type = str(part.get("type") or "").strip()
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if part_type not in {"output_text", "text"}:
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continue
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text = part.get("text", "")
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if text is None:
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text = ""
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if not isinstance(text, str):
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text = str(text)
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normalized_content_parts.append({"type": "output_text", "text": text})
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if not normalized_content_parts:
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continue
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replay_item = {
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"type": "message",
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"role": "assistant",
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"status": _normalize_responses_message_status(raw_item.get("status")),
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"content": normalized_content_parts,
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}
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item_id = raw_item.get("id")
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if isinstance(item_id, str) and item_id.strip():
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replay_item["id"] = item_id.strip()
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phase = raw_item.get("phase")
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if isinstance(phase, str) and phase.strip():
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replay_item["phase"] = phase.strip()
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items.append(replay_item)
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replayed_message_items += 1
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if replayed_message_items > 0:
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pass
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elif content_parts:
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items.append({"role": "assistant", "content": content_parts})
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elif content_text.strip():
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items.append({"role": "assistant", "content": content_text})
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@@ -432,6 +499,47 @@ def _preflight_codex_input_items(raw_items: Any) -> List[Dict[str, Any]]:
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normalized.append(reasoning_item)
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continue
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if item_type == "message":
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role = item.get("role")
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if role != "assistant":
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raise ValueError(f"Codex Responses input[{idx}] message items must have role='assistant'.")
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content = item.get("content")
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if not isinstance(content, list):
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raise ValueError(f"Codex Responses input[{idx}] message item must have content list.")
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normalized_content = []
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for part_idx, part in enumerate(content):
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if not isinstance(part, dict):
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raise ValueError(
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f"Codex Responses input[{idx}] message content[{part_idx}] must be an object."
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)
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part_type = part.get("type")
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if part_type not in {"output_text", "text"}:
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raise ValueError(
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f"Codex Responses input[{idx}] message content[{part_idx}] has unsupported type {part_type!r}."
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)
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text = part.get("text", "")
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if text is None:
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text = ""
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if not isinstance(text, str):
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text = str(text)
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normalized_content.append({"type": "output_text", "text": text})
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if not normalized_content:
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raise ValueError(f"Codex Responses input[{idx}] message item must contain at least one text part.")
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normalized_item: Dict[str, Any] = {
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"type": "message",
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"role": "assistant",
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"status": _normalize_responses_message_status(item.get("status")),
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"content": normalized_content,
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}
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item_id = item.get("id")
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if isinstance(item_id, str) and item_id.strip():
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normalized_item["id"] = item_id.strip()
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phase = item.get("phase")
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if isinstance(phase, str) and phase.strip():
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normalized_item["phase"] = phase.strip()
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normalized.append(normalized_item)
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continue
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role = item.get("role")
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if role in {"user", "assistant"}:
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content = item.get("content", "")
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@@ -716,6 +824,7 @@ def _normalize_codex_response(response: Any) -> tuple[Any, str]:
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content_parts: List[str] = []
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reasoning_parts: List[str] = []
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reasoning_items_raw: List[Dict[str, Any]] = []
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message_items_raw: List[Dict[str, Any]] = []
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tool_calls: List[Any] = []
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has_incomplete_items = response_status in {"queued", "in_progress", "incomplete"}
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saw_commentary_phase = False
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@@ -734,6 +843,7 @@ def _normalize_codex_response(response: Any) -> tuple[Any, str]:
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if item_type == "message":
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item_phase = getattr(item, "phase", None)
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normalized_phase = None
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if isinstance(item_phase, str):
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normalized_phase = item_phase.strip().lower()
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if normalized_phase in {"commentary", "analysis"}:
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@@ -743,6 +853,18 @@ def _normalize_codex_response(response: Any) -> tuple[Any, str]:
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message_text = _extract_responses_message_text(item)
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if message_text:
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content_parts.append(message_text)
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raw_message_item: Dict[str, Any] = {
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"type": "message",
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"role": "assistant",
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"status": _normalize_responses_message_status(item_status),
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"content": [{"type": "output_text", "text": message_text}],
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}
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item_id = getattr(item, "id", None)
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if isinstance(item_id, str) and item_id:
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raw_message_item["id"] = item_id
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if normalized_phase:
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raw_message_item["phase"] = normalized_phase
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message_items_raw.append(raw_message_item)
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elif item_type == "reasoning":
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reasoning_text = _extract_responses_reasoning_text(item)
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if reasoning_text:
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@@ -855,6 +977,7 @@ def _normalize_codex_response(response: Any) -> tuple[Any, str]:
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reasoning_content=None,
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reasoning_details=None,
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codex_reasoning_items=reasoning_items_raw or None,
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codex_message_items=message_items_raw or None,
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)
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if tool_calls:
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@@ -23,9 +23,14 @@ def get_transport(api_mode: str):
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This allows gradual migration — call sites can check for None
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and fall back to the legacy code path.
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"""
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if not _REGISTRY:
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_discover_transports()
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cls = _REGISTRY.get(api_mode)
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if cls is None:
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# The registry can be partially populated when a specific transport
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# module was imported directly (for example chat_completions before
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# codex). Discover on misses, not only when the registry is empty, so
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# test/order-dependent imports do not make valid api_modes unavailable.
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_discover_transports()
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cls = _REGISTRY.get(api_mode)
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if cls is None:
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return None
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return cls()
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@@ -31,15 +31,15 @@ class ChatCompletionsTransport(ProviderTransport):
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def convert_messages(self, messages: List[Dict[str, Any]], **kwargs) -> List[Dict[str, Any]]:
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"""Messages are already in OpenAI format — sanitize Codex leaks only.
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Strips Codex Responses API fields (``codex_reasoning_items`` on the
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message, ``call_id``/``response_item_id`` on tool_calls) that strict
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chat-completions providers reject with 400/422.
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Strips Codex Responses API fields (``codex_reasoning_items`` /
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``codex_message_items`` on the message, ``call_id``/``response_item_id``
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on tool_calls) that strict chat-completions providers reject with 400/422.
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"""
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needs_sanitize = False
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for msg in messages:
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if not isinstance(msg, dict):
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continue
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if "codex_reasoning_items" in msg:
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if "codex_reasoning_items" in msg or "codex_message_items" in msg:
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needs_sanitize = True
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break
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tool_calls = msg.get("tool_calls")
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@@ -59,6 +59,7 @@ class ChatCompletionsTransport(ProviderTransport):
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if not isinstance(msg, dict):
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continue
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msg.pop("codex_reasoning_items", None)
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msg.pop("codex_message_items", None)
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tool_calls = msg.get("tool_calls")
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if isinstance(tool_calls, list):
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for tc in tool_calls:
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@@ -120,6 +120,24 @@ class ResponsesApiTransport(ProviderTransport):
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if request_overrides:
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kwargs.update(request_overrides)
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if is_codex_backend:
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prompt_cache_key = kwargs.get("prompt_cache_key")
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cache_scope_id = str(prompt_cache_key or session_id or "").strip()
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if cache_scope_id:
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existing_extra_headers = kwargs.get("extra_headers")
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merged_extra_headers: Dict[str, str] = {}
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if isinstance(existing_extra_headers, dict):
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merged_extra_headers.update(
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{
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str(key): str(value)
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for key, value in existing_extra_headers.items()
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if key and value is not None
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}
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)
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merged_extra_headers["session_id"] = cache_scope_id
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merged_extra_headers["x-client-request-id"] = cache_scope_id
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kwargs["extra_headers"] = merged_extra_headers
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max_tokens = params.get("max_tokens")
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if max_tokens is not None and not is_codex_backend:
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kwargs["max_output_tokens"] = max_tokens
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@@ -160,6 +178,8 @@ class ResponsesApiTransport(ProviderTransport):
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provider_data = {}
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if msg and hasattr(msg, "codex_reasoning_items") and msg.codex_reasoning_items:
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provider_data["codex_reasoning_items"] = msg.codex_reasoning_items
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if msg and hasattr(msg, "codex_message_items") and msg.codex_message_items:
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provider_data["codex_message_items"] = msg.codex_message_items
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if msg and hasattr(msg, "reasoning_details") and msg.reasoning_details:
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provider_data["reasoning_details"] = msg.reasoning_details
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@@ -97,7 +97,7 @@ class NormalizedResponse:
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Response-level ``provider_data`` examples:
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* Anthropic: ``{"reasoning_details": [...]}``
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* Codex: ``{"codex_reasoning_items": [...]}``
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* Codex: ``{"codex_reasoning_items": [...], "codex_message_items": [...]}``
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* Others: ``None``
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"""
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@@ -126,6 +126,11 @@ class NormalizedResponse:
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pd = self.provider_data or {}
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return pd.get("codex_reasoning_items")
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@property
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def codex_message_items(self):
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pd = self.provider_data or {}
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return pd.get("codex_message_items")
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# ---------------------------------------------------------------------------
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# Factory helpers
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