refactor(provider): share assistant payload replay matching (#3307)

* Share assistant payload replay matching

* fix(provider): recover assistant field when ordinal AI index is taken

The mismatch-length fallback in `_match_ai_message` only tried the exact
`fallback_ordinal` AI index. When serialization drops or reorders an
assistant message, a unique signature match can consume a non-ordinal
index, leaving a later ambiguous payload's ordinal already used — so its
provider field (e.g. `reasoning_content`) was silently dropped.

Scan forward from the ordinal for the next unused `AIMessage` (wrapping to
earlier indices) to preserve the positional bias while still recovering
the field. Forward scanning avoids a naive min-unused pick that could
restore the wrong field after a leading message is dropped.

Add a regression test for the dropped-leading-message case.

* fix(provider): avoid earlier assistant fallback replay

backend/packages/harness/deerflow/models/patched_mimo.py

@@ -17,6 +17,8 @@ from langchain_core.messages import AIMessage, AIMessageChunk
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
 from langchain_openai import ChatOpenAI
 
+from deerflow.models.assistant_payload_replay import restore_assistant_payloads, restore_reasoning_content
+
 _MISSING = object()
 
 
@@ -45,12 +47,6 @@ def _with_reasoning_content(message: AIMessage | AIMessageChunk, reasoning: str)
     return message.model_copy(update={"additional_kwargs": additional_kwargs})
 
 
-def _restore_reasoning_content(payload_msg: dict, orig_msg: AIMessage) -> None:
-    reasoning = orig_msg.additional_kwargs.get("reasoning_content")
-    if reasoning is not None:
-        payload_msg["reasoning_content"] = reasoning
-
-
 def _get_typed_choice_message(response: Any, index: int) -> Any:
     choices = getattr(response, "choices", None)
     if choices is None:
@@ -81,17 +77,11 @@ class PatchedChatMiMo(ChatOpenAI):
     ) -> dict:
         original_messages = self._convert_input(input_).to_messages()
         payload = super()._get_request_payload(input_, stop=stop, **kwargs)
-        payload_messages = payload.get("messages", [])
-
-        if len(payload_messages) == len(original_messages):
-            for payload_msg, orig_msg in zip(payload_messages, original_messages):
-                if payload_msg.get("role") == "assistant" and isinstance(orig_msg, AIMessage):
-                    _restore_reasoning_content(payload_msg, orig_msg)
-        else:
-            ai_messages = [m for m in original_messages if isinstance(m, AIMessage)]
-            assistant_payloads = [m for m in payload_messages if m.get("role") == "assistant"]
-            for payload_msg, ai_msg in zip(assistant_payloads, ai_messages):
-                _restore_reasoning_content(payload_msg, ai_msg)
+        restore_assistant_payloads(
+            payload.get("messages", []),
+            original_messages,
+            restore_reasoning_content,
+        )
 
         return payload