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_openai.py

@@ -27,6 +27,8 @@ from langchain_core.language_models import LanguageModelInput
 from langchain_core.messages import AIMessage
 from langchain_openai import ChatOpenAI
 
+from deerflow.models.assistant_payload_replay import restore_assistant_payloads
+
 
 class PatchedChatOpenAI(ChatOpenAI):
     """ChatOpenAI with ``thought_signature`` preservation for Gemini thinking via OpenAI gateway.
@@ -75,18 +77,7 @@ class PatchedChatOpenAI(ChatOpenAI):
         # Obtain the base payload from the parent implementation.
         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_tool_call_signatures(payload_msg, orig_msg)
-        else:
-            # Fallback: match assistant-role entries positionally against AIMessages.
-            ai_messages = [m for m in original_messages if isinstance(m, AIMessage)]
-            assistant_payloads = [(i, m) for i, m in enumerate(payload_messages) if m.get("role") == "assistant"]
-            for (_, payload_msg), ai_msg in zip(assistant_payloads, ai_messages):
-                _restore_tool_call_signatures(payload_msg, ai_msg)
+        restore_assistant_payloads(payload.get("messages", []), original_messages, _restore_tool_call_signatures)
 
         return payload