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https://github.com/bytedance/deer-flow.git
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e89b128157
* fix(models): preserve DeepSeek thinking tool history * fix(runtime): harden model response recovery * fix(runtime): tighten model response recovery * fix(runtime): protect run-scoped retry state * fix(runtime): complete model recovery review fixes * fix(runtime): preserve empty-response diagnostics * fix(runtime): strip native tool calls on length caps * docs(middleware): fit recovery guidance within inherited size limit --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
103 lines
3.9 KiB
Python
103 lines
3.9 KiB
Python
"""Patched ChatDeepSeek that preserves reasoning_content in multi-turn conversations.
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This module provides a patched version of ChatDeepSeek that properly handles
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reasoning_content when sending messages back to the API. The original implementation
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stores reasoning_content in additional_kwargs but doesn't include it when making
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subsequent API calls, which causes errors with APIs that require reasoning_content
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on all assistant messages when thinking mode is enabled.
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"""
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from typing import Any
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from langchain_core.language_models import LanguageModelInput
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from langchain_core.messages import AIMessage
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from langchain_deepseek import ChatDeepSeek
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from deerflow.models.assistant_payload_replay import restore_assistant_payloads, restore_reasoning_content
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def _thinking_enabled(*sources: Any) -> bool:
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"""Return whether the request explicitly enables DeepSeek thinking mode."""
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for source in sources:
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if not isinstance(source, dict):
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continue
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thinking = source.get("thinking")
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if isinstance(thinking, dict) and thinking.get("type") == "enabled":
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return True
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extra_body = source.get("extra_body")
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if isinstance(extra_body, dict):
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nested = extra_body.get("thinking")
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if isinstance(nested, dict) and nested.get("type") == "enabled":
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return True
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return False
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def _restore_deepseek_assistant_payload(
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payload_msg: dict[str, Any],
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orig_msg: AIMessage,
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*,
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thinking_enabled: bool,
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) -> None:
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"""Restore assistant history and required thinking-mode placeholders."""
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restore_reasoning_content(payload_msg, orig_msg)
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has_tool_calls = bool(payload_msg.get("tool_calls"))
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if has_tool_calls and payload_msg.get("content") is None:
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# DeepSeek requires an empty string, rather than null, for tool-call history.
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payload_msg["content"] = ""
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if thinking_enabled and has_tool_calls and "reasoning_content" not in payload_msg:
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# Thinking-mode tool turns require this field even when no reasoning was emitted.
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payload_msg["reasoning_content"] = ""
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class PatchedChatDeepSeek(ChatDeepSeek):
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"""ChatDeepSeek with proper reasoning_content preservation.
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When using thinking/reasoning enabled models, the API expects reasoning_content
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to be present on ALL assistant messages in multi-turn conversations. This patched
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version ensures reasoning_content from additional_kwargs is included in the
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request payload.
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"""
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@classmethod
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def is_lc_serializable(cls) -> bool:
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return True
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@property
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def lc_secrets(self) -> dict[str, str]:
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return {"api_key": "DEEPSEEK_API_KEY", "openai_api_key": "DEEPSEEK_API_KEY"}
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def _get_request_payload(
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self,
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input_: LanguageModelInput,
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*,
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stop: list[str] | None = None,
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**kwargs: Any,
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) -> dict:
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"""Get request payload with reasoning_content preserved.
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Overrides the parent method to inject reasoning_content from
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additional_kwargs into assistant messages in the payload.
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"""
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original_messages = self._convert_input(input_).to_messages()
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request_messages = [message for message in original_messages if not (isinstance(message, AIMessage) and (message.additional_kwargs or {}).get("deerflow_error_fallback"))]
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# Call parent to get the base payload
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payload = super()._get_request_payload(request_messages, stop=stop, **kwargs)
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request_thinking_enabled = _thinking_enabled(
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payload,
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kwargs,
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{"extra_body": getattr(self, "extra_body", None)},
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)
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restore_assistant_payloads(
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payload.get("messages", []),
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request_messages,
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lambda payload_msg, orig_msg: _restore_deepseek_assistant_payload(
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payload_msg,
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orig_msg,
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thinking_enabled=request_thinking_enabled,
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),
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)
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return payload
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