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https://github.com/bytedance/deer-flow.git
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feat: enhance chat history loading with new hooks and UI components (#2338)
* Refactor API fetch calls to use a unified fetch function; enhance chat history loading with new hooks and UI components - Replaced `fetchWithAuth` with a generic `fetch` function across various API modules for consistency. - Updated `useThreadStream` and `useThreadHistory` hooks to manage chat history loading, including loading states and pagination. - Introduced `LoadMoreHistoryIndicator` component for better user experience when loading more chat history. - Enhanced message handling in `MessageList` to accommodate new loading states and history management. - Added support for run messages in the thread context, improving the overall message handling logic. - Updated translations for loading indicators in English and Chinese. * Fix test assertions for run ordering in RunManager tests - Updated assertions in `test_list_by_thread` to reflect correct ordering of runs. - Modified `test_list_by_thread_is_stable_when_timestamps_tie` to ensure stable ordering when timestamps are tied.
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@@ -5,11 +5,11 @@ from __future__ import annotations
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import logging
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from collections.abc import Collection
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from dataclasses import dataclass
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from typing import Any, Protocol, runtime_checkable
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from typing import Any, Protocol, override, runtime_checkable
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from langchain.agents import AgentState
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from langchain.agents.middleware import SummarizationMiddleware
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from langchain_core.messages import AIMessage, AnyMessage, RemoveMessage, ToolMessage
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from langchain_core.messages import AIMessage, AnyMessage, HumanMessage, RemoveMessage, ToolMessage
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from langgraph.config import get_config
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from langgraph.graph.message import REMOVE_ALL_MESSAGES
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from langgraph.runtime import Runtime
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@@ -173,6 +173,13 @@ class DeerFlowSummarizationMiddleware(SummarizationMiddleware):
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]
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}
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@override
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def _build_new_messages(self, summary: str) -> list[HumanMessage]:
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"""Override the base implementation to let the human message with the special name 'summary'.
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And this message will be ignored to display in the frontend, but still can be used as context for the model.
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"""
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return [HumanMessage(content=f"Here is a summary of the conversation to date:\n\n{summary}", name="summary")]
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def _partition_with_skill_rescue(
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self,
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messages: list[AnyMessage],
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