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@@ -244,6 +244,11 @@ const TERMINAL_RUN_STATUSES = new Set([
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// for a while, then reconcile it from the authoritative run/state endpoints.
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const STREAM_RECONCILIATION_IDLE_MS = 12_000;
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const STREAM_RECONCILIATION_POLL_MS = 5_000;
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// A run can legitimately be quiet while a long tool call is in progress, so
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// reconnect more conservatively than the terminal-status check above. The
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// reconnection only replaces the local SSE reader; the backend run keeps going.
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const STREAM_RECONNECT_IDLE_MS = 30_000;
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const STREAM_RECONNECT_MAX_ATTEMPTS = 3;
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async function fetchThreadTitleRefreshState(
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threadId: string,
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@@ -466,9 +471,15 @@ export function useThreadStream({
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const startedRef = useRef(false);
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const lastStreamActivityAtRef = useRef(0);
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const streamReconciliationInFlightRef = useRef(false);
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const streamReconnectAttemptsRef = useRef(0);
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const streamReconnectToastShownRef = useRef(false);
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const streamReconnectFailureToastShownRef = useRef(false);
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const markStreamActivity = useCallback(() => {
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lastStreamActivityAtRef.current = Date.now();
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streamReconnectAttemptsRef.current = 0;
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streamReconnectToastShownRef.current = false;
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streamReconnectFailureToastShownRef.current = false;
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}, []);
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const listeners = useRef({
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@@ -761,13 +772,6 @@ export function useThreadStream({
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threadStreamRef.current = thread;
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useEffect(() => {
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if (!thread.isLoading) {
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// A normal terminal event reached the browser. A later run may use the
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// same thread, so it must be eligible for recovery again.
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streamReconciliationInFlightRef.current = false;
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return;
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}
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const activeThreadId = threadIdRef.current ?? onStreamThreadId ?? null;
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if (!activeThreadId || typeof window === "undefined") {
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return;
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@@ -776,7 +780,7 @@ export function useThreadStream({
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let disposed = false;
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let refreshTimer: number | null = null;
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const reconcileCompletedRun = async () => {
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const reconcileRun = async () => {
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if (
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disposed ||
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streamReconciliationInFlightRef.current ||
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@@ -793,7 +797,51 @@ export function useThreadStream({
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try {
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const client = getAPIClient(isMock);
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const run = await client.runs.get(activeThreadId, runId);
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if (disposed || !TERMINAL_RUN_STATUSES.has(run.status)) {
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if (disposed) {
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return;
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}
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if (!TERMINAL_RUN_STATUSES.has(run.status)) {
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// ``useStream`` retries one failed connection on its own. If that
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// reader quietly stalls, however, its internal queue never gets a
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// terminal error and the page remains frozen despite the backend
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// continuing the run. Abort only the local reader, then join the
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// same run so no work or tokens are lost server-side.
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if (Date.now() - lastStreamActivityAtRef.current < STREAM_RECONNECT_IDLE_MS) {
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return;
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}
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if (streamReconnectAttemptsRef.current >= STREAM_RECONNECT_MAX_ATTEMPTS) {
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if (!streamReconnectFailureToastShownRef.current) {
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streamReconnectFailureToastShownRef.current = true;
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toast.error("回答仍在后台处理中,但页面连接暂未恢复;请稍后返回此会话查看结果。");
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}
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return;
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}
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streamReconnectAttemptsRef.current += 1;
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// Avoid enqueueing another reconnect before this new reader has had
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// enough time to receive its first event. A genuine event resets
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// the attempt counter through ``markStreamActivity``.
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lastStreamActivityAtRef.current = Date.now();
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if (!streamReconnectToastShownRef.current) {
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streamReconnectToastShownRef.current = true;
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toast.info("回答连接出现波动,正在自动恢复…");
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}
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const stream = threadStreamRef.current;
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void Promise.resolve(stream.stop())
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.catch(() => {
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// Stopping a stale local reader is best-effort; joining is still
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// useful if the SDK already considers the stream stopped.
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})
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.finally(() => {
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if (disposed || threadIdRef.current !== activeThreadId) return;
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void stream.joinStream(runId).catch(() => {
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// The status poll will either reconcile a terminal run or
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// schedule the next bounded reconnect attempt.
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});
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});
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return;
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}
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@@ -801,13 +849,17 @@ export function useThreadStream({
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// receive any more useful events. Load the checkpoint directly before
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// resetting the SDK stream; this preserves the normal onFinish side
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// effects (e.g. marking a position delivery complete) even when the
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// browser missed the terminal event.
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// browser missed the terminal event or already reported a transport
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// error and dropped ``isLoading``.
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const finalState = await client.threads.getState(activeThreadId);
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if (disposed || !threadStreamRef.current.isLoading) {
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if (disposed) {
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return;
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}
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storage?.removeItem(`lg:stream:${activeThreadId}`);
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streamReconnectAttemptsRef.current = 0;
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streamReconnectToastShownRef.current = false;
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streamReconnectFailureToastShownRef.current = false;
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if (run.status === "success") {
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listeners.current.onFinish?.(finalState.values as AgentThreadState);
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void queryClient.invalidateQueries({ queryKey: ["threads", "search"] });
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@@ -836,7 +888,7 @@ export function useThreadStream({
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};
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const interval = window.setInterval(
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() => void reconcileCompletedRun(),
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() => void reconcileRun(),
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STREAM_RECONCILIATION_POLL_MS,
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);
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@@ -64,3 +64,6 @@ ROUNDTABLE_JOB_GATEWAY=inprocess
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DEEPSEEK_CHAT_API_KEY=sk-686b7bc000be4b7cbed6dccb3897c411
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GLM5_FP8_API_KEY=modalresearch_gWu46FDpVLYZWPVEA3b_2fq8Jw2UJiKMgEm_Rxmn1SA
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SILICONFLOW_API_KEY=sk-ighylafootabtuthwueirmoycccyqtdgbifyhozduvolkdyt
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# WeKnora admin credentials (DeerFlow server-side iframe SSO proxy)
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WEKNORA_ADMIN_PASSWORD=1qaz@WSX
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+157
-65
@@ -15,10 +15,10 @@ internal checkpoint callbacks that are not exposed in the Python public API.
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from __future__ import annotations
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import asyncio
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import copy
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import inspect
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import logging
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import asyncio
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import copy
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import inspect
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import logging
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from dataclasses import dataclass, field
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from functools import lru_cache
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from typing import TYPE_CHECKING, Any, Literal, cast
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@@ -28,31 +28,31 @@ from langgraph.checkpoint.base import empty_checkpoint
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if TYPE_CHECKING:
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from langchain_core.messages import HumanMessage
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from deerflow.agents.middlewares.title_middleware import (
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finalize_thread_title,
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log_title_debug,
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)
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from deerflow.config.app_config import AppConfig
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from deerflow.runtime.serialization import serialize
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from deerflow.runtime.stream_bridge import StreamBridge
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from deerflow.agents.middlewares.title_middleware import (
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finalize_thread_title,
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log_title_debug,
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)
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from deerflow.config.app_config import AppConfig
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from deerflow.runtime.serialization import serialize
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from deerflow.runtime.stream_bridge import StreamBridge
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from .manager import RunManager, RunRecord
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from .schemas import RunStatus
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logger = logging.getLogger(__name__)
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logger = logging.getLogger(__name__)
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# Valid stream_mode values for LangGraph's graph.astream()
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_VALID_LG_MODES = {"values", "updates", "checkpoints", "tasks", "debug", "messages", "custom"}
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def _log_background_title_finalize_failure(thread_id: str):
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def _done(task: asyncio.Task[bool]) -> None:
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try:
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task.result()
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except Exception:
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logger.debug("Failed to finalize background title for thread %s", thread_id, exc_info=True)
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return _done
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_VALID_LG_MODES = {"values", "updates", "checkpoints", "tasks", "debug", "messages", "custom"}
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def _log_background_title_finalize_failure(thread_id: str):
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def _done(task: asyncio.Task[bool]) -> None:
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try:
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task.result()
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except Exception:
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logger.debug("Failed to finalize background title for thread %s", thread_id, exc_info=True)
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return _done
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def _build_runtime_context(
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@@ -364,7 +364,40 @@ async def run_agent(
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else:
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await run_manager.set_status(run_id, RunStatus.interrupted)
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else:
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await run_manager.set_status(run_id, RunStatus.success)
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# LLMErrorHandlingMiddleware intentionally converts an exhausted
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# provider failure into a user-safe AIMessage instead of raising.
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# That keeps a malformed upstream response out of the SSE transport,
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# but previously made this worker record the run as ``success``.
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# The UI consequently had no error event to show and looked as if
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# generation had silently stopped halfway through. Inspect the
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# terminal checkpoint before declaring success so the persisted run
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# state and the user-visible SSE outcome stay consistent.
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terminal_llm_error = await _terminal_llm_error_reason(
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checkpointer=checkpointer,
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thread_id=thread_id,
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)
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if terminal_llm_error is not None:
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error_message = "本轮模型生成未能完成,已保留当前对话内容,请稍后重试。"
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logger.warning(
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"Run %s ended with LLM fallback message (reason=%s)",
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run_id,
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terminal_llm_error,
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)
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await run_manager.set_status(
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run_id,
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RunStatus.error,
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error=error_message,
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)
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await bridge.publish(
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run_id,
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"error",
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{
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"message": error_message,
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"name": "ModelGenerationError",
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},
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)
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else:
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await run_manager.set_status(run_id, RunStatus.success)
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except asyncio.CancelledError:
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action = record.abort_action
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@@ -414,47 +447,47 @@ async def run_agent(
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except Exception:
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logger.warning("Failed to persist run completion for %s (non-fatal)", run_id, exc_info=True)
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# Sync title from checkpoint to threads_meta.display_name
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if checkpointer is not None and thread_store is not None:
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try:
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ckpt_config = {"configurable": {"thread_id": thread_id, "checkpoint_ns": ""}}
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ckpt_tuple = await checkpointer.aget_tuple(ckpt_config)
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if ckpt_tuple is not None:
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ckpt = getattr(ckpt_tuple, "checkpoint", {}) or {}
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channel_values = ckpt.get("channel_values", {}) or {}
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title = channel_values.get("title")
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if title:
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await thread_store.update_display_name(thread_id, title)
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if (
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record.status == RunStatus.success
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and channel_values.get("title_provisional") is True
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):
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log_title_debug(
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"Run %s: scheduling background title generation for thread %s",
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run_id,
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thread_id,
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)
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title_task = asyncio.create_task(
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finalize_thread_title(
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checkpointer=checkpointer,
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thread_store=thread_store,
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thread_id=thread_id,
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source_state=copy.deepcopy(channel_values),
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app_config=ctx.app_config,
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),
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name=f"title-finalize:{thread_id}",
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)
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title_task.add_done_callback(_log_background_title_finalize_failure(thread_id))
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elif record.status == RunStatus.success:
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log_title_debug(
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"Run %s: background title generation not scheduled for thread %s because title_provisional=%r title=%r",
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run_id,
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thread_id,
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channel_values.get("title_provisional"),
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channel_values.get("title"),
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)
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except Exception:
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logger.debug("Failed to sync title for thread %s (non-fatal)", thread_id)
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# Sync title from checkpoint to threads_meta.display_name
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if checkpointer is not None and thread_store is not None:
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try:
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ckpt_config = {"configurable": {"thread_id": thread_id, "checkpoint_ns": ""}}
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ckpt_tuple = await checkpointer.aget_tuple(ckpt_config)
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if ckpt_tuple is not None:
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ckpt = getattr(ckpt_tuple, "checkpoint", {}) or {}
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channel_values = ckpt.get("channel_values", {}) or {}
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title = channel_values.get("title")
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if title:
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await thread_store.update_display_name(thread_id, title)
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if (
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record.status == RunStatus.success
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and channel_values.get("title_provisional") is True
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):
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log_title_debug(
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"Run %s: scheduling background title generation for thread %s",
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run_id,
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thread_id,
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)
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title_task = asyncio.create_task(
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finalize_thread_title(
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checkpointer=checkpointer,
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thread_store=thread_store,
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thread_id=thread_id,
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source_state=copy.deepcopy(channel_values),
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app_config=ctx.app_config,
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),
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name=f"title-finalize:{thread_id}",
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)
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title_task.add_done_callback(_log_background_title_finalize_failure(thread_id))
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elif record.status == RunStatus.success:
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log_title_debug(
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"Run %s: background title generation not scheduled for thread %s because title_provisional=%r title=%r",
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run_id,
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thread_id,
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channel_values.get("title_provisional"),
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channel_values.get("title"),
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)
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except Exception:
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logger.debug("Failed to sync title for thread %s (non-fatal)", thread_id)
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# Update threads_meta status based on run outcome
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if thread_store is not None:
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@@ -484,6 +517,65 @@ async def _call_checkpointer_method(checkpointer: Any, async_name: str, sync_nam
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return result
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async def _terminal_llm_error_reason(
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*,
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checkpointer: Any | None,
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thread_id: str,
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) -> str | None:
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"""Return the terminal LLM fallback reason, if this run ended in one.
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``LLMErrorHandlingMiddleware`` persists its fallback as an AI message with
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an internal marker. A normal agent graph treats that message as a valid
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result and completes without an exception, so the worker must check the
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saved conversation rather than relying solely on ``astream`` raising.
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"""
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if checkpointer is None:
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return None
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try:
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checkpoint_config = {
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"configurable": {
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"thread_id": thread_id,
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"checkpoint_ns": "",
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}
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}
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checkpoint_tuple = await _call_checkpointer_method(
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checkpointer,
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"aget_tuple",
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"get_tuple",
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checkpoint_config,
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)
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if checkpoint_tuple is None:
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return None
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checkpoint = getattr(checkpoint_tuple, "checkpoint", {}) or {}
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channel_values = checkpoint.get("channel_values", {})
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messages = channel_values.get("messages", []) if isinstance(channel_values, dict) else []
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if not isinstance(messages, list):
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return None
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# Walk backwards to the latest assistant message. Tool/human messages
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# may be appended around it by middleware, but an older fallback should
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# never turn a later successful response into an error.
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for message in reversed(messages):
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message_type = message.get("type") if isinstance(message, dict) else getattr(message, "type", None)
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if message_type not in {"ai", "assistant"}:
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continue
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from deerflow.agents.middlewares.llm_error_handling_middleware import (
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is_llm_error_message,
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)
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return is_llm_error_message(message)
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except Exception:
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# A status check must never turn a completed answer into a failed run
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# merely because a custom checkpointer cannot expose its latest tuple.
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logger.debug(
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"Could not inspect terminal LLM state for thread %s",
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thread_id,
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exc_info=True,
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)
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return None
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async def _rollback_to_pre_run_checkpoint(
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*,
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checkpointer: Any,
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+7
-1
@@ -3,7 +3,13 @@ from typing import Literal
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from langchain.tools import tool
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@tool("ask_clarification", parse_docstring=True, return_direct=True)
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# ClarificationMiddleware owns the stop behaviour: it returns a Command that
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# writes the ToolMessage and explicitly routes to END. ``return_direct=True``
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# makes the prebuilt tool node short-circuit before that Command update is
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# checkpointed in some LangGraph versions, leaving an assistant tool call
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# without its matching ToolMessage. The next user reply then fails provider
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# validation with "tool_calls must be followed by tool messages".
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@tool("ask_clarification", parse_docstring=True, return_direct=False)
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def ask_clarification_tool(
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question: str,
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clarification_type: Literal[
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Reference in new issue
Block a user