实现RAG参考文献显示模式
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吉鑫升 authored and xuhd committed
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89bd07be92
commit
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20 files changed
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-184
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@@ -12,7 +12,9 @@ import {
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ResizablePanelGroup,
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} from "@/components/ui/resizable";
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import { Tabs, TabsContent, TabsList, TabsTrigger } from "@/components/ui/tabs";
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import { useLocalSettings } from "@/core/settings";
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import { apiFetch } from "@/core/api";
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import { getBackendBaseURL } from "@/core/config";
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import { isThreadRagModeLocked, useLocalSettings } from "@/core/settings";
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import { useSkills } from "@/core/skills/hooks";
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import {
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buildSkillDisplayMap,
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@@ -33,6 +35,33 @@ const CLOSE_MODE = { chat: 100, artifacts: 0 };
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const OPEN_MODE = { chat: 60, artifacts: 40 };
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const SHOW_REFERENCE_EVENT = "workspace:show-reference";
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type BackendReferenceSource = Parameters<typeof SkillDisplaySources>[0]["sources"][number];
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type BackendReferenceBatch = {
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id: string;
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assistant_message_id?: string;
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sources: BackendReferenceSource[];
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};
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function logReferenceDebug(
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event: string,
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threadId: string,
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payload: Record<string, unknown>,
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) {
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console.info(`[RAG引用调试] ${event}`, payload);
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void apiFetch(`${getBackendBaseURL()}/api/threads/reference-debug-log`, {
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method: "POST",
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headers: { "Content-Type": "application/json" },
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body: JSON.stringify({
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event,
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thread_id: threadId,
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payload,
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}),
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}).catch(() => {
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// Debug logging must never affect the chat flow.
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});
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}
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const ChatBox: React.FC<{ children: React.ReactNode; threadId: string }> = ({
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children,
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threadId,
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@@ -42,10 +71,17 @@ const ChatBox: React.FC<{ children: React.ReactNode; threadId: string }> = ({
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const threadIdRef = useRef(threadId);
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const artifactsCountRef = useRef(0);
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const layoutRef = useRef<GroupImperativeHandle>(null);
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const latestReferenceBatchIdRef = useRef<string | null>(null);
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const manualReferenceBatchRef = useRef(false);
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const referenceDebugSignatureRef = useRef<string>("");
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const [sideTab, setSideTab] = useState("document");
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const [referencesOpen, setReferencesOpen] = useState(true);
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const [activeReferenceBatchId, setActiveReferenceBatchId] = useState<string | null>(null);
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const [pinnedReferenceId, setPinnedReferenceId] = useState<string | null>(null);
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const [backendReferenceBatches, setBackendReferenceBatches] = useState<BackendReferenceBatch[]>([]);
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const [settings] = useLocalSettings();
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const ragModeEnabled =
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settings.display.ragModeEnabled || isThreadRagModeLocked(threadId);
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const { skills } = useSkills();
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const {
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@@ -60,27 +96,84 @@ const ChatBox: React.FC<{ children: React.ReactNode; threadId: string }> = ({
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const [autoSelectFirstArtifact, setAutoSelectFirstArtifact] = useState(true);
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const skillDisplayMap = useMemo(
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() => (settings.display.ragModeEnabled ? buildSkillDisplayMap(skills) : new Map()),
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[settings.display.ragModeEnabled, skills],
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() => (ragModeEnabled ? buildSkillDisplayMap(skills) : new Map()),
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[ragModeEnabled, skills],
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);
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const referenceBatches = useMemo(() => {
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if (!settings.display.ragModeEnabled) {
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const fallbackReferenceBatches = useMemo(() => {
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if (!ragModeEnabled) {
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return [];
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}
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const messages = thread.values.messages ?? [];
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return messages
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.filter((message) => message.type === "ai" && message.id)
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.map((message) => ({
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id: message.id!,
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sources: collectRuntimeDisplaySources(messages, skillDisplayMap, {
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afterMessageId: findPreviousHumanMessageId(messages, message.id),
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beforeMessageId: message.id,
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includeBeforeMessage: true,
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includeModes: ["citation"],
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}).filter((source) => source.mode === "citation"),
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}))
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.filter((batch) => batch.sources.length > 0);
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}, [settings.display.ragModeEnabled, skillDisplayMap, thread.values.messages]);
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return buildTurnReferenceBatches(
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thread.values.messages ?? [],
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skillDisplayMap,
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thread.isLoading,
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);
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}, [ragModeEnabled, skillDisplayMap, thread.isLoading, thread.values.messages]);
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useEffect(() => {
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if (!ragModeEnabled) {
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setBackendReferenceBatches([]);
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return;
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}
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if (thread.isLoading) {
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return;
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}
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const controller = new AbortController();
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logReferenceDebug("开始拉取后端参考文献", threadId, {
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messageCount: thread.values.messages?.length ?? 0,
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});
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apiFetch(
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`${getBackendBaseURL()}/api/threads/${encodeURIComponent(threadId)}/reference-batches`,
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{ signal: controller.signal },
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)
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.then(async (response) => {
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if (!response.ok) {
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throw new Error(`Failed to load reference batches: ${response.status}`);
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}
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return (await response.json()) as { batches?: BackendReferenceBatch[] };
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})
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.then((data) => {
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const batches = data.batches ?? [];
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logReferenceDebug("后端参考文献返回", threadId, {
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batchCount: batches.length,
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sourceCounts: batches.map((batch) => batch.sources?.length ?? 0),
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batchIds: batches.map((batch) => batch.id),
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});
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setBackendReferenceBatches(batches);
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})
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.catch((error) => {
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if (!controller.signal.aborted) {
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console.warn("Failed to load backend reference batches", error);
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}
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});
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return () => controller.abort();
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}, [ragModeEnabled, thread.isLoading, threadId, thread.values.messages]);
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const referenceBatches =
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backendReferenceBatches.length > 0
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? backendReferenceBatches
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: fallbackReferenceBatches;
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useEffect(() => {
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if (!ragModeEnabled) {
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return;
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}
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const signature = JSON.stringify({
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backend: backendReferenceBatches.map((batch) => batch.sources?.length ?? 0),
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fallback: fallbackReferenceBatches.map((batch) => batch.sources?.length ?? 0),
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final: referenceBatches.map((batch) => batch.sources?.length ?? 0),
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});
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if (referenceDebugSignatureRef.current === signature) {
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return;
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}
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referenceDebugSignatureRef.current = signature;
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logReferenceDebug("前端参考文献来源选择", threadId, {
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using: backendReferenceBatches.length > 0 ? "后端接口" : "前端兜底",
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backendBatchCount: backendReferenceBatches.length,
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backendSourceCounts: backendReferenceBatches.map((batch) => batch.sources?.length ?? 0),
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fallbackBatchCount: fallbackReferenceBatches.length,
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fallbackSourceCounts: fallbackReferenceBatches.map((batch) => batch.sources?.length ?? 0),
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finalBatchCount: referenceBatches.length,
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finalSourceCounts: referenceBatches.map((batch) => batch.sources?.length ?? 0),
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});
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}, [backendReferenceBatches, fallbackReferenceBatches, ragModeEnabled, referenceBatches, threadId]);
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const latestReferenceBatch =
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referenceBatches.length > 0
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? referenceBatches[referenceBatches.length - 1]!
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@@ -98,20 +191,32 @@ const ChatBox: React.FC<{ children: React.ReactNode; threadId: string }> = ({
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useEffect(() => {
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if (!latestReferenceBatch) {
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setActiveReferenceBatchId(null);
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latestReferenceBatchIdRef.current = null;
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manualReferenceBatchRef.current = false;
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return;
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}
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const previousLatestId = latestReferenceBatchIdRef.current;
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latestReferenceBatchIdRef.current = latestReferenceBatch.id;
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setActiveReferenceBatchId((current) =>
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current && referenceBatches.some((batch) => batch.id === current)
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current &&
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referenceBatches.some((batch) => batch.id === current) &&
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manualReferenceBatchRef.current &&
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current !== previousLatestId
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? current
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: latestReferenceBatch.id,
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);
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}, [latestReferenceBatch?.id, referenceBatches]);
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useEffect(() => {
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const handleShowReference = (event: Event) => {
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const detail = (event as CustomEvent<{ batchId?: string }>).detail;
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const detail = (event as CustomEvent<{ batchId?: string; referenceId?: string }>).detail;
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if (detail?.batchId) {
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manualReferenceBatchRef.current = true;
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setActiveReferenceBatchId(detail.batchId);
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}
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setPinnedReferenceId(null);
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window.setTimeout(() => {
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setPinnedReferenceId(detail?.referenceId ?? null);
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}, 0);
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setReferencesOpen(true);
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setSideTab("references");
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};
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@@ -125,7 +230,13 @@ const ChatBox: React.FC<{ children: React.ReactNode; threadId: string }> = ({
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threadIdRef.current = threadId;
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artifactsCountRef.current = 0;
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deselect();
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setReferencesOpen(true);
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setReferencesOpen(false);
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setActiveReferenceBatchId(null);
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setPinnedReferenceId(null);
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setBackendReferenceBatches([]);
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latestReferenceBatchIdRef.current = null;
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manualReferenceBatchRef.current = false;
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referenceDebugSignatureRef.current = "";
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}
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// Update artifacts from the current thread
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@@ -257,7 +368,10 @@ const ChatBox: React.FC<{ children: React.ReactNode; threadId: string }> = ({
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/>
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</TabsContent>
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<TabsContent value="references" className="min-h-0 flex-1 overflow-y-auto p-0">
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<ReferencePanel sources={referenceSources} />
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<ReferencePanel
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highlightedReferenceId={pinnedReferenceId}
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sources={referenceSources}
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/>
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</TabsContent>
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</Tabs>
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) : selectedArtifact ? (
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@@ -280,7 +394,10 @@ const ChatBox: React.FC<{ children: React.ReactNode; threadId: string }> = ({
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<XIcon />
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</Button>
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</div>
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<ReferencePanel sources={referenceSources} />
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<ReferencePanel
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highlightedReferenceId={pinnedReferenceId}
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sources={referenceSources}
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/>
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</div>
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) : (
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<div className="relative flex size-full justify-center">
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@@ -324,10 +441,27 @@ const ChatBox: React.FC<{ children: React.ReactNode; threadId: string }> = ({
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};
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function ReferencePanel({
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highlightedReferenceId,
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sources,
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}: {
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highlightedReferenceId?: string | null;
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sources: Parameters<typeof SkillDisplaySources>[0]["sources"];
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}) {
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const orderedSources = useMemo(() => {
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if (!highlightedReferenceId) {
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return sources;
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}
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const index = Number(highlightedReferenceId);
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if (!Number.isFinite(index)) {
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return sources;
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}
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const selected = sources.find((source) => source.index === index);
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if (!selected) {
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return sources;
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}
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return [selected, ...sources.filter((source) => source.index !== index)];
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}, [highlightedReferenceId, sources]);
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return (
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<div className="flex size-full flex-col overflow-hidden">
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<header className="shrink-0 px-1 pb-3">
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@@ -344,7 +478,10 @@ function ReferencePanel({
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</p>
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</header>
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<main className="min-h-0 flex-1 overflow-y-auto px-1 pt-1 pb-6">
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<SkillDisplaySources sources={sources} />
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<SkillDisplaySources
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highlightedReferenceId={highlightedReferenceId}
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sources={orderedSources}
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/>
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</main>
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</div>
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);
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@@ -368,4 +505,101 @@ function findPreviousHumanMessageId(
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return undefined;
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}
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function buildTurnReferenceBatches(
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messages: Message[],
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skillDisplayMap: ReturnType<typeof buildSkillDisplayMap>,
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isLoading: boolean,
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): BackendReferenceBatch[] {
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const batches: BackendReferenceBatch[] = [];
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for (let index = 0; index < messages.length; index++) {
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const human = messages[index];
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if (human?.type !== "human" || !human.id) {
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continue;
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}
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const nextHumanIndex = findNextHumanIndex(messages, index + 1);
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if (nextHumanIndex === -1 && isLoading) {
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continue;
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}
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const endIndex = nextHumanIndex === -1 ? messages.length : nextHumanIndex;
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const assistant = findLastAssistantAnswer(messages, index + 1, endIndex);
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if (!assistant?.id) {
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continue;
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}
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const sources = collectRuntimeDisplaySources(messages, skillDisplayMap, {
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afterMessageId: human.id,
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beforeMessageId:
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nextHumanIndex === -1 ? undefined : messages[nextHumanIndex]?.id,
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includeBeforeMessage: false,
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includeModes: ["citation"],
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}).filter((source) => source.mode === "citation");
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if (sources.length > 0) {
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batches.push({
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id: assistant.id,
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assistant_message_id: assistant.id,
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sources,
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});
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}
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}
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return batches;
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}
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function findNextHumanIndex(messages: Message[], start: number): number {
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for (let index = start; index < messages.length; index++) {
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if (messages[index]?.type === "human") {
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return index;
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}
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}
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return -1;
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}
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function findLastAssistantAnswer(
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messages: Message[],
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start: number,
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end: number,
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): Message | null {
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for (let index = end - 1; index >= start; index--) {
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const message = messages[index];
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if (
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message?.type === "ai" &&
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message.id &&
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hasAssistantAnswerContent(message) &&
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!hasAssistantToolCalls(message)
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) {
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return message;
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}
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}
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return null;
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}
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function hasAssistantAnswerContent(message: Message): boolean {
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const content = message.content;
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if (typeof content === "string") {
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return content.trim().length > 0;
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}
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if (!Array.isArray(content)) {
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return false;
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}
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return content.some((part) => {
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if (!part || typeof part !== "object") {
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return false;
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}
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const block = part as Record<string, unknown>;
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return block.type === "text" && typeof block.text === "string" && block.text.trim().length > 0;
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});
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}
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function hasAssistantToolCalls(message: Message): boolean {
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const direct = (message as { tool_calls?: unknown }).tool_calls;
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if (Array.isArray(direct) && direct.length > 0) {
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return true;
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}
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const chunks = (message as { tool_call_chunks?: unknown }).tool_call_chunks;
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if (Array.isArray(chunks) && chunks.length > 0) {
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return true;
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}
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const kwargs = (message as { additional_kwargs?: Record<string, unknown> }).additional_kwargs;
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const extra = kwargs?.tool_calls;
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return Array.isArray(extra) && extra.length > 0;
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}
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export { ChatBox };
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@@ -87,7 +87,11 @@ import {
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} from "../ui/dropdown-menu";
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import { useRecommendedQuestions } from "@/core/recommended-questions/hooks";
|
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import { useLocalSettings } from "@/core/settings";
|
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import {
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isThreadRagModeLocked,
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lockThreadRagMode,
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useLocalSettings,
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} from "@/core/settings";
|
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|
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|
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import { useThread } from "./messages/context";
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@@ -300,10 +304,14 @@ export function InputBox({
|
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});
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}, [context, memoryInjectionEnabled, onContextChange]);
|
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const ragModeEnabled = localSettings.display.ragModeEnabled;
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const handleRagModeToggle = useCallback(() => {
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setLocalSettings("display", { ragModeEnabled: !ragModeEnabled });
|
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}, [ragModeEnabled, setLocalSettings]);
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const ragModeLocked = isThreadRagModeLocked(threadId);
|
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const ragModeEnabled = localSettings.display.ragModeEnabled || ragModeLocked;
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const handleRagModeToggle = useCallback(() => {
|
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if (ragModeLocked) {
|
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return;
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}
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setLocalSettings("display", { ragModeEnabled: !ragModeEnabled });
|
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}, [ragModeEnabled, ragModeLocked, setLocalSettings]);
|
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|
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const handleSubmit = useCallback(
|
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async (message: PromptInputMessage) => {
|
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@@ -316,9 +324,12 @@ export function InputBox({
|
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}
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setFollowups([]);
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setFollowupsHidden(false);
|
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setFollowupsLoading(false);
|
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|
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// Guard against submitting before the initial model auto-selection
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setFollowupsLoading(false);
|
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if (ragModeEnabled) {
|
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lockThreadRagMode(threadId);
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}
|
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|
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// Guard against submitting before the initial model auto-selection
|
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// effect has flushed thread settings to storage/state.
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if (resolvedModelName && context.model_name !== resolvedModelName) {
|
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onContextChange?.({
|
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@@ -340,11 +351,13 @@ export function InputBox({
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onContextChange,
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onSubmit,
|
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onStop,
|
||||
resolvedModelName,
|
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selectedModel?.supports_thinking,
|
||||
status,
|
||||
],
|
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);
|
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resolvedModelName,
|
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ragModeEnabled,
|
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selectedModel?.supports_thinking,
|
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status,
|
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threadId,
|
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],
|
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);
|
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|
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const requestFormSubmit = useCallback(() => {
|
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const form = promptRootRef.current?.querySelector("form");
|
||||
@@ -638,11 +651,13 @@ export function InputBox({
|
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}
|
||||
>
|
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<PromptInputButton
|
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type="button"
|
||||
aria-pressed={ragModeEnabled}
|
||||
className={cn(
|
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"gap-1.5! rounded-full px-3! shadow-none",
|
||||
ragModeEnabled
|
||||
type="button"
|
||||
aria-pressed={ragModeEnabled}
|
||||
disabled={ragModeLocked || disabled}
|
||||
className={cn(
|
||||
"gap-1.5! rounded-full px-3! shadow-none",
|
||||
ragModeLocked && "cursor-not-allowed opacity-80",
|
||||
ragModeEnabled
|
||||
? "border border-emerald-300 bg-emerald-50 text-emerald-700 hover:bg-emerald-100 dark:border-emerald-700 dark:bg-emerald-950/40 dark:text-emerald-200"
|
||||
: "border-0 bg-transparent text-muted-foreground hover:bg-muted/70 hover:text-foreground dark:text-slate-400 dark:hover:bg-slate-700/70 dark:hover:text-slate-100",
|
||||
)}
|
||||
|
||||
@@ -36,10 +36,13 @@ export function MarkdownContent({
|
||||
}: MarkdownContentProps) {
|
||||
const components = useMemo(() => {
|
||||
return {
|
||||
a: (props: AnchorHTMLAttributes<HTMLAnchorElement>) => {
|
||||
if (typeof props.children === "string") {
|
||||
const match = /^citation:(.+)$/.exec(props.children);
|
||||
if (match) {
|
||||
a: (props: AnchorHTMLAttributes<HTMLAnchorElement>) => {
|
||||
if (props.href?.startsWith("#reference-")) {
|
||||
return <CitationLink {...props} />;
|
||||
}
|
||||
if (typeof props.children === "string") {
|
||||
const match = /^citation:(.+)$/.exec(props.children);
|
||||
if (match) {
|
||||
const [, text] = match;
|
||||
return <CitationLink {...props}>{text}</CitationLink>;
|
||||
}
|
||||
|
||||
@@ -21,10 +21,12 @@ import { getStoredAuth } from "@/core/auth";
|
||||
import { enUS, isLocale, zhCN, type Locale } from "@/core/i18n";
|
||||
import { useI18n } from "@/core/i18n/hooks";
|
||||
import { useLocalSettings } from "@/core/settings";
|
||||
import {
|
||||
useAppearanceSettings,
|
||||
useUpdateAppearanceSettings,
|
||||
} from "@/core/system-settings/hooks";
|
||||
import {
|
||||
useAppearanceSettings,
|
||||
useCitationDisplaySettings,
|
||||
useUpdateAppearanceSettings,
|
||||
useUpdateCitationDisplaySettings,
|
||||
} from "@/core/system-settings/hooks";
|
||||
import { cn } from "@/lib/utils";
|
||||
|
||||
import { SettingsSection } from "./settings-section";
|
||||
@@ -40,9 +42,13 @@ export function AppearanceSettingsPage() {
|
||||
const currentTheme = theme;
|
||||
const [settings, setSettings] = useLocalSettings();
|
||||
const isAdmin = getStoredAuth()?.system_role === "admin";
|
||||
const { data: appearance } = useAppearanceSettings();
|
||||
const updateAppearance = useUpdateAppearanceSettings();
|
||||
const globalDefault = appearance?.default_theme ?? "light";
|
||||
const { data: appearance } = useAppearanceSettings();
|
||||
const updateAppearance = useUpdateAppearanceSettings();
|
||||
const { data: citationDisplay } = useCitationDisplaySettings();
|
||||
const updateCitationDisplay = useUpdateCitationDisplaySettings();
|
||||
const globalDefault = appearance?.default_theme ?? "light";
|
||||
const cleanupWords =
|
||||
citationDisplay?.cleanup_words ?? settings.display.citationCleanupWords ?? [];
|
||||
|
||||
const handleSetGlobalDefault = async (value: "light" | "dark") => {
|
||||
if (value === globalDefault) return;
|
||||
@@ -211,16 +217,16 @@ export function AppearanceSettingsPage() {
|
||||
管理员配置。每行一个词或短句，参考文献卡片和详情弹框会自动移除这些广告词、导航词或免责声明。
|
||||
</p>
|
||||
</div>
|
||||
<Textarea
|
||||
value={(settings.display.citationCleanupWords ?? []).join("\n")}
|
||||
onChange={(event) =>
|
||||
setSettings("display", {
|
||||
citationCleanupWords: event.currentTarget.value
|
||||
.split(/\r?\n/)
|
||||
.map((item) => item.trim())
|
||||
.filter(Boolean),
|
||||
})
|
||||
}
|
||||
<Textarea
|
||||
value={cleanupWords.join("\n")}
|
||||
onChange={(event) => {
|
||||
const words = event.currentTarget.value
|
||||
.split(/\r?\n/)
|
||||
.map((item) => item.trim())
|
||||
.filter(Boolean);
|
||||
setSettings("display", { citationCleanupWords: words });
|
||||
updateCitationDisplay.mutate({ cleanup_words: words });
|
||||
}}
|
||||
placeholder={"广告\n点击下载APP\n打开客户端\n免责声明\n责任编辑"}
|
||||
className="min-h-32 text-sm"
|
||||
/>
|
||||
|
||||
@@ -10,13 +10,16 @@ import {
|
||||
} from "@/components/ui/dialog";
|
||||
import type { RuntimeDisplaySource } from "@/core/skill-display/runtime";
|
||||
import { useLocalSettings } from "@/core/settings";
|
||||
import { useCitationDisplaySettings } from "@/core/system-settings/hooks";
|
||||
import { cn } from "@/lib/utils";
|
||||
import { useState } from "react";
|
||||
|
||||
export function SkillDisplaySources({
|
||||
highlightedReferenceId,
|
||||
sources,
|
||||
className,
|
||||
}: {
|
||||
highlightedReferenceId?: string | null;
|
||||
sources: RuntimeDisplaySource[];
|
||||
className?: string;
|
||||
}) {
|
||||
@@ -29,6 +32,7 @@ export function SkillDisplaySources({
|
||||
{sources.map((source) => (
|
||||
<SourceCard
|
||||
key={`${source.skillName}-${source.index}`}
|
||||
highlighted={highlightedReferenceId === String(source.index)}
|
||||
source={source}
|
||||
referenceTarget
|
||||
/>
|
||||
@@ -38,15 +42,19 @@ export function SkillDisplaySources({
|
||||
}
|
||||
|
||||
export function SourceCard({
|
||||
highlighted = false,
|
||||
source,
|
||||
referenceTarget = false,
|
||||
}: {
|
||||
highlighted?: boolean;
|
||||
source: RuntimeDisplaySource;
|
||||
referenceTarget?: boolean;
|
||||
}) {
|
||||
const [open, setOpen] = useState(false);
|
||||
const [settings] = useLocalSettings();
|
||||
const cleanupWords = settings.display.citationCleanupWords ?? [];
|
||||
const { data: citationDisplay } = useCitationDisplaySettings();
|
||||
const cleanupWords =
|
||||
citationDisplay?.cleanup_words ?? settings.display.citationCleanupWords ?? [];
|
||||
const content = cleanReferenceText(source.content || source.snippet, cleanupWords);
|
||||
const snippet = compactReferenceText(content).slice(0, 280);
|
||||
const paragraphs = segmentReferenceText(content);
|
||||
@@ -72,6 +80,8 @@ export function SourceCard({
|
||||
className={cn(
|
||||
"group bg-card/60 hover:bg-card hover:border-primary/40 focus-visible:ring-primary/30 w-full scroll-mt-12 rounded-xl border px-3.5 py-3 text-left shadow-sm transition-all focus-visible:ring-2 focus-visible:outline-none",
|
||||
"target:bg-primary/5 target:border-primary/60",
|
||||
highlighted &&
|
||||
"animate-[reference-flash_1.4s_ease-out] border-amber-400 bg-amber-50 shadow-[0_0_0_3px_rgba(251,191,36,0.22)]",
|
||||
)}
|
||||
onClick={() => setOpen(true)}
|
||||
>
|
||||
@@ -168,10 +178,13 @@ function cleanReferenceText(
|
||||
cleanupWords: string[],
|
||||
): string {
|
||||
let text = raw ?? "";
|
||||
for (const word of cleanupWords) {
|
||||
const trimmed = word.trim();
|
||||
if (!trimmed) continue;
|
||||
text = text.split(trimmed).join("");
|
||||
const words = cleanupWords.map((word) => word.trim()).filter(Boolean);
|
||||
if (words.length > 0) {
|
||||
text = text
|
||||
.replace(/\r\n/g, "\n")
|
||||
.split("\n")
|
||||
.filter((line) => !words.some((word) => line.includes(word)))
|
||||
.join("\n");
|
||||
}
|
||||
return text
|
||||
.replace(/\r\n/g, "\n")
|
||||
|
||||
@@ -7,6 +7,10 @@
|
||||
*/
|
||||
|
||||
export type SearchResultItem = {
|
||||
id?: string;
|
||||
recUuid?: string;
|
||||
uuid?: string;
|
||||
docId?: string;
|
||||
title?: string;
|
||||
url?: string;
|
||||
snippet?: string;
|
||||
@@ -300,6 +304,10 @@ function normalizeSearchResultItem(raw: unknown): SearchResultItem | null {
|
||||
const date =
|
||||
pickFromLayers(layers, DATE_ALIASES) ??
|
||||
pickByKeyPattern(layers, DATE_KEY_PATTERN, { maxLength: 64 });
|
||||
const id = pickFromLayers(layers, ["id", "taskId", "recordId", "record_id"]);
|
||||
const recUuid = pickFromLayers(layers, ["recUuid", "rec_uuid"]);
|
||||
const uuid = pickFromLayers(layers, ["uuid"]);
|
||||
const docId = pickFromLayers(layers, ["docId", "doc_id", "documentId"]);
|
||||
|
||||
const reserved = new Set<string>();
|
||||
for (const value of [title, content, url, source, date]) {
|
||||
@@ -324,6 +332,10 @@ function normalizeSearchResultItem(raw: unknown): SearchResultItem | null {
|
||||
}
|
||||
|
||||
return {
|
||||
id,
|
||||
recUuid,
|
||||
uuid,
|
||||
docId,
|
||||
title,
|
||||
url,
|
||||
snippet: content,
|
||||
|
||||
@@ -1,2 +1,3 @@
|
||||
export { useLocalSettings, useThreadSettings } from "./hooks";
|
||||
export type { LocalSettings } from "./local";
|
||||
export { useLocalSettings, useThreadSettings } from "./hooks";
|
||||
export { isThreadRagModeLocked, lockThreadRagMode } from "./local";
|
||||
export type { LocalSettings } from "./local";
|
||||
@@ -17,8 +17,9 @@ export const DEFAULT_LOCAL_SETTINGS: LocalSettings = {
|
||||
},
|
||||
};
|
||||
|
||||
export const LOCAL_SETTINGS_KEY = "deerflow.local-settings";
|
||||
export const THREAD_MODEL_KEY_PREFIX = "deerflow.thread-model.";
|
||||
export const LOCAL_SETTINGS_KEY = "deerflow.local-settings";
|
||||
export const THREAD_MODEL_KEY_PREFIX = "deerflow.thread-model.";
|
||||
export const THREAD_RAG_MODE_KEY_PREFIX = "deerflow.thread-rag-mode.";
|
||||
|
||||
function isBrowser(): boolean {
|
||||
return typeof window !== "undefined";
|
||||
@@ -90,10 +91,10 @@ export function getThreadModelName(threadId: string): string | undefined {
|
||||
return localStorage.getItem(getThreadModelStorageKey(threadId)) ?? undefined;
|
||||
}
|
||||
|
||||
export function saveThreadModelName(
|
||||
threadId: string,
|
||||
modelName: string | undefined,
|
||||
) {
|
||||
export function saveThreadModelName(
|
||||
threadId: string,
|
||||
modelName: string | undefined,
|
||||
) {
|
||||
if (!isBrowser()) {
|
||||
return;
|
||||
}
|
||||
@@ -102,8 +103,26 @@ export function saveThreadModelName(
|
||||
localStorage.removeItem(key);
|
||||
return;
|
||||
}
|
||||
localStorage.setItem(key, modelName);
|
||||
}
|
||||
localStorage.setItem(key, modelName);
|
||||
}
|
||||
|
||||
function getThreadRagModeStorageKey(threadId: string): string {
|
||||
return `${THREAD_RAG_MODE_KEY_PREFIX}${threadId}`;
|
||||
}
|
||||
|
||||
export function isThreadRagModeLocked(threadId: string): boolean {
|
||||
if (!isBrowser() || !threadId) {
|
||||
return false;
|
||||
}
|
||||
return localStorage.getItem(getThreadRagModeStorageKey(threadId)) === "true";
|
||||
}
|
||||
|
||||
export function lockThreadRagMode(threadId: string) {
|
||||
if (!isBrowser() || !threadId) {
|
||||
return;
|
||||
}
|
||||
localStorage.setItem(getThreadRagModeStorageKey(threadId), "true");
|
||||
}
|
||||
|
||||
export function applyThreadModelOverride(
|
||||
settings: LocalSettings,
|
||||
|
||||
@@ -168,6 +168,7 @@ export function collectRuntimeDisplaySources(
|
||||
const seenCitationKeys = new Map<string, RuntimeDisplaySource>();
|
||||
const seenDisplayKeys = new Set<string>();
|
||||
const consumedToolMessageIds = new Set<string>();
|
||||
const consumedToolMessages = new Set<Message>();
|
||||
|
||||
for (let index = start; index < limit; index++) {
|
||||
const message = messages[index];
|
||||
@@ -180,14 +181,24 @@ export function collectRuntimeDisplaySources(
|
||||
displays,
|
||||
toolCall.args,
|
||||
);
|
||||
const result = findToolResultPayload(toolCall, messages, index);
|
||||
const toolMessage = findToolResultMessage(
|
||||
toolCall,
|
||||
messages,
|
||||
index,
|
||||
consumedToolMessageIds,
|
||||
consumedToolMessages,
|
||||
);
|
||||
if (!toolMessage) {
|
||||
continue;
|
||||
}
|
||||
const result = parseToolMessagePayload(toolMessage);
|
||||
if (result === undefined) {
|
||||
continue;
|
||||
}
|
||||
const linkedToolMessage = findToolMessageById(toolCall.id, messages);
|
||||
if (linkedToolMessage?.id) {
|
||||
consumedToolMessageIds.add(linkedToolMessage.id);
|
||||
if (toolMessage.id) {
|
||||
consumedToolMessageIds.add(toolMessage.id);
|
||||
}
|
||||
consumedToolMessages.add(toolMessage);
|
||||
if (isDisplaySamplePayload(result)) {
|
||||
continue;
|
||||
}
|
||||
@@ -223,7 +234,12 @@ export function collectRuntimeDisplaySources(
|
||||
|
||||
for (let index = start; index < limit; index++) {
|
||||
const message = messages[index];
|
||||
if (!message || message.type !== "tool" || consumedToolMessageIds.has(message.id ?? "")) {
|
||||
if (
|
||||
!message ||
|
||||
message.type !== "tool" ||
|
||||
consumedToolMessages.has(message) ||
|
||||
consumedToolMessageIds.has(message.id ?? "")
|
||||
) {
|
||||
continue;
|
||||
}
|
||||
const result = parseToolMessagePayload(message);
|
||||
@@ -238,7 +254,8 @@ export function collectRuntimeDisplaySources(
|
||||
}
|
||||
const normalized = match
|
||||
? normalizeDisplaySources(result, match.display)
|
||||
: shouldUseDefaultCitationMode(toolName, result)
|
||||
: shouldUseDefaultCitationMode(toolName, result) ||
|
||||
normalizeDefaultDisplaySources(result).length > 0
|
||||
? normalizeDefaultDisplaySources(result)
|
||||
: [];
|
||||
appendDisplaySources(
|
||||
@@ -268,16 +285,14 @@ function appendDisplaySources(
|
||||
) {
|
||||
for (const draft of drafts) {
|
||||
if (draft.mode === "citation") {
|
||||
const key = citationSourceKey(draft);
|
||||
const existing = seenCitationKeys.get(key);
|
||||
if (existing) {
|
||||
continue;
|
||||
}
|
||||
const source = {
|
||||
...draft,
|
||||
index: nextCitationIndex(),
|
||||
};
|
||||
seenCitationKeys.set(key, source);
|
||||
const key = citationSourceKey(draft);
|
||||
if (key) {
|
||||
seenCitationKeys.set(`${key}:${source.index}`, source);
|
||||
}
|
||||
target.push(source);
|
||||
continue;
|
||||
}
|
||||
@@ -331,12 +346,19 @@ function citationSourceKey(source: RuntimeDisplaySourceDraft): string {
|
||||
stringifyMaybe(raw.docId) ||
|
||||
stringifyMaybe(raw.id);
|
||||
if (id) {
|
||||
return normalizeName(`${source.skillName}:${id}`);
|
||||
return normalizeCitationKey(String(id));
|
||||
}
|
||||
const fallback = [source.skillName, source.title, source.source, source.time]
|
||||
const fallback = [
|
||||
source.skillName,
|
||||
source.title,
|
||||
source.source,
|
||||
source.time,
|
||||
source.content,
|
||||
source.snippet,
|
||||
]
|
||||
.filter(Boolean)
|
||||
.join("|");
|
||||
return normalizeName(fallback) || JSON.stringify(raw).slice(0, 300);
|
||||
return normalizeCitationKey(fallback) || normalizeCitationKey(JSON.stringify(raw).slice(0, 300));
|
||||
}
|
||||
|
||||
function nonCitationSourceKey(source: RuntimeDisplaySourceDraft): string {
|
||||
@@ -543,7 +565,12 @@ export function normalizeDefaultDisplaySources(payload: unknown): DisplaySourceI
|
||||
: undefined,
|
||||
);
|
||||
return normalized.map((item, index) => ({
|
||||
id: item.url ?? String(index + 1),
|
||||
id:
|
||||
item.recUuid ??
|
||||
item.uuid ??
|
||||
item.docId ??
|
||||
item.id ??
|
||||
item.url,
|
||||
title: item.title ?? item.source ?? `结果 ${index + 1}`,
|
||||
type: "result",
|
||||
snippet: item.snippet ?? item.content ?? "",
|
||||
@@ -620,18 +647,79 @@ function replaceCitationTokens(
|
||||
byIndex: Map<number, RuntimeDisplaySource>,
|
||||
orderedSources: RuntimeDisplaySource[],
|
||||
): string {
|
||||
return content
|
||||
const normalized = normalizeLooseCitationTokens(content, byIndex, orderedSources);
|
||||
const withDoubleBracketCitations = normalized
|
||||
.replace(/\[\[(\d+)\]\]/g, (match, rawIndex: string) =>
|
||||
citationMarkdown(match, Number(rawIndex), byIndex, orderedSources),
|
||||
)
|
||||
.replace(/(^|[^:\[!])\[(\d+)\](?!\()/g, (match, prefix: string, rawIndex: string) =>
|
||||
`${prefix}${citationMarkdown(
|
||||
match.slice(prefix.length),
|
||||
Number(rawIndex),
|
||||
byIndex,
|
||||
orderedSources,
|
||||
)}`,
|
||||
);
|
||||
return replaceBracketCitationTokens(
|
||||
withDoubleBracketCitations,
|
||||
byIndex,
|
||||
orderedSources,
|
||||
);
|
||||
}
|
||||
|
||||
function replaceBracketCitationTokens(
|
||||
content: string,
|
||||
byIndex: Map<number, RuntimeDisplaySource>,
|
||||
orderedSources: RuntimeDisplaySource[],
|
||||
): string {
|
||||
const tokenPattern = /\\?\[(\d{1,3})\\?\](?!\()/g;
|
||||
let cursor = 0;
|
||||
let next = "";
|
||||
for (const match of content.matchAll(tokenPattern)) {
|
||||
const start = match.index ?? 0;
|
||||
const previous = start > 0 ? content[start - 1] : "";
|
||||
if (previous === ":" || previous === "[" || previous === "!") {
|
||||
continue;
|
||||
}
|
||||
next += content.slice(cursor, start);
|
||||
next += citationMarkdown(match[0], Number(match[1]), byIndex, orderedSources);
|
||||
cursor = start + match[0].length;
|
||||
}
|
||||
next += content.slice(cursor);
|
||||
return next;
|
||||
}
|
||||
|
||||
function normalizeLooseCitationTokens(
|
||||
content: string,
|
||||
byIndex: Map<number, RuntimeDisplaySource>,
|
||||
orderedSources: RuntimeDisplaySource[],
|
||||
): string {
|
||||
const isValidIndex = (index: number) =>
|
||||
Number.isInteger(index) &&
|
||||
index > 0 &&
|
||||
(byIndex.has(index) || !!orderedSources[index - 1]);
|
||||
const toCitationRun = (raw: string) => {
|
||||
const parts = raw.match(/\\?\[\d{1,3}\\?\]|\d{1,3}/g) ?? [];
|
||||
const indexes = parts.map((part) => Number(part.replace(/\D/g, "")));
|
||||
if (indexes.length === 0 || indexes.some((index) => !isValidIndex(index))) {
|
||||
return raw;
|
||||
}
|
||||
return indexes.map((index) => `[${index}]`).join("");
|
||||
};
|
||||
|
||||
let next = content.replace(
|
||||
/(^|[^\d\[\]\\])((?:\d{1,3}|\\?\[\d{1,3}\\?\])(?:\\?\[\d{1,3}\\?\]|\d{1,3})+)/g,
|
||||
(match, prefix: string, rawRun: string) => {
|
||||
if (!rawRun.includes("[")) {
|
||||
return match;
|
||||
}
|
||||
return `${prefix}${toCitationRun(rawRun)}`;
|
||||
},
|
||||
);
|
||||
|
||||
next = next.replace(
|
||||
/(^|[\s\uFF0C\u3002\uFF1B\uFF1A\u3001,!?！？)])(\d{1,3})(?=([\s\uFF0C\u3002\uFF1B\uFF1A\u3001,!?！？)]|$))/g,
|
||||
(match, prefix: string, rawIndex: string) => {
|
||||
const index = Number(rawIndex);
|
||||
if (!isValidIndex(index)) {
|
||||
return match;
|
||||
}
|
||||
return `${prefix}[${index}]`;
|
||||
},
|
||||
);
|
||||
return next;
|
||||
}
|
||||
|
||||
function normalizeExistingCitationLinks(
|
||||
@@ -654,16 +742,16 @@ function normalizeExistingCitationLinks(
|
||||
const index = Number(numberMatch[1]);
|
||||
const source = byIndex.get(index) ?? orderedSources[index - 1];
|
||||
if (source) {
|
||||
return `[citation:[${source.index}]](#reference-${source.index})`;
|
||||
return citationLinkMarkdown(source);
|
||||
}
|
||||
}
|
||||
const sourceByUrl = byUrl.get(url);
|
||||
if (sourceByUrl) {
|
||||
return `[citation:[${sourceByUrl.index}]](#reference-${sourceByUrl.index})`;
|
||||
return citationLinkMarkdown(sourceByUrl);
|
||||
}
|
||||
const sourceByTitle = byTitle.get(label);
|
||||
if (sourceByTitle) {
|
||||
return `[citation:[${sourceByTitle.index}]](#reference-${sourceByTitle.index})`;
|
||||
return citationLinkMarkdown(sourceByTitle);
|
||||
}
|
||||
return match;
|
||||
},
|
||||
@@ -680,11 +768,11 @@ function citationMarkdown(
|
||||
if (!source) {
|
||||
return fallback;
|
||||
}
|
||||
return `[citation:[${source.index}]](#reference-${source.index})`;
|
||||
return citationLinkMarkdown(source);
|
||||
}
|
||||
|
||||
function hasCitationMarkdown(content: string): boolean {
|
||||
return /\[citation:\[[^\]]+\]\]\(#reference-[^)]+\)/.test(content);
|
||||
return /\[citation:(?:\[[^\]]+\]|\d+)\]\(#reference-[^)]+\)/.test(content);
|
||||
}
|
||||
|
||||
function appendCitationSummary(
|
||||
@@ -693,7 +781,7 @@ function appendCitationSummary(
|
||||
): string {
|
||||
const citations = citationSources
|
||||
.slice(0, 5)
|
||||
.map((source) => `[citation:[${source.index}]](#reference-${source.index})`)
|
||||
.map((source) => citationLinkMarkdown(source))
|
||||
.join(" ");
|
||||
if (!citations) {
|
||||
return content;
|
||||
@@ -702,10 +790,22 @@ function appendCitationSummary(
|
||||
return `${trimmed}${trimmed ? "\n\n" : ""}参考来源：${citations}`;
|
||||
}
|
||||
|
||||
function citationLinkMarkdown(source: RuntimeDisplaySource): string {
|
||||
return `[citation:${source.index}](#reference-${source.index})`;
|
||||
}
|
||||
|
||||
function normalizeName(name: string): string {
|
||||
return name.toLowerCase().replace(/[^a-z0-9]+/g, "");
|
||||
}
|
||||
|
||||
function normalizeCitationKey(value: string): string {
|
||||
return value
|
||||
.toLowerCase()
|
||||
.normalize("NFKC")
|
||||
.replace(/\s+/g, " ")
|
||||
.trim();
|
||||
}
|
||||
|
||||
function isRecord(value: unknown): value is Record<string, unknown> {
|
||||
return !!value && typeof value === "object" && !Array.isArray(value);
|
||||
}
|
||||
@@ -714,18 +814,28 @@ function stringifyMaybe(value: unknown): string | undefined {
|
||||
return typeof value === "string" && value.trim() ? value : undefined;
|
||||
}
|
||||
|
||||
function findToolResultPayload(
|
||||
function findToolResultMessage(
|
||||
toolCall: RuntimeToolCall,
|
||||
messages: Message[],
|
||||
toolCallMessageIndex = -1,
|
||||
): unknown {
|
||||
const toolMessage =
|
||||
findToolMessageById(toolCall.id, messages) ??
|
||||
findToolMessageByName(toolCall, messages, toolCallMessageIndex);
|
||||
if (!toolMessage) {
|
||||
return undefined;
|
||||
consumedToolMessageIds?: Set<string>,
|
||||
consumedToolMessages?: Set<Message>,
|
||||
): Message | undefined {
|
||||
const byId = findToolMessageById(toolCall.id, messages);
|
||||
if (
|
||||
byId &&
|
||||
!consumedToolMessages?.has(byId) &&
|
||||
(!byId.id || !consumedToolMessageIds?.has(byId.id))
|
||||
) {
|
||||
return byId;
|
||||
}
|
||||
return parseToolMessagePayload(toolMessage);
|
||||
return findToolMessageByName(
|
||||
toolCall,
|
||||
messages,
|
||||
toolCallMessageIndex,
|
||||
consumedToolMessageIds,
|
||||
consumedToolMessages,
|
||||
);
|
||||
}
|
||||
|
||||
function parseToolMessagePayload(toolMessage: Message): unknown {
|
||||
@@ -782,6 +892,8 @@ function findToolMessageByName(
|
||||
toolCall: RuntimeToolCall,
|
||||
messages: Message[],
|
||||
toolCallMessageIndex: number,
|
||||
consumedToolMessageIds?: Set<string>,
|
||||
consumedToolMessages?: Set<Message>,
|
||||
): Message | undefined {
|
||||
const start = Math.max(toolCallMessageIndex + 1, 0);
|
||||
for (let index = start; index < messages.length; index++) {
|
||||
@@ -795,6 +907,12 @@ function findToolMessageByName(
|
||||
if (message.type !== "tool") {
|
||||
continue;
|
||||
}
|
||||
if (message.id && consumedToolMessageIds?.has(message.id)) {
|
||||
continue;
|
||||
}
|
||||
if (consumedToolMessages?.has(message)) {
|
||||
continue;
|
||||
}
|
||||
const name =
|
||||
stringifyMaybe((message as { name?: unknown }).name) ??
|
||||
stringifyMaybe(
|
||||
|
||||
@@ -53,6 +53,14 @@ export interface PrivateSquareUpdate {
|
||||
password?: string;
|
||||
}
|
||||
|
||||
export interface CitationDisplaySettings {
|
||||
cleanup_words: string[];
|
||||
}
|
||||
|
||||
export interface CitationDisplayUpdate {
|
||||
cleanup_words?: string[];
|
||||
}
|
||||
|
||||
export async function loadPrivateSquareStatus(): Promise<PrivateSquareStatus> {
|
||||
const response = await apiFetch(
|
||||
`${getBackendBaseURL()}/api/system-settings/private-square`,
|
||||
@@ -107,6 +115,38 @@ export async function updateAppearanceSettings(
|
||||
return (await response.json()) as AppearanceSettings;
|
||||
}
|
||||
|
||||
export async function loadCitationDisplaySettings(): Promise<CitationDisplaySettings> {
|
||||
const response = await apiFetch(
|
||||
`${getBackendBaseURL()}/api/system-settings/citation-display`,
|
||||
);
|
||||
if (!response.ok) {
|
||||
throw new Error(
|
||||
`Failed to load citation display settings: ${response.status}`,
|
||||
);
|
||||
}
|
||||
return (await response.json()) as CitationDisplaySettings;
|
||||
}
|
||||
|
||||
export async function updateCitationDisplaySettings(
|
||||
body: CitationDisplayUpdate,
|
||||
): Promise<CitationDisplaySettings> {
|
||||
const response = await apiFetch(
|
||||
`${getBackendBaseURL()}/api/system-settings/citation-display`,
|
||||
{
|
||||
method: "PUT",
|
||||
headers: { "Content-Type": "application/json" },
|
||||
body: JSON.stringify(body),
|
||||
},
|
||||
);
|
||||
if (!response.ok) {
|
||||
const detail = await response
|
||||
.json()
|
||||
.catch(() => ({ detail: "Failed to update citation display" }));
|
||||
throw new Error(detail.detail ?? "Failed to update citation display");
|
||||
}
|
||||
return (await response.json()) as CitationDisplaySettings;
|
||||
}
|
||||
|
||||
export async function updatePrivateSquareSettings(
|
||||
body: PrivateSquareUpdate,
|
||||
): Promise<PrivateSquareStatus> {
|
||||
|
||||
@@ -2,12 +2,15 @@ import { useMutation, useQuery, useQueryClient } from "@tanstack/react-query";
|
||||
|
||||
import {
|
||||
loadAppearanceSettings,
|
||||
loadCitationDisplaySettings,
|
||||
loadPrivateSquareStatus,
|
||||
loadPromptPrefixSettings,
|
||||
updateAppearanceSettings,
|
||||
updateCitationDisplaySettings,
|
||||
updatePrivateSquareSettings,
|
||||
updatePromptPrefixSettings,
|
||||
type AppearanceUpdate,
|
||||
type CitationDisplayUpdate,
|
||||
type PrivateSquareUpdate,
|
||||
type PromptPrefixUpdate,
|
||||
} from "./api";
|
||||
@@ -15,6 +18,7 @@ import {
|
||||
const PROMPT_PREFIX_KEY = ["systemSettings", "promptPrefix"] as const;
|
||||
const PRIVATE_SQUARE_KEY = ["systemSettings", "privateSquare"] as const;
|
||||
const APPEARANCE_KEY = ["systemSettings", "appearance"] as const;
|
||||
const CITATION_DISPLAY_KEY = ["systemSettings", "citationDisplay"] as const;
|
||||
|
||||
export function usePromptPrefixSettings() {
|
||||
return useQuery({
|
||||
@@ -77,3 +81,24 @@ export function useUpdateAppearanceSettings() {
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
export function useCitationDisplaySettings() {
|
||||
return useQuery({
|
||||
queryKey: CITATION_DISPLAY_KEY,
|
||||
queryFn: () => loadCitationDisplaySettings(),
|
||||
staleTime: 60_000,
|
||||
refetchOnWindowFocus: false,
|
||||
retry: false,
|
||||
});
|
||||
}
|
||||
|
||||
export function useUpdateCitationDisplaySettings() {
|
||||
const queryClient = useQueryClient();
|
||||
return useMutation({
|
||||
mutationFn: (body: CitationDisplayUpdate) =>
|
||||
updateCitationDisplaySettings(body),
|
||||
onSuccess: (data) => {
|
||||
queryClient.setQueryData(CITATION_DISPLAY_KEY, data);
|
||||
},
|
||||
});
|
||||
}
|
||||
@@ -3,17 +3,19 @@ import type { ThreadsClient } from "@langchain/langgraph-sdk/client";
|
||||
import { useStream } from "@langchain/langgraph-sdk/react";
|
||||
import { useMutation, useQuery, useQueryClient } from "@tanstack/react-query";
|
||||
import { useCallback, useEffect, useRef, useState } from "react";
|
||||
import { useNavigate } from "react-router-dom";
|
||||
import { toast } from "sonner";
|
||||
|
||||
import type { PromptInputMessage } from "@/components/ai-elements/prompt-input";
|
||||
|
||||
import { getAPIClient } from "../api";
|
||||
import { apiFetch } from "../api";
|
||||
import { getStoredAuth } from "../auth";
|
||||
import { getBackendBaseURL } from "../config";
|
||||
import { useI18n } from "../i18n/hooks";
|
||||
import type { FileInMessage } from "../messages/utils";
|
||||
import type { LocalSettings } from "../settings";
|
||||
import { useLocalSettings } from "../settings";
|
||||
import type { LocalSettings } from "../settings";
|
||||
import { isThreadRagModeLocked, lockThreadRagMode, useLocalSettings } from "../settings";
|
||||
import { useUpdateSubtask } from "../tasks/context";
|
||||
import type { UploadedFileInfo } from "../uploads";
|
||||
import { promptInputFilePartToFile, uploadFiles } from "../uploads";
|
||||
@@ -137,6 +139,42 @@ function getStreamErrorMessage(error: unknown): string {
|
||||
return "Request failed.";
|
||||
}
|
||||
|
||||
/**
|
||||
* Detect "thread not found" / forbidden errors from the LangGraph SDK.
|
||||
*
|
||||
* Backend returns 404 both when a thread truly doesn't exist and when the
|
||||
* currently authenticated user doesn't own it — the SDK surfaces both as
|
||||
* ``HTTP 404: {"detail":"Thread <uuid> not found"}``. The most common cause
|
||||
* we see in practice is a stale tab whose URL still points at the previous
|
||||
* login session's thread. Raw-toasting the 404 just confuses the user, so
|
||||
* we re-frame it around the current login identity.
|
||||
*/
|
||||
function isThreadNotAccessibleError(message: string): boolean {
|
||||
const lowered = message.toLowerCase();
|
||||
if (/thread\s+[\w-]{8,}\s+not\s+found/i.test(message)) {
|
||||
return true;
|
||||
}
|
||||
// Fallback: a bare 404/403 from the threads endpoint when the SDK has
|
||||
// wrapped the detail differently.
|
||||
return (
|
||||
(lowered.includes("http 404") || lowered.includes("http 403")) &&
|
||||
lowered.includes("thread")
|
||||
);
|
||||
}
|
||||
|
||||
function buildCurrentUserLabel(): string {
|
||||
const auth = getStoredAuth();
|
||||
if (!auth) {
|
||||
return "未登录";
|
||||
}
|
||||
const email = auth.email?.trim();
|
||||
if (email) {
|
||||
return email;
|
||||
}
|
||||
const userId = auth.user_id?.trim();
|
||||
return userId ? userId : "未知用户";
|
||||
}
|
||||
|
||||
export function useThreadStream({
|
||||
threadId,
|
||||
context,
|
||||
@@ -195,6 +233,7 @@ export function useThreadStream({
|
||||
|
||||
const queryClient = useQueryClient();
|
||||
const updateSubtask = useUpdateSubtask();
|
||||
const navigate = useNavigate();
|
||||
const runMetadataStorageRef = useRef<
|
||||
ReturnType<typeof getRunMetadataStorage> | undefined
|
||||
>(undefined);
|
||||
@@ -294,7 +333,29 @@ export function useThreadStream({
|
||||
},
|
||||
onError(error) {
|
||||
setOptimisticMessages([]);
|
||||
toast.error(getStreamErrorMessage(error));
|
||||
const message = getStreamErrorMessage(error);
|
||||
// A "thread not found" 404 almost always means the URL points at a
|
||||
// thread from a previous login session — either this tab outlived a
|
||||
// logout/re-login or the thread genuinely belongs to a different user.
|
||||
// Re-frame the error around the *current* logged-in identity and bounce
|
||||
// the user to a fresh chat instead of leaving them stuck on the stale
|
||||
// route looking at a raw HTTP 404.
|
||||
if (isThreadNotAccessibleError(message)) {
|
||||
const userLabel = buildCurrentUserLabel();
|
||||
toast.info(
|
||||
`当前登录用户为 ${userLabel}，原对话不存在或无权访问，已为你打开新对话。`,
|
||||
);
|
||||
// Prefer staying inside an agent chat context when the user is on an
|
||||
// agent thread URL — otherwise fall back to the global new chat.
|
||||
const hash = typeof window !== "undefined" ? window.location.hash : "";
|
||||
const agentMatch = hash.match(/#\/page\/workspace\/agents\/([^/]+)\//);
|
||||
const target = agentMatch
|
||||
? `/page/workspace/agents/${agentMatch[1]}/chats/new`
|
||||
: "/page/workspace/chats/new";
|
||||
navigate(target, { replace: true });
|
||||
return;
|
||||
}
|
||||
toast.error(message);
|
||||
},
|
||||
onFinish(state) {
|
||||
listeners.current.onFinish?.(state.values);
|
||||
@@ -494,7 +555,13 @@ export function useThreadStream({
|
||||
}),
|
||||
);
|
||||
|
||||
await thread.submit(
|
||||
const ragModeEnabled =
|
||||
localSettings.display.ragModeEnabled || isThreadRagModeLocked(threadId);
|
||||
if (ragModeEnabled) {
|
||||
lockThreadRagMode(threadId);
|
||||
}
|
||||
|
||||
await thread.submit(
|
||||
{
|
||||
messages: [
|
||||
{
|
||||
@@ -537,10 +604,10 @@ export function useThreadStream({
|
||||
? "low"
|
||||
: undefined),
|
||||
memory_injection_enabled: context.memory_injection_enabled ?? true,
|
||||
rag_mode_enabled: localSettings.display.ragModeEnabled,
|
||||
thread_id: threadId,
|
||||
},
|
||||
},
|
||||
rag_mode_enabled: ragModeEnabled,
|
||||
thread_id: threadId,
|
||||
},
|
||||
},
|
||||
);
|
||||
void queryClient.invalidateQueries({ queryKey: ["threads", "search"] });
|
||||
} catch (error) {
|
||||
|
||||
@@ -567,6 +567,20 @@
|
||||
transform: translateY(-50%) scale(1);
|
||||
}
|
||||
}
|
||||
|
||||
@keyframes reference-flash {
|
||||
0% {
|
||||
background: rgba(254, 243, 199, 0.95);
|
||||
box-shadow: 0 0 0 4px rgba(251, 191, 36, 0.28);
|
||||
}
|
||||
70% {
|
||||
background: rgba(254, 243, 199, 0.58);
|
||||
box-shadow: 0 0 0 2px rgba(251, 191, 36, 0.14);
|
||||
}
|
||||
100% {
|
||||
box-shadow: none;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/* ─── Tiptap writing editor ─────────────────────────────────────────────── */
|
||||
@@ -818,4 +832,4 @@
|
||||
* {
|
||||
border-color: var(--border);
|
||||
outline-color: var(--ring);
|
||||
}
|
||||
}
|
||||
@@ -49,6 +49,14 @@ class PrivateSquareUpdateRequest(BaseModel):
|
||||
password: str | None = Field(default=None, description="New password in plain text. Pass an empty string to clear.")
|
||||
|
||||
|
||||
class CitationDisplayResponse(BaseModel):
|
||||
cleanup_words: list[str] = Field(default_factory=list, description="Global citation cleanup words")
|
||||
|
||||
|
||||
class CitationDisplayUpdateRequest(BaseModel):
|
||||
cleanup_words: list[str] | None = None
|
||||
|
||||
|
||||
def _to_response(settings: PromptPrefixSettings) -> PromptPrefixResponse:
|
||||
return PromptPrefixResponse(
|
||||
enabled=settings.enabled,
|
||||
@@ -83,6 +91,34 @@ async def update_prompt_prefix(body: PromptPrefixUpdateRequest, request: Request
|
||||
return _to_response(saved.prompt_prefix)
|
||||
|
||||
|
||||
@router.get("/citation-display", response_model=CitationDisplayResponse)
|
||||
async def get_citation_display() -> CitationDisplayResponse:
|
||||
"""Return global citation display cleanup settings."""
|
||||
settings = load_system_settings().citation_display
|
||||
return CitationDisplayResponse(cleanup_words=settings.cleanup_words)
|
||||
|
||||
|
||||
@router.put("/citation-display", response_model=CitationDisplayResponse)
|
||||
async def update_citation_display(
|
||||
body: CitationDisplayUpdateRequest,
|
||||
request: Request,
|
||||
) -> CitationDisplayResponse:
|
||||
"""Update global citation display cleanup settings. Admin only."""
|
||||
await _require_admin(request)
|
||||
|
||||
current = load_system_settings()
|
||||
words = [
|
||||
str(item).strip()
|
||||
for item in (body.cleanup_words or [])
|
||||
if str(item).strip()
|
||||
]
|
||||
updated = current.citation_display.model_copy(update={"cleanup_words": words})
|
||||
saved = save_system_settings(
|
||||
current.model_copy(update={"citation_display": updated})
|
||||
)
|
||||
return CitationDisplayResponse(cleanup_words=saved.citation_display.cleanup_words)
|
||||
|
||||
|
||||
@router.get("/private-square", response_model=PrivateSquareStatusResponse)
|
||||
async def get_private_square_status() -> PrivateSquareStatusResponse:
|
||||
"""Return whether the private square is enabled and a password is set."""
|
||||
|
||||
@@ -12,9 +12,12 @@ matching the LangGraph Platform wire format expected by the
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import uuid
|
||||
from typing import Any
|
||||
import logging
|
||||
import json
|
||||
import os
|
||||
from pathlib import Path
|
||||
import uuid
|
||||
from typing import Any
|
||||
|
||||
from fastapi import APIRouter, HTTPException, Request
|
||||
from langgraph.checkpoint.base import empty_checkpoint
|
||||
@@ -23,13 +26,18 @@ from pydantic import BaseModel, Field, field_validator
|
||||
from app.gateway.authz import require_permission
|
||||
from app.gateway.deps import get_checkpointer
|
||||
from app.gateway.utils import sanitize_log_param
|
||||
from deerflow.config.paths import Paths, get_paths
|
||||
from deerflow.runtime import serialize_channel_values
|
||||
from deerflow.runtime.user_context import get_effective_user_id
|
||||
from deerflow.utils.time import coerce_iso, now_iso
|
||||
from deerflow.config.paths import Paths, get_paths
|
||||
from deerflow.runtime import serialize_channel_values
|
||||
from deerflow.runtime.references import (
|
||||
build_reference_batches as build_runtime_reference_batches,
|
||||
build_reference_debug_summary,
|
||||
)
|
||||
from deerflow.runtime.user_context import get_effective_user_id
|
||||
from deerflow.utils.time import coerce_iso, now_iso
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
router = APIRouter(prefix="/api/threads", tags=["threads"])
|
||||
logger = logging.getLogger(__name__)
|
||||
router = APIRouter(prefix="/api/threads", tags=["threads"])
|
||||
_RAG_DEBUG_LOGGER_NAME = "rag_citation_debug"
|
||||
|
||||
|
||||
# Metadata keys that the server controls; clients are not allowed to set
|
||||
@@ -41,11 +49,38 @@ router = APIRouter(prefix="/api/threads", tags=["threads"])
|
||||
_SERVER_RESERVED_METADATA_KEYS: frozenset[str] = frozenset({"owner_id", "user_id"})
|
||||
|
||||
|
||||
def _strip_reserved_metadata(metadata: dict[str, Any] | None) -> dict[str, Any]:
|
||||
"""Return ``metadata`` with server-controlled keys removed."""
|
||||
if not metadata:
|
||||
return metadata or {}
|
||||
return {k: v for k, v in metadata.items() if k not in _SERVER_RESERVED_METADATA_KEYS}
|
||||
def _strip_reserved_metadata(metadata: dict[str, Any] | None) -> dict[str, Any]:
|
||||
"""Return ``metadata`` with server-controlled keys removed."""
|
||||
if not metadata:
|
||||
return metadata or {}
|
||||
return {k: v for k, v in metadata.items() if k not in _SERVER_RESERVED_METADATA_KEYS}
|
||||
|
||||
|
||||
def _get_rag_debug_logger() -> logging.Logger:
|
||||
debug_logger = logging.getLogger(_RAG_DEBUG_LOGGER_NAME)
|
||||
if getattr(debug_logger, "_rag_file_configured", False):
|
||||
return debug_logger
|
||||
log_path = Path(os.environ.get("RAG_CITATION_DEBUG_LOG", "logs/rag_citation_debug.log"))
|
||||
if not log_path.is_absolute():
|
||||
log_path = Path.cwd() / log_path
|
||||
log_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
handler = logging.FileHandler(log_path, encoding="utf-8")
|
||||
handler.setFormatter(logging.Formatter("%(asctime)s %(levelname)s %(message)s"))
|
||||
debug_logger.addHandler(handler)
|
||||
debug_logger.setLevel(logging.INFO)
|
||||
debug_logger.propagate = False
|
||||
setattr(debug_logger, "_rag_file_configured", True)
|
||||
setattr(debug_logger, "_rag_file_path", str(log_path))
|
||||
return debug_logger
|
||||
|
||||
|
||||
def _rag_debug_file_path() -> str:
|
||||
return str(getattr(_get_rag_debug_logger(), "_rag_file_path", "logs/rag_citation_debug.log"))
|
||||
|
||||
|
||||
def _log_rag_debug(message: str, *args: Any) -> None:
|
||||
logger.info(message, *args)
|
||||
_get_rag_debug_logger().info(message, *args)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
@@ -132,11 +167,43 @@ class HistoryEntry(BaseModel):
|
||||
next: list[str] = Field(default_factory=list)
|
||||
|
||||
|
||||
class ThreadHistoryRequest(BaseModel):
|
||||
class ThreadHistoryRequest(BaseModel):
|
||||
"""Request body for checkpoint history."""
|
||||
|
||||
limit: int = Field(default=10, ge=1, le=100, description="Maximum entries")
|
||||
before: str | None = Field(default=None, description="Cursor for pagination")
|
||||
before: str | None = Field(default=None, description="Cursor for pagination")
|
||||
|
||||
|
||||
class ReferenceSourceResponse(BaseModel):
|
||||
index: int
|
||||
id: str | None = None
|
||||
skillName: str = "backend-reference"
|
||||
mode: str = "citation"
|
||||
title: str
|
||||
type: str = "result"
|
||||
snippet: str = ""
|
||||
source: str | None = None
|
||||
time: str | None = None
|
||||
url: str | None = None
|
||||
content: str | None = None
|
||||
score: float | None = None
|
||||
raw: dict[str, Any] = Field(default_factory=dict)
|
||||
|
||||
|
||||
class ReferenceBatchResponse(BaseModel):
|
||||
id: str
|
||||
assistant_message_id: str
|
||||
sources: list[ReferenceSourceResponse] = Field(default_factory=list)
|
||||
|
||||
|
||||
class ReferenceBatchesResponse(BaseModel):
|
||||
batches: list[ReferenceBatchResponse] = Field(default_factory=list)
|
||||
|
||||
|
||||
class ReferenceDebugLogRequest(BaseModel):
|
||||
event: str
|
||||
thread_id: str | None = None
|
||||
payload: dict[str, Any] = Field(default_factory=dict)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
@@ -163,7 +230,7 @@ def _delete_thread_data(thread_id: str, paths: Paths | None = None, *, user_id:
|
||||
return ThreadDeleteResponse(success=True, message=f"Deleted local thread data for {thread_id}")
|
||||
|
||||
|
||||
def _derive_thread_status(checkpoint_tuple) -> str:
|
||||
def _derive_thread_status(checkpoint_tuple) -> str:
|
||||
"""Derive thread status from checkpoint metadata."""
|
||||
if checkpoint_tuple is None:
|
||||
return "idle"
|
||||
@@ -179,7 +246,251 @@ def _derive_thread_status(checkpoint_tuple) -> str:
|
||||
if tasks:
|
||||
return "interrupted"
|
||||
|
||||
return "idle"
|
||||
return "idle"
|
||||
|
||||
|
||||
def _message_type(message: Any) -> str:
|
||||
if isinstance(message, dict):
|
||||
return str(message.get("type") or message.get("role") or "")
|
||||
return str(getattr(message, "type", "") or "")
|
||||
|
||||
|
||||
def _message_id(message: Any) -> str | None:
|
||||
if isinstance(message, dict):
|
||||
value = message.get("id")
|
||||
else:
|
||||
value = getattr(message, "id", None)
|
||||
return str(value) if value else None
|
||||
|
||||
|
||||
def _message_content(message: Any) -> Any:
|
||||
if isinstance(message, dict):
|
||||
return message.get("content")
|
||||
return getattr(message, "content", None)
|
||||
|
||||
|
||||
def _message_name(message: Any) -> str:
|
||||
if isinstance(message, dict):
|
||||
return str(message.get("name") or (message.get("additional_kwargs") or {}).get("name") or "tool")
|
||||
return str(getattr(message, "name", None) or "tool")
|
||||
|
||||
|
||||
def _has_tool_calls(message: Any) -> bool:
|
||||
if isinstance(message, dict):
|
||||
direct = message.get("tool_calls")
|
||||
chunks = message.get("tool_call_chunks")
|
||||
extra = (message.get("additional_kwargs") or {}).get("tool_calls")
|
||||
else:
|
||||
direct = getattr(message, "tool_calls", None)
|
||||
chunks = getattr(message, "tool_call_chunks", None)
|
||||
extra = (getattr(message, "additional_kwargs", None) or {}).get("tool_calls")
|
||||
return bool(direct or chunks or extra)
|
||||
|
||||
|
||||
def _has_answer_content(message: Any) -> bool:
|
||||
content = _message_content(message)
|
||||
if isinstance(content, str):
|
||||
return bool(content.strip())
|
||||
if isinstance(content, list):
|
||||
for part in content:
|
||||
if isinstance(part, dict) and part.get("type") == "text" and str(part.get("text") or "").strip():
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
def _extract_tool_payload(message: Any) -> Any:
|
||||
content = _message_content(message)
|
||||
if isinstance(content, dict):
|
||||
return _unwrap_tool_payload(content)
|
||||
if isinstance(content, list):
|
||||
texts: list[str] = []
|
||||
for part in content:
|
||||
if not isinstance(part, dict):
|
||||
continue
|
||||
if isinstance(part.get("json"), dict):
|
||||
return _unwrap_tool_payload(part["json"])
|
||||
if part.get("type") == "json" and isinstance(part.get("json"), dict):
|
||||
return _unwrap_tool_payload(part["json"])
|
||||
if part.get("type") == "text" and isinstance(part.get("text"), str):
|
||||
texts.append(part["text"])
|
||||
unwrapped = _unwrap_tool_payload(part)
|
||||
if unwrapped is not None:
|
||||
return unwrapped
|
||||
content = "\n".join(texts)
|
||||
if isinstance(content, str):
|
||||
return _parse_json_like(content)
|
||||
return None
|
||||
|
||||
|
||||
def _unwrap_tool_payload(value: dict[str, Any]) -> Any:
|
||||
if any(isinstance(value.get(key), list) for key in ("results", "data", "items", "hits", "documents", "records", "sources")):
|
||||
return value
|
||||
for key in ("result", "output", "stdout", "content", "text", "payload", "response"):
|
||||
nested = value.get(key)
|
||||
if isinstance(nested, str):
|
||||
parsed = _parse_json_like(nested)
|
||||
if parsed is not None:
|
||||
return parsed
|
||||
if isinstance(nested, dict):
|
||||
unwrapped = _unwrap_tool_payload(nested)
|
||||
if unwrapped is not None:
|
||||
return unwrapped
|
||||
return value
|
||||
|
||||
|
||||
def _parse_json_like(text: str) -> Any:
|
||||
trimmed = text.strip()
|
||||
if not trimmed:
|
||||
return None
|
||||
try:
|
||||
return json.loads(trimmed)
|
||||
except Exception:
|
||||
pass
|
||||
first_obj = trimmed.find("{")
|
||||
last_obj = trimmed.rfind("}")
|
||||
if 0 <= first_obj < last_obj:
|
||||
try:
|
||||
return json.loads(trimmed[first_obj : last_obj + 1])
|
||||
except Exception:
|
||||
return None
|
||||
return None
|
||||
|
||||
|
||||
def _first_list(payload: Any) -> list[Any]:
|
||||
if isinstance(payload, list):
|
||||
return payload
|
||||
if not isinstance(payload, dict):
|
||||
return []
|
||||
for key in ("results", "data", "items", "hits", "documents", "records", "entries", "matches", "chunks", "sources"):
|
||||
value = payload.get(key)
|
||||
if isinstance(value, list):
|
||||
return value
|
||||
for key in ("result", "payload", "response", "output", "data"):
|
||||
nested = payload.get(key)
|
||||
found = _first_list(nested)
|
||||
if found:
|
||||
return found
|
||||
return []
|
||||
|
||||
|
||||
def _nested_records(raw: Any) -> list[dict[str, Any]]:
|
||||
if not isinstance(raw, dict):
|
||||
return []
|
||||
layers = [raw]
|
||||
for key in ("metadata", "meta", "attrs", "attributes", "properties", "extra"):
|
||||
nested = raw.get(key)
|
||||
if isinstance(nested, dict):
|
||||
layers.append(nested)
|
||||
return layers
|
||||
|
||||
|
||||
def _pick(layers: list[dict[str, Any]], keys: tuple[str, ...]) -> str | None:
|
||||
for layer in layers:
|
||||
for key in keys:
|
||||
value = layer.get(key)
|
||||
if isinstance(value, (str, int, float)) and str(value).strip():
|
||||
return str(value).strip()
|
||||
return None
|
||||
|
||||
|
||||
def _normalize_reference_item(raw: Any, fallback_index: int) -> dict[str, Any] | None:
|
||||
if not isinstance(raw, dict):
|
||||
return None
|
||||
layers = _nested_records(raw)
|
||||
title = _pick(layers, ("title", "m_title", "name", "question", "keyword", "query", "text"))
|
||||
content = _pick(layers, ("content", "page_content", "summary", "snippet", "description", "content_preview", "abstract", "body"))
|
||||
url = _pick(layers, ("url", "link", "href", "source_url", "web_url"))
|
||||
source = _pick(layers, ("source", "source1", "site", "provider", "from"))
|
||||
time = _pick(layers, ("time", "date", "published_date", "publishedDate", "m_publish", "publish_time", "created_at"))
|
||||
item_id = _pick(layers, ("recUuid", "rec_uuid", "uuid", "docId", "doc_id", "id", "recordId", "taskId"))
|
||||
score_raw = _pick(layers, ("score", "relevance", "similarity"))
|
||||
score = None
|
||||
if score_raw is not None:
|
||||
try:
|
||||
score = float(score_raw)
|
||||
except Exception:
|
||||
score = None
|
||||
if not title:
|
||||
title = source or f"结果 {fallback_index}"
|
||||
if not content:
|
||||
content = ""
|
||||
if not title and not content and not url:
|
||||
return None
|
||||
return {
|
||||
"id": item_id or url,
|
||||
"title": title,
|
||||
"type": "result",
|
||||
"snippet": content,
|
||||
"content": content,
|
||||
"source": source,
|
||||
"time": time,
|
||||
"url": url,
|
||||
"score": score,
|
||||
"raw": raw,
|
||||
}
|
||||
|
||||
|
||||
def _reference_key(source: dict[str, Any]) -> str:
|
||||
raw = source.get("raw") if isinstance(source.get("raw"), dict) else {}
|
||||
item_id = (
|
||||
source.get("id")
|
||||
or source.get("url")
|
||||
or raw.get("recUuid")
|
||||
or raw.get("uuid")
|
||||
or raw.get("docId")
|
||||
or raw.get("id")
|
||||
)
|
||||
if item_id:
|
||||
return str(item_id).casefold().strip()
|
||||
return "|".join(
|
||||
str(source.get(key) or "").casefold().strip()
|
||||
for key in ("title", "source", "time", "content", "snippet")
|
||||
)
|
||||
|
||||
|
||||
def _build_reference_batches(messages: list[Any]) -> list[ReferenceBatchResponse]:
|
||||
batches: list[ReferenceBatchResponse] = []
|
||||
for index, message in enumerate(messages):
|
||||
if _message_type(message) != "human":
|
||||
continue
|
||||
end = len(messages)
|
||||
for cursor in range(index + 1, len(messages)):
|
||||
if _message_type(messages[cursor]) == "human":
|
||||
end = cursor
|
||||
break
|
||||
assistant_message: Any | None = None
|
||||
for cursor in range(end - 1, index, -1):
|
||||
candidate = messages[cursor]
|
||||
if (
|
||||
_message_type(candidate) == "ai"
|
||||
and _message_id(candidate)
|
||||
and _has_answer_content(candidate)
|
||||
and not _has_tool_calls(candidate)
|
||||
):
|
||||
assistant_message = candidate
|
||||
break
|
||||
if assistant_message is None:
|
||||
continue
|
||||
seen: set[str] = set()
|
||||
sources: list[ReferenceSourceResponse] = []
|
||||
for tool_message in messages[index + 1 : end]:
|
||||
if _message_type(tool_message) != "tool":
|
||||
continue
|
||||
payload = _extract_tool_payload(tool_message)
|
||||
for raw_item in _first_list(payload):
|
||||
normalized = _normalize_reference_item(raw_item, len(sources) + 1)
|
||||
if not normalized:
|
||||
continue
|
||||
key = _reference_key(normalized)
|
||||
if key and key in seen:
|
||||
continue
|
||||
if key:
|
||||
seen.add(key)
|
||||
sources.append(ReferenceSourceResponse(index=len(sources) + 1, **normalized))
|
||||
if sources:
|
||||
mid = _message_id(assistant_message) or str(index)
|
||||
batches.append(ReferenceBatchResponse(id=mid, assistant_message_id=mid, sources=sources))
|
||||
return batches
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
@@ -406,9 +717,9 @@ async def get_thread(thread_id: str, request: Request) -> ThreadResponse:
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
@router.get("/{thread_id}/state", response_model=ThreadStateResponse)
|
||||
@require_permission("threads", "read", owner_check=True)
|
||||
async def get_thread_state(thread_id: str, request: Request) -> ThreadStateResponse:
|
||||
@router.get("/{thread_id}/state", response_model=ThreadStateResponse)
|
||||
@require_permission("threads", "read", owner_check=True)
|
||||
async def get_thread_state(thread_id: str, request: Request) -> ThreadStateResponse:
|
||||
"""Get the latest state snapshot for a thread.
|
||||
|
||||
Channel values are serialized to ensure LangChain message objects
|
||||
@@ -455,12 +766,84 @@ async def get_thread_state(thread_id: str, request: Request) -> ThreadStateRespo
|
||||
parent_checkpoint_id=parent_checkpoint_id,
|
||||
created_at=coerce_iso(metadata.get("created_at", "")),
|
||||
tasks=tasks,
|
||||
)
|
||||
|
||||
|
||||
@router.post("/{thread_id}/state", response_model=ThreadStateResponse)
|
||||
@require_permission("threads", "write", owner_check=True, require_existing=True)
|
||||
async def update_thread_state(thread_id: str, body: ThreadStateUpdateRequest, request: Request) -> ThreadStateResponse:
|
||||
)
|
||||
|
||||
|
||||
@router.get("/{thread_id}/reference-batches", response_model=ReferenceBatchesResponse)
|
||||
@require_permission("threads", "read", owner_check=True)
|
||||
async def get_thread_reference_batches(thread_id: str, request: Request) -> ReferenceBatchesResponse:
|
||||
"""Return backend-built citation batches for completed assistant turns."""
|
||||
checkpointer = get_checkpointer(request)
|
||||
config = {"configurable": {"thread_id": thread_id, "checkpoint_ns": ""}}
|
||||
try:
|
||||
checkpoint_tuple = await checkpointer.aget_tuple(config)
|
||||
except Exception:
|
||||
logger.exception("Failed to get reference batches for thread %s", sanitize_log_param(thread_id))
|
||||
raise HTTPException(status_code=500, detail="Failed to get reference batches")
|
||||
|
||||
if checkpoint_tuple is None:
|
||||
raise HTTPException(status_code=404, detail=f"Thread {thread_id} not found")
|
||||
|
||||
checkpoint = getattr(checkpoint_tuple, "checkpoint", {}) or {}
|
||||
values = serialize_channel_values(checkpoint.get("channel_values", {}) or {})
|
||||
messages = values.get("messages")
|
||||
if not isinstance(messages, list):
|
||||
_log_rag_debug(
|
||||
"backend reference-batches thread=%s messages=missing batches=0 log_file=%s",
|
||||
sanitize_log_param(thread_id),
|
||||
_rag_debug_file_path(),
|
||||
)
|
||||
return ReferenceBatchesResponse(batches=[])
|
||||
raw_batches = build_runtime_reference_batches(messages)
|
||||
debug_summary = build_reference_debug_summary(messages, raw_batches)
|
||||
_log_rag_debug(
|
||||
"backend reference-batches thread=%s messages=%s turns=%s tool_messages=%s raw_items=%s "
|
||||
"normalized_items=%s kept_items=%s batches=%s batch_sources=%s batch_ids=%s turns_detail=%s log_file=%s",
|
||||
sanitize_log_param(thread_id),
|
||||
debug_summary["messages"],
|
||||
debug_summary["turns"],
|
||||
debug_summary["tool_messages"],
|
||||
debug_summary["raw_items"],
|
||||
debug_summary["normalized_items"],
|
||||
debug_summary["kept_items"],
|
||||
len(raw_batches),
|
||||
",".join(str(batch.get("source_count", 0)) for batch in debug_summary["batches"]),
|
||||
",".join(str(batch.get("id") or "") for batch in debug_summary["batches"]),
|
||||
json.dumps(debug_summary["turns_detail"], ensure_ascii=False),
|
||||
_rag_debug_file_path(),
|
||||
)
|
||||
return ReferenceBatchesResponse(
|
||||
batches=[
|
||||
ReferenceBatchResponse(
|
||||
id=str(batch.get("id") or ""),
|
||||
assistant_message_id=str(batch.get("assistant_message_id") or batch.get("id") or ""),
|
||||
sources=[
|
||||
ReferenceSourceResponse(**source)
|
||||
for source in batch.get("sources", [])
|
||||
if isinstance(source, dict)
|
||||
],
|
||||
)
|
||||
for batch in raw_batches
|
||||
]
|
||||
)
|
||||
|
||||
|
||||
@router.post("/reference-debug-log")
|
||||
async def write_reference_debug_log(body: ReferenceDebugLogRequest) -> dict[str, str | bool]:
|
||||
"""Append frontend citation diagnostics to the backend RAG debug log."""
|
||||
_get_rag_debug_logger().info(
|
||||
"frontend %s thread=%s payload=%s log_file=%s",
|
||||
body.event,
|
||||
sanitize_log_param(body.thread_id or ""),
|
||||
json.dumps(body.payload, ensure_ascii=False, default=str),
|
||||
_rag_debug_file_path(),
|
||||
)
|
||||
return {"ok": True, "log_file": _rag_debug_file_path()}
|
||||
|
||||
|
||||
@router.post("/{thread_id}/state", response_model=ThreadStateResponse)
|
||||
@require_permission("threads", "write", owner_check=True, require_existing=True)
|
||||
async def update_thread_state(thread_id: str, body: ThreadStateUpdateRequest, request: Request) -> ThreadStateResponse:
|
||||
"""Update thread state (e.g. for human-in-the-loop resume or title rename).
|
||||
|
||||
Writes a new checkpoint that merges *body.values* into the latest
|
||||
|
||||
@@ -100,7 +100,14 @@ _DEFAULT_ASSISTANT_ID = "lead_agent"
|
||||
|
||||
# Built-in LangGraph graph IDs registered in langgraph.json.
|
||||
# These are NOT stored in the agents DB and must bypass the custom-agent access check.
|
||||
_BUILTIN_GRAPH_IDS: frozenset[str] = frozenset({"lead_agent", "canvas_agent", "ai_writing"})
|
||||
_BUILTIN_GRAPH_IDS: frozenset[str] = frozenset({"lead_agent", "canvas_agent", "ai_writing"})
|
||||
|
||||
_RAG_CITATION_PROMPT = """当前对话已开启参考文献模式。
|
||||
如果本轮调用了搜索、知识库、检索类技能或工具，请基于本轮所有检索结果整体回答。
|
||||
你必须把同一轮内多次检索得到的资料视为同一批参考文献，按出现顺序从 [1] 开始连续编号，不要让每个检索词各自从 [1] 重新编号。
|
||||
回答正文中的关键结论必须标注对应编号，例如 [1]、[2]，多个来源可写为 [1][3][5]。
|
||||
不要引用不存在的编号，不要使用技能内部自带的编号，不要把参考文献完整列表堆在正文末尾。
|
||||
如果没有任何可用检索结果，请直接说明未检索到可靠参考资料。"""
|
||||
|
||||
|
||||
def _prepend_prompt_prefix(graph_input: dict[str, Any], prefix: str) -> dict[str, Any]:
|
||||
@@ -129,7 +136,7 @@ def _prepend_prompt_prefix(graph_input: dict[str, Any], prefix: str) -> dict[str
|
||||
return {**graph_input, "messages": new_messages}
|
||||
|
||||
|
||||
def _prompt_prefix_opted_in(body: Any) -> bool:
|
||||
def _prompt_prefix_opted_in(body: Any) -> bool:
|
||||
"""Detect whether the caller asked for the prompt prefix to be applied."""
|
||||
context = getattr(body, "context", None)
|
||||
if isinstance(context, Mapping) and context.get("prompt_prefix_enabled"):
|
||||
@@ -137,7 +144,44 @@ def _prompt_prefix_opted_in(body: Any) -> bool:
|
||||
metadata = getattr(body, "metadata", None)
|
||||
if isinstance(metadata, Mapping) and metadata.get("prompt_prefix_enabled"):
|
||||
return True
|
||||
return False
|
||||
return False
|
||||
|
||||
|
||||
def _rag_mode_requested(body: Any) -> bool:
|
||||
context = getattr(body, "context", None)
|
||||
if isinstance(context, Mapping) and context.get("rag_mode_enabled"):
|
||||
return True
|
||||
metadata = getattr(body, "metadata", None)
|
||||
if isinstance(metadata, Mapping) and (
|
||||
metadata.get("rag_mode_enabled") or metadata.get("rag_mode")
|
||||
):
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
def _thread_rag_mode_enabled(record: Any) -> bool:
|
||||
if not isinstance(record, Mapping):
|
||||
return False
|
||||
metadata = record.get("metadata")
|
||||
return isinstance(metadata, Mapping) and bool(
|
||||
metadata.get("rag_mode_enabled") or metadata.get("rag_mode")
|
||||
)
|
||||
|
||||
|
||||
def _append_invisible_prompt(graph_input: dict[str, Any], prompt: str) -> dict[str, Any]:
|
||||
messages = graph_input.get("messages")
|
||||
if not isinstance(messages, list) or not messages:
|
||||
return graph_input
|
||||
new_messages = list(messages)
|
||||
for idx, msg in enumerate(new_messages):
|
||||
if not isinstance(msg, HumanMessage):
|
||||
continue
|
||||
extra = dict(getattr(msg, "additional_kwargs", None) or {})
|
||||
existing = str(extra.get("prompt_prefix") or "").strip()
|
||||
extra["prompt_prefix"] = f"{existing}\n\n{prompt}".strip() if existing else prompt
|
||||
new_messages[idx] = msg.model_copy(update={"additional_kwargs": extra})
|
||||
break
|
||||
return {**graph_input, "messages": new_messages}
|
||||
|
||||
|
||||
# Whitelist of run-context keys that the langgraph-compat layer forwards from
|
||||
@@ -399,16 +443,29 @@ async def start_run(
|
||||
# Upsert thread metadata so the thread appears in /threads/search,
|
||||
# even for threads that were never explicitly created via POST /threads
|
||||
# (e.g. stateless runs).
|
||||
try:
|
||||
existing = await run_ctx.thread_store.get(thread_id)
|
||||
if existing is None:
|
||||
await run_ctx.thread_store.create(
|
||||
thread_id,
|
||||
assistant_id=body.assistant_id,
|
||||
metadata=body.metadata,
|
||||
)
|
||||
else:
|
||||
await run_ctx.thread_store.update_status(thread_id, "running")
|
||||
requested_rag_mode = _rag_mode_requested(body)
|
||||
effective_rag_mode = requested_rag_mode
|
||||
try:
|
||||
existing = await run_ctx.thread_store.get(thread_id)
|
||||
effective_rag_mode = requested_rag_mode or _thread_rag_mode_enabled(existing)
|
||||
if existing is None:
|
||||
metadata = dict(body.metadata or {})
|
||||
if effective_rag_mode:
|
||||
metadata["rag_mode_enabled"] = True
|
||||
metadata["rag_mode"] = True
|
||||
await run_ctx.thread_store.create(
|
||||
thread_id,
|
||||
assistant_id=body.assistant_id,
|
||||
metadata=metadata,
|
||||
)
|
||||
else:
|
||||
await run_ctx.thread_store.update_status(thread_id, "running")
|
||||
if requested_rag_mode and not _thread_rag_mode_enabled(existing):
|
||||
await run_ctx.thread_store.update_metadata(
|
||||
thread_id,
|
||||
{"rag_mode_enabled": True, "rag_mode": True},
|
||||
)
|
||||
effective_rag_mode = True
|
||||
# SDK 的 ``client.threads.create()`` 不传 assistant_id —— 先建出来空的 thread，
|
||||
# 真正提交 run 时才知道用哪个 assistant。这里回填一次，避免历史列表 / 按
|
||||
# assistant 筛选时拿不到关联。
|
||||
@@ -428,17 +485,21 @@ async def start_run(
|
||||
# applies once. We intentionally do NOT gate on thread-row existence: the
|
||||
# thread_meta row is frequently pre-created, which previously skipped the
|
||||
# prefix for genuine first turns.
|
||||
if _prompt_prefix_opted_in(body):
|
||||
prefix_settings = load_system_settings().prompt_prefix
|
||||
if prefix_settings.enabled and prefix_settings.prompt_prefix.strip():
|
||||
graph_input = _prepend_prompt_prefix(graph_input, prefix_settings.prompt_prefix.strip())
|
||||
config = build_run_config(thread_id, body.config, body.metadata, assistant_id=body.assistant_id)
|
||||
if _prompt_prefix_opted_in(body):
|
||||
prefix_settings = load_system_settings().prompt_prefix
|
||||
if prefix_settings.enabled and prefix_settings.prompt_prefix.strip():
|
||||
graph_input = _prepend_prompt_prefix(graph_input, prefix_settings.prompt_prefix.strip())
|
||||
if effective_rag_mode:
|
||||
graph_input = _append_invisible_prompt(graph_input, _RAG_CITATION_PROMPT)
|
||||
config = build_run_config(thread_id, body.config, body.metadata, assistant_id=body.assistant_id)
|
||||
|
||||
# Merge DeerFlow-specific context overrides into both ``configurable`` and ``context``.
|
||||
# The ``context`` field is a custom extension for the langgraph-compat layer
|
||||
# that carries agent configuration (model_name, thinking_enabled, etc.).
|
||||
# Only agent-relevant keys are forwarded; unknown keys (e.g. thread_id) are ignored.
|
||||
body_context = dict(getattr(body, "context", None) or {})
|
||||
body_context = dict(getattr(body, "context", None) or {})
|
||||
if effective_rag_mode:
|
||||
body_context["rag_mode_enabled"] = True
|
||||
# Promote whitelisted top-level body fields into the context map so
|
||||
# callers can pass them either nested under ``context`` or as flat
|
||||
# top-level fields (``excluded_tools``, ``skill_stop_names``, …).
|
||||
|
||||
+14
-11
@@ -7,9 +7,10 @@ from langchain_core.runnables import RunnableConfig
|
||||
from deerflow.agents.lead_agent.prompt import apply_prompt_template
|
||||
from deerflow.agents.middlewares.clarification_middleware import ClarificationMiddleware
|
||||
from deerflow.agents.middlewares.loop_detection_middleware import LoopDetectionMiddleware
|
||||
from deerflow.agents.middlewares.memory_middleware import MemoryMiddleware
|
||||
from deerflow.agents.middlewares.prompt_prefix_middleware import PromptPrefixMiddleware
|
||||
from deerflow.agents.middlewares.setup_agent_approval_middleware import SetupAgentApprovalMiddleware
|
||||
from deerflow.agents.middlewares.memory_middleware import MemoryMiddleware
|
||||
from deerflow.agents.middlewares.prompt_prefix_middleware import PromptPrefixMiddleware
|
||||
from deerflow.agents.middlewares.rag_citation_middleware import RagCitationMiddleware
|
||||
from deerflow.agents.middlewares.setup_agent_approval_middleware import SetupAgentApprovalMiddleware
|
||||
from deerflow.agents.middlewares.subagent_limit_middleware import SubagentLimitMiddleware
|
||||
from deerflow.agents.middlewares.summarization_middleware import BeforeSummarizationHook, DeerFlowSummarizationMiddleware
|
||||
from deerflow.agents.middlewares.title_middleware import TitleMiddleware
|
||||
@@ -252,13 +253,16 @@ def _build_middlewares(
|
||||
|
||||
Returns:
|
||||
List of middleware instances.
|
||||
"""
|
||||
resolved_app_config = app_config or get_app_config()
|
||||
middlewares = build_lead_runtime_middlewares(app_config=resolved_app_config, lazy_init=True)
|
||||
"""
|
||||
resolved_app_config = app_config or get_app_config()
|
||||
cfg = _get_runtime_config(config)
|
||||
middlewares = build_lead_runtime_middlewares(app_config=resolved_app_config, lazy_init=True)
|
||||
|
||||
# Inject the admin prompt prefix into the model request (kept out of the
|
||||
# persisted/displayed message so the user never sees it).
|
||||
middlewares.append(PromptPrefixMiddleware())
|
||||
# Inject the admin prompt prefix into the model request (kept out of the
|
||||
# persisted/displayed message so the user never sees it).
|
||||
middlewares.append(PromptPrefixMiddleware())
|
||||
if cfg.get("rag_mode_enabled", False):
|
||||
middlewares.append(RagCitationMiddleware())
|
||||
|
||||
# Add summarization middleware if enabled
|
||||
summarization_middleware = _create_summarization_middleware(app_config=resolved_app_config)
|
||||
@@ -266,8 +270,7 @@ def _build_middlewares(
|
||||
middlewares.append(summarization_middleware)
|
||||
|
||||
# Add TodoList middleware if plan mode is enabled
|
||||
cfg = _get_runtime_config(config)
|
||||
is_plan_mode = cfg.get("is_plan_mode", False)
|
||||
is_plan_mode = cfg.get("is_plan_mode", False)
|
||||
is_bootstrap = cfg.get("is_bootstrap", False)
|
||||
todo_list_middleware = _create_todo_list_middleware(is_plan_mode)
|
||||
if todo_list_middleware is not None:
|
||||
|
||||
+109
@@ -0,0 +1,109 @@
|
||||
"""Inject stable citation numbering before RAG final answers."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import os
|
||||
from pathlib import Path
|
||||
from collections.abc import Awaitable, Callable
|
||||
from typing import Any, override
|
||||
|
||||
from langchain.agents import AgentState
|
||||
from langchain.agents.middleware import AgentMiddleware
|
||||
from langchain.agents.middleware.types import ModelCallResult, ModelRequest, ModelResponse
|
||||
from langchain_core.messages import SystemMessage
|
||||
|
||||
from deerflow.runtime.references import build_latest_reference_prompt, build_reference_debug_summary
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
_RAG_DEBUG_LOGGER_NAME = "rag_citation_debug"
|
||||
|
||||
|
||||
def _get_rag_debug_logger() -> logging.Logger:
|
||||
debug_logger = logging.getLogger(_RAG_DEBUG_LOGGER_NAME)
|
||||
if getattr(debug_logger, "_rag_file_configured", False):
|
||||
return debug_logger
|
||||
log_path = Path(os.environ.get("RAG_CITATION_DEBUG_LOG", "logs/rag_citation_debug.log"))
|
||||
if not log_path.is_absolute():
|
||||
log_path = Path.cwd() / log_path
|
||||
log_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
handler = logging.FileHandler(log_path, encoding="utf-8")
|
||||
handler.setFormatter(logging.Formatter("%(asctime)s %(levelname)s %(message)s"))
|
||||
debug_logger.addHandler(handler)
|
||||
debug_logger.setLevel(logging.INFO)
|
||||
debug_logger.propagate = False
|
||||
setattr(debug_logger, "_rag_file_configured", True)
|
||||
setattr(debug_logger, "_rag_file_path", str(log_path))
|
||||
return debug_logger
|
||||
|
||||
|
||||
def _log_rag_debug(message: str, *args: Any) -> None:
|
||||
logger.info(message, *args)
|
||||
_get_rag_debug_logger().info(message, *args)
|
||||
|
||||
|
||||
class RagCitationMiddleware(AgentMiddleware[AgentState]):
|
||||
"""Give the model the same numbered references the frontend will render."""
|
||||
|
||||
@staticmethod
|
||||
def _enabled(request: ModelRequest) -> bool:
|
||||
runtime = getattr(request, "runtime", None)
|
||||
context = getattr(runtime, "context", None) if runtime is not None else None
|
||||
if isinstance(context, dict) and context.get("rag_mode_enabled"):
|
||||
return True
|
||||
config = getattr(runtime, "config", None) if runtime is not None else None
|
||||
if isinstance(config, dict):
|
||||
configurable = config.get("configurable")
|
||||
if isinstance(configurable, dict) and configurable.get("rag_mode_enabled"):
|
||||
return True
|
||||
runtime_context = config.get("context")
|
||||
if isinstance(runtime_context, dict) and runtime_context.get("rag_mode_enabled"):
|
||||
return True
|
||||
return False
|
||||
|
||||
@staticmethod
|
||||
def _patch(request: ModelRequest) -> ModelRequest | None:
|
||||
if not RagCitationMiddleware._enabled(request):
|
||||
return None
|
||||
messages = list(request.messages)
|
||||
prompt, batch = build_latest_reference_prompt(messages)
|
||||
if not prompt:
|
||||
_log_rag_debug(
|
||||
"middleware reference-prompt enabled=true prompt=false messages=%s",
|
||||
len(messages),
|
||||
)
|
||||
return None
|
||||
summary = build_reference_debug_summary(messages, [batch] if batch else None)
|
||||
_log_rag_debug(
|
||||
"middleware reference-prompt enabled=true prompt=true messages=%s tool_messages=%s "
|
||||
"raw_items=%s normalized_items=%s kept_items=%s latest_batch_sources=%s",
|
||||
summary["messages"],
|
||||
summary["tool_messages"],
|
||||
summary["raw_items"],
|
||||
summary["normalized_items"],
|
||||
summary["kept_items"],
|
||||
len((batch or {}).get("sources") or []),
|
||||
)
|
||||
patched_messages = [
|
||||
*messages,
|
||||
SystemMessage(content=prompt),
|
||||
]
|
||||
return request.override(messages=patched_messages)
|
||||
|
||||
@override
|
||||
def wrap_model_call(
|
||||
self,
|
||||
request: ModelRequest,
|
||||
handler: Callable[[ModelRequest], ModelResponse],
|
||||
) -> ModelCallResult:
|
||||
patched = self._patch(request)
|
||||
return handler(patched or request)
|
||||
|
||||
@override
|
||||
async def awrap_model_call(
|
||||
self,
|
||||
request: ModelRequest,
|
||||
handler: Callable[[ModelRequest], Awaitable[ModelResponse]],
|
||||
) -> ModelCallResult:
|
||||
patched = self._patch(request)
|
||||
return await handler(patched or request)
|
||||
@@ -54,6 +54,16 @@ class AppearanceSettings(BaseModel):
|
||||
model_config = ConfigDict(extra="ignore")
|
||||
|
||||
|
||||
class CitationDisplaySettings(BaseModel):
|
||||
"""System-wide cleanup rules for citation cards and detail dialogs."""
|
||||
|
||||
cleanup_words: list[str] = Field(
|
||||
default_factory=list,
|
||||
description="Words or phrases used to remove noisy advertisement/disclaimer lines from citation display.",
|
||||
)
|
||||
model_config = ConfigDict(extra="ignore")
|
||||
|
||||
|
||||
class PrivateSquareSettings(BaseModel):
|
||||
"""Admin-configurable settings for the agent private-square (私密广场).
|
||||
|
||||
@@ -74,6 +84,7 @@ class SystemSettings(BaseModel):
|
||||
prompt_prefix: PromptPrefixSettings = Field(default_factory=PromptPrefixSettings)
|
||||
private_square: PrivateSquareSettings = Field(default_factory=PrivateSquareSettings)
|
||||
appearance: AppearanceSettings = Field(default_factory=AppearanceSettings)
|
||||
citation_display: CitationDisplaySettings = Field(default_factory=CitationDisplaySettings)
|
||||
model_config = ConfigDict(extra="ignore")
|
||||
|
||||
|
||||
|
||||
@@ -0,0 +1,366 @@
|
||||
"""Build stable per-turn citation batches from LangGraph messages."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
from typing import Any
|
||||
|
||||
|
||||
def build_reference_batches(messages: list[Any]) -> list[dict[str, Any]]:
|
||||
batches: list[dict[str, Any]] = []
|
||||
for index, message in enumerate(messages):
|
||||
if _message_type(message) != "human":
|
||||
continue
|
||||
end = len(messages)
|
||||
for cursor in range(index + 1, len(messages)):
|
||||
if _message_type(messages[cursor]) == "human":
|
||||
end = cursor
|
||||
break
|
||||
assistant = _find_last_assistant_answer(messages, index + 1, end)
|
||||
if assistant is None:
|
||||
continue
|
||||
sources = _collect_sources(messages[index + 1 : end])
|
||||
if sources:
|
||||
message_id = _message_id(assistant) or str(index)
|
||||
batches.append(
|
||||
{
|
||||
"id": message_id,
|
||||
"assistant_message_id": message_id,
|
||||
"sources": sources,
|
||||
}
|
||||
)
|
||||
return batches
|
||||
|
||||
|
||||
def build_latest_reference_prompt(messages: list[Any]) -> tuple[str, dict[str, Any] | None]:
|
||||
human_index = _find_latest_human_index(messages)
|
||||
if human_index is None:
|
||||
return "", None
|
||||
sources = _collect_sources(messages[human_index + 1 :])
|
||||
if not sources:
|
||||
return "", None
|
||||
assistant = _find_last_assistant_answer(messages, human_index + 1, len(messages))
|
||||
message_id = _message_id(assistant) or _message_id(messages[human_index]) or str(human_index)
|
||||
batch = {
|
||||
"id": message_id,
|
||||
"assistant_message_id": message_id,
|
||||
"sources": sources,
|
||||
}
|
||||
lines = [
|
||||
"本轮检索结果已由系统统一合并并重新编号。最终回答必须使用下面这套编号。",
|
||||
"如果你仍需要补充检索，请先继续调用工具；最终回答只能引用最新合并后的编号。",
|
||||
"",
|
||||
]
|
||||
for source in sources:
|
||||
title = source.get("title") or f"参考文献 {source.get('index')}"
|
||||
meta = " · ".join(
|
||||
str(item)
|
||||
for item in (source.get("source"), source.get("time"))
|
||||
if item
|
||||
)
|
||||
content = str(source.get("content") or source.get("snippet") or "").strip()
|
||||
if len(content) > 520:
|
||||
content = content[:517] + "..."
|
||||
head = f"[{source.get('index')}] {title}"
|
||||
if meta:
|
||||
head += f"（{meta}）"
|
||||
lines.append(head)
|
||||
if content:
|
||||
lines.append(content)
|
||||
lines.append("")
|
||||
lines.extend(
|
||||
[
|
||||
"引用规则：",
|
||||
"1. 回答正文中的关键结论必须标注对应编号，例如 [1]、[2]。",
|
||||
"2. 多个来源可写为 [1][3][5]。",
|
||||
"3. 只能引用上方存在的编号，不要编造编号。",
|
||||
"4. 不要使用工具原始编号，也不要重新排序编号。",
|
||||
"5. 不要在正文末尾堆完整参考文献列表，前端会展示右侧参考文献。",
|
||||
]
|
||||
)
|
||||
return "\n".join(lines).strip(), batch
|
||||
|
||||
|
||||
def _find_latest_human_index(messages: list[Any]) -> int | None:
|
||||
for index in range(len(messages) - 1, -1, -1):
|
||||
if _message_type(messages[index]) == "human":
|
||||
return index
|
||||
return None
|
||||
|
||||
|
||||
def build_reference_debug_summary(messages: list[Any], batches: list[dict[str, Any]] | None = None) -> dict[str, Any]:
|
||||
"""Return compact counts for citation extraction logs."""
|
||||
turn_summaries: list[dict[str, Any]] = []
|
||||
total_tool_messages = 0
|
||||
total_raw_items = 0
|
||||
total_normalized_items = 0
|
||||
total_kept_items = 0
|
||||
for index, message in enumerate(messages):
|
||||
if _message_type(message) != "human":
|
||||
continue
|
||||
end = len(messages)
|
||||
for cursor in range(index + 1, len(messages)):
|
||||
if _message_type(messages[cursor]) == "human":
|
||||
end = cursor
|
||||
break
|
||||
tool_messages = 0
|
||||
raw_items = 0
|
||||
normalized_items = 0
|
||||
kept_items = 0
|
||||
for tool_message in messages[index + 1 : end]:
|
||||
if _message_type(tool_message) != "tool":
|
||||
continue
|
||||
tool_messages += 1
|
||||
items = _first_list(_extract_tool_payload(tool_message))
|
||||
raw_items += len(items)
|
||||
for raw_item in items:
|
||||
normalized = _normalize_reference_item(raw_item, normalized_items + 1)
|
||||
if not normalized:
|
||||
continue
|
||||
normalized_items += 1
|
||||
kept_items += 1
|
||||
total_tool_messages += tool_messages
|
||||
total_raw_items += raw_items
|
||||
total_normalized_items += normalized_items
|
||||
total_kept_items += kept_items
|
||||
turn_summaries.append(
|
||||
{
|
||||
"human_index": index,
|
||||
"tool_messages": tool_messages,
|
||||
"raw_items": raw_items,
|
||||
"normalized_items": normalized_items,
|
||||
"kept_items": kept_items,
|
||||
}
|
||||
)
|
||||
batch_summaries = [
|
||||
{
|
||||
"id": batch.get("id"),
|
||||
"assistant_message_id": batch.get("assistant_message_id"),
|
||||
"source_count": len(batch.get("sources") or []),
|
||||
}
|
||||
for batch in (batches or build_reference_batches(messages))
|
||||
]
|
||||
return {
|
||||
"messages": len(messages),
|
||||
"turns": len(turn_summaries),
|
||||
"tool_messages": total_tool_messages,
|
||||
"raw_items": total_raw_items,
|
||||
"normalized_items": total_normalized_items,
|
||||
"kept_items": total_kept_items,
|
||||
"turns_detail": turn_summaries,
|
||||
"batches": batch_summaries,
|
||||
}
|
||||
|
||||
|
||||
def _collect_sources(messages: list[Any]) -> list[dict[str, Any]]:
|
||||
sources: list[dict[str, Any]] = []
|
||||
for message in messages:
|
||||
if _message_type(message) != "tool":
|
||||
continue
|
||||
payload = _extract_tool_payload(message)
|
||||
for raw_item in _first_list(payload):
|
||||
normalized = _normalize_reference_item(raw_item, len(sources) + 1)
|
||||
if not normalized:
|
||||
continue
|
||||
normalized["index"] = len(sources) + 1
|
||||
sources.append(normalized)
|
||||
return sources
|
||||
|
||||
|
||||
def _find_last_assistant_answer(messages: list[Any], start: int, end: int) -> Any | None:
|
||||
for index in range(end - 1, start - 1, -1):
|
||||
candidate = messages[index]
|
||||
if (
|
||||
_message_type(candidate) == "ai"
|
||||
and _message_id(candidate)
|
||||
and _has_answer_content(candidate)
|
||||
and not _has_tool_calls(candidate)
|
||||
):
|
||||
return candidate
|
||||
return None
|
||||
|
||||
|
||||
def _message_type(message: Any) -> str:
|
||||
if isinstance(message, dict):
|
||||
return str(message.get("type") or message.get("role") or "")
|
||||
return str(getattr(message, "type", "") or "")
|
||||
|
||||
|
||||
def _message_id(message: Any) -> str | None:
|
||||
value = message.get("id") if isinstance(message, dict) else getattr(message, "id", None)
|
||||
return str(value) if value else None
|
||||
|
||||
|
||||
def _message_content(message: Any) -> Any:
|
||||
return message.get("content") if isinstance(message, dict) else getattr(message, "content", None)
|
||||
|
||||
|
||||
def _has_tool_calls(message: Any) -> bool:
|
||||
if isinstance(message, dict):
|
||||
direct = message.get("tool_calls")
|
||||
chunks = message.get("tool_call_chunks")
|
||||
extra = (message.get("additional_kwargs") or {}).get("tool_calls")
|
||||
else:
|
||||
direct = getattr(message, "tool_calls", None)
|
||||
chunks = getattr(message, "tool_call_chunks", None)
|
||||
extra = (getattr(message, "additional_kwargs", None) or {}).get("tool_calls")
|
||||
return bool(direct or chunks or extra)
|
||||
|
||||
|
||||
def _has_answer_content(message: Any) -> bool:
|
||||
content = _message_content(message)
|
||||
if isinstance(content, str):
|
||||
return bool(content.strip())
|
||||
if isinstance(content, list):
|
||||
return any(
|
||||
isinstance(part, dict)
|
||||
and part.get("type") == "text"
|
||||
and str(part.get("text") or "").strip()
|
||||
for part in content
|
||||
)
|
||||
return False
|
||||
|
||||
|
||||
def _extract_tool_payload(message: Any) -> Any:
|
||||
content = _message_content(message)
|
||||
if isinstance(content, dict):
|
||||
return _unwrap_tool_payload(content)
|
||||
if isinstance(content, list):
|
||||
texts: list[str] = []
|
||||
for part in content:
|
||||
if not isinstance(part, dict):
|
||||
continue
|
||||
if isinstance(part.get("json"), dict):
|
||||
return _unwrap_tool_payload(part["json"])
|
||||
if part.get("type") == "json" and isinstance(part.get("json"), dict):
|
||||
return _unwrap_tool_payload(part["json"])
|
||||
if part.get("type") == "text" and isinstance(part.get("text"), str):
|
||||
texts.append(part["text"])
|
||||
unwrapped = _unwrap_tool_payload(part)
|
||||
if unwrapped is not None:
|
||||
return unwrapped
|
||||
content = "\n".join(texts)
|
||||
if isinstance(content, str):
|
||||
return _parse_json_like(content)
|
||||
return None
|
||||
|
||||
|
||||
def _unwrap_tool_payload(value: dict[str, Any]) -> Any:
|
||||
list_keys = ("results", "data", "items", "hits", "documents", "records", "sources")
|
||||
if any(isinstance(value.get(key), list) for key in list_keys):
|
||||
return value
|
||||
for key in ("result", "output", "stdout", "content", "text", "payload", "response"):
|
||||
nested = value.get(key)
|
||||
if isinstance(nested, str):
|
||||
parsed = _parse_json_like(nested)
|
||||
if parsed is not None:
|
||||
return parsed
|
||||
if isinstance(nested, dict):
|
||||
unwrapped = _unwrap_tool_payload(nested)
|
||||
if unwrapped is not None:
|
||||
return unwrapped
|
||||
return value
|
||||
|
||||
|
||||
def _parse_json_like(text: str) -> Any:
|
||||
trimmed = text.strip()
|
||||
if not trimmed:
|
||||
return None
|
||||
try:
|
||||
return json.loads(trimmed)
|
||||
except Exception:
|
||||
pass
|
||||
first = trimmed.find("{")
|
||||
last = trimmed.rfind("}")
|
||||
if 0 <= first < last:
|
||||
try:
|
||||
return json.loads(trimmed[first : last + 1])
|
||||
except Exception:
|
||||
return None
|
||||
return None
|
||||
|
||||
|
||||
def _first_list(payload: Any) -> list[Any]:
|
||||
if isinstance(payload, list):
|
||||
return payload
|
||||
if not isinstance(payload, dict):
|
||||
return []
|
||||
for key in ("results", "data", "items", "hits", "documents", "records", "entries", "matches", "chunks", "sources"):
|
||||
value = payload.get(key)
|
||||
if isinstance(value, list):
|
||||
return value
|
||||
for key in ("result", "payload", "response", "output", "data"):
|
||||
found = _first_list(payload.get(key))
|
||||
if found:
|
||||
return found
|
||||
return []
|
||||
|
||||
|
||||
def _nested_records(raw: Any) -> list[dict[str, Any]]:
|
||||
if not isinstance(raw, dict):
|
||||
return []
|
||||
layers = [raw]
|
||||
for key in ("metadata", "meta", "attrs", "attributes", "properties", "extra"):
|
||||
nested = raw.get(key)
|
||||
if isinstance(nested, dict):
|
||||
layers.append(nested)
|
||||
return layers
|
||||
|
||||
|
||||
def _pick(layers: list[dict[str, Any]], keys: tuple[str, ...]) -> str | None:
|
||||
for layer in layers:
|
||||
for key in keys:
|
||||
value = layer.get(key)
|
||||
if isinstance(value, (str, int, float)) and str(value).strip():
|
||||
return str(value).strip()
|
||||
return None
|
||||
|
||||
|
||||
def _normalize_reference_item(raw: Any, fallback_index: int) -> dict[str, Any] | None:
|
||||
if not isinstance(raw, dict):
|
||||
return None
|
||||
layers = _nested_records(raw)
|
||||
title = _pick(layers, ("title", "m_title", "name", "question", "keyword", "query", "text"))
|
||||
content = _pick(layers, ("content", "page_content", "summary", "snippet", "description", "content_preview", "abstract", "body"))
|
||||
url = _pick(layers, ("url", "link", "href", "source_url", "web_url"))
|
||||
source = _pick(layers, ("source", "source1", "site", "provider", "from"))
|
||||
time = _pick(layers, ("time", "date", "published_date", "publishedDate", "m_publish", "publish_time", "created_at"))
|
||||
item_id = _pick(layers, ("recUuid", "rec_uuid", "uuid", "docId", "doc_id", "id", "recordId", "taskId"))
|
||||
score_raw = _pick(layers, ("score", "relevance", "similarity"))
|
||||
score = None
|
||||
if score_raw is not None:
|
||||
try:
|
||||
score = float(score_raw)
|
||||
except Exception:
|
||||
score = None
|
||||
if not title:
|
||||
title = source or f"结果 {fallback_index}"
|
||||
if not content:
|
||||
content = ""
|
||||
if not title and not content and not url:
|
||||
return None
|
||||
return {
|
||||
"id": item_id or url,
|
||||
"skillName": "backend-reference",
|
||||
"mode": "citation",
|
||||
"title": title,
|
||||
"type": "result",
|
||||
"snippet": content,
|
||||
"content": content,
|
||||
"source": source,
|
||||
"time": time,
|
||||
"url": url,
|
||||
"score": score,
|
||||
"raw": raw,
|
||||
}
|
||||
|
||||
|
||||
def _reference_key(source: dict[str, Any]) -> str:
|
||||
raw = source.get("raw") if isinstance(source.get("raw"), dict) else {}
|
||||
item_id = source.get("id") or source.get("url") or raw.get("recUuid") or raw.get("uuid") or raw.get("docId") or raw.get("id")
|
||||
if item_id:
|
||||
return str(item_id).casefold().strip()
|
||||
return "|".join(
|
||||
str(source.get(key) or "").casefold().strip()
|
||||
for key in ("title", "source", "time", "content", "snippet")
|
||||
)
|
||||
Reference in new issue
Block a user