引入LangGraph自动模式流程

This commit is contained in:
Your Name 2026-02-05 21:23:44 +08:00
parent 2ea63d978f
commit 66458e97fb
4 changed files with 501 additions and 41 deletions

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@ -461,61 +461,43 @@ export async function POST(request: Request) {
} }
console.log("[Smart Auto Mode] History context:", historyMessages.length, "messages"); console.log("[Smart Auto Mode] History context:", historyMessages.length, "messages");
// 2. 调用智能分析器(传入历史对话上下文) // 2. 使用 LangGraph 驱动的自动模式工作流
const { analyzeIntent } = await import("@/lib/ai/smart-analyzer"); const { runAutoAgentGraph } = await import("@/lib/ai/auto-agent-graph");
const analysisResult = await analyzeIntent({ const autoGraphResult = await runAutoAgentGraph({
text: textContent, text: textContent,
hasImage, hasImage,
imageUrls, imageUrls,
imageFromHistory: smartAutoHistoryImages.length > 0, // 🆕 标识图片是否来自历史 imageFromHistory: smartAutoHistoryImages.length > 0,
historyMessages, // 🆕 传入历史对话用于上下文理解 historyMessages,
context: autoContextText || undefined, context: autoContextText || undefined,
}); });
console.log("[Smart Auto Mode] Analysis result:", { if (autoGraphResult.analysis) {
intent: analysisResult.intent, console.log("[Smart Auto Mode] Analysis result:", {
subIntent: analysisResult.subIntent, intent: autoGraphResult.analysis.intent,
confidence: analysisResult.confidence, subIntent: autoGraphResult.analysis.subIntent,
needsClarification: analysisResult.needsClarification, confidence: autoGraphResult.analysis.confidence,
}); needsClarification: autoGraphResult.analysis.needsClarification,
});
}
// 🆕 保存AI的自然对话回复(来自千问3 VL的理解) if (autoGraphResult.friendlyMessage) {
if (analysisResult.conversationalReply) { smartAutoFriendlyMessage = autoGraphResult.friendlyMessage;
smartAutoFriendlyMessage = analysisResult.conversationalReply;
console.log("[Smart Auto Mode] 💬 Conversational reply:", smartAutoFriendlyMessage); console.log("[Smart Auto Mode] 💬 Conversational reply:", smartAutoFriendlyMessage);
} }
// 3. 如果是图片编辑类意图,使用 LLM 深度优化提示词 if (autoGraphResult.optimizedPrompt) {
if (analysisResult.intent === "image_edit" && analysisResult.subIntent) { smartAutoOptimizedPrompt = autoGraphResult.optimizedPrompt;
const { optimizePromptWithLLM } = await import("@/lib/ai/prompt-optimizer");
const optimizedResult = await optimizePromptWithLLM({
originalPrompt: textContent,
intent: analysisResult.intent,
subIntent: analysisResult.subIntent,
historyMessages, // 🆕 传入历史对话上下文
context: autoContextText || undefined,
});
console.log("[Smart Auto Mode] ✨ Prompt optimized (LLM):", { console.log("[Smart Auto Mode] ✨ Prompt optimized (LLM):", {
original: textContent.substring(0, 50), original: textContent.substring(0, 50),
optimized: optimizedResult.optimizedPrompt.substring(0, 100), optimized: autoGraphResult.optimizedPrompt.substring(0, 100),
}); });
// 🆕 保存优化后的提示词,但不修改用户消息
// 用户消息保持原样显示,优化后的提示词只用于API调用
smartAutoOptimizedPrompt = optimizedResult.optimizedPrompt;
} }
// 4. 路由到最佳模型 if (autoGraphResult.route) {
const { routeToModel } = await import("@/lib/ai/model-router"); finalModelId = autoGraphResult.route.id;
const routeResult = await routeToModel({ console.log(`[Smart Auto Mode] ✅ Routed to: ${autoGraphResult.route.displayName} (${autoGraphResult.route.reason})`);
intent: analysisResult.intent, }
subIntent: analysisResult.subIntent,
hasImage,
});
finalModelId = routeResult.id;
console.log(`[Smart Auto Mode] ✅ Routed to: ${routeResult.displayName} (${routeResult.reason})`);
} catch (autoError) { } catch (autoError) {
// 智能分析失败时,回退到简单逻辑 // 智能分析失败时,回退到简单逻辑

141
lib/ai/auto-agent-graph.ts Normal file
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@ -0,0 +1,141 @@
import { Annotation, StateGraph, START, END } from "@langchain/langgraph";
import type { AnalysisResult } from "@/lib/ai/smart-analyzer";
import type { RouteResult } from "@/lib/ai/model-router";
interface HistoryMessage {
role: "user" | "assistant";
content: string;
}
export interface AutoAgentInput {
text: string;
hasImage: boolean;
imageUrls?: string[];
imageFromHistory?: boolean;
historyMessages?: HistoryMessage[];
context?: string;
}
export interface AutoAgentResult {
analysis?: AnalysisResult;
friendlyMessage?: string;
optimizedPrompt?: string;
route?: RouteResult;
}
const AutoAgentState = Annotation.Root({
text: Annotation<string>,
hasImage: Annotation<boolean>,
imageUrls: Annotation<string[]>,
imageFromHistory: Annotation<boolean>,
historyMessages: Annotation<HistoryMessage[]>,
context: Annotation<string | null>,
analysis: Annotation<AnalysisResult | null>,
friendlyMessage: Annotation<string | null>,
optimizedPrompt: Annotation<string | null>,
route: Annotation<RouteResult | null>,
});
type AutoAgentStateType = typeof AutoAgentState.State;
const analyzeNode = async (state: AutoAgentStateType) => {
const { analyzeIntent } = await import("./smart-analyzer");
const analysis = await analyzeIntent({
text: state.text,
hasImage: state.hasImage,
imageUrls: state.imageUrls,
imageFromHistory: state.imageFromHistory,
historyMessages: state.historyMessages,
context: state.context ?? undefined,
});
const fallbackQuestion = analysis.needsClarification
? analysis.clarifyingQuestions?.[0]
: undefined;
return {
analysis,
friendlyMessage: analysis.conversationalReply || fallbackQuestion || null,
};
};
const shouldOptimize = (state: AutoAgentStateType) => {
if (!state.analysis) return "route";
if (state.analysis.needsClarification) return "route";
if (state.analysis.intent === "image_edit" && state.analysis.subIntent) {
return "optimize";
}
return "route";
};
const optimizeNode = async (state: AutoAgentStateType) => {
if (!state.analysis || state.analysis.intent !== "image_edit" || !state.analysis.subIntent) {
return {};
}
const { optimizePromptWithLLM } = await import("./prompt-optimizer");
const optimized = await optimizePromptWithLLM({
originalPrompt: state.text,
intent: state.analysis.intent,
subIntent: state.analysis.subIntent,
historyMessages: state.historyMessages,
context: state.context ?? undefined,
});
return { optimizedPrompt: optimized.optimizedPrompt };
};
const routeNode = async (state: AutoAgentStateType) => {
const { routeToModel } = await import("./model-router");
const route = await routeToModel({
intent: state.analysis?.intent || "chat",
subIntent: state.analysis?.subIntent,
hasImage: state.hasImage,
});
return { route };
};
let compiledGraph: ReturnType<typeof buildGraph> | null = null;
function buildGraph() {
return new StateGraph(AutoAgentState)
.addNode("analyze", analyzeNode)
.addNode("optimize", optimizeNode)
.addNode("route", routeNode)
.addEdge(START, "analyze")
.addConditionalEdges("analyze", shouldOptimize, {
optimize: "optimize",
route: "route",
})
.addEdge("optimize", "route")
.addEdge("route", END)
.compile();
}
function getGraph() {
if (!compiledGraph) {
compiledGraph = buildGraph();
}
return compiledGraph;
}
export async function runAutoAgentGraph(params: AutoAgentInput): Promise<AutoAgentResult> {
const graph = getGraph();
const result = await graph.invoke({
text: params.text,
hasImage: params.hasImage,
imageUrls: params.imageUrls ?? [],
imageFromHistory: params.imageFromHistory ?? false,
historyMessages: params.historyMessages ?? [],
context: params.context ?? null,
analysis: null,
friendlyMessage: null,
optimizedPrompt: null,
route: null,
});
return {
analysis: result.analysis ?? undefined,
friendlyMessage: result.friendlyMessage ?? undefined,
optimizedPrompt: result.optimizedPrompt ?? undefined,
route: result.route ?? undefined,
};
}

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@ -32,6 +32,8 @@
"@codemirror/view": "^6.35.3", "@codemirror/view": "^6.35.3",
"@fal-ai/serverless-client": "^0.15.0", "@fal-ai/serverless-client": "^0.15.0",
"@icons-pack/react-simple-icons": "^13.7.0", "@icons-pack/react-simple-icons": "^13.7.0",
"@langchain/core": "^1.1.19",
"@langchain/langgraph": "^1.1.3",
"@opentelemetry/api": "^1.9.0", "@opentelemetry/api": "^1.9.0",
"@opentelemetry/api-logs": "^0.200.0", "@opentelemetry/api-logs": "^0.200.0",
"@radix-ui/react-dialog": "^1.1.4", "@radix-ui/react-dialog": "^1.1.4",

337
pnpm-lock.yaml generated
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@ -50,6 +50,12 @@ importers:
'@icons-pack/react-simple-icons': '@icons-pack/react-simple-icons':
specifier: ^13.7.0 specifier: ^13.7.0
version: 13.8.0(react@19.0.0-rc-45804af1-20241021) version: 13.8.0(react@19.0.0-rc-45804af1-20241021)
'@langchain/core':
specifier: ^1.1.19
version: 1.1.19(@opentelemetry/api@1.9.0)(@opentelemetry/sdk-trace-base@1.30.1(@opentelemetry/api@1.9.0))
'@langchain/langgraph':
specifier: ^1.1.3
version: 1.1.3(@langchain/core@1.1.19(@opentelemetry/api@1.9.0)(@opentelemetry/sdk-trace-base@1.30.1(@opentelemetry/api@1.9.0)))(react-dom@19.0.0-rc-45804af1-20241021(react@19.0.0-rc-45804af1-20241021))(react@19.0.0-rc-45804af1-20241021)(zod-to-json-schema@3.24.5(zod@3.25.76))(zod@3.25.76)
'@opentelemetry/api': '@opentelemetry/api':
specifier: ^1.9.0 specifier: ^1.9.0
version: 1.9.0 version: 1.9.0
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