langgraph_used

src/screens/FlowScreen.tsx

@@ -31,6 +31,8 @@ import * as ImagePicker from 'expo-image-picker';
 import { AIRole } from '../types';
 import { colors, typography, spacing, borderRadius, shadows } from '../theme/colors';
 import { aiService, AIMessage } from '../services/ai.service';
+import { langGraphService } from '../services/langgraph.service';
+import { HumanMessage, AIMessage as LangChainAIMessage, SystemMessage } from "@langchain/core/messages";
 import { assetsService } from '../services/assets.service';
 import { useAuth } from '../context/AuthContext';
 import { AI_CONFIG, getVaultStorageKeys } from '../config';
@@ -280,8 +282,23 @@ export default function FlowScreen() {
     setMessages(prev => [...prev, userMsg]);
 
     try {
-      // Call AI proxy with selected role's system prompt
-      const aiResponse = await aiService.sendMessage(userMessage, token, selectedRole?.systemPrompt || '');
+      // 1. Convert current messages history to LangChain format
+      const history: (HumanMessage | LangChainAIMessage | SystemMessage)[] = messages.map(msg => {
+        if (msg.role === 'user') return new HumanMessage(msg.content);
+        return new LangChainAIMessage(msg.content);
+      });
+
+      // 2. Add system prompt
+      const systemPrompt = new SystemMessage(selectedRole?.systemPrompt || '');
+
+      // 3. Add current new message
+      const currentMsg = new HumanMessage(userMessage);
+
+      // 4. Combine all messages for LangGraph processing
+      const fullMessages = [systemPrompt, ...history, currentMsg];
+
+      // 5. Execute via LangGraph service (handles token limits and context)
+      const aiResponse = await langGraphService.execute(fullMessages, token);
 
       // Add AI response
       const aiMsg: ChatMessage = {

src/services/ai.service.ts

@@ -13,6 +13,7 @@ import {
   logApiDebug,
 } from '../config';
 import { AIRole } from '../types';
+import { trimInternalMessages } from '../utils/token_utils';
 
 // =============================================================================
 // Type Definitions
@@ -259,14 +260,17 @@ export const aiService = {
       });
     }
 
-    const historicalMessages = messages.map(msg => ({
+    // Enforce token limit (10,000 tokens)
+    const trimmedMessages = trimInternalMessages(messages);
+
+    const historicalMessages = trimmedMessages.map(msg => ({
       role: msg.role,
       content: msg.content,
     }));
 
     const summaryPrompt: AIMessage = {
       role: 'user',
-      content: 'Please provide a concise summary of the conversation above in Chinese (since the user request was in Chinese). Focus on the main topics discussed and any key conclusions or actions mentioned.',
+      content: 'Please provide a concise summary of the conversation above in English. Focus on the main topics discussed and any key conclusions or actions mentioned.',
     };
 
     const response = await this.chat([...historicalMessages, summaryPrompt], token);

src/services/langgraph.service.ts

@@ -0,0 +1,96 @@
+/**
+ * LangGraph Service
+ * 
+ * Implements AI chat logic using LangGraph.js for state management
+ * and context handling.
+ */
+
+import { StateGraph, START, END, Annotation } from "@langchain/langgraph";
+import { BaseMessage, HumanMessage, AIMessage, SystemMessage } from "@langchain/core/messages";
+import { aiService } from "./ai.service";
+import { trimLangChainMessages } from "../utils/token_utils";
+
+// =============================================================================
+// Settings
+// =============================================================================
+
+/**
+ * Define the State using Annotation (Standard for latest LangGraph.js)
+ */
+const GraphAnnotation = Annotation.Root({
+    messages: Annotation<BaseMessage[]>({
+        reducer: (x, y) => x.concat(y),
+        default: () => [],
+    }),
+});
+
+// =============================================================================
+// Graph Definition
+// =============================================================================
+
+/**
+ * The main node that calls our existing AI API
+ */
+async function callModel(state: typeof GraphAnnotation.State, config: any) {
+    const { messages } = state;
+    const { token } = config.configurable || {};
+
+    // 1. Trim messages to stay under token limit
+    const trimmedMessages = trimLangChainMessages(messages);
+
+    // 2. Convert LangChain messages to our internal AIMessage format for the API
+    const apiMessages = trimmedMessages.map(m => {
+        let role: 'system' | 'user' | 'assistant' = 'user';
+        const type = (m as any)._getType?.() || (m instanceof SystemMessage ? 'system' : m instanceof HumanMessage ? 'human' : m instanceof AIMessage ? 'ai' : 'user');
+
+        if (type === 'system') role = 'system';
+        else if (type === 'human') role = 'user';
+        else if (type === 'ai') role = 'assistant';
+
+        return {
+            role,
+            content: m.content.toString()
+        };
+    });
+
+    // 3. Call the proxy service
+    const response = await aiService.chat(apiMessages, token);
+    const content = response.choices[0]?.message?.content || "No response generated";
+
+    // 4. Return the new message to satisfy the Graph (it will be appended due to reducer)
+    return {
+        messages: [new AIMessage(content)]
+    };
+}
+
+// =============================================================================
+// Service Export
+// =============================================================================
+
+export const langGraphService = {
+    /**
+     * Run the chat graph with history
+     */
+    async execute(
+        currentMessages: BaseMessage[],
+        userToken: string,
+    ): Promise<string> {
+        // Define the graph
+        const workflow = new StateGraph(GraphAnnotation)
+            .addNode("agent", callModel)
+            .addEdge(START, "agent")
+            .addEdge("agent", END);
+
+        const app = workflow.compile();
+
+        // Execute the graph
+        const result = await app.invoke(
+            { messages: currentMessages },
+            { configurable: { token: userToken } }
+        );
+
+        // Return the content of the last message (the AI response)
+        const lastMsg = result.messages[result.messages.length - 1];
+        return lastMsg.content.toString();
+    }
+};

src/utils/async_hooks_mock.ts

@@ -0,0 +1,22 @@
+/**
+ * Mock for Node.js async_hooks
+ * Used to fix LangGraph.js compatibility with React Native
+ */
+
+export class AsyncLocalStorage {
+    disable() { }
+    getStore() {
+        return undefined;
+    }
+    run(store: any, callback: (...args: any[]) => any, ...args: any[]) {
+        return callback(...args);
+    }
+    exit(callback: (...args: any[]) => any, ...args: any[]) {
+        return callback(...args);
+    }
+    enterWith(store: any) { }
+}
+
+export default {
+    AsyncLocalStorage,
+};

src/utils/token_utils.ts

@@ -0,0 +1,76 @@
+/**
+ * Token Utilities
+ * 
+ * Shared logic for trimming messages to stay within token limits.
+ */
+
+import { BaseMessage, SystemMessage } from "@langchain/core/messages";
+import { AIMessage as ServiceAIMessage } from "../services/ai.service";
+
+export const TOKEN_LIMIT = 10000;
+const CHARS_PER_TOKEN = 3; // Conservative estimate: 1 token ≈ 3 chars
+export const MAX_CHARS = TOKEN_LIMIT * CHARS_PER_TOKEN;
+
+/**
+ * Trims LangChain messages to fit within token limit
+ */
+export function trimLangChainMessages(messages: BaseMessage[]): BaseMessage[] {
+    let totalLength = 0;
+    const trimmed: BaseMessage[] = [];
+
+    // Always keep the system message if it's at the start
+    let systemMsg: BaseMessage | null = null;
+    if (messages.length > 0 && (messages[0] instanceof SystemMessage || (messages[0] as any)._getType?.() === 'system')) {
+        systemMsg = messages[0];
+        totalLength += systemMsg.content.toString().length;
+    }
+
+    // Iterate backwards and add messages until we hit the char limit
+    for (let i = messages.length - 1; i >= (systemMsg ? 1 : 0); i--) {
+        const msg = messages[i];
+        const len = msg.content.toString().length;
+
+        if (totalLength + len > MAX_CHARS) break;
+
+        trimmed.unshift(msg);
+        totalLength += len;
+    }
+
+    if (systemMsg) {
+        trimmed.unshift(systemMsg);
+    }
+
+    return trimmed;
+}
+
+/**
+ * Trims internal AIMessage format messages to fit within token limit
+ */
+export function trimInternalMessages(messages: ServiceAIMessage[]): ServiceAIMessage[] {
+    let totalLength = 0;
+    const trimmed: ServiceAIMessage[] = [];
+
+    // Always keep the system message if it's at the start
+    let systemMsg: ServiceAIMessage | null = null;
+    if (messages.length > 0 && messages[0].role === 'system') {
+        systemMsg = messages[0];
+        totalLength += systemMsg.content.length;
+    }
+
+    // Iterate backwards and add messages until we hit the char limit
+    for (let i = messages.length - 1; i >= (systemMsg ? 1 : 0); i--) {
+        const msg = messages[i];
+        const len = msg.content.length;
+
+        if (totalLength + len > MAX_CHARS) break;
+
+        trimmed.unshift(msg);
+        totalLength += len;
+    }
+
+    if (systemMsg) {
+        trimmed.unshift(systemMsg);
+    }
+
+    return trimmed;
+}