AI coach fixed: acquired access to context data

App.tsx

@@ -9,7 +9,7 @@ import Plans from './components/Plans';
 import Login from './components/Login';
 import Profile from './components/Profile';
 import { TabView, WorkoutSession, WorkoutSet, WorkoutPlan, User, Language } from './types';
-import { getSessions, saveSession, deleteSession } from './services/storage';
+import { getSessions, saveSession, deleteSession, getPlans } from './services/storage';
 import { getCurrentUserProfile, getMe } from './services/auth';
 import { getSystemLanguage } from './services/i18n';
 
@@ -19,6 +19,7 @@ function App() {
   const [language, setLanguage] = useState<Language>('en');
 
   const [sessions, setSessions] = useState<WorkoutSession[]>([]);
+  const [plans, setPlans] = useState<WorkoutPlan[]>([]);
   const [activeSession, setActiveSession] = useState<WorkoutSession | null>(null);
   const [activePlan, setActivePlan] = useState<WorkoutPlan | null>(null);
 
@@ -46,9 +47,12 @@ function App() {
       if (currentUser) {
         const s = await getSessions(currentUser.id);
         setSessions(s);
-        // Profile fetch is skipped for now as it returns undefined
+        // Load plans
+        const p = await getPlans(currentUser.id);
+        setPlans(p);
       } else {
         setSessions([]);
+        setPlans([]);
       }
     };
     loadSessions();
@@ -197,7 +201,7 @@ function App() {
             />
           )}
           {currentTab === 'STATS' && <Stats sessions={sessions} lang={language} />}
-          {currentTab === 'AI_COACH' && <AICoach history={sessions} lang={language} />}
+          {currentTab === 'AI_COACH' && <AICoach history={sessions} userProfile={currentUser.profile} plans={plans} lang={language} />}
           {currentTab === 'PROFILE' && (
             <Profile
               user={currentUser}

components/AICoach.tsx

@@ -2,12 +2,14 @@
 import React, { useState, useRef, useEffect } from 'react';
 import { Send, Bot, User, Loader2, AlertTriangle } from 'lucide-react';
 import { createFitnessChat } from '../services/geminiService';
-import { WorkoutSession, Language } from '../types';
+import { WorkoutSession, Language, UserProfile, WorkoutPlan } from '../types';
 import { Chat, GenerateContentResponse } from '@google/genai';
 import { t } from '../services/i18n';
 
 interface AICoachProps {
   history: WorkoutSession[];
+  userProfile?: UserProfile;
+  plans?: WorkoutPlan[];
   lang: Language;
 }
 
@@ -17,7 +19,7 @@ interface Message {
   text: string;
 }
 
-const AICoach: React.FC<AICoachProps> = ({ history, lang }) => {
+const AICoach: React.FC<AICoachProps> = ({ history, userProfile, plans, lang }) => {
   const [messages, setMessages] = useState<Message[]>([
     { id: 'intro', role: 'model', text: t('ai_intro', lang) }
   ]);
@@ -29,7 +31,7 @@ const AICoach: React.FC<AICoachProps> = ({ history, lang }) => {
 
   useEffect(() => {
     try {
-      const chat = createFitnessChat(history, lang);
+      const chat = createFitnessChat(history, lang, userProfile, plans);
       if (chat) {
         chatSessionRef.current = chat;
       } else {
@@ -38,7 +40,7 @@ const AICoach: React.FC<AICoachProps> = ({ history, lang }) => {
     } catch (err) {
       setError("Failed to initialize AI");
     }
-  }, [history, lang]);
+  }, [history, lang, userProfile, plans]);
 
   const scrollToBottom = () => {
     messagesEndRef.current?.scrollIntoView({ behavior: "smooth" });
@@ -57,7 +59,7 @@ const AICoach: React.FC<AICoachProps> = ({ history, lang }) => {
     setLoading(true);
 
     try {
-      const result: GenerateContentResponse = await chatSessionRef.current.sendMessage({ message: userMsg.text });
+      const result: GenerateContentResponse = await chatSessionRef.current.sendMessage(userMsg.text);
       const text = result.text;
 
       const aiMsg: Message = {

server/src/routes/ai.ts

@@ -1,18 +1,30 @@
-import express from 'express';
+import express, { Request, Response, NextFunction } from 'express';
 import { GoogleGenerativeAI } from '@google/generative-ai';
 import jwt from 'jsonwebtoken';
 
+interface JwtPayload {
+    userId: string;
+    role: string;
+}
+
+interface AuthRequest extends Request {
+    user?: JwtPayload;
+}
+
 const router = express.Router();
 const JWT_SECRET = process.env.JWT_SECRET || 'secret';
 const API_KEY = process.env.API_KEY;
 const MODEL_ID = 'gemini-2.0-flash';
 
-const authenticate = (req: any, res: any, next: any) => {
+// Store chat sessions in memory (in production, use Redis or similar)
+const chatSessions = new Map<string, any>();
+
+const authenticate = (req: AuthRequest, res: Response, next: NextFunction) => {
     const token = req.headers.authorization?.split(' ')[1];
     if (!token) return res.status(401).json({ error: 'Unauthorized' });
 
     try {
-        const decoded = jwt.verify(token, JWT_SECRET) as any;
+        const decoded = jwt.verify(token, JWT_SECRET) as JwtPayload;
         req.user = decoded;
         next();
     } catch {
@@ -22,31 +34,83 @@ const authenticate = (req: any, res: any, next: any) => {
 
 router.use(authenticate);
 
-router.post('/chat', async (req, res) => {
+router.post('/chat', async (req: AuthRequest, res: Response) => {
     try {
-        const { history, message } = req.body;
+        const { systemInstruction, userMessage, sessionId } = req.body;
 
         if (!API_KEY) {
             return res.status(500).json({ error: 'AI service not configured' });
         }
 
+        if (!userMessage) {
+            return res.status(400).json({ error: 'User message is required' });
+        }
+
+        if (!req.user) {
+            return res.status(401).json({ error: 'Unauthorized' });
+        }
+
         const ai = new GoogleGenerativeAI(API_KEY);
+        const userId = req.user.userId;
+        const chatKey = `${userId}-${sessionId || 'default'}`;
 
-        const { systemInstruction, userMessage } = req.body;
+        // Get or create chat session
+        let chat = chatSessions.get(chatKey);
 
-        const model = ai.getGenerativeModel({
+        if (!chat || systemInstruction) {
-            model: MODEL_ID
+            // Create new chat with system instruction
-        });
+            const model = ai.getGenerativeModel({
+                model: MODEL_ID,
+                systemInstruction: systemInstruction || 'You are a helpful fitness coach.'
+            });
 
-        const prompt = `${systemInstruction}\n\nUser: ${userMessage}`;
+            chat = model.startChat({
-        const result = await model.generateContent(prompt);
+                history: []
+            });
+
+            chatSessions.set(chatKey, chat);
+        }
+
+        // Send message and get response
+        const result = await chat.sendMessage(userMessage);
         const response = result.response.text();
 
         res.json({ response });
+    } catch (error: any) {
+        console.error('AI Chat Error:', error);
+
+        // Provide more detailed error messages
+        let errorMessage = 'Failed to generate AI response';
+        if (error.message?.includes('API key')) {
+            errorMessage = 'AI service authentication failed';
+        } else if (error.message?.includes('quota')) {
+            errorMessage = 'AI service quota exceeded';
+        } else if (error.message) {
+            errorMessage = error.message;
+        }
+
+        res.status(500).json({ error: errorMessage });
+    }
+});
+
+// Clear chat session endpoint
+router.delete('/chat/:sessionId', async (req: AuthRequest, res: Response) => {
+    try {
+        if (!req.user) {
+            return res.status(401).json({ error: 'Unauthorized' });
+        }
+
+        const userId = req.user.userId;
+        const sessionId = req.params.sessionId || 'default';
+        const chatKey = `${userId}-${sessionId}`;
+
+        chatSessions.delete(chatKey);
+        res.json({ success: true });
     } catch (error) {
-        console.error(error);
+        console.error('Clear chat error:', error);
-        res.status(500).json({ error: String(error) });
+        res.status(500).json({ error: 'Failed to clear chat session' });
     }
 });
 
 export default router;
+

services/geminiService.ts

@@ -1,49 +1,119 @@
-import { WorkoutSession } from '../types';
+import { WorkoutSession, UserProfile, WorkoutPlan } from '../types';
 import { api } from './api';
 
-export const createFitnessChat = (history: WorkoutSession[], lang: 'en' | 'ru' = 'ru'): any => {
+interface FitnessChatOptions {
-  // The original returned a Chat object.
+  history: WorkoutSession[];
-  // Now we need to return something that behaves like it or refactor the UI.
+  userProfile?: UserProfile;
-  // The UI likely calls `chat.sendMessage(msg)`.
+  plans?: WorkoutPlan[];
-  // So we return an object with `sendMessage`.
+  lang?: 'en' | 'ru';
+  sessionId?: string;
+}
 
-  // Summarize data to reduce token count while keeping relevant context
+export const createFitnessChat = (
-  const summary = history.slice(0, 10).map(s => ({
+  history: WorkoutSession[],
+  lang: 'en' | 'ru' = 'ru',
+  userProfile?: UserProfile,
+  plans?: WorkoutPlan[]
+): any => {
+  // Generate a unique session ID for this chat instance
+  const sessionId = crypto.randomUUID();
+
+  // Summarize workout history
+  const workoutSummary = history.slice(0, 20).map(s => ({
     date: new Date(s.startTime).toLocaleDateString(lang === 'ru' ? 'ru-RU' : 'en-US'),
     userWeight: s.userBodyWeight,
-    exercises: s.sets.map(set => `${set.exerciseName}: ${set.weight ? set.weight + (lang === 'ru' ? 'кг' : 'kg') : ''}${set.reps ? ' x ' + set.reps + (lang === 'ru' ? 'повт' : 'reps') : ''} ${set.distanceMeters ? set.distanceMeters + (lang === 'ru' ? 'м' : 'm') : ''}`).join(', ')
+    planName: s.planName,
+    exercises: s.sets.map(set => {
+      const parts = [];
+      parts.push(set.exerciseName);
+      if (set.weight) parts.push(`${set.weight}${lang === 'ru' ? 'кг' : 'kg'}`);
+      if (set.reps) parts.push(`${set.reps}${lang === 'ru' ? 'повт' : 'reps'}`);
+      if (set.distanceMeters) parts.push(`${set.distanceMeters}${lang === 'ru' ? 'м' : 'm'}`);
+      if (set.durationSeconds) parts.push(`${set.durationSeconds}${lang === 'ru' ? 'сек' : 's'}`);
+      return parts.join(' ');
+    }).join(', ')
   }));
 
+  // Calculate personal records
+  const exerciseRecords = new Map<string, { maxWeight?: number; maxReps?: number; maxDistance?: number }>();
+  history.forEach(session => {
+    session.sets.forEach(set => {
+      const current = exerciseRecords.get(set.exerciseName) || {};
+      exerciseRecords.set(set.exerciseName, {
+        maxWeight: Math.max(current.maxWeight || 0, set.weight || 0),
+        maxReps: Math.max(current.maxReps || 0, set.reps || 0),
+        maxDistance: Math.max(current.maxDistance || 0, set.distanceMeters || 0)
+      });
+    });
+  });
+
+  const personalRecords = Array.from(exerciseRecords.entries()).map(([name, records]) => ({
+    exercise: name,
+    ...records
+  }));
+
+  // Build comprehensive system instruction
   const systemInstruction = lang === 'ru' ? `
-    Ты — опытный и поддерживающий фитнес-тренер. 
+    Ты — опытный и поддерживающий фитнес-тренер AI Expert. 
     Твоя задача — анализировать тренировки пользователя и давать краткие, полезные советы на русском языке.
     
-    Учитывай вес пользователя (userWeight в json), если он указан, при анализе прогресса в упражнениях с собственным весом.
+    ДАННЫЕ ПОЛЬЗОВАТЕЛЯ:
+    ${userProfile ? `
+    - Вес: ${userProfile.weight || 'не указан'} кг
+    - Рост: ${userProfile.height || 'не указан'} см
+    - Пол: ${userProfile.gender || 'не указан'}
+    ` : 'Профиль не заполнен'}
     
-    Вот последние 10 тренировок пользователя (в формате JSON):
+    ТРЕНИРОВОЧНЫЕ ПЛАНЫ:
-    ${JSON.stringify(summary)}
+    ${plans && plans.length > 0 ? JSON.stringify(plans.map(p => ({ name: p.name, exercises: p.steps.map(s => s.exerciseName) }))) : 'Нет активных планов'}
-
+    
-    Если пользователь спрашивает о прогрессе, используй эти данные.
+    ИСТОРИЯ ТРЕНИРОВОК (последние 20):
-    Отвечай емко, мотивирующе. Избегай длинных лекций, если не просили.
+    ${JSON.stringify(workoutSummary, null, 2)}
+    
+    ЛИЧНЫЕ РЕКОРДЫ:
+    ${JSON.stringify(personalRecords, null, 2)}
+    
+    ИНСТРУКЦИИ:
+    - Используй эти данные для анализа прогресса и ответов на вопросы
+    - Учитывай вес пользователя при анализе упражнений с собственным весом
+    - Будь конкретным и ссылайся на реальные данные из истории
+    - Отвечай емко, мотивирующе
+    - Если данных недостаточно для ответа, честно скажи об этом
   ` : `
-    You are an experienced and supportive fitness coach.
+    You are an experienced and supportive fitness coach called AI Expert.
     Your task is to analyze the user's workouts and provide concise, helpful advice in English.
     
-    Consider the user's weight (userWeight in json), if provided, when analyzing progress in bodyweight exercises.
+    USER PROFILE:
+    ${userProfile ? `
+    - Weight: ${userProfile.weight || 'not specified'} kg
+    - Height: ${userProfile.height || 'not specified'} cm
+    - Gender: ${userProfile.gender || 'not specified'}
+    ` : 'Profile not filled'}
     
-    Here are the user's last 10 workouts (in JSON format):
+    WORKOUT PLANS:
-    ${JSON.stringify(summary)}
+    ${plans && plans.length > 0 ? JSON.stringify(plans.map(p => ({ name: p.name, exercises: p.steps.map(s => s.exerciseName) }))) : 'No active plans'}
-
+    
-    If the user asks about progress, use this data.
+    WORKOUT HISTORY (last 20 sessions):
-    Answer concisely and motivationally. Avoid long lectures unless asked.
+    ${JSON.stringify(workoutSummary, null, 2)}
-    ALWAYS answer in the language the user speaks to you, defaulting to English if unsure.
+    
+    PERSONAL RECORDS:
+    ${JSON.stringify(personalRecords, null, 2)}
+    
+    INSTRUCTIONS:
+    - Use this data to analyze progress and answer questions
+    - Consider user's weight when analyzing bodyweight exercises
+    - Be specific and reference actual data from the history
+    - Answer concisely and motivationally
+    - If there's insufficient data to answer, be honest about it
+    - ALWAYS answer in the language the user speaks to you
   `;
 
   return {
     sendMessage: async (userMessage: string) => {
       const res = await api.post('/ai/chat', {
         systemInstruction,
-        userMessage
+        userMessage,
+        sessionId
       });
       return {
         text: res.response,