Integrated context-aware chatbot

Author: aaryagodbole

backend/.env.example

@@ -1,7 +1,7 @@
 JWT_SECRET=
 REFRESH_SECRET=
 SALTING=
-API_URL='http://localhost:4000/api/v1'
+API_URL=
 GOOGLE_CLIENT_ID=
 GOOGLE_CLIENT_SECRET=
 GOOGLE_CALLBACK_URL=

backend/bun.lock

@@ -39,6 +39,7 @@
     "typescript": "^5.8.3"
   },
   "dependencies": {
+    "@google/generative-ai": "^0.24.1",
     "@types/axios": "^0.14.4",
     "@types/bcrypt": "^6.0.0",
     "@types/cookie-parser": "^1.4.10",
@@ -59,6 +60,7 @@
     "helmet": "^8.1.0",
     "jsonwebtoken": "^9.0.2",
     "multer": "^2.0.2",
+    "node-fetch": "^3.3.2",
     "passport": "^0.7.0",
     "resend": "^6.5.2",
     "zod": "^4.0.9"

backend/package.json

@@ -0,0 +1,130 @@
+const formatHistory = (history: { from: string; text: string }[] = []) =>
+  history
+    .map((m) => `${m.from === "user" ? "User" : "Assistant"}: ${m.text}`)
+    .join("\n");
+
+export function buildPrompt({
+  path,
+  ragData,
+  userAnswer,
+  questionContext,
+  history = [],
+}: {
+  path: string;
+  ragData: any;
+  userAnswer: string;
+  questionContext?: any;
+  history?: { from: string; text: string }[];
+}) {
+  const baseRole = `
+You are Cortex, an intelligent AI analyst for "Call of Code".
+CRITICAL: Do NOT start a mock interview. Do NOT introduce yourself as Alex.
+Your ONLY job is to answer the user's question using the DATASET provided below.
+If the DATASET is empty, tell the user you don't see any interviews yet.
+Rules:
+- Always start with a helpful hint.
+- Do NOT give full solution unless user explicitly asks.
+- Be concise, friendly, and use markdown formatting.
+- Do NOT act as an interviewer.
+- Do NOT introduce yourself as "Alex" or start a mock session.
+- Be concise and use markdown.
+`;
+
+  console.log("🧠 QUESTION CONTEXT IN chatBrain 👉", questionContext);
+
+  // --- CASE 1: DSA TOPIC ONLY ---
+  if (questionContext?.type === "DSA" && questionContext.isTopicOnly) {
+    return `
+${baseRole}
+User is currently browsing the topic: ${questionContext.topicTitle}.
+
+Conversation so far:
+${formatHistory(history)}
+
+Instructions:
+- Provide a brief overview of ${questionContext.topicTitle}.
+- Mention common interview patterns.
+
+User Query: ${userAnswer}
+`;
+  }
+
+  // --- CASE 2: SPECIFIC DSA QUESTION ---
+  if (questionContext?.type === "DSA" && questionContext.questionId) {
+    const context = ragData ? `QUESTION: ${ragData.question}\nCONCEPT: ${ragData.concept}` : "No specific details available.";
+    
+    return `
+${baseRole}
+Conversation so far:
+${formatHistory(history)}
+
+CURRENT QUESTION: ${questionContext.questionName} (${questionContext.topicTitle})
+${context}
+
+USER ANSWER / CODE:
+${userAnswer}
+
+Instructions:
+- Give ONLY a hint first.
+- Point out logical mistakes.
+`;
+  }
+
+  // --- CASE 3: INTERVIEW ANALYST (COLLECTION) ---
+  if (questionContext?.type === "INTERVIEW_COLLECTION") {
+    // 🛡️ SAFETY CHECK: Ensure ragData is an array before mapping
+    const allExperiences = Array.isArray(ragData) 
+      ? ragData.map((exp: any) => `
+          Company: ${exp.company}
+          Verdict: ${exp.verdict}
+          Experience: ${exp.content}
+        `).join("\n---\n")
+      : "No interview data available to analyze.";
+
+    return `
+${baseRole}
+You are an Interview Analyst. You have access to ${questionContext.count || 0} interview stories.
+
+DATASET:
+${allExperiences}
+
+User Question: ${userAnswer}
+
+Instructions:
+- Analyze the common patterns in the stories provided.
+- Identify common mistakes leading to "Rejected" verdicts.
+- Determine which companies focused more on DSA.
+`;
+  }
+
+  // --- CASE 4: SINGLE INTERVIEW EXPERIENCE ---
+  // chatBrain.ts update for CASE 4
+// --- CASE 4: SINGLE INTERVIEW EXPERIENCE ---
+if (questionContext?.type === "INTERVIEW_EXPERIENCE") {
+  const interview = ragData || questionContext; 
+  // Added a check to see if content is actually there
+  const content = ragData?.content || "No database content found. Request might have failed.";
+
+  // LOGGING: Check your backend terminal to see what is being packed into the prompt
+  console.log("🛠️ PROMPT BUILDING WITH CONTENT:", content.substring(0, 50) + "...");
+
+  return `
+${baseRole}
+CURRENT CONTEXT:
+Company: ${interview.company}
+Role: ${interview.role}
+Verdict: ${interview.verdict}
+Full Experience: ${content}
+
+User Query: ${userAnswer}
+`;
+}
+
+  // --- CASE 5: DEFAULT FALLBACK ---
+  return `
+${baseRole}
+Conversation so far:
+${formatHistory(history)}
+User message: ${userAnswer}
+`;
+}

backend/src/ai/chatBrain.ts

@@ -8,6 +8,9 @@ import { errorHandler } from './utils/apiError';
 import rateLimit from 'express-rate-limit';
 import helmet from 'helmet';
 import cookieParser from 'cookie-parser'
+import chatRoutes from "./routes/chat.route";
+
+
 
 
 const app = express();
@@ -32,6 +35,8 @@ app.use(limiter)
 app.use(cookieParser());
 app.use(json());
 app.use(urlencoded({ extended: true }));
+app.use(express.json()); 
+app.use("/chat", chatRoutes); 
 
 const upload = multer({ storage: multer.memoryStorage(),
   limits: { fileSize: 2 * 1024 * 1024 }

backend/src/app.ts

@@ -0,0 +1,59 @@
+import { Request, Response } from "express";
+import { fetchRAGContext } from "../services/retrival";
+import { buildPrompt } from "../ai/chatBrain";
+import { geminiModel } from "../services/ai";
+
+export async function chatController(req: Request, res: Response) {
+  try {
+    const {
+      path,
+      userAnswer,
+      questionContext,
+      history,
+    } = req.body;
+
+    // 1️⃣ Debugging: Check what the frontend is actually sending
+    console.log("📥 Incoming Request Context:", JSON.stringify(questionContext, null, 2));
+
+    // 2️⃣ Fetch RAG data (Ab ye Topic aur Question dono handle karega)
+    const ragData = await fetchRAGContext(questionContext);
+    if (ragData) {
+    console.log("✅ DATA FOUND. Company:", ragData.company || "N/A");
+    console.log("📝 CONTENT PREVIEW:", ragData.content?.substring(0, 50) + "...");
+} else {
+    console.log("🔍 DATA TO AI: No record found.");
+}
+
+    // 3️⃣ Build smart prompt 
+    // Isme hum context pass kar rahe hain taaki AI ko pata chale user kahan hai
+    const prompt = buildPrompt({
+      path,
+      ragData,
+      userAnswer,
+      questionContext,
+      history,
+    });
+
+    // 4️⃣ Call Gemini
+    const chat = geminiModel.startChat({
+      history: [], // History hum buildPrompt ke andar handle kar rahe hain string format mein
+    });
+
+    const result = await chat.sendMessage(prompt); // 'prompt' mein baseRole, ragData, aur history sab hai.
+    const reply = result.response.text();
+
+    // 5️⃣ Send Response
+    res.json({ reply });
+
+  } catch (error) {
+    console.error("❌ Chat Controller Error:", error);
+
+    const err = error as Error;
+
+    // Error response ko thoda better banaya taaki debugging easy ho
+    res.status(500).json({
+      reply: "Cortex is having trouble accessing the context right now. Please try again.",
+      error: err.message
+    });
+  }
+}

backend/src/controllers/chatController.ts

@@ -0,0 +1,8 @@
+import { Router } from "express";
+import { chatController } from "../controllers/chatController";
+
+const chatRouter = Router();
+
+chatRouter.post("/", chatController);
+
+export default chatRouter;

backend/src/routes/chat.route.ts

@@ -0,0 +1,7 @@
+import { GoogleGenerativeAI } from "@google/generative-ai";
+
+const genAI = new GoogleGenerativeAI(process.env.GEMINI_API_KEY!);
+
+export const geminiModel = genAI.getGenerativeModel({
+  model: "gemini-2.5-flash",
+});

backend/src/services/ai.ts

@@ -0,0 +1,67 @@
+import fetch from "node-fetch";
+
+export async function fetchRAGContext(questionContext?: any) {
+  if (!questionContext) return null;
+
+  try {
+    // --- 1. DSA LOGIC ---
+    if (questionContext.type === "DSA") {
+      if (questionContext.questionId) {
+        const res = await fetch(`${process.env.API_URL}/dsa/questions/${questionContext.questionId}`);
+        return res.ok ? await res.json() : null;
+      }
+
+      if (questionContext.isTopicOnly && questionContext.topicId) {
+        const res = await fetch(`${process.env.API_URL}/topics/${questionContext.topicId}`);
+        return res.ok ? await res.json() : null;
+      }
+    }
+
+    // --- 2. INTERVIEW COLLECTION (Analysis Mode) ---
+   // --- 2. INTERVIEW COLLECTION (Analysis Mode) ---
+if (questionContext.type === "INTERVIEW_COLLECTION") {
+  // Option A: Specific IDs fetch karein (Agar API support karti hai)
+  if (questionContext.interviewIds && questionContext.interviewIds.length > 0) {
+    // Aap ek query parameter bhej sakte hain ya loop chala sakte hain
+    const res = await fetch(`${process.env.API_URL}/interviews?ids=${questionContext.interviewIds.join(',')}`);
+    const data = await res.json() as any;
+    return Array.isArray(data) ? data : (data.interviews || []);
+  }
+
+  // Option B: Backup - Saare fetch karein (Jo aap abhi kar rahe hain)
+  const res = await fetch(`${process.env.API_URL}/interviews/all`); 
+  if (!res.ok) return [];
+  const data = await res.json() as any;
+  return Array.isArray(data) ? data : (data.interviews || []);
+}
+
+    // --- 3. SINGLE INTERVIEW (Specific Experience) ---
+  // retrival.ts fix
+
+// --- 3. SINGLE INTERVIEW (Specific Experience) ---
+// retrival.ts
+// retrival.ts
+if (questionContext.type === "INTERVIEW_EXPERIENCE") {
+   // Added /v1 to match app.use("/api/v1", routes(upload)) in app.ts
+   const res = await fetch(`http://localhost:3000/api/v1/interviews/${questionContext.id}`);
+   
+   if (res.ok) {
+     const json = await res.json() as any; 
+     
+     // Extract the actual data (handling potential API wrappers)
+     const actualData = json.data || json.interview || json;
+     
+     console.log("✅ SUCCESS: Data found for", actualData.company);
+     return { ...questionContext, ...actualData }; 
+   }
+   console.log("❌ Fetch failed. Status:", res.status); 
+   return questionContext; 
+}
+
+  } catch (error) {
+    console.error("❌ Error in RAG retrieval:", error);
+    return null;
+  }
+
+  return null;
+}