add chat features with documents

Author: kyawzinthant-coding

dump.rdb

@@ -31,6 +31,8 @@ export const pdfUploadFilesController = async (
       message: `Successfully cleared old data and queued ${files.length} new files for processing!`,
     });
   } catch (error) {
+    console.error("🔴 FULL ERROR OBJECT IN CONTROLLER:", error);
+
     for (const file of files) {
       fs.unlink(file.path);
     }

src/controllers/pdf/pdf-upload.ts

@@ -0,0 +1,31 @@
+// src/controllers/pdf/pdf-chat.ts
+import { Request, Response } from "express";
+import { queryKnowledgeBase } from "../../service/vector-store-service";
+import { generateChatResponse } from "../../service/ai-response-service";
+
+export const pdfChatController = async (
+  req: Request,
+  res: Response
+): Promise<any> => {
+  try {
+    const { question } = req.body;
+
+    if (!question) {
+      return res.status(400).json({ message: "Question is required." });
+    }
+
+    // 1. Retrieve relevant context from your knowledge base
+    const context = await queryKnowledgeBase(question);
+
+    // 2. Generate a response from the AI using the context
+    const answer = await generateChatResponse(question, context);
+
+    res.status(200).json({ answer });
+  } catch (error: any) {
+    console.error("🔴 Error in chat controller:", error);
+    res.status(500).json({
+      message: "An error occurred while generating a response.",
+      error: error.message,
+    });
+  }
+};

src/controllers/pdf/pdg-chat.ts

@@ -1,8 +1,10 @@
 import express from "express";
 import { pdfUploadFilesController } from "../controllers/pdf/pdf-upload";
 import { upload } from "../middleware./uploadfiles";
+import { pdfChatController } from "../controllers/pdf/pdg-chat";
 const router = express.Router();
 
 router.post("/uploads", upload.array("files", 10), pdfUploadFilesController);
+router.post("/chat", pdfChatController);
 
 export default router;

src/routes/PDF-routes.ts

@@ -0,0 +1,33 @@
+import "dotenv/config";
+import { GoogleGenerativeAI } from "@google/generative-ai";
+
+const genAI = new GoogleGenerativeAI(process.env.GEMINI_API_KEY!);
+
+const model = genAI.getGenerativeModel({ model: "gemini-pro" });
+
+export async function generateChatResponse(
+  question: string,
+  context: string[]
+): Promise<string> {
+  // Construct a detailed prompt for the AI
+  const prompt = `You are an expert assistant.
+   Using ONLY the following context from documents,
+    please answer the user's question.
+    The context is provided in a JSON array. 
+    If the answer is not in the context, say 'I cannot find that information in the provided documents.'
+
+  Context:
+  ${JSON.stringify(context)}
+
+  User's Question:
+  ${question}`;
+
+  try {
+    const result = await model.generateContent(prompt);
+    const response = await result.response;
+    return response.text();
+  } catch (error) {
+    console.error("Error generating chat response:", error);
+    throw new Error("Failed to generate response from AI model.");
+  }
+}

src/service/ai-response-service.ts

@@ -24,14 +24,29 @@ export async function getKnowledgeCollection() {
   return collection;
 }
 
+export async function queryKnowledgeBase(question: string): Promise<string[]> {
+  const collection = getKnowledgeCollection();
+
+  const results = (await collection).query({
+    queryTexts: [question],
+    nResults: 5,
+  });
+
+  return (await results).documents[0];
+}
+
 export async function cleanUpPreviousData() {
   try {
     await client.deleteCollection({ name: "insight_engine_knowledge" });
     console.log("✅ Previous collection deleted successfully.");
   } catch (error: any) {
+    if (error.name === "ChromaNotFoundError") {
+      console.log("No previous collection to delete. Starting fresh.");
+    }
     if (error.message.includes("does not exist")) {
       console.log("No previous collection to delete. Starting fresh.");
     } else {
+      console.log(error);
       throw error;
     }
   }