feat: add similar questions generation and improve bot service logging

src/helper/utils/index.ts

@@ -60,7 +60,6 @@ export function generateSearchQuery(condition: {
   q?: string;
 }): object {
   const { botId, q } = condition;
-  console.log('🚀 ~ condition:', condition);
   const query: Record<string, any> = {};
 
   if (q !== undefined && q !== '') {

src/modules/auth/auth.service.ts

@@ -184,7 +184,6 @@ export class AuthService {
    */
   async forgotPassword(email: string): Promise<{ message: string }> {
     const user = await this.userRepo.findUser({ email });
-    console.log('🚀 ~ AuthService ~ forgotPassword ~ user:', user);
 
     if (!user)
       throw new HttpException(

src/modules/conversation/conversation.service.ts

@@ -141,7 +141,6 @@ export class ConversationService {
         conversation.botId?._id.toString(),
         conversation._id ?? id,
       );
-      console.log('🚀 ~ ConversationService ~ botMessage:', botMessage);
 
       const botMessageUpdate =
         await this.conversationRepository.addMessageToConversation(
@@ -228,7 +227,6 @@ export class ConversationService {
       botId: botId,
       limit: 3,
     });
-    console.log('🚀 231~ ConversationService ~ botId:', botId);
 
     if (searchResults.data.length === 0) {
       const botDetails = await this.botRepo.findBotById(botId);

src/modules/gemini/gemini.controller.ts

@@ -21,4 +21,11 @@ export class GeminiController {
     const ans = await this.geminiService.enhanceAnswer(question, answer);
     return ans;
   }
+  @Get('/similar')
+  async similarQuestions(
+    @Query('question') question: string,
+  ): Promise<{ questions: string[] }> {
+    const ans = await this.geminiService.generateSimilarQuestions(question);
+    return ans;
+  }
 }

src/modules/gemini/gemini.service.ts

@@ -2,6 +2,8 @@
 import { Injectable } from '@nestjs/common';
 import { GoogleGenerativeAI } from '@google/generative-ai';
 import * as dotenv from 'dotenv';
+import { questionGeneratorPrompt, textGeneratorPrompt } from 'src/prompts';
+import { extractJsonFromText } from 'src/utils';
 
 dotenv.config();
 
@@ -10,6 +12,7 @@ export class GeminiService {
   private genAI: GoogleGenerativeAI;
   private embeddingModel: any;
   private textModel: any;
+  private questionGeneratorModel: any;
 
   constructor() {
     // Initialize Google Generative AI with your API key
@@ -22,31 +25,16 @@ export class GeminiService {
       model: 'text-embedding-004',
     });
 
+    // Initialize the question generation model
+    this.questionGeneratorModel = this.genAI.getGenerativeModel({
+      model: 'gemini-2.0-flash',
+      systemInstruction: questionGeneratorPrompt,
+    });
+
     // Initialize the text generation model
     this.textModel = this.genAI.getGenerativeModel({
       model: 'gemini-2.0-flash',
-      systemInstruction: `
-      You are an intelligent assistant for a website FAQ. Your task is to rewrite formal or technical answers into clear, friendly, and helpful responses that sound like they're from a knowledgeable human.
-
-      Rules to follow:
-      1. Stick to the facts — avoid adding guesses or unnecessary details.
-      2. Use a natural, friendly, and helpful tone that feels human, not robotic.
-      3. Keep the response concise yet informative.
-      4. Use simple, everyday language — avoid jargon unless it's essential for understanding.
-      5. Ensure all key information from the original answer is preserved.
-      6. Structure the response logically, making it easy to follow.
-      7. If the question is unclear, provide the most relevant and practical answer without over-explaining.
-      8. IMPORTANT: Format your entire response using proper markdown. Use markdown formatting for:
-         - Headings (## for main headings, ### for subheadings)
-         - **Bold text** for emphasis
-         - *Italic text* for secondary emphasis
-         - Bullet points and numbered lists
-         - Code blocks with backticks when showing technical content
-         - Tables when presenting structured information
-         - > Blockquotes for highlighting important information
-
-      **Output only the improved answer with proper markdown formatting — no introductions, explanations, or formatting comments.**
-      `,
+      systemInstruction: textGeneratorPrompt,
     });
   }
 
@@ -113,6 +101,35 @@ Format your response using proper markdown including headings, bold/italic text,
       throw new Error('Failed to generate embeddings');
     }
   }
+  /**
+   * Generates similar questions from a given question
+   * @param question - The question to generate similar questions from
+   * @returns Array of similar questions
+   *
+   * Note: This is a simple implementation for generating similar questions. In a real-world scenario, you might want to use a more sophisticated method like semantic search or transformer models.
+   */
+
+  async generateSimilarQuestions(
+    question: string,
+  ): Promise<{ questions: string[] }> {
+    try {
+      const result = await this.questionGeneratorModel.generateContent({
+        contents: [{ role: 'user', parts: [{ text: question }] }],
+        generationConfig: {
+          temperature: 0.2,
+          topK: 40,
+          topP: 0.95,
+          maxOutputTokens: 150,
+        },
+      });
+
+      const response = result.response;
+      return extractJsonFromText(response.text());
+    } catch (error) {
+      console.error('Error generating similar questions:', error);
+      throw new Error('Failed to generate similar questions');
+    }
+  }
 
   /**
    * Comprehensive method to process a FAQ item - enhances the answer and generates embeddings

src/modules/qna/qna.repository.ts

@@ -32,7 +32,6 @@ export class QnARepository {
     try {
       const { skip, limit } = pagination;
       const { botId } = query;
-      console.log('🚀 ~ QnARepository ~ botId:', botId);
 
       let sqlQuery =
         'SELECT id, question, answer, "botId", "createdAt", "updatedAt" FROM question_n_answers';
@@ -67,7 +66,7 @@ export class QnARepository {
 
       if (botId) {
         sqlQuery += ' WHERE "botId" = $1';
-        queryParams.push(botId);
+        queryParams.push(botId?.toString());
       }
 
       const result = await client.query(sqlQuery, queryParams);
@@ -78,7 +77,6 @@ export class QnARepository {
   }
 
   async findVectorById(id: string) {
-    console.log('🚀 ~ QnARepository ~ findVectorById ~ id:', id);
     const client = await this.dbService.getClient();
     try {
       const result = await client.query(

src/modules/qna/qna.service.ts

@@ -51,6 +51,40 @@ export class QnAService {
         embedding,
       );
 
+      if (!createdQna) {
+        throw new Error(QnaErrorMessages.COULD_NOT_CREATE_QNA);
+      }
+      const { questions: similarQuestions = [] } =
+        (await this.geminiService.generateSimilarQuestions(question)) ?? {};
+      console.log(
+        '🚀 ~ QnAService ~ create ~ similarQuestions:',
+        similarQuestions,
+      );
+
+      if (similarQuestions?.length > 0) {
+        const insertPromises = similarQuestions?.map(
+          async (similarQuestion) => {
+            try {
+              const similarEmbedding =
+                await this.geminiService.generateEmbeddings(similarQuestion);
+              return this.qnaRepo.insertVector(
+                similarQuestion,
+                answer,
+                botId,
+                similarEmbedding,
+              );
+            } catch (error) {
+              console.error(
+                `Error processing similar question "${similarQuestion}":`,
+                error,
+              );
+            }
+          },
+        );
+
+        await Promise.all(insertPromises);
+      }
+
       return this.apiResponse.success(createdQna);
     } catch (error) {
       throw new HttpException(
@@ -64,7 +98,6 @@ export class QnAService {
 
   async findAll(condition: { q: string }, pagination: PaginationQueryDto) {
     const query = generateSearchQuery(condition);
-    console.log('🚀 ~ QnAService ~ findAll ~ query:', query);
 
     // Paginate the list of users based on the generated query, role IDs query, and pagination settings
     const { data, page, limit, total } = await this.paginationService.paginate(

src/modules/user/user.service.ts

@@ -126,7 +126,6 @@ export class UserService {
       },
       pagination,
     );
-    console.log('🚀 ~ UserService ~ total:', total);
 
     const users: UserInterface[] = [];
     for (const user of data as UserInterface[]) {

src/prompts/index.ts

@@ -0,0 +1,28 @@
+export const textGeneratorPrompt = `You are an intelligent assistant for a website FAQ. Your task is to rewrite formal or technical answers into clear, friendly, and helpful responses that sound like they're from a knowledgeable human.
+
+      Rules to follow:
+      1. Stick to the facts — avoid adding guesses or unnecessary details.
+      2. Use a natural, friendly, and helpful tone that feels human, not robotic.
+      3. Keep the response concise yet informative.
+      4. Use simple, everyday language — avoid jargon unless it's essential for understanding.
+      5. Ensure all key information from the original answer is preserved.
+      6. Structure the response logically, making it easy to follow.
+      7. If the question is unclear, provide the most relevant and practical answer without over-explaining.
+      8. IMPORTANT: Format your entire response using proper markdown. Use markdown formatting for:
+         - Headings (## for main headings, ### for subheadings)
+         - **Bold text** for emphasis
+         - *Italic text* for secondary emphasis
+         - Bullet points and numbered lists
+         - Code blocks with backticks when showing technical content
+         - Tables when presenting structured information
+         - > Blockquotes for highlighting important information
+
+      **Output only the improved answer with proper markdown formatting — no introductions, explanations, or formatting comments.**`;
+
+export const questionGeneratorPrompt = `You are an intelligent assistant for a generating similar question from given a question. and make sure you return this format
+questions:[
+  "put similar question of the given questions here?",
+]
+  make sure, you are strictly bound to return the output in the above format. I mean maintain this json format. 
+  only and only in json format but don't add code format '''json like that only return the json.
+  `;

src/utils/index.ts

@@ -15,3 +15,48 @@ export function toObjectId(id: string): mongoose.Types.ObjectId {
   }
   return new mongoose.Types.ObjectId(id);
 }
+/**
+ * Extracts a JSON object from a string containing JSON.
+ * @param {string} text - The text containing JSON.
+ * @returns {object|null} - The extracted JSON object or null if extraction fails.
+ */
+export function extractJsonFromText(text: string) {
+  try {
+    // Look for patterns that might be JSON objects
+    const jsonRegex = /{[\s\S]*?}/g;
+    const matches = text.match(jsonRegex);
+
+    if (!matches || matches.length === 0) {
+      return null;
+    }
+
+    // Try to parse each match until we find valid JSON
+    for (const match of matches) {
+      try {
+        const parsedJson = JSON.parse(match);
+        // Check if the parsed object has the expected structure
+        if (
+          parsedJson &&
+          parsedJson.questions &&
+          Array.isArray(parsedJson.questions)
+        ) {
+          return parsedJson;
+        }
+      } catch (innerError) {
+        // Skip invalid JSON matches
+        continue;
+      }
+    }
+
+    // If we haven't returned yet, try to parse the largest match
+    // (which is likely to be the complete JSON object)
+    const largestMatch = matches.reduce(
+      (a, b) => (a.length > b.length ? a : b),
+      '',
+    );
+    return JSON.parse(largestMatch);
+  } catch (error) {
+    console.error('Error extracting JSON:', error);
+    return null;
+  }
+}