111 lines
3.1 KiB
TypeScript
111 lines
3.1 KiB
TypeScript
import { NextRequest, NextResponse } from 'next/server';
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import admin from '@/lib/firebase/admin';
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/**
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* Extract vision answers from chat history and save to project
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* This is a helper endpoint to migrate from AI chat-based vision collection
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* to the structured visionAnswers field
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*/
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export async function POST(
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request: NextRequest,
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{ params }: { params: Promise<{ projectId: string }> }
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) {
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try {
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const { projectId } = await params;
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const db = admin.firestore();
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console.log(`[Extract Vision] Extracting vision answers from chat for project ${projectId}`);
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// Get chat messages
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const conversationRef = db
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.collection('projects')
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.doc(projectId)
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.collection('conversations')
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.doc('ai_chat');
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const messagesSnapshot = await conversationRef
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.collection('messages')
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.orderBy('createdAt', 'asc')
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.get();
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if (messagesSnapshot.empty) {
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return NextResponse.json(
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{ error: 'No chat messages found' },
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{ status: 404 }
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);
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}
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const messages = messagesSnapshot.docs.map(doc => ({
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id: doc.id,
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...doc.data()
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}));
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console.log(`[Extract Vision] Found ${messages.length} total messages`);
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// Extract user messages (answers to the 3 vision questions)
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const userMessages = messages.filter((m: any) => m.role === 'user');
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console.log(`[Extract Vision] Found ${userMessages.length} user messages`);
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if (userMessages.length < 3) {
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return NextResponse.json(
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{
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error: 'Not enough answers found',
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details: `Found ${userMessages.length} answers, need 3`,
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userMessages: userMessages.map((m: any) => m.content?.substring(0, 100))
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},
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{ status: 400 }
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);
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}
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// The first 3 user messages should be the answers to Q1, Q2, Q3
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const visionAnswers = {
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q1: userMessages[0].content,
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q2: userMessages[1].content,
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q3: userMessages[2].content,
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allAnswered: true,
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updatedAt: new Date().toISOString(),
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};
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console.log(`[Extract Vision] Extracted vision answers:`, {
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q1: visionAnswers.q1.substring(0, 50) + '...',
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q2: visionAnswers.q2.substring(0, 50) + '...',
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q3: visionAnswers.q3.substring(0, 50) + '...',
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});
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// Save to project
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await db.collection('projects').doc(projectId).set(
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{
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visionAnswers,
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readyForMVP: true,
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currentPhase: 'mvp',
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phaseStatus: 'ready',
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},
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{ merge: true }
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);
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console.log(`[Extract Vision] ✅ Vision answers saved for project ${projectId}`);
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return NextResponse.json({
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success: true,
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message: 'Vision answers extracted and saved',
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visionAnswers: {
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q1: visionAnswers.q1.substring(0, 100) + '...',
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q2: visionAnswers.q2.substring(0, 100) + '...',
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q3: visionAnswers.q3.substring(0, 100) + '...',
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}
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});
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} catch (error) {
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console.error('[Extract Vision] Error:', error);
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return NextResponse.json(
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{
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error: 'Failed to extract vision answers',
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details: error instanceof Error ? error.message : String(error),
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},
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{ status: 500 }
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);
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}
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}
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