VIBN Frontend for Coolify deployment

app/api/projects/[projectId]/extract-from-chat/route.ts

@@ -0,0 +1,98 @@
+import { NextResponse } from 'next/server';
+import { FieldValue } from 'firebase-admin/firestore';
+import { GeminiLlmClient } from '@/lib/ai/gemini-client';
+import { runChatExtraction } from '@/lib/ai/chat-extractor';
+import { getKnowledgeItem } from '@/lib/server/knowledge';
+import { createChatExtraction } from '@/lib/server/chat-extraction';
+import { getAdminDb } from '@/lib/firebase/admin';
+import type { ProjectPhaseScores } from '@/lib/types/project-artifacts';
+
+interface ExtractFromChatRequest {
+  knowledgeItemId?: string;
+}
+
+// Increase Vercel/Next timeout for large transcripts
+export const maxDuration = 60;
+
+export async function POST(
+  request: Request,
+  { params }: { params: Promise<{ projectId: string }> },
+) {
+  try {
+    const { projectId } = await params;
+    if (!projectId) {
+      return NextResponse.json({ error: 'Missing projectId' }, { status: 400 });
+    }
+
+    const body = (await request.json()) as ExtractFromChatRequest;
+    const knowledgeItemId = body.knowledgeItemId?.trim();
+
+    if (!knowledgeItemId) {
+      return NextResponse.json({ error: 'knowledgeItemId is required' }, { status: 400 });
+    }
+
+    const knowledgeItem = await getKnowledgeItem(projectId, knowledgeItemId);
+    if (!knowledgeItem) {
+      return NextResponse.json({ error: 'Knowledge item not found' }, { status: 404 });
+    }
+
+    console.log(`[extract-from-chat] Starting extraction for knowledgeItemId=${knowledgeItemId}, content length=${knowledgeItem.content.length}`);
+    const llm = new GeminiLlmClient();
+    const extractionData = await runChatExtraction(knowledgeItem, llm);
+    console.log(`[extract-from-chat] Extraction complete for knowledgeItemId=${knowledgeItemId}`);
+
+    const overallCompletion = extractionData.summary_scores.overall_completion ?? 0;
+    const overallConfidence = extractionData.summary_scores.overall_confidence ?? 0;
+
+    const extraction = await createChatExtraction({
+      projectId,
+      knowledgeItemId,
+      data: extractionData,
+      overallCompletion,
+      overallConfidence,
+    });
+
+    const adminDb = getAdminDb();
+    const projectRef = adminDb.collection('projects').doc(projectId);
+    const snapshot = await projectRef.get();
+    const docData = snapshot.data() ?? {};
+    const existingScores = (docData.phaseScores ?? {}) as ProjectPhaseScores;
+    const phaseHistory = Array.isArray(docData.phaseHistory) ? [...docData.phaseHistory] : [];
+    phaseHistory.push({
+      phase: 'extractor',
+      status: 'completed',
+      knowledgeItemId,
+      timestamp: new Date().toISOString(),
+    });
+    existingScores.extractor = {
+      knowledgeItemId,
+      overallCompletion,
+      overallConfidence,
+      updatedAt: new Date().toISOString(),
+    };
+
+    await projectRef.set(
+      {
+        currentPhase: 'analyzed',
+        phaseScores: existingScores,
+        phaseStatus: 'in_progress',
+        phaseHistory,
+        updatedAt: FieldValue.serverTimestamp(),
+      },
+      { merge: true },
+    );
+
+    return NextResponse.json({ extraction });
+  } catch (error) {
+    console.error('[extract-from-chat] Extraction failed', error);
+    return NextResponse.json(
+      {
+        error: 'Failed to extract product signals',
+        details: error instanceof Error ? error.message : String(error),
+      },
+      { status: 500 },
+    );
+  }
+}
+
+