vibn-frontend/app/api/projects/[projectId]/knowledge/upload-document/route.ts

import { NextResponse } from 'next/server';
import { getAdminAuth, getAdminDb } from '@/lib/firebase/admin';
import { createKnowledgeItem } from '@/lib/server/knowledge';
import type { KnowledgeSourceMeta } from '@/lib/types/knowledge';
// import { chunkDocument } from '@/lib/utils/document-chunker'; // Not needed - Extractor AI handles chunking
import { getStorage } from 'firebase-admin/storage';

export const maxDuration = 60;

export async function POST(
  request: Request,
  context: { params: Promise<{ projectId: string }> | { projectId: string } }
) {
  try {
    // Verify auth
    const authHeader = request.headers.get('Authorization');
    if (!authHeader?.startsWith('Bearer ')) {
      return NextResponse.json({ error: 'Unauthorized' }, { status: 401 });
    }

    const idToken = authHeader.split('Bearer ')[1];
    const adminAuth = getAdminAuth();
    
    let userId: string;
    try {
      const decodedToken = await adminAuth.verifyIdToken(idToken);
      userId = decodedToken.uid;
    } catch (error) {
      return NextResponse.json({ error: 'Invalid token' }, { status: 401 });
    }

    // Handle async params in Next.js 16
    const params = 'then' in context.params ? await context.params : context.params;
    const projectId = params.projectId;

    if (!projectId) {
      return NextResponse.json({ error: 'Missing projectId' }, { status: 400 });
    }

    // Parse multipart form data
    const formData = await request.formData();
    const file = formData.get('file') as File;

    if (!file) {
      return NextResponse.json({ error: 'No file provided' }, { status: 400 });
    }

    const adminDb = getAdminDb();
    const projectSnap = await adminDb.collection('projects').doc(projectId).get();
    if (!projectSnap.exists) {
      return NextResponse.json({ error: 'Project not found' }, { status: 404 });
    }

    console.log(`[upload-document] Uploading ${file.name}, size=${file.size}`);

    // Read file content
    const arrayBuffer = await file.arrayBuffer();
    const buffer = Buffer.from(arrayBuffer);
    const content = buffer.toString('utf-8');

    // Upload original file to Firebase Storage
    const storage = getStorage();
    const bucket = storage.bucket();
    const storagePath = `projects/${projectId}/documents/${Date.now()}_${file.name}`;
    const fileRef = bucket.file(storagePath);

    await fileRef.save(buffer, {
      metadata: {
        contentType: file.type,
        metadata: {
          uploadedBy: userId,
          projectId,
          originalFilename: file.name,
          uploadedAt: new Date().toISOString(),
        },
      },
    });

    // Make file publicly accessible (or use signed URLs if you want private)
    await fileRef.makePublic();
    const publicUrl = `https://storage.googleapis.com/${bucket.name}/${storagePath}`;

    console.log(`[upload-document] File saved to Storage: ${publicUrl}`);

    // Store whole document as single knowledge_item (no chunking)
    // Extractor AI will collaboratively chunk important sections later
    const sourceMeta: KnowledgeSourceMeta = {
      origin: 'other',
      url: publicUrl,
      filename: file.name,
      createdAtOriginal: new Date().toISOString(),
      importance: 'primary',
      tags: ['document', 'uploaded', 'pending_extraction'],
    };

    const knowledgeItem = await createKnowledgeItem({
      projectId,
      sourceType: 'imported_document',
      title: file.name,
      content: content,
      sourceMeta,
    });

    console.log(`[upload-document] Stored whole document as knowledge_item: ${knowledgeItem.id}`);

    const knowledgeItemIds = [knowledgeItem.id];

    // Create a summary record in contextSources for UI display
    const contextSourcesRef = adminDb.collection('projects').doc(projectId).collection('contextSources');
    await contextSourcesRef.add({
      type: 'document',
      name: file.name,
      summary: `Document (${content.length} characters) - pending extraction`,
      url: publicUrl,
      connectedAt: new Date(),
      metadata: {
        totalChars: content.length,
        fileSize: file.size,
        mimeType: file.type,
        storagePath,
        knowledgeItemId: knowledgeItem.id,
        uploadedBy: userId,
        status: 'pending_extraction',
      },
    });

    return NextResponse.json({
      success: true,
      filename: file.name,
      url: publicUrl,
      knowledgeItemId: knowledgeItem.id,
      status: 'stored',
      message: 'Document stored. Extractor AI will review and chunk important sections.',
    });
  } catch (error) {
    console.error('[upload-document] Failed to upload document', error);
    return NextResponse.json(
      {
        error: 'Failed to upload document',
        details: error instanceof Error ? error.message : String(error),
      },
      { status: 500 },
    );
  }
}