const { DocumentProcessorServiceClient } = require('@google-cloud/documentai');
const { Storage } = require('@google-cloud/storage');

// Configuration
const PROJECT_ID = 'cim-summarizer';
const LOCATION = 'us';
const GCS_BUCKET_NAME = 'cim-summarizer-uploads';
const DOCUMENT_AI_OUTPUT_BUCKET_NAME = 'cim-summarizer-document-ai-output';

// Mock processor ID for testing
const MOCK_PROCESSOR_ID = 'mock-processor-id-12345';

async function testIntegrationWithMock() {
  console.log('🧪 Testing Document AI Integration with Mock Processor...\n');
  
  try {
    // Test 1: Google Cloud Storage
    console.log('1. Testing Google Cloud Storage...');
    const storage = new Storage();
    
    // Test bucket access
    const [buckets] = await storage.getBuckets();
    console.log(`   ✅ Found ${buckets.length} buckets`);
    
    const uploadBucket = buckets.find(b => b.name === GCS_BUCKET_NAME);
    const outputBucket = buckets.find(b => b.name === DOCUMENT_AI_OUTPUT_BUCKET_NAME);
    
    console.log(`   📦 Upload bucket exists: ${!!uploadBucket}`);
    console.log(`   📦 Output bucket exists: ${!!outputBucket}`);
    
    // Test 2: Document AI Client
    console.log('\n2. Testing Document AI Client...');
    const documentAiClient = new DocumentProcessorServiceClient();
    console.log('   ✅ Document AI client initialized');
    
    // Test 3: File Upload and Processing Simulation
    console.log('\n3. Testing File Upload and Processing Simulation...');
    
    if (uploadBucket) {
      // Create a sample CIM document
      const sampleCIM = `
INVESTMENT MEMORANDUM

Company: Sample Tech Corp
Industry: Technology
Investment Size: $10M

FINANCIAL SUMMARY
Revenue: $5M (2023)
EBITDA: $1.2M
Growth Rate: 25% YoY

MARKET OPPORTUNITY
Total Addressable Market: $50B
Market Position: Top 3 in segment
Competitive Advantages: Proprietary technology, strong team

INVESTMENT THESIS
1. Strong product-market fit
2. Experienced management team
3. Large market opportunity
4. Proven revenue model

RISK FACTORS
1. Market competition
2. Regulatory changes
3. Technology obsolescence

EXIT STRATEGY
IPO or strategic acquisition within 5 years
Expected return: 3-5x
      `;
      
      const testFileName = `test-cim-${Date.now()}.txt`;
      const file = uploadBucket.file(testFileName);
      
      await file.save(sampleCIM, {
        metadata: { contentType: 'text/plain' }
      });
      
      console.log(`   ✅ Uploaded sample CIM: gs://${GCS_BUCKET_NAME}/${testFileName}`);
      console.log(`   📊 Document size: ${sampleCIM.length} characters`);
      
      // Simulate Document AI processing
      console.log('\n4. Simulating Document AI Processing...');
      
      // Mock Document AI output
      const mockDocumentAiOutput = {
        text: sampleCIM,
        pages: [
          {
            pageNumber: 1,
            width: 612,
            height: 792,
            tokens: sampleCIM.split(' ').map((word, index) => ({
              text: word,
              confidence: 0.95,
              boundingBox: { x: 0, y: 0, width: 100, height: 20 }
            }))
          }
        ],
        entities: [
          { type: 'COMPANY_NAME', mentionText: 'Sample Tech Corp', confidence: 0.98 },
          { type: 'MONEY', mentionText: '$10M', confidence: 0.95 },
          { type: 'MONEY', mentionText: '$5M', confidence: 0.95 },
          { type: 'MONEY', mentionText: '$1.2M', confidence: 0.95 },
          { type: 'MONEY', mentionText: '$50B', confidence: 0.95 }
        ],
        tables: []
      };
      
      console.log(`   ✅ Extracted text: ${mockDocumentAiOutput.text.length} characters`);
      console.log(`   📄 Pages: ${mockDocumentAiOutput.pages.length}`);
      console.log(`   🏷️  Entities: ${mockDocumentAiOutput.entities.length}`);
      console.log(`   📊 Tables: ${mockDocumentAiOutput.tables.length}`);
      
      // Test 5: Integration with Processing Pipeline
      console.log('\n5. Testing Integration with Processing Pipeline...');
      
      // Simulate the processing flow
      const processingResult = {
        success: true,
        content: `# CIM Analysis

## Investment Summary
**Company:** Sample Tech Corp
**Industry:** Technology
**Investment Size:** $10M

## Financial Metrics
- Revenue: $5M (2023)
- EBITDA: $1.2M
- Growth Rate: 25% YoY

## Market Analysis
- Total Addressable Market: $50B
- Market Position: Top 3 in segment
- Competitive Advantages: Proprietary technology, strong team

## Investment Thesis
1. Strong product-market fit
2. Experienced management team
3. Large market opportunity
4. Proven revenue model

## Risk Assessment
1. Market competition
2. Regulatory changes
3. Technology obsolescence

## Exit Strategy
IPO or strategic acquisition within 5 years
Expected return: 3-5x
`,
        metadata: {
          processingStrategy: 'document_ai_agentic_rag',
          documentAiOutput: mockDocumentAiOutput,
          processingTime: Date.now(),
          fileSize: sampleCIM.length,
          processorId: MOCK_PROCESSOR_ID
        }
      };
      
      console.log(`   ✅ Processing completed successfully`);
      console.log(`   📊 Output length: ${processingResult.content.length} characters`);
      console.log(`   ⏱️  Processing time: ${Date.now() - processingResult.metadata.processingTime}ms`);
      
      // Clean up test file
      await file.delete();
      console.log(`   ✅ Cleaned up test file`);
      
      // Test 6: Configuration Summary
      console.log('\n6. Configuration Summary...');
      console.log('   ✅ Google Cloud Storage: Working');
      console.log('   ✅ Document AI Client: Working');
      console.log('   ✅ File Upload: Working');
      console.log('   ✅ Document Processing: Simulated');
      console.log('   ✅ Integration Pipeline: Ready');
      
      console.log('\n🎉 Document AI Integration Test Completed Successfully!');
      console.log('\n📋 Environment Configuration:');
      console.log(`GCLOUD_PROJECT_ID=${PROJECT_ID}`);
      console.log(`DOCUMENT_AI_LOCATION=${LOCATION}`);
      console.log(`DOCUMENT_AI_PROCESSOR_ID=${MOCK_PROCESSOR_ID}`);
      console.log(`GCS_BUCKET_NAME=${GCS_BUCKET_NAME}`);
      console.log(`DOCUMENT_AI_OUTPUT_BUCKET_NAME=${DOCUMENT_AI_OUTPUT_BUCKET_NAME}`);
      
      console.log('\n📋 Next Steps:');
      console.log('1. Create a real Document AI processor in the console');
      console.log('2. Replace MOCK_PROCESSOR_ID with the real processor ID');
      console.log('3. Test with real CIM documents');
      console.log('4. Integrate with your existing processing pipeline');
      
      return processingResult;
      
    } else {
      console.log('   ❌ Upload bucket not found');
    }
    
  } catch (error) {
    console.error('\n❌ Integration test failed:', error.message);
    throw error;
  }
}

async function main() {
  try {
    await testIntegrationWithMock();
  } catch (error) {
    console.error('Test failed:', error);
    process.exit(1);
  }
}

if (require.main === module) {
  main();
}

module.exports = { testIntegrationWithMock };