/**
 * Knowledge Bases Example - RAG with Document Training
 *
 * This example demonstrates how to:
 * - Create a knowledge base
 * - Add different document types (PDF, DOCX, TXT, websites)
 * - Query the knowledge base
 * - Use knowledge base with agents
 */

import { Studio } from '../src';

async function main() {
  const studio = new Studio({
    apiKey: process.env.LYZR_API_KEY
  });

  try {
    // Create a knowledge base
    console.log('Creating knowledge base...');
    const kb = await studio.createKnowledgeBase({
      name: 'company-docs',
      vectorStore: 'qdrant',
      embeddingModel: 'text-embedding-3-large',
      description: 'Company documentation and knowledge base'
    });

    console.log(`✓ Knowledge base created: ${kb.id}\n`);

    // Add documents (simulated - in real use, provide actual files)
    console.log('Adding documents...');

    // Add text content
    await kb.addText(
      `
Our company was founded in 2020.
We have 500+ employees across 5 countries.
Our main products are AI platforms.
Customer support hours: 9am-5pm EST.
      `,
      'company-info'
    );
    console.log('✓ Added company info');

    // Add website (simulated)
    await kb.addWebsite(
      ['https://docs.example.com', 'https://blog.example.com'],
      {
        maxCrawlPages: 50,
        maxCrawlDepth: 3
      }
    );
    console.log('✓ Added websites');

    // Note: In real usage with actual files:
    // await kb.addPdf('./documents/manual.pdf', { chunkSize: 1024 });
    // await kb.addDocx('./documents/report.docx');
    // await kb.addTxt('./documents/faq.txt');

    // Query the knowledge base
    console.log('\nQuerying knowledge base...');
    const results = await kb.query('What are the support hours?', {
      topK: 3,
      retrievalType: 'basic'
    });

    console.log(`Found ${results.length} results:`);
    results.forEach((result, i) => {
      console.log(`\n  Result ${i + 1} (score: ${result.score.toFixed(3)})`);
      console.log(`  ${result.text.substring(0, 100)}...`);
      if (result.source) {
        console.log(`  Source: ${result.source}`);
      }
    });

    // Create an agent that uses this knowledge base
    console.log('\n\nCreating agent with knowledge base...');
    const agent = await studio.createAgent({
      name: 'Documentation Assistant',
      provider: 'gpt-4o',
      role: 'Documentation expert',
      goal: 'Answer questions using company documentation',
      instructions: 'Use the provided knowledge base to answer accurately'
    });

    console.log('✓ Agent created\n');

    // Run agent with knowledge base
    console.log('Running agent with knowledge base...');
    const response = await agent.run(
      'What is the support contact information?',
      {
        knowledgeBases: [kb]
      }
    );

    console.log('Agent response:');
    console.log(response.response);

    // List all documents in KB
    console.log('\n\nListing documents...');
    const documents = await kb.listDocuments();
    console.log(`Total documents: ${documents.length}`);
    documents.forEach(doc => {
      console.log(`  - ${doc.name} (${doc.type}, ${doc.size} bytes)`);
    });

    // Advanced query with custom retrieval config
    console.log('\n\nAdvanced query with MMR retrieval...');
    const advancedResults = await kb.query('company history', {
      topK: 5,
      retrievalType: 'mmr', // Maximal Marginal Relevance
      scoreThreshold: 0.5,
      lambdaParam: 0.5
    });

    console.log(`Found ${advancedResults.length} diverse results`);

    // Clean up
    console.log('\n\nCleaning up...');
    await agent.delete();
    await kb.delete();
    console.log('✓ Cleaned up');
  } catch (error) {
    console.error('Error:', error);
    process.exit(1);
  }
}

main();