const fs = require('fs');
const path = require('path');

const PROXY_URL = 'http://localhost:8000/api/vllm-proxy/v1/chat/completions';
const IMAGE_PATH = path.join(__dirname, '..', 'sources', 'test-images', 'do-001.jpg');

async function testGuidedDecoding() {
  console.log('Reading test image from:', IMAGE_PATH);
  if (!fs.existsSync(IMAGE_PATH)) {
    console.error('Test image not found!');
    process.exit(1);
  }

  const imageBuffer = fs.readFileSync(IMAGE_PATH);
  const base64Image = imageBuffer.toString('base64');
  const imageUrl = `data:image/jpeg;base64,${base64Image}`;

  // JSON Schema for DO metadata
  const jsonSchema = {
    type: "object",
    properties: {
      tanggal: { type: "string" },
      noPo: { type: "string" },
      noSo: { type: "string" },
      noDo: { type: "string" },
      kepadaYth: { type: "string" },
      orderUntuk: { type: "string" },
      alamat: { type: "string" },
      platTruk: { type: "string" },
      namaDriver: { type: "string" },
      namaPenerima: { type: "string" },
      items: {
        type: "array",
        items: {
          type: "object",
          properties: {
            nomor_sku: { type: "string" },
            nama_barang: { type: "string" },
            banyak: { type: "string" },
            jumlah: { type: "string" }
          },
          required: ["nomor_sku", "nama_barang", "banyak", "jumlah"]
        }
      }
    },
    required: ["tanggal", "noPo", "noSo", "noDo", "kepadaYth", "items"]
  };

  const payload = {
    model: "PaddleOCR-VL-1.6-0.9B",
    messages: [
      {
        role: "user",
        content: [
          {
            type: "image_url",
            image_url: {
              url: imageUrl
            }
          },
          {
            type: "text",
            text: "Extract all structural details from this Delivery Order. Match the requested JSON Schema exactly."
          }
        ]
      }
    ],
    temperature: 0.1,
    max_tokens: 1024,
    guided_json: JSON.stringify(jsonSchema) // standard vLLM guided JSON schema format
  };

  console.log('Sending request to vLLM proxy with JSON Schema...');
  try {
    const startTime = Date.now();
    const response = await fetch(PROXY_URL, {
      method: 'POST',
      headers: {
        'Content-Type': 'application/json'
      },
      body: JSON.stringify(payload)
    });

    console.log(`Response status: ${response.status} (${response.statusText})`);
    const duration = ((Date.now() - startTime) / 1000).toFixed(2);
    console.log(`Request completed in ${duration}s`);

    const result = await response.json();
    if (response.ok) {
      console.log('=== SUCCESS RESPONSE ===');
      console.log(JSON.stringify(result, null, 2));
      
      const content = result.choices?.[0]?.message?.content;
      console.log('\n=== EXTRACTED CONTENT ===');
      console.log(content);
      
      try {
        const parsed = JSON.parse(content);
        console.log('\nValid JSON parsed successfully! ✅');
        console.log(parsed);
      } catch (err) {
        console.error('\nFailed to parse content as JSON! ❌', err.message);
      }
    } else {
      console.error('=== ERROR RESPONSE ===');
      console.error(result);
    }
  } catch (error) {
    console.error('Request failed:', error);
  }
}

testGuidedDecoding();