110 lines
3.5 KiB
JavaScript
110 lines
3.5 KiB
JavaScript
const fs = require('fs');
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const path = require('path');
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const PIPELINE_URL = 'http://localhost:8000/layout-parsing';
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const PROXY_URL = 'http://localhost:8000/api/vllm-proxy/v1/chat/completions';
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const UPLOADS_DIR = path.join(__dirname, '..', 'uploads');
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const notFoundImages = [
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'1782888211457-rotated_1782888204591_rotated_1782888199962_rotated_1782888195402_CAP7202641176939787142.jpg',
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'1782875064223-CAP2007290974474760139.jpg',
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'1782884586047-CAP9169719214882332189.jpg',
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'1782893409879-CAP4330863738757813156.jpg'
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];
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async function testImage(filename) {
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console.log(`\n========================================`);
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console.log(`TESTING FILE: ${filename}`);
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console.log(`========================================`);
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const filePath = path.join(UPLOADS_DIR, filename);
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if (!fs.existsSync(filePath)) {
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console.error(`File does not exist on disk: ${filePath}`);
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return;
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}
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const fileBuffer = fs.readFileSync(filePath);
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const base64Image = fileBuffer.toString('base64');
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// Test 1: Hit the Layout Parsing Pipeline API
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console.log('\n--- Test 1: Layout Parsing Pipeline (Standard) ---');
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try {
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const res = await fetch(PIPELINE_URL, {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify({
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file: base64Image,
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matchHistoryJob: false,
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useLayoutDetection: true,
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fileType: 1,
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useDocUnwarping: false,
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useDocOrientationClassify: true
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})
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});
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if (res.ok) {
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const data = await res.json();
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const markdown = data.result?.layoutParsingResults?.[0]?.markdown?.text || data.layoutParsingResults?.[0]?.markdown?.text || '';
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console.log('Resulting Markdown snippet (first 300 chars):');
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console.log(markdown.substring(0, 300));
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console.log(`\nDoes it contain PO, SO, DO or Tanggal?`);
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console.log(`- "Tanggal": ${/Tanggal/i.test(markdown)}`);
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console.log(`- "SO": ${/SO/i.test(markdown)}`);
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console.log(`- "DO": ${/DO/i.test(markdown)}`);
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console.log(`- "PO": ${/PO/i.test(markdown)}`);
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} else {
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console.error(`Pipeline returned status ${res.status}: ${await res.text()}`);
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}
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} catch (err) {
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console.error('Pipeline test failed:', err.message);
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}
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// Test 2: Direct vLLM completions with simple extraction prompt
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console.log('\n--- Test 2: Direct vLLM Simple Extraction ---');
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try {
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const res = await fetch(PROXY_URL, {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify({
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model: "PaddleOCR-VL-1.6-0.9B",
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messages: [
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{
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role: "user",
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content: [
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{
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type: "image_url",
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image_url: { url: `data:image/jpeg;base64,${base64Image}` }
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},
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{
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type: "text",
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text: "Read the top right section of the document. Extract Tanggal, No. SO, No. DO, and No. PO."
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}
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]
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}
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],
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temperature: 0.1,
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max_tokens: 300
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})
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});
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if (res.ok) {
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const data = await res.json();
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const content = data.choices?.[0]?.message?.content;
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console.log('vLLM Response:');
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console.log(content);
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} else {
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console.error(`vLLM proxy returned status ${res.status}: ${await res.text()}`);
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}
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} catch (err) {
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console.error('vLLM test failed:', err.message);
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}
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}
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async function runAll() {
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for (const filename of notFoundImages) {
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await testImage(filename);
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}
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}
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runAll();
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