chore: normalize line endings (CRLF -> LF)
No content changes: git diff --ignore-all-space over these files is empty. The churn came from editing on Windows against a repo checked out with LF.
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@@ -1,113 +1,113 @@
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const fs = require('fs');
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const path = require('path');
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const PROXY_URL = 'http://localhost:8000/api/vllm-proxy/v1/chat/completions';
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const IMAGE_PATH = path.join(__dirname, '..', 'sources', 'test-images', 'do-001.jpg');
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async function testGuidedDecoding() {
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console.log('Reading test image from:', IMAGE_PATH);
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if (!fs.existsSync(IMAGE_PATH)) {
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console.error('Test image not found!');
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process.exit(1);
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}
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const imageBuffer = fs.readFileSync(IMAGE_PATH);
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const base64Image = imageBuffer.toString('base64');
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const imageUrl = `data:image/jpeg;base64,${base64Image}`;
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// JSON Schema for DO metadata
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const jsonSchema = {
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type: "object",
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properties: {
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tanggal: { type: "string" },
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noPo: { type: "string" },
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noSo: { type: "string" },
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noDo: { type: "string" },
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kepadaYth: { type: "string" },
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orderUntuk: { type: "string" },
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alamat: { type: "string" },
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platTruk: { type: "string" },
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namaDriver: { type: "string" },
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namaPenerima: { type: "string" },
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items: {
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type: "array",
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items: {
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type: "object",
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properties: {
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nomor_sku: { type: "string" },
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nama_barang: { type: "string" },
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banyak: { type: "string" },
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jumlah: { type: "string" }
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},
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required: ["nomor_sku", "nama_barang", "banyak", "jumlah"]
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}
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}
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},
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required: ["tanggal", "noPo", "noSo", "noDo", "kepadaYth", "items"]
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};
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const payload = {
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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: {
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url: imageUrl
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}
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},
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{
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type: "text",
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text: "Extract all structural details from this Delivery Order. Match the requested JSON Schema exactly."
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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: 1024,
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guided_json: JSON.stringify(jsonSchema) // standard vLLM guided JSON schema format
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};
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console.log('Sending request to vLLM proxy with JSON Schema...');
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try {
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const startTime = Date.now();
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const response = await fetch(PROXY_URL, {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json'
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},
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body: JSON.stringify(payload)
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});
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console.log(`Response status: ${response.status} (${response.statusText})`);
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const duration = ((Date.now() - startTime) / 1000).toFixed(2);
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console.log(`Request completed in ${duration}s`);
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const result = await response.json();
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if (response.ok) {
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console.log('=== SUCCESS RESPONSE ===');
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console.log(JSON.stringify(result, null, 2));
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const content = result.choices?.[0]?.message?.content;
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console.log('\n=== EXTRACTED CONTENT ===');
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console.log(content);
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try {
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const parsed = JSON.parse(content);
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console.log('\nValid JSON parsed successfully! ✅');
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console.log(parsed);
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} catch (err) {
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console.error('\nFailed to parse content as JSON! ❌', err.message);
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}
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} else {
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console.error('=== ERROR RESPONSE ===');
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console.error(result);
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}
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} catch (error) {
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console.error('Request failed:', error);
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}
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}
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testGuidedDecoding();
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const fs = require('fs');
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const path = require('path');
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const PROXY_URL = 'http://localhost:8000/api/vllm-proxy/v1/chat/completions';
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const IMAGE_PATH = path.join(__dirname, '..', 'sources', 'test-images', 'do-001.jpg');
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async function testGuidedDecoding() {
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console.log('Reading test image from:', IMAGE_PATH);
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if (!fs.existsSync(IMAGE_PATH)) {
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console.error('Test image not found!');
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process.exit(1);
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}
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const imageBuffer = fs.readFileSync(IMAGE_PATH);
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const base64Image = imageBuffer.toString('base64');
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const imageUrl = `data:image/jpeg;base64,${base64Image}`;
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// JSON Schema for DO metadata
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const jsonSchema = {
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type: "object",
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properties: {
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tanggal: { type: "string" },
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noPo: { type: "string" },
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noSo: { type: "string" },
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noDo: { type: "string" },
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kepadaYth: { type: "string" },
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orderUntuk: { type: "string" },
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alamat: { type: "string" },
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platTruk: { type: "string" },
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namaDriver: { type: "string" },
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namaPenerima: { type: "string" },
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items: {
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type: "array",
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items: {
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type: "object",
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properties: {
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nomor_sku: { type: "string" },
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nama_barang: { type: "string" },
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banyak: { type: "string" },
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jumlah: { type: "string" }
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},
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required: ["nomor_sku", "nama_barang", "banyak", "jumlah"]
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}
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}
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},
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required: ["tanggal", "noPo", "noSo", "noDo", "kepadaYth", "items"]
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};
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const payload = {
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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: {
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url: imageUrl
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}
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},
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{
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type: "text",
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text: "Extract all structural details from this Delivery Order. Match the requested JSON Schema exactly."
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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: 1024,
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guided_json: JSON.stringify(jsonSchema) // standard vLLM guided JSON schema format
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};
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console.log('Sending request to vLLM proxy with JSON Schema...');
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try {
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const startTime = Date.now();
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const response = await fetch(PROXY_URL, {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json'
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},
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body: JSON.stringify(payload)
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});
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console.log(`Response status: ${response.status} (${response.statusText})`);
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const duration = ((Date.now() - startTime) / 1000).toFixed(2);
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console.log(`Request completed in ${duration}s`);
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const result = await response.json();
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if (response.ok) {
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console.log('=== SUCCESS RESPONSE ===');
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console.log(JSON.stringify(result, null, 2));
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const content = result.choices?.[0]?.message?.content;
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console.log('\n=== EXTRACTED CONTENT ===');
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console.log(content);
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try {
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const parsed = JSON.parse(content);
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console.log('\nValid JSON parsed successfully! ✅');
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console.log(parsed);
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} catch (err) {
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console.error('\nFailed to parse content as JSON! ❌', err.message);
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}
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} else {
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console.error('=== ERROR RESPONSE ===');
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console.error(result);
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}
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} catch (error) {
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console.error('Request failed:', error);
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}
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}
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testGuidedDecoding();
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