fix(tests): improve Qwen3-VL invoice extraction test by switching to non-stream API, adding model availability/pull checks, simplifying response parsing, and tightening model options
This commit is contained in:
10
changelog.md
10
changelog.md
@@ -1,5 +1,15 @@
|
||||
# Changelog
|
||||
|
||||
## 2026-01-18 - 1.10.1 - fix(tests)
|
||||
improve Qwen3-VL invoice extraction test by switching to non-stream API, adding model availability/pull checks, simplifying response parsing, and tightening model options
|
||||
|
||||
- Replaced streaming reader logic with direct JSON parsing of the /api/chat response
|
||||
- Added ensureQwen3Vl() to check and pull the Qwen3-VL:8b model from Ollama
|
||||
- Switched to ensureMiniCpm() to verify Ollama service is running before model checks
|
||||
- Use /no_think prompt for direct JSON output and set temperature to 0.0 and num_predict to 512
|
||||
- Removed retry loop and streaming parsing; improved error messages to include response body
|
||||
- Updated logging and test setup messages for clarity
|
||||
|
||||
## 2026-01-18 - 1.10.0 - feat(vision)
|
||||
add Qwen3-VL vision model support with Dockerfile and tests; improve invoice OCR conversion and prompts; simplify extraction flow by removing consensus voting
|
||||
|
||||
|
||||
@@ -1,18 +1,17 @@
|
||||
/**
|
||||
* Invoice extraction using Qwen3-VL-8B Vision (Direct)
|
||||
* Invoice extraction using Qwen3-VL 8B Vision (Direct)
|
||||
*
|
||||
* Qwen3-VL 8B is a capable vision-language model that fits in 15GB VRAM:
|
||||
* - Q4_K_M quantization (~5GB)
|
||||
* - Good balance of speed and accuracy
|
||||
* Single-step pipeline: PDF → Images → Qwen3-VL → JSON
|
||||
* Uses /no_think to disable reasoning mode for fast, direct responses.
|
||||
*
|
||||
* Pipeline: PDF → Images → Qwen3-VL → JSON
|
||||
* Qwen3-VL outperforms PaddleOCR-VL on certain invoice formats.
|
||||
*/
|
||||
import { tap, expect } from '@git.zone/tstest/tapbundle';
|
||||
import * as fs from 'fs';
|
||||
import * as path from 'path';
|
||||
import { execSync } from 'child_process';
|
||||
import * as os from 'os';
|
||||
import { ensureQwen3Vl } from './helpers/docker.js';
|
||||
import { ensureMiniCpm } from './helpers/docker.js';
|
||||
|
||||
const OLLAMA_URL = 'http://localhost:11434';
|
||||
const VISION_MODEL = 'qwen3-vl:8b';
|
||||
@@ -57,144 +56,68 @@ function convertPdfToImages(pdfPath: string): string[] {
|
||||
}
|
||||
|
||||
/**
|
||||
* Single extraction attempt
|
||||
* Extract invoice data directly from images using Qwen3-VL Vision
|
||||
* Uses /no_think to disable reasoning mode for fast, direct JSON output
|
||||
*/
|
||||
async function tryExtractOnce(images: string[], prompt: string): Promise<string> {
|
||||
async function extractInvoiceFromImages(images: string[]): Promise<IInvoice> {
|
||||
console.log(` [Vision] Processing ${images.length} page(s) with Qwen3-VL`);
|
||||
|
||||
// /no_think disables Qwen3's reasoning mode - crucial for getting direct output
|
||||
const prompt = `/no_think
|
||||
Look at this invoice and extract these fields. Reply with ONLY JSON, no explanation.
|
||||
|
||||
- invoice_number
|
||||
- invoice_date (format: YYYY-MM-DD)
|
||||
- vendor_name
|
||||
- currency (EUR, USD, or GBP)
|
||||
- net_amount
|
||||
- vat_amount
|
||||
- total_amount
|
||||
|
||||
JSON: {"invoice_number":"...","invoice_date":"YYYY-MM-DD","vendor_name":"...","currency":"EUR","net_amount":0,"vat_amount":0,"total_amount":0}`;
|
||||
|
||||
const response = await fetch(`${OLLAMA_URL}/api/chat`, {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
body: JSON.stringify({
|
||||
model: VISION_MODEL,
|
||||
messages: [
|
||||
{
|
||||
role: 'user',
|
||||
content: prompt,
|
||||
images: images,
|
||||
},
|
||||
],
|
||||
stream: true,
|
||||
messages: [{
|
||||
role: 'user',
|
||||
content: prompt,
|
||||
images: images, // Pass all pages
|
||||
}],
|
||||
stream: false,
|
||||
options: {
|
||||
num_predict: 1024,
|
||||
temperature: 0.1, // Slight randomness helps avoid stuck states
|
||||
num_predict: 512,
|
||||
temperature: 0.0,
|
||||
},
|
||||
}),
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
throw new Error(`Ollama API error: ${response.status}`);
|
||||
const err = await response.text();
|
||||
throw new Error(`Ollama API error: ${response.status} - ${err}`);
|
||||
}
|
||||
|
||||
const reader = response.body?.getReader();
|
||||
if (!reader) {
|
||||
throw new Error('No response body');
|
||||
}
|
||||
const data = await response.json();
|
||||
let content = data.message?.content || '';
|
||||
|
||||
const decoder = new TextDecoder();
|
||||
let fullText = '';
|
||||
console.log(` [Vision] Response (${content.length} chars): ${content.substring(0, 200)}...`);
|
||||
|
||||
while (true) {
|
||||
const { done, value } = await reader.read();
|
||||
if (done) break;
|
||||
// Parse JSON from response
|
||||
if (content.startsWith('```json')) content = content.slice(7);
|
||||
else if (content.startsWith('```')) content = content.slice(3);
|
||||
if (content.endsWith('```')) content = content.slice(0, -3);
|
||||
content = content.trim();
|
||||
|
||||
const chunk = decoder.decode(value, { stream: true });
|
||||
const lines = chunk.split('\n').filter((l) => l.trim());
|
||||
|
||||
for (const line of lines) {
|
||||
try {
|
||||
const json = JSON.parse(line);
|
||||
if (json.message?.content) {
|
||||
fullText += json.message.content;
|
||||
}
|
||||
} catch {
|
||||
// Skip invalid JSON lines
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return fullText;
|
||||
}
|
||||
|
||||
/**
|
||||
* Extract invoice data directly from images using Qwen3-VL Vision
|
||||
* Includes retry logic for empty responses
|
||||
*/
|
||||
async function extractInvoiceFromImages(images: string[]): Promise<IInvoice> {
|
||||
console.log(` [Vision] Processing ${images.length} page(s) with Qwen3-VL`);
|
||||
|
||||
// JSON schema for structured output - force the model to output valid JSON
|
||||
const invoiceSchema = {
|
||||
type: 'object',
|
||||
properties: {
|
||||
invoice_number: { type: 'string' },
|
||||
invoice_date: { type: 'string' },
|
||||
vendor_name: { type: 'string' },
|
||||
currency: { type: 'string' },
|
||||
net_amount: { type: 'number' },
|
||||
vat_amount: { type: 'number' },
|
||||
total_amount: { type: 'number' },
|
||||
},
|
||||
required: ['invoice_number', 'invoice_date', 'vendor_name', 'currency', 'net_amount', 'vat_amount', 'total_amount'],
|
||||
};
|
||||
|
||||
// Simple, direct prompt - don't overthink, just read the labeled fields
|
||||
const prompt = `Extract invoice data from this image. Return JSON only.
|
||||
|
||||
Find these fields:
|
||||
- invoice_number: The invoice/document number
|
||||
- invoice_date: Date in YYYY-MM-DD format
|
||||
- vendor_name: Company issuing the invoice
|
||||
- currency: EUR, USD, or GBP
|
||||
- net_amount: Amount before tax
|
||||
- vat_amount: Tax/VAT amount
|
||||
- total_amount: Final total amount
|
||||
|
||||
Return: {"invoice_number":"...", "invoice_date":"YYYY-MM-DD", "vendor_name":"...", "currency":"EUR", "net_amount":0.00, "vat_amount":0.00, "total_amount":0.00}`;
|
||||
|
||||
// Retry logic for empty responses (model sometimes returns nothing)
|
||||
const MAX_RETRIES = 3;
|
||||
let fullText = '';
|
||||
|
||||
for (let attempt = 1; attempt <= MAX_RETRIES; attempt++) {
|
||||
fullText = await tryExtractOnce(images, prompt);
|
||||
|
||||
if (fullText.trim().length > 0) {
|
||||
console.log(` [Attempt ${attempt}] Got ${fullText.length} chars`);
|
||||
break;
|
||||
}
|
||||
|
||||
console.log(` [Attempt ${attempt}] Empty response, retrying...`);
|
||||
// Small delay before retry
|
||||
await new Promise((r) => setTimeout(r, 1000));
|
||||
}
|
||||
|
||||
if (fullText.trim().length === 0) {
|
||||
throw new Error(`Model returned empty response after ${MAX_RETRIES} attempts`);
|
||||
}
|
||||
|
||||
// Parse JSON response
|
||||
let jsonStr = fullText.trim();
|
||||
|
||||
if (jsonStr.startsWith('```json')) jsonStr = jsonStr.slice(7);
|
||||
else if (jsonStr.startsWith('```')) jsonStr = jsonStr.slice(3);
|
||||
if (jsonStr.endsWith('```')) jsonStr = jsonStr.slice(0, -3);
|
||||
jsonStr = jsonStr.trim();
|
||||
|
||||
const startIdx = jsonStr.indexOf('{');
|
||||
const endIdx = jsonStr.lastIndexOf('}') + 1;
|
||||
const startIdx = content.indexOf('{');
|
||||
const endIdx = content.lastIndexOf('}') + 1;
|
||||
|
||||
if (startIdx < 0 || endIdx <= startIdx) {
|
||||
throw new Error(`No JSON found in: ${fullText.substring(0, 500)}`);
|
||||
throw new Error(`No JSON found: ${content.substring(0, 300)}`);
|
||||
}
|
||||
|
||||
const extractedJson = jsonStr.substring(startIdx, endIdx);
|
||||
console.log(` [Debug] Extracted JSON: ${extractedJson.substring(0, 200)}...`);
|
||||
|
||||
let parsed;
|
||||
try {
|
||||
parsed = JSON.parse(extractedJson);
|
||||
} catch (e) {
|
||||
throw new Error(`Invalid JSON: ${extractedJson.substring(0, 500)}`);
|
||||
}
|
||||
const parsed = JSON.parse(content.substring(startIdx, endIdx));
|
||||
|
||||
return {
|
||||
invoice_number: parsed.invoice_number || null,
|
||||
@@ -284,12 +207,48 @@ function findTestCases(): Array<{ name: string; pdfPath: string; jsonPath: strin
|
||||
return testCases.sort((a, b) => a.name.localeCompare(b.name));
|
||||
}
|
||||
|
||||
/**
|
||||
* Ensure Qwen3-VL 8B model is available
|
||||
*/
|
||||
async function ensureQwen3Vl(): Promise<boolean> {
|
||||
try {
|
||||
const response = await fetch(`${OLLAMA_URL}/api/tags`);
|
||||
if (response.ok) {
|
||||
const data = await response.json();
|
||||
const models = data.models || [];
|
||||
if (models.some((m: { name: string }) => m.name === VISION_MODEL)) {
|
||||
console.log(`[Ollama] Model already available: ${VISION_MODEL}`);
|
||||
return true;
|
||||
}
|
||||
}
|
||||
} catch {
|
||||
console.log('[Ollama] Cannot check models');
|
||||
return false;
|
||||
}
|
||||
|
||||
console.log(`[Ollama] Pulling model: ${VISION_MODEL}...`);
|
||||
const pullResponse = await fetch(`${OLLAMA_URL}/api/pull`, {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
body: JSON.stringify({ name: VISION_MODEL, stream: false }),
|
||||
});
|
||||
|
||||
return pullResponse.ok;
|
||||
}
|
||||
|
||||
// Tests
|
||||
|
||||
tap.test('setup: ensure Qwen3-VL is running', async () => {
|
||||
console.log('\n[Setup] Checking Qwen3-VL 8B (~5GB)...\n');
|
||||
const ok = await ensureQwen3Vl();
|
||||
expect(ok).toBeTrue();
|
||||
console.log('\n[Setup] Checking Qwen3-VL 8B...\n');
|
||||
|
||||
// Ensure Ollama service is running
|
||||
const ollamaOk = await ensureMiniCpm();
|
||||
expect(ollamaOk).toBeTrue();
|
||||
|
||||
// Ensure Qwen3-VL 8B model
|
||||
const visionOk = await ensureQwen3Vl();
|
||||
expect(visionOk).toBeTrue();
|
||||
|
||||
console.log('\n[Setup] Ready!\n');
|
||||
});
|
||||
|
||||
@@ -339,7 +298,7 @@ tap.test('summary', async () => {
|
||||
console.log(`\n======================================================`);
|
||||
console.log(` Invoice Extraction Summary (Qwen3-VL Vision)`);
|
||||
console.log(`======================================================`);
|
||||
console.log(` Method: Qwen3-VL 8B (Direct Vision)`);
|
||||
console.log(` Method: Qwen3-VL 8B Direct Vision (/no_think)`);
|
||||
console.log(` Passed: ${passedCount}/${total}`);
|
||||
console.log(` Failed: ${failedCount}/${total}`);
|
||||
console.log(` Accuracy: ${accuracy.toFixed(1)}%`);
|
||||
|
||||
Reference in New Issue
Block a user