feat(invoices): add hybrid OCR + vision invoice/document parsing with PaddleOCR, consensus voting, and prompt/test refactors

This commit is contained in:
2026-01-16 14:24:37 +00:00
parent acded2a165
commit 82358b2d5d
4 changed files with 380 additions and 109 deletions

View File

@@ -45,7 +45,8 @@ async function extractOcrText(imageBase64: string): Promise<string> {
* Build prompt with optional OCR text
*/
function buildPrompt(ocrText: string): string {
const base = `You are an invoice parser. Extract the following fields from this invoice:
const base = `/nothink
You are an invoice parser. Extract the following fields from this invoice:
1. invoice_number: The invoice/receipt number
2. invoice_date: Date in YYYY-MM-DD format
@@ -62,11 +63,17 @@ If a field is not visible, use null for strings or 0 for numbers.
No explanation, just the JSON object.`;
if (ocrText) {
// Limit OCR text to prevent context overflow
const maxOcrLength = 4000;
const truncatedOcr = ocrText.length > maxOcrLength
? ocrText.substring(0, maxOcrLength) + '\n... (truncated)'
: ocrText;
return `${base}
OCR text extracted from the invoice:
OCR text extracted from the invoice (use for reference):
---
${ocrText}
${truncatedOcr}
---
Cross-reference the image with the OCR text above for accuracy.`;

View File

@@ -6,8 +6,11 @@ import * as os from 'os';
const OLLAMA_URL = 'http://localhost:11434';
const MODEL = 'openbmb/minicpm-v4.5:q8_0';
const PADDLEOCR_URL = 'http://localhost:5000';
const EXTRACT_PROMPT = `You are a bank statement parser. Extract EVERY transaction from the table.
// Prompt for visual extraction (with images)
const VISUAL_EXTRACT_PROMPT = `/nothink
You are a bank statement parser. Extract EVERY transaction from the table.
Read the Amount column carefully:
- "- 21,47 €" means DEBIT, output as: -21.47
@@ -18,6 +21,60 @@ For each row output: {"date":"YYYY-MM-DD","counterparty":"NAME","amount":-21.47}
Do not skip any rows. Return ONLY the JSON array, no explanation.`;
// Prompt for OCR-only extraction (no images)
const OCR_EXTRACT_PROMPT = `/nothink
You are a bank statement parser. Extract EVERY transaction from the OCR text below.
Read the Amount values carefully:
- "- 21,47 €" means DEBIT, output as: -21.47
- "+ 1.000,00 €" means CREDIT, output as: 1000.00
- European format: comma = decimal point
For each transaction output: {"date":"YYYY-MM-DD","counterparty":"NAME","amount":-21.47}
Do not skip any transactions. Return ONLY the JSON array, no explanation.`;
/**
* Build prompt for OCR-only extraction (no images)
*/
function buildOcrOnlyPrompt(ocrText: string): string {
// Limit OCR text to prevent context overflow
const maxOcrLength = 12000;
const truncatedOcr = ocrText.length > maxOcrLength
? ocrText.substring(0, maxOcrLength) + '\n... (truncated)'
: ocrText;
return `${OCR_EXTRACT_PROMPT}
OCR text from bank statement:
---
${truncatedOcr}
---`;
}
/**
* Extract OCR text from an image using PaddleOCR
*/
async function extractOcrText(imageBase64: string): Promise<string> {
try {
const response = await fetch(`${PADDLEOCR_URL}/ocr`, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({ image: imageBase64 }),
});
if (!response.ok) return '';
const data = await response.json();
if (data.success && data.results) {
return data.results.map((r: { text: string }) => r.text).join('\n');
}
} catch {
// PaddleOCR unavailable
}
return '';
}
interface ITransaction {
date: string;
counterparty: string;
@@ -53,12 +110,12 @@ function convertPdfToImages(pdfPath: string): string[] {
}
/**
* Single extraction pass
* Visual extraction pass (with images)
*/
async function extractOnce(images: string[], passNum: number): Promise<ITransaction[]> {
async function extractVisual(images: string[], passLabel: string): Promise<ITransaction[]> {
const payload = {
model: MODEL,
prompt: EXTRACT_PROMPT,
prompt: VISUAL_EXTRACT_PROMPT,
images,
stream: true,
options: {
@@ -67,6 +124,31 @@ async function extractOnce(images: string[], passNum: number): Promise<ITransact
},
};
return doExtraction(payload, passLabel);
}
/**
* OCR-only extraction pass (no images, just text)
*/
async function extractFromOcr(ocrText: string, passLabel: string): Promise<ITransaction[]> {
const payload = {
model: MODEL,
prompt: buildOcrOnlyPrompt(ocrText),
stream: true,
options: {
num_predict: 16384,
temperature: 0.1,
},
};
return doExtraction(payload, passLabel);
}
/**
* Common extraction logic
*/
async function doExtraction(payload: object, passLabel: string): Promise<ITransaction[]> {
const response = await fetch(`${OLLAMA_URL}/api/generate`, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
@@ -86,7 +168,7 @@ async function extractOnce(images: string[], passNum: number): Promise<ITransact
let fullText = '';
let lineBuffer = '';
console.log(`[Pass ${passNum}] Extracting...`);
console.log(`[${passLabel}] Extracting...`);
while (true) {
const { done, value } = await reader.read();
@@ -144,30 +226,78 @@ function hashTransactions(transactions: ITransaction[]): string {
/**
* Extract with majority voting - run until 2 passes match
* Strategy: Pass 1 = Visual (images), Pass 2 = OCR-only (text), Pass 3+ = Visual
*/
async function extractWithConsensus(images: string[], maxPasses: number = 5): Promise<ITransaction[]> {
const results: Array<{ transactions: ITransaction[]; hash: string }> = [];
const hashCounts: Map<string, number> = new Map();
for (let pass = 1; pass <= maxPasses; pass++) {
const transactions = await extractOnce(images, pass);
const addResult = (transactions: ITransaction[], passLabel: string): number => {
const hash = hashTransactions(transactions);
results.push({ transactions, hash });
hashCounts.set(hash, (hashCounts.get(hash) || 0) + 1);
console.log(`[${passLabel}] Got ${transactions.length} transactions (hash: ${hash.substring(0, 20)}...)`);
return hashCounts.get(hash)!;
};
console.log(`[Pass ${pass}] Got ${transactions.length} transactions (hash: ${hash.substring(0, 20)}...)`);
// Run Pass 1 (Visual) in parallel with OCR extraction
let ocrText = '';
const pass1Promise = extractVisual(images, 'Pass 1 Visual').catch((err) => ({ error: err }));
// Check if we have consensus (2+ matching)
const count = hashCounts.get(hash)!;
if (count >= 2) {
console.log(`[Consensus] Reached after ${pass} passes (${count} matching results)`);
return transactions;
// Extract OCR from all pages
const ocrPromise = (async () => {
const ocrTexts: string[] = [];
for (let i = 0; i < images.length; i++) {
const pageOcr = await extractOcrText(images[i]);
if (pageOcr) {
ocrTexts.push(`--- Page ${i + 1} ---\n${pageOcr}`);
}
}
ocrText = ocrTexts.join('\n\n');
if (ocrText) {
console.log(`[OCR] Extracted text from ${ocrTexts.length} page(s)`);
}
return ocrText;
})();
// Wait for Pass 1 and OCR to complete
const [pass1Result] = await Promise.all([pass1Promise, ocrPromise]);
// Process Pass 1 result
if ('error' in pass1Result) {
console.log(`[Pass 1] Error: ${(pass1Result as { error: unknown }).error}`);
} else {
addResult(pass1Result as ITransaction[], 'Pass 1 Visual');
}
// Pass 2: OCR-only (no images) - faster, different approach
if (ocrText) {
try {
const pass2Result = await extractFromOcr(ocrText, 'Pass 2 OCR-only');
const count = addResult(pass2Result, 'Pass 2 OCR-only');
if (count >= 2) {
console.log(`[Consensus] Visual and OCR extractions match!`);
return pass2Result;
}
} catch (err) {
console.log(`[Pass 2 OCR-only] Error: ${err}`);
}
}
// Continue with visual passes 3+ if no consensus yet
for (let pass = 3; pass <= maxPasses; pass++) {
try {
const transactions = await extractVisual(images, `Pass ${pass} Visual`);
const count = addResult(transactions, `Pass ${pass} Visual`);
if (count >= 2) {
console.log(`[Consensus] Reached after ${pass} passes`);
return transactions;
}
// After 2 passes, if no match yet, continue
if (pass >= 2) {
console.log(`[Pass ${pass}] No consensus yet, trying again...`);
} catch (err) {
console.log(`[Pass ${pass}] Error: ${err}`);
}
}
@@ -181,6 +311,10 @@ async function extractWithConsensus(images: string[], maxPasses: number = 5): Pr
}
}
if (!bestHash) {
throw new Error('No valid results obtained');
}
const best = results.find((r) => r.hash === bestHash)!;
console.log(`[No consensus] Using most common result (${bestCount}/${maxPasses} passes)`);
return best.transactions;