v1.14.1

changelog.md

@@ -1,5 +1,14 @@
 # Changelog
 
+## 2026-01-19 - 1.14.1 - fix(extraction)
+improve JSON extraction prompts and model options for invoice and bank statement tests
+
+- Refactor JSON extraction prompts to be sent after the document text and add explicit 'WHERE TO FIND DATA' and 'RULES' sections for clearer extraction guidance
+- Change chat message flow to: send document, assistant acknowledgement, then the JSON extraction prompt (avoids concatenating large prompts into one message)
+- Add model options (num_ctx: 32768, temperature: 0) to give larger context windows and deterministic JSON output
+- Simplify logging to avoid printing full prompt contents; log document and prompt lengths instead
+- Increase timeouts for large documents to 600000ms (10 minutes) where applicable
+
 ## 2026-01-19 - 1.14.0 - feat(docker-images)
 add vLLM-based Nanonets-OCR2-3B image, Qwen3-VL Ollama image and refactor build/docs/tests to use new runtime/layout
 

package.json

@@ -1,6 +1,6 @@
 {
   "name": "@host.today/ht-docker-ai",
-  "version": "1.14.0",
+  "version": "1.14.1",
   "type": "module",
   "private": false,
   "description": "Docker images for AI vision-language models including MiniCPM-V 4.5",

test/test.bankstatements.nanonets.ts

@@ -51,11 +51,21 @@ If there is an image in the document and image caption is not present, add a sma
 Watermarks should be wrapped in brackets. Ex: <watermark>OFFICIAL COPY</watermark>.
 Page numbers should be wrapped in brackets. Ex: <page_number>14</page_number>.`;
 
-// JSON extraction prompt for GPT-OSS 20B
+// JSON extraction prompt for GPT-OSS 20B (sent AFTER the statement text is provided)
-const JSON_EXTRACTION_PROMPT = `Extract ALL transactions from this bank statement as JSON array. Each transaction: {"date": "YYYY-MM-DD", "counterparty": "NAME", "amount": -25.99}. Amount negative for debits, positive for credits. Only include actual transactions, not balances. Return ONLY JSON array, no explanation.
+const JSON_EXTRACTION_PROMPT = `Extract ALL transactions from the bank statement. Return ONLY valid JSON array.
 
-STATEMENT:
+WHERE TO FIND DATA:
-`;
+- Transactions are typically in TABLES with columns: Date, Description/Counterparty, Debit, Credit, Balance
+- Look for rows with actual money movements, NOT header rows or summary totals
+
+RULES:
+1. date: Convert to YYYY-MM-DD format
+2. counterparty: The name/description of who the money went to/from
+3. amount: NEGATIVE for debits/withdrawals, POSITIVE for credits/deposits
+4. Only include actual transactions, NOT opening/closing balances
+
+JSON array only:
+[{"date":"YYYY-MM-DD","counterparty":"NAME","amount":-25.99}]`;
 
 // Constants for smart batching
 const MAX_VISUAL_TOKENS = 28000;  // ~32K context minus prompt/output headroom
@@ -246,12 +256,8 @@ async function ensureExtractionModel(): Promise<boolean> {
  */
 async function extractTransactionsFromMarkdown(markdown: string, queryId: string): Promise<ITransaction[]> {
   const startTime = Date.now();
-  const fullPrompt = JSON_EXTRACTION_PROMPT + markdown;
 
-  // Log exact prompt
+  console.log(`      [${queryId}] Statement: ${markdown.length} chars, Prompt: ${JSON_EXTRACTION_PROMPT.length} chars`);
-  console.log(`\n      [${queryId}] ===== PROMPT =====`);
-  console.log(fullPrompt);
-  console.log(`      [${queryId}] ===== END PROMPT (${fullPrompt.length} chars) =====\n`);
 
   const response = await fetch(`${OLLAMA_URL}/api/chat`, {
     method: 'POST',
@@ -261,9 +267,15 @@ async function extractTransactionsFromMarkdown(markdown: string, queryId: string
       messages: [
         { role: 'user', content: 'Hi there, how are you?' },
         { role: 'assistant', content: 'Good, how can I help you today?' },
-        { role: 'user', content: fullPrompt },
+        { role: 'user', content: `Here is a bank statement document:\n\n${markdown}` },
+        { role: 'assistant', content: 'I have read the bank statement document you provided. I can see all the transaction data. What would you like me to do with it?' },
+        { role: 'user', content: JSON_EXTRACTION_PROMPT },
       ],
       stream: true,
+      options: {
+        num_ctx: 32768,  // Larger context for long statements + thinking
+        temperature: 0,  // Deterministic for JSON extraction
+      },
     }),
     signal: AbortSignal.timeout(600000),  // 10 minute timeout
   });

test/test.invoices.extraction.ts

@@ -197,6 +197,10 @@ async function extractInvoiceFromMarkdown(markdown: string, queryId: string): Pr
         { role: 'user', content: JSON_EXTRACTION_PROMPT },
       ],
       stream: true,
+      options: {
+        num_ctx: 32768,  // Larger context for long invoices + thinking
+        temperature: 0,  // Deterministic for JSON extraction
+      },
     }),
     signal: AbortSignal.timeout(120000), // 2 min timeout
   });

test/test.invoices.nanonets.ts

@@ -54,31 +54,24 @@ If there is an image in the document and image caption is not present, add a sma
 Watermarks should be wrapped in brackets. Ex: <watermark>OFFICIAL COPY</watermark>.
 Page numbers should be wrapped in brackets. Ex: <page_number>14</page_number>.`;
 
-// JSON extraction prompt for GPT-OSS 20B
+// JSON extraction prompt for GPT-OSS 20B (sent AFTER the invoice text is provided)
-const JSON_EXTRACTION_PROMPT = `You are an invoice data extractor. Below is an invoice document converted to text/markdown. Extract the key invoice fields as JSON.
+const JSON_EXTRACTION_PROMPT = `Extract key fields from the invoice. Return ONLY valid JSON.
 
-IMPORTANT RULES:
+WHERE TO FIND DATA:
-1. invoice_number: The unique invoice/document number (NOT VAT ID, NOT customer ID)
+- invoice_number, invoice_date, vendor_name: Look in the HEADER section at the TOP of PAGE 1 (near "Invoice no.", "Invoice date:", "Rechnungsnummer")
-2. invoice_date: Format as YYYY-MM-DD
+- net_amount, vat_amount, total_amount: Look in the SUMMARY section at the BOTTOM (look for "Total", "Amount due", "Gesamtbetrag")
-3. vendor_name: The company that issued the invoice
+
+RULES:
+1. invoice_number: Extract ONLY the value (e.g., "R0015632540"), NOT the label "Invoice no."
+2. invoice_date: Convert to YYYY-MM-DD format (e.g., "14/04/2022" → "2022-04-14")
+3. vendor_name: The company issuing the invoice
 4. currency: EUR, USD, or GBP
-5. net_amount: Amount before tax
+5. net_amount: Total before tax
-6. vat_amount: Tax/VAT amount
+6. vat_amount: Tax amount
-7. total_amount: Final total (gross amount)
+7. total_amount: Final total with tax
 
-Return ONLY this JSON format, no explanation:
+JSON only:
-{
+{"invoice_number":"X","invoice_date":"YYYY-MM-DD","vendor_name":"X","currency":"EUR","net_amount":0,"vat_amount":0,"total_amount":0}`;
-  "invoice_number": "INV-2024-001",
-  "invoice_date": "2024-01-15",
-  "vendor_name": "Company Name",
-  "currency": "EUR",
-  "net_amount": 100.00,
-  "vat_amount": 19.00,
-  "total_amount": 119.00
-}
-
-INVOICE TEXT:
-`;
 
 // Constants for smart batching
 const MAX_VISUAL_TOKENS = 28000;  // ~32K context minus prompt/output headroom
@@ -370,12 +363,8 @@ function parseJsonToInvoice(response: string): IInvoice | null {
  */
 async function extractInvoiceFromMarkdown(markdown: string, queryId: string): Promise<IInvoice | null> {
   const startTime = Date.now();
-  const fullPrompt = JSON_EXTRACTION_PROMPT + markdown;
 
-  // Log exact prompt
+  console.log(`      [${queryId}] Invoice: ${markdown.length} chars, Prompt: ${JSON_EXTRACTION_PROMPT.length} chars`);
-  console.log(`\n      [${queryId}] ===== PROMPT =====`);
-  console.log(fullPrompt);
-  console.log(`      [${queryId}] ===== END PROMPT (${fullPrompt.length} chars) =====\n`);
 
   const response = await fetch(`${OLLAMA_URL}/api/chat`, {
     method: 'POST',
@@ -385,9 +374,15 @@ async function extractInvoiceFromMarkdown(markdown: string, queryId: string): Pr
       messages: [
         { role: 'user', content: 'Hi there, how are you?' },
         { role: 'assistant', content: 'Good, how can I help you today?' },
-        { role: 'user', content: fullPrompt },
+        { role: 'user', content: `Here is an invoice document:\n\n${markdown}` },
+        { role: 'assistant', content: 'I have read the invoice document you provided. I can see all the text content. What would you like me to do with it?' },
+        { role: 'user', content: JSON_EXTRACTION_PROMPT },
       ],
       stream: true,
+      options: {
+        num_ctx: 32768,  // Larger context for long invoices + thinking
+        temperature: 0,  // Deterministic for JSON extraction
+      },
     }),
     signal: AbortSignal.timeout(600000), // 10 minute timeout for large documents
   });