v1.16.0

- Update smartai to v0.13.2 (native tool calling support)
- Update smartagent to v1.5.1 (useNativeToolCalling option)
- Enable think: true for GPT-OSS reasoning mode in Ollama config
- Enable useNativeToolCalling: true in DualAgentOrchestrator
- Simplify driver system message (native tools don't need XML instructions)

Native tool calling uses Ollama's built-in Harmony format parser
instead of requiring XML generation, which is more efficient for GPT-OSS models.

changelog.md

@@ -1,5 +1,69 @@
 # Changelog
 
+## 2026-01-20 - 1.16.0 - feat(invoices)
+add line_items extraction and normalization for invoice parsing
+
+- Introduce ILineItem interface and add line_items array to IInvoice.
+- Add extractLineItems helper to normalize item fields (position, product, description, quantity, unit_price, total_price).
+- Include line_items in parsed invoice output and sample JSON in test, defaulting to [] when absent.
+- Update logging to include extracted line item count.
+- Clarify test instructions to extract items from invoice tables and skip subtotal/total rows.
+
+## 2026-01-20 - 1.15.3 - fix(tests(nanonets))
+allow '/' when normalizing invoice strings in tests
+
+- Adjust regex in test/test.invoices.nanonets.ts to preserve forward slashes when cleaning invoice values
+- Changed pattern from [^A-Z0-9-] to [^A-Z0-9\/-] to prevent accidental removal of '/' characters in invoice identifiers
+
+## 2026-01-20 - 1.15.2 - fix(dev-deps)
+bump devDependencies @push.rocks/smartagent to ^1.6.2 and @push.rocks/smartai to ^0.13.3
+
+- Bumped @push.rocks/smartagent from ^1.5.4 to ^1.6.2 in devDependencies
+- Bumped @push.rocks/smartai from ^0.13.2 to ^0.13.3 in devDependencies
+- Updated test/test.invoices.nanonets.ts JSON extraction prompt: instruct not to omit special characters in invoice_number and to use the json validate tool
+- No breaking changes; only dev dependency updates and test prompt adjustments
+
+## 2026-01-20 - 1.15.1 - fix(tests)
+enable progress events in invoice tests and bump @push.rocks/smartagent devDependency to ^1.5.4
+
+- Added an onProgress handler in test/test.invoices.nanonets.ts to log progress events (console.log(event.logMessage)) so tool calls and progress are visible during tests.
+- Bumped devDependency @push.rocks/smartagent from ^1.5.2 to ^1.5.4 in package.json.
+
+## 2026-01-20 - 1.15.0 - feat(tests)
+integrate SmartAi/DualAgentOrchestrator into extraction tests and add JSON self-validation
+
+- Integrate SmartAi and DualAgentOrchestrator into bankstatement and invoice tests to perform structured extraction with streaming
+- Register and use JsonValidatorTool to validate outputs (json.validate) and enforce validation before task completion
+- Add tryExtractJson parsing fallback, improved extraction prompts, retries and clearer parsing/logging
+- Initialize and teardown SmartAi and orchestrator in test setup/summary, and enable onToken streaming handlers for real-time output
+- Bump devDependencies: @push.rocks/smartagent to ^1.3.0 and @push.rocks/smartai to ^0.12.0
+
+## 2026-01-20 - 1.14.3 - fix(repo)
+no changes detected in the diff; no files modified and no release required
+
+- Diff contained no changes
+- No files were added, removed, or modified
+- No code, dependency, or documentation updates to release
+
+## 2026-01-19 - 1.14.2 - fix(readme)
+update README to document Nanonets-OCR2-3B (replaces Nanonets-OCR-s), adjust VRAM and context defaults, expand feature docs, and update examples/test command
+
+- Renamed Nanonets-OCR-s -> Nanonets-OCR2-3B throughout README and examples
+- Updated Nanonets VRAM guidance from ~10GB to ~12-16GB and documented 30K context
+- Changed documented MAX_MODEL_LEN default from 8192 to 30000
+- Updated example model identifiers (model strings and curl/example snippets) to nanonets/Nanonets-OCR2-3B
+- Added MiniCPM and Qwen feature bullets (multilingual, multi-image, flowchart support, expanded context notes)
+- Replaced README test command from ./test-images.sh to pnpm test
+
+## 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": "1.16.0",
   "type": "module",
   "private": false,
   "description": "Docker images for AI vision-language models including MiniCPM-V 4.5",
@@ -14,7 +14,9 @@
   },
   "devDependencies": {
     "@git.zone/tsrun": "^2.0.1",
-    "@git.zone/tstest": "^3.1.5"
+    "@git.zone/tstest": "^3.1.5",
+    "@push.rocks/smartagent": "^1.6.2",
+    "@push.rocks/smartai": "^0.13.3"
   },
   "repository": {
     "type": "git",

readme.md

@@ -2,7 +2,7 @@
 
 Production-ready Docker images for state-of-the-art AI Vision-Language Models. Run powerful multimodal AI locally with GPU acceleration—**no cloud API keys required**.
 
-> 🔥 **Three VLMs, one registry.** From lightweight document OCR to GPT-4o-level vision understanding—pick the right tool for your task.
+> 🔥 **Three VLMs, one registry.** From high-performance document OCR to GPT-4o-level vision understanding—pick the right tool for your task.
 
 ## Issue Reporting and Security
 
@@ -15,7 +15,7 @@ For reporting bugs, issues, or security vulnerabilities, please visit [community
 | Model | Parameters | Best For | API | Port | VRAM |
 |-------|-----------|----------|-----|------|------|
 | **MiniCPM-V 4.5** | 8B | General vision understanding, multi-image analysis | Ollama-compatible | 11434 | ~9GB |
-| **Nanonets-OCR-s** | ~4B | Document OCR with semantic markdown output | OpenAI-compatible | 8000 | ~10GB |
+| **Nanonets-OCR2-3B** | ~3B | Document OCR with semantic markdown, LaTeX, flowcharts | OpenAI-compatible | 8000 | ~12-16GB |
 | **Qwen3-VL-30B** | 30B (A3B) | Advanced visual agents, code generation from images | Ollama-compatible | 11434 | ~20GB |
 
 ---
@@ -29,7 +29,7 @@ code.foss.global/host.today/ht-docker-ai:<tag>
 | Tag | Model | Runtime | Port | VRAM |
 |-----|-------|---------|------|------|
 | `minicpm45v` / `latest` | MiniCPM-V 4.5 | Ollama | 11434 | ~9GB |
-| `nanonets-ocr` | Nanonets-OCR-s | vLLM | 8000 | ~10GB |
+| `nanonets-ocr` | Nanonets-OCR2-3B | vLLM | 8000 | ~12-16GB |
 | `qwen3vl` | Qwen3-VL-30B-A3B | Ollama | 11434 | ~20GB |
 
 ---
@@ -38,6 +38,13 @@ code.foss.global/host.today/ht-docker-ai:<tag>
 
 A GPT-4o level multimodal LLM from OpenBMB—handles image understanding, OCR, multi-image analysis, and visual reasoning across **30+ languages**.
 
+### ✨ Key Features
+
+- 🌍 **Multilingual:** 30+ languages supported
+- 🖼️ **Multi-image:** Analyze multiple images in one request
+- 📊 **Versatile:** Charts, documents, photos, diagrams
+- ⚡ **Efficient:** Runs on consumer GPUs (9GB VRAM)
+
 ### Quick Start
 
 ```bash
@@ -83,21 +90,22 @@ curl http://localhost:11434/api/chat -d '{
 
 | Mode | VRAM Required |
 |------|---------------|
-| int4 quantized | 9GB |
+| int4 quantized | ~9GB |
-| Full precision (bf16) | 18GB |
+| Full precision (bf16) | ~18GB |
 
 ---
 
-## 🔍 Nanonets-OCR-s
+## 🔍 Nanonets-OCR2-3B
 
-A **Qwen2.5-VL-3B** model fine-tuned specifically for document OCR. Outputs structured markdown with semantic HTML tags—perfect for preserving document structure.
+The **latest Nanonets document OCR model** (October 2025 release)—based on Qwen2.5-VL-3B, fine-tuned specifically for document extraction with significant improvements over the original OCR-s.
 
-### Key Features
+### ✨ Key Features
 
-- 📝 **Semantic output:** Tables → HTML, equations → LaTeX, watermarks/page numbers → tagged
+- 📝 **Semantic output:** Tables → HTML, equations → LaTeX, flowcharts → structured markup
 - 🌍 **Multilingual:** Inherits Qwen's broad language support
-- ⚡ **Efficient:** ~10GB VRAM, runs great on consumer GPUs
+- 📄 **30K context:** Handle large, multi-page documents
 - 🔌 **OpenAI-compatible:** Drop-in replacement for existing pipelines
+- 🎯 **Improved accuracy:** Better semantic tagging and LaTeX equation extraction vs. OCR-s
 
 ### Quick Start
 
@@ -116,7 +124,7 @@ docker run -d \
 curl http://localhost:8000/v1/chat/completions \
   -H "Content-Type: application/json" \
   -d '{
-    "model": "nanonets/Nanonets-OCR-s",
+    "model": "nanonets/Nanonets-OCR2-3B",
     "messages": [{
       "role": "user",
       "content": [
@@ -131,7 +139,7 @@ curl http://localhost:8000/v1/chat/completions \
 
 ### Output Format
 
-Nanonets-OCR-s returns markdown with semantic tags:
+Nanonets-OCR2-3B returns markdown with semantic tags:
 
 | Element | Output Format |
 |---------|---------------|
@@ -140,13 +148,14 @@ Nanonets-OCR-s returns markdown with semantic tags:
 | Images | `<img>description</img>` |
 | Watermarks | `<watermark>OFFICIAL COPY</watermark>` |
 | Page numbers | `<page_number>14</page_number>` |
+| Flowcharts | Structured markup |
 
-### Performance
+### Hardware Requirements
 
-| Metric | Value |
+| Config | VRAM |
-|--------|-------|
+|--------|------|
-| Speed | 3–8 seconds per page |
+| 30K context (default) | ~12-16GB |
-| VRAM | ~10GB |
+| Speed | ~3-8 seconds per page |
 
 ---
 
@@ -154,7 +163,7 @@ Nanonets-OCR-s returns markdown with semantic tags:
 
 The **most powerful** Qwen vision model—30B parameters with 3B active (MoE architecture). Handles complex visual reasoning, code generation from screenshots, and visual agent capabilities.
 
-### Key Features
+### ✨ Key Features
 
 - 🚀 **256K context** (expandable to 1M tokens!)
 - 🤖 **Visual agent capabilities** — can plan and execute multi-step tasks
@@ -204,7 +213,6 @@ curl http://localhost:11434/api/chat -d '{
 Run multiple VLMs together for maximum flexibility:
 
 ```yaml
-version: '3.8'
 services:
   # General vision tasks
   minicpm:
@@ -259,10 +267,10 @@ volumes:
 
 | Variable | Default | Description |
 |----------|---------|-------------|
-| `MODEL_NAME` | `nanonets/Nanonets-OCR-s` | HuggingFace model ID |
+| `MODEL_NAME` | `nanonets/Nanonets-OCR2-3B` | HuggingFace model ID |
 | `HOST` | `0.0.0.0` | API bind address |
 | `PORT` | `8000` | API port |
-| `MAX_MODEL_LEN` | `8192` | Maximum sequence length |
+| `MAX_MODEL_LEN` | `30000` | Maximum sequence length |
 | `GPU_MEMORY_UTILIZATION` | `0.9` | GPU memory usage (0-1) |
 
 ---
@@ -283,7 +291,7 @@ This dual-VLM approach catches extraction errors that single models miss.
 ### Why Multi-Model Works
 
 - **Different architectures:** Independent models cross-validate each other
-- **Specialized strengths:** Nanonets-OCR-s excels at document structure; MiniCPM-V handles general vision
+- **Specialized strengths:** Nanonets-OCR2-3B excels at document structure; MiniCPM-V handles general vision
 - **Native processing:** All VLMs see original images—no intermediate structure loss
 
 ### Model Selection Guide
@@ -291,10 +299,11 @@ This dual-VLM approach catches extraction errors that single models miss.
 | Task | Recommended Model |
 |------|-------------------|
 | General image understanding | MiniCPM-V 4.5 |
-| Document OCR with structure preservation | Nanonets-OCR-s |
+| Document OCR with structure preservation | Nanonets-OCR2-3B |
 | Complex visual reasoning / code generation | Qwen3-VL-30B |
 | Multi-image analysis | MiniCPM-V 4.5 |
 | Visual agent tasks | Qwen3-VL-30B |
+| Large documents (30K+ tokens) | Nanonets-OCR2-3B |
 
 ---
 
@@ -309,7 +318,7 @@ cd ht-docker-ai
 ./build-images.sh
 
 # Run tests
-./test-images.sh
+pnpm test
 ```
 
 ---

test/test.bankstatements.minicpm.ts

@@ -1,9 +1,10 @@
 /**
- * Bank statement extraction using MiniCPM-V (visual extraction)
+ * Bank statement extraction using MiniCPM-V via smartagent DualAgentOrchestrator
  *
- * JSON per-page approach:
+ * Uses vision-capable orchestrator with JsonValidatorTool for self-validation:
- * 1. Ask for structured JSON of all transactions per page
+ * 1. Process each page with the orchestrator
- * 2. Consensus: extract twice, compare, retry if mismatch
+ * 2. Driver extracts transactions and validates JSON before completing
+ * 3. Streaming output during extraction
  */
 import { tap, expect } from '@git.zone/tstest/tapbundle';
 import * as fs from 'fs';
@@ -11,6 +12,8 @@ import * as path from 'path';
 import { execSync } from 'child_process';
 import * as os from 'os';
 import { ensureMiniCpm } from './helpers/docker.js';
+import { SmartAi } from '@push.rocks/smartai';
+import { DualAgentOrchestrator, JsonValidatorTool } from '@push.rocks/smartagent';
 
 const OLLAMA_URL = 'http://localhost:11434';
 const MODEL = 'openbmb/minicpm-v4.5:q8_0';
@@ -21,21 +24,9 @@ interface ITransaction {
   amount: number;
 }
 
-const JSON_PROMPT = `Extract ALL transactions from this bank statement page as a JSON array.
+// SmartAi instance and orchestrator (initialized in setup)
-
+let smartAi: SmartAi;
-IMPORTANT RULES:
+let orchestrator: DualAgentOrchestrator;
-1. Each transaction has: date, description/counterparty, and an amount
-2. Amount is NEGATIVE for money going OUT (debits, payments, withdrawals)
-3. Amount is POSITIVE for money coming IN (credits, deposits, refunds)
-4. Date format: YYYY-MM-DD
-5. Do NOT include: opening balance, closing balance, subtotals, headers, or summary rows
-6. Only include actual transactions with a specific date and amount
-
-Return ONLY this JSON format, no explanation:
-[
-  {"date": "2021-06-01", "counterparty": "COMPANY NAME", "amount": -25.99},
-  {"date": "2021-06-02", "counterparty": "DEPOSIT FROM", "amount": 100.00}
-]`;
 
 /**
  * Convert PDF to PNG images using ImageMagick
@@ -65,206 +56,31 @@ function convertPdfToImages(pdfPath: string): string[] {
   }
 }
 
-/**
+const EXTRACTION_PROMPT = `Extract ALL transactions from this bank statement page as a JSON array.
- * Query for JSON extraction
- */
-async function queryJson(image: string, queryId: string): Promise<string> {
-  console.log(`      [${queryId}] Sending request to ${MODEL}...`);
-  const startTime = Date.now();
 
-  const response = await fetch(`${OLLAMA_URL}/api/chat`, {
+IMPORTANT RULES:
-    method: 'POST',
+1. Each transaction has: date, counterparty (description), and an amount
-    headers: { 'Content-Type': 'application/json' },
+2. Amount is NEGATIVE for money going OUT (debits, payments, withdrawals)
-    body: JSON.stringify({
+3. Amount is POSITIVE for money coming IN (credits, deposits, refunds)
-      model: MODEL,
+4. Date format: YYYY-MM-DD
-      messages: [{
+5. Do NOT include: opening balance, closing balance, subtotals, headers, or summary rows
-        role: 'user',
+6. Only include actual transactions with a specific date and amount
-        content: JSON_PROMPT,
-        images: [image],
-      }],
-      stream: false,
-      options: {
-        num_predict: 4000,
-        temperature: 0.1,
-      },
-    }),
-  });
 
-  const elapsed = ((Date.now() - startTime) / 1000).toFixed(1);
+Before completing, validate your JSON output:
 
-  if (!response.ok) {
+<tool_call>
-    console.log(`      [${queryId}] ERROR: ${response.status} (${elapsed}s)`);
+  <tool>json</tool>
-    throw new Error(`Ollama API error: ${response.status}`);
+  <action>validate</action>
-  }
+  <params>{"jsonString": "YOUR_JSON_ARRAY_HERE"}</params>
+</tool_call>
 
-  const data = await response.json();
+Output format (must be a valid JSON array):
-  const content = (data.message?.content || '').trim();
+[
-  console.log(`      [${queryId}] Response received (${elapsed}s, ${content.length} chars)`);
+  {"date": "2021-06-01", "counterparty": "COMPANY NAME", "amount": -25.99},
-  return content;
+  {"date": "2021-06-02", "counterparty": "DEPOSIT FROM", "amount": 100.00}
-}
+]
 
-/**
+Only complete after validation passes. Output the final JSON array in <task_complete> tags.`;
- * Sanitize JSON string - fix common issues from vision model output
- */
-function sanitizeJson(jsonStr: string): string {
-  let s = jsonStr;
-
-  // Fix +number (e.g., +93.80 -> 93.80) - JSON doesn't allow + prefix
-  // Handle various whitespace patterns
-  s = s.replace(/"amount"\s*:\s*\+/g, '"amount": ');
-  s = s.replace(/:\s*\+(\d)/g, ': $1');
-
-  // Fix European number format with thousands separator (e.g., 1.000.00 -> 1000.00)
-  // Pattern: "amount": X.XXX.XX where X.XXX is thousands and .XX is decimal
-  s = s.replace(/"amount"\s*:\s*(-?)(\d{1,3})\.(\d{3})\.(\d{2})\b/g, '"amount": $1$2$3.$4');
-  // Also handle larger numbers like 10.000.00
-  s = s.replace(/"amount"\s*:\s*(-?)(\d{1,3})\.(\d{3})\.(\d{3})\.(\d{2})\b/g, '"amount": $1$2$3$4.$5');
-
-  // Fix trailing commas before ] or }
-  s = s.replace(/,\s*([}\]])/g, '$1');
-
-  // Fix unescaped newlines inside strings (replace with space)
-  s = s.replace(/"([^"\\]*)\n([^"]*)"/g, '"$1 $2"');
-
-  // Fix unescaped tabs inside strings
-  s = s.replace(/"([^"\\]*)\t([^"]*)"/g, '"$1 $2"');
-
-  // Fix unescaped backslashes (but not already escaped ones)
-  s = s.replace(/\\(?!["\\/bfnrtu])/g, '\\\\');
-
-  // Fix common issues with counterparty names containing special chars
-  s = s.replace(/"counterparty":\s*"([^"]*)'([^"]*)"/g, '"counterparty": "$1$2"');
-
-  // Remove control characters except newlines (which we handle above)
-  s = s.replace(/[\x00-\x08\x0B\x0C\x0E-\x1F]/g, ' ');
-
-  return s;
-}
-
-/**
- * Parse JSON response into transactions
- */
-function parseJsonResponse(response: string, queryId: string): ITransaction[] {
-  console.log(`      [${queryId}] Parsing response...`);
-
-  // Try to find JSON in markdown code block
-  const codeBlockMatch = response.match(/```(?:json)?\s*([\s\S]*?)```/);
-  let jsonStr = codeBlockMatch ? codeBlockMatch[1].trim() : response.trim();
-
-  if (codeBlockMatch) {
-    console.log(`      [${queryId}] Found JSON in code block`);
-  }
-
-  // Sanitize JSON (fix +number issue)
-  jsonStr = sanitizeJson(jsonStr);
-
-  try {
-    const parsed = JSON.parse(jsonStr);
-    if (Array.isArray(parsed)) {
-      const txs = parsed.map(tx => ({
-        date: String(tx.date || ''),
-        counterparty: String(tx.counterparty || tx.description || ''),
-        amount: parseAmount(tx.amount),
-      }));
-      console.log(`      [${queryId}] Parsed ${txs.length} transactions (direct)`);
-      return txs;
-    }
-    console.log(`      [${queryId}] Parsed JSON is not an array`);
-  } catch (e) {
-    const errMsg = (e as Error).message;
-    console.log(`      [${queryId}] Direct parse failed: ${errMsg}`);
-
-    // Log problematic section with context
-    const posMatch = errMsg.match(/position (\d+)/);
-    if (posMatch) {
-      const pos = parseInt(posMatch[1]);
-      const start = Math.max(0, pos - 40);
-      const end = Math.min(jsonStr.length, pos + 40);
-      const context = jsonStr.substring(start, end);
-      const marker = ' '.repeat(pos - start) + '^';
-      console.log(`      [${queryId}] Context around error position ${pos}:`);
-      console.log(`      [${queryId}] ...${context}...`);
-      console.log(`      [${queryId}]    ${marker}`);
-    }
-
-    // Try to find JSON array pattern
-    const arrayMatch = jsonStr.match(/\[[\s\S]*\]/);
-    if (arrayMatch) {
-      console.log(`      [${queryId}] Found array pattern, trying to parse...`);
-      const sanitizedArray = sanitizeJson(arrayMatch[0]);
-      try {
-        const parsed = JSON.parse(sanitizedArray);
-        if (Array.isArray(parsed)) {
-          const txs = parsed.map(tx => ({
-            date: String(tx.date || ''),
-            counterparty: String(tx.counterparty || tx.description || ''),
-            amount: parseAmount(tx.amount),
-          }));
-          console.log(`      [${queryId}] Parsed ${txs.length} transactions (array match)`);
-          return txs;
-        }
-      } catch (e2) {
-        const errMsg2 = (e2 as Error).message;
-        console.log(`      [${queryId}] Array parse failed: ${errMsg2}`);
-        const posMatch2 = errMsg2.match(/position (\d+)/);
-        if (posMatch2) {
-          const pos2 = parseInt(posMatch2[1]);
-          console.log(`      [${queryId}] Context around error: ...${sanitizedArray.substring(Math.max(0, pos2 - 30), pos2 + 30)}...`);
-        }
-
-        // Try to extract individual objects from the malformed array
-        console.log(`      [${queryId}] Attempting object-by-object extraction...`);
-        const extracted = extractTransactionsFromMalformedJson(sanitizedArray, queryId);
-        if (extracted.length > 0) {
-          console.log(`      [${queryId}] Recovered ${extracted.length} transactions via object extraction`);
-          return extracted;
-        }
-      }
-    } else {
-      console.log(`      [${queryId}] No array pattern found in response`);
-      console.log(`      [${queryId}] Raw response preview: ${response.substring(0, 200)}...`);
-    }
-  }
-
-  console.log(`      [${queryId}] PARSE FAILED - returning empty array`);
-  return [];
-}
-
-/**
- * Extract transactions from malformed JSON by parsing objects individually
- */
-function extractTransactionsFromMalformedJson(jsonStr: string, queryId: string): ITransaction[] {
-  const transactions: ITransaction[] = [];
-
-  // Match individual transaction objects
-  const objectPattern = /\{\s*"date"\s*:\s*"([^"]+)"\s*,\s*"counterparty"\s*:\s*"([^"]+)"\s*,\s*"amount"\s*:\s*([+-]?\d+\.?\d*)\s*\}/g;
-  let match;
-
-  while ((match = objectPattern.exec(jsonStr)) !== null) {
-    transactions.push({
-      date: match[1],
-      counterparty: match[2],
-      amount: parseFloat(match[3]),
-    });
-  }
-
-  // Also try with different field orders (amount before counterparty, etc.)
-  if (transactions.length === 0) {
-    const altPattern = /\{\s*"date"\s*:\s*"([^"]+)"[^}]*"amount"\s*:\s*([+-]?\d+\.?\d*)[^}]*\}/g;
-    while ((match = altPattern.exec(jsonStr)) !== null) {
-      // Try to extract counterparty from the match
-      const counterpartyMatch = match[0].match(/"counterparty"\s*:\s*"([^"]+)"/);
-      const descMatch = match[0].match(/"description"\s*:\s*"([^"]+)"/);
-      transactions.push({
-        date: match[1],
-        counterparty: counterpartyMatch?.[1] || descMatch?.[1] || 'UNKNOWN',
-        amount: parseFloat(match[2]),
-      });
-    }
-  }
-
-  return transactions;
-}
 
 /**
  * Parse amount from various formats
@@ -284,102 +100,101 @@ function parseAmount(value: unknown): number {
 }
 
 /**
- * Compare two transaction arrays for consensus
+ * Extract JSON from response (handles markdown code blocks and task_complete tags)
  */
-function transactionArraysMatch(a: ITransaction[], b: ITransaction[]): boolean {
+function extractJsonFromResponse(response: string): unknown[] | null {
-  if (a.length !== b.length) return false;
+  // Try to find JSON in task_complete tags
-
+  const completeMatch = response.match(/<task_complete>([\s\S]*?)<\/task_complete>/);
-  for (let i = 0; i < a.length; i++) {
+  if (completeMatch) {
-    const dateMatch = a[i].date === b[i].date;
+    const content = completeMatch[1].trim();
-    const amountMatch = Math.abs(a[i].amount - b[i].amount) < 0.01;
+    // Try to find JSON in the content
-    if (!dateMatch || !amountMatch) return false;
+    const codeBlockMatch = content.match(/```(?:json)?\s*([\s\S]*?)```/);
+    const jsonStr = codeBlockMatch ? codeBlockMatch[1].trim() : content;
+    try {
+      const parsed = JSON.parse(jsonStr);
+      if (Array.isArray(parsed)) return parsed;
+    } catch {
+      // Try to find JSON array pattern
+      const jsonMatch = jsonStr.match(/\[[\s\S]*\]/);
+      if (jsonMatch) {
+        try {
+          const parsed = JSON.parse(jsonMatch[0]);
+          if (Array.isArray(parsed)) return parsed;
+        } catch {
+          return null;
+        }
+      }
+    }
   }
 
-  return true;
+  // Try to find JSON in markdown code block
+  const codeBlockMatch = response.match(/```(?:json)?\s*([\s\S]*?)```/);
+  const jsonStr = codeBlockMatch ? codeBlockMatch[1].trim() : response.trim();
+
+  try {
+    const parsed = JSON.parse(jsonStr);
+    if (Array.isArray(parsed)) return parsed;
+  } catch {
+    // Try to find JSON array pattern
+    const jsonMatch = jsonStr.match(/\[[\s\S]*\]/);
+    if (jsonMatch) {
+      try {
+        const parsed = JSON.parse(jsonMatch[0]);
+        if (Array.isArray(parsed)) return parsed;
+      } catch {
+        return null;
+      }
+    }
+  }
+  return null;
 }
 
 /**
- * Compare two transaction arrays and log differences
+ * Parse JSON response into transactions
  */
-function compareAndLogDifferences(txs1: ITransaction[], txs2: ITransaction[], pageNum: number): void {
+function parseJsonToTransactions(response: string): ITransaction[] {
-  if (txs1.length !== txs2.length) {
+  const parsed = extractJsonFromResponse(response);
-    console.log(`    [Page ${pageNum}] Length mismatch: Q1=${txs1.length}, Q2=${txs2.length}`);
+  if (!parsed || !Array.isArray(parsed)) return [];
-    return;
-  }
 
-  for (let i = 0; i < txs1.length; i++) {
+  return parsed.map((tx: any) => ({
-    const dateMatch = txs1[i].date === txs2[i].date;
+    date: String(tx.date || ''),
-    const amountMatch = Math.abs(txs1[i].amount - txs2[i].amount) < 0.01;
+    counterparty: String(tx.counterparty || tx.description || ''),
-
+    amount: parseAmount(tx.amount),
-    if (!dateMatch || !amountMatch) {
+  }));
-      console.log(`    [Page ${pageNum}] Tx ${i + 1} differs:`);
-      console.log(`      Q1: ${txs1[i].date} | ${txs1[i].amount}`);
-      console.log(`      Q2: ${txs2[i].date} | ${txs2[i].amount}`);
-    }
-  }
 }
 
 /**
- * Extract transactions from a single page with consensus
+ * Extract transactions from a single page using smartagent orchestrator
  */
 async function extractTransactionsFromPage(image: string, pageNum: number): Promise<ITransaction[]> {
-  const MAX_ATTEMPTS = 5;
   console.log(`\n    ======== Page ${pageNum} ========`);
-  console.log(`    [Page ${pageNum}] Starting JSON extraction...`);
 
-  for (let attempt = 1; attempt <= MAX_ATTEMPTS; attempt++) {
+  const startTime = Date.now();
-    console.log(`\n    [Page ${pageNum}] --- Attempt ${attempt}/${MAX_ATTEMPTS} ---`);
 
-    // Extract twice in parallel
+  const result = await orchestrator.run(EXTRACTION_PROMPT, { images: [image] });
-    const q1Id = `P${pageNum}A${attempt}Q1`;
-    const q2Id = `P${pageNum}A${attempt}Q2`;
 
-    const [response1, response2] = await Promise.all([
+  const elapsed = ((Date.now() - startTime) / 1000).toFixed(1);
-      queryJson(image, q1Id),
+  console.log(`\n    [Page ${pageNum}] Completed in ${elapsed}s (${result.iterations} iterations, status: ${result.status})`);
-      queryJson(image, q2Id),
-    ]);
 
-    const txs1 = parseJsonResponse(response1, q1Id);
+  const transactions = parseJsonToTransactions(result.result);
-    const txs2 = parseJsonResponse(response2, q2Id);
 
-    console.log(`    [Page ${pageNum}] Results: Q1=${txs1.length} txs, Q2=${txs2.length} txs`);
+  console.log(`    [Page ${pageNum}] Extracted ${transactions.length} transactions:`);
-
+  for (let i = 0; i < Math.min(transactions.length, 10); i++) {
-    if (txs1.length > 0 && transactionArraysMatch(txs1, txs2)) {
+    const tx = transactions[i];
-      console.log(`    [Page ${pageNum}] ✓ CONSENSUS REACHED: ${txs1.length} transactions`);
-      console.log(`    [Page ${pageNum}] Transactions:`);
-      for (let i = 0; i < txs1.length; i++) {
-        const tx = txs1[i];
     console.log(`      ${(i + 1).toString().padStart(2)}. ${tx.date} | ${tx.counterparty.substring(0, 30).padEnd(30)} | ${tx.amount >= 0 ? '+' : ''}${tx.amount.toFixed(2)}`);
   }
-      return txs1;
+  if (transactions.length > 10) {
+    console.log(`      ... and ${transactions.length - 10} more transactions`);
   }
 
-    console.log(`    [Page ${pageNum}] ✗ NO CONSENSUS`);
+  return transactions;
-    compareAndLogDifferences(txs1, txs2, pageNum);
-
-    if (attempt < MAX_ATTEMPTS) {
-      console.log(`    [Page ${pageNum}] Retrying...`);
-    }
-  }
-
-  // Fallback: use last response
-  console.log(`\n    [Page ${pageNum}] === FALLBACK (no consensus after ${MAX_ATTEMPTS} attempts) ===`);
-  const fallbackId = `P${pageNum}FALLBACK`;
-  const fallbackResponse = await queryJson(image, fallbackId);
-  const fallback = parseJsonResponse(fallbackResponse, fallbackId);
-  console.log(`    [Page ${pageNum}] ~ FALLBACK RESULT: ${fallback.length} transactions`);
-  for (let i = 0; i < fallback.length; i++) {
-    const tx = fallback[i];
-    console.log(`      ${(i + 1).toString().padStart(2)}. ${tx.date} | ${tx.counterparty.substring(0, 30).padEnd(30)} | ${tx.amount >= 0 ? '+' : ''}${tx.amount.toFixed(2)}`);
-  }
-  return fallback;
 }
 
 /**
  * Extract all transactions from bank statement
  */
 async function extractTransactions(images: string[]): Promise<ITransaction[]> {
-  console.log(`    [Vision] Processing ${images.length} page(s) with ${MODEL} (JSON consensus)`);
+  console.log(`    [Vision] Processing ${images.length} page(s) with smartagent DualAgentOrchestrator`);
 
   const allTransactions: ITransaction[] = [];
 
@@ -474,6 +289,80 @@ tap.test('setup: ensure Docker containers are running', async () => {
   console.log('\n[Setup] All containers ready!\n');
 });
 
+tap.test('setup: initialize smartagent orchestrator', async () => {
+  console.log('[Setup] Initializing SmartAi and DualAgentOrchestrator...');
+
+  smartAi = new SmartAi({
+    ollama: {
+      baseUrl: OLLAMA_URL,
+      model: MODEL,
+      defaultOptions: {
+        num_ctx: 32768,
+        num_predict: 4000,
+        temperature: 0.1,
+      },
+      defaultTimeout: 300000, // 5 minutes for vision tasks
+    },
+  });
+
+  await smartAi.start();
+
+  orchestrator = new DualAgentOrchestrator({
+    smartAiInstance: smartAi,
+    defaultProvider: 'ollama',
+    guardianPolicyPrompt: `You are a Guardian agent overseeing bank statement extraction tasks.
+
+APPROVE all tool calls that:
+- Use the json.validate action to verify JSON output
+- Are reasonable attempts to complete the extraction task
+
+REJECT tool calls that:
+- Attempt to access external resources
+- Try to execute arbitrary code
+- Are clearly unrelated to bank statement extraction`,
+    driverSystemMessage: `You are an AI assistant that extracts bank transactions from statement images.
+
+Your task is to analyze bank statement images and extract transaction data.
+You have access to a json.validate tool to verify your JSON output.
+
+IMPORTANT: Always validate your JSON before completing the task.
+
+## Tool Usage Format
+When you need to validate JSON, output:
+
+<tool_call>
+  <tool>json</tool>
+  <action>validate</action>
+  <params>{"jsonString": "YOUR_JSON_ARRAY"}</params>
+</tool_call>
+
+## Completion Format
+After validation passes, complete the task:
+
+<task_complete>
+[{"date": "YYYY-MM-DD", "counterparty": "...", "amount": -123.45}, ...]
+</task_complete>`,
+    maxIterations: 5,
+    maxConsecutiveRejections: 3,
+    onToken: (token, source) => {
+      if (source === 'driver') {
+        process.stdout.write(token);
+      }
+    },
+    onProgress: (event) => {
+      if (event.logLevel === 'error') {
+        console.error(event.logMessage);
+      }
+    },
+  });
+
+  // Register the JsonValidatorTool
+  orchestrator.registerTool(new JsonValidatorTool());
+
+  await orchestrator.start();
+  console.log('[Setup] Orchestrator initialized!\n');
+});
+
 tap.test('should have MiniCPM-V model loaded', async () => {
   const response = await fetch(`${OLLAMA_URL}/api/tags`);
   const data = await response.json();
@@ -482,7 +371,7 @@ tap.test('should have MiniCPM-V model loaded', async () => {
 });
 
 const testCases = findTestCases();
-console.log(`\nFound ${testCases.length} bank statement test cases (MiniCPM-V)\n`);
+console.log(`\nFound ${testCases.length} bank statement test cases (smartagent + MiniCPM-V)\n`);
 
 let passedCount = 0;
 let failedCount = 0;
@@ -514,7 +403,10 @@ for (const testCase of testCases) {
     // Log counterparty variations (names that differ but date/amount matched)
     if (result.variations.length > 0) {
       console.log(`  Counterparty variations (${result.variations.length}):`);
-      result.variations.forEach((v) => console.log(`    ${v}`));
+      result.variations.slice(0, 5).forEach((v) => console.log(`    ${v}`));
+      if (result.variations.length > 5) {
+        console.log(`    ... and ${result.variations.length - 5} more variations`);
+      }
     }
 
     expect(result.matches).toEqual(result.total);
@@ -522,12 +414,20 @@ for (const testCase of testCases) {
   });
 }
 
+tap.test('cleanup: stop orchestrator', async () => {
+  if (orchestrator) {
+    await orchestrator.stop();
+  }
+  console.log('[Cleanup] Orchestrator stopped');
+});
+
 tap.test('summary', async () => {
   const total = testCases.length;
   console.log(`\n======================================================`);
-  console.log(`   Bank Statement Summary (${MODEL})`);
+  console.log(`   Bank Statement Summary`);
+  console.log(`   (smartagent + ${MODEL})`);
   console.log(`======================================================`);
-  console.log(`  Method:   JSON per-page + consensus`);
+  console.log(`  Method:   DualAgentOrchestrator with vision`);
   console.log(`  Passed:   ${passedCount}/${total}`);
   console.log(`  Failed:   ${failedCount}/${total}`);
   console.log(`======================================================\n`);

test/test.bankstatements.nanonets.ts

@@ -11,7 +11,9 @@ import * as fs from 'fs';
 import * as path from 'path';
 import { execSync } from 'child_process';
 import * as os from 'os';
-import { ensureNanonetsOcr, ensureMiniCpm, removeContainer, isContainerRunning } from './helpers/docker.js';
+import { ensureNanonetsOcr, ensureMiniCpm, isContainerRunning } from './helpers/docker.js';
+import { SmartAi } from '@push.rocks/smartai';
+import { DualAgentOrchestrator, JsonValidatorTool } from '@push.rocks/smartagent';
 
 const NANONETS_URL = 'http://localhost:8000/v1';
 const NANONETS_MODEL = 'nanonets/Nanonets-OCR2-3B';
@@ -22,6 +24,22 @@ const EXTRACTION_MODEL = 'gpt-oss:20b';
 // Temp directory for storing markdown between stages
 const TEMP_MD_DIR = path.join(os.tmpdir(), 'nanonets-markdown');
 
+// SmartAi instance for Ollama with optimized settings
+const smartAi = new SmartAi({
+  ollama: {
+    baseUrl: OLLAMA_URL,
+    model: EXTRACTION_MODEL,
+    defaultOptions: {
+      num_ctx: 32768,   // Larger context for long statements + thinking
+      temperature: 0,   // Deterministic for JSON extraction
+    },
+    defaultTimeout: 600000,  // 10 minute timeout for large documents
+  },
+});
+
+// DualAgentOrchestrator for structured task execution
+let orchestrator: DualAgentOrchestrator;
+
 interface ITransaction {
   date: string;
   counterparty: string;
@@ -51,11 +69,21 @@ 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
@@ -242,93 +270,107 @@ async function ensureExtractionModel(): Promise<boolean> {
 }
 
 /**
- * Extract transactions from markdown using GPT-OSS 20B (streaming)
+ * Try to extract valid JSON from a response string
+ */
+function tryExtractJson(response: string): unknown[] | null {
+  // Remove thinking tags
+  let clean = response.replace(/<think>[\s\S]*?<\/think>/g, '').trim();
+
+  // Try task_complete tags first
+  const completeMatch = clean.match(/<task_complete>([\s\S]*?)<\/task_complete>/);
+  if (completeMatch) {
+    clean = completeMatch[1].trim();
+  }
+
+  // Try code block
+  const codeBlockMatch = clean.match(/```(?:json)?\s*([\s\S]*?)```/);
+  const jsonStr = codeBlockMatch ? codeBlockMatch[1].trim() : clean;
+
+  try {
+    const parsed = JSON.parse(jsonStr);
+    if (Array.isArray(parsed)) return parsed;
+  } catch {
+    // Try to find JSON array
+    const jsonMatch = jsonStr.match(/\[[\s\S]*\]/);
+    if (jsonMatch) {
+      try {
+        const parsed = JSON.parse(sanitizeJson(jsonMatch[0]));
+        if (Array.isArray(parsed)) return parsed;
+      } catch {
+        return null;
+      }
+    }
+    return null;
+  }
+  return null;
+}
+
+/**
+ * Extract transactions from markdown using smartagent DualAgentOrchestrator
+ * Validates JSON and retries if invalid
  */
 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: ${markdown.length} chars`);
-  console.log(`\n      [${queryId}] ===== PROMPT =====`);
-  console.log(fullPrompt);
-  console.log(`      [${queryId}] ===== END PROMPT (${fullPrompt.length} chars) =====\n`);
 
-  const response = await fetch(`${OLLAMA_URL}/api/chat`, {
+  // Build the extraction task with document context
-    method: 'POST',
+  const taskPrompt = `Extract all transactions from this bank statement document and output ONLY the JSON array:
-    headers: { 'Content-Type': 'application/json' },
-    body: JSON.stringify({
-      model: EXTRACTION_MODEL,
-      messages: [
-        { role: 'user', content: 'Hi there, how are you?' },
-        { role: 'assistant', content: 'Good, how can I help you today?' },
-        { role: 'user', content: fullPrompt },
-      ],
-      stream: true,
-    }),
-    signal: AbortSignal.timeout(600000),  // 10 minute timeout
-  });
 
-  if (!response.ok) {
+${markdown}
-    const elapsed = ((Date.now() - startTime) / 1000).toFixed(1);
-    console.log(`      [${queryId}] ERROR: ${response.status} (${elapsed}s)`);
-    throw new Error(`Ollama API error: ${response.status}`);
-  }
 
-  // Stream the response
+${JSON_EXTRACTION_PROMPT}
-  let content = '';
+
-  let thinkingContent = '';
+Before completing, validate your JSON using the json.validate tool:
-  let thinkingStarted = false;
+
-  let outputStarted = false;
+<tool_call>
-  const reader = response.body!.getReader();
+  <tool>json</tool>
-  const decoder = new TextDecoder();
+  <action>validate</action>
+  <params>{"jsonString": "YOUR_JSON_ARRAY_HERE"}</params>
+</tool_call>
+
+Only complete after validation passes. Output the final JSON array in <task_complete></task_complete> tags.`;
 
   try {
-    while (true) {
+    const result = await orchestrator.run(taskPrompt);
-      const { done, value } = await reader.read();
-      if (done) break;
-
-      const chunk = decoder.decode(value, { stream: true });
-
-      // Each line is a JSON object
-      for (const line of chunk.split('\n').filter(l => l.trim())) {
-        try {
-          const json = JSON.parse(line);
-
-          // Stream thinking tokens
-          const thinking = json.message?.thinking || '';
-          if (thinking) {
-            if (!thinkingStarted) {
-              process.stdout.write(`      [${queryId}] THINKING: `);
-              thinkingStarted = true;
-            }
-            process.stdout.write(thinking);
-            thinkingContent += thinking;
-          }
-
-          // Stream content tokens
-          const token = json.message?.content || '';
-          if (token) {
-            if (!outputStarted) {
-              if (thinkingStarted) process.stdout.write('\n');
-              process.stdout.write(`      [${queryId}] OUTPUT: `);
-              outputStarted = true;
-            }
-            process.stdout.write(token);
-            content += token;
-          }
-        } catch {
-          // Ignore parse errors for partial chunks
-        }
-      }
-    }
-  } finally {
-    if (thinkingStarted || outputStarted) process.stdout.write('\n');
-  }
-
     const elapsed = ((Date.now() - startTime) / 1000).toFixed(1);
-  console.log(`      [${queryId}] Done: ${thinkingContent.length} thinking chars, ${content.length} output chars (${elapsed}s)`);
+    console.log(`      [${queryId}] Status: ${result.status}, Iterations: ${result.iterations} (${elapsed}s)`);
 
-  return parseJsonResponse(content, queryId);
+    // Try to parse JSON from result
+    let jsonData: unknown[] | null = null;
+    let responseText = result.result || '';
+
+    if (result.success && responseText) {
+      jsonData = tryExtractJson(responseText);
+    }
+
+    // Fallback: try parsing from history
+    if (!jsonData && result.history?.length > 0) {
+      const lastMessage = result.history[result.history.length - 1];
+      if (lastMessage?.content) {
+        responseText = lastMessage.content;
+        jsonData = tryExtractJson(responseText);
+      }
+    }
+
+    if (!jsonData) {
+      console.log(`      [${queryId}] Failed to parse JSON`);
+      return [];
+    }
+
+    // Convert to transactions
+    const txs = jsonData.map((tx: any) => ({
+      date: String(tx.date || ''),
+      counterparty: String(tx.counterparty || tx.description || ''),
+      amount: parseAmount(tx.amount),
+    }));
+    console.log(`      [${queryId}] Parsed ${txs.length} transactions`);
+    return txs;
+  } catch (error) {
+    const elapsed = ((Date.now() - startTime) / 1000).toFixed(1);
+    console.log(`      [${queryId}] ERROR: ${error} (${elapsed}s)`);
+    throw error;
+  }
 }
 
 /**
@@ -579,6 +621,53 @@ tap.test('Stage 2: Setup Ollama + GPT-OSS 20B', async () => {
 
   const extractionOk = await ensureExtractionModel();
   expect(extractionOk).toBeTrue();
+
+  // Initialize SmartAi and DualAgentOrchestrator
+  console.log('  [SmartAgent] Starting SmartAi...');
+  await smartAi.start();
+
+  console.log('  [SmartAgent] Creating DualAgentOrchestrator...');
+  orchestrator = new DualAgentOrchestrator({
+    smartAiInstance: smartAi,
+    defaultProvider: 'ollama',
+    guardianPolicyPrompt: `
+      JSON EXTRACTION POLICY:
+      - APPROVE all JSON extraction tasks
+      - APPROVE all json.validate tool calls
+      - This is a read-only operation - no file system or network access needed
+      - The task is to extract structured transaction data from document text
+    `,
+    driverSystemMessage: `You are a precise JSON extraction assistant. Your only job is to extract transaction data from bank statements.
+
+CRITICAL RULES:
+1. Output valid JSON array with the exact format requested
+2. Amounts should be NEGATIVE for debits/withdrawals, POSITIVE for credits/deposits
+3. IMPORTANT: Before completing, validate your JSON using the json.validate tool:
+
+<tool_call>
+  <tool>json</tool>
+  <action>validate</action>
+  <params>{"jsonString": "YOUR_JSON_ARRAY"}</params>
+</tool_call>
+
+4. Only complete after validation passes
+
+When done, wrap your JSON array in <task_complete></task_complete> tags.`,
+    maxIterations: 5,
+    // Enable streaming for real-time progress visibility
+    onToken: (token, source) => {
+      if (source === 'driver') {
+        process.stdout.write(token);
+      }
+    },
+  });
+
+  // Register JsonValidatorTool for self-validation
+  orchestrator.registerTool(new JsonValidatorTool());
+
+  console.log('  [SmartAgent] Starting orchestrator...');
+  await orchestrator.start();
+  console.log('  [SmartAgent] Ready for extraction');
 });
 
 let passedCount = 0;
@@ -630,11 +719,19 @@ for (const tc of testCases) {
 }
 
 tap.test('Summary', async () => {
+  // Cleanup orchestrator and SmartAi
+  if (orchestrator) {
+    console.log('\n  [SmartAgent] Stopping orchestrator...');
+    await orchestrator.stop();
+  }
+  console.log('  [SmartAgent] Stopping SmartAi...');
+  await smartAi.stop();
+
   console.log(`\n======================================================`);
-  console.log(`   Bank Statement Summary (Nanonets + GPT-OSS 20B Sequential)`);
+  console.log(`   Bank Statement Summary (Nanonets + SmartAgent)`);
   console.log(`======================================================`);
   console.log(`  Stage 1:  Nanonets-OCR-s (document -> markdown)`);
-  console.log(`  Stage 2:  GPT-OSS 20B (markdown -> JSON)`);
+  console.log(`  Stage 2:  GPT-OSS 20B + SmartAgent (markdown -> JSON)`);
   console.log(`  Passed:   ${passedCount}/${testCases.length}`);
   console.log(`  Failed:   ${failedCount}/${testCases.length}`);
   console.log(`======================================================\n`);

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.minicpm.ts

@@ -1,10 +1,10 @@
 /**
- * Invoice extraction test using MiniCPM-V (visual extraction)
+ * Invoice extraction test using MiniCPM-V via smartagent DualAgentOrchestrator
  *
- * Consensus approach:
+ * Uses vision-capable orchestrator with JsonValidatorTool for self-validation:
- * 1. Pass 1: Fast JSON extraction
+ * 1. Pass images to the orchestrator
- * 2. Pass 2: Confirm with thinking enabled
+ * 2. Driver extracts invoice data and validates JSON before completing
- * 3. If mismatch: repeat until consensus or max attempts
+ * 3. If validation fails, driver retries within the same task
  */
 import { tap, expect } from '@git.zone/tstest/tapbundle';
 import * as fs from 'fs';
@@ -12,6 +12,8 @@ import * as path from 'path';
 import { execSync } from 'child_process';
 import * as os from 'os';
 import { ensureMiniCpm } from './helpers/docker.js';
+import { SmartAi } from '@push.rocks/smartai';
+import { DualAgentOrchestrator, JsonValidatorTool } from '@push.rocks/smartagent';
 
 const OLLAMA_URL = 'http://localhost:11434';
 const MODEL = 'openbmb/minicpm-v4.5:q8_0';
@@ -26,6 +28,10 @@ interface IInvoice {
   total_amount: number;
 }
 
+// SmartAi instance and orchestrator (initialized in setup)
+let smartAi: SmartAi;
+let orchestrator: DualAgentOrchestrator;
+
 /**
  * Convert PDF to PNG images using ImageMagick
  */
@@ -54,7 +60,9 @@ function convertPdfToImages(pdfPath: string): string[] {
   }
 }
 
-const JSON_PROMPT = `Extract invoice data from this image. Return ONLY a JSON object with these exact fields:
+const EXTRACTION_PROMPT = `Extract invoice data from the provided image(s).
+
+IMPORTANT: You must output a valid JSON object with these exact fields:
 {
   "invoice_number": "the invoice number (not VAT ID, not customer ID)",
   "invoice_date": "YYYY-MM-DD format",
@@ -64,67 +72,16 @@ const JSON_PROMPT = `Extract invoice data from this image. Return ONLY a JSON ob
   "vat_amount": 0.00,
   "total_amount": 0.00
 }
-Return only the JSON, no explanation.`;
 
-/**
+Before completing, use the json.validate tool to verify your output is valid JSON with all required fields.
- * Query MiniCPM-V for JSON output (fast, no thinking)
- */
-async function queryJsonFast(images: string[]): Promise<string> {
-  const response = await fetch(`${OLLAMA_URL}/api/chat`, {
-    method: 'POST',
-    headers: { 'Content-Type': 'application/json' },
-    body: JSON.stringify({
-      model: MODEL,
-      messages: [{
-        role: 'user',
-        content: JSON_PROMPT,
-        images: images,
-      }],
-      stream: false,
-      options: {
-        num_predict: 1000,
-        temperature: 0.1,
-      },
-    }),
-  });
 
-  if (!response.ok) {
+<tool_call>
-    throw new Error(`Ollama API error: ${response.status}`);
+  <tool>json</tool>
-  }
+  <action>validate</action>
+  <params>{"jsonString": "YOUR_JSON_HERE", "requiredFields": ["invoice_number", "invoice_date", "vendor_name", "currency", "net_amount", "vat_amount", "total_amount"]}</params>
+</tool_call>
 
-  const data = await response.json();
+Only complete the task after validation passes. Output the final JSON in <task_complete> tags.`;
-  return (data.message?.content || '').trim();
-}
-
-/**
- * Query MiniCPM-V for JSON output with thinking enabled (slower, more accurate)
- */
-async function queryJsonWithThinking(images: string[]): Promise<string> {
-  const response = await fetch(`${OLLAMA_URL}/api/chat`, {
-    method: 'POST',
-    headers: { 'Content-Type': 'application/json' },
-    body: JSON.stringify({
-      model: MODEL,
-      messages: [{
-        role: 'user',
-        content: `Think carefully about this invoice image, then ${JSON_PROMPT}`,
-        images: images,
-      }],
-      stream: false,
-      options: {
-        num_predict: 2000,
-        temperature: 0.1,
-      },
-    }),
-  });
-
-  if (!response.ok) {
-    throw new Error(`Ollama API error: ${response.status}`);
-  }
-
-  const data = await response.json();
-  return (data.message?.content || '').trim();
-}
 
 /**
  * Parse amount from string (handles European format)
@@ -190,9 +147,31 @@ function extractCurrency(s: string | undefined): string {
 }
 
 /**
- * Extract JSON from response (handles markdown code blocks)
+ * Extract JSON from response (handles markdown code blocks and task_complete tags)
  */
 function extractJsonFromResponse(response: string): Record<string, unknown> | null {
+  // Try to find JSON in task_complete tags
+  const completeMatch = response.match(/<task_complete>([\s\S]*?)<\/task_complete>/);
+  if (completeMatch) {
+    const content = completeMatch[1].trim();
+    // Try to find JSON in the content
+    const codeBlockMatch = content.match(/```(?:json)?\s*([\s\S]*?)```/);
+    const jsonStr = codeBlockMatch ? codeBlockMatch[1].trim() : content;
+    try {
+      return JSON.parse(jsonStr);
+    } catch {
+      // Try to find JSON object pattern
+      const jsonMatch = jsonStr.match(/\{[\s\S]*\}/);
+      if (jsonMatch) {
+        try {
+          return JSON.parse(jsonMatch[0]);
+        } catch {
+          return null;
+        }
+      }
+    }
+  }
+
   // Try to find JSON in markdown code block
   const codeBlockMatch = response.match(/```(?:json)?\s*([\s\S]*?)```/);
   const jsonStr = codeBlockMatch ? codeBlockMatch[1].trim() : response.trim();
@@ -232,76 +211,27 @@ function parseJsonToInvoice(response: string): IInvoice | null {
 }
 
 /**
- * Compare two invoices for consensus (key fields must match)
+ * Extract invoice data using smartagent orchestrator with vision
- */
-function invoicesMatch(a: IInvoice, b: IInvoice): boolean {
-  const numMatch = a.invoice_number.toLowerCase() === b.invoice_number.toLowerCase();
-  const dateMatch = a.invoice_date === b.invoice_date;
-  const totalMatch = Math.abs(a.total_amount - b.total_amount) < 0.02;
-  return numMatch && dateMatch && totalMatch;
-}
-
-/**
- * Extract invoice data using consensus approach:
- * 1. Pass 1: Fast JSON extraction
- * 2. Pass 2: Confirm with thinking enabled
- * 3. If mismatch: repeat until consensus or max 5 attempts
  */
 async function extractInvoiceFromImages(images: string[]): Promise<IInvoice> {
-  console.log(`    [Vision] Processing ${images.length} page(s) with ${MODEL} (consensus)`);
+  console.log(`    [Vision] Processing ${images.length} page(s) with smartagent DualAgentOrchestrator`);
 
-  const MAX_ATTEMPTS = 5;
+  const startTime = Date.now();
-  let attempt = 0;
 
-  while (attempt < MAX_ATTEMPTS) {
+  const result = await orchestrator.run(EXTRACTION_PROMPT, { images });
-    attempt++;
-    console.log(`    [Attempt ${attempt}/${MAX_ATTEMPTS}]`);
 
-    // PASS 1: Fast JSON extraction
+  const elapsed = ((Date.now() - startTime) / 1000).toFixed(1);
-    console.log(`    [Pass 1] Fast extraction...`);
+  console.log(`    [Vision] Completed in ${elapsed}s (${result.iterations} iterations, status: ${result.status})`);
-    const fastResponse = await queryJsonFast(images);
-    const fastInvoice = parseJsonToInvoice(fastResponse);
 
-    if (!fastInvoice) {
+  const invoice = parseJsonToInvoice(result.result);
-      console.log(`    [Pass 1] JSON parsing failed, retrying...`);
-      continue;
-    }
-    console.log(`    [Pass 1] Result: ${fastInvoice.invoice_number} | ${fastInvoice.invoice_date} | ${fastInvoice.total_amount} ${fastInvoice.currency}`);
 
-    // PASS 2: Confirm with thinking
+  if (invoice) {
-    console.log(`    [Pass 2] Thinking confirmation...`);
+    console.log(`    [Result] ${invoice.invoice_number} | ${invoice.invoice_date} | ${invoice.total_amount} ${invoice.currency}`);
-    const thinkResponse = await queryJsonWithThinking(images);
+    return invoice;
-    const thinkInvoice = parseJsonToInvoice(thinkResponse);
-
-    if (!thinkInvoice) {
-      console.log(`    [Pass 2] JSON parsing failed, retrying...`);
-      continue;
-    }
-    console.log(`    [Pass 2] Result: ${thinkInvoice.invoice_number} | ${thinkInvoice.invoice_date} | ${thinkInvoice.total_amount} ${thinkInvoice.currency}`);
-
-    // Check consensus
-    if (invoicesMatch(fastInvoice, thinkInvoice)) {
-      console.log(`    [Consensus] MATCH - using result`);
-      return thinkInvoice; // Prefer thinking result
   }
 
-    console.log(`    [Consensus] MISMATCH - repeating...`);
+  // Return empty invoice if parsing failed
-    console.log(`      Fast:  ${fastInvoice.invoice_number} | ${fastInvoice.invoice_date} | ${fastInvoice.total_amount}`);
+  console.log(`    [Result] Parsing failed, returning empty invoice`);
-    console.log(`      Think: ${thinkInvoice.invoice_number} | ${thinkInvoice.invoice_date} | ${thinkInvoice.total_amount}`);
-  }
-
-  // Max attempts reached - do one final thinking pass and use that
-  console.log(`    [Final] Max attempts reached, using final thinking pass`);
-  const finalResponse = await queryJsonWithThinking(images);
-  const finalInvoice = parseJsonToInvoice(finalResponse);
-
-  if (finalInvoice) {
-    console.log(`    [Final] Result: ${finalInvoice.invoice_number} | ${finalInvoice.invoice_date} | ${finalInvoice.total_amount} ${finalInvoice.currency}`);
-    return finalInvoice;
-  }
-
-  // Return empty invoice if all else fails
-  console.log(`    [Final] All parsing failed, returning empty`);
   return {
     invoice_number: '',
     invoice_date: '',
@@ -410,6 +340,79 @@ tap.test('setup: ensure Docker containers are running', async () => {
   console.log('\n[Setup] All containers ready!\n');
 });
 
+tap.test('setup: initialize smartagent orchestrator', async () => {
+  console.log('[Setup] Initializing SmartAi and DualAgentOrchestrator...');
+
+  smartAi = new SmartAi({
+    ollama: {
+      baseUrl: OLLAMA_URL,
+      model: MODEL,
+      defaultOptions: {
+        num_ctx: 32768,
+        temperature: 0.1,
+      },
+      defaultTimeout: 300000, // 5 minutes for vision tasks
+    },
+  });
+
+  await smartAi.start();
+
+  orchestrator = new DualAgentOrchestrator({
+    smartAiInstance: smartAi,
+    defaultProvider: 'ollama',
+    guardianPolicyPrompt: `You are a Guardian agent overseeing invoice extraction tasks.
+
+APPROVE all tool calls that:
+- Use the json.validate action to verify JSON output
+- Are reasonable attempts to complete the extraction task
+
+REJECT tool calls that:
+- Attempt to access external resources
+- Try to execute arbitrary code
+- Are clearly unrelated to invoice extraction`,
+    driverSystemMessage: `You are an AI assistant that extracts invoice data from images.
+
+Your task is to analyze invoice images and extract structured data.
+You have access to a json.validate tool to verify your JSON output.
+
+IMPORTANT: Always validate your JSON before completing the task.
+
+## Tool Usage Format
+When you need to validate JSON, output:
+
+<tool_call>
+  <tool>json</tool>
+  <action>validate</action>
+  <params>{"jsonString": "YOUR_JSON", "requiredFields": ["invoice_number", "invoice_date", "vendor_name", "currency", "net_amount", "vat_amount", "total_amount"]}</params>
+</tool_call>
+
+## Completion Format
+After validation passes, complete the task:
+
+<task_complete>
+{"invoice_number": "...", "invoice_date": "YYYY-MM-DD", ...}
+</task_complete>`,
+    maxIterations: 5,
+    maxConsecutiveRejections: 3,
+    onToken: (token, source) => {
+      if (source === 'driver') {
+        process.stdout.write(token);
+      }
+    },
+    onProgress: (event) => {
+      if (event.logLevel === 'error') {
+        console.error(event.logMessage);
+      }
+    },
+  });
+
+  // Register the JsonValidatorTool
+  orchestrator.registerTool(new JsonValidatorTool());
+
+  await orchestrator.start();
+  console.log('[Setup] Orchestrator initialized!\n');
+});
+
 tap.test('should have MiniCPM-V model loaded', async () => {
   const response = await fetch(`${OLLAMA_URL}/api/tags`);
   const data = await response.json();
@@ -418,7 +421,7 @@ tap.test('should have MiniCPM-V model loaded', async () => {
 });
 
 const testCases = findTestCases();
-console.log(`\nFound ${testCases.length} invoice test cases (MiniCPM-V)\n`);
+console.log(`\nFound ${testCases.length} invoice test cases (smartagent + MiniCPM-V)\n`);
 
 let passedCount = 0;
 let failedCount = 0;
@@ -455,6 +458,13 @@ for (const testCase of testCases) {
   });
 }
 
+tap.test('cleanup: stop orchestrator', async () => {
+  if (orchestrator) {
+    await orchestrator.stop();
+  }
+  console.log('[Cleanup] Orchestrator stopped');
+});
+
 tap.test('summary', async () => {
   const totalInvoices = testCases.length;
   const accuracy = totalInvoices > 0 ? (passedCount / totalInvoices) * 100 : 0;
@@ -462,9 +472,10 @@ tap.test('summary', async () => {
   const avgTimeSec = processingTimes.length > 0 ? totalTimeMs / processingTimes.length / 1000 : 0;
 
   console.log(`\n========================================`);
-  console.log(`   Invoice Extraction Summary (${MODEL})`);
+  console.log(`   Invoice Extraction Summary`);
+  console.log(`   (smartagent + ${MODEL})`);
   console.log(`========================================`);
-  console.log(`  Method:    Consensus (fast + thinking)`);
+  console.log(`  Method:    DualAgentOrchestrator with vision`);
   console.log(`  Passed:    ${passedCount}/${totalInvoices}`);
   console.log(`  Failed:    ${failedCount}/${totalInvoices}`);
   console.log(`  Accuracy:  ${accuracy.toFixed(1)}%`);

test/test.invoices.nanonets.ts

@@ -12,6 +12,8 @@ import * as path from 'path';
 import { execSync } from 'child_process';
 import * as os from 'os';
 import { ensureNanonetsOcr, ensureMiniCpm, isContainerRunning } from './helpers/docker.js';
+import { SmartAi } from '@push.rocks/smartai';
+import { DualAgentOrchestrator, JsonValidatorTool } from '@push.rocks/smartagent';
 
 const NANONETS_URL = 'http://localhost:8000/v1';
 const NANONETS_MODEL = 'nanonets/Nanonets-OCR2-3B';
@@ -19,8 +21,35 @@ const NANONETS_MODEL = 'nanonets/Nanonets-OCR2-3B';
 const OLLAMA_URL = 'http://localhost:11434';
 const EXTRACTION_MODEL = 'gpt-oss:20b';
 
-// Temp directory for storing markdown between stages
+// Persistent cache directory for storing markdown between runs
-const TEMP_MD_DIR = path.join(os.tmpdir(), 'nanonets-invoices-markdown');
+const MD_CACHE_DIR = path.join(process.cwd(), '.nogit/invoices-md');
+
+// SmartAi instance for Ollama with optimized settings
+const smartAi = new SmartAi({
+  ollama: {
+    baseUrl: OLLAMA_URL,
+    model: EXTRACTION_MODEL,
+    defaultOptions: {
+      num_ctx: 65536,    // 64K context for long invoices + reasoning chains
+      temperature: 0,    // Deterministic for JSON extraction
+      repeat_penalty: 1.3, // Penalty to prevent repetition loops
+      think: true,       // Enable thinking mode for GPT-OSS reasoning
+    },
+    defaultTimeout: 600000,  // 10 minute timeout for large documents
+  },
+});
+
+// DualAgentOrchestrator for structured task execution
+let orchestrator: DualAgentOrchestrator;
+
+interface ILineItem {
+  position: number;
+  product: string;
+  description: string;
+  quantity: number;
+  unit_price: number;
+  total_price: number;
+}
 
 interface IInvoice {
   invoice_number: string;
@@ -30,6 +59,7 @@ interface IInvoice {
   net_amount: number;
   vat_amount: number;
   total_amount: number;
+  line_items: ILineItem[];
 }
 
 interface IImageData {
@@ -54,34 +84,43 @@ 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"). Use common sense. Btw. an invoice number might start on INV* . Also be sure to not omit special chars like / - and sp on. They are part of the invoice number.
-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
+- line_items: Look in the TABLE(s) with columns like Pos, Product, Description, Quantity, Unit Price, Price
+
+RULES:
+1. Use common sense.
+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
+8. line_items: Array of items from the invoice table. Skip subtotal/total rows.
 
-Return ONLY this JSON format, no explanation:
+JSON format:
 {
-  "invoice_number": "INV-2024-001",
+  "invoice_number": "X",
-  "invoice_date": "2024-01-15",
+  "invoice_date": "YYYY-MM-DD",
-  "vendor_name": "Company Name",
+  "vendor_name": "X",
   "currency": "EUR",
-  "net_amount": 100.00,
+  "net_amount": 0,
-  "vat_amount": 19.00,
+  "vat_amount": 0,
-  "total_amount": 119.00
+  "total_amount": 0,
+  "line_items": [
+    {"position": 1, "product": "X", "description": "X", "quantity": 1, "unit_price": 0, "total_price": 0}
+  ]
 }
 
-INVOICE TEXT:
+Double check for valid JSON syntax. use the json validate tool.
+
 `;
 
 // Constants for smart batching
-const MAX_VISUAL_TOKENS = 28000;  // ~32K context minus prompt/output headroom
 const PATCH_SIZE = 14;  // Qwen2.5-VL uses 14x14 patches
 
 /**
@@ -294,7 +333,7 @@ function extractInvoiceNumber(s: string | undefined): string {
     const match = clean.match(pattern);
     if (match) return match[1];
   }
-  return clean.replace(/[^A-Z0-9-]/gi, '').trim() || clean;
+  return clean.replace(/[^A-Z0-9\/-]/gi, '').trim() || clean;
 }
 
 /**
@@ -325,16 +364,35 @@ function extractCurrency(s: string | undefined): string {
 }
 
 /**
- * Extract JSON from response
+ * Extract and normalize line items array
  */
-function extractJsonFromResponse(response: string): Record<string, unknown> | null {
+function extractLineItems(items: unknown): ILineItem[] {
-  let cleanResponse = response.replace(/<think>[\s\S]*?<\/think>/g, '').trim();
+  if (!Array.isArray(items)) return [];
-  const codeBlockMatch = cleanResponse.match(/```(?:json)?\s*([\s\S]*?)```/);
+  return items.map((item: Record<string, unknown>, index: number) => ({
-  const jsonStr = codeBlockMatch ? codeBlockMatch[1].trim() : cleanResponse;
+    position: typeof item.position === 'number' ? item.position : index + 1,
+    product: String(item.product || '').trim(),
+    description: String(item.description || '').trim(),
+    quantity: parseAmount(item.quantity as string | number) || 1,
+    unit_price: parseAmount(item.unit_price as string | number),
+    total_price: parseAmount(item.total_price as string | number),
+  }));
+}
+
+/**
+ * Try to extract valid JSON from a response string
+ */
+function tryExtractJson(response: string): Record<string, unknown> | null {
+  // Remove thinking tags
+  let clean = response.replace(/<think>[\s\S]*?<\/think>/g, '').trim();
+
+  // Try code block
+  const codeBlockMatch = clean.match(/```(?:json)?\s*([\s\S]*?)```/);
+  const jsonStr = codeBlockMatch ? codeBlockMatch[1].trim() : clean;
 
   try {
     return JSON.parse(jsonStr);
   } catch {
+    // Try to find JSON object
     const jsonMatch = jsonStr.match(/\{[\s\S]*\}/);
     if (jsonMatch) {
       try {
@@ -348,111 +406,93 @@ function extractJsonFromResponse(response: string): Record<string, unknown> | nu
 }
 
 /**
- * Parse JSON response into IInvoice
+ * Extract invoice from markdown using smartagent DualAgentOrchestrator
- */
+ * Validates JSON and retries if invalid
-function parseJsonToInvoice(response: string): IInvoice | null {
-  const parsed = extractJsonFromResponse(response);
-  if (!parsed) return null;
-
-  return {
-    invoice_number: extractInvoiceNumber(String(parsed.invoice_number || '')),
-    invoice_date: extractDate(String(parsed.invoice_date || '')),
-    vendor_name: String(parsed.vendor_name || '').replace(/\*\*/g, '').replace(/`/g, '').trim(),
-    currency: extractCurrency(String(parsed.currency || '')),
-    net_amount: parseAmount(parsed.net_amount as string | number),
-    vat_amount: parseAmount(parsed.vat_amount as string | number),
-    total_amount: parseAmount(parsed.total_amount as string | number),
-  };
-}
-
-/**
- * Extract invoice from markdown using GPT-OSS 20B (streaming)
  */
 async function extractInvoiceFromMarkdown(markdown: string, queryId: string): Promise<IInvoice | null> {
   const startTime = Date.now();
-  const fullPrompt = JSON_EXTRACTION_PROMPT + markdown;
+  const maxRetries = 2;
 
-  // Log exact prompt
+  console.log(`      [${queryId}] Invoice: ${markdown.length} chars`);
-  console.log(`\n      [${queryId}] ===== PROMPT =====`);
-  console.log(fullPrompt);
-  console.log(`      [${queryId}] ===== END PROMPT (${fullPrompt.length} chars) =====\n`);
 
-  const response = await fetch(`${OLLAMA_URL}/api/chat`, {
+  // Build the extraction task with document context
-    method: 'POST',
+  const taskPrompt = `Extract the invoice data from this document and output ONLY the JSON:
-    headers: { 'Content-Type': 'application/json' },
-    body: JSON.stringify({
-      model: EXTRACTION_MODEL,
-      messages: [
-        { role: 'user', content: 'Hi there, how are you?' },
-        { role: 'assistant', content: 'Good, how can I help you today?' },
-        { role: 'user', content: fullPrompt },
-      ],
-      stream: true,
-    }),
-    signal: AbortSignal.timeout(600000), // 10 minute timeout for large documents
-  });
 
-  if (!response.ok) {
+${markdown}
-    const elapsed = ((Date.now() - startTime) / 1000).toFixed(1);
-    console.log(`      [${queryId}] ERROR: ${response.status} (${elapsed}s)`);
-    throw new Error(`Ollama API error: ${response.status}`);
-  }
 
-  // Stream the response
+${JSON_EXTRACTION_PROMPT}`;
-  let content = '';
-  let thinkingContent = '';
-  let thinkingStarted = false;
-  let outputStarted = false;
-  const reader = response.body!.getReader();
-  const decoder = new TextDecoder();
 
   try {
-    while (true) {
+    let result = await orchestrator.run(taskPrompt);
-      const { done, value } = await reader.read();
+    let elapsed = ((Date.now() - startTime) / 1000).toFixed(1);
-      if (done) break;
+    console.log(`      [${queryId}] Status: ${result.status}, Iterations: ${result.iterations} (${elapsed}s)`);
 
-      const chunk = decoder.decode(value, { stream: true });
+    // Try to parse JSON from result
+    let jsonData: Record<string, unknown> | null = null;
+    let responseText = result.result || '';
 
-      // Each line is a JSON object
+    if (result.success && responseText) {
-      for (const line of chunk.split('\n').filter(l => l.trim())) {
+      jsonData = tryExtractJson(responseText);
-        try {
-          const json = JSON.parse(line);
-
-          // Stream thinking tokens
-          const thinking = json.message?.thinking || '';
-          if (thinking) {
-            if (!thinkingStarted) {
-              process.stdout.write(`      [${queryId}] THINKING: `);
-              thinkingStarted = true;
-            }
-            process.stdout.write(thinking);
-            thinkingContent += thinking;
     }
 
-          // Stream content tokens
+    // Fallback: try parsing from history
-          const token = json.message?.content || '';
+    if (!jsonData && result.history?.length > 0) {
-          if (token) {
+      const lastMessage = result.history[result.history.length - 1];
-            if (!outputStarted) {
+      if (lastMessage?.content) {
-              if (thinkingStarted) process.stdout.write('\n');
+        responseText = lastMessage.content;
-              process.stdout.write(`      [${queryId}] OUTPUT: `);
+        jsonData = tryExtractJson(responseText);
-              outputStarted = true;
       }
-            process.stdout.write(token);
-            content += token;
-          }
-        } catch {
-          // Ignore parse errors for partial chunks
-        }
-      }
-    }
-  } finally {
-    if (thinkingStarted || outputStarted) process.stdout.write('\n');
     }
 
+    // If JSON is invalid, retry with correction request
+    let retries = 0;
+    while (!jsonData && retries < maxRetries) {
+      retries++;
+      console.log(`      [${queryId}] Invalid JSON, requesting correction (retry ${retries}/${maxRetries})...`);
+
+      result = await orchestrator.continueTask(
+        `Your response was not valid JSON. Please output ONLY the JSON object with no markdown, no explanation, no thinking tags. Just the raw JSON starting with { and ending with }. Format:
+{"invoice_number":"X","invoice_date":"YYYY-MM-DD","vendor_name":"X","currency":"EUR","net_amount":0,"vat_amount":0,"total_amount":0}`
+      );
+
+      elapsed = ((Date.now() - startTime) / 1000).toFixed(1);
+      console.log(`      [${queryId}] Retry ${retries}: ${result.status} (${elapsed}s)`);
+
+      responseText = result.result || '';
+      if (responseText) {
+        jsonData = tryExtractJson(responseText);
+      }
+
+      if (!jsonData && result.history?.length > 0) {
+        const lastMessage = result.history[result.history.length - 1];
+        if (lastMessage?.content) {
+          responseText = lastMessage.content;
+          jsonData = tryExtractJson(responseText);
+        }
+      }
+    }
+
+    if (!jsonData) {
+      console.log(`      [${queryId}] Failed to get valid JSON after ${retries} retries`);
+      return null;
+    }
+
+    console.log(`      [${queryId}] Valid JSON extracted`);
+    return {
+      invoice_number: extractInvoiceNumber(String(jsonData.invoice_number || '')),
+      invoice_date: extractDate(String(jsonData.invoice_date || '')),
+      vendor_name: String(jsonData.vendor_name || '').replace(/\*\*/g, '').replace(/`/g, '').trim(),
+      currency: extractCurrency(String(jsonData.currency || '')),
+      net_amount: parseAmount(jsonData.net_amount as string | number),
+      vat_amount: parseAmount(jsonData.vat_amount as string | number),
+      total_amount: parseAmount(jsonData.total_amount as string | number),
+      line_items: extractLineItems(jsonData.line_items),
+    };
+  } catch (error) {
     const elapsed = ((Date.now() - startTime) / 1000).toFixed(1);
-  console.log(`      [${queryId}] Done: ${thinkingContent.length} thinking chars, ${content.length} output chars (${elapsed}s)`);
+    console.log(`      [${queryId}] ERROR: ${error} (${elapsed}s)`);
-
+    throw error;
-  return parseJsonToInvoice(content);
+  }
 }
 
 /**
@@ -470,6 +510,7 @@ async function extractInvoice(markdown: string, docName: string): Promise<IInvoi
       net_amount: 0,
       vat_amount: 0,
       total_amount: 0,
+      line_items: [],
     };
   }
   console.log(`    [${docName}] Extracted: ${invoice.invoice_number}`);
@@ -561,23 +602,45 @@ function findTestCases(): ITestCase[] {
 const testCases = findTestCases();
 console.log(`\nFound ${testCases.length} invoice test cases\n`);
 
-// Ensure temp directory exists
+// Ensure cache directory exists
-if (!fs.existsSync(TEMP_MD_DIR)) {
+if (!fs.existsSync(MD_CACHE_DIR)) {
-  fs.mkdirSync(TEMP_MD_DIR, { recursive: true });
+  fs.mkdirSync(MD_CACHE_DIR, { recursive: true });
 }
 
 // -------- STAGE 1: OCR with Nanonets --------
 
-tap.test('Stage 1: Setup Nanonets', async () => {
+tap.test('Stage 1: Convert invoices to markdown (with caching)', async () => {
   console.log('\n========== STAGE 1: Nanonets OCR ==========\n');
-  const ok = await ensureNanonetsOcr();
-  expect(ok).toBeTrue();
-});
 
-tap.test('Stage 1: Convert all invoices to markdown', async () => {
+  // Check which invoices need OCR conversion
-  console.log('\n  Converting all invoice PDFs to markdown with Nanonets-OCR-s...\n');
+  const needsConversion: ITestCase[] = [];
+  let cachedCount = 0;
 
   for (const tc of testCases) {
+    const mdPath = path.join(MD_CACHE_DIR, `${tc.name}.md`);
+    if (fs.existsSync(mdPath)) {
+      cachedCount++;
+      tc.markdownPath = mdPath;
+      console.log(`  [CACHED] ${tc.name} - using cached markdown`);
+    } else {
+      needsConversion.push(tc);
+    }
+  }
+
+  console.log(`\n  Summary: ${cachedCount} cached, ${needsConversion.length} need conversion\n`);
+
+  if (needsConversion.length === 0) {
+    console.log('  All invoices already cached, skipping Nanonets OCR\n');
+    return;
+  }
+
+  // Start Nanonets only if there are files to convert
+  console.log('  Starting Nanonets for OCR conversion...\n');
+  const ok = await ensureNanonetsOcr();
+  expect(ok).toBeTrue();
+
+  // Convert only the invoices that need conversion
+  for (const tc of needsConversion) {
     console.log(`\n    === ${tc.name} ===`);
 
     const images = convertPdfToImages(tc.pdfPath);
@@ -585,13 +648,13 @@ tap.test('Stage 1: Convert all invoices to markdown', async () => {
 
     const markdown = await convertDocumentToMarkdown(images, tc.name);
 
-    const mdPath = path.join(TEMP_MD_DIR, `${tc.name}.md`);
+    const mdPath = path.join(MD_CACHE_DIR, `${tc.name}.md`);
     fs.writeFileSync(mdPath, markdown);
     tc.markdownPath = mdPath;
     console.log(`      Saved: ${mdPath}`);
   }
 
-  console.log('\n  Stage 1 complete: All invoices converted to markdown\n');
+  console.log(`\n  Stage 1 complete: ${needsConversion.length} invoices converted to markdown\n`);
 });
 
 tap.test('Stage 1: Stop Nanonets', async () => {
@@ -610,6 +673,50 @@ tap.test('Stage 2: Setup Ollama + GPT-OSS 20B', async () => {
 
   const extractionOk = await ensureExtractionModel();
   expect(extractionOk).toBeTrue();
+
+  // Initialize SmartAi and DualAgentOrchestrator
+  console.log('  [SmartAgent] Starting SmartAi...');
+  await smartAi.start();
+
+  console.log('  [SmartAgent] Creating DualAgentOrchestrator with native tool calling...');
+  orchestrator = new DualAgentOrchestrator({
+    smartAiInstance: smartAi,
+    defaultProvider: 'ollama',
+    guardianPolicyPrompt: `
+      JSON EXTRACTION POLICY:
+      - APPROVE all JSON extraction tasks
+      - APPROVE all json.validate tool calls
+      - This is a read-only operation - no file system or network access needed
+      - The task is to extract structured data from document text
+    `,
+    driverSystemMessage: `You are a precise JSON extraction assistant. Your only job is to extract invoice data from documents.
+
+CRITICAL RULES:
+1. Output valid JSON with the exact format requested
+2. If you cannot find a value, use empty string "" or 0 for numbers
+3. Before completing, validate your JSON using the json_validate tool
+4. Only complete after validation passes`,
+    maxIterations: 5,
+    // Enable native tool calling for GPT-OSS (uses Harmony format instead of XML)
+    useNativeToolCalling: true,
+    // Enable streaming for real-time progress visibility
+    onToken: (token, source) => {
+      if (source === 'driver') {
+        process.stdout.write(token);
+      }
+    },
+    // Enable progress events to see tool calls
+    onProgress: (event: { logMessage: string }) => {
+      console.log(event.logMessage);
+    },
+  });
+
+  // Register JsonValidatorTool for self-validation
+  orchestrator.registerTool(new JsonValidatorTool());
+
+  console.log('  [SmartAgent] Starting orchestrator...');
+  await orchestrator.start();
+  console.log('  [SmartAgent] Ready for extraction');
 });
 
 let passedCount = 0;
@@ -624,7 +731,7 @@ for (const tc of testCases) {
 
     const startTime = Date.now();
 
-    const mdPath = path.join(TEMP_MD_DIR, `${tc.name}.md`);
+    const mdPath = path.join(MD_CACHE_DIR, `${tc.name}.md`);
     if (!fs.existsSync(mdPath)) {
       throw new Error(`Markdown not found: ${mdPath}. Run Stage 1 first.`);
     }
@@ -636,7 +743,7 @@ for (const tc of testCases) {
     const elapsedMs = Date.now() - startTime;
     processingTimes.push(elapsedMs);
 
-    console.log(`    Extracted: ${extracted.invoice_number} | ${extracted.invoice_date} | ${extracted.total_amount} ${extracted.currency}`);
+    console.log(`    Extracted: ${extracted.invoice_number} | ${extracted.invoice_date} | ${extracted.total_amount} ${extracted.currency} | ${extracted.line_items.length} items`);
 
     const result = compareInvoice(extracted, expected);
 
@@ -654,6 +761,14 @@ for (const tc of testCases) {
 }
 
 tap.test('Summary', async () => {
+  // Cleanup orchestrator and SmartAi
+  if (orchestrator) {
+    console.log('\n  [SmartAgent] Stopping orchestrator...');
+    await orchestrator.stop();
+  }
+  console.log('  [SmartAgent] Stopping SmartAi...');
+  await smartAi.stop();
+
   const totalInvoices = testCases.length;
   const accuracy = totalInvoices > 0 ? (passedCount / totalInvoices) * 100 : 0;
   const totalTimeMs = processingTimes.reduce((a, b) => a + b, 0);
@@ -663,7 +778,7 @@ tap.test('Summary', async () => {
   console.log(`   Invoice Summary (Nanonets + GPT-OSS 20B)`);
   console.log(`========================================`);
   console.log(`  Stage 1:   Nanonets-OCR-s (doc -> md)`);
-  console.log(`  Stage 2:   GPT-OSS 20B (md -> JSON)`);
+  console.log(`  Stage 2:   GPT-OSS 20B + SmartAgent (md -> JSON)`);
   console.log(`  Passed:    ${passedCount}/${totalInvoices}`);
   console.log(`  Failed:    ${failedCount}/${totalInvoices}`);
   console.log(`  Accuracy:  ${accuracy.toFixed(1)}%`);
@@ -671,14 +786,7 @@ tap.test('Summary', async () => {
   console.log(`  Total time:   ${(totalTimeMs / 1000).toFixed(1)}s`);
   console.log(`  Avg per inv:  ${avgTimeSec.toFixed(1)}s`);
   console.log(`========================================\n`);
-
+  console.log(`  Cache location: ${MD_CACHE_DIR}\n`);
-  // Cleanup temp files
-  try {
-    fs.rmSync(TEMP_MD_DIR, { recursive: true, force: true });
-    console.log(`  Cleaned up temp directory: ${TEMP_MD_DIR}\n`);
-  } catch {
-    // Ignore
-  }
 });
 
 export default tap.start();