Add custom prompt generator Lambda function support

Author: Bob Strahan

README.md

@@ -33,6 +33,7 @@ White-glove customization, deployment, and integration support for production us
 - **Modular, pluggable patterns**: Pre-built processing patterns using state-of-the-art models and AWS services
 - **Advanced Classification**: Support for page-level and holistic document packet classification
 - **Few Shot Example Support**: Improve accuracy through example-based prompting
+- **Custom Business Logic Integration**: Inject custom prompt generation logic via Lambda functions for specialized document processing
 - **High Throughput Processing**: Handles large volumes of documents through intelligent queuing
 - **Built-in Resilience**: Comprehensive error handling, retries, and throttling management
 - **Cost Optimization**: Pay-per-use pricing model with built-in controls

docs/extraction.md

@@ -226,6 +226,212 @@ extraction:
 4. **Handle OCR Limitations**: Use images to fill gaps where OCR may miss visual-only content
 5. **Consider Document Types**: Different document types benefit from different image placement strategies
 
+## Custom Prompt Generator Lambda Functions
+
+The extraction service supports custom Lambda functions for advanced prompt generation, allowing you to inject custom business logic into the extraction process while leveraging the existing IDP infrastructure.
+
+### Overview
+
+Custom prompt generator Lambda functions enable:
+
+- **Document type-specific processing** with specialized extraction logic
+- **Integration with external systems** for dynamic configuration retrieval
+- **Conditional processing** based on document content analysis
+- **Regulatory compliance** with industry-specific prompt requirements
+- **Multi-tenant customization** for different customer requirements
+
+### Configuration
+
+Add the `custom_prompt_lambda_arn` field to your extraction configuration:
+
+```yaml
+extraction:
+  model: us.amazon.nova-pro-v1:0
+  temperature: 0.0
+  system_prompt: "Your default system prompt..."
+  task_prompt: "Your default task prompt..."
+  # Custom Lambda function for prompt generation
+  custom_prompt_lambda_arn: "arn:aws:lambda:us-east-1:123456789012:function:GENAIIDP-my-extractor"
+```
+
+**Lambda Function Requirements:**
+- Function name must start with `GENAIIDP-` (required for IAM permissions)
+- Must return valid JSON with `system_prompt` and `task_prompt_content` fields
+- Available in Patterns 2 and 3 only
+
+### Lambda Interface
+
+Your Lambda function receives a comprehensive payload with all context needed for prompt generation:
+
+**Input Payload:**
+```json
+{
+  "config": {
+    "extraction": {...},
+    "classes": [...],
+    "assessment": {...}
+  },
+  "prompt_placeholders": {
+    "DOCUMENT_TEXT": "Full OCR extracted text from all pages",
+    "DOCUMENT_CLASS": "Invoice",
+    "ATTRIBUTE_NAMES_AND_DESCRIPTIONS": "Invoice Number\t[Unique identifier]...",
+    "DOCUMENT_IMAGE": ["s3://bucket/document/pages/1/image.jpg", "s3://bucket/document/pages/2/image.jpg"]
+  },
+  "default_task_prompt_content": [
+    {"text": "Resolved default task prompt with placeholders replaced"},
+    {"image_uri": "<image_placeholder>"}, 
+    {"cachePoint": true}
+  ],
+  "serialized_document": {
+    "id": "document-123",
+    "input_bucket": "my-bucket", 
+    "input_key": "documents/invoice.pdf",
+    "pages": {...},
+    "sections": [...],
+    "status": "EXTRACTING"
+  }
+}
+```
+
+**Required Output:**
+```json
+{
+  "system_prompt": "Your custom system prompt based on document analysis",
+  "task_prompt_content": [
+    {"text": "Your custom task prompt with business logic applied"},
+    {"image_uri": "<preserved_placeholder>"},
+    {"cachePoint": true}
+  ]
+}
+```
+
+### Implementation Examples
+
+**Document Type Detection:**
+```python
+def lambda_handler(event, context):
+    placeholders = event.get('prompt_placeholders', {})
+    document_class = placeholders.get('DOCUMENT_CLASS', '')
+    
+    if 'bank statement' in document_class.lower():
+        return generate_banking_prompts(event)
+    elif 'invoice' in document_class.lower():
+        return generate_invoice_prompts(event)
+    else:
+        return use_default_prompts(event)
+```
+
+**Content-Based Analysis:**
+```python
+def lambda_handler(event, context):
+    placeholders = event.get('prompt_placeholders', {})
+    document_text = placeholders.get('DOCUMENT_TEXT', '')
+    image_uris = placeholders.get('DOCUMENT_IMAGE', [])
+    
+    # Multi-page processing logic
+    if len(image_uris) > 3:
+        return generate_multi_page_prompts(event)
+    
+    # International document detection
+    if any(term in document_text.lower() for term in ['vat', 'gst', 'euro']):
+        return generate_international_prompts(event)
+    
+    return use_standard_prompts(event)
+```
+
+**External System Integration:**
+```python
+import boto3
+
+def lambda_handler(event, context):
+    document = event.get('serialized_document', {})
+    customer_id = document.get('customer_id')  # Custom field
+    
+    # Retrieve customer-specific rules
+    dynamodb = boto3.resource('dynamodb')
+    table = dynamodb.Table('customer-extraction-rules')
+    
+    customer_rules = table.get_item(Key={'customer_id': customer_id}).get('Item', {})
+    
+    # Apply customer-specific customization
+    if customer_rules.get('enhanced_validation'):
+        return generate_enhanced_validation_prompts(event)
+    
+    return use_standard_prompts(event)
+```
+
+### Error Handling
+
+The system implements **fail-fast error handling** for custom Lambda functions:
+
+- **Lambda invocation failures** cause extraction to fail with detailed error messages
+- **Invalid response format** results in extraction failure with validation errors
+- **Function errors** propagate with Lambda error details
+- **Timeout scenarios** fail with timeout information
+
+**Example Error Messages:**
+```
+Failed to invoke custom prompt Lambda arn:aws:lambda:...: Connection timeout
+Custom prompt Lambda failed: KeyError: 'system_prompt' not found in response
+Custom prompt Lambda returned invalid response format: expected dict, got str
+```
+
+### Performance Considerations
+
+- **Lambda Overhead**: Adds latency from Lambda cold starts and execution time
+- **JSON Serialization**: Optimized with URI-based image handling to minimize payload size
+- **Efficient Interface**: Avoids sending large image bytes, uses S3 URIs instead
+- **Monitoring**: Comprehensive logging for performance analysis and troubleshooting
+
+### Deployment and Testing
+
+**1. Demo Lambda Function:**
+Deploy the provided demo Lambda for testing:
+```bash
+cd notebooks/examples/demo-lambda
+sam deploy --guided
+```
+
+**2. Interactive Testing:**
+Use the demo notebook for hands-on experimentation:
+```bash
+jupyter notebook notebooks/examples/step3_extraction_with_custom_lambda.ipynb
+```
+
+**3. Production Deployment:**
+Create your production Lambda with business-specific logic and deploy with appropriate IAM permissions.
+
+### Use Cases
+
+**Financial Services:**
+- Regulatory compliance prompts for different financial products
+- Multi-currency transaction handling with exchange rate awareness
+- Customer-specific formatting for different banking institutions
+
+**Healthcare:**
+- HIPAA compliance with privacy-focused prompts
+- Medical terminology enhancement for clinical documents
+- Provider-specific templates for different healthcare systems
+
+**Legal:**
+- Jurisdiction-specific legal language processing
+- Contract type specialization (NDAs, service agreements, etc.)
+- Compliance requirements for regulatory documents
+
+**Insurance:**
+- Policy type customization for different insurance products
+- Claims processing with adjuster-specific requirements
+- Risk assessment integration with underwriting systems
+
+### Security and Compliance
+
+- **Scoped IAM Permissions**: Only Lambda functions with `GENAIIDP-*` naming can be invoked
+- **Audit Trail**: All Lambda invocations are logged for security monitoring
+- **Input Validation**: Lambda response structure is validated before use
+- **Fail-Safe Operation**: Lambda failures cause extraction to fail rather than continue with potentially incorrect prompts
+
+For complete examples and deployment instructions, see `notebooks/examples/demo-lambda/README.md`.
+
 ## Using CachePoint for Extraction
 
 CachePoint is a feature of select Bedrock models that caches partial computations to improve performance and reduce costs. When used with extraction, it provides: