Skip to content

index.md

Latest commit

 

History

History
198 lines (144 loc) · 5.12 KB

index.md

File metadata and controls

198 lines (144 loc) · 5.12 KB

API Documentation

This section contains comprehensive documentation for the RAG Modulo API and its simplified architecture.

Search API

Core Components

  • Search API - Complete search API documentation with automatic pipeline resolution
  • Search Schemas - Data structures for search requests and responses

Key Features

Simplified Pipeline Resolution: The search API now automatically handles pipeline selection based on user context, eliminating client-side pipeline management complexity.

Breaking Changes from Legacy API:

  • Removed pipeline_id from SearchInput schema
  • Added automatic pipeline resolution in SearchService
  • Simplified CLI interface without pipeline parameters
  • Enhanced error handling for configuration issues

Service Architecture

Backend Services

Development Documentation

Development-specific documentation has been moved to:

Migration Guide

From Legacy API

Before (Legacy):

# Client had to manage pipeline selection
pipeline_id = get_user_pipeline(user_id, collection_id)
search_input = SearchInput(
    question="What is ML?",
    collection_id=collection_id,
    user_id=user_id,
    pipeline_id=pipeline_id  # Client-managed
)

After (Current):

# Backend handles pipeline selection automatically
search_input = SearchInput(
    question="What is ML?",
    collection_id=collection_id,
    user_id=user_id
    # No pipeline_id needed
)

Schema Changes

  1. SearchInput Schema:

    • ✅ Removed pipeline_id field
    • ✅ Added extra="forbid" validation
    • ✅ Simplified field requirements

  2. Service Layer:

    • ✅ Added automatic pipeline resolution
    • ✅ Enhanced error handling
    • ✅ Improved user experience

  3. CLI Interface:

    • ✅ Removed pipeline parameters
    • ✅ Simplified command structure
    • ✅ Automatic configuration

Testing

Test Coverage

  • Unit Tests: Schema validation, service logic, pipeline resolution
  • Integration Tests: End-to-end search flow, database integration
  • API Tests: Endpoint validation, error handling

Running Tests

# Schema and service tests
pytest backend/tests/unit/test_search_service_pipeline_resolution.py

# Integration tests
pytest backend/tests/integration/test_search_integration.py

# API endpoint tests
pytest backend/tests/api/test_search_endpoints.py

Performance Considerations

Automatic Pipeline Creation

  • First search for new users triggers pipeline creation
  • Pipeline creation includes LLM provider validation
  • Default configurations applied automatically
  • All operations logged for audit

Caching Strategy

  • Response caching based on search input hash
  • Pipeline resolution results cached per user
  • Configurable cache TTL (default: 1 hour)

Security

Access Control

  • User authentication required for all operations
  • Collection access validation
  • Pipeline isolation between users
  • Audit logging for all search activities

Input Validation

  • Strict schema validation with extra="forbid"
  • Query length and content validation
  • Configuration parameter range checking
  • SQL injection prevention

Error Handling

Common Error Scenarios

  1. Configuration Errors:

    • No LLM provider configured
    • Invalid provider credentials
    • Missing pipeline configuration

  2. Access Errors:

    • Collection not found or access denied
    • User authentication failures
    • Rate limiting violations

  3. Validation Errors:

    • Invalid search input format
    • Parameter out of range
    • Malformed configuration metadata

Error Response Format

{
    "detail": "Error description",
    "error_code": "STANDARDIZED_ERROR_CODE",
    "timestamp": "2023-12-07T10:30:00Z",
    "request_id": "req-unique-id",
    "user_id": "user-uuid-if-available"
}

Future Enhancements

Planned Improvements

  1. Enhanced Pipeline Resolution:

    • Context-aware pipeline selection
    • Collection-specific optimizations
    • A/B testing support

  2. Advanced Search Features:

    • Multi-collection search
    • Streaming responses
    • Real-time suggestions

  3. Performance Optimizations:

    • Parallel processing
    • Predictive caching
    • Resource optimization

  4. Analytics and Monitoring:

    • Search quality metrics
    • Performance dashboards
    • Usage analytics

Support

For additional help:

Last Updated: December 2023 API Version: 2.0 (Simplified Pipeline Resolution)