TypeAgent
Build powerful structured RAG applications with AI-powered knowledge extraction, incremental indexing, and natural language query processing.
Key Features
Structured RAG
AI-powered extraction of entities, topics, actions, and relationships from conversations
Dual Storage
Choose between in-memory or SQLite persistence with identical APIs
Multi-Index Architecture
Six specialized indexes for semantic search, temporal queries, and knowledge retrieval
Natural Language Queries
Ask questions in plain English and get accurate answers from your indexed data
Quick Start
Get up and running with TypeAgent in minutes.Full Quickstart Guide
Follow our complete quickstart tutorial with working examples
Core Concepts
Understand the architecture and design principles behind TypeAgent.Architecture Overview
Learn about the four-layer architecture and data flow
Knowledge Extraction
Understand how AI models extract structured knowledge
Indexing Strategy
Explore the six specialized indexes and their purposes
Structured RAG
Discover how structured knowledge improves retrieval quality
Integration Guides
Extend TypeAgent with email, podcasts, and custom data sources.Email Integration
Ingest and query email conversations
Podcast Processing
Index podcast transcripts and metadata
Configuration
Customize extraction and indexing settings
API Reference
Explore the complete TypeAgent API.create_conversation()
Factory function for creating conversation objects
ConversationBase
Core conversation class with query and indexing methods
Messages
Message types and metadata structures
Storage Providers
Memory and SQLite storage implementations
Community & Support
GitHub Repository
Star us on GitHub and contribute to the project
Report Issues
Found a bug? Let us know