docs

ContextIQ Documentation

Welcome to the ContextIQ documentation! This guide will help you understand, deploy, and develop with ContextIQ.

Table of Contents

Getting Started

• Main README - Project overview and quick start
• Architecture Overview - System design and components
• API Usage Guide - How to use the ContextIQ APIs

Deployment & Operations

• Deployment Guide - Local, Docker, and production deployment
• Database Migrations - Managing schema changes with Alembic
• Authentication Guide - JWT tokens, API keys, and permissions

Development

• Development Guide - Setting up your development environment
• System Architecture - Detailed architecture documentation
• Data Models - Database schemas and models

Technical Deep Dives

• Processing Layer Guide - Core processing engines (extraction, consolidation, embedding, revision tracking)
• Messaging System Guide - RabbitMQ messaging system with queues, publishers, and consumers
• Memory Lifecycle Guide - Complete journey from sessions to memories (extraction and consolidation)
• Embeddings Guide - Text embeddings with OpenAI (models, configuration, optimization)
• Vector Search Guide - Qdrant vector database and similarity search

Research & Background

• Agent Engine Memory Bank Research - Research notes on Google's approach
• Context Engineering Paper Summary - Summary of Google's Sessions & Memory whitepaper
• Anthropic Context Engineering - Anthropic's perspective on context engineering

Quick Links by Use Case

I want to...

...get started quickly

1. Read the Main README Quick Start section
2. Follow the Deployment Guide for local setup
3. Review API Usage Guide for first API calls

...deploy to production

1. Read the Deployment Guide Production section
2. Configure Authentication properly
3. Set up Database Migrations workflow

...contribute code

1. Follow the Development Guide setup
2. Understand the Architecture
3. Review code quality standards in Development Guide

...integrate with my AI agent

1. Review API Usage Guide for authentication
2. See Sessions API examples
3. See Memory API examples

...understand the system design

1. Read Architecture Overview
2. Review System Architecture details
3. Study Data Models

...understand embeddings and vector search

1. Read Embeddings Guide for text embedding details
2. Read Vector Search Guide for similarity search
3. Review API Usage Guide for memory search examples

...manage database changes

1. Read Database Migrations Guide
2. Learn migration commands and patterns
3. Understand production migration strategies

...configure authentication

1. Read Authentication Guide
2. Generate JWT secrets and API keys
3. Configure middleware in your services

...understand how messaging works

1. Read Messaging System Guide for RabbitMQ details
2. Learn about queue patterns and message flows
3. Review publisher and consumer examples

...understand how memories are created

1. Read Memory Lifecycle Guide for end-to-end flow
2. Learn about extraction with LLM (Anthropic Claude)
3. Understand consolidation and deduplication
4. Review embedding generation and vector storage

...understand the processing layer

1. Read Processing Layer Guide for architecture details
2. Learn about the four core engines and their interactions
3. Understand how processing fits between services and storage
4. Review configuration and optimization strategies

Documentation Structure

Core Documentation

Files in the docs/ root directory cover essential topics:

• Architecture, API usage, deployment, development
• Authentication, database migrations
• Research and background materials

Architecture Details

The docs/architecture/ directory contains detailed technical documentation:

• System architecture diagrams and explanations
• Data models and database schemas
• Design decisions and rationale

PR Summaries

The docs/pr_summaries/ directory contains:

• Summaries of major pull requests
• Implementation notes
• Migration guides for breaking changes

Contributing to Documentation

When updating documentation:

1. Keep it up to date: Update docs when code changes
2. Cross-reference: Link to related documentation
3. Use examples: Show code examples where relevant
4. Be comprehensive: Cover common use cases and edge cases
5. Follow markdown best practices: Use headers, code blocks, lists

Documentation Standards

• Use clear, concise language
• Include a table of contents for documents > 200 lines
• Use code blocks with language hints (python, bash)
• Link to other docs using relative paths
• Keep line length reasonable (100-120 characters)
• Use meaningful heading hierarchy (# → ## → ###)

Getting Help

If you can't find what you're looking for:

1. Search existing documentation
2. Check GitHub Issues
3. Ask in GitHub Discussions
4. Review the code - it's well-commented!

Documentation Roadmap

Planned documentation additions:

• Performance tuning guide
• Monitoring and observability setup guide
• Troubleshooting guide with common issues
• Integration guides for popular frameworks (LangGraph, CrewAI, etc.)
• API client SDK documentation (Python, TypeScript)
• Advanced deployment patterns (K8s, multi-region, etc.)
• Security best practices guide
• Backup and disaster recovery guide

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Last Updated: December 2024

For questions or suggestions about documentation, please open an issue on GitHub.