Ada Brain API Docs
Welcome to Ada! Your personal AI assistant that runs entirely on your hardware.
First time here? Check out the visual introduction 🌱 for a gentle tour!
Ready to dive in? Start here:
Zero to Ada: Zero to Ada - Fastest path from nothing to working Ada (< 10 minutes)
Customize: Getting Started from Scratch - Make Ada truly yours
Explore: Specialist System - Extend Ada’s capabilities
Multiple setup options: Use Nix (any Linux/macOS), local Python 3.13, or Docker. Choose what works for you!
Getting Started
Hardware Setup
- Hardware & GPU Guide
- Ada on Single-Board Computers (SBCs)
- Why SBCs for Ada?
- Best SBCs for Ada (2025)
- Other Notable Options
- Recommended Configurations
- Performance Comparison
- Setup Tips
- Model Recommendations for SBCs
- Power Consumption & Cost
- NPU Acceleration Status
- Real-World Use Cases
- Troubleshooting
- Future: Add-On Options
- Community Projects
- Buying Guide: What to Prioritize
- Conclusion
Core Architecture
- Architecture
- System Overview
- Request Flow
- Specialist System Architecture
- Context Caching System (v2.1)
- RAG System Components
- Bidirectional Specialist Flow
- Testing Infrastructure
- Contextual Router Architecture (v2.7+)
- Multi-Timescale Cache Architecture (v2.1+)
- Parallel Optimization Architecture (v2.9+)
- Data Flow: Conversation Turn (Optimized v2.9)
- Deployment Architecture
- Resources
- Data Model Reference
- Streaming
- Memory
- Biomimetic Features
- Memory Augmentation Research
- Token Budget Monitoring
Interfaces & Adapters
Specialist System
- Specialist System
- Build Your First Specialist
- What You’ll Build
- Prerequisites
- Step 1: Understand the Specialist Protocol
- Step 2: Create the File
- Step 3: Write the Specialist
- Step 4: Add API Key to Environment
- Step 5: Restart Services
- Step 6: Test It
- Step 7: Enable Bidirectional Mode (Advanced)
- Understanding the Code
- Common Patterns
- Testing Your Specialist
- Debugging Tips
- Next Steps
- Need Help?
- Bidirectional Specialist System
- Specialist RAG Documentation System
- Web Search Specialist
- Ada Log Intelligence
Development
- Development Tools
- Testing Guide
- Version Management
- Changelog
- [Unreleased]
- [2.9.0] - 2025-12-19
- [2.8.0] - 2025-12-19
- [2.7.0] - 2025-12-19
- [2.6.0] - 2025-12-19
- [2.5.0] - 2025-12-18
- [2.4.0] - 2025-12-18
- [2.3.0] - 2025-12-18
- [2.2.0] - 2025-12-18
- [2.1.0] - 2025-12-17
- [1.8.0] - 2025-12-16
- [1.7.0] - 2025-12-16
- [1.6.0] - 2025-12-15
- [1.5.0] - 2025-12-10
- Earlier Versions
- Version Format
Philosophy & Design
Research & Validation
Overview
The Brain API provides endpoints for:
Chat with RAG - Generate responses with context from persona, FAQ, memories, and conversation history
Streaming - Real-time token delivery via Server-Sent Events (SSE)
Memory Management - Store and retrieve long-term user/context memories
Health Monitoring - Check service and dependency status
Debug Tools - Inspect RAG system state
Key Features:
✓ Non-blocking streaming responses (see Streaming) ✓ Semantic search on memories (see Memory) ✓ Automatic conversation threading ✓ Thinking/reasoning visibility ✓ Entity-scoped context retrieval (see Data Model Reference) ✓ Conversation summarization ✓ Specialist plugin system (see Specialist System)
Quick Start
Health Check:
curl http://localhost:7000/v1/healthz
Simple Chat:
curl -X POST http://localhost:7000/v1/chat \
-H "Content-Type: application/json" \
-d '{"prompt": "Hello!"}'
Streaming Chat:
curl -N -X POST http://localhost:7000/v1/chat/stream \
-H "Content-Type: application/json" \
-d '{"prompt": "Hello!"}'
See Getting Started for detailed setup and configuration.
Full API Reference
For complete endpoint documentation with parameters, responses, and examples, see API Reference.