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* feat: add POST /api/v1/chat endpoint for sending messages to agents Adds an HTTP endpoint that accepts a JSON message, sends it to the lettabot agent via sendToAgent(), and returns the agent's response. This enables external systems (e.g. server-side tools in other agents) to communicate with lettabot programmatically. - Add ChatRequest/ChatResponse types - Add AgentRouter interface extending MessageDeliverer with sendToAgent() - Implement AgentRouter on LettaGateway with agent-name routing - Add POST /api/v1/chat route with auth, validation, and JSON body parsing Written by Cameron ◯ Letta Code "The most profound technologies are those that disappear." -- Mark Weiser * feat: add SSE streaming support to /api/v1/chat endpoint When the client sends Accept: text/event-stream, the chat endpoint streams SDK messages as SSE events instead of waiting for the full response. Each event is a JSON StreamMsg (assistant, tool_call, tool_result, reasoning, result). The result event signals end-of-stream. - Export StreamMsg type from bot.ts - Add streamToAgent() to AgentSession interface and LettaBot - Wire streamToAgent() through LettaGateway with agent-name routing - Add SSE path in chat route (Accept header content negotiation) - Handle client disconnect mid-stream gracefully Written by Cameron ◯ Letta Code "Any sufficiently advanced technology is indistinguishable from magic." -- Arthur C. Clarke * test+docs: add chat endpoint tests and API documentation - 10 tests for POST /api/v1/chat: auth, validation, sync response, agent routing, SSE streaming, stream error handling - 6 tests for gateway sendToAgent/streamToAgent routing - Fix timingSafeEqual crash on mismatched key lengths (return 401, not 500) - Document chat endpoint in configuration.md with sync and SSE examples - Add Chat API link to docs/README.md index Written by Cameron ◯ Letta Code "First, solve the problem. Then, write the code." -- John Johnson
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LettaBot Documentation
LettaBot is a multi-channel AI assistant powered by Letta that provides persistent memory and local tool execution across Telegram, Slack, Discord, WhatsApp, and Signal.
Guides
- Getting Started - Installation and basic setup
- Self-Hosted Setup - Run with your own Letta server
- Configuration Reference - All config options
- Commands Reference - Bot commands reference
- CLI Tools - Agent/operator CLI tools
- Chat API - HTTP endpoint for programmatic agent access
- Scheduling Tasks - Cron jobs and heartbeats
- Gmail Pub/Sub - Email notifications integration
- Railway Deployment - Deploy to Railway
- Releasing - How to create releases
Channel Setup
- Telegram Setup - BotFather token setup
- Slack Setup - Socket Mode configuration
- Discord Setup - Bot application setup
- WhatsApp Setup - Baileys/QR code setup
- Signal Setup - signal-cli daemon setup
Architecture
LettaBot uses a single agent with unified memory across all channels:
┌──────────────────────────────────────────────────────────────────────────┐
│ Your Server / Machine │
│ │
│ ┌────────────┐ ┌────────────┐ ┌────────────┐ ┌──────────┐ ┌───────┐ │
│ │ Telegram │ │ Slack │ │ Discord │ │ WhatsApp │ │ Signal│ │
│ │ (grammY) │ │ (Socket) │ │ (Gateway) │ │(Baileys) │ │ (CLI) │ │
│ └─────┬──────┘ └─────┬──────┘ └─────┬──────┘ └────┬─────┘ └───┬───┘ │
│ │ │ │ │ │ │
│ └───────────────┴───────────────┴──────────────┴────────────┘ │
│ │ │
│ ┌─────────▼─────────┐ │
│ │ LettaBot Core │ │
│ │ (TypeScript) │ │
│ │ │ │
│ │ • Message Router │ │
│ │ • Session Mgmt │ │
│ │ • Heartbeat/Cron │ │
│ └─────────┬─────────┘ │
│ │ │
│ ┌─────────▼─────────┐ │
│ │ Letta Code SDK │ │
│ │ (subprocess) │ │
│ │ │ │
│ │ Local Tools: │ │
│ │ • Read/Glob/Grep │ │
│ │ • Bash │ │
│ │ • web_search │ │
│ └─────────┬─────────┘ │
└────────────────────────────────────┼──────────────────────────────────────┘
│ Letta API
▼
┌──────────────────────────┐
│ Letta Server │
│ (api.letta.com or │
│ self-hosted Docker) │
│ │
│ • Agent Memory │
│ • LLM Inference │
│ • Conversation History │
└──────────────────────────┘
Key Features
- Multi-Channel - Chat across Telegram, Slack, Discord, WhatsApp, and Signal
- Unified Memory - Single agent remembers everything from all channels
- Persistent Memory - Conversations persist across days/weeks/months
- Local Tool Execution - Agent can search files, run commands on your machine
- Voice Messages - Automatic transcription via OpenAI Whisper
- Streaming Responses - Real-time message updates as the agent thinks
- Background Tasks - Heartbeats and cron jobs for proactive actions