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                                     ╰── your AI, your machine, every chat.

A personal and business AI agent that lives in your chat apps — answering questions from your documents, running commands on your machine, and auto-responding to contacts when you want it to.

Runs locally with persistent memory, governed by allowlists and audit logs.

Why multis?

• Local-first: Your data never leaves your machine
• All your chats, one config: Telegram, WhatsApp, Signal, Discord — via Beeper bridges or self-hosted Matrix
• LLM agnostic: Anthropic, OpenAI, Ollama — swap providers without code changes
• Persistent memory: ACT-R activation decay keeps recent context hot, old conversations fade naturally
• Document-aware: Indexes PDFs and DOCX with hierarchical section-aware chunking, answers with citations
• Governed: Command allowlist/denylist + append-only audit logs

Quick Start

npm install
cp .env.example .env    # add your bot token + LLM API key
node src/index.js       # start the bot

Pair with your bot on Telegram using the pairing code shown on startup.

How It Works

┌──────────────┐  ┌──────────────┐
│  Telegram    │  │  Beeper      │  (WhatsApp, Signal, Discord, ...)
│  Bot API     │  │  Desktop API │
└──────┬───────┘  └──────┬───────┘
       │                 │
┌──────▼─────────────────▼──────────────────────┐
│            Message Router                      │
│  commands · RAG ask · chat modes · doc upload  │
└──────┬─────────┬──────────┬───────────────────┘
       │         │          │
┌──────▼──┐ ┌───▼────┐ ┌───▼──────────┐
│ Skills  │ │  LLM   │ │  Indexer     │
│ (shell, │ │ (any   │ │ (PDF, DOCX,  │
│  files) │ │ provider│ │  MD → FTS5)  │
└─────────┘ └────────┘ └──────────────┘
       │         │          │
┌──────▼─────────▼──────────▼───────────────────┐
│  SQLite (FTS5 search · activation decay)       │
│  Governance (allowlist · denylist · audit log)  │
└────────────────────────────────────────────────┘

Why Not openclaw?

Borrowed the good parts — daemon architecture, pairing flow, skill.md pattern — but made it simpler:

• One config, all chats. openclaw needs a separate API integration per channel (WhatsApp Baileys, Discord bot, Signal, etc). multis uses one config block and talks to Telegram + Beeper bridges + Matrix — all your networks through one setup.
• Persistent activation-decay memory. ACT-R model (ported from Aurora) means recent context stays hot, old conversations fade naturally. Not just a chat log — a memory with priorities.
• Structured document chunking. Hierarchical section-aware chunking for PDFs and DOCX (also from Aurora). The bot knows which chapter and section a chunk came from, not just raw text.
• No gateway, no plugin system. openclaw has a complex gateway + plugin architecture. multis is a flat router with skills — add a command in one file, done.

Features

• Ask questions — /ask or just type naturally. RAG pipeline searches your docs, passes context to the LLM, answers with citations.
• Run commands — /exec ls ~/Documents with governance enforcement (allowlist/denylist)
• Index documents — Upload PDFs and DOCX files, or /index <path>. Hierarchical chunking preserves document structure.
• Chat modes — Set any Beeper chat to personal (self-use) or business (auto-respond to incoming messages)
• Audit everything — Append-only tamper-evident log of all commands and actions

Roadmap

• [x] POC 1: Telegram bot + pairing
• [x] POC 2: Skills (shell exec, file read, governance)
• [x] POC 3: Document indexing (PDF/DOCX → FTS5)
• [x] POC 4: LLM RAG + chat modes
• [x] POC 5: Memory (ACT-R activation decay + memory.md)
• [x] POC 6: Daemon + CLI + security + data isolation
• [ ] Dogfood: End-to-end testing, polish, daily use
• [ ] v0.2: Packaging, onboarding docs, npm install -g ready
• [ ] POC 7: Multi-platform (Beeper Desktop + self-hosted Matrix) — deferred

Tech Stack

Node.js (vanilla, minimal deps) · Telegraf · better-sqlite3 · pdfjs-dist · mammoth

Project Structure

src/
├── bot/handlers.js       # Message router + all command handlers
├── platforms/            # Telegram + Beeper adapters, normalized Message
├── llm/                  # Anthropic, OpenAI, Ollama providers + RAG prompts
├── indexer/              # PDF/DOCX parsing, chunking, SQLite FTS5 store
├── governance/           # Command validation + audit logging
├── skills/               # Shell exec, file read
├── config.js             # ~/.multis/config.json + .env loader
└── index.js              # Entry point

License

MIT