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learning-openclaw

Caution

This repository is public. Never commit secrets, API keys, tokens, .env files, or any personal configuration here.

A personal sandbox for learning OpenClaw — a free, open-source autonomous AI agent (formerly Clawdbot / Moltbot) that runs locally and is reachable via the messaging platforms you already use (Telegram, Discord, Slack, WhatsApp, Signal, and many more).

What is OpenClaw?

OpenClaw connects to a large language model of your choice (Claude, GPT-4o, Gemini, DeepSeek, …) and acts as a personal assistant you interact with through chat. It can browse the web, manage files, summarise documents, handle emails, schedule calendar entries, and more — all running on your own hardware.

Upstream project: https://github.com/openclaw/openclaw

This repo

Experiments with running OpenClaw in a Docker Compose sandbox. Nothing here is meant for production.

compose.yaml    # Docker Compose stack (openclaw-gateway + openclaw-cli)
.env.example    # Template — copy to .env and fill in your secrets
Makefile        # Convenience targets
.gitignore      # Keeps .env and runtime state out of git

Quick start

# 1. Copy the env template and fill in at least one LLM key and one channel token
cp .env.example .env

# 2. Pull the image and start the gateway
make pull
make up

# 3. Open the web UI
open http://localhost:18789

# 4. Or drop into an interactive CLI session
make cli

Makefile targets

Target What it does
make up Start the gateway in detached mode
make down Stop and remove containers
make logs Follow gateway logs
make pull Pull the latest image
make cli Open an interactive CLI session

Runtime state (config, workspace, auth secrets) is stored in .openclaw/ and .openclaw-auth/ — both git-ignored.

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