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sky-agent

(★ 94)

Open-source framework for superagents.

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- __init__.py
- loop.py
- memory.py
- tools.py
- autoswarm.png
- logo_271.gif
- sample_results.png
- superagent.gif
- superagent_solo.gif
- __init__.py
- agent.py
- Dockerfile.base
- evaluator.py
- gepa_adapter.py
- gepa_run.py
- pipeline.py
- pipeline_spec.yaml
- pipeline_spec_base.yaml
- program_pipeline.md
- README.md
- __init__.py
- http_api.py
- telegram.py
- example-note.md
.dockerignore
.gitattributes
.gitignore
agent.yaml
Dockerfile
LICENSE
main.py
pyproject.toml
railway.json
README.md
uv.lock

# Installation Guide

1. Get the code

git clone https://github.com/arteemg/sky-agent

Downloads the entire project code from GitHub to your computer.

cd sky-agent

Moves into the project folder you just downloaded.

2. Docker

Easy Recommended

Prerequisites

Git Needed to download the project code from GitHub.
Docker Desktop Needed to build and run containers. Install it and keep it running in the background.

docker build -t sky-agent .

Builds a runnable image based on the Dockerfile.

docker run -p 8080:80 sky-agent

Runs the built image as an actual container.

✅ Run docker compose ps to check the containers are Up. If the README mentions a port, open http://localhost:PORT in your browser.

3. Python

Easy

Prerequisites

Git Needed to download the project code from GitHub.
Python 3 On Windows, be sure to check 'Add Python to PATH' during installation.

pip install .

Installs the package published on PyPI directly — no need to clone the source.

python main.py

Runs the Python script (or module).

✅ If it runs without errors and prints output in the terminal, it worked.

// repository documentation

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# Sky agent

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Stars](https://img.shields.io/github/stars/arteemg/autoswarm?style=social)](https://github.com/arteemg/autoswarm)
[![Forks](https://img.shields.io/github/forks/arteemg/autoswarm?style=social)](https://github.com/arteemg/autoswarm)
[![Python](https://img.shields.io/badge/python-3.12+-blue.svg)](https://www.python.org/)
[![Docker](https://img.shields.io/badge/Docker-required-2496ED?logo=docker&logoColor=white)](https://docker.com)

<p align="center">
  <br>
  <a href="https://discord.gg/9ggSRAFGKQ">
    <img src="https://img.shields.io/badge/Discord-Join%20Community-5865F2?logo=discord&logoColor=white" alt="Discord" />
  </a>
  <br>
  <img src="assets/logo_271.gif" alt="One-click-agent logo" width="400">
</p>

Deploy your own AI agent to the cloud in one click.

## Deploy

1. Fork this repo.
2. On [Railway](https://railway.com): **New Project → Deploy from GitHub repo** → pick your fork.
3. Add `LLM_API_KEY` - this can be an API key from any provider, including Anthropic, OpenAI, OpenRouter, etc.
4. Add `TELEGRAM_BOT_TOKEN` (see below)
5. Deploy.

Railway auto-redeploys every time you push to your fork, so editing your agent = editing files on GitHub.

## Get a Telegram bot token

1. Open Telegram and message [@BotFather](https://t.me/BotFather).
2. Send `/newbot`, pick a name and a username.
3. Copy the token it gives you — that's your `TELEGRAM_BOT_TOKEN`.

Telegram enables itself when `TELEGRAM_BOT_TOKEN` exists. In chat: `/reset` wipes the bot's memory of that conversation.

## Make it yours

| Want to change...                  | Edit...                                                                         |
| ---------------------------------- | ------------------------------------------------------------------------------- |
| API endpoints                      | `channels/http_api.py`                                                          |
| Personality, model, context length | `agent.yaml`                                                                    |
| The agent's abilities (tools)      | `agent/tools.py`                                                                |
| Channels (add Discord, Slack, ...) | drop a new file in `channels/`                                                  |

## Give your agent files

In the GitHub web UI open `knowledge/`, **Add file → Upload files**, commit. After the auto-redeploy, ask your agent "what files do you have?"

Plain-text formats work (md, txt, csv, code). PDFs and images are detected but not supported for now.

## How it works

```
Telegram / HTTP ──▶ respond(chat_id, text, config) ──▶ Claude API
                          │                              │
                     SQLite memory ◀──── tool use loop ──┘
```

Conversation memory is SQLite on disk, mount a volume (`DB_PATH`) to keep it across redeploys; on Railway, add a volume mounted at `/data` and set `DB_PATH=/data/agent.db`.

## Self-optimizing benchmark

This repo also ships a benchmark harness where a meta-agent rewrites its own multi-agent pipeline (prompts, tools, topology) to hill-climb on Harbor tasks. See `benchmark/` to run an experiment.

## License

MIT — do whatever you want with it. Have fun.