Skip to main content

Multi-Agent Chatbot SDK - Build customizable multi-agent chatbots with ease

Project description

MACSDK - Multi-Agent Chatbot SDK

A comprehensive SDK for building customizable multi-agent chatbots with RAG support, web interfaces, and reusable API tools.

What can it do?

  • Create a chatbot with CLI and Web UI, ready to be used immediately.
  • Create agents with a CLI chat (for testing purposes) ready to be used.
  • Register agents into chatbots, so your chatbot can call any of the agents you add.

How does it work?

The chatbot has a "supervisor" agent that knows about the registered agents and decides when to use one or another. It uses them as tools.

Key Features

  • 🏗️ Scaffolding CLI: Generate chatbot and agent projects with a single command.
  • 🤖 Intelligent Supervisor: Automatic routing and orchestration of specialist agents.
  • 📚 RAG Support: Enable RAG when creating a chatbot to pull docs from URLs (HTML/Markdown) or local files.
  • 🧠 Context Management: Keeps user queries and final answers in context, auto-compressing messages if the history gets too large.
  • 🌐 Web Interface: Built-in FastAPI + WebSocket server with real-time streaming (compatible with other WebSocket UIs).
  • ⏱️ Time Awareness: Injects current time into prompts so agents are aware of the "now" (useful for logs/APIs).
  • 🔧 Built-in Tools: Ready-to-use tools for REST APIs (with JSONPath extraction) and file downloads.
  • 🔄 Progress Tracking: Shows real-time progress when an agent is selected and which tools are being used.

Quick Start

Installation

For detailed installation instructions, see the Installation Guide.

# Clone and install
git clone https://github.com/juanje/macsdk
cd macsdk
uv sync

# Or install via pip/uv (once published)
# uv add macsdk

1. Create a Chatbot

Learn more in the Creating Chatbots Guide.

macsdk new chatbot my-chatbot --display-name "My First Chatbot"
cd my-chatbot
cp .env.example .env
# Edit .env and add your GOOGLE_API_KEY
uv sync
uv run my-chatbot

It's ready to use immediately.

2. Create an Agent

Learn more in the Creating Agents Guide.

cd ..
macsdk new agent infra-agent --description "Monitors infrastructure services"
cd infra-agent
uv sync
uv run infra-agent chat

It has its own chat for testing.

3. Register the Agent to the Chatbot

cd ../my-chatbot/
macsdk add-agent . --path ../infra-agent

Now you'll be able to use the chat, which can delegate to the agent if needed.

uv run my-chatbot chat
# Or using the Web UI
uv run my-chatbot web

You can add as many agents as you want!

Configuration

Environment Variables (.env)

GOOGLE_API_KEY=your_key_here

YAML Configuration (config.yml)

# LLM settings
llm_model: gemini-3-flash-preview
llm_temperature: 0.3

# RAG sources (if --with-rag)
rag:
  enabled: true
  sources:
    - name: "My Docs"
      url: "https://docs.example.com/"
      tags: ["docs", "api"]

Examples

The examples/ directory contains working examples:

  • api-agent: REST API interactions with JSONPlaceholder.
  • devops-chatbot: Multi-agent chatbot with RAG and API tools.

Development

git clone https://github.com/juanje/macsdk
cd macsdk
uv sync

# Run tests
uv run pytest

# Type checking & linting
uv run mypy src/
uv run ruff check .

License

MIT

🤖 AI Tools Disclaimer

This project was developed with the assistance of artificial intelligence tools:

Tools used:

  • Cursor: Code editor with AI capabilities
  • Claude-4.5-Opus: Anthropic's language model

Division of responsibilities:

Human (Juanje Ojeda):

  • 🎯 Specification of objectives and requirements
  • 📋 Definition of project's architecture
  • 🔍 Critical review of code and documentation
  • 💬 Iterative feedback and solution refinement
  • ✅ Final validation of concepts and approaches

AI (Cursor + Claude-4.5-Opus):

  • 🔧 Initial code prototyping
  • 📝 Generation of examples and test cases
  • 🐛 Assistance in debugging and error resolution
  • 📚 Documentation and comments writing
  • 💡 Technical implementation suggestions

Collaboration philosophy: AI tools served as a highly capable technical assistant, while all design decisions and project directions were defined and validated by the human.


Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

macsdk-0.10.0.tar.gz (115.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

macsdk-0.10.0-py3-none-any.whl (156.6 kB view details)

Uploaded Python 3

File details

Details for the file macsdk-0.10.0.tar.gz.

File metadata

  • Download URL: macsdk-0.10.0.tar.gz
  • Upload date:
  • Size: 115.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.9.23 {"installer":{"name":"uv","version":"0.9.23","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for macsdk-0.10.0.tar.gz
Algorithm Hash digest
SHA256 79c7ef0113e55cd7f5c4d4c00752097ae33dd4d3f1407ca59cb1cbf086cad16b
MD5 cb3b641976cbf6de1b72857dec9ceba0
BLAKE2b-256 25093156c0ff7a913e6b58af2101d3d78ff18303fccfef252c159c3369880d90

See more details on using hashes here.

File details

Details for the file macsdk-0.10.0-py3-none-any.whl.

File metadata

  • Download URL: macsdk-0.10.0-py3-none-any.whl
  • Upload date:
  • Size: 156.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.9.23 {"installer":{"name":"uv","version":"0.9.23","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for macsdk-0.10.0-py3-none-any.whl
Algorithm Hash digest
SHA256 8c740d611f4410da29bccb182a2104d3131900af709aae68e28c17a2bbda9714
MD5 73d12c525a8bc55ee7f3e9097d54d0b3
BLAKE2b-256 a212acf74284135df227a313104fb661a0279c0ade6a2baf69877886ce00ddc1

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page