peepsai 0.1.3

Peeps AI is a platform for decentralized AI agents, designed to provide individuals and communities with accessible, transparent and collaborative AI solutions.

Peeps AI - Advanced Multi-Agent Orchestration

🧠 Production-Grade AI Agent Framework

Peeps AI is a powerful framework designed to orchestrate autonomous AI agents that work together seamlessly to execute complex tasks. Whether you're automating workflows, developing AI-powered assistants, or managing data-driven decisions, Peeps AI enables intelligent multi-agent collaboration with fine-grained control and predictable execution.

🔗 Website: peepsai.io
📖 Documentation: Read the Docs
💬 Community: Telegram | Twitter

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✨ Features

✅ Multi-Agent Collaboration - Define AI agents with specialized roles, goals, and tools.
✅ Autonomous Task Delegation - Agents dynamically assign tasks based on expertise.
✅ Production-Ready Architecture - Robust error handling, state management, and extensibility.
✅ Process Control with Workchains - Create AI-driven workflows with fine-tuned execution.
✅ Customizable & Extensible - Use built-in tools or integrate your own.
✅ Blockchain-Enhanced Transparency - Use Peeps AI with ERC20-based governance.

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🚀 Quickstart

1️⃣ Install Peeps AI

pip install git+https://github.com/PeepsAI/PeepsAI.git

Or, if you want to install it with optional tools, use:

pip install git+https://github.com/PeepsAI/PeepsAI.git#egg=peepsai[tools]

If you prefer to clone the repository manually and install it:

git clone https://github.com/PeepsAI/PeepsAI.git
cd PeepsAI
pip install .

2️⃣ Create Your First Group (Peeps Group)

peepsai create group my_project

This generates the following structure:

my_project/
├── src/
│   ├── main.py       # Entry point
│   ├── group.py      # AI group logic
│   ├── tools/        # Custom AI tools
│   ├── config/
│   │   ├── agents.yaml  # Agent definitions
│   │   ├── tasks.yaml   # Task definitions
├── .env             # API keys (LLMs, etc.)
├── pyproject.toml   # Dependencies
├── README.md        # Project description

3️⃣ Run Your AI Agents

Execute your AI workflow with:

peepsai run

Or run manually:

python src/my_project/main.py

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🏗 Example - AI Research & Reporting

Define your AI agents in config/agents.yaml:

researcher:
  role: "Senior AI Researcher"
  goal: "Uncover the latest advancements in AI"
  backstory: "Expert in deep learning, NLP, and AI ethics."

reporting_analyst:
  role: "AI Market Analyst"
  goal: "Analyze AI trends and create detailed reports."

And set up tasks in config/tasks.yaml:

research_task:
  description: "Find the most relevant AI breakthroughs of 2024."
  expected_output: "10 key AI developments in bullet points."
  agent: researcher

reporting_task:
  description: "Expand the findings into a structured market report."
  expected_output: "A Markdown-formatted AI industry report."
  agent: reporting_analyst
  output_file: report.md

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🛠 Advanced Use Cases

🔹 AI-Powered Assistants - Build autonomous virtual agents.
🔹 Data Analysis Pipelines - Automate research and reporting.
🔹 Business Workflow Automation - AI-driven decision-making.
🔹 Decentralized AI Governance - Integrate Peeps AI with blockchain.

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🎯 Roadmap

🟢 2024 - Foundation & Core Framework
🟠 2025 - GUI, Staking, & Smart Contracts
🔴 2026+ - AI NFT Agents & Cross-Chain Integration

📌 View full Peeps AI Roadmap.

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🤝 Contributing

We welcome open-source contributions! To contribute:

1. Fork the repo
2. Create a new branch (feature-xyz)
3. Commit your changes
4. Submit a Pull Request

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🔗 Follow us on Twitter → @peeps_ai