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Agentic AI CLI with tool calling and extensible skills system

Project description

Zeer

PyPI version Python License Code style: black Downloads GitHub stars

Zeer is an OpenSource agentic AI CLI that connects to multiple providers (OpenAI, Gemini, Claude, Ollama) with tool-calling capabilities and an extensible skills system.

Think of it as Claude Code for the terminal, provider-agnostic and developer-friendly.

image

๐ŸŽฏ Why Zeer?

Tools like Claude Code, Kiro, and Cursor are powerful but come with limitations:

  • Subscription Required โ€“ Monthly fees for access
  • Fixed Models โ€“ Locked into specific AI providers
  • Closed Source โ€“ Limited customization options

Zeer is different:

  • โœ… Use Your Own API Keys โ€“ Pay only for what you use, no subscriptions
  • โœ… Multi-Provider Support โ€“ Switch between OpenAI, Gemini, Claude, Ollama, or add your own
  • โœ… Local AI Support โ€“ Run models locally with Ollama (no API key required)
  • โœ… 100% Open Source โ€“ Customize, extend, and contribute freely
  • โœ… Extensible Skills System โ€“ Create custom agent behaviors without code changes
  • โœ… Background Process Management โ€“ Start and manage dev servers in the background
  • โœ… Terminal-First โ€“ Lightweight, fast, and integrates with your workflow

Note: Zeer is currently in beta. We appreciate your contributions and feedback as we continue to improve. This project will always remain open source.


๐Ÿš€ Get Started

Start using Zeer quickly with the following installation options.

For Users (PyPI)

pip install zeer

For Developers (Local / Editable)

# Clone the repository
git clone https://github.com/muhdaliyan/zeer.git
cd zeer

# Install dependencies
pip install -r requirements.txt

# Install in editable mode
pip install -e .

# Run Zeer
zeer

Any code changes will reflect immediately without reinstalling.


๐ŸŽฏ Quick Start

zeer
  1. Select your AI provider
  2. Enter your API key
  3. Choose a model
  4. Start chatting and using AI tools

๐Ÿ’ป Usage Examples

# AI automatically executes tasks
> create a PDF report about machine learning
> list all Python files in this directory
> set up a new React project structure
> read and summarize config.json

# Start dev servers in background
> start a React dev server on port 3000
> run the Flask app in the background

# Commands
/skills    # View available skills
/tools     # View available tools
/processes # View running background processes
/clear     # Clear conversation
/providers # Switch provider
/models    # Switch model

๐Ÿค– AI Providers

Zeer supports multiple AI providers:

Cloud Providers (API Key Required)

  • OpenAI โ€“ GPT-4, GPT-3.5, and more
  • Gemini โ€“ Google's AI models
  • Claude โ€“ Anthropic's Claude models
  • Ollama Cloud โ€“ Cloud-hosted Ollama models

Local Provider (No API Key)

  • Ollama Local โ€“ Run AI models entirely on your machine
    • No internet required
    • No API costs
    • Full privacy
    • See OLLAMA_SETUP.md for setup guide

๐Ÿš€ Ollama Quick Start

Want to run AI locally without API keys?

  1. Install Ollama from ollama.ai
  2. Pull a model: ollama pull llama3.2
  3. Start Zeer: zeer
  4. Select "Ollama" provider
  5. Press Enter (skip API key for local)
  6. Choose your model and start chatting

See OLLAMA_SETUP.md for detailed setup instructions.


๐Ÿ”„ Background Process Management

Zeer can start and manage development servers in the background:

# AI automatically detects and manages servers
> start a Next.js dev server
> run the Django development server
> start the Express API on port 8080

# View running processes
/processes

# AI can stop processes when needed
> stop the React dev server

Features:

  • Automatic URL detection
  • Output monitoring
  • Clean process termination
  • Multiple concurrent servers

๐Ÿ”ง Built-in Skills

  • pdf-builder โ€“ Generate PDF documents with reportlab
  • code-helper โ€“ Project setup & code organization
  • file-operations โ€“ File system operations
  • text-processing โ€“ Text manipulation & analysis
  • frontend-designer โ€“ Frontend development assistance

โœจ Creating Custom Skills

  1. Create skills/your-skill/SKILL.md:
---
name: your-skill
description: What this skill does and when to use it
allowed-tools: create_file read_file run_code
---

## Goal
Your skill's purpose

## Procedure
Step-by-step instructions for the AI

## Examples
Usage examples
  1. Restart Zeer โ€“ skills are auto-discovered.

See SKILLS_IMPLEMENTATION.md for advanced details.


๐Ÿ—๏ธ Architecture

zeer/
โ”œโ”€โ”€ src/
โ”‚   โ”œโ”€โ”€ providers/          # AI provider implementations
โ”‚   โ”œโ”€โ”€ tools.py            # Tool registry & execution
โ”‚   โ”œโ”€โ”€ skills_manager.py   # Skills loading & validation
โ”‚   โ””โ”€โ”€ chat_session.py     # Context management
โ””โ”€โ”€ skills/                 # Modular agent skills
    โ”œโ”€โ”€ backend-developer/
    โ”‚   โ”œโ”€โ”€ SKILL.md        # Skill definition
    โ”‚   โ”œโ”€โ”€ scripts/        # Executable Python scripts
    |   |   โ””โ”€โ”€ script.py
    โ”‚   โ””โ”€โ”€ references/     # Additional documentation
    โ”œโ”€โ”€ code-helper/
    โ”‚   โ””โ”€โ”€ SKILL.md
    โ”œโ”€โ”€ file-operations/
    โ”‚   โ””โ”€โ”€ SKILL.md
    โ””โ”€โ”€ ...

๐Ÿ”„ Tool Calling Flow

  1. User sends a message
  2. AI decides to use tools
  3. Tools execute (file ops, code, etc.)
  4. Results fed back to AI
  5. AI responds with final answer

๐Ÿ“œ Skills System

  • Metadata Loading: Only names/descriptions loaded initially
  • On-Demand Activation: Full skill content loaded when referenced
  • Scripts Support: Skills can include executable Python scripts
  • References: Additional documentation files
  • Validation: Automatic format checking on load

โš™๏ธ Requirements

  • Python 3.8+
  • API key for at least one cloud provider (OpenAI, Gemini, or Claude)
  • OR Ollama installed for local AI (no API key needed)

๐Ÿค Contributing

Contributions are welcome! Follow these steps:

Development Setup

git clone https://github.com/muhdaliyan/zeer.git
cd zeer
pip install -r requirements.txt
pip install -e .

Making Changes

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Make your changes
  4. Test locally with zeer
  5. Commit your changes (git commit -m 'Add amazing feature')
  6. Push (git push origin feature/amazing-feature)
  7. Open a Pull Request

Adding Custom Tools

Edit src/tools.py and add to the registry in create_default_registry().

Adding Custom Skills

Create a new folder in skills/ with a SKILL.md following the agentskills.io specification.


๐Ÿ“œ License

MIT


๐Ÿ”— Links

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