koder 0.3.1

An intuitive AI coding assistant and interactive CLI tool that boosts developer productivity with intelligent automation and context-aware support.

Koder

Koder is an experimental, universal AI coding assistant designed to explore how to build an advanced terminal-based AI coding assistant. Written entirely in Python, it serves as both a functional tool and a learning playground for AI agent development.

🎯 Project Status: Under active vibe coding! This is a learning-focused project where we explore building AI coding agents.

✨ Features

• 🤖 Universal AI Support: Works with OpenAI, Anthropic, Google, GitHub Copilot, and 100+ providers via LiteLLM with intelligent auto-detection
• 💾 Smart Context Management: Persistent sessions with SQLite storage and automatic token-aware compression (50k token limit)
• 🔄 Real-time Streaming: Rich Live displays with intelligent terminal cleanup for responsive user experience
• 🛠️ Comprehensive Toolset: file operations, search, shell, task delegation and todos.
• 🔌 MCP Integration: Model Context Protocol support with stdio, SSE, and HTTP transports for extensible tool ecosystem
• 🛡️ Enterprise Security: SecurityGuard validation, output filtering, permission system, and input sanitization
• 🎯 Zero Configuration: Automatic provider detection with fallback defaults

🛠️ Installation

Using uv (Recommended)

uv tool install koder

Using pip

pip install koder

⚡ Quick Start

Simply run Koder with your question or request:

# Configure one provider (example: OpenAI)
export OPENAI_API_KEY="your-openai-api-key"
export KODER_MODEL="gpt-4o"

# Run in interactive mode
koder

# Run with prompt
koder "create a Python function to calculate fibonacci numbers"

# Execute a single prompt in a named session
koder -s my-project "Help me implement a new feature"

# Use an explicit session flag
koder --session my-project "Your prompt here"

🤖 Configuration

Environment Variables

Koder automatically detects your AI provider based on available environment variables. The KODER_MODEL environment variable controls which model to use:

# OpenAI models
export KODER_MODEL="gpt-4.1"

# Claude models (via LiteLLM)
export KODER_MODEL="claude-opus-4-20250514"

# Google models (via LiteLLM)
export KODER_MODEL="gemini/gemini-2.5-pro"

# Github Copilot (via LiteLLM)
export KODER_MODEL="github_copilot/claude-sonnet-4"

Supported Providers

OpenAI

export OPENAI_API_KEY=your-api-key

# Optional: Use custom endpoint
export OPENAI_API_BASE=https://your-endpoint.com

# Optional: Specify model (default: gpt-4.1)
export KODER_MODEL="gpt-4o"

Anthropic

export ANTHROPIC_API_KEY=your-api-key
export KODER_MODEL="claude-opus-4-20250514"

Google (Gemini)

export GOOGLE_API_KEY=your-api-key
# Optional: Specify model (default: gemini/gemini-2.5-pro)
export KODER_MODEL="gemini/gemini-2.5-pro"

GitHub Copilot

export KODER_MODEL="github_copilot/claude-sonnet-4"

On first run you will see a device code in the terminal. Visit https://github.com/login/device and enter the code to authenticate.

Azure OpenAI

# Required
export AZURE_OPENAI_API_KEY="your-azure-api-key"
export AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com"

# Your Azure deployment name (often different from the base model name)
export AZURE_OPENAI_DEPLOYMENT="my-gpt4o-deployment"

# Choose a model that maps to your deployment
export KODER_MODEL="gpt-4o"

# Optional: API version
export AZURE_OPENAI_API_VERSION="2025-04-01-preview"

Tips:

• Ensure the endpoint hostname matches your Azure resource.
• AZURE_OPENAI_DEPLOYMENT must match the deployed model name in Azure.

Other AI providers (via LiteLLM)

LiteLLM supports 100+ providers including Anthropic, Google, Cohere, Hugging Face, and more:

# Google Vertex AI
export GOOGLE_APPLICATION_CREDENTIALS="your-sa-path.json"
export VERTEXAI_LOCATION="<your-region>"
export KODER_MODEL="vertex_ai/claude-sonnet-4@20250514"

# Custom OpenAI-compatible endpoints
export OPENAI_API_KEY="your-key"
export OPENAI_BASE_URL="https://your-custom-endpoint.com/v1"
export KODER_MODEL="openai/<your-model-name>"

🛠️ Development

Setup Development Environment

# Clone the repository
git clone https://github.com/feiskyer/koder.git
cd koder

uv sync
uv run koder

Code Quality

# Code formatting
black .

# Linting
ruff check --fix

# pylint
pylint koder_agent/ --disable=C,R,W --errors-only

🔒 Security

• API Keys: All API keys are stored in environment variables and never in code.
• Local Storage: Sessions are stored locally in your home directory.
• No Telemetry: Koder doesn't send any data besides API requests to your chosen provider.
• Code Execution: Shell commands require explicit user confirmation.

🤝 Contributing

Contributions are welcome! Here's how you can help:

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

Please read our Contributing Guidelines for more details.

🌐 Code of Conduct

This project follows a Code of Conduct based on the Contributor Covenant. Be kind and respectful. If you observe unacceptable behavior, please open an issue.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

Use of third-party AI services is governed by their respective provider terms.