OLI is an open-source alternative to Claude Code, built in Rust to provide powerful agentic capabilities for coding assistance. It features:

• A flexible TUI interface for working with code
• Support for both local LLMs (via vLLM or ollama) and cloud APIs (currently only tested using Anthropic Claude Sonnet 3.7 and OpenAI GPT4o but other APIs and local LLM support coming soon!)
• Complete agentic capabilities including file search, edit, and command execution

⚠️ This project is in a very early stage and is prone to bugs and issues! Please post your issues as you encounter them.

• LLM-Agnostic Design: Works with any LLM provider - local or cloud-based
• Advanced Prompt Engineering: Optimized prompts for maximum reliability
• Structured JSON Outputs: Enhanced response parsing for reliable tool usage
• Agent Capabilities: Read files, search code, edit code, and execute commands
• Terminal UI: Streamlined interface for maximum productivity
• Cross-Platform: Works on macOS, Linux, and Windows
• GPU Acceleration: Supports Metal acceleration for local models
• Fully Open Source: Apache 2.0 licensed
• Rust Performance: Built for speed and reliability

• Rust toolchain (install via rustup)
• For local models: At least 8GB RAM (16GB+ recommended for larger models)
• For cloud features: API keys for Anthropic or OpenAI

# Clone the repository
git clone https://github.com/amrit110/oli
cd oli

# Build and run
cargo build --release
cargo run

For API-based features, set up your environment variables:

# Create a .env file in the project root
echo "ANTHROPIC_API_KEY=your_key_here" > .env
# OR
echo "OPENAI_API_KEY=your_key_here" > .env

Claude 3.7 Sonnet provides the most reliable and advanced agent capabilities:

1. Obtain an API key from Anthropic
2. Set the ANTHROPIC_API_KEY environment variable
3. Select the "Claude 3.7 Sonnet" model in the UI

This implementation includes:

• Optimized system prompts for Claude 3.7
• JSON schema output formatting for structured responses
• Improved error handling and retry mechanisms

1. Start the application:

cargo run

2. Select a model:

   • Cloud models (Claude 3 Sonnet, GPT-4o) for full agent capabilities
   • Local models for offline use

3. Make your coding query in the chat interface:

   • Ask for file searches
   • Request code edits
   • Execute shell commands
   • Get explanations of code

Here are some example queries to try:

• "Explain the codebase and how to get started"
• "List all files in the project"
• "Summarize the Cargo.toml file"
• "Show me all files that import the 'anyhow' crate"

This project is licensed under the Apache 2.0 License - see the LICENSE file for details.

• This project is inspired by Claude Code and similar AI assistants
• Uses Anthropic's Claude 3.7 Sonnet model for optimal agent capabilities
• Built with Rust and the Ratatui library for terminal UI
• Special thanks to the Rust community for excellent libraries and tools