oli - Open Local Intelligent assistant

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 cloud APIs (Anthropic Claude Sonnet 3.7 and OpenAI GPT4o) and local LLMs (via Ollama)
• Strong agentic capabilities including file search, edit, and command execution
• Tool use support across all model providers (Anthropic, OpenAI, and Ollama)

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

Installation

Using Cargo

cargo install oli-tui

Using Homebrew (macOS)

brew tap amrit110/oli
brew install oli

From Source

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

# Build and run
cargo build --release
cargo run

Environment Setup

Cloud API Models

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

Using Anthropic Claude 3.7 Sonnet (Recommended)

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

Using Ollama Models

oli supports local models through Ollama:

1. Install Ollama if you haven't already
2. Start the Ollama server:

   ollama serve
   

3. Pull the model you want to use (we recommend models with tool use capabilities):

   # Examples of compatible models
   ollama pull qwen2.5-coder:14b
   ollama pull qwen2.5-coder:3b
   ollama pull llama3:8b  
   

4. Start oli and select the Ollama model from the model selection menu

Note: For best results with tool use and agent capabilities, use models like Qwen 2.5 Coder which support function calling.

Usage

1. Start the application:

cargo run

2. Select a model:

   • Cloud models (Claude 3 Sonnet, GPT-4o) for full agent capabilities
   • Local models via Ollama (Qwen, Llama, etc.)

3. Make your coding query in the chat interface:

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

Examples

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"

License

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

Acknowledgments

• 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