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meysamhadeli/codai

⭐ 376 Go added to this list on 2025-03-09 repository created 2024-10-15

Codai is an AI-powered code assistant designed to enhance developer productivity through a session-based command-line interface (CLI). It offers intelligent code suggestions, refactoring capabilities, and detailed code reviews by deeply understanding the full context of a project. This comprehensive context awareness allows Codai to analyze the entire codebase and provide relevant improvements or generate new code tailored to the project's needs. The tool supports multiple large language model (LLM) providers, including OpenAI, DeepSeek, Azure OpenAI, Ollama, Anthropic, and OpenRouter, making it versatile and adaptable to various AI ecosystems. Codai employs two primary methods to manage and summarize the full context of code: Retrieval-Augmented Generation (RAG) and summarization using Tree-sitter. RAG enhances code suggestions by embedding and retrieving the most relevant information based on user input, dynamically finding pertinent details from the entire code context. This method reduces token usage and improves response accuracy by sending only the necessary context to the AI model. The Tree-sitter approach creates a summary of the project's full context by sending only the signature bodies of code without full implementations, allowing retrieval of detailed context for specific code sections upon request. This method also saves tokens but typically uses slightly more than RAG. Installation is straightforward via Go, and configuration is flexible, supporting environment variables, project-specific YAML configuration files, or command-line options. Codai integrates with various AI providers through standard APIs and supports advanced LLM models optimized for code generation, such as GPT-4o, GPT-4, deepseek-chat, and claude-3-5-sonnet. It also supports local models like Ollama and embedding models from OpenAI and Ollama for efficient context retrieval. Overall, Codai is a powerful, flexible AI assistant that streamlines coding workflows by providing context-aware code assistance, making it a valuable tool for developers seeking to improve code quality and productivity.

https://github.com/meysamhadeli/codai

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