Welcome to our guide on leveraging CodeQAI, an innovative tool that allows you to search your codebase semantically and interact with it through a command-line interface (CLI). In this blog post, we will walk you through its setup, usage, and troubleshooting steps to make your coding experience smooth and efficient.

What is CodeQAI?

CodeQAI lets you keep a vector database constantly updated with the latest code changes while ensuring your data remains safe and local. Built with popular libraries like langchain and treesitter, CodeQAI combines semantic code search with advanced chatting capabilities, giving you a “GPT-like” interaction with your codebase.

Features of CodeQAI

• Semantic code search
• GPT-like chat with your codebase
• Easy synchronization of vector store and latest code changes
• Support for local embeddings and LLMs, such as sentence-transformers and llama.cpp
• Integration with Treesitter

Getting Started with CodeQAI

Installation

To install CodeQAI, it’s recommended to use pipx to ensure isolated environments:

pipx install codeqai

When using pipx, ensure you are using Python versions 3.9 or 3.12. To install using a specific version, you can activate it first, for example:

pipx install codeqai --python $(which python)

Start Using CodeQAI

Once installed, you can start using CodeQAI with the following commands:

• To start semantic search:

  codeqai search

• To start a chat dialog:

  codeqai chat

• To synchronize the vector store with the current Git checkout:

  codeqai sync

• To start the Streamlit app:

  codeqai app

How CodeQAI Works

Think of CodeQAI as a librarian for your code. Just like a librarian organizes books, CodeQAI organizes your code repository using Treesitter to extract methods and their documentation and storing this information in a local FAISS vector database. When you perform a semantic search or interact with your code, it functions similarly to asking the librarian about certain topics, providing you with accurate and relevant information.

Troubleshooting Common Issues

Even the best tools can face hiccups. Here are some common issues and solutions:

• Pip Installation Issues: If you encounter errors like “pip failed to build package: tiktoken”, it may be due to missing packages like the Rust compiler. Install it from here.
• Faiss Installation Issue: If you get an error regarding `faiss-cpu`, ensure you are using Python 3.12, as no faiss wheel is available for that version yet.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Conclusion

CodeQAI is an excellent tool for developers looking to enhance their coding workflows with semantic search and intelligent code conversation. The setup is straightforward, and the troubleshooting process can help resolve common issues that might arise.

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.

Get Involved

If you find yourself missing a feature or facing a bug, feel free to contribute by opening an issue or submitting a pull request. Collaborative efforts lead to better tools for everyone!