CodeGenie

Inspiration

The inspiration behind CodeGenie stems from the desire to create an intelligent coding assistant that simplifies the process of code generation and verification. Having a AI Assistant who can double verify your code along with testing its validity is a must that every developer must have.

What it does

CodeGenie is an AI-powered coding assistant that helps users generate code snippets and verify their correctness. Users can interact with CodeGenie through a user-friendly chat interface, where they input their coding problems or requirements. CodeGenie then leverages Gemini Pro to generate code based on the user's input. After generating the code, CodeGenie utilizes e2b code Interpreter sdk to verify the code's functionality and correctness.

How I built it

I built CodeGenie using a combination of cutting-edge technologies, including Google's Gemini Pro for code generation, Streamlit for the user interface, and the new released e2b code Interpreter sdk for code verification. The backend logic was implemented using Python, while the frontend interface was developed using Streamlit's intuitive framework. We integrated Gemini Pro's API to enable seamless communication between the user and the AI-powered assistant.

Challenges we ran into

A lot of Challenges, Firstly My system python got uninstalled when updating to newer version and everything stopped working even after restarting and having it in PATH (Still presists); this was the reason that I worked mostly on collab for this project. Another problem was Integration Complexity and the lack of Documentation in e2b code interpreter sdk, However in the end I was able to build somewhat a presentable application.

Accomplishments that I'm proud of

• Successfully integrating Google's Gemini Pro API with E2B Code Interpreter SDK into our application, enabling advanced code generation capabilities.
• Developing an efficient code execution engine capable of verifying the correctness of generated code.
• Creating a sleek and intuitive user interface using Streamlit, providing users with a seamless experience.
• Implementing a double-check feedback loop to ensure the accuracy and reliability of generated code.

What we learned

Integrating the app together with all of these tech together

What's next for CodeGenie

Among the other future improvements I have a plan to automate the github along with this so you can commit to github automatically Once that is donel The app will be Good enough to monetize to some extend. Other improvements are: Advanced Code Generation: Enhance CodeGenie's code generation capabilities by incorporating more advanced AI models and techniques. Code Refinement Suggestions: Implement intelligent suggestions for refining and optimizing generated code based on user feedback and best practices. Integration with Version Control: Integrate CodeGenie with version control systems to enable seamless collaboration and code management among teams. Expansion to Other Languages: Extend CodeGenie's functionality to support additional programming languages, catering to a broader user base.

Built With

• e2b
• e2b-code-interpreter-sdk
• gemini
• google.generativeai
• localtunnel
• python
• streamlit