🧠 AI_CodeSolver 🤖

Welcome to AI_CodeSolver! 🚀 This is a powerful Python project that leverages state-of-the-art AI models to help you solve coding problems automatically! Whether you're a beginner or an expert, this tool will assist you in generating optimal solutions and executing them in a safe sandbox environment.

🔧 AI_CodeSolver uses OpenAI's GPT-3, Google's Gemini, and E2B sandbox environments to analyze coding problems, generate solutions, and run them in real-time.

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🧑‍💻 Features ✨

• 📸 Image Processing: Upload an image of a coding problem, and the system will extract the problem description using advanced image recognition (powered by Gemini).
• 📝 Text Input: You can also directly type your coding problem.
• 💻 Code Generation: The AI will generate a clean, efficient, and documented Python solution for your coding problem.
• 🚀 Code Execution: Execute the generated solution in a secure sandbox environment, and get real-time results.
• 🔒 Safe Environment: Run potentially unsafe or untrusted Python code without worrying about security issues using the E2B sandbox.
• ⚡ Optimized for LeetCode-like Problems: Designed to handle typical coding challenges with proper time and space complexity.

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💻 Installation 🚀

Prerequisites 🔑

1. Python 3.x installed on your machine.
2. API keys for OpenAI, Gemini, and E2B (sandbox execution).

Steps to Set Up 🛠️

1. Clone the Repository:

   git clone https://github.com/andredisa/AI_CodeSolver.git
   cd AI_CodeSolver

2. Create a Virtual Environment (optional but recommended):

   python3 -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install Dependencies:

   pip install -r requirements.txt

4. Set Up API Keys 🔑:

   • Create a .env file in the project root directory (same level as this README).
   • Add your API keys in this format:

   OPENAI_API_KEY=your-openai-api-key
   GEMINI_API_KEY=your-gemini-api-key
   E2B_API_KEY=your-e2b-api-key

   Make sure you never push your .env file to GitHub for security reasons! 🔐

5. Run the Application:

   Start the app with Streamlit:

   streamlit run app/ui.py

   Your application will open in your browser! 🌐

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🖥️ How to Use 🤖

1. Input Coding Problem:

   • You can upload an image of a coding problem or directly type the problem in the text box.

2. Generate & Execute:

   • Once you’ve entered the problem, hit the "Generate & Execute Solution" button to let the AI generate a solution and run the code.

3. Review the Results:

   • The AI will return the solution with a breakdown of the code.
   • The generated code will be executed in the E2B sandbox, and you’ll get the results right on the platform.

4. Check Files (if any):

   • If the execution creates any files, they’ll be listed below the execution results for you to download.

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🎨 UI/UX Overview 💡

• Sidebar Configuration: On the left side, configure your API keys for OpenAI, Gemini, and E2B.
• Main Area:
  • Input your coding problem as text or upload an image.
  • Get the AI-generated solution along with the execution results.
• Real-time Feedback: See step-by-step execution logs and any generated files right after the code runs.

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🔧 Technologies Used ⚙️

• Streamlit: The frontend framework to build the web interface.
• OpenAI GPT-3: Used for generating Python solutions.
• Google Gemini: For analyzing and extracting coding problems from images.
• E2B Sandbox: A secure environment to run Python code without any security concerns.

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📦 File Structure 🗂️

Here’s an overview of the project structure:

AI_CodeSolver/
│
├── app/ # Main application code
│ ├── init.py
│ ├── ui.py # UI code (Streamlit app)
│ ├── agents.py # Agents for AI interactions (OpenAI, Gemini)
│ ├── sandbox.py # Sandbox management
│ └── image_processing.py # Image processing (Gemini API)
│
├── .env # Your sensitive API keys (don't upload this to GitHub)
├── .env.example # Example .env file
├── .gitignore # Ignore sensitive files (e.g., .env)
└── requirements.txt # List of Python dependencies

🤩 Contribute 💬

We welcome contributions! 🚀 If you have ideas for improvements, bug fixes, or new features, feel free to:

1. Fork the repository.
2. Create a new branch (git checkout -b feature-name).
3. Commit your changes (git commit -am 'Add new feature').
4. Push to the branch (git push origin feature-name).
5. Open a Pull Request.

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📝 License 📜

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

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☕ Support Me

If you find my work useful and would like to support me, you can buy me a coffee! Your support helps me keep creating and improving my projects. Thank you! 😊

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🎉 Enjoy solving problems with AI CodeSolver! 🌟