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Spring Boot AI Code Assistant

This is an open-source tool that helps you generate, test, and document Spring Boot code using local AI models. It's designed to run entirely on your machine, ensuring privacy and eliminating costs.

Features

  • Local AI Model Integration: Uses Ollama to connect with local LLMs like Mistral, DeepSeek, and Llama.
  • Code Generation: Generates complete Spring Boot code examples, REST APIs, entity relationships, and configuration files.
  • Project Management: Manages project metadata (application name, Java version, Spring Boot version, etc.).
  • File Management: Organizes, views, downloads, and tests generated code files.
  • Prompt Management: Includes quick prompts, custom prompts, and chat history.
  • Debugging: Provides tools to troubleshoot local model connections.

Setup

  1. Install Ollama: Follow the instructions on the Ollama website to install Ollama.

  2. Pull a Model: Use Ollama to pull a model (e.g., Mistral):

    ollama pull mistral
    
  3. Clone the Repository:

    git clone https://github.com/dkarthi1973/codeassistant
    cd codeassistant
    
  4. Install Dependencies:

    pip install -r requirements.txt
    
  5. Run the Application:

    streamlit run SpringbootAIAssistant.py
    

Configuration

  • Model Selection: Choose a model in the sidebar. If the model is not loaded try running: ollama pull {model}
  • Project Settings: Configure project metadata like application name, group ID, and artifact ID.
  • Prompts: Use quick prompts or add your own custom prompts.

Usage

  1. Chat Tab: Interact with the AI assistant to generate code.
  2. Project Files Tab: View and download generated files.
  3. Testing Tab: Generate and run tests.
  4. Deployment Tab: Find deployment instructions.
  5. Documentation Tab: Access generated documentation.

Contributing

Feel free to fork the repository and contribute to the project. You can add new features, improve the UI, or fix bugs.

License

This project is open source and available under the MIT License.

Credits

  • This project uses Ollama for local AI model management.
  • The UI is built with Streamlit.

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