🧠 DeepSeek Code Companion

DeepSeek Code Companion is a powerful tool designed to assist developers with error handling, code commenting, and project roadmap suggestions. Built using Streamlit, LangChain, and Ollama, this tool integrates intelligent AI models to provide seamless solutions for debugging, documenting, and strategizing your software development journey.

Features

1. Error Handler 🐞

• Description: Automatically analyzes exceptions raised during code execution, identifies root causes, explains errors, and suggests solutions.
• How it works: Input the exception message along with the corresponding code snippet, and the AI will provide detailed error analysis with suggested fixes.

2. Code Commentator 📝

• Description: Provides detailed feedback on your project’s code. It evaluates the code for architecture, security, and best practices, offering improvement suggestions.
• How it works: Submit your project’s directory structure and code files, and the AI will generate a comprehensive analysis, including architecture suggestions, security checks, and best practice guidelines.

3. Roadmap Suggester 🛣️

• Description: Suggests a development roadmap for your project based on the current code structure. It identifies short, medium, and long-term goals for code quality improvement, performance optimization, and feature expansion.
• How it works: Provide the directory structure and contents of your project in JSON format, and the AI will generate a roadmap that includes suggestions on enhancing code structure, features, performance, and documentation.

Installation

1. Clone the repository:

   git clone https://github.com/SerhatDerya/deepseek-code-companion.git

2. Install dependencies:

   pip install -r requirements.txt

3. Run the Streamlit app:

   streamlit run main.py

Usage

• Error Handler:

  • Input the file path containing the code and the exception message.
  • The system will analyze the exception and offer a structured explanation, including root cause analysis, technical explanation, and suggested solutions.

• Code Commentator:

  • Upload your project directory.
  • The AI will analyze the project and provide a detailed review of the architecture, security, and best practices.

• Roadmap Suggester:

  • Upload the project directory and code files in JSON format.
  • The AI will provide a roadmap with short, medium, and long-term suggestions to improve the project.

Project Structure

deepseek-code-companion/
│
├── main.py                  # The main Streamlit application
├── modes/                   # Contains different modes like error handler, code commentator, roadmap suggester
│   ├── error_handler.py     # Error handling logic
│   ├── code_commentator.py  # Code commenting logic
│   ├── roadmap_suggester.py # Roadmap suggestion logic
│   └── system_prompts/      # Folder containing system prompt files for each mode
│       ├── error_handler_prompt.txt
│       ├── code_commentator_prompt.txt
│       └── roadmap_suggester_prompt.txt
└── directory.py             # Helper functions for getting project directory structure and reading files