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This assistant uses a hybrid Retrieval-Augmented Generation (RAG) model to analyze code files (`.py`, `.c`, `.cpp`, etc.) and answer questions based on the code content.\n\n## Key Features\n\n- ✅ **Code-based Answers**: Provides context-aware responses by examining and understanding the code in your files.\n- ❓ **Programming-Specific Q\u0026A**: Restricted to only programming-related questions, delivering expert responses on various programming languages.\n- 📜 **Embedded RAG Model**: Integrates a hybrid RAG model for storing and retrieving detailed programming knowledge from custom file inputs.\n- 🔍 **Advanced Search and Recall**: Uses Redis for efficient data retrieval and OpenAI embeddings for relevance ranking.\n- 🧩 **Interactive Console**: Simple and interactive user interface powered by Streamlit for ease of use.\n\n## Technologies Used\n\n- 🤖 OpenAI's `gpt-4o` for natural language understanding and response generation.\n- ⚙️ `text-embedding-3-small` for code and query embeddings.\n- 🧩 **Streamlit** for the front-end interface.\n- 📅 **Redis** for quick, indexed access to knowledge base entries.\n- 🐍 **Python** for core application logic.\n\n## Getting Started\n\nAI Coding Assistant has been deployed here: https://aicodingassistant.streamlit.app/\n\n**HOW TO USE:**\n\n1. Upload Code Files: Load your code files to initialize the assistant’s knowledge base.\n2. Ask Programming Questions: Type a coding question related to your files or general programming.\n3. Receive Code-Specific Answers: The assistant will respond with context-based answers, code snippets, or explanations, drawing information from the loaded code files.\n\n## Demo Video\n[![Watch the video](https://img.youtube.com/vi/DcS94kOBI4U/maxresdefault.jpg)](https://youtu.be/DcS94kOBI4U)\n\n### [Watch this video on YouTube](https://youtu.be/DcS94kOBI4U)\n\n## Creators\nV Kamal Jerome | Shakthireka Karthikeyan | Kopika M | Deepesh Raj AY | Ashirvad Janardanan V\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkamaljerome%2Faicodingassistant","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkamaljerome%2Faicodingassistant","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkamaljerome%2Faicodingassistant/lists"}