Coding Assistant Pro is a domain-specific AI assistant designed to provide high-quality programming support. This project was developed as part of an M.Tech CSE research initiative to demonstrate strict logical filtering and technical accuracy in AI-driven development tools.
🛠️ Project Goals
Domain Strictness: The model is constrained to respond only to Computer Science and Programming queries.
Accuracy: Provides line-by-line code explanations and identifies specific logic errors in buggy code.
Efficiency: Utilizes Meta's Llama-3.1-8B-Instruct via the Hugging Face Serverless Inference API for low-latency performance without high hardware costs.
📝 Model Behavior Rules
Programming Queries: Returns detailed explanations and complete code blocks.
Correct Code Analysis: Performs a line-by-line technical walkthrough.
Bug Identification: Identifies specific line numbers and explains the root cause of errors.
Out-of-Domain Filter: Returns "I have no knowledge" for any non-technical or non-CS topics.
🚀 Technical Implementation
Frontend: Streamlit 1.51.0
Backend: Hugging Face Inference API (huggingface_hub)
Model: Meta-Llama-3.1-8B-Instruct
Environment Management: Python-dotenv for secure local credential storage
