README.md

metadata

title: CodeMentor AI
emoji: 🧠
colorFrom: purple
colorTo: blue
sdk: streamlit
sdk_version: 1.30.0
app_file: app/app.py
pinned: true

CodeMentor AI – ChatGPT for Coding Interviews (Fine-Tuned Flan-T5)

CodeMentor AI is a fine-tuned language model specialized for solving coding interview questions, built on top of TinyLlama-1.1B-Chat, trained with 20K+ prompts, and deployed with a sleek ChatGPT-style UI using Streamlit.

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Features

• Fine-tuned LLM using HuggingFace Transformers
• Trained on 20K+ high-quality coding problems (CodeAlpaca dataset)
• Clean ChatGPT-style frontend built with Streamlit
• Docker-ready for easy deployment
• Optimized for local + cloud usage
• Can run inference via terminal or web UI

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Tech Stack

• Flan-T5-small (HuggingFace)
• Transformers + Datasets
• Streamlit
• Docker for packaging
• Render or HuggingFace Spaces for deployment

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Training Details

Config	Value
Model	google/flan-t5-small
Epochs	6
Batch Size	1 (with gradient accumulation)
Learning Rate	5e-5
Max Length	512 tokens
GPU	GTX 1650 (4GB VRAM)
Total Samples	~20,000 examples
Training Time	~4 hours

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Folder Structure

CodeMentor-AI/ │ ├── data/ # Raw + Processed Datasets ├── model/codementor-flan/ # Saved fine-tuned model ├── train/ # Preprocessing + Training scripts ├── app/app.py # Streamlit Chat UI ├── requirements.txt # All dependencies ├── Dockerfile # Docker config ├── render.yaml # Optional Render deployment config

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to Run Locally

git clone https://github.com/chetan10510/CodeMentor-AI.git
cd CodeMentor-AI
python -m venv .venv
.venv\Scripts\activate       # Windows
pip install -r requirements.txt
streamlit run app/app.py