README.md

metadata

title: Olist Text-to-SQL Agent
emoji: 🤖
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 4.44.0
app_file: app_gradio.py
pinned: false
license: mit

🤖 Olist Text-to-SQL Agent

Convert natural language questions into SQL queries using a fine-tuned Mistral-7B model.

🎯 Features

• Fine-Tuned Model: Mistral-7B-Instruct-v0.2 fine-tuned with QLoRA on Olist e-commerce dataset
• Natural Language to SQL: Ask questions in plain English, get executable SQL queries
• Real Database: Query against actual Olist e-commerce data (100K+ orders)
• Interactive UI: Built with Gradio for easy interaction

🚀 How to Use

1. Type your question in natural language
2. Click "Generate SQL & Execute"
3. View the generated SQL query and results

💡 Example Questions

• "How many orders are there?"
• "What are the top 5 best-selling products?"
• "Show total revenue by customer state"
• "Which sellers have the highest ratings?"
• "List all orders from São Paulo"

🛠️ Tech Stack

• Model: Mistral-7B-Instruct-v0.2 (fine-tuned with QLoRA)
• Frontend: Gradio
• Database: SQLite (Olist e-commerce dataset)
• ML Libraries: PyTorch, Transformers, PEFT, BitsAndBytes

📊 Model Details

• Base Model: mistralai/Mistral-7B-Instruct-v0.2
• Fine-Tuned Model: mhdakmal80/Olist-SQL-Agent-Final
• Training Method: QLoRA (4-bit quantization)
• Training Data: 1000+ synthetic question-SQL pairs
• Accuracy: 90% on test set

🎓 About

This project demonstrates:

• Fine-tuning large language models (7B parameters)
• Parameter-efficient fine-tuning with QLoRA
• Production deployment of ML models
• Full-stack application development

Built by mhdakmal80