Update README.md

README.md

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-# text2sql-chatbot
+---
+title: QueryMind — Natural Language to SQL
+emoji: ⚡
+colorFrom: green
+colorTo: teal
+sdk: docker
+pinned: false
+license: mit
+app_port: 7860
+---
+
+# ⚡ QueryMind — Natural Language to SQL
+
+Upload any CSV file and ask questions about your data in plain English.  
+QueryMind converts your question into SQL, runs it on your data, and returns the results instantly.
+
+## How it Works
+
+1. **Upload** your CSV file using the sidebar
+2. **Ask** a question in plain English (e.g. "Show top 5 rows by sales")
+3. **See** the generated SQL and query results in the chat
+
+## Models
+
+This repo contains **two versions** of `app.py` to compare performance:
+
+| File | Model | Size | Speed |
+|------|-------|------|-------|
+| `app_t5.py` | `cssupport/t5-small-awesome-text-to-sql` | ~250MB | Fast (CPU OK) |
+| `app_sqlcoder.py` | `defog/sqlcoder-7b-2` | ~14GB | Slow on CPU, needs GPU |
+
+**To switch models:** rename the desired file to `app.py` before deploying.
+
+## Tech Stack
+
+- **Backend:** FastAPI + Python
+- **Model Inference:** HuggingFace Transformers (PyTorch)
+- **Database:** SQLite (in-memory per session)
+- **Frontend:** Vanilla HTML/CSS/JS (no framework)
+- **Deployment:** Docker on HuggingFace Spaces
+
+## Local Development
+
+```bash
+git clone https://huggingface.co/spaces/<your-username>/<your-space-name>
+cd <your-space-name>
+
+# Install dependencies
+pip install -r requirements.txt
+
+# Run locally
+uvicorn app:app --host 0.0.0.0 --port 7860 --reload
+```
+
+Then open `http://localhost:7860` in your browser.
+
+## Deploying to HuggingFace Spaces (via GitHub)
+
+1. Create a new Space on [huggingface.co/spaces](https://huggingface.co/spaces)
+   - SDK: **Docker**
+   - Connect your GitHub repository in Space settings
+
+2. Push this repo to GitHub — HuggingFace will auto-build & deploy.
+
+## File Structure
+
+```
+├── app.py              ← Active model (rename from app_t5.py or app_sqlcoder.py)
+├── app_t5.py           ← T5-small text-to-SQL (CPU friendly)
+├── app_sqlcoder.py     ← SQLCoder-7B (GPU recommended)
+├── static/
+│   └── index.html      ← Frontend UI
+├── requirements.txt
+├── Dockerfile
+└── README.md
+```
+
+## Notes
+
+- Sessions are in-memory — data is lost when the Space restarts.
+- The T5 model is recommended for free CPU Spaces (fast, lightweight).
+- SQLCoder-7B gives better SQL quality but needs a GPU Space (T4 small or better).