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| title: 2 Natural Lang2SQL Query | |
| emoji: 🐠 | |
| colorFrom: indigo | |
| colorTo: blue | |
| sdk: gradio | |
| sdk_version: 5.30.0 | |
| app_file: app.py | |
| pinned: false | |
| # 🧠 Natural Language to SQL Query Generator with Results 🧠 | |
| Convert human-readable questions into valid SQL queries using a combination of **semantic search**, **LLMs**, and **Gradio UI** — and see the **query results** live from your database! | |
| ## 🚀 Features | |
| * 🔍 **Understand Natural Language:** Converts simple English questions to SQL using powerful embeddings and LLMs (LLaMA3 via Groq). | |
| * 🧠 **Smart Table Matching:** Uses SentenceTransformer-based embeddings and cosine similarity to pick the most relevant tables. | |
| * 🛠️ **Dynamic SQL Generation:** Automatically generates JOINs when needed based on metadata. | |
| * 📄 **Predefined Schema:** Works with three tables — `student`, `employee`, and `course`. | |
| * 🧪 **Instant Execution:** Runs the generated SQL query and shows the result in the UI. | |
| * 🌐 **Interactive UI:** Clean, web-based interface built with Gradio. | |
| --- | |
| ## 🧰 Tech Stack | |
| * Python 🐍 | |
| * [Gradio](https://gradio.app/) — For the frontend UI | |
| * [Sentence Transformers](https://www.sbert.net/) — For encoding metadata and queries | |
| * [Groq API](https://console.groq.com/) — For LLaMA3-powered SQL generation | |
| * SQLite — Lightweight DB backend | |
| --- | |
| ## 🗃️ Tables Overview | |
| ### 🧑🎓 `student` | |
| | Column | Description | | |
| | -------------------- | -------------------- | | |
| | student\_id | Unique ID of student | | |
| | first\_name | First name | | |
| | last\_name | Last name | | |
| | date\_of\_birth | Birthdate | | |
| | email | Email address | | |
| | phone\_number | Contact number | | |
| | major | Field of study | | |
| | year\_of\_enrollment | Year enrolled | | |
| ### 👨💼 `employee` | |
| | Column | Description | | |
| | ----------------- | --------------------- | | |
| | employee\_id | Unique ID of employee | | |
| | first\_name | First name | | |
| | last\_name | Last name | | |
| | email | Email address | | |
| | department | Department name | | |
| | position | Job title | | |
| | salary | Salary | | |
| | date\_of\_joining | Joining date | | |
| ### 📘 `course` | |
| | Column | Description | | |
| | -------------- | ------------------------------ | | |
| | course\_id | Unique ID of course | | |
| | course\_name | Course title | | |
| | course\_code | Code for the course | | |
| | instructor\_id | Refers to `employee_id` | | |
| | department | Department offering the course | | |
| | credits | Number of credits | | |
| | semester | Semester offered | | |
| --- | |
| ## ⚙️ Setup Instructions | |
| ### 1. Clone the Repo | |
| ```bash | |
| git clone https://github.com/your-username/sql-query-generator.git | |
| cd sql-query-generator | |
| ``` | |
| ### 2. Install Dependencies | |
| ```bash | |
| pip install -r requirements.txt | |
| ``` | |
| ### 3. Set Up `.env` | |
| Create a `.env` file in the root directory and add your [Groq API Key](https://console.groq.com/): | |
| ``` | |
| groq_api_key=your_groq_api_key_here | |
| ``` | |
| ### 4. Launch the App | |
| ```bash | |
| python app.py | |
| ``` | |
| Or just run: | |
| ```bash | |
| streamlit run app.py # If you're using a streamlit version | |
| ``` | |
| ### 5. Use the Web Interface | |
| Go to the URL provided in the terminal (typically `http://127.0.0.1:7860`) and enter your natural language query. | |
| --- | |
| ## 🧪 Sample Queries | |
| | Natural Language Query | Action | | |
| | --------------------------------------------------- | ----------------------------- | | |
| | "List all students enrolled in 2022" | Filters `student` table | | |
| | "Show all employees in Computer Science department" | Filters `employee` table | | |
| | "Get courses taught in Fall semester" | Filters `course` table | | |
| | "Find course names and instructor names" | Joins `course` and `employee` | | |
| --- | |
| ## 🔒 Security & Limitations | |
| * This is a prototype/demo and should not be used in production without input sanitization. | |
| * Currently limited to SELECT queries only. | |
| * Works only with the predefined schema (3 tables). | |
| --- | |
| ## 🤝 Contributing | |
| Contributions are welcome! Feel free to open an issue or pull request for: | |
| * New table additions | |
| * Better embeddings | |
| * UI/UX improvements | |
| * Model optimization | |
| ## 👨💻 Author | |
| Built by \Jamgala Bala Swaroop | |
| 📫 Email: [jbsroop@gmail.com](mailto:jbsroop@gmail.com) | |