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| title: NL2SQL API | |
| emoji: 🗄️ | |
| colorFrom: blue | |
| colorTo: indigo | |
| sdk: docker | |
| pinned: false | |
| # NL2SQL | |
| A backend Command Line Interface (CLI) framework designed to evaluate and test various NL2SQL models. | |
| **Note:** The frontend interface for this application is currently in progress and not yet available. All interactions are handled via the CLI. | |
| ## Prerequisites & Installation | |
| To run this CLI tool locally, follow these steps to set up your environment: | |
| 1. Activate the Virtual Environment. | |
| - **Windows**: venv\Scripts\Activate | |
| - **macOS/Linux**: source venv/bin/activate | |
| 2. Install Requirements | |
| - Ensure a *requirements.txt* file exists in your project backend folder. | |
| > pip install -r requirements.txt | |
| 3. Configure Environment Variable (.env) | |
| **Note:** Users must generate your own free access token from your https://huggingface.co/settings/tokens to avoid rate limits. | |
| - Create a *.env* file in the *backend/* directory | |
| - Add your Hugging Face *Read* Token to the file. | |
| > HF_TOKEN=your_hugging_face_read_token_here | |
| ## Usage Guide | |
| Once your environment is set up and your token is configured, you can run the CLI application. | |
| 1. Navigate to the Backend Directory | |
| > cd backend | |
| 2. Launch the Application | |
| > python -m app.main | |
| 3. Interacting with the CLI Menu Upon running the command, you will be presented with a main menu. Choose the number corresponding to your desired action: | |
| 1. Running Question to SQL Test: Evaluates how well a model translates natural language queries into executable SQL commands. | |
| 2. Running Question Answering Test: Evaluates the end-to-end process (Question -> SQL -> Database Execution -> Natural Language Answer). | |
| 3. Exit/Quit: Closes the application. | |
| 4. Model Selection & Batch Testing | |
| 1. After selecting either option 1 or 2, the CLI will display a list of available NL2SQL models. | |
| 2. Enter the number/name of the model you wish to test. | |
| 3. Automatic Execution: Once a model is selected, the system will automatically begin running the batch test against the scenarios defined in scripts/test_cases.json. Sit back and wait for the reports to generate in your root folder! | |
| ## 🚧 Roadmap | |
| - Development and integration of a graphical User Interface (Frontend). | |
| - Additional database schema support. |