Context-Based Data Query Retriever:

The Context-Based Data Query Retriever is a project aimed at retrieving relevant information from a spacecraft dataset based on natural language queries. It utilizes a CSV (Comma-Separated Values) formatted dataset containing spacecraft-related information. The project provides a user-friendly HTML frontend where users can input their queries in natural language. Flask, a Python web framework, is used to send the queries from the frontend to the backend Python code for processing. The backend code then generates answers based on the provided queries.

Features:

Natural language query input: Users can input their queries in natural language, making it easier and more intuitive to interact with the system. CSV dataset: The project uses a CSV dataset to store spacecraft-related information. This dataset can be customized or expanded to include additional data if desired. Flask framework: Flask is employed to handle the communication between the HTML frontend and the Python backend. It provides a straightforward and efficient way to send queries and receive responses. Context-based retrieval: The system retrieves relevant information based on the context of the query, enabling users to obtain accurate and meaningful results. Answer generation: The backend Python code processes the queries and generates informative answers based on the dataset, providing users with the desired information.

Setup and Usage:

To set up and use the Context-Based Data Query Retriever project, follow these steps:

1. Clone the repository: git clone https://github.com/your-username/context-based-query-retriever.git

2. Navigate to the project directory: cd context-based-query-retriever

3. Install the required dependencies: pip install -r requirements.txt

4. Prepare your spacecraft dataset: Replace the existing dataset.csv file with your own CSV dataset. Ensure that the dataset follows the required format.

5. Start the Flask server: Run the following command: python app.py

6. Open your web browser and go to http://localhost:5000 to access the HTML frontend.

7. Input your natural language query in the provided field and click the "Submit" button.

8. The backend code will process your query and generate an answer based on the dataset.

9. The answer will be displayed on the frontend, providing you with the relevant information based on your query.

Customization:

Here are a few ways you can customize and extend the Context-Based Data Query Retriever project:

Dataset: Replace the provided dataset.csv file with your own dataset, ensuring it follows the required format. You can expand or modify the dataset to include additional spacecraft-related information as needed.

Frontend: Modify the HTML templates (templates/index.html) to change the layout, add new elements, or improve the user interface based on your requirements.

Backend: Adjust the backend Python code (app.py) to enhance the query processing logic or incorporate more advanced techniques for information retrieval.