Metadata Schema Builder Interface

Live link Metadata Retrieval

Overview

Welcome to the Metadata Schema Builder Interface! This web application allows users to generate a metadata schema based on an uploaded experimental machine data file. By leveraging the power of a large language model (LLM), the interface processes the input data and outputs a JSON file that represents the metadata schema. This tool is designed to simplify the creation of metadata schemas, making it easier to standardize data across experiments and systems.

Features

• File Upload: Upload your experimental machine data file in the supported format.
• Automated Schema Generation: The interface uses an LLM model to analyze the uploaded data and generate a metadata schema.
• Language Selection: Choose the language for the responses.
• Output: Download the generated metadata schema as a file for further use or integration.
• User-Friendly Interface: The web interface is designed to be intuitive and easy to use, even for users with minimal technical expertise.

Installation

Clone the Repository

git clone https://github.com/teman67/LLM_Metadata.git
cd LLM_Metadata

Set Up a Virtual Environment (Optional but Recommended)

python -m .venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`

Install Required Packages

pip install -r requirements.txt

Set Up Environment Variables

Create a .env file in the root directory with the following content:

API_KEY=your_api_key
API_URL=your_api_url

Replace your_api_key and your_api_url with your actual API key and URL.

Usage

Run the Application

streamlit run app.py

Access the App

Open your web browser and go to http://localhost:8501.

How to Use

Upload a File and Ask a Question

1. Upload a file (supports .txt, .docx, .json, .dat).
2. Enter your question about the file.
3. Select the language for the response.
4. Click "Submit Question about Uploaded File" to get the response.

Ask a Question Directly

1. Enter your question in the text area.
2. Select the language for the response.
3. Click "Submit Question Directly" to receive the answer.

Model Selection

• Choose a model from the dropdown menu.

Conversation History

• View and download the conversation history using the provided button.

Configuration

• API Key: Ensure your API key is set in the .env file.
• API URL: Specify the API endpoint URL in the .env file.
• Models: Modify the list of available models in the source code as needed.

Troubleshooting

• Missing API Key: Make sure the API_KEY is correctly set in the .env file.
• File Upload Issues: Verify file format and encoding, and ensure the file is correctly processed.
• Model Errors: Confirm that the API URL and model configurations are accurate.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

For questions or issues, please contact [email protected].

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Enjoy exploring different language models with this app!