Update README.md

README.md

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-# Roman Empire Q&A Application
-
-https://weaviate-rag.streamlit.app/
-
-This project is a Retrieval-Augmented Generation (RAG) application designed to answer questions related to the Roman Empire. It leverages Weaviate for vector storage and retrieval, OpenAI for generating responses, FastAPI for the backend API, and Next.js for the frontend interface.
-
-
-![RAG-Roman Empire Banner](public/images/workflow.jpg)
-
-## Features
-
-- **Interactive Question-Answering**: Users can input questions about Roman history and culture and receive informative responses.
-- **Sample Questions**: The app provides a list of sample questions to guide users and demonstrate its capabilities.
-- **API Key Management**: Users can securely enter their OpenAI API key via a password input field in the sidebar.
-- **Built With**: The sidebar includes links to the technologies and frameworks used in building the app.
-
-## Getting Started
-
-To run the app locally, follow these steps:
-
-1. Clone this repository to your local machine.
-2. Install the required dependencies by running `pip install -r requirements.txt`.
-3. Create a `.env` file in the root directory of the project and add your Weaviate API key and cluster URL in the following format:
-
-```
-WEAVIATE_API_KEY="your_api_key"
-WEAVIATE_CLUSTER="your_cluster_url"
-```
-
-4. Run the Streamlit app using the command `streamlit run app.py`.
-5. Access the app in your web browser at `localhost:8501`.
+---
+license: mit
+sdk: streamlit
+emoji: 🚀
+colorFrom: yellow
+colorTo: yellow
+---