Update README.md

README.md

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-# Knowledge Graph Generator
-
-A Streamlit application that extract graph data (entities and relationships) from text input using LangChain and OpenAI's GPT models, and generates interactive graphs.
-![CleanShot 2025-05-28 at 13 11 46](https://github.com/user-attachments/assets/4fef9158-8dd8-432d-bb8a-b53953a82c6c)
-
-👉 This repo is part of my project tutorial on Youtube:
-[![](https://img.youtube.com/vi/O-T_6KOXML4/0.jpg)](https://www.youtube.com/watch?v=O-T_6KOXML4)
-
-## Features
-
-- Two input methods: text upload (.txt files) or direct text input
-- Interactive knowledge graph visualization
-- Customizable graph display with physics-based layout
-- Entity relationship extraction powered by OpenAI's GPT-4o model
-
-## Installation
-
-### Prerequisites
-
-- Python 3.8 or higher
-- OpenAI API key
-
-### Dependencies
-
-The application requires the following Python packages:
-
-- langchain (>= 0.1.0): Core LLM framework
-- langchain-experimental (>= 0.0.45): Experimental LangChain features
-- langchain-openai (>= 0.1.0): OpenAI integration for LangChain
-- python-dotenv (>= 1.0.0): Environment variable support
-- pyvis (>= 0.3.2): Graph visualization
-- streamlit (>= 1.32.0): Web UI framework
-
-Install all required dependencies using the provided requirements.txt file:
-
-```bash
-pip install -r requirements.txt
-```
-
-### Setup
-
-1. Clone this repository:
-   ```bash
-   git clone [repository-url]
-   cd knowledge_graph_app_2
-   ```
-
-   Note: Replace `[repository-url]` with the actual URL of this repository.
-
-2. Create a `.env` file in the root directory with your OpenAI API key:
-   ```
-   OPENAI_API_KEY=your_openai_api_key_here
-   ```
-
-## Running the Application
-
-To run the Streamlit app:
-
-```bash
-streamlit run app.py
-```
-
-This will start the application and open it in your default web browser (typically at http://localhost:8501).
-
-## Usage
-
-1. Choose your input method from the sidebar (Upload txt or Input text)
-2. If uploading a file, select a .txt file from your computer
-3. If using direct input, type or paste your text into the text area
-4. Click the "Generate Knowledge Graph" button
-5. Wait for the graph to be generated (this may take a few moments depending on the length of the text)
-6. Explore the interactive knowledge graph:
-   - Drag nodes to rearrange the graph
-   - Hover over nodes and edges to see additional information
-   - Zoom in/out using the mouse wheel
-   - Filter the graph for specific nodes and edges.
-
-## How It Works
-
-The application uses LangChain's experimental graph transformers with OpenAI's GPT-4o model to:
-1. Extract entities from the input text
-2. Identify relationships between these entities
-3. Generate a graph structure representing this information
-4. Visualize the graph using PyVis, a Python interface for the vis.js visualization library
-
-## License
-
-This project is licensed under the MIT License - a permissive open source license that allows for free use, modification, and distribution of the software.
-
-For more details, see the [MIT License](https://opensource.org/licenses/MIT) documentation.
+---
+title: Knowledge Graph Generator
+emoji: 🚀
+colorFrom: red
+colorTo: red
+sdk: docker
+app_port: 8501
+tags:
+- streamlit
+pinned: false
+short_description: Extract graph data from text input and generates interactive
+license: mit
+---
+
+# Welcome to Streamlit!
+
+Edit `/src/streamlit_app.py` to customize this app to your heart's desire. :heart:
+
+If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
+forums](https://discuss.streamlit.io).