Update README.md

README.md

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 title: Beta Lactam Demo
-emoji: 🚀
+emoji: 📚
 colorFrom: gray
 colorTo: red
 sdk: streamlit
@@ -11,4 +11,65 @@ license: mit
 short_description: app to generate and view beta-lactam molecules
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Beta-Lactam Molecule Generator and Viewer
+
+## Overview
+
+This application demonstrates a drug discovery pipeline that allows users to:
+
+Generate novel beta-lactam molecules using a generative AI model.
+View the generated molecules with options to display and copy SMILES or SAFE strings.
+Predict ADMET properties for the generated molecules using ADMET-AI.
+
+## Features
+
+Molecule Generation:
+Generates up to 5 beta-lactam molecules at a time.
+Users can adjust the creativity (temperature) of the generation process.
+Generated molecules are named 'Mol01' to 'Mol05'.
+Molecule Viewing:
+Displays molecule structures using Streamlit.
+Option to view molecules as SMILES or SAFE strings.
+Provides copy-to-clipboard functionality for molecule strings.
+ADMET Property Prediction:
+Integrates ADMET-AI to predict properties such as absorption, distribution, metabolism, excretion, and toxicity.
+Displays predicted properties alongside each molecule.
+
+## How to Use the App
+
+Set Generation Parameters:
+Use the sidebar to adjust the creativity (temperature) slider.
+Select the number of molecules to generate (maximum of 5).
+Choose String Format:
+Select whether to display molecule strings as SMILES or SAFE.
+Generate Molecules:
+Click the 'Generate Molecules' button.
+Generated molecules will appear with their structures, strings, and predicted ADMET properties.
+Copy Molecule Strings:
+Use the 'Copy' button under each molecule to copy the SMILES or SAFE string to your clipboard.
+Installation and Deployment
+
+
+## Technical Details
+
+Generative Model: Utilizes a pre-trained BART model fine-tuned on beta-lactam structures.
+ADMET Predictions: Uses the ADMET-AI library to predict molecular properties.
+Visualization: Employs RDKit and SAFE encoding for molecule rendering.
+Frameworks and Libraries:
+Streamlit for the web interface.
+Transformers library for model loading and generation.
+RDKit for cheminformatics.
+Pandas for data manipulation.
+
+
+
+The application is intended for demonstration purposes and may require adjustments for production use.
+License
+
+This project is licensed under the terms of the MIT license.
+
+## Acknowledgements
+
+ADMET-AI: For providing tools to predict ADMET properties.
+OpenAI and Hugging Face: For models and tools used in molecule generation.
+RDKit: For cheminformatics functionalities.