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README.md

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-# Project overview and instructions 
+# Materials AI App
+
+Materials AI App is a production-grade, full-stack web application designed for advanced text mining and data extraction in the materials science and battery research domains. It leverages domain-specific models (MatSciBERT, MaterialBERT, BatteryBERT) along with OpenAI's GPT‑4 for natural language summarization and Q&A. The application uses FastAPI for the backend API and Gradio for an interactive demo interface, and it is deployed on Hugging Face Spaces.
+
+## Features
+
+- **Domain-Specific Text Mining:**  
+  Extract entities and relations (e.g., material properties, synthesis methods) from scientific literature using specialized BERT models.
+
+- **Interactive Q&A:**  
+  Ask questions related to materials science and battery research and receive context-aware answers.
+
+- **Summarization:**  
+  Generate plain-language summaries of research text with GPT‑4.
+
+- **User-Friendly Interface:**  
+  A Gradio-based demo allows for quick testing and visualization of extracted information.
+
+- **Scalable & Secure:**  
+  Built using FastAPI with containerization (Docker) and CI/CD practices, ensuring robust production deployment on Hugging Face Spaces.
+
+## Repository Structure
+
+/materials-ai-app ├── app │ ├── init.py │ ├── main.py # FastAPI backend server │ ├── models.py # Domain model loading and inference functions │ ├── openai_integration.py # OpenAI helper functions (e.g., summarization) │ └── utils.py # Utility functions (e.g., text/PDF parsing) ├── gradio_app.py # Gradio demo interface for interactive Q&A and extraction ├── Dockerfile # Docker configuration for containerization ├── requirements.txt # List of Python dependencies └── README.md # Project documentation (this file)
+
+bash
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+
+## Installation
+
+1. **Clone the Repository:**
+   ```bash
+   git clone https://huggingface.co/spaces/mgbam/materials-ai-app
+   cd materials-ai-app
+Set Up a Virtual Environment:
+
+bash
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+python -m venv venv
+source venv/bin/activate  # On Windows use: venv\Scripts\activate
+Install Dependencies:
+
+bash
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+pip install -r requirements.txt
+Configure Environment Variables: Set the following environment variables (e.g., in a .env file or your shell):
+
+OPENAI_API_KEY: Your OpenAI API key.
+
+API_URL: URL of your FastAPI backend (if different from localhost).
+
+Running Locally
+Backend API
+Start the FastAPI server:
+
+bash
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+uvicorn app.main:app --reload
+Access the API at http://localhost:8000.
+
+Gradio Demo
+In another terminal, run:
+
+bash
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+python gradio_app.py
+This launches the interactive Gradio interface for testing extraction and summarization.
+
+Deployment
+This repository is configured for deployment on Hugging Face Spaces. Simply push your changes to the repository, and Hugging Face Spaces will build and deploy your app automatically.
+
+Alternatively, you can use the provided Dockerfile:
+
+bash
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+docker build -t materials-ai-app .
+docker run -p 8000:8000 materials-ai-app
+Contributing
+Contributions, issues, and feature requests are welcome! Please check the issues page for more details.
+
+References
+MatSciBERT on Hugging Face
+
+Hugging Face Spaces Documentation
+
+OpenAI API Documentation
+
+License
+This project is licensed under the MIT License.
+
+Contact
+For any questions or feedback, please reach out to [[email protected]].
+
+yaml
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+
+---
+
+You can adjust this template to suit your project's specifics and include any additional sections that might be relevant.