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AI Chemist: Pioneering the Future of Chemical Science with Gemini Vision Pro

Category: Generative AI

Overview

AI Chemist is a state-of-the-art mobile application designed to revolutionize chemical research. Powered by the advanced Gemini Pro model, the app offers personalized chemical solutions, experimental recommendations, and real-time data analysis. Whether you're a pharmaceutical researcher, environmental chemist, or materials scientist, AI Chemist provides intelligent assistance for efficient, data-driven research.

Key Features

  • Experiment Design: Customized experiment designs and chemical synthesis routes based on user inputs, lab conditions, and research goals.
  • Real-Time Monitoring: Track reactions in real-time with automated suggestions to optimize reaction conditions and improve yield and purity.
  • Data-Driven Insights: Receive actionable feedback on experimental outcomes, enhancing the accuracy and efficiency of research.

Example Scenarios

1. Pharmaceutical Research

Dr. Alvarez, a pharmaceutical researcher, inputs bacterial enzyme targets and chemical structures into AI Chemist. The app suggests potential compounds and synthesis pathways. Real-time monitoring adjusts reaction conditions, providing feedback on yield and purity, accelerating drug discovery.

2. Green Chemistry

James, an environmental chemist, is developing an eco-friendly pesticide. AI Chemist suggests sustainable synthesis methods and evaluates biodegradability and toxicity. The app helps James ensure his product meets regulatory standards while minimizing waste.

3. Polymer Science

Dr. Liu, a materials scientist, aims to create a polymer with high tensile strength. AI Chemist suggests monomers and polymerization techniques while monitoring reactions in real-time to optimize polymer properties.

Tech Stack

  • Python
  • Deep Learning
  • Streamlit

Installation

  1. Clone the repository:
  2. git clone https://github.com/Sawanmahna/AI_Chemist.git
    cd AI_Chemist
    
  3. Install dependencies:
  4. pip install -r requirements.txt
    
  5. Set up environment variables:
  6. Create a .env file in the root directory and add your Google API key:

    GOOGLE_API_KEY=your_api_key_here
    
  7. Run the application:
  8. streamlit run app.py
    

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