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๐Ÿ‘จโ€๐ŸซThis project was developed under the guidance of Mr. Lokesh Sir as part of the AI & ML Training Program. It explores LLM integration using Google Gemini APIs with a custom UI built on Streamlit.

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๐Ÿค– Gemini Pro Chat

Gemini Pro Chat is an AI-powered chatbot interface built with Googleโ€™s Gemini API and Streamlit, capable of responding to text and image prompts using large language models like Gemini 1.5 Flash and Gemini Pro Vision. It features a sleek UI with chat history, model selection, image uploads, and more.

Screenshot


๐Ÿš€ Features

  • ๐Ÿง  Text-based chatting using Gemini 1.5 Flash
  • ๐Ÿ–ผ๏ธ Image prompt support with Gemini Pro Vision
  • ๐Ÿ“‹ Persistent Chat History with clickable summaries
  • ๐Ÿงช Model selection (Gemini 1.5 Flash, Pro, Ultra)
  • ๐Ÿงฐ Beautiful UI with custom CSS styling
  • ๐ŸŒ Powered by Google Generative AI via google.generativeai

๐Ÿงช Tech Stack

๐Ÿ’ป Frontend

  • Streamlit for UI
  • Custom CSS (inside Python) for layout and style
  • Markdown and HTML for chat bubble rendering

๐Ÿง  Backend

  • Python
  • Gemini API (Google Generative AI) via google.generativeai
  • LangChain / Gemini SDK
  • Pillow (PIL) for image processing

๐Ÿ“ Project Structure

  • Gemini-Pro-Chat/
  • โ”œโ”€โ”€ app.py # Main Streamlit application
  • โ”œโ”€โ”€ Screenshot 2025-07-27 154923.png # UI Screenshot for README
  • โ”œโ”€โ”€ requirements.txt # Python dependencies
  • โ””โ”€โ”€ README.md # Project documentation

๐Ÿ’ก How to Use

๐Ÿ”ง Setup Instructions

  1. Clone the repository
    git clone https://github.com/your-username/Gemini-Pro-Chat.git
    cd Gemini-Pro-Chat
    

๐Ÿค– How It Works

  • User types a message and optionally uploads an image
  • The selected Gemini model responds with a smart reply
  • Gemini Pro Vision handles images with prompts
  • Chat history is maintained using Streamlit session state
  • All responses are rendered beautifully using Markdown & custom HTML

๐Ÿ”ฎ Future Improvements

  • ๐Ÿ—‚๏ธ Chat history export/download
  • ๐Ÿ’ฌ Voice-to-text input
  • ๐ŸŒ Multilingual support
  • โ˜๏ธ Deployment on Streamlit Cloud or Render

๐Ÿ™Œ Acknowledgements

  • ๐Ÿค– Google Gemini API
  • ๐ŸŽจ Streamlit for the front-end
  • ๐Ÿง‘โ€๐Ÿซ Mr. Lokesh Sir for continuous support

About

๐Ÿ‘จโ€๐ŸซThis project was developed under the guidance of Mr. Lokesh Sir as part of the AI & ML Training Program. It explores LLM integration using Google Gemini APIs with a custom UI built on Streamlit.

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