Can Google Gemini power intelligent conversational AI? This project demonstrates the power of Google's latest Gemini model through a real-time AI Chatbot built with Streamlit, featuring conversation memory and dynamic response generation using cutting-edge Large Language Model technology. Live Demo: https://deploy-llm-chatbot-app-gemini.streamlit.app/ 🤖✨
🔍 Project Overview:
LLM-Powered Conversations: Leverages Google Gemini 2.0 Flash for natural, context-aware dialogue with full chat history retention
Real-time Streaming: Instant responses with typing animation for smooth user experience
Session Persistence: Maintains conversation context across multiple interactions
Responsive Interface: Clean, mobile-friendly Streamlit UI optimized for all devices
Production Deployed: Live at https://deploy-llm-chatbot-app-gemini.streamlit.app/
Error-Resilient: Graceful handling of API quotas and network conditions
🎯 Learning Outcomes:
Integrating Google's Gemini API with Python web frameworks
Building stateful conversational AI with session management
Creating responsive web UIs using Streamlit
Deploying LLM-powered applications to Streamlit Cloud
Handling real-time API quotas and error states
⚙️ Technologies & Tools: Python | Google Gemini API | Streamlit | google-generativeai | python-dotenv
Local Setup: streamlit run main.py Opens: http://localhost:8501
If dependencies missing: pip install streamlit google-generativeai python-dotenv pillow Add your Gemini API key to .env: GOOGLE_API_KEY=your_api_key_here