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Gemini ChatBot Demo | Gemini API Integration with Flask | highlight.js | marked.js | ChatGPT API

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Professional ChatBot Portfolio Demo | ChatGPT-Like Interface with Gemini API Integration
In this video, I showcase my professional chatbot portfolio project, designed to mimic popular AI conversational interfaces like ChatGPT. The chatbot is built using Flask, and integrates with the Gemini API to generate intelligent responses and maintain conversation context.
Key Features Demonstrated:
1. ChatGPT-Like Interface: Clean, user-friendly design for seamless conversations.
2. Gemini API Integration: The chatbot uses the Gemini API to generate responses and handle multi-turn conversations by maintaining context.
3. Markdown Support: Bot responses include rich text formatting like bold, italics, bullet points, and headings.
5. Auto-Resizing Input Field: The input box expands dynamically as the user types long questions or sentences.
6. Mobile-Responsive Design: The interface is optimized for mobile users, ensuring a smooth experience across devices.
Technology Stack:
1. Flask (Python) for the backend.
4. Gemini API for response generation and conversation management.
Check out this video to see how the chatbot handles complex conversations, formats code, and provides context-aware responses!
Reach Out:
#ChatbotPortfolio
#ChatGPTClone
#ChatbotDemo
#AIChatbot
#GeminiAPI
#FlaskChatbot
#PythonChatbot
#ChatbotInterfaceDesign
#MarkdownChatbot
#CodeHighlighting
#NLPChatbot
#ChatbotWithAPIIntegration
#ChatbotProject
#AIDevelopment
#ProfessionalChatbot
#ChatbotTutorial
#ChatbotWebApp
#PythonFlaskProject
#InteractiveChatbot
#AIConversation
In this video, I showcase my professional chatbot portfolio project, designed to mimic popular AI conversational interfaces like ChatGPT. The chatbot is built using Flask, and integrates with the Gemini API to generate intelligent responses and maintain conversation context.
Key Features Demonstrated:
1. ChatGPT-Like Interface: Clean, user-friendly design for seamless conversations.
2. Gemini API Integration: The chatbot uses the Gemini API to generate responses and handle multi-turn conversations by maintaining context.
3. Markdown Support: Bot responses include rich text formatting like bold, italics, bullet points, and headings.
5. Auto-Resizing Input Field: The input box expands dynamically as the user types long questions or sentences.
6. Mobile-Responsive Design: The interface is optimized for mobile users, ensuring a smooth experience across devices.
Technology Stack:
1. Flask (Python) for the backend.
4. Gemini API for response generation and conversation management.
Check out this video to see how the chatbot handles complex conversations, formats code, and provides context-aware responses!
Reach Out:
#ChatbotPortfolio
#ChatGPTClone
#ChatbotDemo
#AIChatbot
#GeminiAPI
#FlaskChatbot
#PythonChatbot
#ChatbotInterfaceDesign
#MarkdownChatbot
#CodeHighlighting
#NLPChatbot
#ChatbotWithAPIIntegration
#ChatbotProject
#AIDevelopment
#ProfessionalChatbot
#ChatbotTutorial
#ChatbotWebApp
#PythonFlaskProject
#InteractiveChatbot
#AIConversation