PR Description: Gemini AI Integration in Python

Overview:
This PR integrates the Gemini AI model into a Python environment, allowing for enhanced natural language processing capabilities within our application. The integration enables developers to leverage Gemini's advanced conversational AI features, including text generation, sentiment analysis, and context-aware responses.

Key Features:

• Gemini AI Model Integration: Gemini AI, known for its contextual understanding and dynamic response generation, is now accessible within our Python-based application.
• Enhanced Text Generation: Ability to generate coherent, contextually relevant responses to input queries or requests.
• Sentiment Analysis: The integration allows for understanding and reacting to the sentiment of user inputs, improving interactions.
• Adaptability: The model adapts to different conversational tones, offering more personalized experiences.

Technical Details:

• The Gemini AI model has been integrated via an API connection, utilizing Python libraries such as requests and json for data handling and communication with the AI engine.
• A wrapper function was created to interface with the AI and handle responses in a structured format.
• Error handling has been implemented to manage unexpected inputs or communication failures with the Gemini service.

Impact:
This integration improves the quality and responsiveness of interactions, enabling more natural conversations with users. It also lays the foundation for future AI-based features, such as automated content creation and personalized recommendations.