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Project: Building a Simple Chatbot with Memory

Technologies Used

Flask: A lightweight and flexible Python web framework that provides the foundation for building the chatbot application. It handles routing, request processing, and template rendering while maintaining a small footprint.
Streamlit: A powerful Python framework specifically designed for creating data applications and interactive web interfaces. It offers built-in components and layouts that make it easier to build user-friendly chat interfaces.
OpenAI API: Provides access to advanced language models like GPT-4o, enabling natural language processing capabilities. This API handles the core conversational intelligence of the chatbot, generating contextually relevant responses.
SQLite: A serverless, self-contained database engine that provides reliable storage for conversation history. It's perfect for development and smaller applications, requiring no separate server process while maintaining ACID compliance.

Flask: A lightweight and flexible Python web framework that provides the foundation for building the chatbot application. It handles routing, request processing, and template rendering while maintaining a small footprint.
Streamlit: A powerful Python framework specifically designed for creating data applications and interactive web interfaces. It offers built-in components and layouts that make it easier to build user-friendly chat interfaces.
OpenAI API: Provides access to advanced language models like GPT-4o, enabling natural language processing capabilities. This API handles the core conversational intelligence of the chatbot, generating contextually relevant responses.
SQLite: A serverless, self-contained database engine that provides reliable storage for conversation history. It's perfect for development and smaller applications, requiring no separate server process while maintaining ACID compliance.

Flask: A lightweight and flexible Python web framework that provides the foundation for building the chatbot application. It handles routing, request processing, and template rendering while maintaining a small footprint.
Streamlit: A powerful Python framework specifically designed for creating data applications and interactive web interfaces. It offers built-in components and layouts that make it easier to build user-friendly chat interfaces.
OpenAI API: Provides access to advanced language models like GPT-4o, enabling natural language processing capabilities. This API handles the core conversational intelligence of the chatbot, generating contextually relevant responses.
SQLite: A serverless, self-contained database engine that provides reliable storage for conversation history. It's perfect for development and smaller applications, requiring no separate server process while maintaining ACID compliance.

Flask: A lightweight and flexible Python web framework that provides the foundation for building the chatbot application. It handles routing, request processing, and template rendering while maintaining a small footprint.
Streamlit: A powerful Python framework specifically designed for creating data applications and interactive web interfaces. It offers built-in components and layouts that make it easier to build user-friendly chat interfaces.
OpenAI API: Provides access to advanced language models like GPT-4o, enabling natural language processing capabilities. This API handles the core conversational intelligence of the chatbot, generating contextually relevant responses.
SQLite: A serverless, self-contained database engine that provides reliable storage for conversation history. It's perfect for development and smaller applications, requiring no separate server process while maintaining ACID compliance.