Adding database capabilities to the chat-interface.py to make it more personalized

[sagnik-create]

🐛 Issue: Volatile Local Storage for Chat Data

🔍 Problem

Currently, the chat data is stored in cache storage, which resets every time the website is relaunched. This results in a loss of user context and chat history, negatively impacting the overall user experience.

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💡 Proposed Solution

Implement a persistent and scalable database-backed storage system using SQLAlchemy with SQLite to manage user sessions and chat data.

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✅ Goals

• Integrate SQLAlchemy for ORM-based database interaction
• Use SQLite to manage chat sessions and memory locally (with potential to scale)
• Create dynamic user-specific tables or entries for storing conversation history
• Establish clean data retrieval and storage mechanisms for seamless integration with the chatbot engine
• Enable personalized chatbot experiences by persisting contextual memory per user

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🧠 Benefits

• Persistent chat memory across sessions
• Personalized experience per user
• Foundation for scaling up to multi-user or multi-session architectures

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📌 Notes

This issue was previously identified but hasn’t been fully implemented.
Kindly assign this to me so I can work on a resolution.

[sagnik-create]

@eccentriccoder01 Created the issue

[eccentriccoder01]

Thanks for outlining this so clearly @sagnik-create! Assigning this issue to you, 5 days for this. All the best!

[sagnik-create]

Hi I have created pull request and please give me your valuable suggestions and also tell me if I done any mistakes, as I am still new to creating pull requests and merge conflicts