Implement Graph Memory in AI Assistant

[Aftar-Ahmad-Sami]

Description

This pull request adds a new Jupyter notebook to the mem0 cookbook, demonstrating an AI companion application that utilizes mem0's graph memory capabilities. The notebook showcases how to create an interactive AI assistant that can remember and recall information from previous conversations using OpenAI's GPT-4 model and mem0's memory system.

Key features:

• Integration of OpenAI's GPT-4 with mem0's memory management
• Utilization of Qdrant for vector storage and Neo4j for graph storage
• Interactive conversation loop with memory retention and retrieval

This addition aims to provide mem0 users with a practical example of building an AI companion system, highlighting the power of graph-based memory in conversational AI applications.

Fixes # (No specific issue number, as this is a new feature addition)

Type of change

• [x] New feature (non-breaking change which adds functionality)
• [x] Documentation update

How Has This Been Tested?

The notebook has been tested in Google Colab environment. To reproduce:

1. Open the notebook in Google Colab
2. Set up the required environment variables using Google Colab's userdata
3. Run all cells sequentially
4. Test the interactive conversation loop with various inputs

Checklist:

• [x] My code follows the style guidelines of this project
• [x] I have performed a self-review of my own code
• [x] I have commented my code, particularly in hard-to-understand areas
• [x] My changes generate no new warnings
• [x] I have checked my code and corrected any misspellings

Maintainer Checklist

• [ ] closes #xxxx (Not applicable for this new feature addition)
• [ ] Made sure Checks passed

[CLAassistant]

All committers have signed the CLA.

[Dev-Khant]

Hey @Aftar-Ahmad-Sami Can you please add more relevant example which showcases the use of relations and entities?

[Dev-Khant]

Closing this PR as it has been pretty outdated now, please feel free to reopen it. Thanks.