GitHub user simon824 edited a discussion: [Proposal] introduce a sub project 
about graph intelligence for hugegraph

Deer all,

Graph intelligence has seen significant growth and popularity in recent years, 
with many applications emerging in different industries. This field is closely 
connected to HugeGraph, which serves as a strong foundation for storing, 
analyzing, and processing graph-based data.

I suggest creating a new Python repository for artificial intelligence related 
to HugeGraph. This repository will include applications and integrations of 
HugeGraph with large language models, graph machine learning, graph neural 
networks, graph embeddings, and more.

By establishing this repository, our goal is to explore the integration of 
HugeGraph with various AI frameworks, providing a comprehensive resource for AI 
practitioners to utilize the power of HugeGraph in their projects.

The repository will consist of the following sub-modules:

1. hugegraph-llm:
This module will house the implementation and research related to large 
language models. It will include runnable demos and can also be used as a 
third-party library, reducing the cost of using graph systems and the 
complexity of building knowledge graphs. Graph systems can help large models 
address challenges like timeliness and hallucination, while large models can 
assist graph systems with cost-related issues. Therefore, this module will 
explore more applications and integration solutions for graph systems and large 
language models. We have already integrated with the LLM application frameworks 
LangChain and Llama-Index, and will provide usage examples in this module.

2. hugegraph-ml:
This module will focus on integrating HugeGraph with graph machine learning, 
graph neural networks, and graph embeddings libraries. It will build an 
efficient and versatile intermediate layer to seamlessly connect with 
third-party graph-related ML frameworks.

3. hugegraph-python-client/computer-client:
The hugegraph-python-client is a Python client for HugeGraph. It is used to 
define graph structures and perform CRUD operations on graph data. Both the 
hugegraph-llm and hugegraph-ml modules will depend on this foundational 
library. Additionally, the client will be integrated with HugeGraph-Computer. 
Graph computation is often necessary for graph learning and preprocessing graph 
data. Developers can significantly improve processing efficiency by leveraging 
HugeGraph-Computer.

If anyone has any ideas or questions about this proposal, please leave a 
comment here for discussion.

GitHub link: https://github.com/apache/incubator-hugegraph/discussions/2318

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