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hugegraph-ai
hugegraph-ai aims to explore the integration of HugeGraph with artificial
intelligence (AI) and provide comprehensive support for developers to leverage HugeGraph's AI capabilities
in their projects.
Modules
- hugegraph-llm:The
hugegraph-llmwill 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 help graph systems with cost-related issues. Therefore, this module will explore more applications and integration solutions for graph systems and large language models. - hugegraph-ml: The
hugegraph-mlwill 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. - hugegraph-python-client: The
hugegraph-python-clientis a Python client for HugeGraph. It is used to define graph structures and perform CRUD operations on graph data. Both thehugegraph-llmandhugegraph-mlmodules will depend on this foundational library.
Contributing
- Welcome to contribute to HugeGraph, please see Guidelines for more information.
- Note: It's recommended to use GitHub Desktop to greatly simplify the PR and commit process.
- Code format: Please run
./style/code_format_and_analysis.shto format your code before submitting a PR. - Thank you to all the people who already contributed to HugeGraph!
License
hugegraph-ai is licensed under Apache 2.0 License.
Contact Us
- GitHub Issues: Feedback on usage issues and functional requirements (quick response)
- Feedback Email: dev@hugegraph.apache.org (subscriber only)
- WeChat public account: Apache HugeGraph, welcome to scan this QR code to follow us.