fix(llm): enable tasks concurrency configs in Gradio (#188) fix #176 Blocking and Queuing Behavior: Gradio, by default, has a concurrency limit of 1. This causes blocking when multiple users or windows are accessing the application simultaneously. No Asynchronous Execution: The current implementation does not specify concurrency_limit, leading to sequential execution. Queue Configuration: If queue() is not configured properly, tasks are processed one at a time. --------- Co-authored-by: imbajin <jin@apache.org>
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.
hugegraph-llm 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 help graph systems with cost-related issues. Therefore, this module will explore more applications and integration solutions for graph systems and large language models. (GraphRAG/Agent)hugegraph-ml 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.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.The project homepage contains more information about hugegraph-ai.
And here are links of other repositories:
./style/code_format_and_analysis.sh to format your code before submitting a PR. (Use pylint to check code style)hugegraph-ai is licensed under Apache 2.0 License.