Open Source Vector Database & AI Infrastructure Solutions
Zilliz engineers are the original creators of many renowned open-source projects for AI-powered applications, offering comprehensive solutions for building and enhancing your artificial intelligence infrastructure. The Milvus vector database and various accompanying AI tools are specifically designed to simplify data management and optimize the performance of your AI applications.
We are proud to be the maintainers of these popular open source AI infrastructure projects
Explore the following AI tools to acquire essential insights for deploying and utilizing Zilliz's advanced vector search technology, unlocking the potential of unstructured data for maximized AI capabilities.
milvus
Milvus is an open source vector database used to store, index, and manage massive embedding vectors generated by deep neural networks and other machine learning (ML) models.
towhee
Towhee makes it easy to build neural data processing pipelines for AI applications. With hundreds of models, algorithms, and transformations, Towhee helps you encode your unstructured data into embeddings.
attu
Attu is an open-source management tool for Milvus with an intuitive GUI, allowing you to interact easily with your databases. With just a few clicks, you can visualize your cluster status, manage metadata, perform data queries, and much more.
cli
Milvus CLI is a command-line tool that supports database connection, data operations, and import and export of data. Based on Milvus Python SDK, it allows the execution of commands through a terminal using interactive command-line prompts.
feder
Feder is a JavaScript tool designed to aid in comprehending embedding vectors. It visualizes index files from Faiss, HNSWlib, and other ANN libraries to provide insight into how these libraries function.
GPTCache
GPTCache is an open-source tool designed to improve the efficiency and speed of GPT-based applications by implementing a cache to store the responses generated by language models.