semitechnologies/weaviate
The AI-native database for a new generation of software
Weaviate is an open-source vector database that simplifies the development of AI applications. Built-in vector and hybrid search, easy-to-connect machine learning models, and a focus on data privacy enable developers of all levels to build, iterate, and scale AI capabilities faster.
To get started quickly, have a look at one of these pages:
For more details, read through the summary on this page or see the system documentation.
Weaviate uses state-of-the-art machine learning (ML) models to turn your data - text, images, and more - into a searchable vector database.
Here are some highlights.
Weaviate is fast. The core engine can run a 10-NN nearest neighbor search on millions of objects in milliseconds. See benchmarks.
Weaviate can vectorize your data at import time. Or, if you have already vectorized your data, you can upload your own vectors instead.
Modules give you the flexibility to tune Weaviate for your needs. More than two dozen modules connect you to popular services and model hubs such as OpenAI, Cohere, VoyageAI and HuggingFace. Use custom modules to work with your own models or third party services.
Weaviate is built with scaling, replication, and security in mind so you can go smoothly from rapid prototyping to production at scale.
Weaviate doesn't just power lightning-fast vector searches. Other superpowers include recommendation, summarization, and integration with neural search frameworks.
Software Engineers
Data Engineers
Data Scientists
A Weaviate vector database can search text, images, or a combination of both. Fast vector search provides a foundation for chatbots, recommendation systems, summarizers, and classification systems.
Here are some examples that show how Weaviate integrates with other AI and ML tools:
These demos are working applications that highlight some of Weaviate's capabilities. Their source code is available on GitHub.
Weaviate exposes a GraphQL API and a REST API. Starting in v1.23, a new gRPC API provides even faster access to your data.
Weaviate provides client libraries for several popular languages:
There are also community supported libraries for additional languages.
Free, self-paced courses in Weaviate Academy teach you how to use Weaviate. The Tutorials repo has code for example projects. The Recipes repo has even more project code to get you started.
The Weaviate blog and podcast regularly post stories on Weaviate and AI.
Here are some popular posts:
At Weaviate, we love to connect with our community. We love helping amazing people build cool things. And, we love to talk with you about you passion for vector databases and AI.
Please reach out, and join our community:
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docker pull semitechnologies/weaviate