Using Weaviate Modules
Explore and integrate Weaviate's extensive module ecosystem for functionalities like Q&A, summarization, and more.
Weaviate Modules Introduction
Weaviate's power comes from its flexible architecture, which can be extended using modules. These modules add specialized functionalities directly to your Weaviate instance.
Think of them as plugins that enhance Weaviate's core capabilities. They can handle tasks like generating embeddings, performing Q&A, or even processing images.
Why Use Weaviate Modules?
Modules streamline your data pipeline by integrating advanced AI functionalities directly into your vector database. This means:
- Automatic Vectorization: Weaviate can create embeddings for you.
- Enhanced Search: Add capabilities like Q&A or summarization to queries.
- Simplified Development: Less external code needed for common AI tasks.
- Multi-modal Support: Handle various data types like text and images.
All lessons in this course
- Semantic Search & Hybrid Search
- Using Weaviate Modules
- Backup and Restore Strategies
- Multi-Tenancy in Weaviate