CrewAI
CrewAI is a framework for building multi-agent applications.
CrewAI and Weaviate
Weaviate is a supported vector search tool in CrewAI. It enables you to run semantic search queries over your documents stored in your Weaviate cluster.
You can initialize the tool with:
from crewai_tools import WeaviateVectorSearchTool
# Initialize the tool
tool = WeaviateVectorSearchTool(
collection_name='example_collections',
limit=3,
weaviate_cluster_url="https://your-weaviate-cluster-url.com",
weaviate_api_key="your-weaviate-api-key",
)
Our Resources
The resources are broken into two categories:
Hands on Learning: Build your technical understanding with end-to-end tutorials.
Read and Listen: Develop your conceptual understanding of these technologies.
Hands on Learning
| Topic | Description | Resource |
|---|---|---|
| Weaviate Query Agent with Crew AI | This notebook will show you how to define the Weaviate Query Agent as a tool through the Crew AI. | Notebook |
Read and Listen
| Topic | Description | Resource |
|---|---|---|
| Practical Multi Agent RAG using CrewAI, Weaviate, Groq and ExaTool | Learn how to build RAG powered CrewAI agents that enables code_interpretation, rag, memory, and building a custom tool. | Blog |
| Rag Techniques Tutorial for Agentic Rag | A video on RAG techniques for beginners. | Video |
| How to Build an Agentic RAG Recommendation Engine | Learn how you can leverage Knowledge to give your crew of agents access to relevant context and information. | Video |