Follow steps mentioned in Weaviate setup guide to setup Weaviate.

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Setup

Install weaviate packages

pip install weaviate-client

Run weaviate

docker run -d \
-p 8080:8080 \
-p 50051:50051 \
--name weaviate \
cr.weaviate.io/semitechnologies/weaviate:1.28.4

or

./cookbook/scripts/run_weaviate.sh

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Example

agent_with_knowledge.py
from agno.agent import Agent
from agno.knowledge.pdf_url import PDFUrlKnowledgeBase
from agno.vectordb.search import SearchType
from agno.vectordb.weaviate import Distance, VectorIndex, Weaviate

vector_db = Weaviate(
    collection="recipes",
    search_type=SearchType.hybrid,
    vector_index=VectorIndex.HNSW,
    distance=Distance.COSINE,
    local=True,  # Set to False if using Weaviate Cloud and True if using local instance
)
# Create knowledge base
knowledge_base = PDFUrlKnowledgeBase(
    urls=["https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf"],
    vector_db=vector_db,
)
knowledge_base.load(recreate=False)  # Comment out after first run

# Create and use the agent
agent = Agent(
    knowledge=knowledge_base,
    search_knowledge=True,
    show_tool_calls=True,
)
agent.print_response("How to make Thai curry?", markdown=True)

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Developer Resources