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"""
Weaviate Hybrid Search
======================

Demonstrates Weaviate hybrid retrieval with interactive querying.
"""

import typer
from agno.agent import Agent
from agno.knowledge.knowledge import Knowledge
from agno.vectordb.search import SearchType
from agno.vectordb.weaviate import Distance, VectorIndex, Weaviate
from rich.prompt import Prompt

# ---------------------------------------------------------------------------
# Setup
# ---------------------------------------------------------------------------
vector_db = Weaviate(
    collection="recipes",
    search_type=SearchType.hybrid,
    vector_index=VectorIndex.HNSW,
    distance=Distance.COSINE,
    local=False,
    hybrid_search_alpha=0.6,
)


# ---------------------------------------------------------------------------
# Create Knowledge Base
# ---------------------------------------------------------------------------
knowledge_base = Knowledge(
    name="Weaviate Hybrid Search",
    description="A knowledge base for Weaviate hybrid search",
    vector_db=vector_db,
)


# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
def weaviate_agent(user: str = "user"):
    agent = Agent(
        user_id=user,
        knowledge=knowledge_base,
        search_knowledge=True,
    )

    while True:
        message = Prompt.ask(f"[bold]{user}[/bold]")
        if message in ("exit", "bye"):
            break
        agent.print_response(message)


# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
def main() -> None:
    knowledge_base.insert(
        url="https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf"
    )
    typer.run(weaviate_agent)


if __name__ == "__main__":
    main()

​
Run the Example

# Clone and setup repo
git clone https://github.com/agno-agi/agno.git
cd agno/cookbook/07_knowledge/vector_db/weaviate_db

# Create and activate virtual environment
./scripts/demo_setup.sh
source .venvs/demo/bin/activate

python weaviate_db_hybrid_search.py