Insert, Search, and Delete with LanceDB

lance_db.py

from agno.agent import Agent
from agno.knowledge.knowledge import Knowledge
from agno.vectordb.lancedb import LanceDb

vector_db = LanceDb(table_name="recipes", uri="tmp/lancedb")
knowledge = Knowledge(vector_db=vector_db)
agent = Agent(knowledge=knowledge, search_knowledge=True)

if __name__ == "__main__":
    knowledge.insert(
        name="Recipes",
        url="https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf",
        metadata={"doc_type": "recipe_book"},
    )

    agent.print_response(
        "List the ingredients for Massaman Gai.",
        markdown=True,
    )

    vector_db.delete_by_name("Recipes")
    # To delete by metadata instead:
    # vector_db.delete_by_metadata({"doc_type": "recipe_book"})

Choose one deletion method after the search. delete_by_name() and delete_by_metadata() load matching rows and delete their IDs from the LanceDB table.

Run the Example

Set up your virtual environment

uv venv --python 3.12
source .venv/bin/activate

uv venv --python 3.12
.venv\Scripts\activate

Install dependencies

uv pip install -U agno lancedb openai pypdf

Export the API key

export OPENAI_API_KEY=your_openai_api_key_here

Run the example

python lance_db.py

Next Steps

Task	Guide
Call async Agno methods	Async LanceDB usage
Configure hybrid search	LanceDB hybrid search
Configure search behavior	LanceDB overview

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Insert, Search, and Delete with LanceDB

Run the Example

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​Run the Example

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Run the Example

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