Code
cookbook/agent_concepts/vector_dbs/lance_db.py
Usage
1
Create a virtual environment
Open the
Terminal and create a python virtual environment.2
Install libraries
3
Run Agent
Documentation Index
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from agno.agent import Agent
from agno.knowledge.pdf_url import PDFUrlKnowledgeBase
from agno.vectordb.lancedb import LanceDb
vector_db = LanceDb(
table_name="recipes",
uri="/tmp/lancedb", # You can change this path to store data elsewhere
)
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
agent = Agent(knowledge=knowledge_base, show_tool_calls=True)
agent.print_response("How to make Tom Kha Gai", markdown=True)
Create a virtual environment
Terminal and create a python virtual environment.python3 -m venv .venv
source .venv/bin/activate
python3 -m venv .venv
.venv/scripts/activate
Install libraries
pip install -U lancedb pypdf openai agno
Run Agent
python cookbook/agent_concepts/vector_dbs/lance_db.py
python cookbook/agent_concepts/vector_dbs/lance_db.py
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