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from agno.agent import Agent
from agno.knowledge.chunking.row import RowChunking
from agno.knowledge.knowledge import Knowledge
from agno.knowledge.reader.csv_reader import CSVReader
from agno.vectordb.pgvector import PgVector

db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"

knowledge_base = Knowledge(
    vector_db=PgVector(table_name="imdb_movies_row_chunking", db_url=db_url),
)

knowledge_base.insert(
    url="https://agno-public.s3.amazonaws.com/demo_data/IMDB-Movie-Data.csv",
    reader=CSVReader(
        chunking_strategy=RowChunking(),
    ),
)

# Initialize the Agent with the knowledge_base
agent = Agent(
    knowledge=knowledge_base,
    search_knowledge=True,
)

# Use the agent
agent.print_response("Tell me about the movie Guardians of the Galaxy", markdown=True)

​
Run the Example

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

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

# Optiona: Run PgVector (needs docker)
./cookbook/scripts/run_pgvector.sh

python csv_row_chunking.py