from pathlib import Path
from agno.agent import Agent
from agno.knowledge.csv import CSVKnowledgeBase
from agno.vectordb.pgvector import PgVector
db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
knowledge_base = CSVKnowledgeBase(
path=Path("data/csvs"),
vector_db=PgVector(
table_name="csv_documents",
db_url=db_url,
),
num_documents=5, # Number of documents to return on search
)
# Load the knowledge base
knowledge_base.load(recreate=False)
# Initialize the Agent with the knowledge_base
agent = Agent(
knowledge=knowledge_base,
search_knowledge=True,
)
# Use the agent
agent.print_response("Ask me about something from the knowledge base", markdown=True)
Create a virtual environment
Open the Terminal
and create a python virtual environment.
python3 -m venv .venv
source .venv/bin/activate
Install libraries
pip install -U sqlalchemy 'psycopg[binary]' pgvector agno
Run PgVector
docker run -d \
-e POSTGRES_DB=ai \
-e POSTGRES_USER=ai \
-e POSTGRES_PASSWORD=ai \
-e PGDATA=/var/lib/postgresql/data/pgdata \
-v pgvolume:/var/lib/postgresql/data \
-p 5532:5432 \
--name pgvector \
agnohq/pgvector:16
Run Agent
python cookbook/agent_concepts/knowledge/csv_kb.py
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from pathlib import Path
from agno.agent import Agent
from agno.knowledge.csv import CSVKnowledgeBase
from agno.vectordb.pgvector import PgVector
db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
knowledge_base = CSVKnowledgeBase(
path=Path("data/csvs"),
vector_db=PgVector(
table_name="csv_documents",
db_url=db_url,
),
num_documents=5, # Number of documents to return on search
)
# Load the knowledge base
knowledge_base.load(recreate=False)
# Initialize the Agent with the knowledge_base
agent = Agent(
knowledge=knowledge_base,
search_knowledge=True,
)
# Use the agent
agent.print_response("Ask me about something from the knowledge base", markdown=True)
Create a virtual environment
Open the Terminal
and create a python virtual environment.
python3 -m venv .venv
source .venv/bin/activate
Install libraries
pip install -U sqlalchemy 'psycopg[binary]' pgvector agno
Run PgVector
docker run -d \
-e POSTGRES_DB=ai \
-e POSTGRES_USER=ai \
-e POSTGRES_PASSWORD=ai \
-e PGDATA=/var/lib/postgresql/data/pgdata \
-v pgvolume:/var/lib/postgresql/data \
-p 5532:5432 \
--name pgvector \
agnohq/pgvector:16
Run Agent
python cookbook/agent_concepts/knowledge/csv_kb.py
Was this page helpful?