Documentation Index
Fetch the complete documentation index at: /llms.txt
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Store an Ollama llama3.1:8b agent’s history in Postgres with WebSearchTools and add_history_to_context for multi-turn context.
from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.models.ollama import Ollama
from agno.tools.websearch import WebSearchTools
# Setup the database
db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
db = PostgresDb(db_url=db_url)
agent = Agent(
model=Ollama(id="llama3.1:8b"),
db=db,
tools=[WebSearchTools()],
add_history_to_context=True,
)
agent.print_response("How many people live in Canada?")
agent.print_response("What is their national anthem called?")
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activate
uv venv --python 3.12
.venv\Scripts\activate
Install Ollama
ollama pull llama3.1:8b
Install dependencies
uv pip install -U ddgs sqlalchemy psycopg ollama 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:18
Run Agent
db.py, then run:python db.py
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