> ## Documentation Index
> Fetch the complete documentation index at: https://phidatainc.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# DB

> Persist Ollama agent sessions in Postgres and reuse history in a follow-up turn.

```python db.py theme={null}
"""Run `uv pip install ddgs sqlalchemy ollama` to install dependencies."""

from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.models.ollama import Ollama
from agno.tools.websearch import WebSearchTools

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------

# 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?")

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------

if __name__ == "__main__":
    pass
```

## Run the Example

<Steps>
  <Snippet file="create-venv-step.mdx" />

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U agno "psycopg[binary]" ddgs ollama sqlalchemy
    ```
  </Step>

  <Snippet file="run-pgvector-step.mdx" />

  <Step title="Prepare Ollama">
    Install and start Ollama, then pull the model used by this example:

    ```bash theme={null}
    ollama pull llama3.1:8b
    ```
  </Step>

  <Step title="Run the example">
    Save the code above as `db.py`, then run:

    ```bash theme={null}
    python db.py
    ```
  </Step>
</Steps>

Full source: [cookbook/90\_models/ollama/chat/db.py](https://github.com/agno-agi/agno/blob/main/cookbook/90_models/ollama/chat/db.py)