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

# Agent with Storage

> Persist a LiteLLM-backed agent's chat history to SQLite and reuse it across runs.

## Code

```python db.py theme={null}
from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.litellm import LiteLLM
from agno.tools.websearch import WebSearchTools

# Setup the database
db = SqliteDb(
    db_file="tmp/data.db",
)

# Add storage to the Agent
agent = Agent(
    model=LiteLLM(id="gpt-4o"),
    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?")
```

## Usage

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

  <Step title="Set your API key">
    ```bash theme={null}
    export LITELLM_API_KEY=xxx
    ```
  </Step>

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U "litellm<=1.82.6" openai ddgs sqlalchemy agno
    ```
  </Step>

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

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