> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Agent with Storage

> Persist an LMStudio agent's chat history to PostgreSQL and give it web search tools with add_history_to_context enabled.

## Code

```python db.py theme={null}
from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.models.lmstudio import LMStudio
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=LMStudio(id="qwen2.5-7b-instruct-1m"),
    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

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

**1. Install LM Studio**

Install LM Studio from [here](https://lmstudio.ai/download) and download the
model you want to use.

**2. Install dependencies**

```bash theme={null}
uv pip install -U ddgs sqlalchemy psycopg openai agno
```

**3. Run PgVector**

```bash theme={null}
docker run -d \
  -e POSTGRES_DB=ai \
  -e POSTGRES_USER=ai \
  -e POSTGRES_PASSWORD=ai \
  -e PGDATA=/var/lib/postgresql \
  -v pgvolume:/var/lib/postgresql \
  -p 5532:5432 \
  --name pgvector \
  agnohq/pgvector:18
```

**4. Run Agent**

Save the code above as `db.py`, then run:

```bash theme={null}
python db.py
```


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