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

# Postgres Agent Storage

Phidata supports using PostgreSQL as a storage backend for Agents using the `PgAgentStorage` class.

## Usage

## Run PgVector

Install [docker desktop](https://docs.docker.com/desktop/install/mac-install/) and run **PgVector** on port **5532** using:

```bash theme={null}
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 \
  phidata/pgvector:16
```

```python storage.py theme={null}
from phi.storage.agent.postgres import PgAgentStorage

db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"

# Create a storage backend using the Postgres database
storage = PgAgentStorage(
    # store sessions in the ai.sessions table
    table_name="agent_sessions",
    # db_url: Postgres database URL
    db_url=db_url,
)

# Add storage to the Agent
agent = Agent(storage=storage)
```

## Params

<Snippet file="storage-postgres-params.mdx" />