# Connecting to TablePlus (/faq/connecting-to-tableplus)



Use TablePlus to inspect the tables Agno creates in your pgvector container: sessions, memories, and knowledge embeddings.

## Step 1: Start Your `pgvector` Container [#step-1-start-your-pgvector-container]

```bash
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
```

* `POSTGRES_DB=ai` sets the default database name.
* `POSTGRES_USER=ai` and `POSTGRES_PASSWORD=ai` define the database credentials.
* The container exposes port `5432`, mapped to `5532` on your local machine.

## Step 2: Create the Session Table [#step-2-create-the-session-table]

Agno creates database tables when a database-backed feature first uses them. Run this example to create the default `agno_sessions` table:

```python create_session.py
from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.models.openai import OpenAIResponses

db = PostgresDb(db_url="postgresql+psycopg://ai:ai@localhost:5532/ai")

agent = Agent(
    model=OpenAIResponses(id="gpt-5.4-mini"),
    db=db,
)
agent.print_response("What is the capital of France?", session_id="tableplus-demo")
```

<Steps>
    <Step title="Set up your virtual environment">
      <CodeBlockTabs defaultValue="Mac">
        <CodeBlockTabsList>
          <CodeBlockTabsTrigger value="Mac">
            Mac
          </CodeBlockTabsTrigger>

          <CodeBlockTabsTrigger value="Windows">
            Windows
          </CodeBlockTabsTrigger>
        </CodeBlockTabsList>

        <CodeBlockTab value="Mac">
          ```bash
          uv venv --python 3.12
          source .venv/bin/activate
          ```
        </CodeBlockTab>

        <CodeBlockTab value="Windows">
          ```bash
          uv venv --python 3.12
          .venv\Scripts\activate
          ```
        </CodeBlockTab>
      </CodeBlockTabs>
    </Step>

  <Step title="Install dependencies">
    ```bash
    uv pip install -U agno openai "psycopg[binary]" sqlalchemy
    ```
  </Step>

  <Step title="Export your OpenAI API key">
    <CodeBlockTabs defaultValue="macOS / Linux">
      <CodeBlockTabsList>
        <CodeBlockTabsTrigger value="macOS / Linux">
          macOS / Linux
        </CodeBlockTabsTrigger>

        <CodeBlockTabsTrigger value="Windows">
          Windows
        </CodeBlockTabsTrigger>
      </CodeBlockTabsList>

      <CodeBlockTab value="macOS / Linux">
        ```bash
        export OPENAI_API_KEY="your_openai_api_key_here"
        ```
      </CodeBlockTab>

      <CodeBlockTab value="Windows">
        ```powershell
        $Env:OPENAI_API_KEY="your_openai_api_key_here"
        ```
      </CodeBlockTab>
    </CodeBlockTabs>
  </Step>

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

    ```bash
    python create_session.py
    ```
  </Step>
</Steps>

Only table types exercised against this database appear. Run the [Postgres memory guide](/memory/working-with-memories/postgres-memory) to create memory tables and the [PgVector guide](/knowledge/vector-stores/pgvector/overview) to create knowledge tables.

## Step 3: Configure TablePlus [#step-3-configure-tableplus]

1. Launch TablePlus.
2. Click the `+` icon to add a new connection.
3. Choose PostgreSQL as the database type.

Fill in the connection details:

* **Host**: `localhost`
* **Port**: `5532`
* **Database**: `ai`
* **User**: `ai`
* **Password**: `ai`

<img src="/images/tableplus.png" alt="TablePlus PostgreSQL connection settings" width="492" height="386" />