Connecting to TablePlus

Inspect your pgvector container’s sessions and knowledge tables with TablePlus.

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

Step 1: Start Your pgvector Container

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

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

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")

1. Set up your virtual environment

   Mac

   uv venv --python 3.12
   source .venv/bin/activate
   

   uv venv --python 3.12
   .venv\Scripts\activate
   
2. Install dependencies

   uv pip install -U agno openai "psycopg[binary]" sqlalchemy
   
3. Export your OpenAI API key

   macOS / Linux

   export OPENAI_API_KEY="your_openai_api_key_here"
   

   $Env:OPENAI_API_KEY="your_openai_api_key_here"
   
4. Run the example

   Save the code as create_session.py, then run:

   python create_session.py
   

Only table types exercised against this database appear. Run the Postgres memory guide to create memory tables and the PgVector guide to create knowledge tables.

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