Postgres Agent Storage

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

​Usage

​Run PgVector

Install docker desktop and run PgVector on port 5532 using:

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 \
  bitcadata/pgvector:16

storage.py

from bitca.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

Parameter	Type	Default	Description
table_name	str	-	Name of the table to be used.
schema	Optional[str]	"ai"	Schema name, default is "ai".
db_url	Optional[str]	None	Database URL, if provided.
db_engine	Optional[Engine]	None	Database engine to be used.
schema_version	int	1	Version of the schema, default is 1.
auto_upgrade_schema	bool	False	If true, automatically upgrades the schema when necessary.