PostgresStorage class.
Usage
Run PgVector
Install docker desktop and run PgVector on port 5532 using:postgres_storage_for_agent.py
Params
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PostgresStorage class.
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 \
agno/pgvector:16
from agno.storage.postgres import PostgresStorage
db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
# Create a storage backend using the Postgres database
storage = PostgresStorage(
# 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)
| 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. |
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