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.
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