The langchain-postgres package implementations of core LangChain abstractions using Postgres.
The package is released under the MIT license.
Feel free to use the abstraction as provided or else modify them / extend them as appropriate for your own application.
The package currently only supports the psycogp3 driver.
pip install -U langchain-postgres0.0.6:
- Remove langgraph as a dependency as it was causing dependency conflicts.
- Base interface for checkpointer changed in langgraph, so existing implementation would've broken regardless.
The chat message history abstraction helps to persist chat message history in a postgres table.
PostgresChatMessageHistory is parameterized using a table_name and a session_id.
The table_name is the name of the table in the database where
the chat messages will be stored.
The session_id is a unique identifier for the chat session. It can be assigned
by the caller using uuid.uuid4().
import uuid
from langchain_core.messages import SystemMessage, AIMessage, HumanMessage
from langchain_postgres import PostgresChatMessageHistory
import psycopg
# Establish a synchronous connection to the database
# (or use psycopg.AsyncConnection for async)
conn_info = ... # Fill in with your connection info
sync_connection = psycopg.connect(conn_info)
# Create the table schema (only needs to be done once)
table_name = "chat_history"
PostgresChatMessageHistory.create_tables(sync_connection, table_name)
session_id = str(uuid.uuid4())
# Initialize the chat history manager
chat_history = PostgresChatMessageHistory(
table_name,
session_id,
sync_connection=sync_connection
)
# Add messages to the chat history
chat_history.add_messages([
SystemMessage(content="Meow"),
AIMessage(content="woof"),
HumanMessage(content="bark"),
])
print(chat_history.messages)See example for the PGVector vectorstore here
