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-postgres

0.0.6:

• 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