BREAKING: remove langgraph checkpointer

README.md

@@ -25,97 +25,6 @@ pip install -U langchain-postgres
 
 ## Usage
 
-### PostgresSaver (LangGraph Checkpointer) 
-
-The LangGraph checkpointer can be used to add memory to your LangGraph application.
-
-`PostgresSaver` is an implementation of the checkpointer saver using
-Postgres as the backend.
-
-Currently, only the psycopg3 driver is supported.
-
-Sync usage:
-
-```python 
-from psycopg_pool import ConnectionPool
-from langchain_postgres import (
-    PostgresSaver, PickleCheckpointSerializer
-)
-
-pool = ConnectionPool(
-    # Example configuration
-    conninfo="postgresql://langchain:langchain@localhost:6024/langchain",
-    max_size=20,
-)
-
-PostgresSaver.create_tables(pool)
-
-checkpointer = PostgresSaver(
-    serializer=PickleCheckpointSerializer(),
-    sync_connection=pool,
-)
-
-# Set up the langgraph workflow with the checkpointer
-workflow = ... # Fill in with your workflow
-app = workflow.compile(checkpointer=checkpointer)
-
-# Use with the sync methods of `app` (e.g., `app.stream())
-
-pool.close() # Remember to close the connection pool.
-```
-
-Async usage:
-
-```python
-from psycopg_pool import AsyncConnectionPool
-from langchain_postgres import (
-    PostgresSaver, PickleCheckpointSerializer
-)
-
-pool = AsyncConnectionPool(
-    # Example configuration
-    conninfo="postgresql://langchain:langchain@localhost:6024/langchain",
-    max_size=20,
-)
-
-# Create the tables in postgres (only needs to be done once)
-await PostgresSaver.acreate_tables(pool)
-
-checkpointer = PostgresSaver(
-    serializer=PickleCheckpointSerializer(),
-    async_connection=pool,
-)
-
-# Set up the langgraph workflow with the checkpointer
-workflow = ... # Fill in with your workflow
-app = workflow.compile(checkpointer=checkpointer)
-
-# Use with the async methods of `app` (e.g., `app.astream()`)
-
-await pool.close() # Remember to close the connection pool.
-```
-
-#### Testing
-
-If testing with the postgres checkpointer it may be useful to both create and
-drop the tables before and after the tests.
-
-```python
-from psycopg_pool import ConnectionPool
-from langchain_postgres import (
-    PostgresSaver 
-)
-with ConnectionPool(
-    # Example configuration
-    conninfo="postgresql://langchain:langchain@localhost:6024/langchain",
-    max_size=20,
-) as conn:
-    PostgresSaver.create_tables(conn)
-    PostgresSaver.drop_tables(conn)
-    # Run your unit tests with langgraph
-```
-
-
 ### ChatMessageHistory
 
 The chat message history abstraction helps to persist chat message history