LangGraph Checkpoint implementation for Cloudflare D1
Project description
langgraph-checkpoint-cloudflare-d1
Installation
pip install -U langgraph-checkpoint-cloudflare-d1
Usage
This package provides both synchronous and asynchronous interfaces for saving and retrieving LangGraph checkpoints in Cloudflare D1.
Synchronous
from langgraph_checkpoint_cloudflare_d1 import CloudflareD1Saver
# Cloudflare credentials
account_id = "your-cloudflare-account-id"
database_id = "your-d1-database-id"
api_token = "your-cloudflare-api-token"
# Configuration for checkpoint operations
write_config = {"configurable": {"thread_id": "1", "checkpoint_ns": ""}}
read_config = {"configurable": {"thread_id": "1"}}
# Initialize the saver with proper credentials
with CloudflareD1Saver(
account_id=account_id,
database_id=database_id,
api_token=api_token
) as checkpointer:
# Setup the database tables (idempotent operation)
checkpointer.setup()
# Sample checkpoint data
checkpoint = {
"v": 2,
"ts": "2024-07-31T20:14:19.804150+00:00",
"id": "1ef4f797-8335-6428-8001-8a1503f9b875",
"channel_values": {
"my_key": "meow",
"node": "node"
},
"channel_versions": {
"__start__": 2,
"my_key": 3,
"start:node": 3,
"node": 3
},
"versions_seen": {
"__input__": {},
"__start__": {
"__start__": 1
},
"node": {
"start:node": 2
}
},
"pending_sends": [],
}
# Store checkpoint
checkpointer.put(write_config, checkpoint, {}, {})
# Load checkpoint
loaded_checkpoint = checkpointer.get_tuple(read_config)
# List checkpoints
checkpoints = list(checkpointer.list(read_config))
Async
from langgraph_checkpoint_cloudflare_d1 import AsyncCloudflareD1Saver
import asyncio
async def main():
# Cloudflare credentials
account_id = "your-cloudflare-account-id"
database_id = "your-d1-database-id"
api_token = "your-cloudflare-api-token"
# Configuration for checkpoint operations
write_config = {"configurable": {"thread_id": "1", "checkpoint_ns": ""}}
read_config = {"configurable": {"thread_id": "1"}}
# Initialize the async saver with proper credentials
async with AsyncCloudflareD1Saver(
account_id=account_id,
database_id=database_id,
api_token=api_token
) as checkpointer:
# Sample checkpoint data
checkpoint = {
"v": 2,
"ts": "2024-07-31T20:14:19.804150+00:00",
"id": "1ef4f797-8335-6428-8001-8a1503f9b875",
"channel_values": {
"my_key": "meow",
"node": "node"
},
"channel_versions": {
"__start__": 2,
"my_key": 3,
"start:node": 3,
"node": 3
},
"versions_seen": {
"__input__": {},
"__start__": {
"__start__": 1
},
"node": {
"start:node": 2
}
},
"pending_sends": [],
}
# Setup happens automatically but can be called explicitly
await checkpointer.setup()
# Store checkpoint
await checkpointer.put(write_config, checkpoint, {}, {})
# Load checkpoint
loaded_checkpoint = await checkpointer.get_tuple(read_config)
# List checkpoints
checkpoints = [cp async for cp in checkpointer.list(read_config)]
# For local execution
if __name__ == "__main__":
asyncio.run(main())
Integration with LangGraph
To use this checkpoint saver with LangGraph, you can pass it when compiling your graph:
from langgraph.graph import StateGraph
from langgraph_checkpoint_cloudflare_d1 import CloudflareD1Saver
# Create a simple graph
builder = StateGraph(int)
builder.add_node("add_one", lambda x: x + 1)
builder.set_entry_point("add_one")
builder.set_finish_point("add_one")
# Create the checkpoint saver
checkpointer = CloudflareD1Saver(
account_id="your-account-id",
database_id="your-database-id",
api_token="your-api-token"
)
checkpointer.setup() # Create necessary tables
# Compile the graph with the checkpointer
graph = builder.compile(checkpointer=checkpointer)
# Use the graph with checkpointing
config = {"configurable": {"thread_id": "my-thread-1"}}
result = graph.invoke(3, config)
Release Notes
v0.1.2 (2025-05-11)
- Added support for environmental variables
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