mirror of
https://github.com/langchain-ai/langgraph.git
synced 2026-08-20 14:42:28 +02:00
135 lines
4.5 KiB
Python
135 lines
4.5 KiB
Python
import asyncio
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import os
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import tempfile
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from collections import defaultdict
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from functools import partial
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from typing import Any, Optional
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from langchain_core.runnables import RunnableConfig
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from langgraph.checkpoint.base import (
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ChannelVersions,
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Checkpoint,
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CheckpointMetadata,
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CheckpointTuple,
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SerializerProtocol,
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copy_checkpoint,
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)
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from langgraph.checkpoint.memory import InMemorySaver, PersistentDict
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class NoopSerializer(SerializerProtocol):
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def loads_typed(self, data: tuple[str, bytes]) -> Any:
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return data[1]
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def dumps_typed(self, obj: Any) -> tuple[str, bytes]:
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return "type", obj
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class MemorySaverAssertImmutable(InMemorySaver):
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storage_for_copies: defaultdict[str, dict[str, dict[str, Checkpoint]]]
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def __init__(
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self,
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*,
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serde: Optional[SerializerProtocol] = None,
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put_sleep: Optional[float] = None,
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) -> None:
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_, filename = tempfile.mkstemp()
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super().__init__(
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serde=serde, factory=partial(PersistentDict, filename=filename)
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)
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self.storage_for_copies = defaultdict(lambda: defaultdict(dict))
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self.put_sleep = put_sleep
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self.stack.callback(os.remove, filename)
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def put(
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self,
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config: dict,
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checkpoint: Checkpoint,
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metadata: CheckpointMetadata,
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new_versions: ChannelVersions,
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) -> None:
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if self.put_sleep:
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import time
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time.sleep(self.put_sleep)
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# assert checkpoint hasn't been modified since last written
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thread_id = config["configurable"]["thread_id"]
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checkpoint_ns = config["configurable"]["checkpoint_ns"]
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if saved := super().get(config):
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assert (
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self.serde.loads_typed(
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self.storage_for_copies[thread_id][checkpoint_ns][saved["id"]]
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)
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== saved
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)
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self.storage_for_copies[thread_id][checkpoint_ns][checkpoint["id"]] = (
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self.serde.dumps_typed(copy_checkpoint(checkpoint))
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)
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# call super to write checkpoint
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return super().put(config, checkpoint, metadata, new_versions)
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class MemorySaverAssertCheckpointMetadata(InMemorySaver):
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"""This custom checkpointer is for verifying that a run's configurable
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fields are merged with the previous checkpoint config for each step in
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the run. This is the desired behavior. Because the checkpointer's (a)put()
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method is called for each step, the implementation of this checkpointer
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should produce a side effect that can be asserted.
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"""
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def put(
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self,
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config: RunnableConfig,
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checkpoint: Checkpoint,
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metadata: CheckpointMetadata,
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new_versions: ChannelVersions,
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) -> None:
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"""The implementation of put() merges config["configurable"] (a run's
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configurable fields) with the metadata field. The state of the
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checkpoint metadata can be asserted to confirm that the run's
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configurable fields were merged with the previous checkpoint config.
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"""
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configurable = config["configurable"].copy()
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# remove checkpoint_id to make testing simpler
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checkpoint_id = configurable.pop("checkpoint_id", None)
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thread_id = config["configurable"]["thread_id"]
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checkpoint_ns = config["configurable"]["checkpoint_ns"]
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self.storage[thread_id][checkpoint_ns].update(
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{
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checkpoint["id"]: (
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self.serde.dumps_typed(checkpoint),
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# merge configurable fields and metadata
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self.serde.dumps_typed({**configurable, **metadata}),
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checkpoint_id,
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)
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}
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)
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return {
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"configurable": {
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"thread_id": config["configurable"]["thread_id"],
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"checkpoint_id": checkpoint["id"],
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}
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}
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async def aput(
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self,
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config: RunnableConfig,
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checkpoint: Checkpoint,
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metadata: CheckpointMetadata,
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new_versions: ChannelVersions,
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) -> RunnableConfig:
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return await asyncio.get_running_loop().run_in_executor(
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None, self.put, config, checkpoint, metadata, new_versions
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)
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class MemorySaverNoPending(InMemorySaver):
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def get_tuple(self, config: RunnableConfig) -> Optional[CheckpointTuple]:
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result = super().get_tuple(config)
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if result:
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return CheckpointTuple(result.config, result.checkpoint, result.metadata)
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return result
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