diff --git a/libs/langgraph/langgraph/constants.py b/libs/langgraph/langgraph/constants.py index f19c562f5..9cc287277 100644 --- a/libs/langgraph/langgraph/constants.py +++ b/libs/langgraph/langgraph/constants.py @@ -9,6 +9,7 @@ CONFIG_KEY_STREAM = "__pregel_stream" CONFIG_KEY_STORE = "__pregel_store" CONFIG_KEY_RESUMING = "__pregel_resuming" CONFIG_KEY_TASK_ID = "__pregel_task_id" +CONFIG_KEY_DEDUPE_TASKS = "__pregel_dedupe_tasks" # this one part of public API so more readable CONFIG_KEY_CHECKPOINT_MAP = "checkpoint_map" INTERRUPT = "__interrupt__" @@ -30,6 +31,7 @@ RESERVED = { CONFIG_KEY_STORE, CONFIG_KEY_RESUMING, CONFIG_KEY_TASK_ID, + CONFIG_KEY_DEDUPE_TASKS, INPUT, RUNTIME_PLACEHOLDER, } diff --git a/libs/langgraph/langgraph/pregel/loop.py b/libs/langgraph/langgraph/pregel/loop.py index afd29ec1b..c18fe5efb 100644 --- a/libs/langgraph/langgraph/pregel/loop.py +++ b/libs/langgraph/langgraph/pregel/loop.py @@ -39,6 +39,7 @@ from langgraph.checkpoint.base import ( ) from langgraph.constants import ( CONFIG_KEY_CHECKPOINT_MAP, + CONFIG_KEY_DEDUPE_TASKS, CONFIG_KEY_RESUMING, CONFIG_KEY_STREAM, CONFIG_KEY_TASK_ID, @@ -179,7 +180,10 @@ class PregelLoop: self.output_keys = output_keys self.stream_keys = stream_keys self.is_nested = CONFIG_KEY_TASK_ID in self.config.get("configurable", {}) - self.skip_done_tasks = "checkpoint_id" not in config["configurable"] + self.skip_done_tasks = ( + "checkpoint_id" not in config["configurable"] + or CONFIG_KEY_DEDUPE_TASKS in config["configurable"] + ) self.debug = debug if CONFIG_KEY_STREAM in config["configurable"]: self.stream = DuplexStream( @@ -595,6 +599,7 @@ class SyncPregelLoop(PregelLoop, ContextManager): **self.config, **saved.config, "configurable": { + "checkpoint_ns": "", **self.config.get("configurable", {}), **saved.config.get("configurable", {}), }, @@ -697,6 +702,7 @@ class AsyncPregelLoop(PregelLoop, AsyncContextManager): **self.config, **saved.config, "configurable": { + "checkpoint_ns": "", **self.config.get("configurable", {}), **saved.config.get("configurable", {}), }, diff --git a/libs/scheduler-kafka/LICENSE b/libs/scheduler-kafka/LICENSE new file mode 100644 index 000000000..fc0602fee --- /dev/null +++ b/libs/scheduler-kafka/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2024 LangChain, Inc. + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/libs/scheduler-kafka/Makefile b/libs/scheduler-kafka/Makefile new file mode 100644 index 000000000..53c67e9a4 --- /dev/null +++ b/libs/scheduler-kafka/Makefile @@ -0,0 +1,46 @@ +.PHONY: test test_watch lint format + +###################### +# TESTING AND COVERAGE +###################### + +start-services: + docker compose -f testss/compose.yml up -V --force-recreate --wait --remove-orphans + +stop-services: + docker compose -f testss/compose.yml down + +test: + make start-services && poetry run pytest; \ + EXIT_CODE=$$?; \ + make stop-services; \ + exit $$EXIT_CODE + +test_watch: + make start-services && poetry run ptw .; \ + EXIT_CODE=$$?; \ + make stop-services; \ + exit $$EXIT_CODE + +###################### +# LINTING AND FORMATTING +###################### + +# Define a variable for Python and notebook files. +PYTHON_FILES=. +MYPY_CACHE=.mypy_cache +lint format: PYTHON_FILES=. +lint_diff format_diff: PYTHON_FILES=$(shell git diff --name-only --relative --diff-filter=d main . | grep -E '\.py$$|\.ipynb$$') +lint_package: PYTHON_FILES=langgraph +lint_tests: PYTHON_FILES=tests +lint_tests: MYPY_CACHE=.mypy_cache_test + +lint lint_diff lint_package lint_tests: + poetry run ruff check . + [ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) --diff + [ "$(PYTHON_FILES)" = "" ] || poetry run ruff check --select I $(PYTHON_FILES) + [ "$(PYTHON_FILES)" = "" ] || mkdir -p $(MYPY_CACHE) || poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE) + +format format_diff: + poetry run ruff format $(PYTHON_FILES) + poetry run ruff check --select I --fix $(PYTHON_FILES) diff --git a/libs/scheduler-kafka/README.md b/libs/scheduler-kafka/README.md new file mode 100644 index 000000000..cedfcc53f --- /dev/null +++ b/libs/scheduler-kafka/README.md @@ -0,0 +1,3 @@ +# LangGraph Scheduler for Kafka + +... diff --git a/libs/scheduler-kafka/langgraph/scheduler/kafka/__init__.py b/libs/scheduler-kafka/langgraph/scheduler/kafka/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/libs/scheduler-kafka/langgraph/scheduler/kafka/executor.py b/libs/scheduler-kafka/langgraph/scheduler/kafka/executor.py new file mode 100644 index 000000000..de1e61e09 --- /dev/null +++ b/libs/scheduler-kafka/langgraph/scheduler/kafka/executor.py @@ -0,0 +1,94 @@ +import asyncio +from contextlib import AbstractAsyncContextManager +from typing import Any + +import aiokafka + +import langgraph.scheduler.kafka.serde as serde +from langgraph.constants import ERROR +from langgraph.errors import TaskNotFound +from langgraph.pregel import Pregel +from langgraph.pregel.algo import prepare_single_task +from langgraph.pregel.executor import AsyncBackgroundExecutor +from langgraph.pregel.manager import AsyncChannelsManager +from langgraph.pregel.runner import PregelRunner +from langgraph.scheduler.kafka.types import ( + MessageToExecutor, + MessageToOrchestrator, + Topics, +) + + +class KafkaExecutor(AbstractAsyncContextManager): + def __init__(self, graph: Pregel, topics: Topics, **kwargs: Any) -> None: + self.graph = graph + self.topics = topics + self.consumer = aiokafka.AIOKafkaConsumer( + topics.executor, value_deserializer=serde.loads, **kwargs + ) + self.producer = aiokafka.AIOKafkaProducer( + value_serializer=serde.dumps, **kwargs + ) + + async def __aenter__(self) -> "KafkaExecutor": + await self.consumer.start() + await self.producer.start() + return self + + async def __aexit__(self, *args: Any) -> None: + await self.consumer.stop() + await self.producer.stop() + + def __aiter__(self) -> "KafkaExecutor": + return self + + async def __anext__(self) -> Any: + # wait for next message + try: + rec = await self.consumer.getone() + msg: MessageToExecutor = rec.value + except aiokafka.ConsumerStoppedError: + raise StopAsyncIteration from None + # process message + saved = await self.graph.checkpointer.aget_tuple(msg["config"]) + if saved is None: + raise RuntimeError("Checkpoint not found") + async with AsyncChannelsManager( + self.graph.channels, saved.checkpoint, msg["config"], self.graph.store + ) as (channels, managed), AsyncBackgroundExecutor() as submit: + + def put_writes(task_id: str, writes: list[tuple[str, Any]]) -> None: + print("put_writes", task_id, writes) + return submit( + self.graph.checkpointer.aput_writes, msg["config"], writes, task_id + ) + + if task := await asyncio.to_thread( + prepare_single_task, + msg["task"]["path"], + msg["task"]["id"], + checkpoint=saved.checkpoint, + processes=self.graph.nodes, + channels=channels, + managed=managed, + config=msg["config"], + step=msg["task"]["step"], + for_execution=True, + is_resuming=msg["task"]["resuming"], + ): + # execute task, saving writes + runner = PregelRunner(submit=submit, put_writes=put_writes) + async for _ in runner.atick([task]): + pass + else: + # task was not found + await self.graph.checkpointer.put_writes( + msg["config"], [(ERROR, TaskNotFound())] + ) + # notify orchestrator + await self.producer.send( + self.topics.orchestrator, + value=MessageToOrchestrator(input=None, config=msg["config"]), + ) + # return message + return msg diff --git a/libs/scheduler-kafka/langgraph/scheduler/kafka/orchestrator.py b/libs/scheduler-kafka/langgraph/scheduler/kafka/orchestrator.py new file mode 100644 index 000000000..5187f0435 --- /dev/null +++ b/libs/scheduler-kafka/langgraph/scheduler/kafka/orchestrator.py @@ -0,0 +1,94 @@ +from contextlib import AbstractAsyncContextManager +from typing import Any + +import aiokafka +from langchain_core.runnables import ensure_config + +import langgraph.scheduler.kafka.serde as serde +from langgraph.constants import CONFIG_KEY_DEDUPE_TASKS, SCHEDULED +from langgraph.pregel import Pregel +from langgraph.pregel.loop import INPUT_RESUMING, AsyncPregelLoop +from langgraph.scheduler.kafka.types import ( + ExecutorTask, + MessageToExecutor, + MessageToOrchestrator, + Topics, +) +from langgraph.utils.config import patch_configurable + + +class KafkaOrchestrator(AbstractAsyncContextManager): + def __init__(self, graph: Pregel, topics: Topics, **kwargs: Any) -> None: + self.graph = graph + self.topics = topics + self.consumer = aiokafka.AIOKafkaConsumer( + topics.orchestrator, value_deserializer=serde.loads, **kwargs + ) + self.producer = aiokafka.AIOKafkaProducer( + value_serializer=serde.dumps, **kwargs + ) + + async def __aenter__(self) -> "KafkaOrchestrator": + await self.consumer.start() + await self.producer.start() + return self + + async def __aexit__(self, *args: Any) -> None: + await self.consumer.stop() + await self.producer.stop() + + def __aiter__(self) -> "KafkaOrchestrator": + return self + + async def __anext__(self) -> Any: + # wait for next message + try: + rec = await self.consumer.getone() + msg: MessageToOrchestrator = rec.value + except aiokafka.ConsumerStoppedError: + raise StopAsyncIteration from None + # process message + async with AsyncPregelLoop( + msg["input"], + config=ensure_config(msg["config"]), + stream=None, + store=self.graph.store, + checkpointer=self.graph.checkpointer, + nodes=self.graph.nodes, + specs=self.graph.channels, + output_keys=self.graph.output_channels, + stream_keys=self.graph.stream_channels, + ) as loop: + if loop.tick(input_keys=self.graph.input_channels): + if hasattr(loop, "_put_checkpoint_fut"): + await loop._put_checkpoint_fut + if new_tasks := [t for t in loop.tasks.values() if not t.scheduled]: + # send messages to executor + for task in new_tasks: + if task.scheduled: + continue + await self.producer.send( + self.topics.executor, + value=MessageToExecutor( + config=patch_configurable( + loop.config, + { + **loop.checkpoint_config["configurable"], + CONFIG_KEY_DEDUPE_TASKS: True, + }, + ), + task=ExecutorTask( + id=task.id, + path=task.path, + step=loop.step, + resuming=loop.input is INPUT_RESUMING, + ), + ), + ) + # flush producer + await self.producer.flush() + # mark as scheduled + for task in new_tasks: + loop.put_writes(task.id, [(SCHEDULED, None)]) + # return message + return msg diff --git a/libs/scheduler-kafka/langgraph/scheduler/kafka/serde.py b/libs/scheduler-kafka/langgraph/scheduler/kafka/serde.py new file mode 100644 index 000000000..952de1721 --- /dev/null +++ b/libs/scheduler-kafka/langgraph/scheduler/kafka/serde.py @@ -0,0 +1,16 @@ +from typing import Any + +import orjson + + +def loads(v: bytes) -> Any: + return orjson.loads(v) + + +def dumps(v: Any) -> bytes: + return orjson.dumps(v, default=_default) + + +def _default(v: Any) -> Any: + # things we don't know how to serialize (eg. functions) ignore + return None diff --git a/libs/scheduler-kafka/langgraph/scheduler/kafka/types.py b/libs/scheduler-kafka/langgraph/scheduler/kafka/types.py new file mode 100644 index 000000000..ce2a01d9b --- /dev/null +++ b/libs/scheduler-kafka/langgraph/scheduler/kafka/types.py @@ -0,0 +1,25 @@ +from typing import Any, NamedTuple, Optional, TypedDict + +from langchain_core.runnables import RunnableConfig + + +class Topics(NamedTuple): + orchestrator: str + executor: str + + +class MessageToOrchestrator(TypedDict): + input: Optional[dict[str, Any]] + config: RunnableConfig + + +class ExecutorTask(TypedDict): + id: str + path: tuple[str, ...] + step: int + resuming: bool + + +class MessageToExecutor(TypedDict): + config: RunnableConfig + task: ExecutorTask diff --git a/libs/scheduler-kafka/langgraph/scheduler/py.typed b/libs/scheduler-kafka/langgraph/scheduler/py.typed new file mode 100644 index 000000000..e69de29bb diff --git a/libs/scheduler-kafka/poetry.lock b/libs/scheduler-kafka/poetry.lock new file mode 100644 index 000000000..14ac0aac5 --- /dev/null +++ b/libs/scheduler-kafka/poetry.lock @@ -0,0 +1,1182 @@ +# This file is automatically @generated by Poetry 1.8.2 and should not be 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/dev/null +++ b/libs/scheduler-kafka/pyproject.toml @@ -0,0 +1,57 @@ +[tool.poetry] +name = "langgraph-scheduler-kafka" +version = "1.0.0" +description = "Library with Kafka-based work scheduler." +authors = [] +license = "MIT" +readme = "README.md" +repository = "https://www.github.com/langchain-ai/langgraph" +packages = [{ include = "langgraph" }] + +[tool.poetry.dependencies] +python = "^3.9.0,<4.0" +orjson = "^3.10.7" +crc32c = "^2.7.post1" +aiokafka = "^0.11.0" +kafka-python-ng = "^2.2.2" + +[tool.poetry.group.dev.dependencies] +ruff = "^0.6.2" +codespell = "^2.2.0" +pytest = "^7.2.1" +pytest-mock = "^3.11.1" +pytest-watcher = "^0.4.1" +mypy = "^1.10.0" +langgraph = {path = "../langgraph", develop = true} +langgraph-checkpoint-postgres = {path = "../checkpoint-postgres", develop = true} +langgraph-checkpoint = {path = "../checkpoint", develop = true} + +[tool.pytest.ini_options] +# --strict-markers will raise errors on unknown marks. +# https://docs.pytest.org/en/7.1.x/how-to/mark.html#raising-errors-on-unknown-marks +# +# https://docs.pytest.org/en/7.1.x/reference/reference.html +# --strict-config any warnings encountered while parsing the `pytest` +# section of the configuration file raise errors. +addopts = "--strict-markers --strict-config --durations=5 -vv" + + +[build-system] +requires = ["poetry-core"] +build-backend = "poetry.core.masonry.api" + +[tool.ruff] +lint.select = [ + "E", # pycodestyle + "F", # Pyflakes + "UP", # pyupgrade + "B", # flake8-bugbear + "I", # isort +] +lint.ignore = ["E501", "B008", "UP007", "UP006"] + +[tool.pytest-watcher] +now = true +delay = 0.1 +runner_args = ["-s", "--ff", "-v", "--tb", "short"] +patterns = ["*.py"] diff --git a/libs/scheduler-kafka/testss/__init__.py b/libs/scheduler-kafka/testss/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/libs/scheduler-kafka/testss/compose.yml b/libs/scheduler-kafka/testss/compose.yml new file mode 100644 index 000000000..59571371e --- /dev/null +++ b/libs/scheduler-kafka/testss/compose.yml @@ -0,0 +1,20 @@ +services: + broker: + image: apache/kafka:latest + ports: + - "9092:9092" + postgres: + image: postgres:16 + ports: + - "5443:5432" + environment: + POSTGRES_DB: postgres + POSTGRES_USER: postgres + POSTGRES_PASSWORD: postgres + healthcheck: + test: pg_isready -U postgres + start_period: 10s + timeout: 1s + retries: 5 + interval: 60s + start_interval: 1s diff --git a/libs/scheduler-kafka/testss/conftest.py b/libs/scheduler-kafka/testss/conftest.py new file mode 100644 index 000000000..4296b9851 --- /dev/null +++ b/libs/scheduler-kafka/testss/conftest.py @@ -0,0 +1,58 @@ +from typing import AsyncIterator, Iterator +from uuid import uuid4 + +import kafka.admin +import pytest +from psycopg import AsyncConnection + +from langgraph.checkpoint.postgres.aio import AsyncPostgresSaver +from langgraph.scheduler.kafka.types import Topics + +DEFAULT_POSTGRES_URI = "postgres://postgres:postgres@localhost:5443/" + + +@pytest.fixture +def anyio_backend(): + return "asyncio" + + +@pytest.fixture +def topics() -> Iterator[Topics]: + o = f"test_{uuid4().hex[:16]}" + e = f"test_{uuid4().hex[:16]}" + admin = kafka.admin.KafkaAdminClient() + # create topics + admin.create_topics( + [ + kafka.admin.NewTopic(name=o, num_partitions=1, replication_factor=1), + kafka.admin.NewTopic(name=e, num_partitions=1, replication_factor=1), + ] + ) + # yield topics + yield Topics(orchestrator=o, executor=e) + # delete topics + admin.delete_topics([o, e]) + admin.close() + + +@pytest.fixture +async def checkpointer() -> AsyncIterator[AsyncPostgresSaver]: + database = f"test_{uuid4().hex[:16]}" + # create unique db + async with await AsyncConnection.connect( + DEFAULT_POSTGRES_URI, autocommit=True + ) as conn: + await conn.execute(f"CREATE DATABASE {database}") + try: + # yield checkpointer + async with AsyncPostgresSaver.from_conn_string( + DEFAULT_POSTGRES_URI + database + ) as checkpointer: + await checkpointer.setup() + yield checkpointer + finally: + # drop unique db + async with await AsyncConnection.connect( + DEFAULT_POSTGRES_URI, autocommit=True + ) as conn: + await conn.execute(f"DROP DATABASE {database}") diff --git a/libs/scheduler-kafka/testss/test_scheduler.py b/libs/scheduler-kafka/testss/test_scheduler.py new file mode 100644 index 000000000..b53abd361 --- /dev/null +++ b/libs/scheduler-kafka/testss/test_scheduler.py @@ -0,0 +1,124 @@ +import asyncio +import operator +from typing import Annotated, TypedDict, Union + +import pytest +from aiokafka import AIOKafkaProducer + +from langgraph.checkpoint.base import BaseCheckpointSaver +from langgraph.graph.state import StateGraph +from langgraph.pregel import Pregel +from langgraph.scheduler.kafka import serde +from langgraph.scheduler.kafka.executor import KafkaExecutor +from langgraph.scheduler.kafka.orchestrator import KafkaOrchestrator +from langgraph.scheduler.kafka.types import MessageToOrchestrator, Topics + +pytestmark = pytest.mark.anyio + + +def mk_fanout_graph(checkpointer: BaseCheckpointSaver) -> Pregel: + # copied from test_in_one_fan_out_state_graph_waiting_edge_multiple_cond_edge + def sorted_add( + x: list[str], y: Union[list[str], list[tuple[str, str]]] + ) -> list[str]: + if isinstance(y[0], tuple): + for rem, _ in y: + x.remove(rem) + y = [t[1] for t in y] + return sorted(operator.add(x, y)) + + class State(TypedDict, total=False): + query: str + answer: str + docs: Annotated[list[str], sorted_add] + + async def rewrite_query(data: State) -> State: + print("rewrite_query", data) + return {"query": f'query: {data["query"]}'} + + async def retriever_picker(data: State) -> list[str]: + return ["analyzer_one", "retriever_two"] + + async def analyzer_one(data: State) -> State: + return {"query": f'analyzed: {data["query"]}'} + + async def retriever_one(data: State) -> State: + return {"docs": ["doc1", "doc2"]} + + async def retriever_two(data: State) -> State: + await asyncio.sleep(0.1) + return {"docs": ["doc3", "doc4"]} + + async def qa(data: State) -> State: + return {"answer": ",".join(data["docs"])} + + async def decider(data: State) -> None: + return None + + def decider_cond(data: State) -> str: + if data["query"].count("analyzed") > 1: + return "qa" + else: + return "rewrite_query" + + builder = StateGraph(State) + + builder.add_node("rewrite_query", rewrite_query) + builder.add_node("analyzer_one", analyzer_one) + builder.add_node("retriever_one", retriever_one) + builder.add_node("retriever_two", retriever_two) + builder.add_node("decider", decider) + builder.add_node("qa", qa) + + builder.set_entry_point("rewrite_query") + builder.add_conditional_edges("rewrite_query", retriever_picker) + builder.add_edge("analyzer_one", "retriever_one") + builder.add_edge(["retriever_one", "retriever_two"], "decider") + builder.add_conditional_edges("decider", decider_cond) + builder.set_finish_point("qa") + + return builder.compile(checkpointer) + + +async def test_fanout_graph(topics: Topics, checkpointer: BaseCheckpointSaver) -> None: + graph = mk_fanout_graph(checkpointer) + n_orch_msgs = 0 + n_exec_msgs = 0 + + async def orchestrator() -> None: + nonlocal n_orch_msgs + async with KafkaOrchestrator(graph, topics) as orch: + async for msg in orch: + n_orch_msgs += 1 + print("orch", msg) + + async def executor() -> None: + nonlocal n_exec_msgs + async with KafkaExecutor(graph, topics) as exec: + async for msg in exec: + n_exec_msgs += 1 + print("exec", msg) + + async with asyncio.TaskGroup() as tg: + o = tg.create_task(orchestrator(), name="orchestrator") + e = tg.create_task(executor(), name="executor") + + # start a new run + producer = AIOKafkaProducer(value_serializer=serde.dumps) + await producer.start() + await producer.send_and_wait( + topics.orchestrator, + MessageToOrchestrator( + input={"query": "what is weather in sf"}, + config={"configurable": {"thread_id": "1"}}, + ), + ) + await producer.stop() + + # wait for the run to finish + await asyncio.sleep(5) + o.cancel() + e.cancel() + + assert n_orch_msgs == 13 + assert n_exec_msgs == 12