mirror of
https://github.com/langchain-ai/langgraph.git
synced 2026-10-02 14:35:18 +02:00
Compare commits
13
Commits
| Author | SHA1 | Date | |
|---|---|---|---|
 Quanzheng Long
|
388d6b3593 | ||
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Quanzheng Long
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667b679694 | ||
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Quanzheng Long
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ccb9f4c41a | ||
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Quanzheng Long
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789be99634 | ||
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Quanzheng Long
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e33842ff54 | ||
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Quanzheng Long
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89d37a0f9b | ||
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Quanzheng Long
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8f717d3874 | ||
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Quanzheng Long
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508193272a | ||
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Quanzheng Long
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788ae6cb72 | ||
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Quanzheng Long
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b2dca399e8 | ||
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Quanzheng Long
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4b2167dd25 | ||
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Quanzheng Long
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be46e91180 | ||
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Quanzheng Long
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bbb308259b |
@@ -117,8 +117,8 @@ jobs:
|
||||
timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-h
|
||||
echo "Finished starting up langgraph-test-h"
|
||||
LANGGRAPH_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langgraph'); print(v);")
|
||||
if [ "$LANGGRAPH_VERSION" != "1.1.2" ]; then
|
||||
echo "LANGGRAPH_VERSION != 1.1.2; $LANGGRAPH_VERSION"
|
||||
if [ "$LANGGRAPH_VERSION" != "1.0.8" ]; then
|
||||
echo "LANGGRAPH_VERSION != 1.0.8; $LANGGRAPH_VERSION"
|
||||
exit 1
|
||||
fi
|
||||
LANGCHAIN_OPENAI_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langchain-openai'); print(v);")
|
||||
|
||||
@@ -30,7 +30,7 @@ jobs:
|
||||
deps: ${{ steps.filter.outputs.deps || 'true' }}
|
||||
steps:
|
||||
- uses: actions/checkout@v6
|
||||
- uses: dorny/paths-filter@v4
|
||||
- uses: dorny/paths-filter@v3
|
||||
if: github.event_name != 'workflow_dispatch'
|
||||
id: filter
|
||||
with:
|
||||
|
||||
@@ -1,14 +0,0 @@
|
||||
{
|
||||
"MD013": false,
|
||||
"MD024": {
|
||||
"siblings_only": true
|
||||
},
|
||||
"MD025": false,
|
||||
"MD033": false,
|
||||
"MD034": false,
|
||||
"MD036": false,
|
||||
"MD041": false,
|
||||
"MD046": {
|
||||
"style": "fenced"
|
||||
}
|
||||
}
|
||||
@@ -1,81 +1,93 @@
|
||||
<div align="center">
|
||||
<a href="https://www.langchain.com/langgraph">
|
||||
<picture>
|
||||
<source media="(prefers-color-scheme: dark)" srcset=".github/images/logo-dark.svg">
|
||||
<source media="(prefers-color-scheme: light)" srcset=".github/images/logo-light.svg">
|
||||
<img alt="LangGraph Logo" src=".github/images/logo-dark.svg" width="50%">
|
||||
</picture>
|
||||
</a>
|
||||
</div>
|
||||
|
||||
<div align="center">
|
||||
<h3>Low-level orchestration framework for building stateful agents.</h3>
|
||||
</div>
|
||||
|
||||
<div align="center">
|
||||
<a href="https://opensource.org/licenses/MIT" target="_blank"><img src="https://img.shields.io/pypi/l/langgraph" alt="PyPI - License"></a>
|
||||
<a href="https://pypistats.org/packages/langgraph" target="_blank"><img src="https://img.shields.io/pepy/dt/langgraph" alt="PyPI - Downloads"></a>
|
||||
<a href="https://pypi.org/project/langgraph/" target="_blank"><img src="https://img.shields.io/pypi/v/langgraph.svg?label=%20" alt="Version"></a>
|
||||
<a href="https://x.com/langchain" target="_blank"><img src="https://img.shields.io/twitter/url/https/twitter.com/langchain.svg?style=social&label=Follow%20%40LangChain" alt="Twitter / X"></a>
|
||||
</div>
|
||||
<picture class="github-only">
|
||||
<source media="(prefers-color-scheme: light)" srcset=".github/images/logo-light.svg">
|
||||
<source media="(prefers-color-scheme: dark)" srcset=".github/images/logo-dark.svg">
|
||||
<img alt="LangGraph Logo" src=".github/images/logo-dark.svg" width="50%">
|
||||
</picture>
|
||||
|
||||
<div>
|
||||
<br>
|
||||
</div>
|
||||
|
||||
[](https://pypi.org/project/langgraph/)
|
||||
[](https://pepy.tech/project/langgraph)
|
||||
[](https://github.com/langchain-ai/langgraph/issues)
|
||||
[](https://docs.langchain.com/oss/python/langgraph/overview)
|
||||
|
||||
Trusted by companies shaping the future of agents – including Klarna, Replit, Elastic, and more – LangGraph is a low-level orchestration framework for building, managing, and deploying long-running, stateful agents.
|
||||
|
||||
```bash
|
||||
## Get started
|
||||
|
||||
Install LangGraph:
|
||||
|
||||
```
|
||||
pip install -U langgraph
|
||||
```
|
||||
|
||||
If you're looking to quickly build agents with LangChain's `create_agent` (built on LangGraph), check out the [LangChain Agents documentation](https://docs.langchain.com/oss/python/langchain/agents).
|
||||
Create a simple workflow:
|
||||
|
||||
> [!NOTE]
|
||||
> Looking for the JS/TS library? Check out [LangGraph.js](https://github.com/langchain-ai/langgraphjs) and the [JS docs](https://docs.langchain.com/oss/javascript/langgraph/overview).
|
||||
```python
|
||||
from langgraph.graph import START, StateGraph
|
||||
from typing_extensions import TypedDict
|
||||
|
||||
## Why use LangGraph?
|
||||
|
||||
LangGraph provides low-level supporting infrastructure for *any* long-running, stateful workflow or agent:
|
||||
class State(TypedDict):
|
||||
text: str
|
||||
|
||||
- **[Durable execution](https://docs.langchain.com/oss/python/langgraph/durable-execution)** — Build agents that persist through failures and can run for extended periods, automatically resuming from exactly where they left off.
|
||||
- **[Human-in-the-loop](https://docs.langchain.com/oss/python/langgraph/interrupts)** — Seamlessly incorporate human oversight by inspecting and modifying agent state at any point during execution.
|
||||
- **[Comprehensive memory](https://docs.langchain.com/oss/python/langgraph/memory)** — Create truly stateful agents with both short-term working memory for ongoing reasoning and long-term persistent memory across sessions.
|
||||
- **[Debugging with LangSmith](https://www.langchain.com/langsmith)** — Gain deep visibility into complex agent behavior with visualization tools that trace execution paths, capture state transitions, and provide detailed runtime metrics.
|
||||
- **[Production-ready deployment](https://docs.langchain.com/langsmith/deployments)** — Deploy sophisticated agent systems confidently with scalable infrastructure designed to handle the unique challenges of stateful, long-running workflows.
|
||||
|
||||
def node_a(state: State) -> dict:
|
||||
return {"text": state["text"] + "a"}
|
||||
|
||||
|
||||
def node_b(state: State) -> dict:
|
||||
return {"text": state["text"] + "b"}
|
||||
|
||||
|
||||
graph = StateGraph(State)
|
||||
graph.add_node("node_a", node_a)
|
||||
graph.add_node("node_b", node_b)
|
||||
graph.add_edge(START, "node_a")
|
||||
graph.add_edge("node_a", "node_b")
|
||||
|
||||
print(graph.compile().invoke({"text": ""}))
|
||||
# {'text': 'ab'}
|
||||
```
|
||||
|
||||
Get started with the [LangGraph Quickstart](https://docs.langchain.com/oss/python/langgraph/quickstart).
|
||||
|
||||
To quickly build agents with LangChain's `create_agent` (built on LangGraph), see the [LangChain Agents documentation](https://docs.langchain.com/oss/python/langchain/agents).
|
||||
|
||||
> [!TIP]
|
||||
> For developing, debugging, and deploying AI agents and LLM applications, see [LangSmith](https://docs.langchain.com/langsmith/home).
|
||||
|
||||
## LangGraph ecosystem
|
||||
## Core benefits
|
||||
|
||||
While LangGraph can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools for building agents.
|
||||
LangGraph provides low-level supporting infrastructure for *any* long-running, stateful workflow or agent. LangGraph does not abstract prompts or architecture, and provides the following central benefits:
|
||||
|
||||
To improve your LLM application development, pair LangGraph with:
|
||||
- [Durable execution](https://docs.langchain.com/oss/python/langgraph/durable-execution): Build agents that persist through failures and can run for extended periods, automatically resuming from exactly where they left off.
|
||||
- [Human-in-the-loop](https://docs.langchain.com/oss/python/langgraph/interrupts): Seamlessly incorporate human oversight by inspecting and modifying agent state at any point during execution.
|
||||
- [Comprehensive memory](https://docs.langchain.com/oss/python/langgraph/memory): Create truly stateful agents with both short-term working memory for ongoing reasoning and long-term persistent memory across sessions.
|
||||
- [Debugging with LangSmith](http://www.langchain.com/langsmith): Gain deep visibility into complex agent behavior with visualization tools that trace execution paths, capture state transitions, and provide detailed runtime metrics.
|
||||
- [Production-ready deployment](https://docs.langchain.com/langsmith/app-development): Deploy sophisticated agent systems confidently with scalable infrastructure designed to handle the unique challenges of stateful, long-running workflows.
|
||||
|
||||
- [Deep Agents](https://github.com/langchain-ai/deepagents) *(new!)* – Build agents that can plan, use subagents, and leverage file systems for complex tasks.
|
||||
## LangGraph’s ecosystem
|
||||
|
||||
While LangGraph can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools for building agents. To improve your LLM application development, pair LangGraph with:
|
||||
|
||||
- [LangSmith](http://www.langchain.com/langsmith) — Helpful for agent evals and observability. Debug poor-performing LLM app runs, evaluate agent trajectories, gain visibility in production, and improve performance over time.
|
||||
- [LangSmith Deployment](https://docs.langchain.com/langsmith/deployments) — Deploy and scale agents effortlessly with a purpose-built deployment platform for long running, stateful workflows. Discover, reuse, configure, and share agents across teams — and iterate quickly with visual prototyping in [LangGraph Studio](https://docs.langchain.com/oss/python/langgraph/studio).
|
||||
- [LangChain](https://docs.langchain.com/oss/python/langchain/overview) – Provides integrations and composable components to streamline LLM application development.
|
||||
- [LangSmith](https://www.langchain.com/langsmith) – Helpful for agent evals and observability. Debug poor-performing LLM app runs, evaluate agent trajectories, gain visibility in production, and improve performance over time.
|
||||
- [LangSmith Deployment](https://docs.langchain.com/langsmith/deployments) – Deploy and scale agents effortlessly with a purpose-built deployment platform for long-running, stateful workflows. Discover, reuse, configure, and share agents across teams – and iterate quickly with visual prototyping in [LangSmith Studio](https://docs.langchain.com/langsmith/studio).
|
||||
|
||||
---
|
||||
|
||||
## Documentation
|
||||
|
||||
- [docs.langchain.com](https://docs.langchain.com/oss/python/langgraph/overview) – Comprehensive documentation, including conceptual overviews and guides
|
||||
- [reference.langchain.com/python/langgraph](https://reference.langchain.com/python/langgraph) – API reference docs for LangGraph packages
|
||||
- [LangGraph Quickstart](https://docs.langchain.com/oss/python/langgraph/quickstart) – Get started building with LangGraph
|
||||
- [Chat LangChain](https://chat.langchain.com/) – Chat with the LangChain documentation and get answers to your questions
|
||||
|
||||
**Discussions**: Visit the [LangChain Forum](https://forum.langchain.com) to connect with the community and share all of your technical questions, ideas, and feedback.
|
||||
> [!NOTE]
|
||||
> Looking for the JS version of LangGraph? See the [JS repo](https://github.com/langchain-ai/langgraphjs) and the [JS docs](https://docs.langchain.com/oss/javascript/langgraph/overview).
|
||||
|
||||
## Additional resources
|
||||
|
||||
- **[Guides](https://docs.langchain.com/oss/python/learn)** – Quick, actionable code snippets for topics such as streaming, adding memory & persistence, and design patterns (e.g. branching, subgraphs, etc.).
|
||||
- **[LangChain Academy](https://academy.langchain.com/courses/intro-to-langgraph)** – Learn the basics of LangGraph in our free, structured course.
|
||||
- **[Case studies](https://www.langchain.com/built-with-langgraph)** – Hear how industry leaders use LangGraph to ship AI applications at scale.
|
||||
- [Contributing Guide](https://docs.langchain.com/oss/python/contributing/overview) – Learn how to contribute to LangChain projects and find good first issues.
|
||||
- [Code of Conduct](https://github.com/langchain-ai/langchain/?tab=coc-ov-file) – Our community guidelines and standards for participation.
|
||||
|
||||
---
|
||||
- [Guides](https://docs.langchain.com/oss/python/langgraph/overview): Quick, actionable code snippets for topics such as streaming, adding memory & persistence, and design patterns (e.g. branching, subgraphs, etc.).
|
||||
- [Reference](https://reference.langchain.com/python/langgraph/): Detailed reference on core classes, methods, how to use the graph and checkpointing APIs, and higher-level prebuilt components.
|
||||
- [Examples](https://docs.langchain.com/oss/python/langgraph/agentic-rag): Guided examples on getting started with LangGraph.
|
||||
- [LangChain Forum](https://forum.langchain.com/): Connect with the community and share all of your technical questions, ideas, and feedback.
|
||||
- [LangChain Academy](https://academy.langchain.com/courses/intro-to-langgraph): Learn the basics of LangGraph in our free, structured course.
|
||||
- [Case studies](https://www.langchain.com/built-with-langgraph): Hear how industry leaders use LangGraph to ship AI applications at scale.
|
||||
|
||||
## Acknowledgements
|
||||
|
||||
|
||||
@@ -89,7 +89,7 @@ async def put_test_checkpoint(
|
||||
vals = channel_values or {}
|
||||
cv = channel_versions
|
||||
if cv is None and vals:
|
||||
cv: ChannelVersions = {k: 1 for k in vals}
|
||||
cv = {k: 1 for k in vals}
|
||||
cp["channel_versions"] = cv
|
||||
nv = new_versions
|
||||
if nv is None:
|
||||
|
||||
Generated
+40
-40
@@ -250,15 +250,15 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "langgraph-checkpoint"
|
||||
version = "4.0.1"
|
||||
version = "4.0.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "langchain-core" },
|
||||
{ name = "ormsgpack" },
|
||||
]
|
||||
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||||
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||||
wheels = [
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|
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|
||||
[[package]]
|
||||
@@ -746,27 +746,27 @@ wheels = [
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|
||||
[[package]]
|
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|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
||||
@@ -164,11 +164,12 @@ class AsyncPostgresStore(AsyncBatchedBaseStore, BasePostgresStore[_ainternal.Con
|
||||
grouped_ops, num_ops = _group_ops(ops)
|
||||
results: list[Result] = [None] * num_ops
|
||||
|
||||
if self.pipe:
|
||||
async with self.pipe:
|
||||
await self._execute_batch(grouped_ops, results)
|
||||
else:
|
||||
await self._execute_batch(grouped_ops, results)
|
||||
async with _ainternal.get_connection(self.conn) as conn:
|
||||
if self.pipe:
|
||||
async with self.pipe:
|
||||
await self._execute_batch(grouped_ops, results, conn)
|
||||
else:
|
||||
await self._execute_batch(grouped_ops, results, conn)
|
||||
|
||||
return results
|
||||
|
||||
@@ -409,10 +410,8 @@ class AsyncPostgresStore(AsyncBatchedBaseStore, BasePostgresStore[_ainternal.Con
|
||||
self,
|
||||
grouped_ops: dict,
|
||||
results: list[Result],
|
||||
conn: AsyncConnection[DictRow] | None = None,
|
||||
conn: AsyncConnection[DictRow],
|
||||
) -> None:
|
||||
# Keep `conn` for compatibility with subclasses overriding this private hook.
|
||||
# All database I/O goes through `_cursor()`, which owns connection acquisition.
|
||||
async with self._cursor(pipeline=True) as cur:
|
||||
if GetOp in grouped_ops:
|
||||
await self._batch_get_ops(
|
||||
|
||||
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
|
||||
|
||||
[project]
|
||||
name = "langgraph-checkpoint-postgres"
|
||||
version = "3.0.5"
|
||||
version = "3.0.4"
|
||||
description = "Library with a Postgres implementation of LangGraph checkpoint saver."
|
||||
authors = []
|
||||
requires-python = ">=3.10"
|
||||
|
||||
@@ -20,7 +20,6 @@ from langgraph.store.base import (
|
||||
)
|
||||
from psycopg import AsyncConnection
|
||||
|
||||
from langgraph.checkpoint.postgres import _ainternal
|
||||
from langgraph.store.postgres import AsyncPostgresStore
|
||||
from tests.conftest import (
|
||||
DEFAULT_URI,
|
||||
@@ -347,59 +346,6 @@ async def test_batch_list_namespaces_ops(store: AsyncPostgresStore) -> None:
|
||||
assert ("test", "namespace2") in results[0]
|
||||
|
||||
|
||||
@asynccontextmanager
|
||||
async def _create_pool_store() -> AsyncIterator[AsyncPostgresStore]:
|
||||
database = f"test_{uuid.uuid4().hex[:16]}"
|
||||
uri_parts = DEFAULT_URI.split("/")
|
||||
uri_base = "/".join(uri_parts[:-1])
|
||||
query_params = ""
|
||||
if "?" in uri_parts[-1]:
|
||||
_, query_params = uri_parts[-1].split("?", 1)
|
||||
query_params = "?" + query_params
|
||||
|
||||
conn_string = f"{uri_base}/{database}{query_params}"
|
||||
admin_conn_string = DEFAULT_URI
|
||||
async with await AsyncConnection.connect(
|
||||
admin_conn_string, autocommit=True
|
||||
) as conn:
|
||||
await conn.execute(f"CREATE DATABASE {database}")
|
||||
try:
|
||||
async with AsyncPostgresStore.from_conn_string(
|
||||
conn_string, pool_config={"min_size": 1, "max_size": 1}
|
||||
) as store:
|
||||
await store.setup()
|
||||
yield store
|
||||
finally:
|
||||
async with await AsyncConnection.connect(
|
||||
admin_conn_string, autocommit=True
|
||||
) as conn:
|
||||
await conn.execute(f"DROP DATABASE {database}")
|
||||
|
||||
|
||||
async def test_abatch_uses_single_pool_checkout(monkeypatch) -> None:
|
||||
async with _create_pool_store() as store:
|
||||
await store.aput(("test",), "key1", {"data": "value1"})
|
||||
|
||||
original_get_connection = _ainternal.get_connection
|
||||
checkout_count = 0
|
||||
|
||||
@asynccontextmanager
|
||||
async def counting_get_connection(conn):
|
||||
nonlocal checkout_count
|
||||
checkout_count += 1
|
||||
async with original_get_connection(conn) as checked_out_conn:
|
||||
yield checked_out_conn
|
||||
|
||||
monkeypatch.setattr(_ainternal, "get_connection", counting_get_connection)
|
||||
|
||||
results = await store.abatch([GetOp(namespace=("test",), key="key1")])
|
||||
|
||||
assert len(results) == 1
|
||||
assert results[0] is not None
|
||||
assert results[0].value == {"data": "value1"}
|
||||
assert checkout_count == 1
|
||||
|
||||
|
||||
@asynccontextmanager
|
||||
async def _create_vector_store(
|
||||
vector_type: str,
|
||||
|
||||
Generated
+20
-20
@@ -307,7 +307,7 @@ test = [
|
||||
|
||||
[[package]]
|
||||
name = "langgraph-checkpoint-postgres"
|
||||
version = "3.0.5"
|
||||
version = "3.0.4"
|
||||
source = { editable = "." }
|
||||
dependencies = [
|
||||
{ name = "langgraph-checkpoint" },
|
||||
@@ -1074,27 +1074,27 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "ruff"
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||||
version = "0.15.6"
|
||||
version = "0.15.5"
|
||||
source = { registry = "https://pypi.org/simple" }
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||||
sdist = { url = "https://files.pythonhosted.org/packages/51/df/f8629c19c5318601d3121e230f74cbee7a3732339c52b21daa2b82ef9c7d/ruff-0.15.6.tar.gz", hash = "sha256:8394c7bb153a4e3811a4ecdacd4a8e6a4fa8097028119160dffecdcdf9b56ae4", size = 4597916, upload-time = "2026-03-12T23:05:47.51Z" }
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||||
sdist = { url = "https://files.pythonhosted.org/packages/77/9b/840e0039e65fcf12758adf684d2289024d6140cde9268cc59887dc55189c/ruff-0.15.5.tar.gz", hash = "sha256:7c3601d3b6d76dce18c5c824fc8d06f4eef33d6df0c21ec7799510cde0f159a2", size = 4574214, upload-time = "2026-03-05T20:06:34.946Z" }
|
||||
wheels = [
|
||||
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||||
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{ url = "https://files.pythonhosted.org/packages/6c/25/3fc9114abf979a41673ce877c08016f8e660ad6cf508c3957f537d2e9fa9/ruff-0.15.6-py3-none-win32.whl", hash = "sha256:bbf67d39832404812a2d23020dda68fee7f18ce15654e96fb1d3ad21a5fe436c", size = 10616872, upload-time = "2026-03-12T23:05:42.451Z" },
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||||
{ url = "https://files.pythonhosted.org/packages/7f/d0/578c47dd68152ddddddf31cd7fc67dc30b7cdf639a86275fda821b0d9d98/ruff-0.15.6-py3-none-win_arm64.whl", hash = "sha256:c34de3dd0b0ba203be50ae70f5910b17188556630e2178fd7d79fc030eb0d837", size = 11060497, upload-time = "2026-03-12T23:05:25.968Z" },
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||||
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||||
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{ url = "https://files.pythonhosted.org/packages/c4/8f/533075f00aaf19b07c5cd6aa6e5d89424b06b3b3f4583bfa9c640a079059/ruff-0.15.5-py3-none-macosx_11_0_arm64.whl", hash = "sha256:89f463f7c8205a9f8dea9d658d59eff49db05f88f89cc3047fb1a02d9f344010", size = 10184752, upload-time = "2026-03-05T20:06:40.312Z" },
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{ url = "https://files.pythonhosted.org/packages/66/0e/ba49e2c3fa0395b3152bad634c7432f7edfc509c133b8f4529053ff024fb/ruff-0.15.5-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ba786a8295c6574c1116704cf0b9e6563de3432ac888d8f83685654fe528fd65", size = 10534857, upload-time = "2026-03-05T20:06:19.581Z" },
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]
|
||||
|
||||
[[package]]
|
||||
|
||||
@@ -328,9 +328,6 @@ async def _run(
|
||||
store: weakref.ReferenceType[BaseStore],
|
||||
) -> None:
|
||||
while item := await aqueue.get():
|
||||
# don't run batch if the future is done (e.g. cancelled)
|
||||
if item[0].done():
|
||||
continue
|
||||
# check if store is still alive
|
||||
if s := store():
|
||||
try:
|
||||
@@ -338,9 +335,6 @@ async def _run(
|
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items = [item]
|
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try:
|
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while item := aqueue.get_nowait():
|
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# don't insert if the future is done (e.g. cancelled)
|
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if item[0].done():
|
||||
continue
|
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items.append(item)
|
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except asyncio.QueueEmpty:
|
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pass
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Generated
+97
-97
@@ -267,7 +267,7 @@ wheels = [
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[[package]]
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{ name = "jsonpatch" },
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[[package]]
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@@ -676,83 +676,83 @@ wheels = [
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||||
[[package]]
|
||||
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
|
||||
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|
||||
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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File diff suppressed because it is too large
Load Diff
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|
||||
version "8.57.0"
|
||||
resolved "https://registry.yarnpkg.com/@typescript-eslint/scope-manager/-/scope-manager-8.57.0.tgz#7d2a2aeaaef2ae70891b21939fadb4cb0b19f840"
|
||||
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||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"@typescript-eslint/utils" "8.56.1"
|
||||
debug "^4.4.3"
|
||||
ts-api-utils "^2.4.0"
|
||||
|
||||
"@typescript-eslint/types@8.57.0", "@typescript-eslint/types@^8.57.0":
|
||||
version "8.57.0"
|
||||
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|
||||
integrity sha512-dTLI8PEXhjUC7B9Kre+u0XznO696BhXcTlOn0/6kf1fHaQW8+VjJAVHJ3eTI14ZapTxdkOmc80HblPQLaEeJdg==
|
||||
"@typescript-eslint/types@8.56.1", "@typescript-eslint/types@^8.56.1":
|
||||
version "8.56.1"
|
||||
resolved "https://registry.yarnpkg.com/@typescript-eslint/types/-/types-8.56.1.tgz#975e5942bf54895291337c91b9191f6eb0632ab9"
|
||||
integrity sha512-dbMkdIUkIkchgGDIv7KLUpa0Mda4IYjo4IAMJUZ+3xNoUXxMsk9YtKpTHSChRS85o+H9ftm51gsK1dZReY9CVw==
|
||||
|
||||
"@typescript-eslint/typescript-estree@8.57.0":
|
||||
version "8.57.0"
|
||||
resolved "https://registry.yarnpkg.com/@typescript-eslint/typescript-estree/-/typescript-estree-8.57.0.tgz#e0e4a89bfebb207de314826df876e2dabc7dea04"
|
||||
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|
||||
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|
||||
version "8.56.1"
|
||||
resolved "https://registry.yarnpkg.com/@typescript-eslint/typescript-estree/-/typescript-estree-8.56.1.tgz#3b9e57d8129a860c50864c42188f761bdef3eab0"
|
||||
integrity sha512-qzUL1qgalIvKWAf9C1HpvBjif+Vm6rcT5wZd4VoMb9+Km3iS3Cv9DY6dMRMDtPnwRAFyAi7YXJpTIEXLvdfPxg==
|
||||
dependencies:
|
||||
"@typescript-eslint/project-service" "8.57.0"
|
||||
"@typescript-eslint/tsconfig-utils" "8.57.0"
|
||||
"@typescript-eslint/types" "8.57.0"
|
||||
"@typescript-eslint/visitor-keys" "8.57.0"
|
||||
"@typescript-eslint/project-service" "8.56.1"
|
||||
"@typescript-eslint/tsconfig-utils" "8.56.1"
|
||||
"@typescript-eslint/types" "8.56.1"
|
||||
"@typescript-eslint/visitor-keys" "8.56.1"
|
||||
debug "^4.4.3"
|
||||
minimatch "^10.2.2"
|
||||
semver "^7.7.3"
|
||||
tinyglobby "^0.2.15"
|
||||
ts-api-utils "^2.4.0"
|
||||
|
||||
"@typescript-eslint/utils@8.57.0":
|
||||
version "8.57.0"
|
||||
resolved "https://registry.yarnpkg.com/@typescript-eslint/utils/-/utils-8.57.0.tgz#c7193385b44529b788210d20c94c11de79ad3498"
|
||||
integrity sha512-5iIHvpD3CZe06riAsbNxxreP+MuYgVUsV0n4bwLH//VJmgtt54sQeY2GszntJ4BjYCpMzrfVh2SBnUQTtys2lQ==
|
||||
"@typescript-eslint/utils@8.56.1":
|
||||
version "8.56.1"
|
||||
resolved "https://registry.yarnpkg.com/@typescript-eslint/utils/-/utils-8.56.1.tgz#5a86acaf9f1b4c4a85a42effb217f73059f6deb7"
|
||||
integrity sha512-HPAVNIME3tABJ61siYlHzSWCGtOoeP2RTIaHXFMPqjrQKCGB9OgUVdiNgH7TJS2JNIQ5qQ4RsAUDuGaGme/KOA==
|
||||
dependencies:
|
||||
"@eslint-community/eslint-utils" "^4.9.1"
|
||||
"@typescript-eslint/scope-manager" "8.57.0"
|
||||
"@typescript-eslint/types" "8.57.0"
|
||||
"@typescript-eslint/typescript-estree" "8.57.0"
|
||||
"@typescript-eslint/scope-manager" "8.56.1"
|
||||
"@typescript-eslint/types" "8.56.1"
|
||||
"@typescript-eslint/typescript-estree" "8.56.1"
|
||||
|
||||
"@typescript-eslint/visitor-keys@8.57.0":
|
||||
version "8.57.0"
|
||||
resolved "https://registry.yarnpkg.com/@typescript-eslint/visitor-keys/-/visitor-keys-8.57.0.tgz#23aea662279bb66209700854453807a119350f85"
|
||||
integrity sha512-zm6xx8UT/Xy2oSr2ZXD0pZo7Jx2XsCoID2IUh9YSTFRu7z+WdwYTRk6LhUftm1crwqbuoF6I8zAFeCMw0YjwDg==
|
||||
"@typescript-eslint/visitor-keys@8.56.1":
|
||||
version "8.56.1"
|
||||
resolved "https://registry.yarnpkg.com/@typescript-eslint/visitor-keys/-/visitor-keys-8.56.1.tgz#50e03475c33a42d123dc99e63acf1841c0231f87"
|
||||
integrity sha512-KiROIzYdEV85YygXw6BI/Dx4fnBlFQu6Mq4QE4MOH9fFnhohw6wX/OAvDY2/C+ut0I3RSPKenvZJIVYqJNkhEw==
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||||
dependencies:
|
||||
"@typescript-eslint/types" "8.57.0"
|
||||
"@typescript-eslint/types" "8.56.1"
|
||||
eslint-visitor-keys "^5.0.0"
|
||||
|
||||
acorn-jsx@^5.3.2:
|
||||
@@ -1850,47 +1850,47 @@ tsconfig-paths@^3.15.0:
|
||||
minimist "^1.2.6"
|
||||
strip-bom "^3.0.0"
|
||||
|
||||
turbo-darwin-64@2.8.17:
|
||||
version "2.8.17"
|
||||
resolved "https://registry.yarnpkg.com/turbo-darwin-64/-/turbo-darwin-64-2.8.17.tgz#265fe92ca6c923fae0c688b2dbcce5602e121221"
|
||||
integrity sha512-ZFkv2hv7zHpAPEXBF6ouRRXshllOavYc+jjcrYyVHvxVTTwJWsBZwJ/gpPzmOKGvkSjsEyDO5V6aqqtZzwVF+Q==
|
||||
turbo-darwin-64@2.8.14:
|
||||
version "2.8.14"
|
||||
resolved "https://registry.yarnpkg.com/turbo-darwin-64/-/turbo-darwin-64-2.8.14.tgz#80d0d414c3e7738df9eb414b4d7de46a4a6be55f"
|
||||
integrity sha512-9sFi7n2lLfEsGWi5OEoA/eTtQU2BPKtzSYKqufMtDeRmqMT9vKjbv9gJCRkllSVE9BOXA0qXC3diyX8V8rKIKw==
|
||||
|
||||
turbo-darwin-arm64@2.8.17:
|
||||
version "2.8.17"
|
||||
resolved "https://registry.yarnpkg.com/turbo-darwin-arm64/-/turbo-darwin-arm64-2.8.17.tgz#0a0fd172a0ea28cc10e494ccf56f8e44301cdd2d"
|
||||
integrity sha512-5DXqhQUt24ycEryXDfMNKEkW5TBHs+QmU23a2qxXwwFDaJsWcPo2obEhBxxdEPOv7qmotjad+09RGeWCcJ9JDw==
|
||||
turbo-darwin-arm64@2.8.14:
|
||||
version "2.8.14"
|
||||
resolved "https://registry.yarnpkg.com/turbo-darwin-arm64/-/turbo-darwin-arm64-2.8.14.tgz#82223469a29f5831ddba7439c31dff4e0e31bb0b"
|
||||
integrity sha512-aS4yJuy6A1PCLws+PJpZP0qCURG8Y5iVx13z/WAbKyeDTY6W6PiGgcEllSaeLGxyn++382ztN/EZH85n2zZ6VQ==
|
||||
|
||||
turbo-linux-64@2.8.17:
|
||||
version "2.8.17"
|
||||
resolved "https://registry.yarnpkg.com/turbo-linux-64/-/turbo-linux-64-2.8.17.tgz#d4361e48bb0b3c849200723157ecfa085fe465dd"
|
||||
integrity sha512-KLUbz6w7F73D/Ihh51hVagrKR0/CTsPEbRkvXLXvoND014XJ4BCrQUqSxlQ4/hu+nqp1v5WlM85/h3ldeyujuA==
|
||||
turbo-linux-64@2.8.14:
|
||||
version "2.8.14"
|
||||
resolved "https://registry.yarnpkg.com/turbo-linux-64/-/turbo-linux-64-2.8.14.tgz#98c38fa898ae8f9f693256c0a3abe8852e64b907"
|
||||
integrity sha512-XC6wPUDJkakjhNLaS0NrHDMiujRVjH+naEAwvKLArgqRaFkNxjmyNDRM4eu3soMMFmjym6NTxYaF74rvET+Orw==
|
||||
|
||||
turbo-linux-arm64@2.8.17:
|
||||
version "2.8.17"
|
||||
resolved "https://registry.yarnpkg.com/turbo-linux-arm64/-/turbo-linux-arm64-2.8.17.tgz#3fc2d0c93786874651b679ea7a269e3449b2463c"
|
||||
integrity sha512-pJK67XcNJH40lTAjFu7s/rUlobgVXyB3A3lDoq+/JccB3hf+SysmkpR4Itlc93s8LEaFAI4mamhFuTV17Z6wOg==
|
||||
turbo-linux-arm64@2.8.14:
|
||||
version "2.8.14"
|
||||
resolved "https://registry.yarnpkg.com/turbo-linux-arm64/-/turbo-linux-arm64-2.8.14.tgz#60402c49e31f603d903c7d3d9aa92fbc981ca915"
|
||||
integrity sha512-ChfE7isyVNjZrVSPDwcfqcHLG/FuIBbOFxnt1FM8vSuBGzHAs8AlTdwFNIxlEMJfZ8Ad9mdMxdmsCUPIWiQ6cg==
|
||||
|
||||
turbo-windows-64@2.8.17:
|
||||
version "2.8.17"
|
||||
resolved "https://registry.yarnpkg.com/turbo-windows-64/-/turbo-windows-64-2.8.17.tgz#67f45f883fef586f12807d332702fb8009cce1af"
|
||||
integrity sha512-EijeQ6zszDMmGZLP2vT2RXTs/GVi9rM0zv2/G4rNu2SSRSGFapgZdxgW4b5zUYLVaSkzmkpWlGfPfj76SW9yUg==
|
||||
turbo-windows-64@2.8.14:
|
||||
version "2.8.14"
|
||||
resolved "https://registry.yarnpkg.com/turbo-windows-64/-/turbo-windows-64-2.8.14.tgz#dcf39ef4ffe307fe6e460aa1261cf01e2cf3b723"
|
||||
integrity sha512-FTbIeQL1ycLFW2t9uQNMy+bRSzi3Xhwun/e7ZhFBdM+U0VZxxrtfYEBM9CHOejlfqomk6Jh7aRz0sJoqYn39Hg==
|
||||
|
||||
turbo-windows-arm64@2.8.17:
|
||||
version "2.8.17"
|
||||
resolved "https://registry.yarnpkg.com/turbo-windows-arm64/-/turbo-windows-arm64-2.8.17.tgz#e3c2a471f6f64e1e4084bd3e51d219cbd6e60608"
|
||||
integrity sha512-crpfeMPkfECd4V1PQ/hMoiyVcOy04+bWedu/if89S15WhOalHZ2BYUi6DOJhZrszY+mTT99OwpOsj4wNfb/GHQ==
|
||||
turbo-windows-arm64@2.8.14:
|
||||
version "2.8.14"
|
||||
resolved "https://registry.yarnpkg.com/turbo-windows-arm64/-/turbo-windows-arm64-2.8.14.tgz#03115f32db5a3980c1e747541aff135d828baf3f"
|
||||
integrity sha512-KgZX12cTyhY030qS7ieT8zRkhZZE2VWJasDFVUSVVn17nR7IShpv68/7j5UqJNeRLIGF1XPK0phsP5V5yw3how==
|
||||
|
||||
turbo@^2.8.17:
|
||||
version "2.8.17"
|
||||
resolved "https://registry.yarnpkg.com/turbo/-/turbo-2.8.17.tgz#45abeefe9d2ee06bc69c906e8384514b49822dbc"
|
||||
integrity sha512-YwPsNSqU2f/RXU/+Kcb7cPkPZARxom4+me7LKEdN5jsvy2tpfze3zDZ4EiGrJnvOm9Avu9rK0aaYsP7qZ3iz7A==
|
||||
turbo@^2.8.14:
|
||||
version "2.8.14"
|
||||
resolved "https://registry.yarnpkg.com/turbo/-/turbo-2.8.14.tgz#182e8427536d981c106a7f9ac0150727e3d08d87"
|
||||
integrity sha512-UCTxeMNYT1cKaHiIFdLCQ7ulI+jw5i5uOnJOrRXsgUD7G3+OjlUjwVd7JfeVt2McWSVGjYA3EVW/v1FSsJ5DtA==
|
||||
optionalDependencies:
|
||||
turbo-darwin-64 "2.8.17"
|
||||
turbo-darwin-arm64 "2.8.17"
|
||||
turbo-linux-64 "2.8.17"
|
||||
turbo-linux-arm64 "2.8.17"
|
||||
turbo-windows-64 "2.8.17"
|
||||
turbo-windows-arm64 "2.8.17"
|
||||
turbo-darwin-64 "2.8.14"
|
||||
turbo-darwin-arm64 "2.8.14"
|
||||
turbo-linux-64 "2.8.14"
|
||||
turbo-linux-arm64 "2.8.14"
|
||||
turbo-windows-64 "2.8.14"
|
||||
turbo-windows-arm64 "2.8.14"
|
||||
|
||||
type-check@^0.4.0, type-check@~0.4.0:
|
||||
version "0.4.0"
|
||||
|
||||
@@ -1 +1 @@
|
||||
__version__ = "0.4.19"
|
||||
__version__ = "0.4.15"
|
||||
|
||||
+125
-573
@@ -13,7 +13,6 @@ import tempfile
|
||||
import time
|
||||
from collections.abc import Callable, Sequence
|
||||
from contextlib import contextmanager
|
||||
from datetime import datetime, timezone
|
||||
|
||||
import click
|
||||
import click.exceptions
|
||||
@@ -27,15 +26,10 @@ from langgraph_cli.config import Config
|
||||
from langgraph_cli.constants import DEFAULT_CONFIG, DEFAULT_PORT
|
||||
from langgraph_cli.docker import DockerCapabilities
|
||||
from langgraph_cli.exec import Runner, subp_exec
|
||||
from langgraph_cli.helpers import format_log_entry, level_fg, resolve_deployment_id
|
||||
from langgraph_cli.host_backend import HostBackendClient, HostBackendError
|
||||
from langgraph_cli.progress import Progress
|
||||
from langgraph_cli.templates import TEMPLATE_HELP_STRING, create_new
|
||||
from langgraph_cli.util import (
|
||||
format_deployments_table,
|
||||
format_revisions_table,
|
||||
warn_non_wolfi_distro,
|
||||
)
|
||||
from langgraph_cli.util import warn_non_wolfi_distro
|
||||
from langgraph_cli.version import __version__
|
||||
|
||||
RESERVED_ENV_VARS = frozenset(
|
||||
@@ -293,33 +287,6 @@ OPT_API_VERSION = click.option(
|
||||
help="API server version to use for the base image. If unspecified, the latest version will be used.",
|
||||
)
|
||||
|
||||
OPT_HOST_API_KEY = click.option(
|
||||
"--api-key",
|
||||
envvar="LANGGRAPH_HOST_API_KEY",
|
||||
help=(
|
||||
"API key. Can also be set via LANGGRAPH_HOST_API_KEY, "
|
||||
"LANGSMITH_API_KEY, or LANGCHAIN_API_KEY environment variable or .env file."
|
||||
),
|
||||
)
|
||||
|
||||
|
||||
OPT_HOST_DEPLOYMENT_NAME = click.option(
|
||||
"--name",
|
||||
envvar=_DEPLOYMENT_NAME_ENV,
|
||||
help=(
|
||||
"Deployment name. Can also be set via LANGSMITH_DEPLOYMENT_NAME "
|
||||
"environment variable or .env file. Defaults to current directory name "
|
||||
"if --deployment-id is not provided."
|
||||
),
|
||||
)
|
||||
|
||||
OPT_HOST_URL = click.option(
|
||||
"--host-url",
|
||||
envvar="LANGGRAPH_HOST_URL",
|
||||
default="https://api.host.langchain.com",
|
||||
hidden=True,
|
||||
)
|
||||
|
||||
OPT_ENGINE_RUNTIME_MODE = click.option(
|
||||
"--engine-runtime-mode",
|
||||
type=click.Choice(["combined_queue_worker", "distributed"]),
|
||||
@@ -328,84 +295,7 @@ OPT_ENGINE_RUNTIME_MODE = click.option(
|
||||
)
|
||||
|
||||
|
||||
class NestedHelpGroup(click.Group):
|
||||
"""Click group that shows one level of nested subcommands in top-level help."""
|
||||
|
||||
def format_commands(
|
||||
self, ctx: click.Context, formatter: click.HelpFormatter
|
||||
) -> None:
|
||||
command_entries: list[tuple[str, click.Command]] = []
|
||||
|
||||
def collect_commands(
|
||||
group: click.Group, parent_ctx: click.Context, prefix: str = ""
|
||||
) -> None:
|
||||
for command_name in group.list_commands(parent_ctx):
|
||||
command = group.get_command(parent_ctx, command_name)
|
||||
if command is None or command.hidden:
|
||||
continue
|
||||
qualified_name = f"{prefix} {command_name}" if prefix else command_name
|
||||
command_entries.append((qualified_name, command))
|
||||
if isinstance(command, click.Group):
|
||||
sub_ctx = click.Context(
|
||||
command,
|
||||
info_name=qualified_name,
|
||||
parent=parent_ctx,
|
||||
)
|
||||
collect_commands(command, sub_ctx, qualified_name)
|
||||
|
||||
collect_commands(self, ctx)
|
||||
|
||||
# Compute the available width for help text up front so we can truncate
|
||||
# descriptions before handing them to Click. That keeps each command on
|
||||
# a single line instead of allowing wrapped descriptions.
|
||||
command_width = max((len(name) for name, _ in command_entries), default=0)
|
||||
help_width = max(formatter.width - command_width - 6, 10)
|
||||
rows = [
|
||||
(name, command.get_short_help_str(help_width))
|
||||
for name, command in command_entries
|
||||
]
|
||||
|
||||
if rows:
|
||||
# Render the flattened command list using Click's standard
|
||||
# definition-list formatter so alignment stays consistent with the
|
||||
# rest of the CLI help output.
|
||||
with formatter.section("Commands"):
|
||||
formatter.write_dl(rows)
|
||||
|
||||
|
||||
class DeployGroup(NestedHelpGroup):
|
||||
"""Group that treats leading '-' args as passthrough docker flags."""
|
||||
|
||||
def parse_args(self, ctx: click.Context, args: list[str]) -> list[str]:
|
||||
"""Treat leading option-like subcommand tokens as passthrough args.
|
||||
|
||||
Click stores the unresolved nested command token on the context after
|
||||
``Group.parse_args()`` runs, but the backing attribute changed across
|
||||
supported Click versions. Click 8.1.x stores the value directly on
|
||||
``protected_args``, while Click 8.2+ stores it on ``_protected_args``
|
||||
and exposes ``protected_args`` as a deprecated compatibility property.
|
||||
Since this package allows ``click>=8.1.7``, we need to check both
|
||||
names to support the full version range without relying on one
|
||||
version-specific internal detail.
|
||||
"""
|
||||
result = super().parse_args(ctx, args)
|
||||
protected_args = ctx.__dict__.get("protected_args")
|
||||
if protected_args is None:
|
||||
protected_args = ctx.__dict__.get("_protected_args", [])
|
||||
if protected_args and protected_args[0].startswith("-"):
|
||||
# Click stores the would-be subcommand in _protected_args; if it looks
|
||||
# like an option (e.g. --build-arg) treat it as passthrough docker
|
||||
# args instead of insisting on a nested command.
|
||||
ctx.args = [*protected_args, *ctx.args]
|
||||
if "protected_args" in ctx.__dict__:
|
||||
ctx.protected_args = []
|
||||
elif "_protected_args" in ctx.__dict__:
|
||||
ctx._protected_args = []
|
||||
return ctx.args
|
||||
return result
|
||||
|
||||
|
||||
@click.group(cls=NestedHelpGroup)
|
||||
@click.group()
|
||||
@click.version_option(version=__version__, prog_name="LangGraph CLI")
|
||||
def cli():
|
||||
pass
|
||||
@@ -703,122 +593,84 @@ def build(
|
||||
)
|
||||
|
||||
|
||||
def _deploy_base_options(
|
||||
func: Callable | None = None,
|
||||
*,
|
||||
include_docker_args: bool = True,
|
||||
validate_config_path: bool = True,
|
||||
):
|
||||
"""Apply shared deploy flags.
|
||||
|
||||
The group shares most options but should not consume subcommands, so the
|
||||
docker build args are only attached when requested.
|
||||
"""
|
||||
|
||||
def _apply(target: Callable) -> Callable:
|
||||
decorators = [
|
||||
OPT_HOST_API_KEY,
|
||||
OPT_HOST_DEPLOYMENT_NAME,
|
||||
click.option(
|
||||
"--deployment-id",
|
||||
help=(
|
||||
"ID of an existing deployment to update. If omitted, "
|
||||
"--name is used to find or create the deployment."
|
||||
),
|
||||
),
|
||||
click.option(
|
||||
"--deployment-type",
|
||||
type=click.Choice(["dev", "prod"]),
|
||||
default="dev",
|
||||
show_default=True,
|
||||
help="Deployment type (used when creating a new deployment).",
|
||||
),
|
||||
click.option(
|
||||
"--no-wait",
|
||||
is_flag=True,
|
||||
default=False,
|
||||
help="Skip waiting for deployment status.",
|
||||
),
|
||||
OPT_VERBOSE,
|
||||
OPT_HOST_URL,
|
||||
click.option("--image-name", hidden=True),
|
||||
click.option(
|
||||
"--tag",
|
||||
"-t",
|
||||
default="latest",
|
||||
show_default=True,
|
||||
help="Tag to use for the pushed deployment image.",
|
||||
),
|
||||
click.option(
|
||||
"--config",
|
||||
"-c",
|
||||
default=DEFAULT_CONFIG,
|
||||
hidden=True,
|
||||
type=click.Path(
|
||||
exists=validate_config_path,
|
||||
file_okay=True,
|
||||
dir_okay=False,
|
||||
resolve_path=True,
|
||||
path_type=pathlib.Path,
|
||||
),
|
||||
),
|
||||
click.option("--pull/--no-pull", default=True, hidden=True),
|
||||
click.option("--base-image", hidden=True),
|
||||
click.option("--install-command", hidden=True),
|
||||
click.option("--build-command", hidden=True),
|
||||
click.option("--api-version", type=str, hidden=True),
|
||||
]
|
||||
if include_docker_args:
|
||||
# Only attach build args to the default command; on the group they
|
||||
# would capture subcommand names like `list` before Click resolves
|
||||
# them, making those subcommands unreachable.
|
||||
decorators.append(
|
||||
click.argument("docker_build_args", nargs=-1, type=click.UNPROCESSED)
|
||||
)
|
||||
for decorator in reversed(decorators):
|
||||
target = decorator(target)
|
||||
return target
|
||||
|
||||
return _apply(func) if func is not None else _apply
|
||||
|
||||
|
||||
@cli.group(
|
||||
cls=DeployGroup,
|
||||
@click.option(
|
||||
"--api-key",
|
||||
envvar="LANGGRAPH_HOST_API_KEY",
|
||||
help=(
|
||||
"[Beta] Build and deploy a LangGraph image to LangSmith Deployment.\n\n"
|
||||
"API key. Can also be set via LANGGRAPH_HOST_API_KEY, "
|
||||
"LANGSMITH_API_KEY, or LANGCHAIN_API_KEY environment variable or .env file."
|
||||
),
|
||||
)
|
||||
@click.option(
|
||||
"--name",
|
||||
envvar="LANGSMITH_DEPLOYMENT_NAME",
|
||||
help=(
|
||||
"Deployment name. Can also be set via LANGSMITH_DEPLOYMENT_NAME "
|
||||
"environment variable or .env file. Defaults to current directory name "
|
||||
"if --deployment-id is not provided."
|
||||
),
|
||||
)
|
||||
@click.option(
|
||||
"--deployment-id",
|
||||
help=(
|
||||
"ID of an existing deployment to update. If omitted, "
|
||||
"--name is used to find or create the deployment."
|
||||
),
|
||||
)
|
||||
@click.option(
|
||||
"--deployment-type",
|
||||
type=click.Choice(["dev", "prod"]),
|
||||
default="dev",
|
||||
show_default=True,
|
||||
help="Deployment type (used when creating a new deployment).",
|
||||
)
|
||||
@click.option(
|
||||
"--no-wait",
|
||||
is_flag=True,
|
||||
default=False,
|
||||
help="Skip waiting for deployment status.",
|
||||
)
|
||||
@OPT_VERBOSE
|
||||
@click.option(
|
||||
"--host-url",
|
||||
envvar="LANGGRAPH_HOST_URL",
|
||||
default="https://api.host.langchain.com",
|
||||
hidden=True,
|
||||
)
|
||||
@click.option("--image-name", hidden=True)
|
||||
@click.option("--image-tag", default="latest", hidden=True)
|
||||
@click.option(
|
||||
"--config",
|
||||
"-c",
|
||||
default=DEFAULT_CONFIG,
|
||||
hidden=True,
|
||||
type=click.Path(
|
||||
exists=True,
|
||||
file_okay=True,
|
||||
dir_okay=False,
|
||||
resolve_path=True,
|
||||
path_type=pathlib.Path,
|
||||
),
|
||||
)
|
||||
@click.option("--pull/--no-pull", default=True, hidden=True)
|
||||
@click.option("--base-image", hidden=True)
|
||||
@click.option("--install-command", hidden=True)
|
||||
@click.option("--build-command", hidden=True)
|
||||
@click.option("--api-version", type=str, hidden=True)
|
||||
@click.argument("docker_build_args", nargs=-1, type=click.UNPROCESSED)
|
||||
@cli.command(
|
||||
help=(
|
||||
"[Beta] Build and deploy a LangGraph image to LangSmith Deployments.\n\n"
|
||||
"This command is in beta and under active development. "
|
||||
"Expect frequent updates and improvements.\n\n"
|
||||
"Run from the root of your LangGraph project (where langgraph.json "
|
||||
"is located). This command also accepts build flags (--base-image, "
|
||||
"--config, --pull, etc.). See 'langgraph build --help' for details."
|
||||
"--pull, etc.). See 'langgraph build --help' for details."
|
||||
),
|
||||
context_settings=dict(ignore_unknown_options=True, allow_extra_args=True),
|
||||
invoke_without_command=True, # allow `deploy` click group to execute without command
|
||||
context_settings=dict(ignore_unknown_options=True),
|
||||
)
|
||||
@_deploy_base_options(include_docker_args=False, validate_config_path=False)
|
||||
@click.pass_context
|
||||
@log_command
|
||||
def deploy(ctx: click.Context, **_: object):
|
||||
# We register deploy as both a group and a command here.
|
||||
# if we detect no subcommand, we run _deploy (basically run langgraph deploy as a top level command)
|
||||
# otherwise, we return None here and click will proceed to actually run the subcommand (list or delete)
|
||||
if ctx.invoked_subcommand is not None:
|
||||
return
|
||||
docker_build_args = tuple(ctx.args)
|
||||
ctx.args = [] # Prevent Click from re-processing passthrough args later.
|
||||
return ctx.forward(_deploy, docker_build_args=docker_build_args)
|
||||
|
||||
|
||||
@deploy.group(
|
||||
"revisions", cls=NestedHelpGroup, help="[Beta] Manage deployment revisions."
|
||||
)
|
||||
def deploy_revisions() -> None:
|
||||
pass
|
||||
|
||||
|
||||
@_deploy_base_options()
|
||||
@click.command(context_settings=dict(ignore_unknown_options=True))
|
||||
def _deploy(
|
||||
def deploy(
|
||||
config: pathlib.Path,
|
||||
pull: bool,
|
||||
verbose: bool,
|
||||
@@ -829,7 +681,7 @@ def _deploy(
|
||||
deployment_type: str,
|
||||
name: str | None,
|
||||
image_name: str | None,
|
||||
tag: str,
|
||||
image_tag: str,
|
||||
base_image: str | None,
|
||||
install_command: str | None,
|
||||
build_command: str | None,
|
||||
@@ -846,6 +698,15 @@ def _deploy(
|
||||
|
||||
env_vars = _parse_env_from_config(config_json, config)
|
||||
|
||||
if not api_key:
|
||||
for key_name in _API_KEY_ENV_NAMES:
|
||||
val = env_vars.get(key_name) or os.environ.get(key_name)
|
||||
if val:
|
||||
api_key = val
|
||||
break
|
||||
if not api_key:
|
||||
api_key = click.prompt("Host API key", hide_input=True)
|
||||
|
||||
if not deployment_id and not name:
|
||||
name = env_vars.get(_DEPLOYMENT_NAME_ENV)
|
||||
if not deployment_id and not name:
|
||||
@@ -882,21 +743,55 @@ def _deploy(
|
||||
def log_step(message: str) -> None:
|
||||
click.secho(message, fg="cyan")
|
||||
|
||||
client = _create_host_backend_client(host_url, api_key, env_vars=env_vars)
|
||||
client = HostBackendClient(host_url, api_key)
|
||||
step = 1
|
||||
needs_creation = False
|
||||
|
||||
if deployment_id:
|
||||
log_step(f"{step}. Using deployment {deployment_id}")
|
||||
_call_host_backend_with_optional_tenant(
|
||||
client, lambda c: c.get_deployment(deployment_id)
|
||||
)
|
||||
try:
|
||||
client.get_deployment(deployment_id)
|
||||
except HostBackendError as err:
|
||||
if (
|
||||
err.status_code == 403
|
||||
and "requires workspace specification" in err.message
|
||||
):
|
||||
click.secho(
|
||||
"Your API key is org-scoped and requires a workspace ID.",
|
||||
fg="yellow",
|
||||
)
|
||||
click.secho(
|
||||
"Find your workspace ID in LangSmith under Settings > Workspaces.",
|
||||
fg="yellow",
|
||||
)
|
||||
tenant_id = click.prompt("Workspace ID")
|
||||
client = HostBackendClient(host_url, api_key, tenant_id=tenant_id)
|
||||
client.get_deployment(deployment_id)
|
||||
else:
|
||||
raise
|
||||
step += 1
|
||||
else:
|
||||
log_step(f"{step}. Looking up deployment '{name}'")
|
||||
existing = _call_host_backend_with_optional_tenant(
|
||||
client, lambda c: c.list_deployments(name_contains=name)
|
||||
)
|
||||
try:
|
||||
existing = client.list_deployments(name_contains=name)
|
||||
except HostBackendError as err:
|
||||
if (
|
||||
err.status_code == 403
|
||||
and "requires workspace specification" in err.message
|
||||
):
|
||||
click.secho(
|
||||
"Your API key is org-scoped and requires a workspace ID.",
|
||||
fg="yellow",
|
||||
)
|
||||
click.secho(
|
||||
"Find your workspace ID in LangSmith under Settings > Workspaces.",
|
||||
fg="yellow",
|
||||
)
|
||||
tenant_id = click.prompt("Workspace ID")
|
||||
client = HostBackendClient(host_url, api_key, tenant_id=tenant_id)
|
||||
existing = client.list_deployments(name_contains=name)
|
||||
else:
|
||||
raise
|
||||
found_id = None
|
||||
if isinstance(existing, dict):
|
||||
for dep in existing.get("resources", []):
|
||||
@@ -1010,7 +905,7 @@ def _deploy(
|
||||
normalized_registry = normalized_registry.split("//", 1)[1]
|
||||
repo_seed = image_name or name or config.parent.name
|
||||
repo_name = _normalize_image_name(repo_seed)
|
||||
tag_value = _normalize_image_tag(tag)
|
||||
tag_value = _normalize_image_tag(image_tag)
|
||||
remote_image = f"{normalized_registry}/{repo_name}:{tag_value}"
|
||||
|
||||
registry_host = normalized_registry.split("/")[0]
|
||||
@@ -1150,180 +1045,11 @@ def _deploy(
|
||||
)
|
||||
else:
|
||||
click.secho(
|
||||
" Check status in the LangSmith Deployment dashboard.",
|
||||
" Check status in the LangSmith Deployments dashboard.",
|
||||
fg="yellow",
|
||||
)
|
||||
|
||||
|
||||
def _create_host_backend_client(
|
||||
host_url: str | None,
|
||||
api_key: str | None,
|
||||
env_vars: dict[str, str] | None = None,
|
||||
) -> HostBackendClient:
|
||||
if env_vars is None:
|
||||
env_vars = _parse_env_from_config({}, pathlib.Path.cwd() / DEFAULT_CONFIG)
|
||||
resolved_api_key = api_key
|
||||
if not resolved_api_key:
|
||||
for key_name in _API_KEY_ENV_NAMES:
|
||||
val = env_vars.get(key_name)
|
||||
if val:
|
||||
resolved_api_key = val
|
||||
break
|
||||
val = os.environ.get(key_name)
|
||||
if val:
|
||||
resolved_api_key = val
|
||||
break
|
||||
if not resolved_api_key:
|
||||
click.secho(
|
||||
"No LangSmith API key found. Create one at Settings > API Keys in LangSmith.",
|
||||
fg="yellow",
|
||||
)
|
||||
resolved_api_key = click.prompt("Enter LangSmith API key", hide_input=True)
|
||||
return HostBackendClient(host_url, resolved_api_key)
|
||||
|
||||
|
||||
def _call_host_backend_with_optional_tenant(
|
||||
client: HostBackendClient,
|
||||
operation: Callable[[HostBackendClient], object],
|
||||
) -> object:
|
||||
"""Run *operation*, prompting for a workspace ID on org-scoped 403s.
|
||||
|
||||
On success the original *client* is returned as-is. If the user is
|
||||
prompted for a workspace ID, the tenant header is set on *client*
|
||||
in-place so all subsequent calls through the same instance are
|
||||
tenant-aware.
|
||||
"""
|
||||
prompted_for_tenant = False
|
||||
|
||||
while True:
|
||||
try:
|
||||
return operation(client)
|
||||
except HostBackendError as err:
|
||||
if (
|
||||
not prompted_for_tenant
|
||||
and err.status_code == 403
|
||||
and "requires workspace specification" in err.message
|
||||
):
|
||||
click.secho(
|
||||
"Your API key is org-scoped and requires a workspace ID.",
|
||||
fg="yellow",
|
||||
)
|
||||
click.secho(
|
||||
"Find your workspace ID in LangSmith under Settings > Workspaces.",
|
||||
fg="yellow",
|
||||
)
|
||||
client._client.headers["X-Tenant-ID"] = click.prompt("Workspace ID")
|
||||
prompted_for_tenant = True
|
||||
continue
|
||||
if err.status_code == 403 and "not enabled" in err.message.lower():
|
||||
from urllib.parse import urlparse
|
||||
|
||||
smith_host = "smith.langchain.com"
|
||||
parsed = urlparse(client._base_url)
|
||||
if (parsed.hostname or "").startswith("eu."):
|
||||
smith_host = "eu.smith.langchain.com"
|
||||
raise HostBackendError(
|
||||
"LangSmith Deployment is not enabled for this organization. "
|
||||
f"Enable it at https://{smith_host}/host/deployments"
|
||||
" (ensure this matches the organization for your API key).",
|
||||
status_code=403,
|
||||
) from None
|
||||
raise
|
||||
|
||||
|
||||
@OPT_HOST_API_KEY
|
||||
@OPT_HOST_URL
|
||||
@click.option(
|
||||
"--name-contains",
|
||||
default="",
|
||||
help="Only show deployments whose names contain this value.",
|
||||
)
|
||||
@deploy.command("list", help="[Beta] List LangSmith Deployments.")
|
||||
def deploy_list(api_key: str | None, host_url: str | None, name_contains: str) -> None:
|
||||
client = _create_host_backend_client(host_url, api_key)
|
||||
response = _call_host_backend_with_optional_tenant(
|
||||
client,
|
||||
lambda c: c.list_deployments(name_contains=name_contains),
|
||||
)
|
||||
resources = response.get("resources", []) if isinstance(response, dict) else []
|
||||
deployments = [item for item in resources if isinstance(item, dict)]
|
||||
if not deployments:
|
||||
click.echo("No deployments found.")
|
||||
return
|
||||
click.echo(format_deployments_table(deployments))
|
||||
|
||||
|
||||
@OPT_HOST_API_KEY
|
||||
@OPT_HOST_URL
|
||||
@click.option(
|
||||
"--limit",
|
||||
type=int,
|
||||
default=10,
|
||||
show_default=True,
|
||||
help="Maximum number of revisions to return.",
|
||||
)
|
||||
@click.argument("deployment_id")
|
||||
@deploy_revisions.command(
|
||||
"list",
|
||||
help=(
|
||||
"[Beta] List revisions for a LangSmith Deployment.\n\n"
|
||||
"Use the `deploy list` command to list deployment IDs."
|
||||
),
|
||||
)
|
||||
def deploy_revisions_list(
|
||||
api_key: str | None, host_url: str | None, limit: int, deployment_id: str
|
||||
) -> None:
|
||||
client = _create_host_backend_client(host_url, api_key)
|
||||
response = _call_host_backend_with_optional_tenant(
|
||||
client,
|
||||
lambda c: c.list_revisions(deployment_id, limit=limit),
|
||||
)
|
||||
resources = response.get("resources", []) if isinstance(response, dict) else []
|
||||
revisions = [item for item in resources if isinstance(item, dict)]
|
||||
if not revisions:
|
||||
click.echo(f"No revisions found for deployment {deployment_id}.")
|
||||
return
|
||||
click.echo(format_revisions_table(revisions))
|
||||
|
||||
|
||||
@OPT_HOST_API_KEY
|
||||
@OPT_HOST_URL
|
||||
@click.option(
|
||||
"--force",
|
||||
is_flag=True,
|
||||
default=False,
|
||||
help="Delete without prompting for confirmation.",
|
||||
)
|
||||
@click.argument("deployment_id")
|
||||
@deploy.command(
|
||||
"delete",
|
||||
help=(
|
||||
"[Beta] Delete a LangSmith Deployment.\n\n"
|
||||
"Use the `deploy list` command to list deployment IDs."
|
||||
),
|
||||
)
|
||||
def deploy_delete(
|
||||
api_key: str | None, host_url: str | None, force: bool, deployment_id: str
|
||||
) -> None:
|
||||
if not force:
|
||||
response = click.prompt(
|
||||
click.style(
|
||||
f"Are you sure you want to delete deployment ID {deployment_id}? (Y/n)",
|
||||
fg="yellow",
|
||||
),
|
||||
default="Y",
|
||||
show_default=False,
|
||||
)
|
||||
if response.strip().lower() not in {"y", "yes"}:
|
||||
raise click.Abort()
|
||||
client = _create_host_backend_client(host_url, api_key)
|
||||
_call_host_backend_with_optional_tenant(
|
||||
client,
|
||||
lambda c: c.delete_deployment(deployment_id),
|
||||
)
|
||||
click.secho(f"Deleted deployment {deployment_id}.", fg="green")
|
||||
|
||||
|
||||
def _normalize_image_name(value: str | None) -> str:
|
||||
"""Sanitize a deployment/directory name into a valid Docker repository name.
|
||||
|
||||
@@ -1350,180 +1076,6 @@ def _normalize_image_tag(value: str) -> str:
|
||||
return value
|
||||
|
||||
|
||||
@OPT_HOST_API_KEY
|
||||
@OPT_HOST_DEPLOYMENT_NAME
|
||||
@click.option(
|
||||
"--deployment-id",
|
||||
help="Deployment ID. If omitted, --name is used to find the deployment.",
|
||||
)
|
||||
@click.option(
|
||||
"--type",
|
||||
"log_type",
|
||||
type=click.Choice(["deploy", "build"]),
|
||||
default="deploy",
|
||||
show_default=True,
|
||||
help=(
|
||||
"Log stream to fetch: 'deploy' shows agent server runtime logs; "
|
||||
"'build' shows build logs (for deployments built remotely)."
|
||||
),
|
||||
)
|
||||
@click.option(
|
||||
"--revision-id",
|
||||
help="Specific revision ID. For build logs, defaults to latest revision.",
|
||||
)
|
||||
@click.option(
|
||||
"--level",
|
||||
type=click.Choice(
|
||||
["DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"], case_sensitive=False
|
||||
),
|
||||
help="Filter by log level.",
|
||||
)
|
||||
@click.option(
|
||||
"--limit",
|
||||
type=int,
|
||||
default=100,
|
||||
show_default=True,
|
||||
help="Max log entries to fetch.",
|
||||
)
|
||||
@click.option(
|
||||
"--query",
|
||||
"-q",
|
||||
help="Search string filter.",
|
||||
)
|
||||
@click.option(
|
||||
"--start-time",
|
||||
help="ISO8601 start time (e.g. 2026-03-08T00:00:00Z).",
|
||||
)
|
||||
@click.option(
|
||||
"--end-time",
|
||||
help="ISO8601 end time. (e.g. 2026-03-08T00:00:00Z)",
|
||||
)
|
||||
@click.option(
|
||||
"--follow",
|
||||
"-f",
|
||||
is_flag=True,
|
||||
default=False,
|
||||
help="Continuously poll for new logs.",
|
||||
)
|
||||
@OPT_HOST_URL
|
||||
@deploy.command(
|
||||
"logs",
|
||||
help=(
|
||||
"[Beta] Fetch LangSmith Deployment logs. Use 'deploy' for agent runtime "
|
||||
"logs, or 'build' for remote build logs."
|
||||
),
|
||||
)
|
||||
@log_command
|
||||
def deploy_logs(
|
||||
api_key: str | None,
|
||||
name: str | None,
|
||||
deployment_id: str | None,
|
||||
log_type: str,
|
||||
revision_id: str | None,
|
||||
level: str | None,
|
||||
limit: int,
|
||||
query: str | None,
|
||||
start_time: str | None,
|
||||
end_time: str | None,
|
||||
follow: bool,
|
||||
host_url: str,
|
||||
):
|
||||
env_vars = _parse_env_from_config({}, pathlib.Path.cwd() / DEFAULT_CONFIG)
|
||||
client = _create_host_backend_client(host_url, api_key, env_vars=env_vars)
|
||||
if not deployment_id and not name:
|
||||
name = env_vars.get(_DEPLOYMENT_NAME_ENV)
|
||||
dep_id = _call_host_backend_with_optional_tenant(
|
||||
client, lambda c: resolve_deployment_id(c, deployment_id, name)
|
||||
)
|
||||
|
||||
if log_type == "build" and not revision_id:
|
||||
revisions_resp = client.list_revisions(dep_id, limit=1)
|
||||
resources = (
|
||||
revisions_resp.get("resources", [])
|
||||
if isinstance(revisions_resp, dict)
|
||||
else []
|
||||
)
|
||||
if not resources:
|
||||
raise click.ClickException(
|
||||
"No revisions found for this deployment. Cannot fetch build logs."
|
||||
)
|
||||
revision_id = str(resources[0]["id"])
|
||||
click.secho(f"Using latest revision: {revision_id}", fg="cyan")
|
||||
|
||||
payload: dict = {"limit": limit, "order": "desc"}
|
||||
if level:
|
||||
payload["level"] = level.upper()
|
||||
if query:
|
||||
payload["query"] = query
|
||||
if start_time:
|
||||
payload["start_time"] = start_time
|
||||
if end_time:
|
||||
payload["end_time"] = end_time
|
||||
|
||||
def _fetch(request_payload: dict) -> list[dict]:
|
||||
if log_type == "build":
|
||||
resp = client.get_build_logs(dep_id, revision_id, request_payload)
|
||||
else:
|
||||
resp = client.get_deploy_logs(dep_id, request_payload, revision_id)
|
||||
|
||||
if isinstance(resp, dict):
|
||||
return resp.get("logs", [])
|
||||
return []
|
||||
|
||||
def _print_entries(entries: list[dict], *, reverse: bool = False) -> None:
|
||||
iterable = reversed(entries) if reverse else entries
|
||||
for entry in iterable:
|
||||
line = format_log_entry(entry)
|
||||
fg = level_fg(entry.get("level", ""))
|
||||
click.secho(line, fg=fg)
|
||||
|
||||
def _fetch_and_print(request_payload: dict, *, reverse: bool = False) -> list[dict]:
|
||||
entries = _fetch(request_payload)
|
||||
_print_entries(entries, reverse=reverse)
|
||||
return entries
|
||||
|
||||
def _fetch_and_print_new(request_payload: dict, seen_ids: set[str]) -> list[dict]:
|
||||
entries = _fetch(request_payload)
|
||||
new = [e for e in entries if e.get("id", "") not in seen_ids]
|
||||
if new:
|
||||
_print_entries(new)
|
||||
seen_ids.update(e.get("id", "") for e in new)
|
||||
return new
|
||||
|
||||
# initial log fetch will be newest -> oldest, so we need to reverse
|
||||
entries = _fetch_and_print(payload, reverse=True)
|
||||
|
||||
if not follow:
|
||||
if not entries:
|
||||
click.secho("No log entries found.", fg="yellow")
|
||||
return
|
||||
|
||||
payload["order"] = "asc"
|
||||
seen_ids: set[str] = {e.get("id", "") for e in entries if e.get("id")}
|
||||
|
||||
def _update_start_time(ts) -> None:
|
||||
if ts is None:
|
||||
return
|
||||
if isinstance(ts, (int, float)):
|
||||
dt = datetime.fromtimestamp(ts / 1000, tz=timezone.utc)
|
||||
payload["start_time"] = dt.isoformat()
|
||||
else:
|
||||
payload["start_time"] = str(ts)
|
||||
|
||||
if entries:
|
||||
# entries are in descending order here, so index 0 is the newest log
|
||||
_update_start_time(entries[0].get("timestamp"))
|
||||
|
||||
try:
|
||||
while True:
|
||||
time.sleep(2)
|
||||
new_entries = _fetch_and_print_new(payload, seen_ids)
|
||||
if new_entries:
|
||||
_update_start_time(new_entries[-1].get("timestamp"))
|
||||
except KeyboardInterrupt:
|
||||
click.echo("\nStopped.")
|
||||
|
||||
|
||||
def _get_docker_ignore_content() -> str:
|
||||
"""Return the content of a .dockerignore file.
|
||||
|
||||
|
||||
@@ -1,59 +0,0 @@
|
||||
"""Helpers for the ``langgraph logs`` CLI command."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from datetime import datetime, timezone
|
||||
|
||||
import click
|
||||
|
||||
from langgraph_cli.host_backend import HostBackendClient
|
||||
|
||||
|
||||
def resolve_deployment_id(
|
||||
client: HostBackendClient,
|
||||
deployment_id: str | None,
|
||||
name: str | None,
|
||||
) -> str:
|
||||
"""Resolve a deployment ID from --deployment-id or --name."""
|
||||
if deployment_id:
|
||||
return deployment_id
|
||||
if not name:
|
||||
raise click.UsageError("Either --deployment-id or --name is required.")
|
||||
existing = client.list_deployments(name_contains=name)
|
||||
if isinstance(existing, dict):
|
||||
for dep in existing.get("resources", []):
|
||||
if isinstance(dep, dict) and dep.get("name") == name:
|
||||
found_id = dep.get("id")
|
||||
if found_id:
|
||||
return str(found_id)
|
||||
raise click.ClickException(f"Deployment '{name}' not found.")
|
||||
|
||||
|
||||
def format_timestamp(ts) -> str:
|
||||
"""Convert a timestamp (epoch ms or string) to a readable string."""
|
||||
if isinstance(ts, (int, float)):
|
||||
dt = datetime.fromtimestamp(ts / 1000, tz=timezone.utc)
|
||||
return dt.strftime("%Y-%m-%d %H:%M:%S")
|
||||
return str(ts) if ts else ""
|
||||
|
||||
|
||||
def format_log_entry(entry: dict) -> str:
|
||||
"""Format a single log entry for display."""
|
||||
ts = format_timestamp(entry.get("timestamp", ""))
|
||||
level = entry.get("level", "")
|
||||
message = entry.get("message", "")
|
||||
if ts and level:
|
||||
return f"[{ts}] [{level}] {message}"
|
||||
elif ts:
|
||||
return f"[{ts}] {message}"
|
||||
return message
|
||||
|
||||
|
||||
def level_fg(level: str) -> str | None:
|
||||
"""Return click color for a log level."""
|
||||
level_upper = level.upper() if level else ""
|
||||
if level_upper in {"ERROR", "CRITICAL"}:
|
||||
return "red"
|
||||
if level_upper == "WARNING":
|
||||
return "yellow"
|
||||
return None
|
||||
@@ -19,12 +19,7 @@ class HostBackendError(click.ClickException):
|
||||
class HostBackendClient:
|
||||
"""Minimal JSON HTTP client for the host backend deployment service."""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
base_url: str,
|
||||
api_key: str,
|
||||
tenant_id: str | None = None,
|
||||
):
|
||||
def __init__(self, base_url: str, api_key: str, tenant_id: str | None = None):
|
||||
if not base_url:
|
||||
raise click.UsageError("Host backend URL is required")
|
||||
transport = httpx.HTTPTransport(retries=3)
|
||||
@@ -35,6 +30,7 @@ class HostBackendClient:
|
||||
if tenant_id:
|
||||
headers["X-Tenant-ID"] = tenant_id
|
||||
self._base_url = base_url.rstrip("/")
|
||||
self._api_key = api_key
|
||||
self._client = httpx.Client(
|
||||
base_url=self._base_url,
|
||||
headers=headers,
|
||||
@@ -43,14 +39,10 @@ class HostBackendClient:
|
||||
)
|
||||
|
||||
def _request(
|
||||
self,
|
||||
method: str,
|
||||
path: str,
|
||||
payload: dict[str, Any] | None = None,
|
||||
params: dict[str, Any] | None = None,
|
||||
self, method: str, path: str, payload: dict[str, Any] | None = None
|
||||
) -> Any:
|
||||
try:
|
||||
resp = self._client.request(method, path, json=payload, params=params)
|
||||
resp = self._client.request(method, path, json=payload)
|
||||
resp.raise_for_status()
|
||||
except httpx.HTTPStatusError as err:
|
||||
detail = err.response.text or str(err.response.status_code)
|
||||
@@ -73,19 +65,12 @@ class HostBackendClient:
|
||||
def create_deployment(self, payload: dict[str, Any]) -> dict[str, Any]:
|
||||
return self._request("POST", "/v2/deployments", payload)
|
||||
|
||||
def list_deployments(self, name_contains: str = "") -> dict[str, Any]:
|
||||
return self._request(
|
||||
"GET",
|
||||
"/v2/deployments",
|
||||
params={"name_contains": name_contains},
|
||||
)
|
||||
def list_deployments(self, name_contains: str) -> dict[str, Any]:
|
||||
return self._request("GET", f"/v2/deployments?name_contains={name_contains}")
|
||||
|
||||
def get_deployment(self, deployment_id: str) -> dict[str, Any]:
|
||||
return self._request("GET", f"/v2/deployments/{deployment_id}")
|
||||
|
||||
def delete_deployment(self, deployment_id: str) -> None:
|
||||
return self._request("DELETE", f"/v2/deployments/{deployment_id}")
|
||||
|
||||
def request_push_token(self, deployment_id: str) -> dict[str, Any]:
|
||||
return self._request(
|
||||
"POST",
|
||||
@@ -120,24 +105,3 @@ class HostBackendClient:
|
||||
"GET",
|
||||
f"/v2/deployments/{deployment_id}/revisions/{revision_id}",
|
||||
)
|
||||
|
||||
def get_build_logs(
|
||||
self, project_id: str, revision_id: str, payload: dict[str, Any]
|
||||
) -> Any:
|
||||
return self._request(
|
||||
"POST",
|
||||
f"/v1/projects/{project_id}/revisions/{revision_id}/build_logs",
|
||||
payload,
|
||||
)
|
||||
|
||||
def get_deploy_logs(
|
||||
self,
|
||||
project_id: str,
|
||||
payload: dict[str, Any],
|
||||
revision_id: str | None = None,
|
||||
) -> Any:
|
||||
if revision_id:
|
||||
path = f"/v1/projects/{project_id}/revisions/{revision_id}/deploy_logs"
|
||||
else:
|
||||
path = f"/v1/projects/{project_id}/deploy_logs"
|
||||
return self._request("POST", path, payload)
|
||||
|
||||
@@ -8,20 +8,31 @@ from zipfile import ZipFile
|
||||
import click
|
||||
|
||||
TEMPLATES: dict[str, dict[str, str]] = {
|
||||
"Deep Agent": {
|
||||
"description": "An opinionated deployment template for a Deep Agent.",
|
||||
"python": "https://github.com/langchain-ai/deep-agent-template/archive/refs/heads/main.zip",
|
||||
"js": "https://github.com/langchain-ai/deep-agent-template-js/archive/refs/heads/main.zip",
|
||||
},
|
||||
"Agent": {
|
||||
"description": "A simple agent that can be flexibly extended to many tools.",
|
||||
"python": "https://github.com/langchain-ai/simple-agent-template/archive/refs/heads/main.zip",
|
||||
},
|
||||
"New LangGraph Project": {
|
||||
"description": "A simple, minimal chatbot with memory.",
|
||||
"python": "https://github.com/langchain-ai/new-langgraph-project/archive/refs/heads/main.zip",
|
||||
"js": "https://github.com/langchain-ai/new-langgraphjs-project/archive/refs/heads/main.zip",
|
||||
},
|
||||
"ReAct Agent": {
|
||||
"description": "A simple agent that can be flexibly extended to many tools.",
|
||||
"python": "https://github.com/langchain-ai/react-agent/archive/refs/heads/main.zip",
|
||||
"js": "https://github.com/langchain-ai/react-agent-js/archive/refs/heads/main.zip",
|
||||
},
|
||||
"Memory Agent": {
|
||||
"description": "A ReAct-style agent with an additional tool to store memories for use across conversational threads.",
|
||||
"python": "https://github.com/langchain-ai/memory-agent/archive/refs/heads/main.zip",
|
||||
"js": "https://github.com/langchain-ai/memory-agent-js/archive/refs/heads/main.zip",
|
||||
},
|
||||
"Retrieval Agent": {
|
||||
"description": "An agent that includes a retrieval-based question-answering system.",
|
||||
"python": "https://github.com/langchain-ai/retrieval-agent-template/archive/refs/heads/main.zip",
|
||||
"js": "https://github.com/langchain-ai/retrieval-agent-template-js/archive/refs/heads/main.zip",
|
||||
},
|
||||
"Data-enrichment Agent": {
|
||||
"description": "An agent that performs web searches and organizes its findings into a structured format.",
|
||||
"python": "https://github.com/langchain-ai/data-enrichment/archive/refs/heads/main.zip",
|
||||
"js": "https://github.com/langchain-ai/data-enrichment-js/archive/refs/heads/main.zip",
|
||||
},
|
||||
}
|
||||
|
||||
# Generate TEMPLATE_IDS programmatically
|
||||
@@ -67,25 +78,19 @@ def _choose_template() -> str:
|
||||
click.secho("❌ Invalid choice. Please try again.", fg="red")
|
||||
return _choose_template()
|
||||
|
||||
template_info = TEMPLATES[selected_template]
|
||||
available_langs = [lang for lang in ("python", "js") if lang in template_info]
|
||||
|
||||
# Prompt the user to choose between Python or JS/TS version
|
||||
click.secho(
|
||||
f"\nYou selected: {selected_template} - {template_info['description']}",
|
||||
f"\nYou selected: {selected_template} - {TEMPLATES[selected_template]['description']}",
|
||||
fg="green",
|
||||
)
|
||||
|
||||
if len(available_langs) == 1:
|
||||
return template_info[available_langs[0]]
|
||||
|
||||
version_choice: int = click.prompt(
|
||||
"Choose language (1 for Python 🐍, 2 for JS/TS 🌐)", type=int
|
||||
)
|
||||
|
||||
if version_choice == 1:
|
||||
return template_info["python"]
|
||||
return TEMPLATES[selected_template]["python"]
|
||||
elif version_choice == 2:
|
||||
return template_info["js"]
|
||||
return TEMPLATES[selected_template]["js"]
|
||||
else:
|
||||
click.secho("❌ Invalid choice. Please try again.", fg="red")
|
||||
return _choose_template()
|
||||
@@ -125,6 +130,37 @@ def _download_repo_with_requests(repo_url: str, path: str) -> None:
|
||||
sys.exit(1)
|
||||
|
||||
|
||||
def _get_template_url(template_name: str) -> str | None:
|
||||
"""
|
||||
Retrieves the template URL based on the provided template name.
|
||||
|
||||
Args:
|
||||
template_name: The name of the template.
|
||||
|
||||
Returns:
|
||||
Optional[str]: The URL of the template if found, else None.
|
||||
"""
|
||||
if template_name in TEMPLATES:
|
||||
click.secho(f"Template selected: {template_name}", fg="green")
|
||||
version_choice: int = click.prompt(
|
||||
"Choose version (1 for Python 🐍, 2 for JS/TS 🌐)", type=int
|
||||
)
|
||||
|
||||
if version_choice == 1:
|
||||
return TEMPLATES[template_name]["python"]
|
||||
elif version_choice == 2:
|
||||
return TEMPLATES[template_name]["js"]
|
||||
else:
|
||||
click.secho("❌ Invalid choice. Please try again.", fg="red")
|
||||
return None
|
||||
else:
|
||||
click.secho(
|
||||
f"Template '{template_name}' not found. Please select from the available options.",
|
||||
fg="red",
|
||||
)
|
||||
return None
|
||||
|
||||
|
||||
def create_new(path: str | None, template: str | None) -> None:
|
||||
"""Create a new LangGraph project at the specified PATH using the chosen TEMPLATE.
|
||||
|
||||
|
||||
@@ -1,5 +1,3 @@
|
||||
from collections.abc import Sequence
|
||||
|
||||
import click
|
||||
|
||||
|
||||
@@ -25,67 +23,3 @@ def warn_non_wolfi_distro(config_json: dict) -> None:
|
||||
fg="yellow",
|
||||
)
|
||||
click.secho("") # Empty line for better readability
|
||||
|
||||
|
||||
def _extract_deployment_url(deployment: dict[str, object]) -> str:
|
||||
source_config = deployment.get("source_config")
|
||||
if isinstance(source_config, dict):
|
||||
custom_url = source_config.get("custom_url")
|
||||
if isinstance(custom_url, str) and custom_url:
|
||||
return custom_url
|
||||
return "-"
|
||||
|
||||
|
||||
def format_deployments_table(deployments: Sequence[dict[str, object]]) -> str:
|
||||
headers = ("Deployment ID", "Deployment Name", "Deployment URL")
|
||||
rows = [
|
||||
(
|
||||
str(deployment.get("id", "-") or "-"),
|
||||
str(deployment.get("name", "-") or "-"),
|
||||
_extract_deployment_url(deployment),
|
||||
)
|
||||
for deployment in deployments
|
||||
]
|
||||
widths = [
|
||||
max(len(headers[index]), *(len(row[index]) for row in rows))
|
||||
for index in range(len(headers))
|
||||
]
|
||||
|
||||
def format_row(row: Sequence[str]) -> str:
|
||||
return " ".join(value.ljust(widths[index]) for index, value in enumerate(row))
|
||||
|
||||
lines = [format_row(headers), format_row(tuple("-" * width for width in widths))]
|
||||
lines.extend(format_row(row) for row in rows)
|
||||
return "\n".join(lines)
|
||||
|
||||
|
||||
def format_revisions_table(revisions: Sequence[dict[str, object]]) -> str:
|
||||
headers = ("Revision ID", "Status", "Created At")
|
||||
latest_deployed_seen = False
|
||||
rows = []
|
||||
for revision in revisions:
|
||||
status = str(revision.get("status", "-") or "-")
|
||||
if status == "DEPLOYED":
|
||||
if latest_deployed_seen:
|
||||
status = "REPLACED"
|
||||
else:
|
||||
latest_deployed_seen = True
|
||||
rows.append(
|
||||
(
|
||||
str(revision.get("id", "-") or "-"),
|
||||
status,
|
||||
str(revision.get("created_at", "-") or "-"),
|
||||
)
|
||||
)
|
||||
|
||||
widths = [
|
||||
max(len(headers[index]), *(len(row[index]) for row in rows))
|
||||
for index in range(len(headers))
|
||||
]
|
||||
|
||||
def format_row(row: Sequence[str]) -> str:
|
||||
return " ".join(value.ljust(widths[index]) for index, value in enumerate(row))
|
||||
|
||||
lines = [format_row(headers), format_row(tuple("-" * width for width in widths))]
|
||||
lines.extend(format_row(row) for row in rows)
|
||||
return "\n".join(lines)
|
||||
|
||||
@@ -9,7 +9,6 @@ from pathlib import Path
|
||||
|
||||
from click.testing import CliRunner
|
||||
|
||||
import langgraph_cli.cli as cli_module
|
||||
from langgraph_cli.cli import cli, prepare_args_and_stdin
|
||||
from langgraph_cli.config import Config, _get_pip_cleanup_lines, validate_config
|
||||
from langgraph_cli.docker import DEFAULT_POSTGRES_URI, DockerCapabilities, Version
|
||||
@@ -288,374 +287,6 @@ def test_version_option() -> None:
|
||||
)
|
||||
|
||||
|
||||
def test_top_level_help_shows_deploy_subcommands() -> None:
|
||||
runner = CliRunner()
|
||||
|
||||
result = runner.invoke(cli, ["--help"])
|
||||
|
||||
assert result.exit_code == 0, result.output
|
||||
assert "deploy" in result.output
|
||||
assert "deploy list" in result.output
|
||||
assert "deploy delete" in result.output
|
||||
assert "deploy revisions" in result.output
|
||||
assert "deploy revisions list" in result.output
|
||||
assert "[Beta] List LangSmith Deployments." in result.output
|
||||
|
||||
|
||||
def test_top_level_help_truncates_command_descriptions_to_single_line() -> None:
|
||||
runner = CliRunner()
|
||||
|
||||
result = runner.invoke(cli, ["--help"])
|
||||
|
||||
assert result.exit_code == 0, result.output
|
||||
lines = result.output.splitlines()
|
||||
deploy_line = next(line for line in lines if line.strip().startswith("deploy"))
|
||||
deploy_list_line = next(
|
||||
line for line in lines if line.strip().startswith("deploy list")
|
||||
)
|
||||
|
||||
assert not lines[lines.index(deploy_line) + 1].startswith(" ")
|
||||
assert "..." in deploy_line
|
||||
assert "[Beta] List LangSmith Deployments." in deploy_list_line
|
||||
|
||||
|
||||
def test_deploy_list_command(monkeypatch) -> None:
|
||||
runner = CliRunner()
|
||||
captured: dict[str, str] = {}
|
||||
|
||||
class FakeClient:
|
||||
def __init__(self, host_url: str, api_key: str, tenant_id: str | None = None):
|
||||
captured["host_url"] = host_url
|
||||
captured["api_key"] = api_key
|
||||
captured["tenant_id"] = tenant_id or ""
|
||||
|
||||
def list_deployments(self, name_contains: str = ""):
|
||||
captured["name_contains"] = name_contains
|
||||
return {
|
||||
"resources": [
|
||||
{
|
||||
"id": "dep-123",
|
||||
"name": "alpha",
|
||||
"source_config": {"custom_url": "https://alpha.example.com"},
|
||||
},
|
||||
{
|
||||
"id": "dep-456",
|
||||
"name": "beta",
|
||||
"source_config": {"custom_url": "https://beta.example.com"},
|
||||
},
|
||||
]
|
||||
}
|
||||
|
||||
monkeypatch.setattr(cli_module, "HostBackendClient", FakeClient)
|
||||
|
||||
result = runner.invoke(
|
||||
cli,
|
||||
[
|
||||
"deploy",
|
||||
"list",
|
||||
"--api-key",
|
||||
"test-key",
|
||||
"--host-url",
|
||||
"https://api.example.com",
|
||||
"--name-contains",
|
||||
"alp",
|
||||
],
|
||||
)
|
||||
|
||||
assert result.exit_code == 0, result.output
|
||||
assert captured == {
|
||||
"host_url": "https://api.example.com",
|
||||
"api_key": "test-key",
|
||||
"tenant_id": "",
|
||||
"name_contains": "alp",
|
||||
}
|
||||
assert "Deployment ID" in result.output
|
||||
assert "Deployment Name" in result.output
|
||||
assert "Deployment URL" in result.output
|
||||
assert "dep-123" in result.output
|
||||
assert "https://beta.example.com" in result.output
|
||||
|
||||
|
||||
def test_deploy_list_command_no_results(monkeypatch) -> None:
|
||||
runner = CliRunner()
|
||||
|
||||
class FakeClient:
|
||||
def __init__(self, host_url: str, api_key: str, tenant_id: str | None = None):
|
||||
pass
|
||||
|
||||
def list_deployments(self, name_contains: str = ""):
|
||||
return {"resources": []}
|
||||
|
||||
monkeypatch.setattr(cli_module, "HostBackendClient", FakeClient)
|
||||
|
||||
result = runner.invoke(
|
||||
cli,
|
||||
[
|
||||
"deploy",
|
||||
"list",
|
||||
"--api-key",
|
||||
"test-key",
|
||||
"--host-url",
|
||||
"https://api.example.com",
|
||||
],
|
||||
)
|
||||
|
||||
assert result.exit_code == 0, result.output
|
||||
assert result.output.strip() == "No deployments found."
|
||||
|
||||
|
||||
def test_deploy_revisions_list_command(monkeypatch) -> None:
|
||||
runner = CliRunner()
|
||||
captured: dict[str, str] = {}
|
||||
|
||||
class FakeClient:
|
||||
def __init__(self, host_url: str, api_key: str, tenant_id: str | None = None):
|
||||
captured["host_url"] = host_url
|
||||
captured["api_key"] = api_key
|
||||
captured["tenant_id"] = tenant_id or ""
|
||||
|
||||
def list_revisions(self, deployment_id: str, limit: int = 1):
|
||||
captured["deployment_id"] = deployment_id
|
||||
captured["limit"] = str(limit)
|
||||
return {
|
||||
"resources": [
|
||||
{
|
||||
"id": "rev-123",
|
||||
"status": "CREATING",
|
||||
"created_at": "2023-11-07T05:31:56Z",
|
||||
},
|
||||
{
|
||||
"id": "rev-456",
|
||||
"status": "DEPLOYED",
|
||||
"created_at": "2023-11-08T10:00:00Z",
|
||||
},
|
||||
]
|
||||
}
|
||||
|
||||
monkeypatch.setattr(cli_module, "HostBackendClient", FakeClient)
|
||||
|
||||
result = runner.invoke(
|
||||
cli,
|
||||
[
|
||||
"deploy",
|
||||
"revisions",
|
||||
"list",
|
||||
"--api-key",
|
||||
"test-key",
|
||||
"--host-url",
|
||||
"https://api.example.com",
|
||||
"dep-123",
|
||||
],
|
||||
)
|
||||
|
||||
assert result.exit_code == 0, result.output
|
||||
assert captured == {
|
||||
"host_url": "https://api.example.com",
|
||||
"api_key": "test-key",
|
||||
"tenant_id": "",
|
||||
"deployment_id": "dep-123",
|
||||
"limit": "10",
|
||||
}
|
||||
assert "Revision ID" in result.output
|
||||
assert "Status" in result.output
|
||||
assert "Created At" in result.output
|
||||
assert "rev-123" in result.output
|
||||
assert "2023-11-08T10:00:00Z" in result.output
|
||||
|
||||
|
||||
def test_deploy_revisions_list_command_no_results(monkeypatch) -> None:
|
||||
runner = CliRunner()
|
||||
|
||||
class FakeClient:
|
||||
def __init__(self, host_url: str, api_key: str, tenant_id: str | None = None):
|
||||
pass
|
||||
|
||||
def list_revisions(self, deployment_id: str, limit: int = 1):
|
||||
return {"resources": []}
|
||||
|
||||
monkeypatch.setattr(cli_module, "HostBackendClient", FakeClient)
|
||||
|
||||
result = runner.invoke(
|
||||
cli,
|
||||
[
|
||||
"deploy",
|
||||
"revisions",
|
||||
"list",
|
||||
"--api-key",
|
||||
"test-key",
|
||||
"--host-url",
|
||||
"https://api.example.com",
|
||||
"dep-123",
|
||||
],
|
||||
)
|
||||
|
||||
assert result.exit_code == 0, result.output
|
||||
assert result.output.strip() == "No revisions found for deployment dep-123."
|
||||
|
||||
|
||||
def test_deploy_revisions_list_command_with_explicit_limit(monkeypatch) -> None:
|
||||
runner = CliRunner()
|
||||
captured: dict[str, str] = {}
|
||||
|
||||
class FakeClient:
|
||||
def __init__(self, host_url: str, api_key: str, tenant_id: str | None = None):
|
||||
pass
|
||||
|
||||
def list_revisions(self, deployment_id: str, limit: int = 1):
|
||||
captured["deployment_id"] = deployment_id
|
||||
captured["limit"] = str(limit)
|
||||
return {"resources": []}
|
||||
|
||||
monkeypatch.setattr(cli_module, "HostBackendClient", FakeClient)
|
||||
|
||||
result = runner.invoke(
|
||||
cli,
|
||||
[
|
||||
"deploy",
|
||||
"revisions",
|
||||
"list",
|
||||
"--api-key",
|
||||
"test-key",
|
||||
"--host-url",
|
||||
"https://api.example.com",
|
||||
"--limit",
|
||||
"25",
|
||||
"dep-123",
|
||||
],
|
||||
)
|
||||
|
||||
assert result.exit_code == 0, result.output
|
||||
assert captured == {"deployment_id": "dep-123", "limit": "25"}
|
||||
assert result.output.strip() == "No revisions found for deployment dep-123."
|
||||
|
||||
|
||||
def test_deploy_revisions_list_missing_deployment_id_shows_usage() -> None:
|
||||
runner = CliRunner()
|
||||
|
||||
result = runner.invoke(cli, ["deploy", "revisions", "list"])
|
||||
|
||||
assert result.exit_code == 2, result.output
|
||||
assert "Missing argument 'DEPLOYMENT_ID'" in result.output
|
||||
|
||||
|
||||
def test_deploy_delete_command(monkeypatch) -> None:
|
||||
runner = CliRunner()
|
||||
captured: dict[str, str] = {}
|
||||
|
||||
class FakeClient:
|
||||
def __init__(self, host_url: str, api_key: str, tenant_id: str | None = None):
|
||||
captured["host_url"] = host_url
|
||||
captured["api_key"] = api_key
|
||||
captured["tenant_id"] = tenant_id or ""
|
||||
|
||||
def delete_deployment(self, deployment_id: str):
|
||||
captured["deployment_id"] = deployment_id
|
||||
return None
|
||||
|
||||
monkeypatch.setattr(cli_module, "HostBackendClient", FakeClient)
|
||||
|
||||
result = runner.invoke(
|
||||
cli,
|
||||
[
|
||||
"deploy",
|
||||
"delete",
|
||||
"--api-key",
|
||||
"test-key",
|
||||
"--host-url",
|
||||
"https://api.example.com",
|
||||
"dep-123",
|
||||
],
|
||||
input="y\n",
|
||||
)
|
||||
|
||||
assert result.exit_code == 0, result.output
|
||||
assert captured == {
|
||||
"host_url": "https://api.example.com",
|
||||
"api_key": "test-key",
|
||||
"tenant_id": "",
|
||||
"deployment_id": "dep-123",
|
||||
}
|
||||
assert (
|
||||
"Are you sure you want to delete deployment ID dep-123? (Y/n):" in result.output
|
||||
)
|
||||
assert result.output.strip().endswith("Deleted deployment dep-123.")
|
||||
|
||||
|
||||
def test_deploy_delete_command_cancelled(monkeypatch) -> None:
|
||||
runner = CliRunner()
|
||||
deleted = False
|
||||
|
||||
class FakeClient:
|
||||
def __init__(self, host_url: str, api_key: str, tenant_id: str | None = None):
|
||||
pass
|
||||
|
||||
def delete_deployment(self, deployment_id: str):
|
||||
nonlocal deleted
|
||||
deleted = True
|
||||
return None
|
||||
|
||||
monkeypatch.setattr(cli_module, "HostBackendClient", FakeClient)
|
||||
|
||||
result = runner.invoke(
|
||||
cli,
|
||||
[
|
||||
"deploy",
|
||||
"delete",
|
||||
"--api-key",
|
||||
"test-key",
|
||||
"--host-url",
|
||||
"https://api.example.com",
|
||||
"dep-123",
|
||||
],
|
||||
input="n\n",
|
||||
)
|
||||
|
||||
assert result.exit_code == 1, result.output
|
||||
assert not deleted
|
||||
assert "Aborted!" in result.output
|
||||
|
||||
|
||||
def test_deploy_delete_command_force(monkeypatch) -> None:
|
||||
runner = CliRunner()
|
||||
captured: dict[str, str] = {}
|
||||
|
||||
class FakeClient:
|
||||
def __init__(self, host_url: str, api_key: str, tenant_id: str | None = None):
|
||||
captured["host_url"] = host_url
|
||||
captured["api_key"] = api_key
|
||||
captured["tenant_id"] = tenant_id or ""
|
||||
|
||||
def delete_deployment(self, deployment_id: str):
|
||||
captured["deployment_id"] = deployment_id
|
||||
return None
|
||||
|
||||
monkeypatch.setattr(cli_module, "HostBackendClient", FakeClient)
|
||||
|
||||
result = runner.invoke(
|
||||
cli,
|
||||
[
|
||||
"deploy",
|
||||
"delete",
|
||||
"--force",
|
||||
"--api-key",
|
||||
"test-key",
|
||||
"--host-url",
|
||||
"https://api.example.com",
|
||||
"dep-123",
|
||||
],
|
||||
)
|
||||
|
||||
assert result.exit_code == 0, result.output
|
||||
assert "Are you sure you want to delete deployment ID dep-123?" not in result.output
|
||||
assert captured == {
|
||||
"host_url": "https://api.example.com",
|
||||
"api_key": "test-key",
|
||||
"tenant_id": "",
|
||||
"deployment_id": "dep-123",
|
||||
}
|
||||
assert result.output.strip() == "Deleted deployment dep-123."
|
||||
|
||||
|
||||
def test_dockerfile_command_basic() -> None:
|
||||
"""Test the 'dockerfile' command with basic configuration."""
|
||||
runner = CliRunner()
|
||||
|
||||
@@ -1784,9 +1784,7 @@ def test_config_to_compose_distributed_mode():
|
||||
# Executor service is present with correct base image
|
||||
assert "langgraph-executor:" in actual_compose_stdin
|
||||
assert "FROM langchain/langgraph-executor:3.11" in actual_compose_stdin
|
||||
assert (
|
||||
'entrypoint: ["sh", "/storage/executor_entrypoint.sh"]' in actual_compose_stdin
|
||||
)
|
||||
assert 'entrypoint: ["sh", "/storage/executor_entrypoint.sh"]' in actual_compose_stdin
|
||||
|
||||
# Executor has required environment variables
|
||||
assert "EXECUTOR_GRPC_PORT:" in actual_compose_stdin
|
||||
|
||||
@@ -3,17 +3,14 @@ import json
|
||||
import os
|
||||
|
||||
import click
|
||||
import httpx
|
||||
import pytest
|
||||
|
||||
from langgraph_cli.cli import (
|
||||
_call_host_backend_with_optional_tenant,
|
||||
_docker_config_for_token,
|
||||
_normalize_image_name,
|
||||
_normalize_image_tag,
|
||||
_parse_env_from_config,
|
||||
)
|
||||
from langgraph_cli.host_backend import HostBackendClient, HostBackendError
|
||||
|
||||
|
||||
class TestDockerConfigForToken:
|
||||
@@ -135,92 +132,3 @@ class TestParseEnvFromConfig:
|
||||
assert result["GOOD"] == "value"
|
||||
# EMPTY= gives empty string, not None, so it should be present
|
||||
assert result["EMPTY"] == ""
|
||||
|
||||
|
||||
class TestCallHostBackendWithOptionalTenant:
|
||||
def _make_client(self, handler):
|
||||
c = HostBackendClient("https://api.example.com", "test-key")
|
||||
c._client = httpx.Client(
|
||||
base_url="https://api.example.com",
|
||||
transport=httpx.MockTransport(handler),
|
||||
headers={"X-Api-Key": "test-key", "Accept": "application/json"},
|
||||
timeout=30,
|
||||
)
|
||||
return c
|
||||
|
||||
def _make_eu_client(self, handler):
|
||||
c = HostBackendClient("https://eu.api.host.langchain.com", "test-key")
|
||||
c._client = httpx.Client(
|
||||
base_url="https://eu.api.host.langchain.com",
|
||||
transport=httpx.MockTransport(handler),
|
||||
headers={"X-Api-Key": "test-key", "Accept": "application/json"},
|
||||
timeout=30,
|
||||
)
|
||||
return c
|
||||
|
||||
def test_success_passes_through(self):
|
||||
client = self._make_client(lambda req: httpx.Response(200, json={"ok": True}))
|
||||
result = _call_host_backend_with_optional_tenant(
|
||||
client, lambda c: c.list_deployments()
|
||||
)
|
||||
assert result == {"ok": True}
|
||||
|
||||
def test_403_not_enabled_gives_actionable_error(self):
|
||||
detail = (
|
||||
'{"detail":"LangSmith Deployment is not enabled for this organization"}'
|
||||
)
|
||||
client = self._make_client(lambda req: httpx.Response(403, text=detail))
|
||||
with pytest.raises(HostBackendError, match="not enabled") as exc_info:
|
||||
_call_host_backend_with_optional_tenant(
|
||||
client, lambda c: c.list_deployments()
|
||||
)
|
||||
assert exc_info.value.status_code == 403
|
||||
assert "smith.langchain.com" in exc_info.value.message
|
||||
|
||||
def test_403_not_enabled_eu_url(self):
|
||||
detail = (
|
||||
'{"detail":"LangSmith Deployment is not enabled for this organization"}'
|
||||
)
|
||||
client = self._make_eu_client(lambda req: httpx.Response(403, text=detail))
|
||||
with pytest.raises(HostBackendError, match="not enabled") as exc_info:
|
||||
_call_host_backend_with_optional_tenant(
|
||||
client, lambda c: c.list_deployments()
|
||||
)
|
||||
assert "eu.smith.langchain.com" in exc_info.value.message
|
||||
|
||||
def test_workspace_retry_then_not_enabled_gives_actionable_error(self, monkeypatch):
|
||||
requires_workspace = '{"detail":"requires workspace specification"}'
|
||||
not_enabled = (
|
||||
'{"detail":"LangSmith Deployment is not enabled for this organization"}'
|
||||
)
|
||||
seen_tenant_ids = []
|
||||
|
||||
def handler(req):
|
||||
seen_tenant_ids.append(req.headers.get("X-Tenant-ID"))
|
||||
if len(seen_tenant_ids) == 1:
|
||||
return httpx.Response(403, text=requires_workspace)
|
||||
if len(seen_tenant_ids) == 2:
|
||||
return httpx.Response(403, text=not_enabled)
|
||||
raise AssertionError("unexpected extra request")
|
||||
|
||||
monkeypatch.setattr(click, "prompt", lambda _text: "workspace-123")
|
||||
client = self._make_client(handler)
|
||||
|
||||
with pytest.raises(HostBackendError, match="not enabled") as exc_info:
|
||||
_call_host_backend_with_optional_tenant(
|
||||
client, lambda c: c.list_deployments()
|
||||
)
|
||||
|
||||
assert exc_info.value.status_code == 403
|
||||
assert "smith.langchain.com" in exc_info.value.message
|
||||
assert seen_tenant_ids == [None, "workspace-123"]
|
||||
assert client._client.headers["X-Tenant-ID"] == "workspace-123"
|
||||
|
||||
def test_other_403_re_raises_original(self):
|
||||
client = self._make_client(
|
||||
lambda req: httpx.Response(403, text='{"detail":"some other error"}')
|
||||
)
|
||||
with pytest.raises(HostBackendError, match="some other error"):
|
||||
_call_host_backend_with_optional_tenant(
|
||||
client, lambda c: c.list_deployments()
|
||||
)
|
||||
|
||||
@@ -135,28 +135,6 @@ def test_list_deployments(client):
|
||||
assert result == {"ok": True}
|
||||
|
||||
|
||||
def test_list_deployments_sends_query_params():
|
||||
def handler(req: httpx.Request) -> httpx.Response:
|
||||
assert req.url.path == "/v2/deployments"
|
||||
assert req.url.params["name_contains"] == "my app"
|
||||
return httpx.Response(200, json={"ok": True})
|
||||
|
||||
c = HostBackendClient("https://api.example.com", "test-key")
|
||||
c._client = httpx.Client(
|
||||
base_url="https://api.example.com",
|
||||
transport=httpx.MockTransport(handler),
|
||||
headers={"X-Api-Key": "test-key", "Accept": "application/json"},
|
||||
timeout=30,
|
||||
)
|
||||
result = c.list_deployments("my app")
|
||||
assert result == {"ok": True}
|
||||
|
||||
|
||||
def test_delete_deployment(client):
|
||||
result = client.delete_deployment("dep-123")
|
||||
assert result == {"ok": True}
|
||||
|
||||
|
||||
def test_request_push_token(client):
|
||||
result = client.request_push_token("dep-123")
|
||||
assert result == {"ok": True}
|
||||
@@ -182,41 +160,3 @@ def test_list_revisions(client):
|
||||
def test_get_revision(client):
|
||||
result = client.get_revision("dep-123", "rev-456")
|
||||
assert result == {"ok": True}
|
||||
|
||||
|
||||
def test_get_build_logs(client):
|
||||
result = client.get_build_logs("proj-1", "rev-1", {"limit": 10})
|
||||
assert result == {"ok": True}
|
||||
|
||||
|
||||
def test_get_deploy_logs_all_revisions():
|
||||
def handler(req: httpx.Request) -> httpx.Response:
|
||||
assert "/v1/projects/proj-1/deploy_logs" in str(req.url)
|
||||
assert "/revisions/" not in str(req.url)
|
||||
return httpx.Response(200, json={"logs": [{"message": "running"}]})
|
||||
|
||||
c = HostBackendClient("https://api.example.com", "key")
|
||||
c._client = httpx.Client(
|
||||
base_url="https://api.example.com",
|
||||
transport=httpx.MockTransport(handler),
|
||||
headers={"X-Api-Key": "key", "Accept": "application/json"},
|
||||
timeout=30,
|
||||
)
|
||||
result = c.get_deploy_logs("proj-1", {"limit": 10})
|
||||
assert result == {"logs": [{"message": "running"}]}
|
||||
|
||||
|
||||
def test_get_deploy_logs_specific_revision():
|
||||
def handler(req: httpx.Request) -> httpx.Response:
|
||||
assert "/v1/projects/proj-1/revisions/rev-2/deploy_logs" in str(req.url)
|
||||
return httpx.Response(200, json={"logs": []})
|
||||
|
||||
c = HostBackendClient("https://api.example.com", "key")
|
||||
c._client = httpx.Client(
|
||||
base_url="https://api.example.com",
|
||||
transport=httpx.MockTransport(handler),
|
||||
headers={"X-Api-Key": "key", "Accept": "application/json"},
|
||||
timeout=30,
|
||||
)
|
||||
result = c.get_deploy_logs("proj-1", {"limit": 10}, revision_id="rev-2")
|
||||
assert result == {"logs": []}
|
||||
|
||||
@@ -1,58 +0,0 @@
|
||||
from langgraph_cli.helpers import format_log_entry, format_timestamp, level_fg
|
||||
|
||||
|
||||
class TestFormatTimestamp:
|
||||
def test_epoch_ms(self):
|
||||
assert format_timestamp(1773119644012) == "2026-03-10 05:14:04"
|
||||
|
||||
def test_string_passthrough(self):
|
||||
assert format_timestamp("2026-03-08T00:00:00Z") == "2026-03-08T00:00:00Z"
|
||||
|
||||
def test_empty(self):
|
||||
assert format_timestamp("") == ""
|
||||
|
||||
def test_none(self):
|
||||
assert format_timestamp(None) == ""
|
||||
|
||||
|
||||
class TestFormatLogEntry:
|
||||
def test_full_entry_epoch(self):
|
||||
entry = {"timestamp": 1773119644012, "level": "ERROR", "message": "boom"}
|
||||
result = format_log_entry(entry)
|
||||
assert result == "[2026-03-10 05:14:04] [ERROR] boom"
|
||||
|
||||
def test_full_entry_string(self):
|
||||
entry = {
|
||||
"timestamp": "2026-03-08T12:00:00Z",
|
||||
"level": "ERROR",
|
||||
"message": "boom",
|
||||
}
|
||||
assert format_log_entry(entry) == "[2026-03-08T12:00:00Z] [ERROR] boom"
|
||||
|
||||
def test_no_level(self):
|
||||
entry = {"timestamp": "2026-03-08T12:00:00Z", "message": "hello"}
|
||||
assert format_log_entry(entry) == "[2026-03-08T12:00:00Z] hello"
|
||||
|
||||
def test_no_timestamp(self):
|
||||
entry = {"message": "bare message"}
|
||||
assert format_log_entry(entry) == "bare message"
|
||||
|
||||
def test_empty_entry(self):
|
||||
assert format_log_entry({}) == ""
|
||||
|
||||
|
||||
class TestLevelFg:
|
||||
def test_error(self):
|
||||
assert level_fg("ERROR") == "red"
|
||||
|
||||
def test_error_lowercase(self):
|
||||
assert level_fg("error") == "red"
|
||||
|
||||
def test_warning(self):
|
||||
assert level_fg("WARNING") == "yellow"
|
||||
|
||||
def test_info_returns_none(self):
|
||||
assert level_fg("INFO") is None
|
||||
|
||||
def test_empty_returns_none(self):
|
||||
assert level_fg("") is None
|
||||
@@ -1,12 +1,6 @@
|
||||
from unittest.mock import patch
|
||||
|
||||
from langgraph_cli.util import (
|
||||
_extract_deployment_url,
|
||||
clean_empty_lines,
|
||||
format_deployments_table,
|
||||
format_revisions_table,
|
||||
warn_non_wolfi_distro,
|
||||
)
|
||||
from langgraph_cli.util import clean_empty_lines, warn_non_wolfi_distro
|
||||
|
||||
|
||||
def test_clean_empty_lines():
|
||||
@@ -192,67 +186,3 @@ def test_warn_non_wolfi_distro_does_not_modify_config():
|
||||
warn_non_wolfi_distro(config_copy)
|
||||
|
||||
assert config_copy == original_config # Config should remain unchanged
|
||||
|
||||
|
||||
def test_extract_deployment_url_uses_custom_url():
|
||||
deployment = {"source_config": {"custom_url": "https://example.com/custom"}}
|
||||
assert _extract_deployment_url(deployment) == "https://example.com/custom"
|
||||
|
||||
|
||||
def test_extract_deployment_url_defaults_to_dash():
|
||||
assert _extract_deployment_url({"id": "dep-123"}) == "-"
|
||||
|
||||
|
||||
def test_format_deployments_table():
|
||||
output = format_deployments_table(
|
||||
[
|
||||
{
|
||||
"id": "dep-123",
|
||||
"name": "alpha",
|
||||
"source_config": {"custom_url": "https://alpha.example.com"},
|
||||
},
|
||||
{
|
||||
"id": "dep-456",
|
||||
"name": "beta",
|
||||
"url": "https://beta.example.com",
|
||||
},
|
||||
]
|
||||
)
|
||||
assert "Deployment ID" in output
|
||||
assert "Deployment Name" in output
|
||||
assert "Deployment URL" in output
|
||||
assert "dep-123" in output
|
||||
assert "alpha" in output
|
||||
assert "https://alpha.example.com" in output
|
||||
assert "dep-456" in output
|
||||
|
||||
|
||||
def test_format_revisions_table():
|
||||
output = format_revisions_table(
|
||||
[
|
||||
{
|
||||
"id": "rev-123",
|
||||
"status": "DEPLOYED",
|
||||
"created_at": "2023-11-09T10:00:00Z",
|
||||
},
|
||||
{
|
||||
"id": "rev-456",
|
||||
"status": "CREATING",
|
||||
"created_at": "2023-11-07T05:31:56Z",
|
||||
},
|
||||
{
|
||||
"id": "rev-789",
|
||||
"status": "DEPLOYED",
|
||||
"created_at": "2023-11-08T10:00:00Z",
|
||||
},
|
||||
]
|
||||
)
|
||||
assert "Revision ID" in output
|
||||
assert "Status" in output
|
||||
assert "Created At" in output
|
||||
assert "rev-123" in output
|
||||
assert "CREATING" in output
|
||||
assert "2023-11-07T05:31:56Z" in output
|
||||
assert "rev-456" in output
|
||||
assert "rev-789" in output
|
||||
assert "REPLACED" in output
|
||||
|
||||
Generated
+26
-25
@@ -992,6 +992,7 @@ dependencies = [
|
||||
inmem = [
|
||||
{ name = "langgraph-api", marker = "python_full_version >= '3.11'" },
|
||||
{ name = "langgraph-runtime-inmem", marker = "python_full_version >= '3.11'" },
|
||||
{ name = "python-dotenv" },
|
||||
]
|
||||
|
||||
[package.dev-dependencies]
|
||||
@@ -1088,15 +1089,15 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "langgraph-sdk"
|
||||
version = "0.3.11"
|
||||
version = "0.3.9"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "httpx", marker = "python_full_version >= '3.11'" },
|
||||
{ name = "orjson", marker = "python_full_version >= '3.11'" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/35/cd/a019f1b1e97c519f2425593f9bccd3ac463a18fb5d2111cff59ce1ef62fe/langgraph_sdk-0.3.11.tar.gz", hash = "sha256:3640134835d89d2c7c8bb7de73bd10673d4b282db3ff0e2fdaf1cee9e50cb1eb", size = 190387, upload-time = "2026-03-11T00:46:45.25Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/3a/bd/ca8ae5c6a34be6d4f7aa86016e010ff96b3a939456041565797952e3014d/langgraph_sdk-0.3.9.tar.gz", hash = "sha256:8be8958529b3f6d493ec248fdb46e539362efda75784654a42a7091d22504e0e", size = 184287, upload-time = "2026-02-24T18:39:03.276Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/13/c8/b8d15d4b9a320a3f57a851030a371066b91dbd1420f097d3d0338da9adc9/langgraph_sdk-0.3.11-py3-none-any.whl", hash = "sha256:18905fd6248ade98b0995d859a98672d57c811fbfffc0d63d1c107a512351b26", size = 94887, upload-time = "2026-03-11T00:46:43.855Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/6a/4c/7a7510260fbda788efd13bf4650d3e7d80988118441ac811ec78e0aa03ac/langgraph_sdk-0.3.9-py3-none-any.whl", hash = "sha256:94654294250c920789b6ed0d8a70c0117fed5736b61efc24ff647157359453c5", size = 90511, upload-time = "2026-02-24T18:39:02.012Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -1796,11 +1797,11 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "pyjwt"
|
||||
version = "2.12.0"
|
||||
version = "2.11.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/a8/10/e8192be5f38f3e8e7e046716de4cae33d56fd5ae08927a823bb916be36c1/pyjwt-2.12.0.tar.gz", hash = "sha256:2f62390b667cd8257de560b850bb5a883102a388829274147f1d724453f8fb02", size = 102511, upload-time = "2026-03-12T17:15:30.831Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/5c/5a/b46fa56bf322901eee5b0454a34343cdbdae202cd421775a8ee4e42fd519/pyjwt-2.11.0.tar.gz", hash = "sha256:35f95c1f0fbe5d5ba6e43f00271c275f7a1a4db1dab27bf708073b75318ea623", size = 98019, upload-time = "2026-01-30T19:59:55.694Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/15/70/70f895f404d363d291dcf62c12c85fdd47619ad9674ac0f53364d035925a/pyjwt-2.12.0-py3-none-any.whl", hash = "sha256:9bb459d1bdd0387967d287f5656bf7ec2b9a26645d1961628cda1764e087fd6e", size = 29700, upload-time = "2026-03-12T17:15:29.257Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/6f/01/c26ce75ba460d5cd503da9e13b21a33804d38c2165dec7b716d06b13010c/pyjwt-2.11.0-py3-none-any.whl", hash = "sha256:94a6bde30eb5c8e04fee991062b534071fd1439ef58d2adc9ccb823e7bcd0469", size = 28224, upload-time = "2026-01-30T19:59:54.539Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -2026,27 +2027,27 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "ruff"
|
||||
version = "0.15.6"
|
||||
version = "0.15.5"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/51/df/f8629c19c5318601d3121e230f74cbee7a3732339c52b21daa2b82ef9c7d/ruff-0.15.6.tar.gz", hash = "sha256:8394c7bb153a4e3811a4ecdacd4a8e6a4fa8097028119160dffecdcdf9b56ae4", size = 4597916, upload-time = "2026-03-12T23:05:47.51Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/77/9b/840e0039e65fcf12758adf684d2289024d6140cde9268cc59887dc55189c/ruff-0.15.5.tar.gz", hash = "sha256:7c3601d3b6d76dce18c5c824fc8d06f4eef33d6df0c21ec7799510cde0f159a2", size = 4574214, upload-time = "2026-03-05T20:06:34.946Z" }
|
||||
wheels = [
|
||||
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[[package]]
|
||||
|
||||
@@ -0,0 +1,25 @@
|
||||
from langgraph.advanced_graph.state import (
|
||||
AdvancedStateGraph,
|
||||
AnyOfCondition,
|
||||
ChannelCondition,
|
||||
CompiledGraphEngine,
|
||||
Context,
|
||||
GraphRunHandler,
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||||
TimerCondition,
|
||||
any_of,
|
||||
channel_condition,
|
||||
timer_condition,
|
||||
)
|
||||
|
||||
__all__ = (
|
||||
"AdvancedStateGraph",
|
||||
"AnyOfCondition",
|
||||
"ChannelCondition",
|
||||
"Context",
|
||||
"CompiledGraphEngine",
|
||||
"GraphRunHandler",
|
||||
"TimerCondition",
|
||||
"any_of",
|
||||
"channel_condition",
|
||||
"timer_condition",
|
||||
)
|
||||
@@ -0,0 +1,130 @@
|
||||
# Evolve/Extend LangGraph with next level of orchestration
|
||||
|
||||
## LangGraph Today: A Strong Foundation with Creative Innovation
|
||||
|
||||
LangGraph is already an exceptional orchestration framework. It has introduced a number of creative features that no other workflow engine on the market has even attempted.
|
||||
|
||||
**First-class streaming.** No workflow engine has ever integrated streaming as seamlessly as LangGraph. Streaming is not an afterthought bolted on top — it is woven into the core execution model, allowing every node, every tool call, and every LLM interaction to emit incremental output naturally.
|
||||
|
||||
**Flexible durability modes.** LangGraph defaults to asynchronous execution and supports sync and "exit" modes as well. This is a significant departure from traditional workflow engines, which typically only offer synchronous execution. The ability to choose a durability mode gives developers fine-grained control over the trade-off between persistence guarantees and execution speed.
|
||||
|
||||
**Reusable checkpoints.** The checkpoint system allows state to be captured at any point during graph execution and freely replayed, forked, or resumed later. This enables powerful patterns like time-travel debugging, human-in-the-loop approval flows, and long-running conversations that can be picked up exactly where they left off.
|
||||
|
||||
**Double texting.** LangGraph natively handles the real-world scenario where a user sends a new message while a previous one is still being processed — a problem most orchestration frameworks simply ignore.
|
||||
|
||||
Beyond these innovative features, LangGraph provides solid support for the foundational workflow execution patterns that developers rely on daily. Sequential execution, or loops and conditional branching. Basic parallelism is also well supported: when multiple LLM calls or tool invocations are independent of each other, they can run concurrently to avoid the latency cost of sequential execution, and their results are merged back into the shared state for downstream processing.
|
||||
|
||||
LangGraph also offers a simple and intuitive mechanism for human-in-the-loop interactions, allowing a graph to pause execution and wait for user input before continuing.
|
||||
|
||||
Combined with the broader LangChain ecosystem, these have made LangGraph a significant success in the market.
|
||||
|
||||
## Emerging Gaps: What LangGraph Struggles to Support
|
||||
|
||||
As adoption has grown and use cases have become more sophisticated, we have discovered an increasing number of scenarios and design patterns that LangGraph cannot support well today.
|
||||
|
||||
**Complex sub-agent coordination.** A main agent often needs to manage multiple sub-agents, but the coordination involved is far more nuanced than simply launching a batch of sub-agents, waiting for all of them to finish, and then moving on. In practice, a main agent may launch a sub-agent, continue doing other work, spawn additional sub-agents later, wait selectively for certain results, retry with a different strategy if one sub-agent fails, or dynamically decide what to do next based on partial results that arrive at unpredictable times.
|
||||
|
||||
LangGraph today lacks the coordination primitives to express this. The current parallelism model groups multiple nodes into a single superstep — all of them execute concurrently, but _all_ must complete before the graph can advance to the next step. There is no way for one node to proceed independently while others are still running, and no built-in mechanism for selective waiting, partial result handling, or dynamic task spawning mid-execution.
|
||||
|
||||
Sub-agents also cannot simply be modeled as subgraphs, because subgraphs today execute within the same run. They cannot be scaled up independently — if a sub-agent is resource-intensive, there is no straightforward way to run it on a separate machine. Ideally, launching a sub-agent should be(or opt in) as simple as dispatching it for distributed execution across multiple machines.
|
||||
|
||||
**Concurrent input and output (e.g. audio agents).** Audio agents also present a particularly clear example of a pattern LangGraph cannot express today. In a voice interaction, speech input and speech output may happen simultaneously — the agent should be able to process a previous utterance, continue receiving new audio input, and produce output all at the same time. These three activities should not be mutually exclusive.
|
||||
|
||||
The closest workaround today is double texting, but it has a fundamental flaw: when a new audio input arrives, the previous one is interrupted and canceled rather than being allowed to gracefully complete. The workflow code itself should have the control to decide whether to stop running.
|
||||
|
||||
LangGraph is, at its core, a general-purpose workflow engine. Although we focus primarily on agent development, none of the primitives it offers are exclusive to agents or dedicated solely to agentic use cases. Conversely, there is nothing that a general-purpose workflow engine provides that we can safely assume agent development will _never_ need.
|
||||
|
||||
The difference is probably only priority. For example, durable timer where a step can sleep for hours, days or months before resuming. Traditional workflow engines — those built for general microservice orchestration(which doesn't need streaming) -- they may need durable timers. In the agent development world today, most agents are still relatively simple. There are not yet many scenarios that require a step to wait for hours or days before proceeding.
|
||||
|
||||
|
||||
## Deriving What's Needed from First Principles
|
||||
|
||||
Before jumping to solutions, it is worth stepping back and asking a fundamental question: what is an orchestration engine, and what do users expect it to provide?
|
||||
|
||||
At its most fundamental level, a workflow engine's value proposition is making a long-running process execute reliably. If a machine crashes, execution should smoothly fail over to another machine and resume from the last point where it was interrupted — not start over from the beginning. So we can reason about what is needed by asking: what would a developer do if they had to build a long-running process _without_ a workflow engine?
|
||||
|
||||
Starting from the simple. A developer could write a simple `main` function — a single-threaded program, just like everyone writes when they first learn to code. It would have `if/else` branches, `for` loops, and maybe it would wait for command-line input. Many early agent use cases look exactly like this: execute a sequence of steps, make decisions along the way, loop when necessary.
|
||||
|
||||
But if that machine crashes, you probably do not want the process to start over from scratch. You want it to resume from the last step that completed successfully. And if a step fails, you might want it to retry automatically before giving up.
|
||||
|
||||
LangGraph handles this case very well.
|
||||
|
||||
There is an important constraint worth calling out explicitly: LangGraph requires the developer to organize their code into **nodes**, which serve as the boundaries at which checkpoints can be taken. This is a constraint shared by every workflow engine — it is simply not feasible to persist a checkpoint after every single line of arbitrary code.
|
||||
|
||||
### From Single-Threaded to Concurrent: Where the Model Breaks Down
|
||||
|
||||
But as product requirements grow more complex, a single-threaded program is no longer sufficient. The process becomes multi-threaded or multi-process. And in a multi-threaded program, each thread executes independently — when one thread finishes a step and moves on to its next step, it does not need to wait for another thread to finish _its_ current step first.
|
||||
|
||||
This is precisely why LangGraph's superstep restriction feels awkward in practice. In the superstep model, all concurrently executing nodes must complete before any of them can advance. But that is not how independent threads work. Each thread should be able to progress at its own pace, checkpoint its own state, and move to its next step without being blocked by unrelated work happening in parallel.
|
||||
|
||||
Multiple threads and processes do, however, need to coordinate with each other. In concurrent programming, channels are an essential primitive precisely because they provide a safe, structured way for threads to communicate and synchronize without relying on shared mutable memory — avoiding data races and deadlocks. In some cases, threads may use locking for coordination, but the preferred approach is message passing through channels.
|
||||
|
||||
NOTE: "channel" is overloaded term here as it's also an internal term within current LangGraph pregel algorithm.
|
||||
|
||||
LangGraph already has a mechanism that is closely related: `interrupt`. A run can be interrupted, and then another run can resume it. If we look at this through the lens of channels, `interrupt` is essentially a **channel with size 0** — a synchronous rendezvous point where one side blocks until the other side is ready.
|
||||
|
||||
The natural extension:
|
||||
|
||||
1. **Variable-size channels.** The channel buffer size should be configurable — size 0 for synchronous handoff (like `interrupt` today), size N for buffered communication where the sender can proceed without waiting, and unbounded for fully asynchronous fire-and-forget messaging.
|
||||
2. **Channels across boundaries.** Channels should not be limited to communication between separate runs. Nodes within the same graph should also be able to send and receive through channels — mirroring the way both multi-process communication (between runs) and multi-thread communication (between nodes within a run) work in ordinary concurrent programs.
|
||||
3. **Node-level blocking, not run-level pausing.** When a node waits on a channel (i.e. `interrupt`), only that node should block — the rest of the graph should continue executing. Today, `interrupt` pauses the entire run. In a concurrent program, when one thread blocks on a channel read, the other threads keep running. The same should be true: an interrupt should suspend the individual node, not halt the whole run.
|
||||
|
||||
## Summmary of all extension opportunity
|
||||
|
||||
### P1: urgently needed
|
||||
#### Remove the Superstep Restriction
|
||||
|
||||
Today, when multiple nodes execute in parallel, they are grouped into a superstep. All nodes in a superstep must complete before any downstream node can begin. This means that even if `b1` finishes quickly and its successor `b11` is ready to run, it must wait for `b2` to finish first.
|
||||
|
||||
With the superstep restriction removed, each parallel branch progresses independently. As soon as a node completes, its downstream successor can begin immediately — regardless of what is happening in other branches.
|
||||
|
||||
**Current behavior (superstep model):**
|
||||
|
||||
```
|
||||
Step 1: a
|
||||
Step 2: b1, b2 ← both must finish before step 3
|
||||
Step 3: b11, b22 ← both start together
|
||||
```
|
||||
|
||||
Even if `b1` finishes in 1 second and `b2` takes 30 seconds, `b11` cannot start until `b2` is done.
|
||||
|
||||
**Proposed behavior (independent branches):**
|
||||
|
||||
```
|
||||
Branch 1: a → b1 → b11 → ...
|
||||
Branch 2: a → b2 → b22 → ...
|
||||
```
|
||||
|
||||
Each branch advances at its own pace. `b1` finishing triggers `b11` immediately, without waiting for `b2`.
|
||||
|
||||
|
||||
No API change is needed from the user's perspective — the graph definition stays the same. The change is in the execution semantics: the engine no longer forces all parallel nodes to synchronize at each step boundary. Each branch is checkpointed independently, so if `b1 → b11` completes while `b2` is still running, `b11`'s result is already persisted.
|
||||
|
||||
This is necessary for the next one -- Light-weight Interrupt: Only Block the Current Node. Because we want to let other nodes continue to run while a node is waiting on something.
|
||||
|
||||
#### Light-weight Interrupt -- wait_for API: Only Block the Current Node Until Channel Has Enough Messages
|
||||
|
||||
Today, `interrupt` pauses the entire run. Every node stops, and nothing can proceed until the interrupt is resolved externally. This is the right behavior for a simple single-threaded workflow, but it breaks down when multiple branches are executing concurrently — one branch needing input should not freeze all the others.
|
||||
|
||||
The proposed change has three parts:
|
||||
|
||||
1. **Named channels.** A graph can declare named channels as coordination points. These are distinct from the graph's state — they are message-passing primitives, not shared memory.
|
||||
2. **`wait_for` blocks only the current node.** When a node calls `wait_for`, it suspends itself and waits for messages on the specified channel. All other nodes in the graph continue executing normally.
|
||||
3. A channel can be published from both external and internal
|
||||
|
||||
The `wait_for` call takes a channel name and optionally a count `N`, meaning "wait until N messages have arrived on this channel before resuming."
|
||||
|
||||
**Prototype:**
|
||||
|
||||
See [test_sub_agents.py](../libs/langgraph/tests/advanced-graph/test_sub_agents.py)
|
||||
|
||||
|
||||
### P2: likely needed
|
||||
#### subGraph redesign
|
||||
#### durable timers
|
||||
#### more flexiable waiting conditions on interrupts
|
||||
#### locking on state fields
|
||||
|
||||
|
||||
### P3: future needed or nice to have
|
||||
#### RPC
|
||||
@@ -0,0 +1,445 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import inspect
|
||||
from collections.abc import Callable, Mapping, Sequence
|
||||
from dataclasses import dataclass
|
||||
from datetime import timedelta
|
||||
from typing import Any, Generic, TypeVar, cast
|
||||
|
||||
from langgraph.types import Command, Send
|
||||
|
||||
StateT = TypeVar("StateT")
|
||||
|
||||
|
||||
@dataclass(frozen=True)
|
||||
class _ChannelSpec:
|
||||
typ: Any
|
||||
|
||||
|
||||
@dataclass(frozen=True)
|
||||
class ChannelCondition:
|
||||
channel: str
|
||||
n: int = 1
|
||||
|
||||
|
||||
@dataclass(frozen=True)
|
||||
class TimerCondition:
|
||||
seconds: float
|
||||
|
||||
|
||||
@dataclass(frozen=True)
|
||||
class AnyOfCondition:
|
||||
conditions: tuple[WaitCondition, ...]
|
||||
|
||||
|
||||
WaitCondition = ChannelCondition | TimerCondition
|
||||
|
||||
|
||||
class AdvancedStateGraph(Generic[StateT]):
|
||||
"""Experimental in-memory graph engine with async channels."""
|
||||
|
||||
def __init__(self, state_schema: type[StateT]) -> None:
|
||||
self.state_schema = state_schema
|
||||
self._nodes: dict[str, Callable[..., Any]] = {}
|
||||
self._async_channels: dict[str, _ChannelSpec] = {}
|
||||
self._entry_point: str | None = None
|
||||
self._finish_point: str | None = None
|
||||
|
||||
def add_node(
|
||||
self,
|
||||
name_or_node: str | Callable[..., Any],
|
||||
node: Callable[..., Any] | None = None,
|
||||
) -> str:
|
||||
if node is None:
|
||||
if not callable(name_or_node):
|
||||
raise TypeError("add_node() expects a callable when name is omitted")
|
||||
node_name = _infer_node_name(name_or_node)
|
||||
node_fn = name_or_node
|
||||
else:
|
||||
if not isinstance(name_or_node, str):
|
||||
raise TypeError("add_node() expects a string node name")
|
||||
node_name = name_or_node
|
||||
node_fn = node
|
||||
|
||||
if node_name in self._nodes:
|
||||
raise ValueError(f"Node `{node_name}` already exists")
|
||||
self._nodes[node_name] = node_fn
|
||||
return node_name
|
||||
|
||||
def add_async_channel(self, name: str, typ: Any) -> None:
|
||||
if name in self._async_channels:
|
||||
raise ValueError(f"Channel `{name}` already exists")
|
||||
self._async_channels[name] = _ChannelSpec(typ=typ)
|
||||
|
||||
def set_entry_point(self, name_or_node: str | Callable[..., Any]) -> None:
|
||||
self._entry_point = self._resolve_node_name(name_or_node)
|
||||
|
||||
def set_finish_point(self, name_or_node: str | Callable[..., Any]) -> None:
|
||||
self._finish_point = self._resolve_node_name(name_or_node)
|
||||
|
||||
def add_entry_node(self, node: Callable[..., Any]) -> str:
|
||||
node_name = self.add_node(node)
|
||||
self.set_entry_point(node_name)
|
||||
return node_name
|
||||
|
||||
def add_finish_node(self, node: Callable[..., Any]) -> str:
|
||||
node_name = self.add_node(node)
|
||||
self.set_finish_point(node_name)
|
||||
return node_name
|
||||
|
||||
def _resolve_node_name(self, name_or_node: str | Callable[..., Any]) -> str:
|
||||
if isinstance(name_or_node, str):
|
||||
return name_or_node
|
||||
node_name = _infer_node_name(name_or_node)
|
||||
if node_name not in self._nodes:
|
||||
self._nodes[node_name] = name_or_node
|
||||
return node_name
|
||||
|
||||
def compile(self) -> CompiledGraphEngine[StateT]:
|
||||
if self._entry_point is None:
|
||||
raise ValueError("Entry point is not set")
|
||||
if self._finish_point is None:
|
||||
raise ValueError("Finish point is not set")
|
||||
if self._entry_point not in self._nodes:
|
||||
raise ValueError(f"Entry point node `{self._entry_point}` does not exist")
|
||||
if self._finish_point not in self._nodes:
|
||||
raise ValueError(f"Finish point node `{self._finish_point}` does not exist")
|
||||
return CompiledGraphEngine(
|
||||
nodes=dict(self._nodes),
|
||||
async_channels=dict(self._async_channels),
|
||||
entry_point=self._entry_point,
|
||||
finish_point=self._finish_point,
|
||||
)
|
||||
|
||||
|
||||
class CompiledGraphEngine(Generic[StateT]):
|
||||
"""Executable runtime for `AdvancedStateGraph`."""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
*,
|
||||
nodes: dict[str, Callable[..., Any]],
|
||||
async_channels: dict[str, _ChannelSpec],
|
||||
entry_point: str,
|
||||
finish_point: str,
|
||||
) -> None:
|
||||
self._nodes = nodes
|
||||
self._async_channels = async_channels
|
||||
self._entry_point = entry_point
|
||||
self._finish_point = finish_point
|
||||
|
||||
async def ainvoke(self, initial_state: StateT) -> StateT:
|
||||
handler = await self.astart(initial_state)
|
||||
return await handler
|
||||
|
||||
async def astart(self, initial_state: StateT) -> GraphRunHandler[StateT]:
|
||||
run = _GraphEngineRun(
|
||||
nodes=self._nodes,
|
||||
async_channel_specs=self._async_channels,
|
||||
entry_point=self._entry_point,
|
||||
finish_point=self._finish_point,
|
||||
)
|
||||
task = asyncio.create_task(run.run(initial_state))
|
||||
return GraphRunHandler(run=run, task=task)
|
||||
|
||||
|
||||
class Context:
|
||||
"""Per-run context injected into advanced graph nodes."""
|
||||
|
||||
def __init__(self, run: _GraphEngineRun) -> None:
|
||||
self._run = run
|
||||
|
||||
async def wait_for(self, target: WaitCondition | AnyOfCondition) -> Any:
|
||||
return await self._run.wait_for(target)
|
||||
|
||||
def publish_to_channel(self, channel: str, value: Any) -> None:
|
||||
self._run.publish_nowait(channel, value)
|
||||
|
||||
async def apublish_to_channel(self, channel: str, value: Any) -> None:
|
||||
await self._run.publish(channel, value)
|
||||
|
||||
|
||||
class GraphRunHandler(Generic[StateT]):
|
||||
"""Handle for an active in-memory run."""
|
||||
|
||||
def __init__(self, *, run: _GraphEngineRun, task: asyncio.Task[StateT]) -> None:
|
||||
self._run = run
|
||||
self._task = task
|
||||
|
||||
async def apublish_to_channel(self, channel: str, value: Any) -> None:
|
||||
if self._task.done():
|
||||
raise RuntimeError("Run has already completed")
|
||||
await self._run.publish(channel, value)
|
||||
|
||||
async def aresult(self) -> StateT:
|
||||
return await self._task
|
||||
|
||||
def __await__(self) -> Any:
|
||||
return self._task.__await__()
|
||||
|
||||
|
||||
class _GraphEngineRun:
|
||||
def __init__(
|
||||
self,
|
||||
*,
|
||||
nodes: dict[str, Callable[..., Any]],
|
||||
async_channel_specs: dict[str, _ChannelSpec],
|
||||
entry_point: str,
|
||||
finish_point: str,
|
||||
) -> None:
|
||||
self._nodes = nodes
|
||||
self._entry_point = entry_point
|
||||
self._finish_point = finish_point
|
||||
self._async_channels: dict[str, asyncio.Queue[Any]] = {
|
||||
name: asyncio.Queue() for name, _spec in async_channel_specs.items()
|
||||
}
|
||||
self._tasks: set[asyncio.Task[list[Send]]] = set()
|
||||
self._finished = False
|
||||
self._state: Any = None
|
||||
self.context = Context(self)
|
||||
|
||||
async def run(self, initial_state: StateT) -> StateT:
|
||||
self._state = initial_state
|
||||
self._schedule(Send(self._entry_point, initial_state))
|
||||
try:
|
||||
while self._tasks and not self._finished:
|
||||
done, _ = await asyncio.wait(
|
||||
self._tasks, return_when=asyncio.FIRST_COMPLETED
|
||||
)
|
||||
for task in done:
|
||||
self._tasks.remove(task)
|
||||
exc = task.exception()
|
||||
if exc is not None:
|
||||
await self._cancel_all_tasks()
|
||||
raise exc
|
||||
sends = task.result()
|
||||
for send in sends:
|
||||
self._schedule(send)
|
||||
if self._finished:
|
||||
await self._cancel_all_tasks()
|
||||
return cast(StateT, self._state)
|
||||
finally:
|
||||
await self._cancel_all_tasks()
|
||||
|
||||
async def publish(self, channel: str, value: Any) -> None:
|
||||
queue = self._get_async_channel(channel)
|
||||
await queue.put(value)
|
||||
|
||||
def publish_nowait(self, channel: str, value: Any) -> None:
|
||||
queue = self._get_async_channel(channel)
|
||||
queue.put_nowait(value)
|
||||
|
||||
async def wait_for(self, target: WaitCondition | AnyOfCondition) -> Any:
|
||||
if isinstance(target, ChannelCondition):
|
||||
value = await self._wait_for_channel_values(target.channel, n=target.n)
|
||||
return {
|
||||
"condition": "channel",
|
||||
"channel": target.channel,
|
||||
"value": value,
|
||||
}
|
||||
if isinstance(target, TimerCondition):
|
||||
await asyncio.sleep(target.seconds)
|
||||
return {"condition": "timer", "seconds": target.seconds}
|
||||
if isinstance(target, AnyOfCondition):
|
||||
return await self._wait_for_any_of(target)
|
||||
raise ValueError(f"Unsupported wait condition type: {type(target)!r}")
|
||||
|
||||
async def _wait_for_channel_values(self, channel: str, n: int) -> Any:
|
||||
if n < 1:
|
||||
raise ValueError("wait_for count `n` must be >= 1")
|
||||
queue = self._get_async_channel(channel)
|
||||
if n == 1:
|
||||
return await queue.get()
|
||||
values: list[Any] = []
|
||||
for _ in range(n):
|
||||
values.append(await queue.get())
|
||||
return values
|
||||
|
||||
async def _wait_for_any_of(self, condition: AnyOfCondition) -> Any:
|
||||
if not condition.conditions:
|
||||
raise ValueError("any_of() requires at least one condition")
|
||||
|
||||
tasks = [
|
||||
asyncio.create_task(self.wait_for(inner_condition))
|
||||
for inner_condition in condition.conditions
|
||||
]
|
||||
done, pending = await asyncio.wait(tasks, return_when=asyncio.FIRST_COMPLETED)
|
||||
for task in pending:
|
||||
task.cancel()
|
||||
await asyncio.gather(*pending, return_exceptions=True)
|
||||
first = done.pop()
|
||||
return first.result()
|
||||
|
||||
def _get_async_channel(self, channel: str) -> asyncio.Queue[Any]:
|
||||
if channel not in self._async_channels:
|
||||
raise ValueError(f"Unknown channel `{channel}`")
|
||||
return self._async_channels[channel]
|
||||
|
||||
def _schedule(self, send: Send) -> None:
|
||||
if self._finished:
|
||||
return
|
||||
task: asyncio.Task[list[Send]] = asyncio.create_task(self._execute_send(send))
|
||||
self._tasks.add(task)
|
||||
|
||||
async def _cancel_all_tasks(self) -> None:
|
||||
if not self._tasks:
|
||||
return
|
||||
to_cancel = list(self._tasks)
|
||||
for task in to_cancel:
|
||||
task.cancel()
|
||||
await asyncio.gather(*to_cancel, return_exceptions=True)
|
||||
self._tasks.clear()
|
||||
|
||||
async def _execute_send(self, send: Send) -> list[Send]:
|
||||
node_name = _resolve_target_name(send.node)
|
||||
if node_name not in self._nodes:
|
||||
raise ValueError(f"Unknown node `{node_name}`")
|
||||
node = self._nodes[node_name]
|
||||
|
||||
result = _invoke_node(node, self.context, send.arg)
|
||||
if inspect.isawaitable(result):
|
||||
result = await result
|
||||
|
||||
if isinstance(result, Command):
|
||||
self._apply_update(result.update)
|
||||
next_sends = _normalize_goto(result.goto, default_arg=self._state)
|
||||
else:
|
||||
self._apply_update(result)
|
||||
next_sends = _normalize_result_to_sends(result, default_arg=self._state)
|
||||
|
||||
if node_name == self._finish_point:
|
||||
self._finished = True
|
||||
return []
|
||||
return next_sends
|
||||
|
||||
def _apply_update(self, update: Any) -> None:
|
||||
if update is None:
|
||||
return
|
||||
if isinstance(update, Mapping):
|
||||
if isinstance(self._state, Mapping):
|
||||
# Keep semantics simple: in-place update for mapping-like state.
|
||||
cast(dict[str, Any], self._state).update(update)
|
||||
return
|
||||
if isinstance(update, Sequence) and not isinstance(update, (str, bytes)):
|
||||
pairs = list(update)
|
||||
if all(
|
||||
isinstance(item, tuple) and len(item) == 2 and isinstance(item[0], str)
|
||||
for item in pairs
|
||||
):
|
||||
if isinstance(self._state, Mapping):
|
||||
cast(dict[str, Any], self._state).update(
|
||||
cast(dict[str, Any], pairs)
|
||||
)
|
||||
return
|
||||
|
||||
|
||||
def _normalize_result_to_sends(result: Any, *, default_arg: Any) -> list[Send]:
|
||||
if result is None:
|
||||
return []
|
||||
if isinstance(result, Send):
|
||||
return [result]
|
||||
if callable(result):
|
||||
return [Send(_infer_node_name(result), default_arg)]
|
||||
if isinstance(result, str):
|
||||
return [Send(result, default_arg)]
|
||||
if isinstance(result, Sequence) and not isinstance(result, (str, bytes)):
|
||||
sends: list[Send] = []
|
||||
for item in result:
|
||||
if isinstance(item, Send):
|
||||
sends.append(item)
|
||||
elif callable(item):
|
||||
sends.append(Send(_infer_node_name(item), default_arg))
|
||||
elif isinstance(item, str):
|
||||
sends.append(Send(item, default_arg))
|
||||
return sends
|
||||
return []
|
||||
|
||||
|
||||
def _normalize_goto(goto: Any, *, default_arg: Any) -> list[Send]:
|
||||
if not goto:
|
||||
return []
|
||||
if isinstance(goto, Send):
|
||||
return [goto]
|
||||
if callable(goto):
|
||||
return [Send(_infer_node_name(goto), default_arg)]
|
||||
if isinstance(goto, str):
|
||||
return [Send(goto, default_arg)]
|
||||
if isinstance(goto, Sequence):
|
||||
sends: list[Send] = []
|
||||
for item in goto:
|
||||
if isinstance(item, Send):
|
||||
sends.append(item)
|
||||
elif callable(item):
|
||||
sends.append(Send(_infer_node_name(item), default_arg))
|
||||
elif isinstance(item, str):
|
||||
sends.append(Send(item, default_arg))
|
||||
return sends
|
||||
return []
|
||||
|
||||
|
||||
def channel_condition(channel: str, n: int = 1) -> ChannelCondition:
|
||||
if n < 1:
|
||||
raise ValueError("channel_condition `n` must be >= 1")
|
||||
return ChannelCondition(channel=channel, n=n)
|
||||
|
||||
|
||||
def timer_condition(
|
||||
timeout: float | timedelta | None = None,
|
||||
*,
|
||||
seconds: float | None = None,
|
||||
minutes: float | None = None,
|
||||
) -> TimerCondition:
|
||||
if timeout is not None and (seconds is not None or minutes is not None):
|
||||
raise ValueError(
|
||||
"Provide either `timeout` or named `seconds`/`minutes`, not both"
|
||||
)
|
||||
|
||||
if isinstance(timeout, timedelta):
|
||||
resolved_seconds = timeout.total_seconds()
|
||||
elif isinstance(timeout, (int, float)):
|
||||
resolved_seconds = float(timeout)
|
||||
else:
|
||||
resolved_seconds = 0.0
|
||||
if seconds is not None:
|
||||
resolved_seconds += float(seconds)
|
||||
if minutes is not None:
|
||||
resolved_seconds += float(minutes) * 60.0
|
||||
|
||||
if resolved_seconds <= 0:
|
||||
raise ValueError("timer_condition must be greater than 0 seconds")
|
||||
return TimerCondition(seconds=resolved_seconds)
|
||||
|
||||
|
||||
def any_of(*conditions: WaitCondition) -> AnyOfCondition:
|
||||
if not conditions:
|
||||
raise ValueError("any_of() requires at least one condition")
|
||||
return AnyOfCondition(conditions=tuple(conditions))
|
||||
|
||||
|
||||
def _infer_node_name(node: Callable[..., Any]) -> str:
|
||||
node_name = getattr(node, "__name__", "")
|
||||
if not node_name or node_name == "<lambda>":
|
||||
raise ValueError("Cannot infer node name from anonymous callable")
|
||||
return node_name
|
||||
|
||||
|
||||
def _resolve_target_name(target: Any) -> str:
|
||||
if isinstance(target, str):
|
||||
return target
|
||||
if callable(target):
|
||||
return _infer_node_name(target)
|
||||
raise ValueError(f"Unsupported node target type: {type(target)!r}")
|
||||
|
||||
|
||||
def _invoke_node(node: Callable[..., Any], ctx: Context, state: Any) -> Any:
|
||||
try:
|
||||
params = list(inspect.signature(node).parameters.values())
|
||||
except (TypeError, ValueError):
|
||||
params = []
|
||||
|
||||
if len(params) >= 2:
|
||||
return node(ctx, state)
|
||||
if len(params) == 1:
|
||||
return node(state)
|
||||
return node()
|
||||
@@ -647,24 +647,13 @@ class PregelLoop:
|
||||
# writes so that interrupt() calls re-fire instead of returning
|
||||
# stale values. But if we're actively resuming, keep them —
|
||||
# multi-interrupt scenarios need previously resolved values preserved.
|
||||
if self.is_replaying and (
|
||||
# Time-travel to a subgraph checkpoint: the parent sets
|
||||
# RESUMING=True (it can't distinguish time-travel from resume),
|
||||
# so we check if this subgraph's own ns is in checkpoint_map.
|
||||
# Normally the map only has ancestor entries (_algo.py); the
|
||||
# subgraph's own entry only appears via get_state(subgraphs=True).
|
||||
(
|
||||
self.is_nested
|
||||
and configurable.get(CONFIG_KEY_CHECKPOINT_NS, "")
|
||||
in configurable.get(CONFIG_KEY_CHECKPOINT_MAP, {})
|
||||
)
|
||||
or not (
|
||||
# Outer graph: resume arrives as Command(resume=...)
|
||||
(input_is_command and cast(Command, self.input).resume is not None)
|
||||
# Subgraphs: resume arrives via config flag from parent
|
||||
# (subgraph input is a Send arg, not a Command)
|
||||
or configurable.get(CONFIG_KEY_RESUMING, False)
|
||||
)
|
||||
# We check two conditions because resume signals arrive differently:
|
||||
# - Command(resume=...): the outer graph receives resume via input
|
||||
# - CONFIG_KEY_RESUMING: child subgraphs receive it via config from
|
||||
# the parent (their input is a Send arg, not a Command)
|
||||
if self.is_replaying and not (
|
||||
(input_is_command and cast(Command, self.input).resume is not None)
|
||||
or configurable.get(CONFIG_KEY_RESUMING, False)
|
||||
):
|
||||
self.checkpoint_pending_writes = [
|
||||
w for w in self.checkpoint_pending_writes if w[1] != RESUME
|
||||
@@ -1138,15 +1127,9 @@ class SyncPregelLoop(PregelLoop, AbstractContextManager):
|
||||
def __enter__(self) -> Self:
|
||||
if not self.checkpointer:
|
||||
saved = None
|
||||
elif self.checkpoint_config[CONF].get(CONFIG_KEY_CHECKPOINT_ID):
|
||||
# Explicit checkpoint_id requested — fetch that exact checkpoint.
|
||||
# This covers both normal replay and subgraphs resolved via
|
||||
# checkpoint_map during time-travel.
|
||||
saved = self.checkpointer.get_tuple(self.checkpoint_config)
|
||||
elif replay_state := self.config[CONF].get(CONFIG_KEY_REPLAY_STATE):
|
||||
# Subgraph replay: the parent is replaying and passed us a
|
||||
# replay_state with its checkpoint_id. Look up our checkpoint
|
||||
# from the parent's checkpoint_map instead of fetching latest.
|
||||
elif self.is_nested and (
|
||||
replay_state := self.config[CONF].get(CONFIG_KEY_REPLAY_STATE)
|
||||
):
|
||||
saved = replay_state.get_checkpoint(
|
||||
self.config[CONF].get(CONFIG_KEY_CHECKPOINT_NS, ""),
|
||||
self.checkpointer,
|
||||
@@ -1158,7 +1141,9 @@ class SyncPregelLoop(PregelLoop, AbstractContextManager):
|
||||
self.config[CONF].pop(CONFIG_KEY_RESUMING, None)
|
||||
else:
|
||||
# Normal case: fetch the most recent checkpoint for this
|
||||
# graph/thread. Returns None on first invocation.
|
||||
# graph/thread. If a specific checkpoint_id is in the config,
|
||||
# fetch that exact checkpoint; otherwise fetch the latest one.
|
||||
# Returns None on first invocation (no checkpoints exist yet).
|
||||
saved = self.checkpointer.get_tuple(self.checkpoint_config)
|
||||
|
||||
if saved is None:
|
||||
@@ -1337,15 +1322,9 @@ class AsyncPregelLoop(PregelLoop, AbstractAsyncContextManager):
|
||||
async def __aenter__(self) -> Self:
|
||||
if not self.checkpointer:
|
||||
saved = None
|
||||
elif self.checkpoint_config[CONF].get(CONFIG_KEY_CHECKPOINT_ID):
|
||||
# Explicit checkpoint_id requested — fetch that exact checkpoint.
|
||||
# This covers both normal replay and subgraphs resolved via
|
||||
# checkpoint_map during time-travel.
|
||||
saved = await self.checkpointer.aget_tuple(self.checkpoint_config)
|
||||
elif replay_state := self.config[CONF].get(CONFIG_KEY_REPLAY_STATE):
|
||||
# Subgraph replay: the parent is replaying and passed us a
|
||||
# replay_state with its checkpoint_id. Look up our checkpoint
|
||||
# from the parent's checkpoint_map instead of fetching latest.
|
||||
elif self.is_nested and (
|
||||
replay_state := self.config[CONF].get(CONFIG_KEY_REPLAY_STATE)
|
||||
):
|
||||
saved = await replay_state.aget_checkpoint(
|
||||
self.config[CONF].get(CONFIG_KEY_CHECKPOINT_NS, ""),
|
||||
self.checkpointer,
|
||||
@@ -1357,7 +1336,9 @@ class AsyncPregelLoop(PregelLoop, AbstractAsyncContextManager):
|
||||
self.config[CONF].pop(CONFIG_KEY_RESUMING, None)
|
||||
else:
|
||||
# Normal case: fetch the most recent checkpoint for this
|
||||
# graph/thread. Returns None on first invocation.
|
||||
# graph/thread. If a specific checkpoint_id is in the config,
|
||||
# fetch that exact checkpoint; otherwise fetch the latest one.
|
||||
# Returns None on first invocation (no checkpoints exist yet).
|
||||
saved = await self.checkpointer.aget_tuple(self.checkpoint_config)
|
||||
|
||||
if saved is None:
|
||||
|
||||
@@ -14,11 +14,9 @@ from langgraph._internal._constants import (
|
||||
CONF,
|
||||
CONFIG_KEY_CHECKPOINT_NS,
|
||||
CONFIG_KEY_RESUMING,
|
||||
CONFIG_KEY_RUNTIME,
|
||||
NS_SEP,
|
||||
)
|
||||
from langgraph.errors import GraphBubbleUp, ParentCommand
|
||||
from langgraph.runtime import Runtime
|
||||
from langgraph.types import Command, PregelExecutableTask, RetryPolicy
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
@@ -62,33 +60,10 @@ def run_with_retry(
|
||||
"""Run a task with retries."""
|
||||
retry_policy = task.retry_policy or retry_policy
|
||||
attempts = 0
|
||||
node_first_attempt_time = time.time()
|
||||
config = task.config
|
||||
if configurable is not None:
|
||||
config = patch_configurable(config, configurable)
|
||||
runtime = config.get(CONF, {}).get(CONFIG_KEY_RUNTIME)
|
||||
if isinstance(runtime, Runtime):
|
||||
config = patch_configurable(
|
||||
config,
|
||||
{
|
||||
CONFIG_KEY_RUNTIME: runtime.patch_execution_info(
|
||||
node_first_attempt_time=node_first_attempt_time,
|
||||
)
|
||||
},
|
||||
)
|
||||
while True:
|
||||
runtime = config.get(CONF, {}).get(CONFIG_KEY_RUNTIME)
|
||||
if isinstance(runtime, Runtime):
|
||||
config = patch_configurable(
|
||||
config,
|
||||
{
|
||||
CONFIG_KEY_RUNTIME: runtime.patch_execution_info(
|
||||
# node_attempt is execution count (1-indexed): 1 on first run,
|
||||
# then 2, 3, ... on subsequent retries.
|
||||
node_attempt=attempts + 1,
|
||||
)
|
||||
},
|
||||
)
|
||||
try:
|
||||
# clear any writes from previous attempts
|
||||
task.writes.clear()
|
||||
@@ -127,7 +102,7 @@ def run_with_retry(
|
||||
if not matching_policy:
|
||||
raise
|
||||
|
||||
# attempts tracks failed tries only; it increments after a failure.
|
||||
# increment attempts
|
||||
attempts += 1
|
||||
# check if we should give up
|
||||
if attempts >= matching_policy.max_attempts:
|
||||
@@ -166,38 +141,15 @@ async def arun_with_retry(
|
||||
"""Run a task asynchronously with retries."""
|
||||
retry_policy = task.retry_policy or retry_policy
|
||||
attempts = 0
|
||||
node_first_attempt_time = time.time()
|
||||
config = task.config
|
||||
if configurable is not None:
|
||||
config = patch_configurable(config, configurable)
|
||||
runtime = config.get(CONF, {}).get(CONFIG_KEY_RUNTIME)
|
||||
if isinstance(runtime, Runtime):
|
||||
config = patch_configurable(
|
||||
config,
|
||||
{
|
||||
CONFIG_KEY_RUNTIME: runtime.patch_execution_info(
|
||||
node_first_attempt_time=node_first_attempt_time,
|
||||
)
|
||||
},
|
||||
)
|
||||
if match_cached_writes is not None and task.cache_key is not None:
|
||||
for t in await match_cached_writes():
|
||||
if t is task:
|
||||
# if the task is already cached, return
|
||||
return
|
||||
while True:
|
||||
runtime = config.get(CONF, {}).get(CONFIG_KEY_RUNTIME)
|
||||
if isinstance(runtime, Runtime):
|
||||
config = patch_configurable(
|
||||
config,
|
||||
{
|
||||
CONFIG_KEY_RUNTIME: runtime.patch_execution_info(
|
||||
# node_attempt is execution count (1-indexed): 1 on first run,
|
||||
# then 2, 3, ... on subsequent retries.
|
||||
node_attempt=attempts + 1,
|
||||
)
|
||||
},
|
||||
)
|
||||
try:
|
||||
# clear any writes from previous attempts
|
||||
task.writes.clear()
|
||||
@@ -242,8 +194,7 @@ async def arun_with_retry(
|
||||
if not matching_policy:
|
||||
raise
|
||||
|
||||
# attempts tracks failed tries only; it increments after a failure.
|
||||
# The next execution's node_attempt is derived as attempts + 1.
|
||||
# increment attempts
|
||||
attempts += 1
|
||||
# check if we should give up
|
||||
if attempts >= matching_policy.max_attempts:
|
||||
|
||||
@@ -136,7 +136,7 @@ from langgraph.pregel._validate import validate_graph, validate_keys
|
||||
from langgraph.pregel._write import ChannelWrite, ChannelWriteEntry
|
||||
from langgraph.pregel.debug import get_bolded_text, get_colored_text, tasks_w_writes
|
||||
from langgraph.pregel.protocol import PregelProtocol, StreamChunk, StreamProtocol
|
||||
from langgraph.runtime import DEFAULT_RUNTIME, ExecutionInfo, Runtime
|
||||
from langgraph.runtime import DEFAULT_RUNTIME, Runtime
|
||||
from langgraph.types import (
|
||||
All,
|
||||
CachePolicy,
|
||||
@@ -2456,7 +2456,7 @@ class Pregel(
|
||||
debug: bool | None = None,
|
||||
version: Literal["v2"],
|
||||
**kwargs: Unpack[DeprecatedKwargs],
|
||||
) -> Iterator[StreamPart[StateT, OutputT]]: ...
|
||||
) -> Iterator[StreamPart[OutputT, StateT]]: ...
|
||||
|
||||
@overload
|
||||
def stream(
|
||||
@@ -2648,7 +2648,6 @@ class Pregel(
|
||||
store=store,
|
||||
stream_writer=stream_writer,
|
||||
previous=None,
|
||||
execution_info=ExecutionInfo(),
|
||||
)
|
||||
parent_runtime = config[CONF].get(CONFIG_KEY_RUNTIME, DEFAULT_RUNTIME)
|
||||
runtime = parent_runtime.merge(runtime)
|
||||
@@ -2788,7 +2787,7 @@ class Pregel(
|
||||
debug: bool | None = None,
|
||||
version: Literal["v2"],
|
||||
**kwargs: Unpack[DeprecatedKwargs],
|
||||
) -> AsyncIterator[StreamPart[StateT, OutputT]]: ...
|
||||
) -> AsyncIterator[StreamPart[OutputT, StateT]]: ...
|
||||
|
||||
@overload
|
||||
def astream(
|
||||
@@ -3015,7 +3014,6 @@ class Pregel(
|
||||
store=store,
|
||||
stream_writer=stream_writer,
|
||||
previous=None,
|
||||
execution_info=ExecutionInfo(),
|
||||
)
|
||||
parent_runtime = config[CONF].get(CONFIG_KEY_RUNTIME, DEFAULT_RUNTIME)
|
||||
runtime = parent_runtime.merge(runtime)
|
||||
@@ -3196,7 +3194,7 @@ class Pregel(
|
||||
durability: Durability | None = None,
|
||||
version: Literal["v2"],
|
||||
**kwargs: Any,
|
||||
) -> list[StreamPart[StateT, OutputT]]: ...
|
||||
) -> list[StreamPart[OutputT, StateT]]: ...
|
||||
|
||||
@overload
|
||||
def invoke(
|
||||
@@ -3366,7 +3364,7 @@ class Pregel(
|
||||
durability: Durability | None = None,
|
||||
version: Literal["v2"],
|
||||
**kwargs: Any,
|
||||
) -> list[StreamPart[StateT, OutputT]]: ...
|
||||
) -> list[StreamPart[OutputT, StateT]]: ...
|
||||
|
||||
@overload
|
||||
async def ainvoke(
|
||||
|
||||
@@ -117,7 +117,7 @@ class PregelProtocol(Runnable[InputT, Any], Generic[StateT, ContextT, InputT, Ou
|
||||
interrupt_after: All | Sequence[str] | None = None,
|
||||
subgraphs: bool = False,
|
||||
version: Literal["v2"],
|
||||
) -> Iterator[StreamPart[StateT, OutputT]]: ...
|
||||
) -> Iterator[StreamPart[OutputT, StateT]]: ...
|
||||
|
||||
@overload
|
||||
@abstractmethod
|
||||
@@ -161,7 +161,7 @@ class PregelProtocol(Runnable[InputT, Any], Generic[StateT, ContextT, InputT, Ou
|
||||
interrupt_after: All | Sequence[str] | None = None,
|
||||
subgraphs: bool = False,
|
||||
version: Literal["v2"],
|
||||
) -> AsyncIterator[StreamPart[StateT, OutputT]]: ...
|
||||
) -> AsyncIterator[StreamPart[OutputT, StateT]]: ...
|
||||
|
||||
@overload
|
||||
@abstractmethod
|
||||
|
||||
@@ -31,7 +31,6 @@ from langgraph_sdk.client import (
|
||||
)
|
||||
from langgraph_sdk.schema import (
|
||||
Checkpoint,
|
||||
Context,
|
||||
QueryParamTypes,
|
||||
ThreadState,
|
||||
)
|
||||
@@ -692,7 +691,6 @@ class RemoteGraph(PregelProtocol):
|
||||
input: dict[str, Any] | Any,
|
||||
config: RunnableConfig | None = None,
|
||||
*,
|
||||
context: Context | None = None,
|
||||
stream_mode: StreamMode | list[StreamMode] | None = None,
|
||||
interrupt_before: All | Sequence[str] | None = None,
|
||||
interrupt_after: All | Sequence[str] | None = None,
|
||||
@@ -709,7 +707,6 @@ class RemoteGraph(PregelProtocol):
|
||||
input: dict[str, Any] | Any,
|
||||
config: RunnableConfig | None = None,
|
||||
*,
|
||||
context: Context | None = None,
|
||||
stream_mode: StreamMode | list[StreamMode] | None = None,
|
||||
interrupt_before: All | Sequence[str] | None = None,
|
||||
interrupt_after: All | Sequence[str] | None = None,
|
||||
@@ -725,7 +722,6 @@ class RemoteGraph(PregelProtocol):
|
||||
input: dict[str, Any] | Any,
|
||||
config: RunnableConfig | None = None,
|
||||
*,
|
||||
context: Context | None = None,
|
||||
stream_mode: StreamMode | list[StreamMode] | None = None,
|
||||
interrupt_before: All | Sequence[str] | None = None,
|
||||
interrupt_after: All | Sequence[str] | None = None,
|
||||
@@ -738,7 +734,7 @@ class RemoteGraph(PregelProtocol):
|
||||
"""Create a run and stream the results.
|
||||
|
||||
This method calls `POST /threads/{thread_id}/runs/stream` if a `thread_id`
|
||||
is specified in the `configurable` field of the config or
|
||||
is speciffed in the `configurable` field of the config or
|
||||
`POST /runs/stream` otherwise.
|
||||
|
||||
Args:
|
||||
@@ -773,7 +769,6 @@ class RemoteGraph(PregelProtocol):
|
||||
input=input,
|
||||
command=command,
|
||||
config=sanitized_config,
|
||||
context=context,
|
||||
stream_mode=stream_modes,
|
||||
interrupt_before=interrupt_before,
|
||||
interrupt_after=interrupt_after,
|
||||
@@ -847,7 +842,6 @@ class RemoteGraph(PregelProtocol):
|
||||
input: dict[str, Any] | Any,
|
||||
config: RunnableConfig | None = None,
|
||||
*,
|
||||
context: Context | None = None,
|
||||
stream_mode: StreamMode | list[StreamMode] | None = None,
|
||||
interrupt_before: All | Sequence[str] | None = None,
|
||||
interrupt_after: All | Sequence[str] | None = None,
|
||||
@@ -864,7 +858,6 @@ class RemoteGraph(PregelProtocol):
|
||||
input: dict[str, Any] | Any,
|
||||
config: RunnableConfig | None = None,
|
||||
*,
|
||||
context: Context | None = None,
|
||||
stream_mode: StreamMode | list[StreamMode] | None = None,
|
||||
interrupt_before: All | Sequence[str] | None = None,
|
||||
interrupt_after: All | Sequence[str] | None = None,
|
||||
@@ -880,7 +873,6 @@ class RemoteGraph(PregelProtocol):
|
||||
input: dict[str, Any] | Any,
|
||||
config: RunnableConfig | None = None,
|
||||
*,
|
||||
context: Context | None = None,
|
||||
stream_mode: StreamMode | list[StreamMode] | None = None,
|
||||
interrupt_before: All | Sequence[str] | None = None,
|
||||
interrupt_after: All | Sequence[str] | None = None,
|
||||
@@ -893,7 +885,7 @@ class RemoteGraph(PregelProtocol):
|
||||
"""Create a run and stream the results.
|
||||
|
||||
This method calls `POST /threads/{thread_id}/runs/stream` if a `thread_id`
|
||||
is specified in the `configurable` field of the config or
|
||||
is speciffed in the `configurable` field of the config or
|
||||
`POST /runs/stream` otherwise.
|
||||
|
||||
Args:
|
||||
@@ -928,7 +920,6 @@ class RemoteGraph(PregelProtocol):
|
||||
input=input,
|
||||
command=command,
|
||||
config=sanitized_config,
|
||||
context=context,
|
||||
stream_mode=stream_modes,
|
||||
interrupt_before=interrupt_before,
|
||||
interrupt_after=interrupt_after,
|
||||
@@ -1018,7 +1009,6 @@ class RemoteGraph(PregelProtocol):
|
||||
input: dict[str, Any] | Any,
|
||||
config: RunnableConfig | None = None,
|
||||
*,
|
||||
context: Context | None = None,
|
||||
interrupt_before: All | Sequence[str] | None = None,
|
||||
interrupt_after: All | Sequence[str] | None = None,
|
||||
headers: dict[str, str] | None = None,
|
||||
@@ -1033,7 +1023,6 @@ class RemoteGraph(PregelProtocol):
|
||||
input: dict[str, Any] | Any,
|
||||
config: RunnableConfig | None = None,
|
||||
*,
|
||||
context: Context | None = None,
|
||||
interrupt_before: All | Sequence[str] | None = None,
|
||||
interrupt_after: All | Sequence[str] | None = None,
|
||||
headers: dict[str, str] | None = None,
|
||||
@@ -1047,7 +1036,6 @@ class RemoteGraph(PregelProtocol):
|
||||
input: dict[str, Any] | Any,
|
||||
config: RunnableConfig | None = None,
|
||||
*,
|
||||
context: Context | None = None,
|
||||
interrupt_before: All | Sequence[str] | None = None,
|
||||
interrupt_after: All | Sequence[str] | None = None,
|
||||
headers: dict[str, str] | None = None,
|
||||
@@ -1073,7 +1061,6 @@ class RemoteGraph(PregelProtocol):
|
||||
for chunk in self.stream( # type: ignore[misc, call-overload]
|
||||
input,
|
||||
config=config,
|
||||
context=context,
|
||||
interrupt_before=interrupt_before,
|
||||
interrupt_after=interrupt_after,
|
||||
headers=headers,
|
||||
@@ -1100,7 +1087,6 @@ class RemoteGraph(PregelProtocol):
|
||||
input: dict[str, Any] | Any,
|
||||
config: RunnableConfig | None = None,
|
||||
*,
|
||||
context: Context | None = None,
|
||||
interrupt_before: All | Sequence[str] | None = None,
|
||||
interrupt_after: All | Sequence[str] | None = None,
|
||||
headers: dict[str, str] | None = None,
|
||||
@@ -1115,7 +1101,6 @@ class RemoteGraph(PregelProtocol):
|
||||
input: dict[str, Any] | Any,
|
||||
config: RunnableConfig | None = None,
|
||||
*,
|
||||
context: Context | None = None,
|
||||
interrupt_before: All | Sequence[str] | None = None,
|
||||
interrupt_after: All | Sequence[str] | None = None,
|
||||
headers: dict[str, str] | None = None,
|
||||
@@ -1129,7 +1114,6 @@ class RemoteGraph(PregelProtocol):
|
||||
input: dict[str, Any] | Any,
|
||||
config: RunnableConfig | None = None,
|
||||
*,
|
||||
context: Context | None = None,
|
||||
interrupt_before: All | Sequence[str] | None = None,
|
||||
interrupt_after: All | Sequence[str] | None = None,
|
||||
headers: dict[str, str] | None = None,
|
||||
@@ -1155,7 +1139,6 @@ class RemoteGraph(PregelProtocol):
|
||||
async for chunk in self.astream( # type: ignore[misc, call-overload]
|
||||
input,
|
||||
config=config,
|
||||
context=context,
|
||||
interrupt_before=interrupt_before,
|
||||
interrupt_after=interrupt_after,
|
||||
headers=headers,
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from dataclasses import dataclass, field, replace
|
||||
from typing import Any, Generic, NamedTuple, cast
|
||||
from typing import Any, Generic, cast
|
||||
|
||||
from langgraph.store.base import BaseStore
|
||||
from typing_extensions import TypedDict, Unpack
|
||||
@@ -11,21 +11,7 @@ from langgraph.config import get_config
|
||||
from langgraph.types import _DC_KWARGS, StreamWriter
|
||||
from langgraph.typing import ContextT
|
||||
|
||||
__all__ = ("ExecutionInfo", "Runtime", "get_runtime")
|
||||
|
||||
|
||||
class ExecutionInfo(NamedTuple):
|
||||
"""Read-only execution info/metadata for the execution of current thread/run/node."""
|
||||
|
||||
node_attempt: int = 1
|
||||
"""Current node execution attempt number (1-indexed)."""
|
||||
|
||||
node_first_attempt_time: float | None = None
|
||||
"""Unix timestamp (seconds) for when the first attempt started."""
|
||||
|
||||
def patch(self, **overrides: Any) -> ExecutionInfo:
|
||||
"""Return a new execution info object with selected fields replaced."""
|
||||
return self._replace(**overrides)
|
||||
__all__ = ("Runtime", "get_runtime")
|
||||
|
||||
|
||||
def _no_op_stream_writer(_: Any) -> None: ...
|
||||
@@ -36,7 +22,6 @@ class _RuntimeOverrides(TypedDict, Generic[ContextT], total=False):
|
||||
store: BaseStore | None
|
||||
stream_writer: StreamWriter
|
||||
previous: Any
|
||||
execution_info: ExecutionInfo
|
||||
|
||||
|
||||
@dataclass(**_DC_KWARGS)
|
||||
@@ -44,7 +29,7 @@ class Runtime(Generic[ContextT]):
|
||||
"""Convenience class that bundles run-scoped context and other runtime utilities.
|
||||
|
||||
This class is injected into graph nodes and middleware. It provides access to
|
||||
`context`, `store`, `stream_writer`, `previous`, and `execution_info`.
|
||||
`context`, `store`, `stream_writer`, and `previous`.
|
||||
|
||||
!!! note "Accessing `config`"
|
||||
|
||||
@@ -130,9 +115,6 @@ class Runtime(Generic[ContextT]):
|
||||
Only available with the functional API when a checkpointer is provided.
|
||||
"""
|
||||
|
||||
execution_info: ExecutionInfo = field(default_factory=ExecutionInfo)
|
||||
"""Read-only execution information/metadata for the current node run."""
|
||||
|
||||
def merge(self, other: Runtime[ContextT]) -> Runtime[ContextT]:
|
||||
"""Merge two runtimes together.
|
||||
|
||||
@@ -145,7 +127,6 @@ class Runtime(Generic[ContextT]):
|
||||
if other.stream_writer is not _no_op_stream_writer
|
||||
else self.stream_writer,
|
||||
previous=self.previous if other.previous is None else other.previous,
|
||||
execution_info=other.execution_info,
|
||||
)
|
||||
|
||||
def override(
|
||||
@@ -154,20 +135,12 @@ class Runtime(Generic[ContextT]):
|
||||
"""Replace the runtime with a new runtime with the given overrides."""
|
||||
return replace(self, **overrides)
|
||||
|
||||
def patch_execution_info(self, **overrides: Any) -> Runtime[ContextT]:
|
||||
"""Return a new runtime with selected execution_info fields replaced."""
|
||||
return replace(
|
||||
self,
|
||||
execution_info=self.execution_info.patch(**overrides),
|
||||
)
|
||||
|
||||
|
||||
DEFAULT_RUNTIME = Runtime(
|
||||
context=None,
|
||||
store=None,
|
||||
stream_writer=_no_op_stream_writer,
|
||||
previous=None,
|
||||
execution_info=ExecutionInfo(),
|
||||
)
|
||||
|
||||
|
||||
|
||||
@@ -335,7 +335,7 @@ StreamPart = TypeAliasType(
|
||||
| CheckpointStreamPart[StateT]
|
||||
| TasksStreamPart
|
||||
| DebugStreamPart[StateT],
|
||||
type_params=(StateT, OutputT),
|
||||
type_params=(OutputT, StateT),
|
||||
)
|
||||
"""A discriminated union of all v2 stream part types.
|
||||
|
||||
|
||||
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
|
||||
|
||||
[project]
|
||||
name = "langgraph"
|
||||
version = "1.1.3"
|
||||
version = "1.1.0"
|
||||
description = "Building stateful, multi-actor applications with LLMs"
|
||||
authors = []
|
||||
requires-python = ">=3.10"
|
||||
|
||||
@@ -0,0 +1,219 @@
|
||||
import asyncio
|
||||
from dataclasses import dataclass
|
||||
from typing import Any, Literal
|
||||
|
||||
import pytest
|
||||
from typing_extensions import TypedDict
|
||||
|
||||
from langgraph.advanced_graph import (
|
||||
AdvancedStateGraph,
|
||||
Context,
|
||||
any_of,
|
||||
channel_condition,
|
||||
timer_condition,
|
||||
)
|
||||
from langgraph.constants import END, START
|
||||
from langgraph.graph import StateGraph
|
||||
from langgraph.types import Command, Send
|
||||
|
||||
pytestmark = pytest.mark.anyio
|
||||
|
||||
|
||||
class MainAgentState(TypedDict):
|
||||
input: str
|
||||
output: list[str]
|
||||
done: str | None
|
||||
|
||||
|
||||
class SubAgentState(TypedDict):
|
||||
input: str
|
||||
output: str
|
||||
|
||||
|
||||
@dataclass(frozen=True)
|
||||
class Decision:
|
||||
type: Literal["end", "sub_agent", "tool"]
|
||||
sub_agent: str | None = None
|
||||
tool: str | None = None
|
||||
complete: str | None = None
|
||||
|
||||
|
||||
class MockPlanner:
|
||||
def __init__(self) -> None:
|
||||
self.responses: list[list[Decision]] = []
|
||||
self._idx = 0
|
||||
|
||||
async def ainvoke(self, _: MainAgentState) -> list[Decision]:
|
||||
if self._idx >= len(self.responses):
|
||||
return []
|
||||
response = self.responses[self._idx]
|
||||
self._idx += 1
|
||||
return response
|
||||
|
||||
|
||||
def build_sub_agent() -> Any:
|
||||
# Sub-agent uses the regular/simple StateGraph API.
|
||||
sub_agent = StateGraph(SubAgentState)
|
||||
|
||||
async def research_node(state: SubAgentState) -> dict[str, str]:
|
||||
# Intentionally slower than timer_condition(seconds=1) to validate timer path.
|
||||
await asyncio.sleep(5)
|
||||
return {"output": f"research sub agent completed for: {state['input']}"}
|
||||
|
||||
sub_agent.add_node("research_node", research_node)
|
||||
sub_agent.add_edge(START, "research_node")
|
||||
sub_agent.add_edge("research_node", END)
|
||||
return sub_agent.compile()
|
||||
|
||||
|
||||
def build_main_agent(planner: MockPlanner, sub_agent: Any) -> Any:
|
||||
async def llm_node(state: MainAgentState) -> Command:
|
||||
# Planner decides whether to call a tool, spawn a sub-agent, or finish.
|
||||
decisions = await planner.ainvoke(state)
|
||||
sends: list[Send] = []
|
||||
for decision in decisions:
|
||||
if decision.type == "end":
|
||||
# NOTE: this can be simplified further in the future with a dedicated
|
||||
# complete primitive, instead of routing to a finish node manually.
|
||||
return Command(
|
||||
goto=Send(
|
||||
order_food_node,
|
||||
{
|
||||
"state": state,
|
||||
"complete": decision.complete or "order flow completed",
|
||||
},
|
||||
)
|
||||
)
|
||||
if decision.type == "sub_agent" and decision.sub_agent:
|
||||
sends.append(Send("sub_agent_node", decision.sub_agent))
|
||||
if decision.type == "tool" and decision.tool:
|
||||
sends.append(Send("tool_node", decision.tool))
|
||||
# Keep the main loop responsive: wait for one inbound message and continue.
|
||||
sends.append(Send("wait_node", state))
|
||||
return Command(goto=sends)
|
||||
|
||||
async def wait_node(ctx: Context, state: MainAgentState) -> Command:
|
||||
# Lightweight interrupt: only this node blocks for the next relevant signal.
|
||||
event = await ctx.wait_for(
|
||||
any_of(
|
||||
channel_condition("tool_completion_channel"),
|
||||
channel_condition("subagent_completion_channel"),
|
||||
channel_condition("user_input_channel"),
|
||||
timer_condition(seconds=1),
|
||||
)
|
||||
)
|
||||
if event["condition"] == "channel":
|
||||
channel = event["channel"]
|
||||
payload = event["value"]
|
||||
if channel == "tool_completion_channel":
|
||||
state["output"].append(f"tool: {payload}")
|
||||
elif channel == "subagent_completion_channel":
|
||||
state["output"].append(f"sub_agent: {payload}")
|
||||
elif channel == "user_input_channel":
|
||||
state["output"].append(f"user_input: {payload}")
|
||||
# State changed -> ask planner what to do next.
|
||||
return Command(goto=Send("llm_node", state))
|
||||
else:
|
||||
state["output"].append("timer: no updates yet")
|
||||
# No meaningful state change -> keep waiting without calling planner.
|
||||
return Command(goto=Send("wait_node", state))
|
||||
|
||||
async def tool_node(ctx: Context, tool_input: str) -> None:
|
||||
await asyncio.sleep(0.1)
|
||||
# Fire-and-forget style completion: publish result to inbox and exit.
|
||||
# (i.e., just complete without explicitly going to a next node)
|
||||
ctx.publish_to_channel(
|
||||
"tool_completion_channel",
|
||||
f"tool completed for: {tool_input}",
|
||||
)
|
||||
|
||||
async def sub_agent_node(ctx: Context, sub_agent_input: str) -> None:
|
||||
# Sub-agent remains a regular StateGraph, compiled independently.
|
||||
sub_agent_output = await sub_agent.ainvoke(
|
||||
{"input": sub_agent_input, "output": ""}
|
||||
)
|
||||
# Same pattern as tool node: publish result and complete current node.
|
||||
ctx.publish_to_channel(
|
||||
"subagent_completion_channel",
|
||||
sub_agent_output["output"],
|
||||
)
|
||||
|
||||
async def order_food_node(payload: dict[str, Any]) -> dict[str, Any]:
|
||||
state = payload["state"]
|
||||
complete_message = payload["complete"]
|
||||
return {
|
||||
"done": complete_message,
|
||||
"output": [*state["output"], f"order_food: {complete_message}"],
|
||||
}
|
||||
|
||||
advanced_flow = AdvancedStateGraph(MainAgentState)
|
||||
# Default behavior is an unbounded async channel like Rust channel
|
||||
advanced_flow.add_async_channel("tool_completion_channel", str)
|
||||
advanced_flow.add_async_channel("subagent_completion_channel", str)
|
||||
advanced_flow.add_async_channel("user_input_channel", str)
|
||||
# nodes are the same as in the regular StateGraph API
|
||||
advanced_flow.add_entry_node(llm_node)
|
||||
advanced_flow.add_node(wait_node)
|
||||
advanced_flow.add_node(tool_node)
|
||||
advanced_flow.add_node(sub_agent_node)
|
||||
advanced_flow.add_finish_node(order_food_node)
|
||||
|
||||
return advanced_flow.compile()
|
||||
|
||||
|
||||
async def test_async_sub_graph() -> None:
|
||||
planner = MockPlanner()
|
||||
sub_agent = build_sub_agent()
|
||||
main_agent = build_main_agent(planner, sub_agent)
|
||||
|
||||
planner.responses = [
|
||||
[
|
||||
# First planner pass triggers one slow sub-agent.
|
||||
Decision(type="sub_agent", sub_agent="research lunch options"),
|
||||
Decision(type="tool", tool="slack_tool"),
|
||||
],
|
||||
# After user input.
|
||||
[],
|
||||
# After tool completion.
|
||||
[],
|
||||
# After first sub-agent completion, planner decides to run second research.
|
||||
[Decision(type="sub_agent", sub_agent="find vegetarian fallback")],
|
||||
# After second sub-agent completion, planner decides to end.
|
||||
[Decision(type="end", complete="order submitted")],
|
||||
]
|
||||
|
||||
handler = await main_agent.astart(
|
||||
{"input": "help me get something for lunch", "output": [], "done": None}
|
||||
)
|
||||
|
||||
# External input can be injected while graph execution is in progress.
|
||||
await asyncio.sleep(0.01)
|
||||
await handler.apublish_to_channel("user_input_channel", "No spicy food please")
|
||||
result = await handler.aresult()
|
||||
|
||||
assert result["input"] == "help me get something for lunch"
|
||||
assert result["done"] == "order submitted"
|
||||
|
||||
output = result["output"]
|
||||
assert output.count("timer: no updates yet") >= 3
|
||||
assert "user_input: No spicy food please" in output
|
||||
assert "tool: tool completed for: slack_tool" in output
|
||||
assert (
|
||||
"sub_agent: research sub agent completed for: research lunch options" in output
|
||||
)
|
||||
assert (
|
||||
"sub_agent: research sub agent completed for: find vegetarian fallback" in output
|
||||
)
|
||||
assert output[-1] == "order_food: order submitted"
|
||||
|
||||
first_sub_idx = output.index(
|
||||
"sub_agent: research sub agent completed for: research lunch options"
|
||||
)
|
||||
second_sub_idx = output.index(
|
||||
"sub_agent: research sub agent completed for: find vegetarian fallback"
|
||||
)
|
||||
order_food_idx = output.index("order_food: order submitted")
|
||||
assert first_sub_idx < second_sub_idx < order_food_idx
|
||||
assert planner._idx == len(planner.responses)
|
||||
import json
|
||||
print(json.dumps(result, ensure_ascii=False, indent=2))
|
||||
@@ -1,6 +1,5 @@
|
||||
import re
|
||||
import sys
|
||||
from dataclasses import dataclass
|
||||
from typing import Annotated
|
||||
from unittest.mock import AsyncMock, MagicMock
|
||||
|
||||
@@ -11,7 +10,6 @@ from langchain_core.runnables import RunnableConfig
|
||||
from langchain_core.runnables.graph import Edge as DrawableEdge
|
||||
from langchain_core.runnables.graph import Node as DrawableNode
|
||||
from langgraph_sdk.schema import StreamPart
|
||||
from pydantic import BaseModel
|
||||
from typing_extensions import TypedDict
|
||||
|
||||
from langgraph.errors import GraphInterrupt
|
||||
@@ -910,188 +908,6 @@ async def test_ainvoke():
|
||||
assert result == {"messages": [{"type": "human", "content": "world"}]}
|
||||
|
||||
|
||||
def test_stream_context():
|
||||
"""Test that context is passed through to the SDK client in stream."""
|
||||
mock_sync_client = MagicMock()
|
||||
mock_sync_client.runs.stream.return_value = [
|
||||
StreamPart(event="values", data={"chunk": "data1"}),
|
||||
]
|
||||
|
||||
remote_pregel = RemoteGraph(
|
||||
"test_graph_id",
|
||||
sync_client=mock_sync_client,
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "thread_1"}}
|
||||
context = {"model_name": "anthropic", "user_id": "123"}
|
||||
stream_parts = list(
|
||||
remote_pregel.stream(
|
||||
{"input": "data"},
|
||||
config,
|
||||
context=context,
|
||||
stream_mode="values",
|
||||
)
|
||||
)
|
||||
|
||||
assert stream_parts == [{"chunk": "data1"}]
|
||||
_, kwargs = mock_sync_client.runs.stream.call_args
|
||||
assert kwargs["context"] == {"model_name": "anthropic", "user_id": "123"}
|
||||
|
||||
|
||||
def test_stream_context_none():
|
||||
"""Test that context defaults to None when not provided."""
|
||||
mock_sync_client = MagicMock()
|
||||
mock_sync_client.runs.stream.return_value = [
|
||||
StreamPart(event="values", data={"chunk": "data1"}),
|
||||
]
|
||||
|
||||
remote_pregel = RemoteGraph(
|
||||
"test_graph_id",
|
||||
sync_client=mock_sync_client,
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "thread_1"}}
|
||||
list(remote_pregel.stream({"input": "data"}, config, stream_mode="values"))
|
||||
|
||||
_, kwargs = mock_sync_client.runs.stream.call_args
|
||||
assert kwargs["context"] is None
|
||||
|
||||
|
||||
@pytest.mark.anyio
|
||||
async def test_astream_context():
|
||||
"""Test that context is passed through to the SDK client in astream."""
|
||||
mock_async_client = MagicMock()
|
||||
async_iter = MagicMock()
|
||||
async_iter.__aiter__.return_value = [
|
||||
StreamPart(event="values", data={"chunk": "data1"}),
|
||||
]
|
||||
mock_async_client.runs.stream.return_value = async_iter
|
||||
|
||||
remote_pregel = RemoteGraph(
|
||||
"test_graph_id",
|
||||
client=mock_async_client,
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "thread_1"}}
|
||||
context = {"model_name": "anthropic"}
|
||||
chunks = []
|
||||
async for chunk in remote_pregel.astream(
|
||||
{"input": "data"},
|
||||
config,
|
||||
context=context,
|
||||
stream_mode="values",
|
||||
):
|
||||
chunks.append(chunk)
|
||||
|
||||
assert chunks == [{"chunk": "data1"}]
|
||||
_, kwargs = mock_async_client.runs.stream.call_args
|
||||
assert kwargs["context"] == {"model_name": "anthropic"}
|
||||
|
||||
|
||||
def test_invoke_context():
|
||||
"""Test that context is passed through to the SDK client in invoke."""
|
||||
mock_sync_client = MagicMock()
|
||||
mock_sync_client.runs.stream.return_value = [
|
||||
StreamPart(event="values", data={"result": "done"}),
|
||||
]
|
||||
|
||||
remote_pregel = RemoteGraph(
|
||||
"test_graph_id",
|
||||
sync_client=mock_sync_client,
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "thread_1"}}
|
||||
context = {"model_name": "openai"}
|
||||
result = remote_pregel.invoke({"input": "data"}, config, context=context)
|
||||
|
||||
assert result == {"result": "done"}
|
||||
_, kwargs = mock_sync_client.runs.stream.call_args
|
||||
assert kwargs["context"] == {"model_name": "openai"}
|
||||
|
||||
|
||||
@pytest.mark.anyio
|
||||
async def test_ainvoke_context():
|
||||
"""Test that context is passed through to the SDK client in ainvoke."""
|
||||
mock_async_client = MagicMock()
|
||||
async_iter = MagicMock()
|
||||
async_iter.__aiter__.return_value = [
|
||||
StreamPart(event="values", data={"result": "done"}),
|
||||
]
|
||||
mock_async_client.runs.stream.return_value = async_iter
|
||||
|
||||
remote_pregel = RemoteGraph(
|
||||
"test_graph_id",
|
||||
client=mock_async_client,
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "thread_1"}}
|
||||
context = {"user_id": "456"}
|
||||
result = await remote_pregel.ainvoke({"input": "data"}, config, context=context)
|
||||
|
||||
assert result == {"result": "done"}
|
||||
_, kwargs = mock_async_client.runs.stream.call_args
|
||||
assert kwargs["context"] == {"user_id": "456"}
|
||||
|
||||
|
||||
def test_stream_context_dataclass():
|
||||
"""Test that a dataclass context is passed through to the SDK client."""
|
||||
|
||||
@dataclass
|
||||
class MyContext:
|
||||
model_name: str
|
||||
user_id: str
|
||||
|
||||
mock_sync_client = MagicMock()
|
||||
mock_sync_client.runs.stream.return_value = [
|
||||
StreamPart(event="values", data={"chunk": "data1"}),
|
||||
]
|
||||
|
||||
remote_pregel = RemoteGraph(
|
||||
"test_graph_id",
|
||||
sync_client=mock_sync_client,
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "thread_1"}}
|
||||
ctx = MyContext(model_name="anthropic", user_id="123")
|
||||
list(
|
||||
remote_pregel.stream(
|
||||
{"input": "data"}, config, context=ctx, stream_mode="values"
|
||||
)
|
||||
)
|
||||
|
||||
_, kwargs = mock_sync_client.runs.stream.call_args
|
||||
assert kwargs["context"] == ctx
|
||||
|
||||
|
||||
def test_stream_context_base_model():
|
||||
"""Test that a BaseModel context is passed through to the SDK client."""
|
||||
|
||||
class MyContext(BaseModel):
|
||||
model_name: str
|
||||
user_id: str
|
||||
|
||||
mock_sync_client = MagicMock()
|
||||
mock_sync_client.runs.stream.return_value = [
|
||||
StreamPart(event="values", data={"chunk": "data1"}),
|
||||
]
|
||||
|
||||
remote_pregel = RemoteGraph(
|
||||
"test_graph_id",
|
||||
sync_client=mock_sync_client,
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "thread_1"}}
|
||||
ctx = MyContext(model_name="anthropic", user_id="123")
|
||||
list(
|
||||
remote_pregel.stream(
|
||||
{"input": "data"}, config, context=ctx, stream_mode="values"
|
||||
)
|
||||
)
|
||||
|
||||
_, kwargs = mock_sync_client.runs.stream.call_args
|
||||
assert kwargs["context"] == ctx
|
||||
|
||||
|
||||
@pytest.mark.skip(
|
||||
"Unskip this test to manually test the LangSmith Deployment integration"
|
||||
)
|
||||
|
||||
@@ -5,7 +5,6 @@ from typing_extensions import TypedDict
|
||||
|
||||
from langgraph.graph import START, StateGraph
|
||||
from langgraph.pregel._retry import _checkpoint_ns_for_parent_command, _should_retry_on
|
||||
from langgraph.runtime import Runtime
|
||||
from langgraph.types import RetryPolicy
|
||||
|
||||
|
||||
@@ -169,15 +168,10 @@ def test_graph_with_single_retry_policy():
|
||||
foo: str
|
||||
|
||||
attempt_count = 0
|
||||
attempt_numbers: list[int] = []
|
||||
first_attempt_times: list[float | None] = []
|
||||
|
||||
def failing_node(state: State, runtime: Runtime):
|
||||
def failing_node(state: State):
|
||||
nonlocal attempt_count
|
||||
attempt_count += 1
|
||||
assert runtime.execution_info.node_attempt == attempt_count
|
||||
attempt_numbers.append(runtime.execution_info.node_attempt)
|
||||
first_attempt_times.append(runtime.execution_info.node_first_attempt_time)
|
||||
if attempt_count < 3: # Fail the first two attempts
|
||||
raise ValueError("Intentional failure")
|
||||
return {"foo": "success"}
|
||||
@@ -209,11 +203,6 @@ def test_graph_with_single_retry_policy():
|
||||
|
||||
# Verify retry behavior
|
||||
assert attempt_count == 3 # The node should have been tried 3 times
|
||||
assert attempt_numbers == [1, 2, 3]
|
||||
assert len(first_attempt_times) == 3
|
||||
assert first_attempt_times[0] is not None
|
||||
assert first_attempt_times[1] == first_attempt_times[0]
|
||||
assert first_attempt_times[2] == first_attempt_times[0]
|
||||
assert result["foo"] == "other_node" # Final result should be from other_node
|
||||
|
||||
# Verify the sleep intervals
|
||||
@@ -221,30 +210,6 @@ def test_graph_with_single_retry_policy():
|
||||
assert call_args_list == [0.01, 0.02]
|
||||
|
||||
|
||||
def test_runtime_execution_info_defaults_without_retry():
|
||||
"""Test execution_info defaults when no retry and no config are provided."""
|
||||
|
||||
class State(TypedDict):
|
||||
foo: str
|
||||
|
||||
captured = {}
|
||||
|
||||
def node(state: State, runtime: Runtime):
|
||||
captured["node_attempt"] = runtime.execution_info.node_attempt
|
||||
captured["node_first_attempt_time"] = (
|
||||
runtime.execution_info.node_first_attempt_time
|
||||
)
|
||||
return {"foo": "ok"}
|
||||
|
||||
graph = StateGraph(State).add_node("node", node).add_edge(START, "node").compile()
|
||||
|
||||
result = graph.invoke({"foo": ""})
|
||||
|
||||
assert result["foo"] == "ok"
|
||||
assert captured["node_attempt"] == 1
|
||||
assert isinstance(captured["node_first_attempt_time"], float)
|
||||
|
||||
|
||||
def test_graph_with_jitter_retry_policy():
|
||||
"""Test a graph with a RetryPolicy that uses jitter."""
|
||||
|
||||
|
||||
@@ -1129,7 +1129,7 @@ _OutputT = TypeVar("_OutputT")
|
||||
_StateT = TypeVar("_StateT")
|
||||
|
||||
|
||||
def _check_type_narrowing(part: StreamPart[_StateT, _OutputT]) -> None:
|
||||
def _check_type_narrowing(part: StreamPart[_OutputT, _StateT]) -> None:
|
||||
"""Compile-time type narrowing checks — never called at runtime."""
|
||||
if part["type"] == "values":
|
||||
assert_type(part, ValuesStreamPart[_OutputT])
|
||||
|
||||
@@ -1116,631 +1116,6 @@ def test_subgraph_replay_from_subgraph_checkpoint(
|
||||
assert "post" in final_result["value"]
|
||||
|
||||
|
||||
def test_subgraph_time_travel_to_first_interrupt(
|
||||
sync_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
"""Time travel to a subgraph checkpoint at the FIRST interrupt.
|
||||
|
||||
Architecture:
|
||||
Parent: START --> executor (subgraph, checkpointer=True) --> END
|
||||
Executor: START --> step_a --> ask_1 (interrupt) --> ask_2 (interrupt) --> END
|
||||
|
||||
Flow: run through both interrupts, then time travel back to the subgraph
|
||||
checkpoint captured at the first interrupt. ask_1 should re-fire,
|
||||
step_a should NOT re-run. Then resume through both interrupts with new answers.
|
||||
"""
|
||||
|
||||
called: list[str] = []
|
||||
|
||||
def step_a(state: State) -> State:
|
||||
called.append("step_a")
|
||||
return {"value": ["step_a_done"]}
|
||||
|
||||
def ask_1(state: State) -> State:
|
||||
called.append("ask_1")
|
||||
answer = interrupt("Question 1?")
|
||||
return {"value": [f"ask_1:{answer}"]}
|
||||
|
||||
def ask_2(state: State) -> State:
|
||||
called.append("ask_2")
|
||||
answer = interrupt("Question 2?")
|
||||
return {"value": [f"ask_2:{answer}"]}
|
||||
|
||||
executor = (
|
||||
StateGraph(State)
|
||||
.add_node("step_a", step_a)
|
||||
.add_node("ask_1", ask_1)
|
||||
.add_node("ask_2", ask_2)
|
||||
.add_edge(START, "step_a")
|
||||
.add_edge("step_a", "ask_1")
|
||||
.add_edge("ask_1", "ask_2")
|
||||
.add_edge("ask_2", "__end__")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
graph = (
|
||||
StateGraph(State)
|
||||
.add_node("executor", executor)
|
||||
.add_edge(START, "executor")
|
||||
.compile(checkpointer=sync_checkpointer)
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "1"}}
|
||||
|
||||
# Run until first interrupt (ask_1)
|
||||
result = graph.invoke({"value": []}, config)
|
||||
assert "__interrupt__" in result
|
||||
assert result["__interrupt__"][0].value == "Question 1?"
|
||||
|
||||
# Capture subgraph state at the first interrupt
|
||||
parent_state = graph.get_state(config, subgraphs=True)
|
||||
sub_config_at_first = parent_state.tasks[0].state.config
|
||||
|
||||
# Resume first interrupt
|
||||
result = graph.invoke(Command(resume="answer_1"), config)
|
||||
assert result["__interrupt__"][0].value == "Question 2?"
|
||||
|
||||
# Resume second interrupt to complete
|
||||
result = graph.invoke(Command(resume="answer_2"), config)
|
||||
assert "__interrupt__" not in result
|
||||
|
||||
# --- Scenario 1: Replay from subgraph checkpoint at 1st interrupt ---
|
||||
called.clear()
|
||||
replay_result = graph.invoke(None, sub_config_at_first)
|
||||
assert "__interrupt__" in replay_result
|
||||
assert replay_result["__interrupt__"][0].value == "Question 1?"
|
||||
# step_a should NOT re-run — it was before this checkpoint
|
||||
assert "step_a" not in called
|
||||
# ask_1 re-fires because the interrupt replays
|
||||
assert "ask_1" in called
|
||||
|
||||
# --- Scenario 2: Fork from subgraph checkpoint at 1st interrupt ---
|
||||
called.clear()
|
||||
fork_config = graph.update_state(sub_config_at_first, {"value": ["forked"]})
|
||||
fork_result = graph.invoke(None, fork_config)
|
||||
assert "__interrupt__" in fork_result
|
||||
assert fork_result["__interrupt__"][0].value == "Question 1?"
|
||||
assert "step_a" not in called
|
||||
assert "ask_1" in called
|
||||
|
||||
|
||||
def test_subgraph_time_travel_to_second_interrupt(
|
||||
sync_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
"""Time travel to a subgraph checkpoint at the SECOND interrupt.
|
||||
|
||||
Architecture:
|
||||
Parent: START --> executor (subgraph, checkpointer=True) --> END
|
||||
Executor: START --> step_a --> ask_1 (interrupt) --> ask_2 (interrupt) --> END
|
||||
|
||||
Flow: run through both interrupts resuming each, then time travel back to the
|
||||
subgraph checkpoint at the second interrupt. Only ask_2 should re-fire.
|
||||
Then resume with a new answer and verify state.
|
||||
"""
|
||||
|
||||
called: list[str] = []
|
||||
|
||||
def step_a(state: State) -> State:
|
||||
called.append("step_a")
|
||||
return {"value": ["step_a_done"]}
|
||||
|
||||
def ask_1(state: State) -> State:
|
||||
called.append("ask_1")
|
||||
answer = interrupt("Question 1?")
|
||||
return {"value": [f"ask_1:{answer}"]}
|
||||
|
||||
def ask_2(state: State) -> State:
|
||||
called.append("ask_2")
|
||||
answer = interrupt("Question 2?")
|
||||
return {"value": [f"ask_2:{answer}"]}
|
||||
|
||||
executor = (
|
||||
StateGraph(State)
|
||||
.add_node("step_a", step_a)
|
||||
.add_node("ask_1", ask_1)
|
||||
.add_node("ask_2", ask_2)
|
||||
.add_edge(START, "step_a")
|
||||
.add_edge("step_a", "ask_1")
|
||||
.add_edge("ask_1", "ask_2")
|
||||
.add_edge("ask_2", "__end__")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
graph = (
|
||||
StateGraph(State)
|
||||
.add_node("executor", executor)
|
||||
.add_edge(START, "executor")
|
||||
.compile(checkpointer=sync_checkpointer)
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "1"}}
|
||||
|
||||
# Run until first interrupt (ask_1)
|
||||
result = graph.invoke({"value": []}, config)
|
||||
assert result["__interrupt__"][0].value == "Question 1?"
|
||||
|
||||
# Resume first interrupt
|
||||
result = graph.invoke(Command(resume="answer_1"), config)
|
||||
assert result["__interrupt__"][0].value == "Question 2?"
|
||||
|
||||
# Capture subgraph state at the second interrupt
|
||||
parent_state = graph.get_state(config, subgraphs=True)
|
||||
sub_config = parent_state.tasks[0].state.config
|
||||
|
||||
# Resume second interrupt to complete the graph
|
||||
result = graph.invoke(Command(resume="answer_2"), config)
|
||||
assert "__interrupt__" not in result
|
||||
|
||||
# --- Scenario 1: Replay from subgraph checkpoint at 2nd interrupt ---
|
||||
called.clear()
|
||||
replay_result = graph.invoke(None, sub_config)
|
||||
assert "__interrupt__" in replay_result
|
||||
assert replay_result["__interrupt__"][0].value == "Question 2?"
|
||||
# step_a and ask_1 should NOT re-run — they were before this checkpoint
|
||||
assert "step_a" not in called
|
||||
assert "ask_1" not in called
|
||||
|
||||
# --- Scenario 2: Fork from subgraph checkpoint at 2nd interrupt ---
|
||||
called.clear()
|
||||
fork_config = graph.update_state(sub_config, {"value": ["forked"]})
|
||||
fork_result = graph.invoke(None, fork_config)
|
||||
assert "__interrupt__" in fork_result
|
||||
assert fork_result["__interrupt__"][0].value == "Question 2?"
|
||||
assert "step_a" not in called
|
||||
assert "ask_1" not in called
|
||||
|
||||
|
||||
def test_subgraph_time_travel_after_completion(
|
||||
sync_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
"""Time travel to a subgraph checkpoint AFTER both interrupts are resolved.
|
||||
|
||||
Architecture:
|
||||
Parent: START --> executor (subgraph, checkpointer=True) --> END
|
||||
Executor: START --> step_a --> ask_1 (interrupt) --> ask_2 (interrupt) --> END
|
||||
|
||||
After completing the full flow, capture the subgraph's final state checkpoint
|
||||
and replay from it — should be a no-op (no nodes re-run).
|
||||
"""
|
||||
|
||||
called: list[str] = []
|
||||
|
||||
def step_a(state: State) -> State:
|
||||
called.append("step_a")
|
||||
return {"value": ["step_a_done"]}
|
||||
|
||||
def ask_1(state: State) -> State:
|
||||
called.append("ask_1")
|
||||
answer = interrupt("Question 1?")
|
||||
return {"value": [f"ask_1:{answer}"]}
|
||||
|
||||
def ask_2(state: State) -> State:
|
||||
called.append("ask_2")
|
||||
answer = interrupt("Question 2?")
|
||||
return {"value": [f"ask_2:{answer}"]}
|
||||
|
||||
executor = (
|
||||
StateGraph(State)
|
||||
.add_node("step_a", step_a)
|
||||
.add_node("ask_1", ask_1)
|
||||
.add_node("ask_2", ask_2)
|
||||
.add_edge(START, "step_a")
|
||||
.add_edge("step_a", "ask_1")
|
||||
.add_edge("ask_1", "ask_2")
|
||||
.add_edge("ask_2", "__end__")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
graph = (
|
||||
StateGraph(State)
|
||||
.add_node("executor", executor)
|
||||
.add_edge(START, "executor")
|
||||
.compile(checkpointer=sync_checkpointer)
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "1"}}
|
||||
|
||||
# Run through both interrupts
|
||||
graph.invoke({"value": []}, config)
|
||||
graph.invoke(Command(resume="answer_1"), config)
|
||||
|
||||
# Before resuming 2nd interrupt, get state history to find the
|
||||
# subgraph checkpoint that will exist after ask_2 completes
|
||||
graph.invoke(Command(resume="answer_2"), config)
|
||||
|
||||
# Get the final parent state — no pending tasks
|
||||
final_state = graph.get_state(config)
|
||||
assert len(final_state.tasks) == 0
|
||||
|
||||
# Replay from the final parent checkpoint — should be a no-op
|
||||
called.clear()
|
||||
replay_result = graph.invoke(None, final_state.config)
|
||||
assert "__interrupt__" not in replay_result
|
||||
assert "step_a" not in called
|
||||
assert "ask_1" not in called
|
||||
assert "ask_2" not in called
|
||||
# All values should be present
|
||||
assert "step_a_done" in replay_result["value"]
|
||||
assert "ask_1:answer_1" in replay_result["value"]
|
||||
assert "ask_2:answer_2" in replay_result["value"]
|
||||
|
||||
|
||||
def test_3_levels_deep_time_travel_to_first_interrupt(
|
||||
sync_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
"""Time travel to the innermost subgraph checkpoint at the FIRST interrupt.
|
||||
|
||||
Architecture:
|
||||
Parent: START --> outer (subgraph, checkpointer=True) --> END
|
||||
Outer: START --> inner (subgraph, checkpointer=True) --> END
|
||||
Inner: START --> step_a --> ask_1 (interrupt) --> ask_2 (interrupt) --> END
|
||||
"""
|
||||
|
||||
called: list[str] = []
|
||||
|
||||
def step_a(state: State) -> State:
|
||||
called.append("step_a")
|
||||
return {"value": ["step_a_done"]}
|
||||
|
||||
def ask_1(state: State) -> State:
|
||||
called.append("ask_1")
|
||||
answer = interrupt("Question 1?")
|
||||
return {"value": [f"ask_1:{answer}"]}
|
||||
|
||||
def ask_2(state: State) -> State:
|
||||
called.append("ask_2")
|
||||
answer = interrupt("Question 2?")
|
||||
return {"value": [f"ask_2:{answer}"]}
|
||||
|
||||
inner = (
|
||||
StateGraph(State)
|
||||
.add_node("step_a", step_a)
|
||||
.add_node("ask_1", ask_1)
|
||||
.add_node("ask_2", ask_2)
|
||||
.add_edge(START, "step_a")
|
||||
.add_edge("step_a", "ask_1")
|
||||
.add_edge("ask_1", "ask_2")
|
||||
.add_edge("ask_2", "__end__")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
middle = (
|
||||
StateGraph(State)
|
||||
.add_node("inner", inner)
|
||||
.add_edge(START, "inner")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
graph = (
|
||||
StateGraph(State)
|
||||
.add_node("outer", middle)
|
||||
.add_edge(START, "outer")
|
||||
.compile(checkpointer=sync_checkpointer)
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "1"}}
|
||||
|
||||
# Run until first interrupt
|
||||
result = graph.invoke({"value": []}, config)
|
||||
assert result["__interrupt__"][0].value == "Question 1?"
|
||||
|
||||
# Capture innermost subgraph state at the first interrupt
|
||||
parent_state = graph.get_state(config, subgraphs=True)
|
||||
mid_state = parent_state.tasks[0].state
|
||||
inner_config = mid_state.tasks[0].state.config
|
||||
|
||||
# Resume through both interrupts to complete
|
||||
graph.invoke(Command(resume="answer_1"), config)
|
||||
graph.invoke(Command(resume="answer_2"), config)
|
||||
|
||||
# --- Scenario 1: Replay from innermost checkpoint at 1st interrupt ---
|
||||
called.clear()
|
||||
replay_result = graph.invoke(None, inner_config)
|
||||
assert "__interrupt__" in replay_result
|
||||
assert replay_result["__interrupt__"][0].value == "Question 1?"
|
||||
assert "step_a" not in called
|
||||
assert "ask_1" in called
|
||||
|
||||
# --- Scenario 2: Fork from innermost checkpoint at 1st interrupt ---
|
||||
called.clear()
|
||||
fork_config = graph.update_state(inner_config, {"value": ["forked"]})
|
||||
fork_result = graph.invoke(None, fork_config)
|
||||
assert "__interrupt__" in fork_result
|
||||
assert fork_result["__interrupt__"][0].value == "Question 1?"
|
||||
assert "step_a" not in called
|
||||
assert "ask_1" in called
|
||||
|
||||
|
||||
def test_3_levels_deep_time_travel_to_second_interrupt(
|
||||
sync_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
"""Time travel to the innermost subgraph checkpoint at the SECOND interrupt.
|
||||
|
||||
Architecture:
|
||||
Parent: START --> outer (subgraph, checkpointer=True) --> END
|
||||
Outer: START --> inner (subgraph, checkpointer=True) --> END
|
||||
Inner: START --> step_a --> ask_1 (interrupt) --> ask_2 (interrupt) --> END
|
||||
"""
|
||||
|
||||
called: list[str] = []
|
||||
|
||||
def step_a(state: State) -> State:
|
||||
called.append("step_a")
|
||||
return {"value": ["step_a_done"]}
|
||||
|
||||
def ask_1(state: State) -> State:
|
||||
called.append("ask_1")
|
||||
answer = interrupt("Question 1?")
|
||||
return {"value": [f"ask_1:{answer}"]}
|
||||
|
||||
def ask_2(state: State) -> State:
|
||||
called.append("ask_2")
|
||||
answer = interrupt("Question 2?")
|
||||
return {"value": [f"ask_2:{answer}"]}
|
||||
|
||||
inner = (
|
||||
StateGraph(State)
|
||||
.add_node("step_a", step_a)
|
||||
.add_node("ask_1", ask_1)
|
||||
.add_node("ask_2", ask_2)
|
||||
.add_edge(START, "step_a")
|
||||
.add_edge("step_a", "ask_1")
|
||||
.add_edge("ask_1", "ask_2")
|
||||
.add_edge("ask_2", "__end__")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
middle = (
|
||||
StateGraph(State)
|
||||
.add_node("inner", inner)
|
||||
.add_edge(START, "inner")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
graph = (
|
||||
StateGraph(State)
|
||||
.add_node("outer", middle)
|
||||
.add_edge(START, "outer")
|
||||
.compile(checkpointer=sync_checkpointer)
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "1"}}
|
||||
|
||||
# Run until first interrupt
|
||||
graph.invoke({"value": []}, config)
|
||||
|
||||
# Resume first interrupt
|
||||
result = graph.invoke(Command(resume="answer_1"), config)
|
||||
assert result["__interrupt__"][0].value == "Question 2?"
|
||||
|
||||
# Capture innermost subgraph state at the second interrupt
|
||||
parent_state = graph.get_state(config, subgraphs=True)
|
||||
mid_state = parent_state.tasks[0].state
|
||||
inner_config = mid_state.tasks[0].state.config
|
||||
|
||||
# Resume second interrupt to complete
|
||||
graph.invoke(Command(resume="answer_2"), config)
|
||||
|
||||
# --- Scenario 1: Replay from innermost checkpoint at 2nd interrupt ---
|
||||
called.clear()
|
||||
replay_result = graph.invoke(None, inner_config)
|
||||
assert "__interrupt__" in replay_result
|
||||
assert replay_result["__interrupt__"][0].value == "Question 2?"
|
||||
assert "step_a" not in called
|
||||
assert "ask_1" not in called
|
||||
|
||||
# --- Scenario 2: Fork from innermost checkpoint at 2nd interrupt ---
|
||||
called.clear()
|
||||
fork_config = graph.update_state(inner_config, {"value": ["forked"]})
|
||||
fork_result = graph.invoke(None, fork_config)
|
||||
assert "__interrupt__" in fork_result
|
||||
assert fork_result["__interrupt__"][0].value == "Question 2?"
|
||||
assert "step_a" not in called
|
||||
assert "ask_1" not in called
|
||||
|
||||
|
||||
def test_3_levels_deep_time_travel_to_middle_subgraph(
|
||||
sync_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
"""Time travel to the MIDDLE-level subgraph checkpoint (not innermost).
|
||||
|
||||
Architecture:
|
||||
Parent: START --> outer (subgraph, checkpointer=True) --> END
|
||||
Outer: START --> inner (subgraph, checkpointer=True) --> END
|
||||
Inner: START --> step_a --> ask_1 (interrupt) --> ask_2 (interrupt) --> END
|
||||
|
||||
After completing the full flow, time travel back to the middle subgraph's
|
||||
checkpoint at the second interrupt. The middle subgraph should replay the
|
||||
inner subgraph from the correct point.
|
||||
"""
|
||||
|
||||
called: list[str] = []
|
||||
|
||||
def step_a(state: State) -> State:
|
||||
called.append("step_a")
|
||||
return {"value": ["step_a_done"]}
|
||||
|
||||
def ask_1(state: State) -> State:
|
||||
called.append("ask_1")
|
||||
answer = interrupt("Question 1?")
|
||||
return {"value": [f"ask_1:{answer}"]}
|
||||
|
||||
def ask_2(state: State) -> State:
|
||||
called.append("ask_2")
|
||||
answer = interrupt("Question 2?")
|
||||
return {"value": [f"ask_2:{answer}"]}
|
||||
|
||||
inner = (
|
||||
StateGraph(State)
|
||||
.add_node("step_a", step_a)
|
||||
.add_node("ask_1", ask_1)
|
||||
.add_node("ask_2", ask_2)
|
||||
.add_edge(START, "step_a")
|
||||
.add_edge("step_a", "ask_1")
|
||||
.add_edge("ask_1", "ask_2")
|
||||
.add_edge("ask_2", "__end__")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
middle = (
|
||||
StateGraph(State)
|
||||
.add_node("inner", inner)
|
||||
.add_edge(START, "inner")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
graph = (
|
||||
StateGraph(State)
|
||||
.add_node("outer", middle)
|
||||
.add_edge(START, "outer")
|
||||
.compile(checkpointer=sync_checkpointer)
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "1"}}
|
||||
|
||||
# Run until first interrupt
|
||||
graph.invoke({"value": []}, config)
|
||||
|
||||
# Resume first, capture middle config at second interrupt
|
||||
graph.invoke(Command(resume="answer_1"), config)
|
||||
parent_state = graph.get_state(config, subgraphs=True)
|
||||
mid_config = parent_state.tasks[0].state.config
|
||||
|
||||
# Resume second to complete
|
||||
graph.invoke(Command(resume="answer_2"), config)
|
||||
|
||||
# --- Scenario 1: Replay from middle-level subgraph checkpoint ---
|
||||
# The middle subgraph's checkpoint knows about the inner subgraph's state
|
||||
# via checkpoint_map, so the inner replays from the correct point.
|
||||
called.clear()
|
||||
replay_result = graph.invoke(None, mid_config)
|
||||
assert "__interrupt__" in replay_result
|
||||
|
||||
# --- Scenario 2: Fork from middle-level subgraph checkpoint ---
|
||||
called.clear()
|
||||
fork_config = graph.update_state(mid_config, {"value": ["forked"]})
|
||||
fork_result = graph.invoke(None, fork_config)
|
||||
assert "__interrupt__" in fork_result
|
||||
|
||||
|
||||
def test_3_levels_deep_middle_has_interrupts(
|
||||
sync_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
"""Time travel when the MIDDLE subgraph itself has interrupts.
|
||||
|
||||
Architecture:
|
||||
Parent: START --> outer (subgraph, checkpointer=True) --> END
|
||||
Outer: START --> pre (interrupt) --> inner (subgraph, checkpointer=True) --> END
|
||||
Inner: START --> step_a --> ask_1 (interrupt) --> END
|
||||
|
||||
Flow: run through both interrupts (pre then ask_1), then time travel back to
|
||||
the middle subgraph checkpoint at each interrupt point.
|
||||
"""
|
||||
|
||||
called: list[str] = []
|
||||
|
||||
def pre(state: State) -> State:
|
||||
called.append("pre")
|
||||
answer = interrupt("Pre-question?")
|
||||
return {"value": [f"pre:{answer}"]}
|
||||
|
||||
def step_a(state: State) -> State:
|
||||
called.append("step_a")
|
||||
return {"value": ["step_a_done"]}
|
||||
|
||||
def ask_1(state: State) -> State:
|
||||
called.append("ask_1")
|
||||
answer = interrupt("Question 1?")
|
||||
return {"value": [f"ask_1:{answer}"]}
|
||||
|
||||
inner = (
|
||||
StateGraph(State)
|
||||
.add_node("step_a", step_a)
|
||||
.add_node("ask_1", ask_1)
|
||||
.add_edge(START, "step_a")
|
||||
.add_edge("step_a", "ask_1")
|
||||
.add_edge("ask_1", "__end__")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
middle = (
|
||||
StateGraph(State)
|
||||
.add_node("pre", pre)
|
||||
.add_node("inner", inner)
|
||||
.add_edge(START, "pre")
|
||||
.add_edge("pre", "inner")
|
||||
.add_edge("inner", "__end__")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
graph = (
|
||||
StateGraph(State)
|
||||
.add_node("outer", middle)
|
||||
.add_edge(START, "outer")
|
||||
.compile(checkpointer=sync_checkpointer)
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "1"}}
|
||||
|
||||
# Run until first interrupt (pre in middle subgraph)
|
||||
result = graph.invoke({"value": []}, config)
|
||||
assert result["__interrupt__"][0].value == "Pre-question?"
|
||||
|
||||
# Capture middle subgraph config at the pre interrupt
|
||||
parent_state = graph.get_state(config, subgraphs=True)
|
||||
mid_config_at_pre = parent_state.tasks[0].state.config
|
||||
|
||||
# Resume pre, hits ask_1 in inner subgraph
|
||||
result = graph.invoke(Command(resume="pre_answer"), config)
|
||||
assert result["__interrupt__"][0].value == "Question 1?"
|
||||
|
||||
# Capture middle subgraph config at the ask_1 interrupt
|
||||
parent_state = graph.get_state(config, subgraphs=True)
|
||||
mid_config_at_ask1 = parent_state.tasks[0].state.config
|
||||
|
||||
# Resume ask_1 to complete
|
||||
result = graph.invoke(Command(resume="answer_1"), config)
|
||||
assert "__interrupt__" not in result
|
||||
|
||||
# --- Time travel to middle checkpoint at pre interrupt ---
|
||||
called.clear()
|
||||
replay_result = graph.invoke(None, mid_config_at_pre)
|
||||
assert "__interrupt__" in replay_result
|
||||
assert replay_result["__interrupt__"][0].value == "Pre-question?"
|
||||
# pre should re-fire (interrupt replays), but nothing else should run
|
||||
assert "pre" in called
|
||||
assert "step_a" not in called
|
||||
assert "ask_1" not in called
|
||||
|
||||
# Fork from middle checkpoint at pre interrupt
|
||||
called.clear()
|
||||
fork_config = graph.update_state(mid_config_at_pre, {"value": ["forked"]})
|
||||
fork_result = graph.invoke(None, fork_config)
|
||||
assert "__interrupt__" in fork_result
|
||||
assert fork_result["__interrupt__"][0].value == "Pre-question?"
|
||||
assert "pre" in called
|
||||
assert "step_a" not in called
|
||||
|
||||
# --- Time travel to middle checkpoint at ask_1 interrupt ---
|
||||
called.clear()
|
||||
replay_result = graph.invoke(None, mid_config_at_ask1)
|
||||
assert "__interrupt__" in replay_result
|
||||
assert replay_result["__interrupt__"][0].value == "Question 1?"
|
||||
# pre should NOT re-run (it completed before this checkpoint)
|
||||
assert "pre" not in called
|
||||
# ask_1 re-fires
|
||||
assert "ask_1" in called
|
||||
|
||||
# Fork from middle checkpoint at ask_1 interrupt
|
||||
called.clear()
|
||||
fork_config = graph.update_state(mid_config_at_ask1, {"value": ["forked"]})
|
||||
fork_result = graph.invoke(None, fork_config)
|
||||
assert "__interrupt__" in fork_result
|
||||
assert fork_result["__interrupt__"][0].value == "Question 1?"
|
||||
assert "pre" not in called
|
||||
assert "ask_1" in called
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Section 6: __copy__ / update_state(None)
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
@@ -1051,552 +1051,6 @@ async def test_subgraph_interrupt_full_flow_no_sub_checkpointer(
|
||||
assert "post" in final_result["value"]
|
||||
|
||||
|
||||
@NEEDS_CONTEXTVARS
|
||||
async def test_subgraph_time_travel_to_first_interrupt_async(
|
||||
async_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
"""Time travel to a subgraph checkpoint at the FIRST interrupt (async)."""
|
||||
|
||||
called: list[str] = []
|
||||
|
||||
async def step_a(state: State) -> State:
|
||||
called.append("step_a")
|
||||
return {"value": ["step_a_done"]}
|
||||
|
||||
async def ask_1(state: State) -> State:
|
||||
called.append("ask_1")
|
||||
answer = interrupt("Question 1?")
|
||||
return {"value": [f"ask_1:{answer}"]}
|
||||
|
||||
async def ask_2(state: State) -> State:
|
||||
called.append("ask_2")
|
||||
answer = interrupt("Question 2?")
|
||||
return {"value": [f"ask_2:{answer}"]}
|
||||
|
||||
executor = (
|
||||
StateGraph(State)
|
||||
.add_node("step_a", step_a)
|
||||
.add_node("ask_1", ask_1)
|
||||
.add_node("ask_2", ask_2)
|
||||
.add_edge(START, "step_a")
|
||||
.add_edge("step_a", "ask_1")
|
||||
.add_edge("ask_1", "ask_2")
|
||||
.add_edge("ask_2", "__end__")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
graph = (
|
||||
StateGraph(State)
|
||||
.add_node("executor", executor)
|
||||
.add_edge(START, "executor")
|
||||
.compile(checkpointer=async_checkpointer)
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "1"}}
|
||||
|
||||
# Run until first interrupt (ask_1)
|
||||
result = await graph.ainvoke({"value": []}, config)
|
||||
assert result["__interrupt__"][0].value == "Question 1?"
|
||||
|
||||
# Capture subgraph state at the first interrupt
|
||||
parent_state = await graph.aget_state(config, subgraphs=True)
|
||||
sub_config_at_first = parent_state.tasks[0].state.config
|
||||
|
||||
# Resume through both interrupts to complete
|
||||
await graph.ainvoke(Command(resume="answer_1"), config)
|
||||
await graph.ainvoke(Command(resume="answer_2"), config)
|
||||
|
||||
# --- Scenario 1: Replay from subgraph checkpoint at 1st interrupt ---
|
||||
called.clear()
|
||||
replay_result = await graph.ainvoke(None, sub_config_at_first)
|
||||
assert "__interrupt__" in replay_result
|
||||
assert replay_result["__interrupt__"][0].value == "Question 1?"
|
||||
assert "step_a" not in called
|
||||
assert "ask_1" in called
|
||||
|
||||
# --- Scenario 2: Fork from subgraph checkpoint at 1st interrupt ---
|
||||
called.clear()
|
||||
fork_config = await graph.aupdate_state(sub_config_at_first, {"value": ["forked"]})
|
||||
fork_result = await graph.ainvoke(None, fork_config)
|
||||
assert "__interrupt__" in fork_result
|
||||
assert fork_result["__interrupt__"][0].value == "Question 1?"
|
||||
assert "step_a" not in called
|
||||
assert "ask_1" in called
|
||||
|
||||
|
||||
@NEEDS_CONTEXTVARS
|
||||
async def test_subgraph_time_travel_to_second_interrupt_async(
|
||||
async_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
"""Time travel to a subgraph checkpoint at the SECOND interrupt (async)."""
|
||||
|
||||
called: list[str] = []
|
||||
|
||||
async def step_a(state: State) -> State:
|
||||
called.append("step_a")
|
||||
return {"value": ["step_a_done"]}
|
||||
|
||||
async def ask_1(state: State) -> State:
|
||||
called.append("ask_1")
|
||||
answer = interrupt("Question 1?")
|
||||
return {"value": [f"ask_1:{answer}"]}
|
||||
|
||||
async def ask_2(state: State) -> State:
|
||||
called.append("ask_2")
|
||||
answer = interrupt("Question 2?")
|
||||
return {"value": [f"ask_2:{answer}"]}
|
||||
|
||||
executor = (
|
||||
StateGraph(State)
|
||||
.add_node("step_a", step_a)
|
||||
.add_node("ask_1", ask_1)
|
||||
.add_node("ask_2", ask_2)
|
||||
.add_edge(START, "step_a")
|
||||
.add_edge("step_a", "ask_1")
|
||||
.add_edge("ask_1", "ask_2")
|
||||
.add_edge("ask_2", "__end__")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
graph = (
|
||||
StateGraph(State)
|
||||
.add_node("executor", executor)
|
||||
.add_edge(START, "executor")
|
||||
.compile(checkpointer=async_checkpointer)
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "1"}}
|
||||
|
||||
# Run until first interrupt
|
||||
await graph.ainvoke({"value": []}, config)
|
||||
|
||||
# Resume first interrupt
|
||||
result = await graph.ainvoke(Command(resume="answer_1"), config)
|
||||
assert result["__interrupt__"][0].value == "Question 2?"
|
||||
|
||||
# Capture subgraph state at the second interrupt
|
||||
parent_state = await graph.aget_state(config, subgraphs=True)
|
||||
sub_config = parent_state.tasks[0].state.config
|
||||
|
||||
# Resume second interrupt to complete
|
||||
await graph.ainvoke(Command(resume="answer_2"), config)
|
||||
|
||||
# --- Scenario 1: Replay from subgraph checkpoint at 2nd interrupt ---
|
||||
called.clear()
|
||||
replay_result = await graph.ainvoke(None, sub_config)
|
||||
assert "__interrupt__" in replay_result
|
||||
assert replay_result["__interrupt__"][0].value == "Question 2?"
|
||||
assert "step_a" not in called
|
||||
assert "ask_1" not in called
|
||||
|
||||
# --- Scenario 2: Fork from subgraph checkpoint at 2nd interrupt ---
|
||||
called.clear()
|
||||
fork_config = await graph.aupdate_state(sub_config, {"value": ["forked"]})
|
||||
fork_result = await graph.ainvoke(None, fork_config)
|
||||
assert "__interrupt__" in fork_result
|
||||
assert fork_result["__interrupt__"][0].value == "Question 2?"
|
||||
assert "step_a" not in called
|
||||
assert "ask_1" not in called
|
||||
|
||||
|
||||
@NEEDS_CONTEXTVARS
|
||||
async def test_subgraph_time_travel_after_completion_async(
|
||||
async_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
"""Time travel to a subgraph checkpoint AFTER both interrupts resolved (async)."""
|
||||
|
||||
called: list[str] = []
|
||||
|
||||
async def step_a(state: State) -> State:
|
||||
called.append("step_a")
|
||||
return {"value": ["step_a_done"]}
|
||||
|
||||
async def ask_1(state: State) -> State:
|
||||
called.append("ask_1")
|
||||
answer = interrupt("Question 1?")
|
||||
return {"value": [f"ask_1:{answer}"]}
|
||||
|
||||
async def ask_2(state: State) -> State:
|
||||
called.append("ask_2")
|
||||
answer = interrupt("Question 2?")
|
||||
return {"value": [f"ask_2:{answer}"]}
|
||||
|
||||
executor = (
|
||||
StateGraph(State)
|
||||
.add_node("step_a", step_a)
|
||||
.add_node("ask_1", ask_1)
|
||||
.add_node("ask_2", ask_2)
|
||||
.add_edge(START, "step_a")
|
||||
.add_edge("step_a", "ask_1")
|
||||
.add_edge("ask_1", "ask_2")
|
||||
.add_edge("ask_2", "__end__")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
graph = (
|
||||
StateGraph(State)
|
||||
.add_node("executor", executor)
|
||||
.add_edge(START, "executor")
|
||||
.compile(checkpointer=async_checkpointer)
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "1"}}
|
||||
|
||||
await graph.ainvoke({"value": []}, config)
|
||||
await graph.ainvoke(Command(resume="answer_1"), config)
|
||||
await graph.ainvoke(Command(resume="answer_2"), config)
|
||||
|
||||
final_state = await graph.aget_state(config)
|
||||
assert len(final_state.tasks) == 0
|
||||
|
||||
# Replay from the final parent checkpoint — should be a no-op
|
||||
called.clear()
|
||||
replay_result = await graph.ainvoke(None, final_state.config)
|
||||
assert "__interrupt__" not in replay_result
|
||||
assert "step_a" not in called
|
||||
assert "ask_1" not in called
|
||||
assert "ask_2" not in called
|
||||
assert "step_a_done" in replay_result["value"]
|
||||
assert "ask_1:answer_1" in replay_result["value"]
|
||||
assert "ask_2:answer_2" in replay_result["value"]
|
||||
|
||||
|
||||
@NEEDS_CONTEXTVARS
|
||||
async def test_3_levels_deep_time_travel_to_first_interrupt_async(
|
||||
async_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
"""Time travel to innermost subgraph checkpoint at FIRST interrupt (async, 3 levels)."""
|
||||
|
||||
called: list[str] = []
|
||||
|
||||
async def step_a(state: State) -> State:
|
||||
called.append("step_a")
|
||||
return {"value": ["step_a_done"]}
|
||||
|
||||
async def ask_1(state: State) -> State:
|
||||
called.append("ask_1")
|
||||
answer = interrupt("Question 1?")
|
||||
return {"value": [f"ask_1:{answer}"]}
|
||||
|
||||
async def ask_2(state: State) -> State:
|
||||
called.append("ask_2")
|
||||
answer = interrupt("Question 2?")
|
||||
return {"value": [f"ask_2:{answer}"]}
|
||||
|
||||
inner = (
|
||||
StateGraph(State)
|
||||
.add_node("step_a", step_a)
|
||||
.add_node("ask_1", ask_1)
|
||||
.add_node("ask_2", ask_2)
|
||||
.add_edge(START, "step_a")
|
||||
.add_edge("step_a", "ask_1")
|
||||
.add_edge("ask_1", "ask_2")
|
||||
.add_edge("ask_2", "__end__")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
middle = (
|
||||
StateGraph(State)
|
||||
.add_node("inner", inner)
|
||||
.add_edge(START, "inner")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
graph = (
|
||||
StateGraph(State)
|
||||
.add_node("outer", middle)
|
||||
.add_edge(START, "outer")
|
||||
.compile(checkpointer=async_checkpointer)
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "1"}}
|
||||
|
||||
result = await graph.ainvoke({"value": []}, config)
|
||||
assert result["__interrupt__"][0].value == "Question 1?"
|
||||
|
||||
parent_state = await graph.aget_state(config, subgraphs=True)
|
||||
mid_state = parent_state.tasks[0].state
|
||||
inner_config = mid_state.tasks[0].state.config
|
||||
|
||||
await graph.ainvoke(Command(resume="answer_1"), config)
|
||||
await graph.ainvoke(Command(resume="answer_2"), config)
|
||||
|
||||
# --- Scenario 1: Replay from innermost checkpoint at 1st interrupt ---
|
||||
called.clear()
|
||||
replay_result = await graph.ainvoke(None, inner_config)
|
||||
assert "__interrupt__" in replay_result
|
||||
assert replay_result["__interrupt__"][0].value == "Question 1?"
|
||||
assert "step_a" not in called
|
||||
assert "ask_1" in called
|
||||
|
||||
# --- Scenario 2: Fork from innermost checkpoint at 1st interrupt ---
|
||||
called.clear()
|
||||
fork_config = await graph.aupdate_state(inner_config, {"value": ["forked"]})
|
||||
fork_result = await graph.ainvoke(None, fork_config)
|
||||
assert "__interrupt__" in fork_result
|
||||
assert fork_result["__interrupt__"][0].value == "Question 1?"
|
||||
assert "step_a" not in called
|
||||
assert "ask_1" in called
|
||||
|
||||
|
||||
@NEEDS_CONTEXTVARS
|
||||
async def test_3_levels_deep_time_travel_to_second_interrupt_async(
|
||||
async_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
"""Time travel to innermost subgraph checkpoint at SECOND interrupt (async, 3 levels)."""
|
||||
|
||||
called: list[str] = []
|
||||
|
||||
async def step_a(state: State) -> State:
|
||||
called.append("step_a")
|
||||
return {"value": ["step_a_done"]}
|
||||
|
||||
async def ask_1(state: State) -> State:
|
||||
called.append("ask_1")
|
||||
answer = interrupt("Question 1?")
|
||||
return {"value": [f"ask_1:{answer}"]}
|
||||
|
||||
async def ask_2(state: State) -> State:
|
||||
called.append("ask_2")
|
||||
answer = interrupt("Question 2?")
|
||||
return {"value": [f"ask_2:{answer}"]}
|
||||
|
||||
inner = (
|
||||
StateGraph(State)
|
||||
.add_node("step_a", step_a)
|
||||
.add_node("ask_1", ask_1)
|
||||
.add_node("ask_2", ask_2)
|
||||
.add_edge(START, "step_a")
|
||||
.add_edge("step_a", "ask_1")
|
||||
.add_edge("ask_1", "ask_2")
|
||||
.add_edge("ask_2", "__end__")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
middle = (
|
||||
StateGraph(State)
|
||||
.add_node("inner", inner)
|
||||
.add_edge(START, "inner")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
graph = (
|
||||
StateGraph(State)
|
||||
.add_node("outer", middle)
|
||||
.add_edge(START, "outer")
|
||||
.compile(checkpointer=async_checkpointer)
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "1"}}
|
||||
|
||||
await graph.ainvoke({"value": []}, config)
|
||||
|
||||
result = await graph.ainvoke(Command(resume="answer_1"), config)
|
||||
assert result["__interrupt__"][0].value == "Question 2?"
|
||||
|
||||
parent_state = await graph.aget_state(config, subgraphs=True)
|
||||
mid_state = parent_state.tasks[0].state
|
||||
inner_config = mid_state.tasks[0].state.config
|
||||
|
||||
await graph.ainvoke(Command(resume="answer_2"), config)
|
||||
|
||||
# --- Scenario 1: Replay ---
|
||||
called.clear()
|
||||
replay_result = await graph.ainvoke(None, inner_config)
|
||||
assert "__interrupt__" in replay_result
|
||||
assert replay_result["__interrupt__"][0].value == "Question 2?"
|
||||
assert "step_a" not in called
|
||||
assert "ask_1" not in called
|
||||
|
||||
# --- Scenario 2: Fork ---
|
||||
called.clear()
|
||||
fork_config = await graph.aupdate_state(inner_config, {"value": ["forked"]})
|
||||
fork_result = await graph.ainvoke(None, fork_config)
|
||||
assert "__interrupt__" in fork_result
|
||||
assert fork_result["__interrupt__"][0].value == "Question 2?"
|
||||
assert "step_a" not in called
|
||||
assert "ask_1" not in called
|
||||
|
||||
|
||||
@NEEDS_CONTEXTVARS
|
||||
async def test_3_levels_deep_time_travel_to_middle_subgraph_async(
|
||||
async_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
"""Time travel to the MIDDLE-level subgraph checkpoint (async, 3 levels)."""
|
||||
|
||||
called: list[str] = []
|
||||
|
||||
async def step_a(state: State) -> State:
|
||||
called.append("step_a")
|
||||
return {"value": ["step_a_done"]}
|
||||
|
||||
async def ask_1(state: State) -> State:
|
||||
called.append("ask_1")
|
||||
answer = interrupt("Question 1?")
|
||||
return {"value": [f"ask_1:{answer}"]}
|
||||
|
||||
async def ask_2(state: State) -> State:
|
||||
called.append("ask_2")
|
||||
answer = interrupt("Question 2?")
|
||||
return {"value": [f"ask_2:{answer}"]}
|
||||
|
||||
inner = (
|
||||
StateGraph(State)
|
||||
.add_node("step_a", step_a)
|
||||
.add_node("ask_1", ask_1)
|
||||
.add_node("ask_2", ask_2)
|
||||
.add_edge(START, "step_a")
|
||||
.add_edge("step_a", "ask_1")
|
||||
.add_edge("ask_1", "ask_2")
|
||||
.add_edge("ask_2", "__end__")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
middle = (
|
||||
StateGraph(State)
|
||||
.add_node("inner", inner)
|
||||
.add_edge(START, "inner")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
graph = (
|
||||
StateGraph(State)
|
||||
.add_node("outer", middle)
|
||||
.add_edge(START, "outer")
|
||||
.compile(checkpointer=async_checkpointer)
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "1"}}
|
||||
|
||||
await graph.ainvoke({"value": []}, config)
|
||||
await graph.ainvoke(Command(resume="answer_1"), config)
|
||||
|
||||
parent_state = await graph.aget_state(config, subgraphs=True)
|
||||
mid_config = parent_state.tasks[0].state.config
|
||||
|
||||
await graph.ainvoke(Command(resume="answer_2"), config)
|
||||
|
||||
# --- Scenario 1: Replay from middle-level subgraph checkpoint ---
|
||||
# The middle subgraph's checkpoint knows about the inner subgraph's state
|
||||
# via checkpoint_map, so the inner replays from the correct point.
|
||||
called.clear()
|
||||
replay_result = await graph.ainvoke(None, mid_config)
|
||||
assert "__interrupt__" in replay_result
|
||||
|
||||
# --- Scenario 2: Fork from middle-level subgraph checkpoint ---
|
||||
called.clear()
|
||||
fork_config = await graph.aupdate_state(mid_config, {"value": ["forked"]})
|
||||
fork_result = await graph.ainvoke(None, fork_config)
|
||||
assert "__interrupt__" in fork_result
|
||||
|
||||
|
||||
@NEEDS_CONTEXTVARS
|
||||
async def test_3_levels_deep_middle_has_interrupts_async(
|
||||
async_checkpointer: BaseCheckpointSaver,
|
||||
) -> None:
|
||||
"""Time travel when the MIDDLE subgraph itself has interrupts (async)."""
|
||||
|
||||
called: list[str] = []
|
||||
|
||||
async def pre(state: State) -> State:
|
||||
called.append("pre")
|
||||
answer = interrupt("Pre-question?")
|
||||
return {"value": [f"pre:{answer}"]}
|
||||
|
||||
async def step_a(state: State) -> State:
|
||||
called.append("step_a")
|
||||
return {"value": ["step_a_done"]}
|
||||
|
||||
async def ask_1(state: State) -> State:
|
||||
called.append("ask_1")
|
||||
answer = interrupt("Question 1?")
|
||||
return {"value": [f"ask_1:{answer}"]}
|
||||
|
||||
inner = (
|
||||
StateGraph(State)
|
||||
.add_node("step_a", step_a)
|
||||
.add_node("ask_1", ask_1)
|
||||
.add_edge(START, "step_a")
|
||||
.add_edge("step_a", "ask_1")
|
||||
.add_edge("ask_1", "__end__")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
middle = (
|
||||
StateGraph(State)
|
||||
.add_node("pre", pre)
|
||||
.add_node("inner", inner)
|
||||
.add_edge(START, "pre")
|
||||
.add_edge("pre", "inner")
|
||||
.add_edge("inner", "__end__")
|
||||
.compile(checkpointer=True)
|
||||
)
|
||||
|
||||
graph = (
|
||||
StateGraph(State)
|
||||
.add_node("outer", middle)
|
||||
.add_edge(START, "outer")
|
||||
.compile(checkpointer=async_checkpointer)
|
||||
)
|
||||
|
||||
config = {"configurable": {"thread_id": "1"}}
|
||||
|
||||
# Run until first interrupt (pre in middle subgraph)
|
||||
result = await graph.ainvoke({"value": []}, config)
|
||||
assert result["__interrupt__"][0].value == "Pre-question?"
|
||||
|
||||
# Capture middle subgraph config at the pre interrupt
|
||||
parent_state = await graph.aget_state(config, subgraphs=True)
|
||||
mid_config_at_pre = parent_state.tasks[0].state.config
|
||||
|
||||
# Resume pre, hits ask_1 in inner subgraph
|
||||
result = await graph.ainvoke(Command(resume="pre_answer"), config)
|
||||
assert result["__interrupt__"][0].value == "Question 1?"
|
||||
|
||||
# Capture middle subgraph config at the ask_1 interrupt
|
||||
parent_state = await graph.aget_state(config, subgraphs=True)
|
||||
mid_config_at_ask1 = parent_state.tasks[0].state.config
|
||||
|
||||
# Resume ask_1 to complete
|
||||
result = await graph.ainvoke(Command(resume="answer_1"), config)
|
||||
assert "__interrupt__" not in result
|
||||
|
||||
# --- Time travel to middle checkpoint at pre interrupt ---
|
||||
called.clear()
|
||||
replay_result = await graph.ainvoke(None, mid_config_at_pre)
|
||||
assert "__interrupt__" in replay_result
|
||||
assert replay_result["__interrupt__"][0].value == "Pre-question?"
|
||||
assert "pre" in called
|
||||
assert "step_a" not in called
|
||||
assert "ask_1" not in called
|
||||
|
||||
# Fork from middle checkpoint at pre interrupt
|
||||
called.clear()
|
||||
fork_config = await graph.aupdate_state(mid_config_at_pre, {"value": ["forked"]})
|
||||
fork_result = await graph.ainvoke(None, fork_config)
|
||||
assert "__interrupt__" in fork_result
|
||||
assert fork_result["__interrupt__"][0].value == "Pre-question?"
|
||||
assert "pre" in called
|
||||
assert "step_a" not in called
|
||||
|
||||
# --- Time travel to middle checkpoint at ask_1 interrupt ---
|
||||
called.clear()
|
||||
replay_result = await graph.ainvoke(None, mid_config_at_ask1)
|
||||
assert "__interrupt__" in replay_result
|
||||
assert replay_result["__interrupt__"][0].value == "Question 1?"
|
||||
assert "pre" not in called
|
||||
assert "ask_1" in called
|
||||
|
||||
# Fork from middle checkpoint at ask_1 interrupt
|
||||
called.clear()
|
||||
fork_config = await graph.aupdate_state(mid_config_at_ask1, {"value": ["forked"]})
|
||||
fork_result = await graph.ainvoke(None, fork_config)
|
||||
assert "__interrupt__" in fork_result
|
||||
assert fork_result["__interrupt__"][0].value == "Question 1?"
|
||||
assert "pre" not in called
|
||||
assert "ask_1" in called
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Section 6: __copy__ / update_state(None)
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
Generated
+119
-117
@@ -1348,7 +1348,7 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "langchain-core"
|
||||
version = "1.2.19"
|
||||
version = "1.2.17"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "jsonpatch" },
|
||||
@@ -1360,14 +1360,14 @@ dependencies = [
|
||||
{ name = "typing-extensions" },
|
||||
{ name = "uuid-utils" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/ac/da/075720d37ebc668f48743bd540b047b2b08b8ba22b46d8f61166c5ad1d1c/langchain_core-1.2.19.tar.gz", hash = "sha256:87fa82c3eb4cc3d7a65f574cb447b5df09ec2131c8c2a0a02d4737ad02685438", size = 836647, upload-time = "2026-03-13T13:44:54.8Z" }
|
||||
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||||
|
||||
[[package]]
|
||||
|
||||
@@ -3,6 +3,6 @@ from langgraph_sdk.client import get_client, get_sync_client
|
||||
from langgraph_sdk.encryption import Encryption
|
||||
from langgraph_sdk.encryption.types import EncryptionContext
|
||||
|
||||
__version__ = "0.3.12"
|
||||
__version__ = "0.3.10"
|
||||
|
||||
__all__ = ["Auth", "Encryption", "EncryptionContext", "get_client", "get_sync_client"]
|
||||
|
||||
@@ -4,11 +4,10 @@ from __future__ import annotations
|
||||
|
||||
import warnings
|
||||
from collections.abc import Mapping, Sequence
|
||||
from datetime import datetime, tzinfo
|
||||
from datetime import datetime
|
||||
from typing import Any
|
||||
|
||||
from langgraph_sdk._async.http import HttpClient
|
||||
from langgraph_sdk._shared.utilities import _resolve_timezone
|
||||
from langgraph_sdk.schema import (
|
||||
All,
|
||||
Config,
|
||||
@@ -71,7 +70,6 @@ class CronClient:
|
||||
multitask_strategy: str | None = None,
|
||||
end_time: datetime | None = None,
|
||||
enabled: bool | None = None,
|
||||
timezone: str | tzinfo | None = None,
|
||||
stream_mode: StreamMode | Sequence[StreamMode] | None = None,
|
||||
stream_subgraphs: bool | None = None,
|
||||
stream_resumable: bool | None = None,
|
||||
@@ -86,7 +84,7 @@ class CronClient:
|
||||
assistant_id: The assistant ID or graph name to use for the cron job.
|
||||
If using graph name, will default to first assistant created from that graph.
|
||||
schedule: The cron schedule to execute this job on.
|
||||
Schedules are interpreted in UTC unless a timezone is specified.
|
||||
Schedules are interpreted in UTC.
|
||||
input: The input to the graph.
|
||||
metadata: Metadata to assign to the cron job runs.
|
||||
config: The configuration for the assistant.
|
||||
@@ -102,7 +100,6 @@ class CronClient:
|
||||
Must be one of 'reject', 'interrupt', 'rollback', or 'enqueue'.
|
||||
end_time: The time to stop running the cron job. If not provided, the cron job will run indefinitely.
|
||||
enabled: Whether the cron job is enabled or not.
|
||||
timezone: IANA timezone for the cron schedule. Accepts a string (e.g. 'America/New_York') or a ``datetime.tzinfo`` instance (e.g. ``ZoneInfo("America/New_York")``).
|
||||
stream_mode: The stream mode(s) to use.
|
||||
stream_subgraphs: Whether to stream output from subgraphs.
|
||||
stream_resumable: Whether to persist the stream chunks in order to resume the stream later.
|
||||
@@ -155,7 +152,6 @@ class CronClient:
|
||||
"webhook": webhook,
|
||||
"end_time": end_time.isoformat() if end_time else None,
|
||||
"enabled": enabled,
|
||||
"timezone": _resolve_timezone(timezone),
|
||||
"stream_mode": stream_mode,
|
||||
"stream_subgraphs": stream_subgraphs,
|
||||
"stream_resumable": stream_resumable,
|
||||
@@ -188,7 +184,6 @@ class CronClient:
|
||||
multitask_strategy: str | None = None,
|
||||
end_time: datetime | None = None,
|
||||
enabled: bool | None = None,
|
||||
timezone: str | tzinfo | None = None,
|
||||
stream_mode: StreamMode | Sequence[StreamMode] | None = None,
|
||||
stream_subgraphs: bool | None = None,
|
||||
stream_resumable: bool | None = None,
|
||||
@@ -202,7 +197,7 @@ class CronClient:
|
||||
assistant_id: The assistant ID or graph name to use for the cron job.
|
||||
If using graph name, will default to first assistant created from that graph.
|
||||
schedule: The cron schedule to execute this job on.
|
||||
Schedules are interpreted in UTC unless a timezone is specified.
|
||||
Schedules are interpreted in UTC.
|
||||
input: The input to the graph.
|
||||
metadata: Metadata to assign to the cron job runs.
|
||||
config: The configuration for the assistant.
|
||||
@@ -220,7 +215,6 @@ class CronClient:
|
||||
Must be one of 'reject', 'interrupt', 'rollback', or 'enqueue'.
|
||||
end_time: The time to stop running the cron job. If not provided, the cron job will run indefinitely.
|
||||
enabled: Whether the cron job is enabled or not.
|
||||
timezone: IANA timezone for the cron schedule. Accepts a string (e.g. 'America/New_York') or a ``datetime.tzinfo`` instance (e.g. ``ZoneInfo("America/New_York")``).
|
||||
stream_mode: The stream mode(s) to use.
|
||||
stream_subgraphs: Whether to stream output from subgraphs.
|
||||
stream_resumable: Whether to persist the stream chunks in order to resume the stream later.
|
||||
@@ -274,7 +268,6 @@ class CronClient:
|
||||
"on_run_completed": on_run_completed,
|
||||
"end_time": end_time.isoformat() if end_time else None,
|
||||
"enabled": enabled,
|
||||
"timezone": _resolve_timezone(timezone),
|
||||
"stream_mode": stream_mode,
|
||||
"stream_subgraphs": stream_subgraphs,
|
||||
"stream_resumable": stream_resumable,
|
||||
@@ -331,7 +324,6 @@ class CronClient:
|
||||
interrupt_after: All | list[str] | None = None,
|
||||
on_run_completed: OnCompletionBehavior | None = None,
|
||||
enabled: bool | None = None,
|
||||
timezone: str | tzinfo | None = None,
|
||||
stream_mode: StreamMode | Sequence[StreamMode] | None = None,
|
||||
stream_subgraphs: bool | None = None,
|
||||
stream_resumable: bool | None = None,
|
||||
@@ -344,7 +336,7 @@ class CronClient:
|
||||
Args:
|
||||
cron_id: The cron ID to update.
|
||||
schedule: The cron schedule to execute this job on.
|
||||
Schedules are interpreted in UTC unless a timezone is specified.
|
||||
Schedules are interpreted in UTC.
|
||||
end_time: The end date to stop running the cron.
|
||||
input: The input to the graph.
|
||||
metadata: Metadata to assign to the cron job runs.
|
||||
@@ -358,7 +350,6 @@ class CronClient:
|
||||
after execution. 'keep' creates a new thread for each execution but does not
|
||||
clean them up.
|
||||
enabled: Enable or disable the cron job.
|
||||
timezone: IANA timezone for the cron schedule. Accepts a string (e.g. 'America/New_York') or a ``datetime.tzinfo`` instance (e.g. ``ZoneInfo("America/New_York")``).
|
||||
stream_mode: The stream mode(s) to use.
|
||||
stream_subgraphs: Whether to stream output from subgraphs.
|
||||
stream_resumable: Whether to persist the stream chunks in order to resume the stream later.
|
||||
@@ -393,7 +384,6 @@ class CronClient:
|
||||
"interrupt_after": interrupt_after,
|
||||
"on_run_completed": on_run_completed,
|
||||
"enabled": enabled,
|
||||
"timezone": _resolve_timezone(timezone),
|
||||
"stream_mode": stream_mode,
|
||||
"stream_subgraphs": stream_subgraphs,
|
||||
"stream_resumable": stream_resumable,
|
||||
|
||||
@@ -6,17 +6,13 @@ import functools
|
||||
import os
|
||||
import re
|
||||
from collections.abc import Mapping
|
||||
from datetime import tzinfo
|
||||
from typing import TYPE_CHECKING, Any, cast
|
||||
from typing import Any, cast
|
||||
|
||||
import httpx
|
||||
|
||||
import langgraph_sdk
|
||||
from langgraph_sdk.schema import RunCreateMetadata
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from zoneinfo import ZoneInfo
|
||||
|
||||
RESERVED_HEADERS = ("x-api-key",)
|
||||
|
||||
NOT_PROVIDED = cast(None, object())
|
||||
@@ -129,35 +125,6 @@ def _sse_to_v2_dict(event: str, data: Any) -> dict[str, Any] | None:
|
||||
return result
|
||||
|
||||
|
||||
def _resolve_timezone(tz: str | tzinfo | ZoneInfo | None) -> str | None:
|
||||
"""Convert a timezone argument to an IANA timezone string.
|
||||
|
||||
Accepts:
|
||||
- A string (returned as-is, assumed to be an IANA timezone name)
|
||||
- A ``datetime.tzinfo`` instance (e.g. ``zoneinfo.ZoneInfo("America/New_York")``,
|
||||
``datetime.timezone.utc``). The ``key`` attribute is used if available,
|
||||
otherwise ``tzname(None)`` is used.
|
||||
- ``None`` (returned as ``None``)
|
||||
"""
|
||||
if tz is None or isinstance(tz, str):
|
||||
return tz
|
||||
if isinstance(tz, tzinfo):
|
||||
# ZoneInfo objects have a .key attribute with the IANA name
|
||||
if hasattr(tz, "key"):
|
||||
return tz.key # type: ignore[union-attr]
|
||||
# Fall back to tzname for fixed-offset timezones like datetime.timezone.utc
|
||||
name = tz.tzname(None)
|
||||
if name is not None:
|
||||
return name
|
||||
raise ValueError(
|
||||
f"Cannot determine timezone name from {tz!r}. "
|
||||
"Use a zoneinfo.ZoneInfo instance or pass a string like 'America/New_York'."
|
||||
)
|
||||
raise TypeError(
|
||||
f"Expected str, datetime.tzinfo, or None for timezone, got {type(tz).__name__}"
|
||||
)
|
||||
|
||||
|
||||
def _provided_vals(d: Mapping[str, Any]) -> dict[str, Any]:
|
||||
return {k: v for k, v in d.items() if v is not None}
|
||||
|
||||
|
||||
@@ -4,10 +4,9 @@ from __future__ import annotations
|
||||
|
||||
import warnings
|
||||
from collections.abc import Mapping, Sequence
|
||||
from datetime import datetime, tzinfo
|
||||
from datetime import datetime
|
||||
from typing import Any
|
||||
|
||||
from langgraph_sdk._shared.utilities import _resolve_timezone
|
||||
from langgraph_sdk._sync.http import SyncHttpClient
|
||||
from langgraph_sdk.schema import (
|
||||
All,
|
||||
@@ -65,7 +64,6 @@ class SyncCronClient:
|
||||
multitask_strategy: str | None = None,
|
||||
end_time: datetime | None = None,
|
||||
enabled: bool | None = None,
|
||||
timezone: str | tzinfo | None = None,
|
||||
stream_mode: StreamMode | Sequence[StreamMode] | None = None,
|
||||
stream_subgraphs: bool | None = None,
|
||||
stream_resumable: bool | None = None,
|
||||
@@ -80,7 +78,7 @@ class SyncCronClient:
|
||||
assistant_id: The assistant ID or graph name to use for the cron job.
|
||||
If using graph name, will default to first assistant created from that graph.
|
||||
schedule: The cron schedule to execute this job on.
|
||||
Schedules are interpreted in UTC unless a timezone is specified.
|
||||
Schedules are interpreted in UTC.
|
||||
input: The input to the graph.
|
||||
metadata: Metadata to assign to the cron job runs.
|
||||
config: The configuration for the assistant.
|
||||
@@ -94,7 +92,6 @@ class SyncCronClient:
|
||||
Must be one of 'reject', 'interrupt', 'rollback', or 'enqueue'.
|
||||
end_time: The time to stop running the cron job. If not provided, the cron job will run indefinitely.
|
||||
enabled: Whether the cron job is enabled. By default, it is considered enabled.
|
||||
timezone: IANA timezone for the cron schedule. Accepts a string (e.g. 'America/New_York') or a ``datetime.tzinfo`` instance (e.g. ``ZoneInfo("America/New_York")``).
|
||||
stream_mode: The stream mode(s) to use.
|
||||
stream_subgraphs: Whether to stream output from subgraphs.
|
||||
stream_resumable: Whether to persist the stream chunks in order to resume the stream later.
|
||||
@@ -147,7 +144,6 @@ class SyncCronClient:
|
||||
"multitask_strategy": multitask_strategy,
|
||||
"end_time": end_time.isoformat() if end_time else None,
|
||||
"enabled": enabled,
|
||||
"timezone": _resolve_timezone(timezone),
|
||||
"stream_mode": stream_mode,
|
||||
"stream_subgraphs": stream_subgraphs,
|
||||
"stream_resumable": stream_resumable,
|
||||
@@ -178,7 +174,6 @@ class SyncCronClient:
|
||||
multitask_strategy: str | None = None,
|
||||
end_time: datetime | None = None,
|
||||
enabled: bool | None = None,
|
||||
timezone: str | tzinfo | None = None,
|
||||
stream_mode: StreamMode | Sequence[StreamMode] | None = None,
|
||||
stream_subgraphs: bool | None = None,
|
||||
stream_resumable: bool | None = None,
|
||||
@@ -192,7 +187,7 @@ class SyncCronClient:
|
||||
assistant_id: The assistant ID or graph name to use for the cron job.
|
||||
If using graph name, will default to first assistant created from that graph.
|
||||
schedule: The cron schedule to execute this job on.
|
||||
Schedules are interpreted in UTC unless a timezone is specified.
|
||||
Schedules are interpreted in UTC.
|
||||
input: The input to the graph.
|
||||
metadata: Metadata to assign to the cron job runs.
|
||||
config: The configuration for the assistant.
|
||||
@@ -210,7 +205,6 @@ class SyncCronClient:
|
||||
Must be one of 'reject', 'interrupt', 'rollback', or 'enqueue'.
|
||||
end_time: The time to stop running the cron job. If not provided, the cron job will run indefinitely.
|
||||
enabled: Whether the cron job is enabled. By default, it is considered enabled.
|
||||
timezone: IANA timezone for the cron schedule. Accepts a string (e.g. 'America/New_York') or a ``datetime.tzinfo`` instance (e.g. ``ZoneInfo("America/New_York")``).
|
||||
stream_mode: The stream mode(s) to use.
|
||||
stream_subgraphs: Whether to stream output from subgraphs.
|
||||
stream_resumable: Whether to persist the stream chunks in order to resume the stream later.
|
||||
@@ -265,7 +259,6 @@ class SyncCronClient:
|
||||
"multitask_strategy": multitask_strategy,
|
||||
"end_time": end_time.isoformat() if end_time else None,
|
||||
"enabled": enabled,
|
||||
"timezone": _resolve_timezone(timezone),
|
||||
"stream_mode": stream_mode,
|
||||
"stream_subgraphs": stream_subgraphs,
|
||||
"stream_resumable": stream_resumable,
|
||||
@@ -320,7 +313,6 @@ class SyncCronClient:
|
||||
interrupt_after: All | list[str] | None = None,
|
||||
on_run_completed: OnCompletionBehavior | None = None,
|
||||
enabled: bool | None = None,
|
||||
timezone: str | tzinfo | None = None,
|
||||
stream_mode: StreamMode | Sequence[StreamMode] | None = None,
|
||||
stream_subgraphs: bool | None = None,
|
||||
stream_resumable: bool | None = None,
|
||||
@@ -333,7 +325,7 @@ class SyncCronClient:
|
||||
Args:
|
||||
cron_id: The cron ID to update.
|
||||
schedule: The cron schedule to execute this job on.
|
||||
Schedules are interpreted in UTC unless a timezone is specified.
|
||||
Schedules are interpreted in UTC.
|
||||
end_time: The end date to stop running the cron.
|
||||
input: The input to the graph.
|
||||
metadata: Metadata to assign to the cron job runs.
|
||||
@@ -347,7 +339,6 @@ class SyncCronClient:
|
||||
after execution. 'keep' creates a new thread for each execution but does not
|
||||
clean them up.
|
||||
enabled: Enable or disable the cron job.
|
||||
timezone: IANA timezone for the cron schedule. Accepts a string (e.g. 'America/New_York') or a ``datetime.tzinfo`` instance (e.g. ``ZoneInfo("America/New_York")``).
|
||||
stream_mode: The stream mode(s) to use.
|
||||
stream_subgraphs: Whether to stream output from subgraphs.
|
||||
stream_resumable: Whether to persist the stream chunks in order to resume the stream later.
|
||||
@@ -382,7 +373,6 @@ class SyncCronClient:
|
||||
"interrupt_after": interrupt_after,
|
||||
"on_run_completed": on_run_completed,
|
||||
"enabled": enabled,
|
||||
"timezone": _resolve_timezone(timezone),
|
||||
"stream_mode": stream_mode,
|
||||
"stream_subgraphs": stream_subgraphs,
|
||||
"stream_resumable": stream_resumable,
|
||||
|
||||
@@ -7,13 +7,8 @@ Values must be JSON-serializable (dicts, lists, strings, numbers, booleans,
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from collections.abc import Awaitable, Callable
|
||||
from datetime import timedelta
|
||||
from typing import Any, Generic, Literal, TypeVar
|
||||
|
||||
T = TypeVar("T")
|
||||
|
||||
CacheStatus = Literal["miss", "fresh", "stale", "expired"]
|
||||
from typing import Any
|
||||
|
||||
try:
|
||||
from langgraph_api.cache import ( # type: ignore[unresolved-import]
|
||||
@@ -27,29 +22,9 @@ except ImportError:
|
||||
_cache_set = None
|
||||
|
||||
|
||||
try:
|
||||
from langgraph_api.cache import SWRResult # type: ignore[unresolved-import]
|
||||
from langgraph_api.cache import swr as _api_swr # type: ignore[unresolved-import]
|
||||
|
||||
except ImportError:
|
||||
_api_swr = None
|
||||
|
||||
class SWRResult(Generic[T]):
|
||||
"""Result wrapper returned by :func:`swr`."""
|
||||
|
||||
value: T
|
||||
status: CacheStatus
|
||||
|
||||
async def mutate(self, value: T = ...) -> T: # type: ignore[assignment]
|
||||
"""Update or revalidate the cached value."""
|
||||
...
|
||||
|
||||
|
||||
__all__ = [
|
||||
"SWRResult",
|
||||
"cache_get",
|
||||
"cache_set",
|
||||
"swr",
|
||||
]
|
||||
|
||||
|
||||
@@ -85,56 +60,3 @@ async def cache_set(key: str, value: Any, *, ttl: timedelta | None = None) -> No
|
||||
"(https://docs.langchain.com/langsmith/deployments)."
|
||||
)
|
||||
await _cache_set(key, value, ttl)
|
||||
|
||||
|
||||
async def swr(
|
||||
key: str,
|
||||
loader: Callable[[], Awaitable[T]],
|
||||
*,
|
||||
fresh_for: timedelta | None = None,
|
||||
max_age: timedelta | None = None,
|
||||
model: type[T] | None = None,
|
||||
) -> SWRResult[T]:
|
||||
"""Load a cached value using stale-while-revalidate semantics.
|
||||
|
||||
This helper is server-side only and is intended for caching internal async
|
||||
dependencies such as auth or metadata lookups.
|
||||
|
||||
Args:
|
||||
key: Cache key.
|
||||
loader: Async callable that fetches the value on miss/revalidation.
|
||||
fresh_for: How long a cached value is considered fresh (no revalidation).
|
||||
Defaults to ``timedelta(0)`` so every access triggers a background
|
||||
revalidate while still returning the cached value instantly. Values
|
||||
above :data:`MAX_CACHE_TTL` are clamped to the backend maximum.
|
||||
max_age: Total lifetime of a cached entry. After this, the next access
|
||||
blocks on the loader. Defaults to :data:`MAX_CACHE_TTL` (24 h by
|
||||
default). Values above :data:`MAX_CACHE_TTL` are clamped to the
|
||||
backend maximum.
|
||||
model: Optional Pydantic model class. When provided, values are
|
||||
serialized via ``model_dump(mode="json")`` before storage and
|
||||
deserialized via ``model.model_validate()`` on read.
|
||||
|
||||
Returns:
|
||||
An :class:`SWRResult` with ``.value``, ``.status``, and an async
|
||||
``.mutate()`` method.
|
||||
|
||||
Semantics:
|
||||
- cache miss: await ``loader()``, store the value, return it
|
||||
- fresh hit (age < fresh_for): return the cached value
|
||||
- stale hit (fresh_for <= age < max_age): return the cached value
|
||||
immediately and trigger a best-effort background refresh
|
||||
- expired (age >= max_age): await ``loader()``, store the value, return it
|
||||
"""
|
||||
if _api_swr is None:
|
||||
raise RuntimeError(
|
||||
"Cache is only available server-side within the LangGraph Agent Server "
|
||||
"(https://docs.langchain.com/langsmith/deployments)."
|
||||
)
|
||||
if fresh_for is None:
|
||||
fresh_for = timedelta(0)
|
||||
if max_age is None:
|
||||
max_age = timedelta(days=1)
|
||||
return await _api_swr(
|
||||
key, loader, fresh_for=fresh_for, max_age=max_age, model=model
|
||||
)
|
||||
|
||||
@@ -385,8 +385,6 @@ class Cron(TypedDict):
|
||||
"""The end date to stop running the cron."""
|
||||
schedule: str
|
||||
"""The schedule to run, cron format."""
|
||||
timezone: str | None
|
||||
"""IANA timezone for the cron schedule (e.g. 'America/New_York'). Defaults to null, which is treated as UTC."""
|
||||
created_at: datetime
|
||||
"""The time the cron was created."""
|
||||
updated_at: datetime
|
||||
@@ -408,8 +406,6 @@ class CronUpdate(TypedDict, total=False):
|
||||
|
||||
schedule: str
|
||||
"""The cron schedule to execute this job on."""
|
||||
timezone: str
|
||||
"""IANA timezone for the cron schedule (e.g. 'America/New_York')."""
|
||||
end_time: datetime
|
||||
"""The end date to stop running the cron."""
|
||||
input: Input
|
||||
@@ -486,7 +482,6 @@ CronSelectField = Literal[
|
||||
"thread_id",
|
||||
"end_time",
|
||||
"schedule",
|
||||
"timezone",
|
||||
"created_at",
|
||||
"updated_at",
|
||||
"user_id",
|
||||
|
||||
@@ -30,10 +30,10 @@ test = [
|
||||
"pytest-watch",
|
||||
]
|
||||
lint = [
|
||||
"ruff==0.15.6",
|
||||
"ruff==0.15.5",
|
||||
"codespell",
|
||||
"mypy==1.19.1",
|
||||
"ty==0.0.23",
|
||||
"ty==0.0.21",
|
||||
"starlette",
|
||||
]
|
||||
dev = [
|
||||
|
||||
@@ -1,69 +0,0 @@
|
||||
from datetime import timedelta
|
||||
from unittest.mock import AsyncMock
|
||||
|
||||
import pytest
|
||||
|
||||
import langgraph_sdk.cache as cache_module
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_swr_proxies_to_server_impl(monkeypatch):
|
||||
loader = AsyncMock(return_value={"ok": True})
|
||||
forwarded = {}
|
||||
|
||||
async def fake_swr(key, inner_loader, *, fresh_for, max_age, model):
|
||||
forwarded["key"] = key
|
||||
forwarded["fresh_for"] = fresh_for
|
||||
forwarded["max_age"] = max_age
|
||||
forwarded["model"] = model
|
||||
return await inner_loader()
|
||||
|
||||
monkeypatch.setattr(cache_module, "_api_swr", fake_swr)
|
||||
|
||||
result = await cache_module.swr(
|
||||
"test-key",
|
||||
loader,
|
||||
fresh_for=timedelta(seconds=1),
|
||||
max_age=timedelta(seconds=10),
|
||||
)
|
||||
|
||||
assert result == {"ok": True}
|
||||
assert forwarded == {
|
||||
"key": "test-key",
|
||||
"fresh_for": timedelta(seconds=1),
|
||||
"max_age": timedelta(seconds=10),
|
||||
"model": None,
|
||||
}
|
||||
loader.assert_awaited_once()
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_swr_requires_server_runtime(monkeypatch):
|
||||
monkeypatch.setattr(cache_module, "_api_swr", None)
|
||||
|
||||
with pytest.raises(RuntimeError, match="Cache is only available server-side"):
|
||||
await cache_module.swr(
|
||||
"test-key",
|
||||
AsyncMock(return_value="unused"),
|
||||
fresh_for=timedelta(seconds=1),
|
||||
max_age=timedelta(seconds=10),
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_swr_defaults(monkeypatch):
|
||||
"""fresh_for defaults to 0, max_age defaults to 1 day."""
|
||||
loader = AsyncMock(return_value="val")
|
||||
forwarded = {}
|
||||
|
||||
async def fake_swr(_key, inner_loader, *, fresh_for, max_age, model): # noqa: ARG001
|
||||
forwarded["fresh_for"] = fresh_for
|
||||
forwarded["max_age"] = max_age
|
||||
return await inner_loader()
|
||||
|
||||
monkeypatch.setattr(cache_module, "_api_swr", fake_swr)
|
||||
|
||||
await cache_module.swr("k", loader)
|
||||
|
||||
assert forwarded["fresh_for"] == timedelta(0)
|
||||
assert forwarded["max_age"] == timedelta(days=1)
|
||||
Generated
+230
-258
@@ -36,116 +36,100 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "certifi"
|
||||
version = "2026.2.25"
|
||||
version = "2026.1.4"
|
||||
source = { registry = "https://pypi.org/simple" }
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||||
sdist = { url = "https://files.pythonhosted.org/packages/af/2d/7bf41579a8986e348fa033a31cdd0e4121114f6bce2457e8876010b092dd/certifi-2026.2.25.tar.gz", hash = "sha256:e887ab5cee78ea814d3472169153c2d12cd43b14bd03329a39a9c6e2e80bfba7", size = 155029, upload-time = "2026-02-25T02:54:17.342Z" }
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||||
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||||
wheels = [
|
||||
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|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "charset-normalizer"
|
||||
version = "3.4.6"
|
||||
version = "3.4.4"
|
||||
source = { registry = "https://pypi.org/simple" }
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sdist = { url = "https://files.pythonhosted.org/packages/7b/60/e3bec1881450851b087e301bedc3daa9377a4d45f1c26aa90b0b235e38aa/charset_normalizer-3.4.6.tar.gz", hash = "sha256:1ae6b62897110aa7c79ea2f5dd38d1abca6db663687c0b1ad9aed6f6bae3d9d6", size = 143363, upload-time = "2026-03-15T18:53:25.478Z" }
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|
||||
wheels = [
|
||||
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|
||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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|
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{ url = "https://files.pythonhosted.org/packages/63/d4/acad86ce012b42ce18a12f31ee2aa3cbeeb98664f865f05f68c882945913/uuid_utils-0.14.0-pp311-pypy311_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:3fd9112ca96978361201e669729784f26c71fecc9c13a7f8a07162c31bd4d1e2", size = 359217, upload-time = "2026-01-20T20:36:59.687Z" },
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]
|
||||
|
||||
[[package]]
|
||||
|
||||
Reference in New Issue
Block a user