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"""Async client exports."""
from langgraph_sdk._async.assistants import AssistantsClient
from langgraph_sdk._async.client import LangGraphClient, get_client
from langgraph_sdk._async.cron import CronClient
from langgraph_sdk._async.http import HttpClient
from langgraph_sdk._async.runs import RunsClient
from langgraph_sdk._async.store import StoreClient
from langgraph_sdk._async.threads import ThreadsClient
__all__ = [
"AssistantsClient",
"CronClient",
"HttpClient",
"LangGraphClient",
"RunsClient",
"StoreClient",
"ThreadsClient",
"get_client",
]

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"""Async client for managing assistants in LangGraph."""
from __future__ import annotations
from collections.abc import Mapping
from typing import Any, Literal, cast, overload
import httpx
from langgraph_sdk._async.http import HttpClient
from langgraph_sdk.schema import (
Assistant,
AssistantSelectField,
AssistantSortBy,
AssistantsSearchResponse,
AssistantVersion,
Config,
Context,
GraphSchema,
Json,
OnConflictBehavior,
QueryParamTypes,
SortOrder,
Subgraphs,
)
class AssistantsClient:
"""Client for managing assistants in LangGraph.
This class provides methods to interact with assistants,
which are versioned configurations of your graph.
???+ example "Example"
```python
client = get_client(url="http://localhost:2024")
assistant = await client.assistants.get("assistant_id_123")
```
"""
def __init__(self, http: HttpClient) -> None:
self.http = http
async def get(
self,
assistant_id: str,
*,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> Assistant:
"""Get an assistant by ID.
Args:
assistant_id: The ID of the assistant to get.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
Assistant: Assistant Object.
???+ example "Example Usage"
```python
assistant = await client.assistants.get(
assistant_id="my_assistant_id"
)
print(assistant)
```
```shell
----------------------------------------------------
{
'assistant_id': 'my_assistant_id',
'graph_id': 'agent',
'created_at': '2024-06-25T17:10:33.109781+00:00',
'updated_at': '2024-06-25T17:10:33.109781+00:00',
'config': {},
'metadata': {'created_by': 'system'},
'version': 1,
'name': 'my_assistant'
}
```
"""
return await self.http.get(
f"/assistants/{assistant_id}", headers=headers, params=params
)
async def get_graph(
self,
assistant_id: str,
*,
xray: int | bool = False,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> dict[str, list[dict[str, Any]]]:
"""Get the graph of an assistant by ID.
Args:
assistant_id: The ID of the assistant to get the graph of.
xray: Include graph representation of subgraphs. If an integer value is provided, only subgraphs with a depth less than or equal to the value will be included.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
Graph: The graph information for the assistant in JSON format.
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024")
graph_info = await client.assistants.get_graph(
assistant_id="my_assistant_id"
)
print(graph_info)
```
```shell
--------------------------------------------------------------------------------------------------------------------------
{
'nodes':
[
{'id': '__start__', 'type': 'schema', 'data': '__start__'},
{'id': '__end__', 'type': 'schema', 'data': '__end__'},
{'id': 'agent','type': 'runnable','data': {'id': ['langgraph', 'utils', 'RunnableCallable'],'name': 'agent'}},
],
'edges':
[
{'source': '__start__', 'target': 'agent'},
{'source': 'agent','target': '__end__'}
]
}
```
"""
query_params = {"xray": xray}
if params:
query_params.update(params)
return await self.http.get(
f"/assistants/{assistant_id}/graph", params=query_params, headers=headers
)
async def get_schemas(
self,
assistant_id: str,
*,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> GraphSchema:
"""Get the schemas of an assistant by ID.
Args:
assistant_id: The ID of the assistant to get the schema of.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
GraphSchema: The graph schema for the assistant.
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024")
schema = await client.assistants.get_schemas(
assistant_id="my_assistant_id"
)
print(schema)
```
```shell
----------------------------------------------------------------------------------------------------------------------------
{
'graph_id': 'agent',
'state_schema':
{
'title': 'LangGraphInput',
'$ref': '#/definitions/AgentState',
'definitions':
{
'BaseMessage':
{
'title': 'BaseMessage',
'description': 'Base abstract Message class. Messages are the inputs and outputs of ChatModels.',
'type': 'object',
'properties':
{
'content':
{
'title': 'Content',
'anyOf': [
{'type': 'string'},
{'type': 'array','items': {'anyOf': [{'type': 'string'}, {'type': 'object'}]}}
]
},
'additional_kwargs':
{
'title': 'Additional Kwargs',
'type': 'object'
},
'response_metadata':
{
'title': 'Response Metadata',
'type': 'object'
},
'type':
{
'title': 'Type',
'type': 'string'
},
'name':
{
'title': 'Name',
'type': 'string'
},
'id':
{
'title': 'Id',
'type': 'string'
}
},
'required': ['content', 'type']
},
'AgentState':
{
'title': 'AgentState',
'type': 'object',
'properties':
{
'messages':
{
'title': 'Messages',
'type': 'array',
'items': {'$ref': '#/definitions/BaseMessage'}
}
},
'required': ['messages']
}
}
},
'context_schema':
{
'title': 'Context',
'type': 'object',
'properties':
{
'model_name':
{
'title': 'Model Name',
'enum': ['anthropic', 'openai'],
'type': 'string'
}
}
}
}
```
"""
return await self.http.get(
f"/assistants/{assistant_id}/schemas", headers=headers, params=params
)
async def get_subgraphs(
self,
assistant_id: str,
namespace: str | None = None,
recurse: bool = False,
*,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> Subgraphs:
"""Get the schemas of an assistant by ID.
Args:
assistant_id: The ID of the assistant to get the schema of.
namespace: Optional namespace to filter by.
recurse: Whether to recursively get subgraphs.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
Subgraphs: The graph schema for the assistant.
"""
get_params = {"recurse": recurse}
if params:
get_params = {**get_params, **dict(params)}
if namespace is not None:
return await self.http.get(
f"/assistants/{assistant_id}/subgraphs/{namespace}",
params=get_params,
headers=headers,
)
else:
return await self.http.get(
f"/assistants/{assistant_id}/subgraphs",
params=get_params,
headers=headers,
)
async def create(
self,
graph_id: str | None,
config: Config | None = None,
*,
context: Context | None = None,
metadata: Json = None,
assistant_id: str | None = None,
if_exists: OnConflictBehavior | None = None,
name: str | None = None,
headers: Mapping[str, str] | None = None,
description: str | None = None,
params: QueryParamTypes | None = None,
) -> Assistant:
"""Create a new assistant.
Useful when graph is configurable and you want to create different assistants based on different configurations.
Args:
graph_id: The ID of the graph the assistant should use. The graph ID is normally set in your langgraph.json configuration.
config: Configuration to use for the graph.
metadata: Metadata to add to assistant.
context: Static context to add to the assistant.
!!! version-added "Added in version 0.6.0"
assistant_id: Assistant ID to use, will default to a random UUID if not provided.
if_exists: How to handle duplicate creation. Defaults to 'raise' under the hood.
Must be either 'raise' (raise error if duplicate), or 'do_nothing' (return existing assistant).
name: The name of the assistant. Defaults to 'Untitled' under the hood.
headers: Optional custom headers to include with the request.
description: Optional description of the assistant.
The description field is available for langgraph-api server version>=0.0.45
params: Optional query parameters to include with the request.
Returns:
Assistant: The created assistant.
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024")
assistant = await client.assistants.create(
graph_id="agent",
context={"model_name": "openai"},
metadata={"number":1},
assistant_id="my-assistant-id",
if_exists="do_nothing",
name="my_name"
)
```
"""
payload: dict[str, Any] = {
"graph_id": graph_id,
}
if config:
payload["config"] = config
if context:
payload["context"] = context
if metadata:
payload["metadata"] = metadata
if assistant_id:
payload["assistant_id"] = assistant_id
if if_exists:
payload["if_exists"] = if_exists
if name:
payload["name"] = name
if description:
payload["description"] = description
return await self.http.post(
"/assistants", json=payload, headers=headers, params=params
)
async def update(
self,
assistant_id: str,
*,
graph_id: str | None = None,
config: Config | None = None,
context: Context | None = None,
metadata: Json = None,
name: str | None = None,
headers: Mapping[str, str] | None = None,
description: str | None = None,
params: QueryParamTypes | None = None,
) -> Assistant:
"""Update an assistant.
Use this to point to a different graph, update the configuration, or change the metadata of an assistant.
Args:
assistant_id: Assistant to update.
graph_id: The ID of the graph the assistant should use.
The graph ID is normally set in your langgraph.json configuration. If `None`, assistant will keep pointing to same graph.
config: Configuration to use for the graph.
context: Static context to add to the assistant.
!!! version-added "Added in version 0.6.0"
metadata: Metadata to merge with existing assistant metadata.
name: The new name for the assistant.
headers: Optional custom headers to include with the request.
description: Optional description of the assistant.
The description field is available for langgraph-api server version>=0.0.45
params: Optional query parameters to include with the request.
Returns:
The updated assistant.
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024")
assistant = await client.assistants.update(
assistant_id='e280dad7-8618-443f-87f1-8e41841c180f',
graph_id="other-graph",
context={"model_name": "anthropic"},
metadata={"number":2}
)
```
"""
payload: dict[str, Any] = {}
if graph_id:
payload["graph_id"] = graph_id
if config is not None:
payload["config"] = config
if context is not None:
payload["context"] = context
if metadata:
payload["metadata"] = metadata
if name:
payload["name"] = name
if description:
payload["description"] = description
return await self.http.patch(
f"/assistants/{assistant_id}",
json=payload,
headers=headers,
params=params,
)
async def delete(
self,
assistant_id: str,
*,
delete_threads: bool = False,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> None:
"""Delete an assistant.
Args:
assistant_id: The assistant ID to delete.
delete_threads: If true, delete all threads with `metadata.assistant_id`
matching this assistant, along with runs and checkpoints belonging to
those threads.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
`None`
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024")
await client.assistants.delete(
assistant_id="my_assistant_id"
)
```
"""
query_params: dict[str, Any] = {}
if delete_threads:
query_params["delete_threads"] = True
if params:
query_params.update(params)
await self.http.delete(
f"/assistants/{assistant_id}",
headers=headers,
params=query_params or None,
)
@overload
async def search(
self,
*,
metadata: Json = None,
graph_id: str | None = None,
name: str | None = None,
limit: int = 10,
offset: int = 0,
sort_by: AssistantSortBy | None = None,
sort_order: SortOrder | None = None,
select: list[AssistantSelectField] | None = None,
response_format: Literal["object"],
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> AssistantsSearchResponse: ...
@overload
async def search(
self,
*,
metadata: Json = None,
graph_id: str | None = None,
name: str | None = None,
limit: int = 10,
offset: int = 0,
sort_by: AssistantSortBy | None = None,
sort_order: SortOrder | None = None,
select: list[AssistantSelectField] | None = None,
response_format: Literal["array"] = "array",
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> list[Assistant]: ...
async def search(
self,
*,
metadata: Json = None,
graph_id: str | None = None,
name: str | None = None,
limit: int = 10,
offset: int = 0,
sort_by: AssistantSortBy | None = None,
sort_order: SortOrder | None = None,
select: list[AssistantSelectField] | None = None,
response_format: Literal["array", "object"] = "array",
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> AssistantsSearchResponse | list[Assistant]:
"""Search for assistants.
Args:
metadata: Metadata to filter by. Exact match filter for each KV pair.
graph_id: The ID of the graph to filter by.
The graph ID is normally set in your langgraph.json configuration.
name: The name of the assistant to filter by.
The filtering logic will match assistants where 'name' is a substring (case insensitive) of the assistant name.
limit: The maximum number of results to return.
offset: The number of results to skip.
sort_by: The field to sort by.
sort_order: The order to sort by.
select: Specific assistant fields to include in the response.
response_format: Controls the response shape. Use `"array"` (default)
to return a bare list of assistants, or `"object"` to return
a mapping containing assistants plus pagination metadata.
Defaults to "array", though this default will be changed to "object" in a future release.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
A list of assistants (when `response_format="array"`) or a mapping
with the assistants and the next pagination cursor (when
`response_format="object"`).
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024")
response = await client.assistants.search(
metadata = {"name":"my_name"},
graph_id="my_graph_id",
limit=5,
offset=5,
response_format="object"
)
next_cursor = response["next"]
assistants = response["assistants"]
```
"""
if response_format not in ("array", "object"):
raise ValueError(
f"response_format must be 'array' or 'object', got {response_format!r}"
)
payload: dict[str, Any] = {
"limit": limit,
"offset": offset,
}
if metadata:
payload["metadata"] = metadata
if graph_id:
payload["graph_id"] = graph_id
if name:
payload["name"] = name
if sort_by:
payload["sort_by"] = sort_by
if sort_order:
payload["sort_order"] = sort_order
if select:
payload["select"] = select
next_cursor: str | None = None
def capture_pagination(response: httpx.Response) -> None:
nonlocal next_cursor
next_cursor = response.headers.get("X-Pagination-Next")
assistants = cast(
list[Assistant],
await self.http.post(
"/assistants/search",
json=payload,
headers=headers,
params=params,
on_response=capture_pagination if response_format == "object" else None,
),
)
if response_format == "object":
return {"assistants": assistants, "next": next_cursor}
return assistants
async def count(
self,
*,
metadata: Json = None,
graph_id: str | None = None,
name: str | None = None,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> int:
"""Count assistants matching filters.
Args:
metadata: Metadata to filter by. Exact match for each key/value.
graph_id: Optional graph id to filter by.
name: Optional name to filter by.
The filtering logic will match assistants where 'name' is a substring (case insensitive) of the assistant name.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
int: Number of assistants matching the criteria.
"""
payload: dict[str, Any] = {}
if metadata:
payload["metadata"] = metadata
if graph_id:
payload["graph_id"] = graph_id
if name:
payload["name"] = name
return await self.http.post(
"/assistants/count", json=payload, headers=headers, params=params
)
async def get_versions(
self,
assistant_id: str,
metadata: Json = None,
limit: int = 10,
offset: int = 0,
*,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> list[AssistantVersion]:
"""List all versions of an assistant.
Args:
assistant_id: The assistant ID to get versions for.
metadata: Metadata to filter versions by. Exact match filter for each KV pair.
limit: The maximum number of versions to return.
offset: The number of versions to skip.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
A list of assistant versions.
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024")
assistant_versions = await client.assistants.get_versions(
assistant_id="my_assistant_id"
)
```
"""
payload: dict[str, Any] = {
"limit": limit,
"offset": offset,
}
if metadata:
payload["metadata"] = metadata
return await self.http.post(
f"/assistants/{assistant_id}/versions",
json=payload,
headers=headers,
params=params,
)
async def set_latest(
self,
assistant_id: str,
version: int,
*,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> Assistant:
"""Change the version of an assistant.
Args:
assistant_id: The assistant ID to delete.
version: The version to change to.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
Assistant Object.
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024")
new_version_assistant = await client.assistants.set_latest(
assistant_id="my_assistant_id",
version=3
)
```
"""
payload: dict[str, Any] = {"version": version}
return await self.http.post(
f"/assistants/{assistant_id}/latest",
json=payload,
headers=headers,
params=params,
)

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"""Async LangGraph client."""
from __future__ import annotations
import logging
import os
from collections.abc import Mapping
from types import TracebackType
import httpx
from langgraph_sdk._async.assistants import AssistantsClient
from langgraph_sdk._async.cron import CronClient
from langgraph_sdk._async.http import HttpClient
from langgraph_sdk._async.runs import RunsClient
from langgraph_sdk._async.store import StoreClient
from langgraph_sdk._async.threads import ThreadsClient
from langgraph_sdk._shared.types import TimeoutTypes
from langgraph_sdk._shared.utilities import (
NOT_PROVIDED,
_get_headers,
_registered_transports,
get_asgi_transport,
)
logger = logging.getLogger(__name__)
def get_client(
*,
url: str | None = None,
api_key: str | None = NOT_PROVIDED,
headers: Mapping[str, str] | None = None,
timeout: TimeoutTypes | None = None,
) -> LangGraphClient:
"""Create and configure a LangGraphClient.
The client provides programmatic access to LangSmith Deployment. It supports
both remote servers and local in-process connections (when running inside a LangGraph server).
Args:
url:
Base URL of the LangGraph API.
- If `None`, the client first attempts an in-process connection via ASGI transport.
If that fails, it defers registration until after app initialization. This
only works if the client is used from within the Agent server.
api_key:
API key for authentication. Can be:
- A string: use this exact API key
- `None`: explicitly skip loading from environment variables
- Not provided (default): auto-load from environment in this order:
1. `LANGGRAPH_API_KEY`
2. `LANGSMITH_API_KEY`
3. `LANGCHAIN_API_KEY`
headers:
Additional HTTP headers to include in requests. Merged with authentication headers.
timeout:
HTTP timeout configuration. May be:
- `httpx.Timeout` instance
- float (total seconds)
- tuple `(connect, read, write, pool)` in seconds
Defaults: connect=5, read=300, write=300, pool=5.
Returns:
LangGraphClient:
A top-level client exposing sub-clients for assistants, threads,
runs, and cron operations.
???+ example "Connect to a remote server:"
```python
from langgraph_sdk import get_client
# get top-level LangGraphClient
client = get_client(url="http://localhost:8123")
# example usage: client.<model>.<method_name>()
assistants = await client.assistants.get(assistant_id="some_uuid")
```
???+ example "Connect in-process to a running LangGraph server:"
```python
from langgraph_sdk import get_client
client = get_client(url=None)
async def my_node(...):
subagent_result = await client.runs.wait(
thread_id=None,
assistant_id="agent",
input={"messages": [{"role": "user", "content": "Foo"}]},
)
```
???+ example "Skip auto-loading API key from environment:"
```python
from langgraph_sdk import get_client
# Don't load API key from environment variables
client = get_client(
url="http://localhost:8123",
api_key=None
)
```
"""
transport: httpx.AsyncBaseTransport | None = None
if url is None:
url = "http://api"
if os.environ.get("__LANGGRAPH_DEFER_LOOPBACK_TRANSPORT") == "true":
transport = get_asgi_transport()(app=None, root_path="/noauth") # type: ignore[invalid-argument-type]
_registered_transports.append(transport)
else:
try:
from langgraph_api.server import app # type: ignore
transport = get_asgi_transport()(app, root_path="/noauth")
except Exception:
logger.debug(
"Failed to connect to in-process LangGraph server. Deferring configuration.",
exc_info=True,
)
transport = get_asgi_transport()(app=None, root_path="/noauth") # type: ignore[invalid-argument-type]
_registered_transports.append(transport)
if transport is None:
transport = httpx.AsyncHTTPTransport(retries=5)
client = httpx.AsyncClient(
base_url=url,
transport=transport,
timeout=(
httpx.Timeout(timeout) # type: ignore[arg-type]
if timeout is not None
else httpx.Timeout(connect=5, read=300, write=300, pool=5)
),
headers=_get_headers(api_key, headers),
)
return LangGraphClient(client)
class LangGraphClient:
"""Top-level client for LangGraph API.
Attributes:
assistants: Manages versioned configuration for your graphs.
threads: Handles (potentially) multi-turn interactions, such as conversational threads.
runs: Controls individual invocations of the graph.
crons: Manages scheduled operations.
store: Interfaces with persistent, shared data storage.
"""
def __init__(self, client: httpx.AsyncClient) -> None:
self.http = HttpClient(client)
self.assistants = AssistantsClient(self.http)
self.threads = ThreadsClient(self.http)
self.runs = RunsClient(self.http)
self.crons = CronClient(self.http)
self.store = StoreClient(self.http)
async def __aenter__(self) -> LangGraphClient:
"""Enter the async context manager."""
return self
async def __aexit__(
self,
exc_type: type[BaseException] | None,
exc_val: BaseException | None,
exc_tb: TracebackType | None,
) -> None:
"""Exit the async context manager."""
await self.aclose()
async def aclose(self) -> None:
"""Close the underlying HTTP client."""
if hasattr(self, "http"):
await self.http.client.aclose()

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"""Async client for managing recurrent runs (cron jobs) in LangGraph."""
from __future__ import annotations
import warnings
from collections.abc import Mapping, Sequence
from datetime import datetime
from typing import Any
from langgraph_sdk._async.http import HttpClient
from langgraph_sdk.schema import (
All,
Config,
Context,
Cron,
CronSelectField,
CronSortBy,
Durability,
Input,
OnCompletionBehavior,
QueryParamTypes,
Run,
SortOrder,
StreamMode,
)
class CronClient:
"""Client for managing recurrent runs (cron jobs) in LangGraph.
A run is a single invocation of an assistant with optional input, config, and context.
This client allows scheduling recurring runs to occur automatically.
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024"))
cron_job = await client.crons.create_for_thread(
thread_id="thread_123",
assistant_id="asst_456",
schedule="0 9 * * *",
input={"message": "Daily update"}
)
```
!!! note "Feature Availability"
The crons client functionality is not supported on all licenses.
Please check the relevant license documentation for the most up-to-date
details on feature availability.
"""
def __init__(self, http_client: HttpClient) -> None:
self.http = http_client
async def create_for_thread(
self,
thread_id: str,
assistant_id: str,
*,
schedule: str,
input: Input | None = None,
metadata: Mapping[str, Any] | None = None,
config: Config | None = None,
context: Context | None = None,
checkpoint_during: bool | None = None, # deprecated
interrupt_before: All | list[str] | None = None,
interrupt_after: All | list[str] | None = None,
webhook: str | None = None,
multitask_strategy: str | None = None,
end_time: datetime | None = None,
enabled: bool | None = None,
stream_mode: StreamMode | Sequence[StreamMode] | None = None,
stream_subgraphs: bool | None = None,
stream_resumable: bool | None = None,
durability: Durability | None = None,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> Run:
"""Create a cron job for a thread.
Args:
thread_id: the thread ID to run the cron job on.
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.
input: The input to the graph.
metadata: Metadata to assign to the cron job runs.
config: The configuration for the assistant.
context: Static context to add to the assistant.
!!! version-added "Added in version 0.6.0"
checkpoint_during: (deprecated) Whether to checkpoint during the run (or only at the end/interruption).
interrupt_before: Nodes to interrupt immediately before they get executed.
interrupt_after: Nodes to Nodes to interrupt immediately after they get executed.
webhook: Webhook to call after LangGraph API call is done.
multitask_strategy: Multitask strategy to use.
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.
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.
durability: Durability level for the run. Must be one of 'sync', 'async', or 'exit'.
"async" means checkpoints are persisted async while next graph step executes, replaces checkpoint_during=True
"sync" means checkpoints are persisted sync after graph step executes, replaces checkpoint_during=False
"exit" means checkpoints are only persisted when the run exits, does not save intermediate steps
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
The cron run.
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024")
cron_run = await client.crons.create_for_thread(
thread_id="my-thread-id",
assistant_id="agent",
schedule="27 15 * * *",
input={"messages": [{"role": "user", "content": "hello!"}]},
metadata={"name":"my_run"},
context={"model_name": "openai"},
interrupt_before=["node_to_stop_before_1","node_to_stop_before_2"],
interrupt_after=["node_to_stop_after_1","node_to_stop_after_2"],
webhook="https://my.fake.webhook.com",
multitask_strategy="interrupt",
enabled=True,
)
```
"""
if checkpoint_during is not None:
warnings.warn(
"`checkpoint_during` is deprecated and will be removed in a future version. Use `durability` instead.",
DeprecationWarning,
stacklevel=2,
)
payload = {
"schedule": schedule,
"input": input,
"config": config,
"metadata": metadata,
"context": context,
"assistant_id": assistant_id,
"checkpoint_during": checkpoint_during,
"interrupt_before": interrupt_before,
"interrupt_after": interrupt_after,
"webhook": webhook,
"end_time": end_time.isoformat() if end_time else None,
"enabled": enabled,
"stream_mode": stream_mode,
"stream_subgraphs": stream_subgraphs,
"stream_resumable": stream_resumable,
"durability": durability,
}
if multitask_strategy:
payload["multitask_strategy"] = multitask_strategy
payload = {k: v for k, v in payload.items() if v is not None}
return await self.http.post(
f"/threads/{thread_id}/runs/crons",
json=payload,
headers=headers,
params=params,
)
async def create(
self,
assistant_id: str,
*,
schedule: str,
input: Input | None = None,
metadata: Mapping[str, Any] | None = None,
config: Config | None = None,
context: Context | None = None,
checkpoint_during: bool | None = None, # deprecated
interrupt_before: All | list[str] | None = None,
interrupt_after: All | list[str] | None = None,
webhook: str | None = None,
on_run_completed: OnCompletionBehavior | None = None,
multitask_strategy: str | None = None,
end_time: datetime | None = None,
enabled: bool | None = None,
stream_mode: StreamMode | Sequence[StreamMode] | None = None,
stream_subgraphs: bool | None = None,
stream_resumable: bool | None = None,
durability: Durability | None = None,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> Run:
"""Create a cron run.
Args:
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.
input: The input to the graph.
metadata: Metadata to assign to the cron job runs.
config: The configuration for the assistant.
context: Static context to add to the assistant.
!!! version-added "Added in version 0.6.0"
checkpoint_during: (deprecated) Whether to checkpoint during the run (or only at the end/interruption).
interrupt_before: Nodes to interrupt immediately before they get executed.
interrupt_after: Nodes to Nodes to interrupt immediately after they get executed.
webhook: Webhook to call after LangGraph API call is done.
on_run_completed: What to do with the thread after the run completes.
Must be one of 'delete' (default) or 'keep'. 'delete' removes the thread
after execution. 'keep' creates a new thread for each execution but does not
clean them up. Clients are responsible for cleaning up kept threads.
multitask_strategy: Multitask strategy to use.
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.
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.
durability: Durability level for the run. Must be one of 'sync', 'async', or 'exit'.
"async" means checkpoints are persisted async while next graph step executes, replaces checkpoint_during=True
"sync" means checkpoints are persisted sync after graph step executes, replaces checkpoint_during=False
"exit" means checkpoints are only persisted when the run exits, does not save intermediate steps
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
The cron run.
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024")
cron_run = client.crons.create(
assistant_id="agent",
schedule="27 15 * * *",
input={"messages": [{"role": "user", "content": "hello!"}]},
metadata={"name":"my_run"},
context={"model_name": "openai"},
interrupt_before=["node_to_stop_before_1","node_to_stop_before_2"],
interrupt_after=["node_to_stop_after_1","node_to_stop_after_2"],
webhook="https://my.fake.webhook.com",
multitask_strategy="interrupt",
enabled=True,
)
```
"""
if checkpoint_during is not None:
warnings.warn(
"`checkpoint_during` is deprecated and will be removed in a future version. Use `durability` instead.",
DeprecationWarning,
stacklevel=2,
)
payload = {
"schedule": schedule,
"input": input,
"config": config,
"metadata": metadata,
"context": context,
"assistant_id": assistant_id,
"checkpoint_during": checkpoint_during,
"interrupt_before": interrupt_before,
"interrupt_after": interrupt_after,
"webhook": webhook,
"on_run_completed": on_run_completed,
"end_time": end_time.isoformat() if end_time else None,
"enabled": enabled,
"stream_mode": stream_mode,
"stream_subgraphs": stream_subgraphs,
"stream_resumable": stream_resumable,
"durability": durability,
}
if multitask_strategy:
payload["multitask_strategy"] = multitask_strategy
payload = {k: v for k, v in payload.items() if v is not None}
return await self.http.post(
"/runs/crons", json=payload, headers=headers, params=params
)
async def delete(
self,
cron_id: str,
*,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> None:
"""Delete a cron.
Args:
cron_id: The cron ID to delete.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
`None`
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024")
await client.crons.delete(
cron_id="cron_to_delete"
)
```
"""
await self.http.delete(f"/runs/crons/{cron_id}", headers=headers, params=params)
async def update(
self,
cron_id: str,
*,
schedule: str | None = None,
end_time: datetime | None = None,
input: Input | None = None,
metadata: Mapping[str, Any] | None = None,
config: Config | None = None,
context: Context | None = None,
webhook: str | None = None,
interrupt_before: All | list[str] | None = None,
interrupt_after: All | list[str] | None = None,
on_run_completed: OnCompletionBehavior | None = None,
enabled: bool | None = None,
stream_mode: StreamMode | Sequence[StreamMode] | None = None,
stream_subgraphs: bool | None = None,
stream_resumable: bool | None = None,
durability: Durability | None = None,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> Cron:
"""Update a cron job by ID.
Args:
cron_id: The cron ID to update.
schedule: The cron schedule to execute this job on.
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.
config: The configuration for the assistant.
context: Static context added to the assistant.
webhook: Webhook to call after LangGraph API call is done.
interrupt_before: Nodes to interrupt immediately before they get executed.
interrupt_after: Nodes to interrupt immediately after they get executed.
on_run_completed: What to do with the thread after the run completes.
Must be one of 'delete' or 'keep'. 'delete' removes the thread
after execution. 'keep' creates a new thread for each execution but does not
clean them up.
enabled: Enable or disable the cron job.
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.
durability: Durability level for the run. Must be one of 'sync', 'async', or 'exit'.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
The updated cron job.
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024")
updated_cron = await client.crons.update(
cron_id="1ef3cefa-4c09-6926-96d0-3dc97fd5e39b",
schedule="0 10 * * *",
enabled=False,
)
```
"""
payload = {
"schedule": schedule,
"end_time": end_time.isoformat() if end_time else None,
"input": input,
"metadata": metadata,
"config": config,
"context": context,
"webhook": webhook,
"interrupt_before": interrupt_before,
"interrupt_after": interrupt_after,
"on_run_completed": on_run_completed,
"enabled": enabled,
"stream_mode": stream_mode,
"stream_subgraphs": stream_subgraphs,
"stream_resumable": stream_resumable,
"durability": durability,
}
payload = {k: v for k, v in payload.items() if v is not None}
return await self.http.patch(
f"/runs/crons/{cron_id}",
json=payload,
headers=headers,
params=params,
)
async def search(
self,
*,
assistant_id: str | None = None,
thread_id: str | None = None,
enabled: bool | None = None,
limit: int = 10,
offset: int = 0,
sort_by: CronSortBy | None = None,
sort_order: SortOrder | None = None,
select: list[CronSelectField] | None = None,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> list[Cron]:
"""Get a list of cron jobs.
Args:
assistant_id: The assistant ID or graph name to search for.
thread_id: the thread ID to search for.
enabled: The enabled status to search for.
limit: The maximum number of results to return.
offset: The number of results to skip.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
The list of cron jobs returned by the search,
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024")
cron_jobs = await client.crons.search(
assistant_id="my_assistant_id",
thread_id="my_thread_id",
enabled=True,
limit=5,
offset=5,
)
print(cron_jobs)
```
```shell
----------------------------------------------------------
[
{
'cron_id': '1ef3cefa-4c09-6926-96d0-3dc97fd5e39b',
'assistant_id': 'my_assistant_id',
'thread_id': 'my_thread_id',
'user_id': None,
'payload':
{
'input': {'start_time': ''},
'schedule': '4 * * * *',
'assistant_id': 'my_assistant_id'
},
'schedule': '4 * * * *',
'next_run_date': '2024-07-25T17:04:00+00:00',
'end_time': None,
'created_at': '2024-07-08T06:02:23.073257+00:00',
'updated_at': '2024-07-08T06:02:23.073257+00:00'
}
]
```
"""
payload = {
"assistant_id": assistant_id,
"thread_id": thread_id,
"enabled": enabled,
"limit": limit,
"offset": offset,
}
if sort_by:
payload["sort_by"] = sort_by
if sort_order:
payload["sort_order"] = sort_order
if select:
payload["select"] = select
payload = {k: v for k, v in payload.items() if v is not None}
return await self.http.post(
"/runs/crons/search", json=payload, headers=headers, params=params
)
async def count(
self,
*,
assistant_id: str | None = None,
thread_id: str | None = None,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> int:
"""Count cron jobs matching filters.
Args:
assistant_id: Assistant ID to filter by.
thread_id: Thread ID to filter by.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
int: Number of crons matching the criteria.
"""
payload: dict[str, Any] = {}
if assistant_id:
payload["assistant_id"] = assistant_id
if thread_id:
payload["thread_id"] = thread_id
return await self.http.post(
"/runs/crons/count", json=payload, headers=headers, params=params
)

View File

@@ -0,0 +1,305 @@
"""HTTP client for async operations."""
from __future__ import annotations
import asyncio
import logging
import sys
import warnings
from collections.abc import AsyncIterator, Callable, Mapping
from typing import Any, cast
import httpx
import orjson
from langgraph_sdk._shared.utilities import _orjson_default
from langgraph_sdk.errors import _araise_for_status_typed
from langgraph_sdk.schema import QueryParamTypes, StreamPart
from langgraph_sdk.sse import SSEDecoder, aiter_lines_raw
logger = logging.getLogger(__name__)
class HttpClient:
"""Handle async requests to the LangGraph API.
Adds additional error messaging & content handling above the
provided httpx client.
Attributes:
client (httpx.AsyncClient): Underlying HTTPX async client.
"""
def __init__(self, client: httpx.AsyncClient) -> None:
self.client = client
async def get(
self,
path: str,
*,
params: QueryParamTypes | None = None,
headers: Mapping[str, str] | None = None,
on_response: Callable[[httpx.Response], None] | None = None,
) -> Any:
"""Send a `GET` request."""
r = await self.client.get(path, params=params, headers=headers)
if on_response:
on_response(r)
await _araise_for_status_typed(r)
return await _adecode_json(r)
async def post(
self,
path: str,
*,
json: dict[str, Any] | list | None,
params: QueryParamTypes | None = None,
headers: Mapping[str, str] | None = None,
on_response: Callable[[httpx.Response], None] | None = None,
) -> Any:
"""Send a `POST` request."""
if json is not None:
request_headers, content = await _aencode_json(json)
else:
request_headers, content = {}, b""
# Merge headers, with runtime headers taking precedence
if headers:
request_headers.update(headers)
r = await self.client.post(
path, headers=request_headers, content=content, params=params
)
if on_response:
on_response(r)
await _araise_for_status_typed(r)
return await _adecode_json(r)
async def put(
self,
path: str,
*,
json: dict,
params: QueryParamTypes | None = None,
headers: Mapping[str, str] | None = None,
on_response: Callable[[httpx.Response], None] | None = None,
) -> Any:
"""Send a `PUT` request."""
request_headers, content = await _aencode_json(json)
if headers:
request_headers.update(headers)
r = await self.client.put(
path, headers=request_headers, content=content, params=params
)
if on_response:
on_response(r)
await _araise_for_status_typed(r)
return await _adecode_json(r)
async def patch(
self,
path: str,
*,
json: dict,
params: QueryParamTypes | None = None,
headers: Mapping[str, str] | None = None,
on_response: Callable[[httpx.Response], None] | None = None,
) -> Any:
"""Send a `PATCH` request."""
request_headers, content = await _aencode_json(json)
if headers:
request_headers.update(headers)
r = await self.client.patch(
path, headers=request_headers, content=content, params=params
)
if on_response:
on_response(r)
await _araise_for_status_typed(r)
return await _adecode_json(r)
async def delete(
self,
path: str,
*,
json: Any | None = None,
params: QueryParamTypes | None = None,
headers: Mapping[str, str] | None = None,
on_response: Callable[[httpx.Response], None] | None = None,
) -> None:
"""Send a `DELETE` request."""
r = await self.client.request(
"DELETE", path, json=json, params=params, headers=headers
)
if on_response:
on_response(r)
await _araise_for_status_typed(r)
async def request_reconnect(
self,
path: str,
method: str,
*,
json: dict[str, Any] | None = None,
params: QueryParamTypes | None = None,
headers: Mapping[str, str] | None = None,
on_response: Callable[[httpx.Response], None] | None = None,
reconnect_limit: int = 5,
) -> Any:
"""Send a request that automatically reconnects to Location header."""
request_headers, content = await _aencode_json(json)
if headers:
request_headers.update(headers)
async with self.client.stream(
method, path, headers=request_headers, content=content, params=params
) as r:
if on_response:
on_response(r)
try:
r.raise_for_status()
except httpx.HTTPStatusError as e:
body = (await r.aread()).decode()
if sys.version_info >= (3, 11):
e.add_note(body)
else:
logger.error(f"Error from langgraph-api: {body}", exc_info=e)
raise e
loc = r.headers.get("location")
if reconnect_limit <= 0 or not loc:
return await _adecode_json(r)
try:
return await _adecode_json(r)
except httpx.HTTPError:
warnings.warn(
f"Request failed, attempting reconnect to Location: {loc}",
stacklevel=2,
)
await r.aclose()
return await self.request_reconnect(
loc,
"GET",
headers=request_headers,
# don't pass on_response so it's only called once
reconnect_limit=reconnect_limit - 1,
)
async def stream(
self,
path: str,
method: str,
*,
json: dict[str, Any] | None = None,
params: QueryParamTypes | None = None,
headers: Mapping[str, str] | None = None,
on_response: Callable[[httpx.Response], None] | None = None,
) -> AsyncIterator[StreamPart]:
"""Stream results using SSE."""
request_headers, content = await _aencode_json(json)
request_headers["Accept"] = "text/event-stream"
request_headers["Cache-Control"] = "no-store"
# Add runtime headers with precedence
if headers:
request_headers.update(headers)
reconnect_headers = {
key: value
for key, value in request_headers.items()
if key.lower() not in {"content-length", "content-type"}
}
last_event_id: str | None = None
reconnect_path: str | None = None
reconnect_attempts = 0
max_reconnect_attempts = 5
while True:
current_headers = dict(
request_headers if reconnect_path is None else reconnect_headers
)
if last_event_id is not None:
current_headers["Last-Event-ID"] = last_event_id
current_method = method if reconnect_path is None else "GET"
current_content = content if reconnect_path is None else None
current_params = params if reconnect_path is None else None
retry = False
async with self.client.stream(
current_method,
reconnect_path or path,
headers=current_headers,
content=current_content,
params=current_params,
) as res:
if reconnect_path is None and on_response:
on_response(res)
# check status
await _araise_for_status_typed(res)
# check content type
content_type = res.headers.get("content-type", "").partition(";")[0]
if "text/event-stream" not in content_type:
raise httpx.TransportError(
"Expected response header Content-Type to contain 'text/event-stream', "
f"got {content_type!r}"
)
reconnect_location = res.headers.get("location")
if reconnect_location:
reconnect_path = reconnect_location
# parse SSE
decoder = SSEDecoder()
try:
async for line in aiter_lines_raw(res):
sse = decoder.decode(line=cast("bytes", line).rstrip(b"\n"))
if sse is not None:
if decoder.last_event_id is not None:
last_event_id = decoder.last_event_id
if sse.event or sse.data is not None:
yield sse
except httpx.HTTPError:
# httpx.TransportError inherits from HTTPError, so transient
# disconnects during streaming land here.
if reconnect_path is None:
raise
retry = True
else:
if sse := decoder.decode(b""):
if decoder.last_event_id is not None:
last_event_id = decoder.last_event_id
if sse.event or sse.data is not None:
# decoder.decode(b"") flushes the in-flight event and may
# return an empty placeholder when there is no pending
# message. Skip these no-op events so the stream doesn't
# emit a trailing blank item after reconnects.
yield sse
if retry:
reconnect_attempts += 1
if reconnect_attempts > max_reconnect_attempts:
raise httpx.TransportError(
"Exceeded maximum SSE reconnection attempts"
)
continue
break
async def _aencode_json(json: Any) -> tuple[dict[str, str], bytes | None]:
if json is None:
return {}, None
body = await asyncio.get_running_loop().run_in_executor(
None,
orjson.dumps,
json,
_orjson_default,
orjson.OPT_SERIALIZE_NUMPY | orjson.OPT_NON_STR_KEYS,
)
content_length = str(len(body))
content_type = "application/json"
headers = {"Content-Length": content_length, "Content-Type": content_type}
return headers, body
async def _adecode_json(r: httpx.Response) -> Any:
body = await r.aread()
return (
await asyncio.get_running_loop().run_in_executor(None, orjson.loads, body)
if body
else None
)

File diff suppressed because it is too large Load Diff

View File

@@ -0,0 +1,313 @@
"""Async Store client for LangGraph SDK."""
from __future__ import annotations
from collections.abc import Mapping, Sequence
from typing import Any, Literal
from langgraph_sdk._async.http import HttpClient
from langgraph_sdk._shared.utilities import _provided_vals
from langgraph_sdk.schema import (
Item,
ListNamespaceResponse,
QueryParamTypes,
SearchItemsResponse,
)
class StoreClient:
"""Client for interacting with the graph's shared storage.
The Store provides a key-value storage system for persisting data across graph executions,
allowing for stateful operations and data sharing across threads.
???+ example "Example"
```python
client = get_client(url="http://localhost:2024")
await client.store.put_item(["users", "user123"], "mem-123451342", {"name": "Alice", "score": 100})
```
"""
def __init__(self, http: HttpClient) -> None:
self.http = http
async def put_item(
self,
namespace: Sequence[str],
/,
key: str,
value: Mapping[str, Any],
index: Literal[False] | list[str] | None = None,
ttl: int | None = None,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> None:
"""Store or update an item.
Args:
namespace: A list of strings representing the namespace path.
key: The unique identifier for the item within the namespace.
value: A dictionary containing the item's data.
index: Controls search indexing - None (use defaults), False (disable), or list of field paths to index.
ttl: Optional time-to-live in minutes for the item, or None for no expiration.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
`None`
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024")
await client.store.put_item(
["documents", "user123"],
key="item456",
value={"title": "My Document", "content": "Hello World"}
)
```
"""
for label in namespace:
if "." in label:
raise ValueError(
f"Invalid namespace label '{label}'. Namespace labels cannot contain periods ('.')."
)
payload = {
"namespace": namespace,
"key": key,
"value": value,
"index": index,
"ttl": ttl,
}
await self.http.put(
"/store/items", json=_provided_vals(payload), headers=headers, params=params
)
async def get_item(
self,
namespace: Sequence[str],
/,
key: str,
*,
refresh_ttl: bool | None = None,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> Item:
"""Retrieve a single item.
Args:
key: The unique identifier for the item.
namespace: Optional list of strings representing the namespace path.
refresh_ttl: Whether to refresh the TTL on this read operation. If `None`, uses the store's default behavior.
Returns:
Item: The retrieved item.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024")
item = await client.store.get_item(
["documents", "user123"],
key="item456",
)
print(item)
```
```shell
----------------------------------------------------------------
{
'namespace': ['documents', 'user123'],
'key': 'item456',
'value': {'title': 'My Document', 'content': 'Hello World'},
'created_at': '2024-07-30T12:00:00Z',
'updated_at': '2024-07-30T12:00:00Z'
}
```
"""
for label in namespace:
if "." in label:
raise ValueError(
f"Invalid namespace label '{label}'. Namespace labels cannot contain periods ('.')."
)
get_params = {"namespace": ".".join(namespace), "key": key}
if refresh_ttl is not None:
get_params["refresh_ttl"] = refresh_ttl
if params:
get_params = {**get_params, **dict(params)}
return await self.http.get("/store/items", params=get_params, headers=headers)
async def delete_item(
self,
namespace: Sequence[str],
/,
key: str,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> None:
"""Delete an item.
Args:
key: The unique identifier for the item.
namespace: Optional list of strings representing the namespace path.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
`None`
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024")
await client.store.delete_item(
["documents", "user123"],
key="item456",
)
```
"""
await self.http.delete(
"/store/items",
json={"namespace": namespace, "key": key},
headers=headers,
params=params,
)
async def search_items(
self,
namespace_prefix: Sequence[str],
/,
filter: Mapping[str, Any] | None = None,
limit: int = 10,
offset: int = 0,
query: str | None = None,
refresh_ttl: bool | None = None,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> SearchItemsResponse:
"""Search for items within a namespace prefix.
Args:
namespace_prefix: List of strings representing the namespace prefix.
filter: Optional dictionary of key-value pairs to filter results.
limit: Maximum number of items to return (default is 10).
offset: Number of items to skip before returning results (default is 0).
query: Optional query for natural language search.
refresh_ttl: Whether to refresh the TTL on items returned by this search. If `None`, uses the store's default behavior.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
A list of items matching the search criteria.
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024")
items = await client.store.search_items(
["documents"],
filter={"author": "John Doe"},
limit=5,
offset=0
)
print(items)
```
```shell
----------------------------------------------------------------
{
"items": [
{
"namespace": ["documents", "user123"],
"key": "item789",
"value": {
"title": "Another Document",
"author": "John Doe"
},
"created_at": "2024-07-30T12:00:00Z",
"updated_at": "2024-07-30T12:00:00Z"
},
# ... additional items ...
]
}
```
"""
payload = {
"namespace_prefix": namespace_prefix,
"filter": filter,
"limit": limit,
"offset": offset,
"query": query,
"refresh_ttl": refresh_ttl,
}
return await self.http.post(
"/store/items/search",
json=_provided_vals(payload),
headers=headers,
params=params,
)
async def list_namespaces(
self,
prefix: list[str] | None = None,
suffix: list[str] | None = None,
max_depth: int | None = None,
limit: int = 100,
offset: int = 0,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> ListNamespaceResponse:
"""List namespaces with optional match conditions.
Args:
prefix: Optional list of strings representing the prefix to filter namespaces.
suffix: Optional list of strings representing the suffix to filter namespaces.
max_depth: Optional integer specifying the maximum depth of namespaces to return.
limit: Maximum number of namespaces to return (default is 100).
offset: Number of namespaces to skip before returning results (default is 0).
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
A list of namespaces matching the criteria.
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024")
namespaces = await client.store.list_namespaces(
prefix=["documents"],
max_depth=3,
limit=10,
offset=0
)
print(namespaces)
----------------------------------------------------------------
[
["documents", "user123", "reports"],
["documents", "user456", "invoices"],
...
]
```
"""
payload = {
"prefix": prefix,
"suffix": suffix,
"max_depth": max_depth,
"limit": limit,
"offset": offset,
}
return await self.http.post(
"/store/namespaces",
json=_provided_vals(payload),
headers=headers,
params=params,
)

View File

@@ -0,0 +1,732 @@
"""Async client for managing threads in LangGraph."""
from __future__ import annotations
from collections.abc import AsyncIterator, Mapping, Sequence
from typing import Any
from langgraph_sdk._async.http import HttpClient
from langgraph_sdk.schema import (
Checkpoint,
Json,
OnConflictBehavior,
PruneStrategy,
QueryParamTypes,
SortOrder,
StreamPart,
Thread,
ThreadSelectField,
ThreadSortBy,
ThreadState,
ThreadStatus,
ThreadStreamMode,
ThreadUpdateStateResponse,
)
class ThreadsClient:
"""Client for managing threads in LangGraph.
A thread maintains the state of a graph across multiple interactions/invocations (aka runs).
It accumulates and persists the graph's state, allowing for continuity between separate
invocations of the graph.
???+ example "Example"
```python
client = get_client(url="http://localhost:2024"))
new_thread = await client.threads.create(metadata={"user_id": "123"})
```
"""
def __init__(self, http: HttpClient) -> None:
self.http = http
async def get(
self,
thread_id: str,
*,
include: Sequence[str] | None = None,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> Thread:
"""Get a thread by ID.
Args:
thread_id: The ID of the thread to get.
include: Additional fields to include in the response.
Supported values: `"ttl"`.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
Thread object.
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024")
thread = await client.threads.get(
thread_id="my_thread_id"
)
print(thread)
```
```shell
-----------------------------------------------------
{
'thread_id': 'my_thread_id',
'created_at': '2024-07-18T18:35:15.540834+00:00',
'updated_at': '2024-07-18T18:35:15.540834+00:00',
'metadata': {'graph_id': 'agent'}
}
```
"""
query_params: dict[str, Any] = {}
if include:
query_params["include"] = ",".join(include)
if params:
query_params.update(params)
return await self.http.get(
f"/threads/{thread_id}",
headers=headers,
params=query_params or None,
)
async def create(
self,
*,
metadata: Json = None,
thread_id: str | None = None,
if_exists: OnConflictBehavior | None = None,
supersteps: Sequence[dict[str, Sequence[dict[str, Any]]]] | None = None,
graph_id: str | None = None,
ttl: int | Mapping[str, Any] | None = None,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> Thread:
"""Create a new thread.
Args:
metadata: Metadata to add to thread.
thread_id: ID of thread.
If `None`, ID will be a randomly generated UUID.
if_exists: How to handle duplicate creation. Defaults to 'raise' under the hood.
Must be either 'raise' (raise error if duplicate), or 'do_nothing' (return existing thread).
supersteps: Apply a list of supersteps when creating a thread, each containing a sequence of updates.
Each update has `values` or `command` and `as_node`. Used for copying a thread between deployments.
graph_id: Optional graph ID to associate with the thread.
ttl: Optional time-to-live in minutes for the thread. You can pass an
integer (minutes) or a mapping with keys `ttl` and optional
`strategy` (defaults to "delete").
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
The created thread.
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024")
thread = await client.threads.create(
metadata={"number":1},
thread_id="my-thread-id",
if_exists="raise"
)
```
"""
payload: dict[str, Any] = {}
if thread_id:
payload["thread_id"] = thread_id
if metadata or graph_id:
payload["metadata"] = {
**(metadata or {}),
**({"graph_id": graph_id} if graph_id else {}),
}
if if_exists:
payload["if_exists"] = if_exists
if supersteps:
payload["supersteps"] = [
{
"updates": [
{
"values": u["values"],
"command": u.get("command"),
"as_node": u["as_node"],
}
for u in s["updates"]
]
}
for s in supersteps
]
if ttl is not None:
if isinstance(ttl, (int, float)):
payload["ttl"] = {"ttl": ttl, "strategy": "delete"}
else:
payload["ttl"] = ttl
return await self.http.post(
"/threads", json=payload, headers=headers, params=params
)
async def update(
self,
thread_id: str,
*,
metadata: Mapping[str, Any],
ttl: int | Mapping[str, Any] | None = None,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> Thread:
"""Update a thread.
Args:
thread_id: ID of thread to update.
metadata: Metadata to merge with existing thread metadata.
ttl: Optional time-to-live in minutes for the thread. You can pass an
integer (minutes) or a mapping with keys `ttl` and optional
`strategy` (defaults to "delete").
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
The created thread.
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024")
thread = await client.threads.update(
thread_id="my-thread-id",
metadata={"number":1},
ttl=43_200,
)
```
"""
payload: dict[str, Any] = {"metadata": metadata}
if ttl is not None:
if isinstance(ttl, (int, float)):
payload["ttl"] = {"ttl": ttl, "strategy": "delete"}
else:
payload["ttl"] = ttl
return await self.http.patch(
f"/threads/{thread_id}",
json=payload,
headers=headers,
params=params,
)
async def delete(
self,
thread_id: str,
*,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> None:
"""Delete a thread.
Args:
thread_id: The ID of the thread to delete.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
`None`
???+ example "Example Usage"
```python
client = get_client(url="http://localhost2024)
await client.threads.delete(
thread_id="my_thread_id"
)
```
"""
await self.http.delete(f"/threads/{thread_id}", headers=headers, params=params)
async def search(
self,
*,
metadata: Json = None,
values: Json = None,
ids: Sequence[str] | None = None,
status: ThreadStatus | None = None,
limit: int = 10,
offset: int = 0,
sort_by: ThreadSortBy | None = None,
sort_order: SortOrder | None = None,
select: list[ThreadSelectField] | None = None,
extract: dict[str, str] | None = None,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> list[Thread]:
"""Search for threads.
Args:
metadata: Thread metadata to filter on.
values: State values to filter on.
ids: List of thread IDs to filter by.
status: Thread status to filter on.
Must be one of 'idle', 'busy', 'interrupted' or 'error'.
limit: Limit on number of threads to return.
offset: Offset in threads table to start search from.
sort_by: Sort by field.
sort_order: Sort order.
select: List of fields to include in the response.
extract: Dictionary mapping aliases to JSONB paths to extract
from thread data. Paths use dot notation for nested keys and
bracket notation for array indices (e.g.,
`{"last_msg": "values.messages[-1]"}`). Extracted values are
returned in an `extracted` field on each thread. Maximum 10
paths per request.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
List of the threads matching the search parameters.
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024")
threads = await client.threads.search(
metadata={"number":1},
status="interrupted",
limit=15,
offset=5
)
```
"""
payload: dict[str, Any] = {
"limit": limit,
"offset": offset,
}
if metadata:
payload["metadata"] = metadata
if values:
payload["values"] = values
if ids:
payload["ids"] = ids
if status:
payload["status"] = status
if sort_by:
payload["sort_by"] = sort_by
if sort_order:
payload["sort_order"] = sort_order
if select:
payload["select"] = select
if extract:
payload["extract"] = extract
return await self.http.post(
"/threads/search",
json=payload,
headers=headers,
params=params,
)
async def count(
self,
*,
metadata: Json = None,
values: Json = None,
status: ThreadStatus | None = None,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> int:
"""Count threads matching filters.
Args:
metadata: Thread metadata to filter on.
values: State values to filter on.
status: Thread status to filter on.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
int: Number of threads matching the criteria.
"""
payload: dict[str, Any] = {}
if metadata:
payload["metadata"] = metadata
if values:
payload["values"] = values
if status:
payload["status"] = status
return await self.http.post(
"/threads/count", json=payload, headers=headers, params=params
)
async def copy(
self,
thread_id: str,
*,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> None:
"""Copy a thread.
Args:
thread_id: The ID of the thread to copy.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
`None`
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024)
await client.threads.copy(
thread_id="my_thread_id"
)
```
"""
return await self.http.post(
f"/threads/{thread_id}/copy", json=None, headers=headers, params=params
)
async def prune(
self,
thread_ids: Sequence[str],
*,
strategy: PruneStrategy = "delete",
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> dict[str, Any]:
"""Prune threads by ID.
Args:
thread_ids: List of thread IDs to prune.
strategy: The prune strategy. `"delete"` removes threads entirely.
`"keep_latest"` prunes old checkpoints but keeps threads and their
latest state. Defaults to `"delete"`.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
A dict containing `pruned_count` (number of threads pruned).
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024")
result = await client.threads.prune(
thread_ids=["thread_1", "thread_2"],
)
print(result) # {'pruned_count': 2}
```
"""
payload: dict[str, Any] = {
"thread_ids": thread_ids,
}
if strategy != "delete":
payload["strategy"] = strategy
return await self.http.post(
"/threads/prune", json=payload, headers=headers, params=params
)
async def get_state(
self,
thread_id: str,
checkpoint: Checkpoint | None = None,
checkpoint_id: str | None = None, # deprecated
*,
subgraphs: bool = False,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> ThreadState:
"""Get the state of a thread.
Args:
thread_id: The ID of the thread to get the state of.
checkpoint: The checkpoint to get the state of.
checkpoint_id: (deprecated) The checkpoint ID to get the state of.
subgraphs: Include subgraphs states.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
The thread of the state.
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024)
thread_state = await client.threads.get_state(
thread_id="my_thread_id",
checkpoint_id="my_checkpoint_id"
)
print(thread_state)
```
```shell
----------------------------------------------------------------------------------------------------------------------------------------------------------------------
{
'values': {
'messages': [
{
'content': 'how are you?',
'additional_kwargs': {},
'response_metadata': {},
'type': 'human',
'name': None,
'id': 'fe0a5778-cfe9-42ee-b807-0adaa1873c10',
'example': False
},
{
'content': "I'm doing well, thanks for asking! I'm an AI assistant created by Anthropic to be helpful, honest, and harmless.",
'additional_kwargs': {},
'response_metadata': {},
'type': 'ai',
'name': None,
'id': 'run-159b782c-b679-4830-83c6-cef87798fe8b',
'example': False,
'tool_calls': [],
'invalid_tool_calls': [],
'usage_metadata': None
}
]
},
'next': [],
'checkpoint':
{
'thread_id': 'e2496803-ecd5-4e0c-a779-3226296181c2',
'checkpoint_ns': '',
'checkpoint_id': '1ef4a9b8-e6fb-67b1-8001-abd5184439d1'
}
'metadata':
{
'step': 1,
'run_id': '1ef4a9b8-d7da-679a-a45a-872054341df2',
'source': 'loop',
'writes':
{
'agent':
{
'messages': [
{
'id': 'run-159b782c-b679-4830-83c6-cef87798fe8b',
'name': None,
'type': 'ai',
'content': "I'm doing well, thanks for asking! I'm an AI assistant created by Anthropic to be helpful, honest, and harmless.",
'example': False,
'tool_calls': [],
'usage_metadata': None,
'additional_kwargs': {},
'response_metadata': {},
'invalid_tool_calls': []
}
]
}
},
'user_id': None,
'graph_id': 'agent',
'thread_id': 'e2496803-ecd5-4e0c-a779-3226296181c2',
'created_by': 'system',
'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca'},
'created_at': '2024-07-25T15:35:44.184703+00:00',
'parent_config':
{
'thread_id': 'e2496803-ecd5-4e0c-a779-3226296181c2',
'checkpoint_ns': '',
'checkpoint_id': '1ef4a9b8-d80d-6fa7-8000-9300467fad0f'
}
}
```
"""
if checkpoint:
return await self.http.post(
f"/threads/{thread_id}/state/checkpoint",
json={"checkpoint": checkpoint, "subgraphs": subgraphs},
headers=headers,
params=params,
)
elif checkpoint_id:
get_params = {"subgraphs": subgraphs}
if params:
get_params = {**get_params, **dict(params)}
return await self.http.get(
f"/threads/{thread_id}/state/{checkpoint_id}",
params=get_params,
headers=headers,
)
else:
get_params = {"subgraphs": subgraphs}
if params:
get_params = {**get_params, **dict(params)}
return await self.http.get(
f"/threads/{thread_id}/state",
params=get_params,
headers=headers,
)
async def update_state(
self,
thread_id: str,
values: dict[str, Any] | Sequence[dict] | None,
*,
as_node: str | None = None,
checkpoint: Checkpoint | None = None,
checkpoint_id: str | None = None, # deprecated
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> ThreadUpdateStateResponse:
"""Update the state of a thread.
Args:
thread_id: The ID of the thread to update.
values: The values to update the state with.
as_node: Update the state as if this node had just executed.
checkpoint: The checkpoint to update the state of.
checkpoint_id: (deprecated) The checkpoint ID to update the state of.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
Response after updating a thread's state.
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024)
response = await client.threads.update_state(
thread_id="my_thread_id",
values={"messages":[{"role": "user", "content": "hello!"}]},
as_node="my_node",
)
print(response)
```
```shell
----------------------------------------------------------------------------------------------------------------------------------------------------------------------
{
'checkpoint': {
'thread_id': 'e2496803-ecd5-4e0c-a779-3226296181c2',
'checkpoint_ns': '',
'checkpoint_id': '1ef4a9b8-e6fb-67b1-8001-abd5184439d1',
'checkpoint_map': {}
}
}
```
"""
payload: dict[str, Any] = {
"values": values,
}
if checkpoint_id:
payload["checkpoint_id"] = checkpoint_id
if checkpoint:
payload["checkpoint"] = checkpoint
if as_node:
payload["as_node"] = as_node
return await self.http.post(
f"/threads/{thread_id}/state", json=payload, headers=headers, params=params
)
async def get_history(
self,
thread_id: str,
*,
limit: int = 10,
before: str | Checkpoint | None = None,
metadata: Mapping[str, Any] | None = None,
checkpoint: Checkpoint | None = None,
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> list[ThreadState]:
"""Get the state history of a thread.
Args:
thread_id: The ID of the thread to get the state history for.
checkpoint: Return states for this subgraph. If empty defaults to root.
limit: The maximum number of states to return.
before: Return states before this checkpoint.
metadata: Filter states by metadata key-value pairs.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
The state history of the thread.
???+ example "Example Usage"
```python
client = get_client(url="http://localhost:2024)
thread_state = await client.threads.get_history(
thread_id="my_thread_id",
limit=5,
)
```
"""
payload: dict[str, Any] = {
"limit": limit,
}
if before:
payload["before"] = before
if metadata:
payload["metadata"] = metadata
if checkpoint:
payload["checkpoint"] = checkpoint
return await self.http.post(
f"/threads/{thread_id}/history",
json=payload,
headers=headers,
params=params,
)
async def join_stream(
self,
thread_id: str,
*,
last_event_id: str | None = None,
stream_mode: ThreadStreamMode | Sequence[ThreadStreamMode] = "run_modes",
headers: Mapping[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> AsyncIterator[StreamPart]:
"""Get a stream of events for a thread.
Args:
thread_id: The ID of the thread to get the stream for.
last_event_id: The ID of the last event to get.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
An iterator of stream parts.
???+ example "Example Usage"
```python
for chunk in client.threads.join_stream(
thread_id="my_thread_id",
last_event_id="my_event_id",
):
print(chunk)
```
"""
query_params = {
"stream_mode": stream_mode,
}
if params:
query_params.update(params)
return self.http.stream(
f"/threads/{thread_id}/stream",
"GET",
headers={
**({"Last-Event-ID": last_event_id} if last_event_id else {}),
**(headers or {}),
},
params=query_params,
)