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19
Commits
| Author | SHA1 | Date | |
|---|---|---|---|
 Sydney Runkle
|
f26ca07716 | ||
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Sydney Runkle
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b250823532 | ||
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Sydney Runkle
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120d34303d | ||
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Sydney Runkle
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6ff9e4a764 | ||
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Sydney Runkle
|
3c36d2e2c8 | ||
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Sydney Runkle
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f6d0382d66 | ||
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Sydney Runkle
|
0386fe5f6a | ||
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Sydney Runkle
|
b11ece823b | ||
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Nuno Campos
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46ce6ad927 | ||
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Nuno Campos
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0c929e62eb | ||
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Nuno Campos
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88c434048f | ||
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Nuno Campos
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f67a089a68 | ||
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Harrison Chase
|
cc97fad7e5 | ||
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Nuno Campos
|
75c73369a3 | ||
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Nuno Campos
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fdbcc07381 | ||
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Harrison Chase
|
80e19ecf4d | ||
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Nuno Campos
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54272afe01 | ||
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Nuno Campos
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e1aeb24a4e | ||
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Nuno Campos
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a51c0bfa31 |
@@ -99,8 +99,8 @@ Starting from the `LangGraph Platform` view...
|
||||
1. In the top-right corner, select the gear icon (`Deployment Settings`).
|
||||
1. Update the `Git Branch` to the desired branch.
|
||||
1. Check/uncheck checkbox to `Automatically update deployment on push to branch`.
|
||||
1. Branch creation/deletion and tag creation/deletion events will not trigger an update. Only pushes to an existing branch will trigger an update.
|
||||
1. Pushes in quick succession to a branch will queue subsequent updates. Once a build completes, the most recent commit will begin building and the other queued builds will be skipped.
|
||||
1. Branch creation/deletion and tag creation/deletion events will not trigger an update. Only pushes to an existing branch will trigger an update.
|
||||
1. Pushes in quick succession to a branch will not trigger subsequent updates. In the future, this functionality may be changed/improved.
|
||||
|
||||
## Add or Remove GitHub Repositories
|
||||
|
||||
|
||||
@@ -1520,73 +1520,6 @@
|
||||
}
|
||||
}
|
||||
},
|
||||
"/threads/{thread_id}/stream": {
|
||||
"get": {
|
||||
"tags": [
|
||||
"Threads"
|
||||
],
|
||||
"summary": "Join Thread Stream",
|
||||
"description": "This endpoint streams output in real-time from a thread. The stream will include the output of each run executed sequentially on the thread and will remain open indefinitely. It is the responsibility of the calling client to close the connection.",
|
||||
"operationId": "join_thread_stream_threads__thread_id__stream_get",
|
||||
"parameters": [
|
||||
{
|
||||
"description": "The ID of the thread.",
|
||||
"required": true,
|
||||
"schema": {
|
||||
"type": "string",
|
||||
"format": "uuid",
|
||||
"title": "Thread Id",
|
||||
"description": "The ID of the thread."
|
||||
},
|
||||
"name": "thread_id",
|
||||
"in": "path"
|
||||
},
|
||||
{
|
||||
"required": false,
|
||||
"schema": {
|
||||
"type": "string",
|
||||
"title": "Last Event ID",
|
||||
"description": "The ID of the last event received. Used to resume streaming from a specific point. Pass '-' to resume from the beginning."
|
||||
},
|
||||
"name": "Last-Event-ID",
|
||||
"in": "header"
|
||||
}
|
||||
],
|
||||
"responses": {
|
||||
"200": {
|
||||
"description": "Success",
|
||||
"content": {
|
||||
"text/event-stream": {
|
||||
"schema": {
|
||||
"type": "string",
|
||||
"description": "The server will send a stream of events in SSE format.\n\n**Example event**:\n\nid: 1\n\nevent: message\n\ndata: {}"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"404": {
|
||||
"description": "Not Found",
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {
|
||||
"$ref": "#/components/schemas/ErrorResponse"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"422": {
|
||||
"description": "Validation Error",
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {
|
||||
"$ref": "#/components/schemas/ErrorResponse"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"/threads/{thread_id}/runs": {
|
||||
"get": {
|
||||
"tags": [
|
||||
|
||||
@@ -1040,7 +1040,7 @@ def node_a(state: State, runtime: Runtime[ContextSchema]):
|
||||
...
|
||||
```
|
||||
|
||||
See [this guide](../how-tos/graph-api.md#add-runtime-configuration) for a full breakdown on configuration.
|
||||
See [this guide](../how-tos/graph-api.ipynb#add-runtime-configuration) for a full breakdown on configuration.
|
||||
:::
|
||||
|
||||
:::js
|
||||
|
||||
@@ -1 +1 @@
|
||||
__version__ = "0.4.0"
|
||||
__version__ = "0.3.8"
|
||||
|
||||
@@ -357,8 +357,6 @@ class HttpConfig(TypedDict, total=False):
|
||||
|
||||
You can include or exclude headers as configurable values to condition your
|
||||
agent's behavior or permissions on a request's headers."""
|
||||
logging_headers: Optional[ConfigurableHeaderConfig]
|
||||
"""Optional. Defines which headers are excluded from logging."""
|
||||
|
||||
|
||||
class Config(TypedDict, total=False):
|
||||
|
||||
@@ -19,8 +19,8 @@ dependencies = [
|
||||
path = "langgraph_cli/__init__.py"
|
||||
[project.optional-dependencies]
|
||||
inmem = [
|
||||
"langgraph-api>=0.3,<0.5.0 ; python_version >= '3.11'",
|
||||
"langgraph-runtime-inmem>=0.7 ; python_version >= '3.11'",
|
||||
"langgraph-api>=0.2.120,<0.4.0 ; python_version >= '3.11'",
|
||||
"langgraph-runtime-inmem>=0.6.8 ; python_version >= '3.11'",
|
||||
"python-dotenv>=0.8.0",
|
||||
]
|
||||
|
||||
|
||||
@@ -576,17 +576,6 @@
|
||||
"disable_threads": {
|
||||
"type": "boolean",
|
||||
"description": "Optional. If True, /threads routes are removed.\n\nDefault is False.\n"
|
||||
},
|
||||
"logging_headers": {
|
||||
"anyOf": [
|
||||
{
|
||||
"$ref": "#/$defs/ConfigurableHeaderConfig"
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"description": "Optional. Defines which headers are excluded from logging."
|
||||
}
|
||||
},
|
||||
"required": []
|
||||
|
||||
@@ -576,17 +576,6 @@
|
||||
"disable_threads": {
|
||||
"type": "boolean",
|
||||
"description": "Optional. If True, /threads routes are removed.\n\nDefault is False.\n"
|
||||
},
|
||||
"logging_headers": {
|
||||
"anyOf": [
|
||||
{
|
||||
"$ref": "#/$defs/ConfigurableHeaderConfig"
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"description": "Optional. Defines which headers are excluded from logging."
|
||||
}
|
||||
},
|
||||
"required": []
|
||||
|
||||
Generated
+40
-40
@@ -489,7 +489,7 @@ wheels = [
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|
||||
[[package]]
|
||||
name = "langgraph-api"
|
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version = "0.4.1"
|
||||
version = "0.3.0"
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source = { registry = "https://pypi.org/simple" }
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dependencies = [
|
||||
{ name = "cloudpickle", marker = "python_full_version >= '3.11'" },
|
||||
@@ -512,9 +512,9 @@ dependencies = [
|
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{ name = "uvicorn", marker = "python_full_version >= '3.11'" },
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{ name = "watchfiles", marker = "python_full_version >= '3.11'" },
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]
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wheels = [
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{ url = "https://files.pythonhosted.org/packages/06/34/cdbb0b5abf603fd01c91a63c9436fbe733f56cae448f42c7a1c7e3f4508e/langgraph_api-0.3.0-py3-none-any.whl", hash = "sha256:b76a7ced3bb559560b42a8d8f3cc7cff638c2022d0881d476caa1d511fb36a2e", size = 206012, upload-time = "2025-08-21T00:49:26.917Z" },
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|
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[[package]]
|
||||
@@ -561,8 +561,8 @@ dev = [
|
||||
[package.metadata]
|
||||
requires-dist = [
|
||||
{ name = "click", specifier = ">=8.1.7" },
|
||||
{ name = "langgraph-api", marker = "python_full_version >= '3.11' and extra == 'inmem'", specifier = ">=0.3,<0.5.0" },
|
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{ name = "langgraph-runtime-inmem", marker = "python_full_version >= '3.11' and extra == 'inmem'", specifier = ">=0.7" },
|
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{ name = "langgraph-api", marker = "python_full_version >= '3.11' and extra == 'inmem'", specifier = ">=0.2.120,<0.4.0" },
|
||||
{ name = "langgraph-runtime-inmem", marker = "python_full_version >= '3.11' and extra == 'inmem'", specifier = ">=0.6.8" },
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{ name = "langgraph-sdk", marker = "python_full_version >= '3.11'", specifier = ">=0.1.0" },
|
||||
{ name = "python-dotenv", marker = "extra == 'inmem'", specifier = ">=0.8.0" },
|
||||
]
|
||||
@@ -595,7 +595,7 @@ wheels = [
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|
||||
[[package]]
|
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name = "langgraph-runtime-inmem"
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@@ -605,27 +605,27 @@ dependencies = [
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[[package]]
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[[package]]
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[[package]]
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||||
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[[package]]
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{ name = "anyio", marker = "python_full_version >= '3.11'" },
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{ name = "typing-extensions", marker = "python_full_version >= '3.11' and python_full_version < '3.13'" },
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||||
[[package]]
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||||
@@ -1335,11 +1335,11 @@ wheels = [
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||||
|
||||
[[package]]
|
||||
name = "typing-extensions"
|
||||
version = "4.15.0"
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wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl", hash = "sha256:f0fa19c6845758ab08074a0cfa8b7aecb71c999ca73d62883bc25cc018c4e548", size = 44614, upload-time = "2025-08-25T13:49:24.86Z" },
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{ url = "https://files.pythonhosted.org/packages/b5/00/d631e67a838026495268c2f6884f3711a15a9a2a96cd244fdaea53b823fb/typing_extensions-4.14.1-py3-none-any.whl", hash = "sha256:d1e1e3b58374dc93031d6eda2420a48ea44a36c2b4766a4fdeb3710755731d76", size = 43906, upload-time = "2025-07-04T13:28:32.743Z" },
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||||
]
|
||||
|
||||
[[package]]
|
||||
|
||||
@@ -0,0 +1,314 @@
|
||||
from collections.abc import Sequence
|
||||
from inspect import signature
|
||||
from typing import Any, Callable, cast
|
||||
|
||||
from langchain_core.language_models.chat_models import BaseChatModel
|
||||
from langchain_core.messages import AIMessage, SystemMessage
|
||||
from langchain_core.tools import BaseTool
|
||||
|
||||
from langgraph.agent.types import (
|
||||
AgentJump,
|
||||
AgentMiddleware,
|
||||
AgentState,
|
||||
AgentUpdate,
|
||||
JumpTo,
|
||||
ModelRequest,
|
||||
ResponseFormat,
|
||||
)
|
||||
from langgraph.constants import END, START
|
||||
from langgraph.graph.state import StateGraph
|
||||
from langgraph.prebuilt.tool_node import ToolNode
|
||||
|
||||
|
||||
def create_agent(
|
||||
*,
|
||||
model: str | BaseChatModel,
|
||||
tools: Sequence[BaseTool | Callable] | ToolNode,
|
||||
system_prompt: str,
|
||||
middleware: Sequence[AgentMiddleware] = (),
|
||||
response_format: ResponseFormat | None = None,
|
||||
context_schema: type[Any] | None = None,
|
||||
) -> StateGraph[AgentState, None, AgentUpdate]:
|
||||
# init chat model
|
||||
if isinstance(model, str):
|
||||
try:
|
||||
from langchain.chat_models import ( # type: ignore[import-not-found]
|
||||
init_chat_model,
|
||||
)
|
||||
except ImportError:
|
||||
raise ImportError(
|
||||
"Please install langchain (`pip install langchain`) to "
|
||||
"use '<provider>:<model>' string syntax for `model` parameter."
|
||||
)
|
||||
|
||||
model = cast(BaseChatModel, init_chat_model(model))
|
||||
|
||||
if isinstance(tools, list):
|
||||
all_tools = [t for m in middleware for t in m.tools] + list(tools)
|
||||
tool_node = ToolNode(tools=all_tools)
|
||||
default_tools = tools
|
||||
else:
|
||||
# TODO: what do we do when middleware tools are specified, plus a ToolNode is used?
|
||||
tool_node = tools
|
||||
default_tools = list(tool_node.tools_by_name.values())
|
||||
|
||||
# validate middleware
|
||||
assert len({m.__class__.__name__ for m in middleware}) == len(middleware), (
|
||||
"Please remove duplicate middleware instances."
|
||||
) # this is just to keep the node names simple, we can change if needed
|
||||
middleware_w_before = [
|
||||
m
|
||||
for m in middleware
|
||||
if m.__class__.before_model is not AgentMiddleware.before_model
|
||||
]
|
||||
middleware_w_modify_model_request = [
|
||||
m
|
||||
for m in middleware
|
||||
if m.__class__.modify_model_request is not AgentMiddleware.modify_model_request
|
||||
]
|
||||
middleware_w_after = [
|
||||
m
|
||||
for m in middleware
|
||||
if m.__class__.after_model is not AgentMiddleware.after_model
|
||||
]
|
||||
|
||||
# create graph, add nodes
|
||||
graph = StateGraph(
|
||||
AgentState,
|
||||
input_schema=AgentUpdate,
|
||||
output_schema=AgentUpdate,
|
||||
context_schema=context_schema,
|
||||
)
|
||||
|
||||
def model_request(state: AgentState) -> AgentState:
|
||||
request = state.model_request or ModelRequest(
|
||||
model=model,
|
||||
tools=default_tools,
|
||||
system_prompt=system_prompt,
|
||||
response_format=response_format,
|
||||
messages=state.messages,
|
||||
tool_choice=None,
|
||||
)
|
||||
|
||||
# prepare messages
|
||||
print(request.system_prompt)
|
||||
if request.system_prompt:
|
||||
messages = [SystemMessage(request.system_prompt)] + request.messages
|
||||
else:
|
||||
messages = request.messages
|
||||
# call model
|
||||
if request.response_format:
|
||||
model_ = request.model.with_structured_output(
|
||||
request.response_format, include_raw=True
|
||||
)
|
||||
output = model_.invoke(
|
||||
messages, tools=request.tools, tool_choice=request.tool_choice
|
||||
)
|
||||
return {"messages": output["raw"], "response": output["parsed"]}
|
||||
else:
|
||||
model_ = request.model.bind_tools(
|
||||
request.tools,
|
||||
tool_choice=request.tool_choice,
|
||||
parallel_tool_calls=False,
|
||||
)
|
||||
output = model_.invoke(messages)
|
||||
if state.response is not None:
|
||||
return {"messages": output, "response": None}
|
||||
else:
|
||||
return {"messages": output}
|
||||
|
||||
graph.add_node("model_request", model_request)
|
||||
graph.add_node("tools", tool_node)
|
||||
|
||||
for m in middleware:
|
||||
if m.__class__.before_model is not AgentMiddleware.before_model:
|
||||
graph.add_node(
|
||||
f"{m.__class__.__name__}.before_model",
|
||||
m.before_model,
|
||||
input_schema=m.State,
|
||||
)
|
||||
if m.__class__.modify_model_request is not AgentMiddleware.modify_model_request:
|
||||
|
||||
def modify_model_request_node(state: AgentState) -> dict[str, ModelRequest]:
|
||||
# TODO assert request.tools in tools, or pass them to tool node
|
||||
|
||||
default_model_request = ModelRequest(
|
||||
model=model,
|
||||
tools=default_tools,
|
||||
system_prompt=system_prompt,
|
||||
response_format=response_format,
|
||||
messages=state.messages,
|
||||
tool_choice=None,
|
||||
)
|
||||
|
||||
return {
|
||||
"model_request": m.modify_model_request(
|
||||
state.model_request or default_model_request, state
|
||||
)
|
||||
}
|
||||
|
||||
graph.add_node(
|
||||
f"{m.__class__.__name__}.modify_model_request",
|
||||
modify_model_request_node,
|
||||
input_schema=m.State,
|
||||
)
|
||||
|
||||
if m.__class__.after_model is not AgentMiddleware.after_model:
|
||||
graph.add_node(
|
||||
f"{m.__class__.__name__}.after_model",
|
||||
m.after_model,
|
||||
input_schema=m.State,
|
||||
)
|
||||
|
||||
# add start edge
|
||||
first_node = (
|
||||
f"{middleware_w_before[0].__class__.__name__}.before_model"
|
||||
if middleware_w_before
|
||||
else f"{middleware_w_modify_model_request[0].__class__.__name__}.modify_model_request"
|
||||
if middleware_w_modify_model_request
|
||||
else "model_request"
|
||||
)
|
||||
last_node = (
|
||||
f"{middleware_w_after[0].__class__.__name__}.after_model"
|
||||
if middleware_w_after
|
||||
else "model_request"
|
||||
)
|
||||
graph.add_edge(START, first_node)
|
||||
|
||||
# add cond edges
|
||||
graph.add_conditional_edges(
|
||||
"tools",
|
||||
_make_tools_to_model_edge(tool_node, first_node),
|
||||
[first_node, END],
|
||||
)
|
||||
graph.add_conditional_edges(
|
||||
last_node, _make_model_to_tools_edge(first_node), [first_node, "tools", END]
|
||||
)
|
||||
|
||||
# add before model edges
|
||||
if middleware_w_before:
|
||||
for m1, m2 in zip(middleware_w_before, middleware_w_before[1:]):
|
||||
_add_middleware_edge(
|
||||
graph,
|
||||
m1.before_model,
|
||||
f"{m1.__class__.__name__}.before_model",
|
||||
f"{m2.__class__.__name__}.before_model",
|
||||
first_node,
|
||||
)
|
||||
_add_middleware_edge(
|
||||
graph,
|
||||
middleware_w_before[-1].before_model,
|
||||
f"{middleware_w_before[-1].__class__.__name__}.before_model",
|
||||
"model_request",
|
||||
first_node,
|
||||
)
|
||||
|
||||
# add modify model request edges
|
||||
if middleware_w_modify_model_request:
|
||||
for m1, m2 in zip(
|
||||
middleware_w_modify_model_request, middleware_w_modify_model_request[1:]
|
||||
):
|
||||
_add_middleware_edge(
|
||||
graph,
|
||||
m1.modify_model_request,
|
||||
f"{m1.__class__.__name__}.modify_model_request",
|
||||
f"{m2.__class__.__name__}.modify_model_request",
|
||||
first_node,
|
||||
)
|
||||
_add_middleware_edge(
|
||||
graph,
|
||||
middleware_w_modify_model_request[-1].modify_model_request,
|
||||
f"{middleware_w_modify_model_request[-1].__class__.__name__}.modify_model_request",
|
||||
"model_request",
|
||||
first_node,
|
||||
)
|
||||
|
||||
# add after model edges
|
||||
if middleware_w_after:
|
||||
graph.add_edge(
|
||||
"model_request", f"{middleware_w_after[-1].__class__.__name__}.after_model"
|
||||
)
|
||||
for idx in range(len(middleware_w_after) - 1, 0, -1):
|
||||
m1 = middleware_w_after[idx]
|
||||
m2 = middleware_w_after[idx - 1]
|
||||
_add_middleware_edge(
|
||||
graph,
|
||||
m1.after_model,
|
||||
f"{m1.__class__.__name__}.after_model",
|
||||
f"{m2.__class__.__name__}.after_model",
|
||||
first_node,
|
||||
)
|
||||
# _add_middleware_edge(
|
||||
# graph,
|
||||
# middleware_w_after[-1].after_model,
|
||||
# f"{middleware_w_after[-1].__class__.__name__}.after_model",
|
||||
# "model_request",
|
||||
# first_node,
|
||||
# )
|
||||
|
||||
return graph
|
||||
|
||||
|
||||
def _resolve_jump(jump_to: JumpTo | None, first_node: str) -> str | None:
|
||||
if jump_to == "model":
|
||||
return first_node
|
||||
elif jump_to:
|
||||
return jump_to
|
||||
|
||||
|
||||
def _make_model_to_tools_edge(first_node: str) -> Callable[[AgentState], str | None]:
|
||||
def model_to_tools(state: AgentState) -> str | None:
|
||||
if state.jump_to:
|
||||
return _resolve_jump(state.jump_to, first_node)
|
||||
message = state.messages[-1]
|
||||
if isinstance(message, AIMessage) and message.tool_calls:
|
||||
return "tools"
|
||||
|
||||
return END
|
||||
|
||||
return model_to_tools
|
||||
|
||||
|
||||
def _make_tools_to_model_edge(
|
||||
tool_node: ToolNode, next_node: str
|
||||
) -> Callable[[AgentState], str | None]:
|
||||
def tools_to_model(state: AgentState) -> str | None:
|
||||
ai_message = [m for m in state.messages if isinstance(m, AIMessage)][-1]
|
||||
if all(
|
||||
tool_node.tools_by_name[c["name"]].return_direct
|
||||
for c in ai_message.tool_calls
|
||||
if c["name"] in tool_node.tools_by_name
|
||||
):
|
||||
return END
|
||||
|
||||
return next_node
|
||||
|
||||
return tools_to_model
|
||||
|
||||
|
||||
def _add_middleware_edge(
|
||||
graph: StateGraph,
|
||||
method: Callable[[AgentState], AgentUpdate | AgentJump | None],
|
||||
name: str,
|
||||
default_destination: str,
|
||||
model_destination: str,
|
||||
) -> None:
|
||||
sig = signature(method)
|
||||
uses_jump = sig.return_annotation is AgentJump or AgentJump in getattr(
|
||||
sig.return_annotation, "__args__", ()
|
||||
)
|
||||
|
||||
if uses_jump:
|
||||
|
||||
def jump_edge(state: AgentState) -> str:
|
||||
return (
|
||||
_resolve_jump(state.jump_to, model_destination) or default_destination
|
||||
)
|
||||
|
||||
destinations = [default_destination, END, "tools"]
|
||||
if name != model_destination:
|
||||
destinations.append(model_destination)
|
||||
|
||||
graph.add_conditional_edges(name, jump_edge, destinations)
|
||||
else:
|
||||
graph.add_edge(name, default_destination)
|
||||
@@ -0,0 +1,35 @@
|
||||
from dataclasses import dataclass
|
||||
from typing import Literal
|
||||
|
||||
from langchain_core.language_models.chat_models import BaseChatModel
|
||||
|
||||
from langgraph.agent.types import (
|
||||
AgentJump,
|
||||
AgentMiddleware,
|
||||
AgentState,
|
||||
AgentUpdate,
|
||||
ModelRequest,
|
||||
)
|
||||
|
||||
|
||||
class DynamicModelMiddleware(AgentMiddleware):
|
||||
"""Selects different models based on task complexity"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
basic_model: BaseChatModel,
|
||||
complex_model: BaseChatModel,
|
||||
message_threshold: int = 5,
|
||||
):
|
||||
self.basic_model = basic_model
|
||||
self.complex_model = complex_model
|
||||
self.message_threshold = message_threshold
|
||||
|
||||
def modify_model_request(
|
||||
self, request: ModelRequest, state: AgentState
|
||||
) -> ModelRequest:
|
||||
if len(state.messages) > self.message_threshold:
|
||||
request.model = self.complex_model
|
||||
else:
|
||||
request.model = self.basic_model
|
||||
return request
|
||||
@@ -0,0 +1,102 @@
|
||||
from langgraph.agent.types import AgentJump, AgentMiddleware, AgentState, AgentUpdate
|
||||
from langgraph.prebuilt.interrupt import (
|
||||
ActionRequest,
|
||||
HumanInterrupt,
|
||||
HumanInterruptConfig,
|
||||
HumanResponse,
|
||||
)
|
||||
from langgraph.types import interrupt
|
||||
|
||||
ToolInterruptConfig = dict[str, HumanInterruptConfig]
|
||||
|
||||
|
||||
class HumanInTheLoopMiddleware(AgentMiddleware):
|
||||
def __init__(
|
||||
self,
|
||||
tool_configs: ToolInterruptConfig,
|
||||
message_prefix: str = "Tool execution requires approval",
|
||||
):
|
||||
super().__init__()
|
||||
self.tool_configs = tool_configs
|
||||
self.message_prefix = message_prefix
|
||||
|
||||
def after_model(self, state: AgentState) -> AgentUpdate | AgentJump | None:
|
||||
messages = state.messages
|
||||
if not messages:
|
||||
return
|
||||
|
||||
last_message = messages[-1]
|
||||
|
||||
if not hasattr(last_message, "tool_calls") or not last_message.tool_calls:
|
||||
return
|
||||
|
||||
# Separate tool calls that need interrupts from those that don't
|
||||
interrupt_tool_calls = []
|
||||
auto_approved_tool_calls = []
|
||||
|
||||
for tool_call in last_message.tool_calls:
|
||||
tool_name = tool_call["name"]
|
||||
if tool_name in self.tool_configs:
|
||||
interrupt_tool_calls.append(tool_call)
|
||||
else:
|
||||
auto_approved_tool_calls.append(tool_call)
|
||||
|
||||
# If no interrupts needed, return early
|
||||
if not interrupt_tool_calls:
|
||||
return
|
||||
|
||||
approved_tool_calls = auto_approved_tool_calls.copy()
|
||||
|
||||
# Process all tool calls that need interrupts in parallel
|
||||
requests = []
|
||||
|
||||
for tool_call in interrupt_tool_calls:
|
||||
tool_name = tool_call["name"]
|
||||
tool_args = tool_call["args"]
|
||||
description = (
|
||||
f"{self.message_prefix}\n\nTool: {tool_name}\nArgs: {tool_args}"
|
||||
)
|
||||
tool_config = self.tool_configs[tool_name]
|
||||
|
||||
request: HumanInterrupt = {
|
||||
"action_request": ActionRequest(
|
||||
action=tool_name,
|
||||
args=tool_args,
|
||||
),
|
||||
"config": tool_config,
|
||||
"description": description,
|
||||
}
|
||||
requests.append(request)
|
||||
|
||||
responses: list[HumanResponse] = interrupt(requests)
|
||||
|
||||
for i, response in enumerate(responses):
|
||||
tool_call = interrupt_tool_calls[i]
|
||||
|
||||
if response["type"] == "accept":
|
||||
approved_tool_calls.append(tool_call)
|
||||
elif response["type"] == "edit":
|
||||
edited: ActionRequest = response["args"]
|
||||
new_tool_call = {
|
||||
"name": tool_call["name"],
|
||||
"args": edited["args"],
|
||||
"id": tool_call["id"],
|
||||
}
|
||||
approved_tool_calls.append(new_tool_call)
|
||||
elif response["type"] == "ignore":
|
||||
# NOTE: does not work with multiple interrupts
|
||||
return {"goto": "__end__"}
|
||||
elif response["type"] == "response":
|
||||
# NOTE: does not work with multiple interrupts
|
||||
tool_message = {
|
||||
"role": "tool",
|
||||
"tool_call_id": tool_call["id"],
|
||||
"content": response["args"],
|
||||
}
|
||||
return {"messages": [tool_message], "goto": "model"}
|
||||
else:
|
||||
raise ValueError(f"Unknown response type: {response['type']}")
|
||||
|
||||
last_message.tool_calls = approved_tool_calls
|
||||
|
||||
return {"messages": [last_message]}
|
||||
@@ -0,0 +1,23 @@
|
||||
import operator
|
||||
from dataclasses import dataclass
|
||||
from typing import Annotated
|
||||
|
||||
from langgraph.agent.types import AgentJump, AgentMiddleware, AgentState, AgentUpdate
|
||||
|
||||
|
||||
class ModelRequestLimitMiddleware(AgentMiddleware):
|
||||
"""Terminates after N model requests"""
|
||||
|
||||
@dataclass
|
||||
class State(AgentMiddleware.State):
|
||||
model_request_count: Annotated[int, operator.add] = 0
|
||||
|
||||
def __init__(self, max_requests: int = 10):
|
||||
self.max_requests = max_requests
|
||||
|
||||
def before_model(self, state: State) -> AgentUpdate | AgentJump | None:
|
||||
# TODO: want to be able to configure end behavior here
|
||||
if state.model_request_count == self.max_requests:
|
||||
return {"jump_to": "__end__"}
|
||||
|
||||
return {"model_request_count": 1}
|
||||
@@ -0,0 +1,108 @@
|
||||
import uuid
|
||||
from collections.abc import Sequence
|
||||
from typing import Callable, Iterable
|
||||
|
||||
from langchain_core.language_models import LanguageModelLike
|
||||
from langchain_core.messages import (
|
||||
AIMessage,
|
||||
AnyMessage,
|
||||
MessageLikeRepresentation,
|
||||
RemoveMessage,
|
||||
ToolMessage,
|
||||
)
|
||||
from langchain_core.messages.utils import count_tokens_approximately
|
||||
|
||||
TokenCounter = Callable[[Iterable[MessageLikeRepresentation]], int]
|
||||
|
||||
|
||||
from langgraph.agent.types import AgentMiddleware, AgentState
|
||||
|
||||
DEFAULT_SUMMARY_PROMPT = """<role>
|
||||
Context Extraction Assistant
|
||||
</role>
|
||||
|
||||
<primary_objective>
|
||||
Your sole objective in this task is to extract the highest quality/most relevant context from the conversation history below.
|
||||
</primary_objective>
|
||||
|
||||
<objective_information>
|
||||
You're nearing the total number of input tokens you can accept, so you must extract the highest quality/most relevant pieces of information from your conversation history.
|
||||
This context will then overwrite the conversation history presented below. Because of this, ensure the context you extract is only the most important information to your overall goal.
|
||||
</objective_information>
|
||||
|
||||
<instructions>
|
||||
The conversation history below will be replaced with the context you extract in this step. Because of this, you must do your very best to extract and record all of the most important context from the conversation history.
|
||||
You want to ensure that you don't repeat any actions you've already completed, so the context you extract from the conversation history should be focused on the most important information to your overall goal.
|
||||
</instructions>
|
||||
|
||||
The user will message you with the full message history you'll be extracting context from, to then replace. Carefully read over it all, and think deeply about what information is most important to your overall goal that should be saved:
|
||||
|
||||
With all of this in mind, please carefully read over the entire conversation history, and extract the most important and relevant context to replace it so that you can free up space in the conversation history.
|
||||
Respond ONLY with the extracted context. Do not include any additional information, or text before or after the extracted context."""
|
||||
|
||||
|
||||
class SummarizationMiddleware(AgentMiddleware):
|
||||
def __init__(
|
||||
self,
|
||||
model: LanguageModelLike,
|
||||
max_tokens_before_summary: int | None = None,
|
||||
token_counter: TokenCounter = count_tokens_approximately,
|
||||
messages_to_leave: int = 20,
|
||||
summary_system_prompt: str = DEFAULT_SUMMARY_PROMPT,
|
||||
fake_tool_call_name: str = "summarize_convo",
|
||||
):
|
||||
super().__init__()
|
||||
self.model = model
|
||||
self.max_tokens_before_summary = max_tokens_before_summary
|
||||
self.token_counter = token_counter
|
||||
self.messages_to_leave = messages_to_leave
|
||||
self.summary_system_prompt = summary_system_prompt
|
||||
self.fake_tool_call_name = fake_tool_call_name
|
||||
|
||||
def before_model(self, state: AgentState) -> AgentState | None:
|
||||
messages = state.messages
|
||||
token_counts = self.token_counter(messages)
|
||||
# If token counts are less than max allowed, then end this hook early
|
||||
if token_counts < self.max_tokens_before_summary:
|
||||
return None
|
||||
# Otherwise, we create a summary!
|
||||
# Get messages that we want to create a summary for
|
||||
messages_to_summarize = messages[: -self.messages_to_leave]
|
||||
# Create summary text
|
||||
summary = self._summarize_messages(messages_to_summarize)
|
||||
# Create fake messages to add to history
|
||||
fake_tool_call_id = str(uuid.uuid4())
|
||||
fake_messages = [
|
||||
AIMessage(
|
||||
content="Looks like I'm running out of tokens. I'm going to summarize the conversation history to free up space.",
|
||||
tool_calls={
|
||||
"id": fake_tool_call_id,
|
||||
"name": self.fake_tool_call_name,
|
||||
"args": {
|
||||
"reasoning": "I'm running out of tokens. I'm going to summarize all of the messages since my last summary message to free up space.",
|
||||
},
|
||||
},
|
||||
),
|
||||
ToolMessage(tool_call_id=fake_tool_call_id, content=summary),
|
||||
]
|
||||
return {
|
||||
"messages": [RemoveMessage(id=m.id) for m in messages_to_summarize]
|
||||
+ fake_messages
|
||||
}
|
||||
|
||||
def _summarize_messages(self, messages_to_summarize: Sequence[AnyMessage]) -> str:
|
||||
system_message = self.summary_system_prompt
|
||||
user_message = self._format_messages(messages_to_summarize)
|
||||
response = self.model.invoke(
|
||||
[
|
||||
{"role": "system", "content": system_message},
|
||||
{"role": "user", "content": user_message},
|
||||
]
|
||||
)
|
||||
# Use new .text attribute when ready
|
||||
return response.content
|
||||
|
||||
@staticmethod
|
||||
def _format_messages(messages_to_summarize: Sequence[AnyMessage]) -> str:
|
||||
# TODO: better formatting logic
|
||||
return "\n".join([m.content for m in messages_to_summarize])
|
||||
@@ -0,0 +1,84 @@
|
||||
from dataclasses import dataclass
|
||||
from typing import cast
|
||||
|
||||
from langchain_core.messages import AIMessage, HumanMessage, ToolMessage
|
||||
from langchain_core.tools import BaseTool, tool
|
||||
|
||||
from langgraph.agent import create_agent
|
||||
from langgraph.agent.types import AgentJump, AgentMiddleware, ModelRequest
|
||||
|
||||
|
||||
@dataclass
|
||||
class SwarmAgent:
|
||||
name: str
|
||||
system_prompt: str
|
||||
tools: list[BaseTool]
|
||||
|
||||
|
||||
class MultiAgentMiddleware(AgentMiddleware):
|
||||
"""Multi agent middleware (enabling swarm like behavior).
|
||||
|
||||
TODOs:
|
||||
* Support create_agent for handoffs
|
||||
* Support handoff customization
|
||||
* do we want to include handoff messages / enable togglging
|
||||
* default active agent
|
||||
* handoff tool naming / descriptions
|
||||
"""
|
||||
|
||||
@dataclass
|
||||
class State(AgentMiddleware.State):
|
||||
active_agent: str | None = None
|
||||
|
||||
@staticmethod
|
||||
def _create_handoff_tools(agents: list[SwarmAgent]) -> list[BaseTool]:
|
||||
handoff_tools: list[BaseTool] = []
|
||||
|
||||
for agent in agents:
|
||||
|
||||
def handoff_tool() -> str:
|
||||
return f"Handing off to {agent.name}"
|
||||
|
||||
handoff_tools.append(
|
||||
tool(
|
||||
f"handoff_to_{agent.name}",
|
||||
description=f"Handoff tool to trigger a handoff to {agent.name}",
|
||||
)(handoff_tool)
|
||||
)
|
||||
|
||||
return handoff_tools
|
||||
|
||||
def __init__(self, agents: list[SwarmAgent]):
|
||||
self.agents: dict[str, SwarmAgent] = {agent.name: agent for agent in agents}
|
||||
self.handoff_tools = self._create_handoff_tools(agents)
|
||||
|
||||
def modify_model_request(self, request: ModelRequest, state: State) -> ModelRequest:
|
||||
if (active_agent := getattr(state, "active_agent", None)) is not None:
|
||||
agent = self.agents[active_agent]
|
||||
request.system_prompt = agent.system_prompt
|
||||
request.tools = agent.tools
|
||||
|
||||
request.tools.extend(self.handoff_tools)
|
||||
|
||||
return request
|
||||
|
||||
def after_model(self, state) -> State | None:
|
||||
# TODO: handle parallel handoffs, we don't do this currently
|
||||
|
||||
ai_msg: AIMessage = cast(AIMessage, state.messages[-1])
|
||||
if ai_msg.tool_calls:
|
||||
for call in ai_msg.tool_calls:
|
||||
if call["name"].startswith("handoff_to_"):
|
||||
active_agent = call["name"].replace("handoff_to_", "")
|
||||
return {
|
||||
"messages": [
|
||||
ToolMessage(
|
||||
name=call["name"],
|
||||
content=f"Successfully transferred to {active_agent}",
|
||||
tool_call_id=call["id"],
|
||||
)
|
||||
],
|
||||
"active_agent": active_agent,
|
||||
"jump_to": "model",
|
||||
}
|
||||
return None
|
||||
@@ -0,0 +1,44 @@
|
||||
from dataclasses import dataclass, field
|
||||
from typing import Annotated, Any, Dict, List, cast
|
||||
|
||||
from langchain_core.messages import AIMessage
|
||||
from typing_extensions import Annotated
|
||||
|
||||
from langgraph.agent.types import AgentJump, AgentMiddleware, AgentState, AgentUpdate
|
||||
|
||||
|
||||
class ToolCallLimitMiddleware(AgentMiddleware):
|
||||
"""Terminates after a specific tool is called N times"""
|
||||
|
||||
@dataclass
|
||||
class State(AgentMiddleware.State):
|
||||
important: Annotated[dict[str, int], Input, Output] = field(default_factory=dict)
|
||||
|
||||
@dataclass
|
||||
class InputState(AgentMiddleware.State):
|
||||
important: dict[str, int]
|
||||
|
||||
@dataclass
|
||||
class OutputState(AgentMiddleware.State):
|
||||
important: dict[str, int]
|
||||
|
||||
def __init__(self, tool_limits: dict[str, int]):
|
||||
self.tool_limits = tool_limits
|
||||
|
||||
def after_model(self, state: State) -> AgentUpdate | AgentJump | None:
|
||||
ai_msg: AIMessage = cast(AIMessage, state.messages[-1])
|
||||
|
||||
tool_calls = {}
|
||||
for call in ai_msg.tool_calls or []:
|
||||
tool_calls[call["name"]] = tool_calls.get(call["name"], 0) + 1
|
||||
|
||||
aggregate_calls = state.tool_call_count.copy()
|
||||
for tool_name in tool_calls.keys():
|
||||
aggregate_calls[tool_name] = aggregate_calls.get(tool_name, 0) + 1
|
||||
|
||||
for tool_name, max_calls in self.tool_limits.items():
|
||||
count = aggregate_calls.get(tool_name, 0)
|
||||
if count == max_calls:
|
||||
return {"tool_call_count": aggregate_calls, "jump_to": "__end__"}
|
||||
|
||||
return {"tool_call_count": aggregate_calls}
|
||||
@@ -0,0 +1,62 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from collections.abc import Sequence
|
||||
from dataclasses import dataclass
|
||||
from typing import Annotated, Any, Literal
|
||||
|
||||
from langchain_core.language_models.chat_models import BaseChatModel
|
||||
from langchain_core.messages import AnyMessage
|
||||
from langchain_core.tools import BaseTool
|
||||
from pydantic import BaseModel
|
||||
from typing_extensions import TypedDict
|
||||
|
||||
from langgraph.channels.ephemeral_value import EphemeralValue
|
||||
from langgraph.graph.message import Messages, add_messages
|
||||
from langgraph.runtime import Runtime
|
||||
|
||||
ResponseFormat = dict | type[BaseModel]
|
||||
JumpTo = Literal["tools", "model", "__end__"]
|
||||
|
||||
|
||||
@dataclass
|
||||
class ModelRequest:
|
||||
model: BaseChatModel
|
||||
system_prompt: str
|
||||
messages: list[AnyMessage] # excluding system prompt
|
||||
tool_choice: Any
|
||||
tools: list[BaseTool]
|
||||
response_format: ResponseFormat | None
|
||||
|
||||
|
||||
@dataclass
|
||||
class AgentState:
|
||||
messages: Annotated[list[AnyMessage], add_messages]
|
||||
model_request: Annotated[ModelRequest | None, EphemeralValue] = None
|
||||
jump_to: Annotated[JumpTo | None, EphemeralValue] = None
|
||||
response: dict | None = None
|
||||
|
||||
|
||||
class AgentMiddleware:
|
||||
class State(AgentState):
|
||||
pass
|
||||
|
||||
tools: list[BaseTool]
|
||||
|
||||
def before_model(self, state: State) -> AgentUpdate | AgentJump | None:
|
||||
pass
|
||||
|
||||
def modify_model_request(self, request: ModelRequest, state: State) -> ModelRequest:
|
||||
return request
|
||||
|
||||
def after_model(self, state: State) -> AgentUpdate | AgentJump | None:
|
||||
pass
|
||||
|
||||
|
||||
class AgentUpdate(TypedDict, total=False):
|
||||
messages: Messages
|
||||
response: dict
|
||||
|
||||
|
||||
class AgentJump(TypedDict, total=False):
|
||||
messages: Messages
|
||||
jump_to: JumpTo
|
||||
@@ -198,11 +198,8 @@ def local_read(
|
||||
# apply writes
|
||||
local_channels: dict[str, BaseChannel] = {}
|
||||
for k in channels:
|
||||
if k in updated:
|
||||
cc = channels[k].copy()
|
||||
cc.update(updated[k])
|
||||
else:
|
||||
cc = channels[k]
|
||||
cc = channels[k].copy()
|
||||
cc.update(updated[k])
|
||||
local_channels[k] = cc
|
||||
# read fresh values
|
||||
values = read_channels(local_channels, select)
|
||||
|
||||
@@ -0,0 +1,313 @@
|
||||
# serializer version: 1
|
||||
# name: test_create_agent_diagram
|
||||
'''
|
||||
---
|
||||
config:
|
||||
flowchart:
|
||||
curve: linear
|
||||
---
|
||||
graph TD;
|
||||
__start__([<p>__start__</p>]):::first
|
||||
model_request(model_request)
|
||||
tools(tools)
|
||||
__end__([<p>__end__</p>]):::last
|
||||
__start__ --> model_request;
|
||||
model_request -.-> __end__;
|
||||
model_request -.-> tools;
|
||||
tools -.-> __end__;
|
||||
tools -.-> model_request;
|
||||
classDef default fill:#f2f0ff,line-height:1.2
|
||||
classDef first fill-opacity:0
|
||||
classDef last fill:#bfb6fc
|
||||
|
||||
'''
|
||||
# ---
|
||||
# name: test_create_agent_diagram.1
|
||||
'''
|
||||
---
|
||||
config:
|
||||
flowchart:
|
||||
curve: linear
|
||||
---
|
||||
graph TD;
|
||||
__start__([<p>__start__</p>]):::first
|
||||
model_request(model_request)
|
||||
tools(tools)
|
||||
NoopOne_before_model(NoopOne.before_model)
|
||||
__end__([<p>__end__</p>]):::last
|
||||
NoopOne_before_model --> model_request;
|
||||
__start__ --> NoopOne_before_model;
|
||||
model_request -.-> __end__;
|
||||
model_request -.-> tools;
|
||||
tools -.-> NoopOne_before_model;
|
||||
tools -.-> __end__;
|
||||
classDef default fill:#f2f0ff,line-height:1.2
|
||||
classDef first fill-opacity:0
|
||||
classDef last fill:#bfb6fc
|
||||
|
||||
'''
|
||||
# ---
|
||||
# name: test_create_agent_diagram.2
|
||||
'''
|
||||
---
|
||||
config:
|
||||
flowchart:
|
||||
curve: linear
|
||||
---
|
||||
graph TD;
|
||||
__start__([<p>__start__</p>]):::first
|
||||
model_request(model_request)
|
||||
tools(tools)
|
||||
NoopOne_before_model(NoopOne.before_model)
|
||||
NoopTwo_before_model(NoopTwo.before_model)
|
||||
__end__([<p>__end__</p>]):::last
|
||||
NoopOne_before_model --> NoopTwo_before_model;
|
||||
NoopTwo_before_model --> model_request;
|
||||
__start__ --> NoopOne_before_model;
|
||||
model_request -.-> __end__;
|
||||
model_request -.-> tools;
|
||||
tools -.-> NoopOne_before_model;
|
||||
tools -.-> __end__;
|
||||
classDef default fill:#f2f0ff,line-height:1.2
|
||||
classDef first fill-opacity:0
|
||||
classDef last fill:#bfb6fc
|
||||
|
||||
'''
|
||||
# ---
|
||||
# name: test_create_agent_diagram.3
|
||||
'''
|
||||
---
|
||||
config:
|
||||
flowchart:
|
||||
curve: linear
|
||||
---
|
||||
graph TD;
|
||||
__start__([<p>__start__</p>]):::first
|
||||
model_request(model_request)
|
||||
tools(tools)
|
||||
NoopOne_before_model(NoopOne.before_model)
|
||||
NoopTwo_before_model(NoopTwo.before_model)
|
||||
NoopThree_before_model(NoopThree.before_model)
|
||||
__end__([<p>__end__</p>]):::last
|
||||
NoopOne_before_model --> NoopTwo_before_model;
|
||||
NoopThree_before_model --> model_request;
|
||||
NoopTwo_before_model --> NoopThree_before_model;
|
||||
__start__ --> NoopOne_before_model;
|
||||
model_request -.-> __end__;
|
||||
model_request -.-> tools;
|
||||
tools -.-> NoopOne_before_model;
|
||||
tools -.-> __end__;
|
||||
classDef default fill:#f2f0ff,line-height:1.2
|
||||
classDef first fill-opacity:0
|
||||
classDef last fill:#bfb6fc
|
||||
|
||||
'''
|
||||
# ---
|
||||
# name: test_create_agent_diagram.4
|
||||
'''
|
||||
---
|
||||
config:
|
||||
flowchart:
|
||||
curve: linear
|
||||
---
|
||||
graph TD;
|
||||
__start__([<p>__start__</p>]):::first
|
||||
model_request(model_request)
|
||||
tools(tools)
|
||||
NoopFour_after_model(NoopFour.after_model)
|
||||
__end__([<p>__end__</p>]):::last
|
||||
NoopFour_after_model -.-> __end__;
|
||||
NoopFour_after_model -.-> tools;
|
||||
__start__ --> model_request;
|
||||
model_request --> NoopFour_after_model;
|
||||
tools -.-> __end__;
|
||||
tools -.-> model_request;
|
||||
classDef default fill:#f2f0ff,line-height:1.2
|
||||
classDef first fill-opacity:0
|
||||
classDef last fill:#bfb6fc
|
||||
|
||||
'''
|
||||
# ---
|
||||
# name: test_create_agent_diagram.5
|
||||
'''
|
||||
---
|
||||
config:
|
||||
flowchart:
|
||||
curve: linear
|
||||
---
|
||||
graph TD;
|
||||
__start__([<p>__start__</p>]):::first
|
||||
model_request(model_request)
|
||||
tools(tools)
|
||||
NoopFour_after_model(NoopFour.after_model)
|
||||
NoopFive_after_model(NoopFive.after_model)
|
||||
__end__([<p>__end__</p>]):::last
|
||||
NoopFive_after_model --> NoopFour_after_model;
|
||||
NoopFour_after_model -.-> __end__;
|
||||
NoopFour_after_model -.-> tools;
|
||||
__start__ --> model_request;
|
||||
model_request --> NoopFive_after_model;
|
||||
tools -.-> __end__;
|
||||
tools -.-> model_request;
|
||||
classDef default fill:#f2f0ff,line-height:1.2
|
||||
classDef first fill-opacity:0
|
||||
classDef last fill:#bfb6fc
|
||||
|
||||
'''
|
||||
# ---
|
||||
# name: test_create_agent_diagram.6
|
||||
'''
|
||||
---
|
||||
config:
|
||||
flowchart:
|
||||
curve: linear
|
||||
---
|
||||
graph TD;
|
||||
__start__([<p>__start__</p>]):::first
|
||||
model_request(model_request)
|
||||
tools(tools)
|
||||
NoopFour_after_model(NoopFour.after_model)
|
||||
NoopFive_after_model(NoopFive.after_model)
|
||||
NoopSix_after_model(NoopSix.after_model)
|
||||
__end__([<p>__end__</p>]):::last
|
||||
NoopFive_after_model --> NoopFour_after_model;
|
||||
NoopFour_after_model -.-> __end__;
|
||||
NoopFour_after_model -.-> tools;
|
||||
NoopSix_after_model --> NoopFive_after_model;
|
||||
__start__ --> model_request;
|
||||
model_request --> NoopSix_after_model;
|
||||
tools -.-> __end__;
|
||||
tools -.-> model_request;
|
||||
classDef default fill:#f2f0ff,line-height:1.2
|
||||
classDef first fill-opacity:0
|
||||
classDef last fill:#bfb6fc
|
||||
|
||||
'''
|
||||
# ---
|
||||
# name: test_create_agent_diagram.7
|
||||
'''
|
||||
---
|
||||
config:
|
||||
flowchart:
|
||||
curve: linear
|
||||
---
|
||||
graph TD;
|
||||
__start__([<p>__start__</p>]):::first
|
||||
model_request(model_request)
|
||||
tools(tools)
|
||||
NoopSeven_before_model(NoopSeven.before_model)
|
||||
NoopSeven_after_model(NoopSeven.after_model)
|
||||
__end__([<p>__end__</p>]):::last
|
||||
NoopSeven_after_model -.-> __end__;
|
||||
NoopSeven_after_model -.-> tools;
|
||||
NoopSeven_before_model --> model_request;
|
||||
__start__ --> NoopSeven_before_model;
|
||||
model_request --> NoopSeven_after_model;
|
||||
tools -.-> NoopSeven_before_model;
|
||||
tools -.-> __end__;
|
||||
classDef default fill:#f2f0ff,line-height:1.2
|
||||
classDef first fill-opacity:0
|
||||
classDef last fill:#bfb6fc
|
||||
|
||||
'''
|
||||
# ---
|
||||
# name: test_create_agent_diagram.8
|
||||
'''
|
||||
---
|
||||
config:
|
||||
flowchart:
|
||||
curve: linear
|
||||
---
|
||||
graph TD;
|
||||
__start__([<p>__start__</p>]):::first
|
||||
model_request(model_request)
|
||||
tools(tools)
|
||||
NoopSeven_before_model(NoopSeven.before_model)
|
||||
NoopSeven_after_model(NoopSeven.after_model)
|
||||
NoopEight_before_model(NoopEight.before_model)
|
||||
NoopEight_after_model(NoopEight.after_model)
|
||||
__end__([<p>__end__</p>]):::last
|
||||
NoopEight_after_model --> NoopSeven_after_model;
|
||||
NoopEight_before_model --> model_request;
|
||||
NoopSeven_after_model -.-> __end__;
|
||||
NoopSeven_after_model -.-> tools;
|
||||
NoopSeven_before_model --> NoopEight_before_model;
|
||||
__start__ --> NoopSeven_before_model;
|
||||
model_request --> NoopEight_after_model;
|
||||
tools -.-> NoopSeven_before_model;
|
||||
tools -.-> __end__;
|
||||
classDef default fill:#f2f0ff,line-height:1.2
|
||||
classDef first fill-opacity:0
|
||||
classDef last fill:#bfb6fc
|
||||
|
||||
'''
|
||||
# ---
|
||||
# name: test_create_agent_diagram.9
|
||||
'''
|
||||
---
|
||||
config:
|
||||
flowchart:
|
||||
curve: linear
|
||||
---
|
||||
graph TD;
|
||||
__start__([<p>__start__</p>]):::first
|
||||
model_request(model_request)
|
||||
tools(tools)
|
||||
NoopSeven_before_model(NoopSeven.before_model)
|
||||
NoopSeven_after_model(NoopSeven.after_model)
|
||||
NoopEight_before_model(NoopEight.before_model)
|
||||
NoopEight_after_model(NoopEight.after_model)
|
||||
NoopNine_before_model(NoopNine.before_model)
|
||||
NoopNine_after_model(NoopNine.after_model)
|
||||
__end__([<p>__end__</p>]):::last
|
||||
NoopEight_after_model --> NoopSeven_after_model;
|
||||
NoopEight_before_model --> NoopNine_before_model;
|
||||
NoopNine_after_model --> NoopEight_after_model;
|
||||
NoopNine_before_model --> model_request;
|
||||
NoopSeven_after_model -.-> __end__;
|
||||
NoopSeven_after_model -.-> tools;
|
||||
NoopSeven_before_model --> NoopEight_before_model;
|
||||
__start__ --> NoopSeven_before_model;
|
||||
model_request --> NoopNine_after_model;
|
||||
tools -.-> NoopSeven_before_model;
|
||||
tools -.-> __end__;
|
||||
classDef default fill:#f2f0ff,line-height:1.2
|
||||
classDef first fill-opacity:0
|
||||
classDef last fill:#bfb6fc
|
||||
|
||||
'''
|
||||
# ---
|
||||
# name: test_create_agent_jump[memory]
|
||||
'''
|
||||
---
|
||||
config:
|
||||
flowchart:
|
||||
curve: linear
|
||||
---
|
||||
graph TD;
|
||||
__start__([<p>__start__</p>]):::first
|
||||
model_request(model_request)
|
||||
tools(tools)
|
||||
NoopSeven_before_model(NoopSeven.before_model)
|
||||
NoopSeven_after_model(NoopSeven.after_model)
|
||||
NoopEight_before_model(NoopEight.before_model)
|
||||
NoopEight_after_model(NoopEight.after_model)
|
||||
__end__([<p>__end__</p>]):::last
|
||||
NoopEight_after_model --> NoopSeven_after_model;
|
||||
NoopEight_before_model -.-> NoopSeven_before_model;
|
||||
NoopEight_before_model -.-> __end__;
|
||||
NoopEight_before_model -.-> model_request;
|
||||
NoopEight_before_model -.-> tools;
|
||||
NoopSeven_after_model -.-> __end__;
|
||||
NoopSeven_after_model -.-> tools;
|
||||
NoopSeven_before_model --> NoopEight_before_model;
|
||||
__start__ --> NoopSeven_before_model;
|
||||
model_request --> NoopEight_after_model;
|
||||
tools -.-> NoopSeven_before_model;
|
||||
tools -.-> __end__;
|
||||
classDef default fill:#f2f0ff,line-height:1.2
|
||||
classDef first fill-opacity:0
|
||||
classDef last fill:#bfb6fc
|
||||
|
||||
'''
|
||||
# ---
|
||||
@@ -0,0 +1,298 @@
|
||||
from langchain_core.messages import AIMessage, ToolCall
|
||||
from syrupy import SnapshotAssertion
|
||||
|
||||
from langgraph.agent import create_agent
|
||||
from langgraph.agent.types import AgentJump, AgentMiddleware
|
||||
from langgraph.checkpoint.base import BaseCheckpointSaver
|
||||
from langgraph.checkpoint.memory import InMemorySaver
|
||||
from langgraph.constants import END
|
||||
from tests.fake_chat import FakeChatModel
|
||||
from tests.messages import _AnyIdToolMessage
|
||||
|
||||
|
||||
def test_create_agent_diagram(
|
||||
snapshot: SnapshotAssertion,
|
||||
):
|
||||
class NoopOne(AgentMiddleware):
|
||||
def before_model(self, state):
|
||||
pass
|
||||
|
||||
class NoopTwo(AgentMiddleware):
|
||||
def before_model(self, state):
|
||||
pass
|
||||
|
||||
class NoopThree(AgentMiddleware):
|
||||
def before_model(self, state):
|
||||
pass
|
||||
|
||||
class NoopFour(AgentMiddleware):
|
||||
def after_model(self, state):
|
||||
pass
|
||||
|
||||
class NoopFive(AgentMiddleware):
|
||||
def after_model(self, state):
|
||||
pass
|
||||
|
||||
class NoopSix(AgentMiddleware):
|
||||
def after_model(self, state):
|
||||
pass
|
||||
|
||||
class NoopSeven(AgentMiddleware):
|
||||
def before_model(self, state):
|
||||
pass
|
||||
|
||||
def after_model(self, state):
|
||||
pass
|
||||
|
||||
class NoopEight(AgentMiddleware):
|
||||
def before_model(self, state):
|
||||
pass
|
||||
|
||||
def after_model(self, state):
|
||||
pass
|
||||
|
||||
class NoopNine(AgentMiddleware):
|
||||
def before_model(self, state):
|
||||
pass
|
||||
|
||||
def after_model(self, state):
|
||||
pass
|
||||
|
||||
agent_zero = create_agent(
|
||||
model=FakeChatModel(messages=[]),
|
||||
tools=[],
|
||||
system_prompt="You are a helpful assistant.",
|
||||
)
|
||||
|
||||
assert agent_zero.compile().get_graph().draw_mermaid() == snapshot
|
||||
|
||||
agent_one = create_agent(
|
||||
model=FakeChatModel(messages=[]),
|
||||
tools=[],
|
||||
system_prompt="You are a helpful assistant.",
|
||||
middleware=[NoopOne()],
|
||||
)
|
||||
|
||||
assert agent_one.compile().get_graph().draw_mermaid() == snapshot
|
||||
|
||||
agent_two = create_agent(
|
||||
model=FakeChatModel(messages=[]),
|
||||
tools=[],
|
||||
system_prompt="You are a helpful assistant.",
|
||||
middleware=[NoopOne(), NoopTwo()],
|
||||
)
|
||||
|
||||
assert agent_two.compile().get_graph().draw_mermaid() == snapshot
|
||||
|
||||
agent_three = create_agent(
|
||||
model=FakeChatModel(messages=[]),
|
||||
tools=[],
|
||||
system_prompt="You are a helpful assistant.",
|
||||
middleware=[NoopOne(), NoopTwo(), NoopThree()],
|
||||
)
|
||||
|
||||
assert agent_three.compile().get_graph().draw_mermaid() == snapshot
|
||||
|
||||
agent_four = create_agent(
|
||||
model=FakeChatModel(messages=[]),
|
||||
tools=[],
|
||||
system_prompt="You are a helpful assistant.",
|
||||
middleware=[NoopFour()],
|
||||
)
|
||||
|
||||
assert agent_four.compile().get_graph().draw_mermaid() == snapshot
|
||||
|
||||
agent_five = create_agent(
|
||||
model=FakeChatModel(messages=[]),
|
||||
tools=[],
|
||||
system_prompt="You are a helpful assistant.",
|
||||
middleware=[NoopFour(), NoopFive()],
|
||||
)
|
||||
|
||||
assert agent_five.compile().get_graph().draw_mermaid() == snapshot
|
||||
|
||||
agent_six = create_agent(
|
||||
model=FakeChatModel(messages=[]),
|
||||
tools=[],
|
||||
system_prompt="You are a helpful assistant.",
|
||||
middleware=[NoopFour(), NoopFive(), NoopSix()],
|
||||
)
|
||||
|
||||
assert agent_six.compile().get_graph().draw_mermaid() == snapshot
|
||||
|
||||
agent_seven = create_agent(
|
||||
model=FakeChatModel(messages=[]),
|
||||
tools=[],
|
||||
system_prompt="You are a helpful assistant.",
|
||||
middleware=[NoopSeven()],
|
||||
)
|
||||
|
||||
assert agent_seven.compile().get_graph().draw_mermaid() == snapshot
|
||||
|
||||
agent_eight = create_agent(
|
||||
model=FakeChatModel(messages=[]),
|
||||
tools=[],
|
||||
system_prompt="You are a helpful assistant.",
|
||||
middleware=[NoopSeven(), NoopEight()],
|
||||
)
|
||||
|
||||
assert agent_eight.compile().get_graph().draw_mermaid() == snapshot
|
||||
|
||||
agent_nine = create_agent(
|
||||
model=FakeChatModel(messages=[]),
|
||||
tools=[],
|
||||
system_prompt="You are a helpful assistant.",
|
||||
middleware=[NoopSeven(), NoopEight(), NoopNine()],
|
||||
)
|
||||
|
||||
assert agent_nine.compile().get_graph().draw_mermaid() == snapshot
|
||||
|
||||
|
||||
def test_create_agent_invoke(
|
||||
snapshot: SnapshotAssertion,
|
||||
sync_checkpointer: BaseCheckpointSaver,
|
||||
):
|
||||
calls = []
|
||||
|
||||
class NoopSeven(AgentMiddleware):
|
||||
def before_model(self, state):
|
||||
calls.append("NoopSeven.before_model")
|
||||
|
||||
def modify_model_request(self, request, state):
|
||||
calls.append("NoopSeven.modify_model_request")
|
||||
return request
|
||||
|
||||
def after_model(self, state):
|
||||
calls.append("NoopSeven.after_model")
|
||||
|
||||
class NoopEight(AgentMiddleware):
|
||||
def before_model(self, state):
|
||||
calls.append("NoopEight.before_model")
|
||||
|
||||
def modify_model_request(self, request, state):
|
||||
calls.append("NoopEight.modify_model_request")
|
||||
return request
|
||||
|
||||
def after_model(self, state):
|
||||
calls.append("NoopEight.after_model")
|
||||
|
||||
def my_tool(input: str) -> str:
|
||||
"""A great tool"""
|
||||
calls.append("my_tool")
|
||||
return input.upper()
|
||||
|
||||
agent_one = create_agent(
|
||||
model=FakeChatModel(
|
||||
messages=[
|
||||
AIMessage(
|
||||
"",
|
||||
id="ai1",
|
||||
tool_calls=[ToolCall(id="1", name="my_tool", args={"input": "yo"})],
|
||||
),
|
||||
AIMessage(id="ai2", content="Hello, how can I assist you today?"),
|
||||
]
|
||||
),
|
||||
tools=[my_tool],
|
||||
system_prompt="You are a helpful assistant.",
|
||||
middleware=[NoopSeven(), NoopEight()],
|
||||
).compile(checkpointer=sync_checkpointer)
|
||||
|
||||
thread1 = {"configurable": {"thread_id": "1"}}
|
||||
assert agent_one.invoke({"messages": []}, thread1) == {
|
||||
"messages": [
|
||||
AIMessage(
|
||||
content="",
|
||||
additional_kwargs={},
|
||||
response_metadata={},
|
||||
id="ai1",
|
||||
tool_calls=[
|
||||
{
|
||||
"name": "my_tool",
|
||||
"args": {"input": "yo"},
|
||||
"id": "1",
|
||||
"type": "tool_call",
|
||||
}
|
||||
],
|
||||
),
|
||||
_AnyIdToolMessage(content="YO", name="my_tool", tool_call_id="1"),
|
||||
AIMessage(
|
||||
content="Hello, how can I assist you today?",
|
||||
additional_kwargs={},
|
||||
response_metadata={},
|
||||
id="ai2",
|
||||
),
|
||||
],
|
||||
}
|
||||
assert calls == [
|
||||
"NoopSeven.before_model",
|
||||
"NoopEight.before_model",
|
||||
"NoopSeven.modify_model_request",
|
||||
"NoopEight.modify_model_request",
|
||||
"NoopEight.after_model",
|
||||
"NoopSeven.after_model",
|
||||
"my_tool",
|
||||
"NoopSeven.before_model",
|
||||
"NoopEight.before_model",
|
||||
"NoopSeven.modify_model_request",
|
||||
"NoopEight.modify_model_request",
|
||||
"NoopEight.after_model",
|
||||
"NoopSeven.after_model",
|
||||
]
|
||||
|
||||
|
||||
def test_create_agent_jump(
|
||||
snapshot: SnapshotAssertion,
|
||||
sync_checkpointer: BaseCheckpointSaver,
|
||||
):
|
||||
calls = []
|
||||
|
||||
class NoopSeven(AgentMiddleware):
|
||||
def before_model(self, state):
|
||||
calls.append("NoopSeven.before_model")
|
||||
|
||||
def modify_model_request(self, request, state):
|
||||
calls.append("NoopSeven.modify_model_request")
|
||||
return request
|
||||
|
||||
def after_model(self, state):
|
||||
calls.append("NoopSeven.after_model")
|
||||
|
||||
class NoopEight(AgentMiddleware):
|
||||
def before_model(self, state) -> AgentJump:
|
||||
calls.append("NoopEight.before_model")
|
||||
return {"jump_to": END}
|
||||
|
||||
def modify_model_request(self, request, state):
|
||||
calls.append("NoopEight.modify_model_request")
|
||||
return request
|
||||
|
||||
def after_model(self, state):
|
||||
calls.append("NoopEight.after_model")
|
||||
|
||||
def my_tool(input: str) -> str:
|
||||
"""A great tool"""
|
||||
calls.append("my_tool")
|
||||
return input.upper()
|
||||
|
||||
agent_one = create_agent(
|
||||
model=FakeChatModel(
|
||||
messages=[
|
||||
AIMessage(
|
||||
"",
|
||||
id="ai1",
|
||||
tool_calls=[ToolCall(id="1", name="my_tool", args={"input": "yo"})],
|
||||
),
|
||||
AIMessage(id="ai2", content="Hello, how can I assist you today?"),
|
||||
]
|
||||
),
|
||||
tools=[my_tool],
|
||||
system_prompt="You are a helpful assistant.",
|
||||
middleware=[NoopSeven(), NoopEight()],
|
||||
).compile(checkpointer=sync_checkpointer)
|
||||
|
||||
if isinstance(sync_checkpointer, InMemorySaver):
|
||||
assert agent_one.get_graph().draw_mermaid() == snapshot
|
||||
|
||||
thread1 = {"configurable": {"thread_id": "1"}}
|
||||
assert agent_one.invoke({"messages": []}, thread1) == {"messages": []}
|
||||
assert calls == ["NoopSeven.before_model", "NoopEight.before_model"]
|
||||
Generated
+218
-218
@@ -194,15 +194,15 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "beautifulsoup4"
|
||||
version = "4.13.5"
|
||||
version = "4.13.4"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "soupsieve" },
|
||||
{ name = "typing-extensions" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/85/2e/3e5079847e653b1f6dc647aa24549d68c6addb4c595cc0d902d1b19308ad/beautifulsoup4-4.13.5.tar.gz", hash = "sha256:5e70131382930e7c3de33450a2f54a63d5e4b19386eab43a5b34d594268f3695", size = 622954, upload-time = "2025-08-24T14:06:13.168Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/d8/e4/0c4c39e18fd76d6a628d4dd8da40543d136ce2d1752bd6eeeab0791f4d6b/beautifulsoup4-4.13.4.tar.gz", hash = "sha256:dbb3c4e1ceae6aefebdaf2423247260cd062430a410e38c66f2baa50a8437195", size = 621067, upload-time = "2025-04-15T17:05:13.836Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/04/eb/f4151e0c7377a6e08a38108609ba5cede57986802757848688aeedd1b9e8/beautifulsoup4-4.13.5-py3-none-any.whl", hash = "sha256:642085eaa22233aceadff9c69651bc51e8bf3f874fb6d7104ece2beb24b47c4a", size = 105113, upload-time = "2025-08-24T14:06:14.884Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/50/cd/30110dc0ffcf3b131156077b90e9f60ed75711223f306da4db08eff8403b/beautifulsoup4-4.13.4-py3-none-any.whl", hash = "sha256:9bbbb14bfde9d79f38b8cd5f8c7c85f4b8f2523190ebed90e950a8dea4cb1c4b", size = 187285, upload-time = "2025-04-15T17:05:12.221Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -448,97 +448,97 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "coverage"
|
||||
version = "7.10.5"
|
||||
version = "7.10.4"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/61/83/153f54356c7c200013a752ce1ed5448573dca546ce125801afca9e1ac1a4/coverage-7.10.5.tar.gz", hash = "sha256:f2e57716a78bc3ae80b2207be0709a3b2b63b9f2dcf9740ee6ac03588a2015b6", size = 821662, upload-time = "2025-08-23T14:42:44.78Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/d6/4e/08b493f1f1d8a5182df0044acc970799b58a8d289608e0d891a03e9d269a/coverage-7.10.4.tar.gz", hash = "sha256:25f5130af6c8e7297fd14634955ba9e1697f47143f289e2a23284177c0061d27", size = 823798, upload-time = "2025-08-17T00:26:43.314Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/af/70/e77b0061a6c7157bfce645c6b9a715a08d4c86b3360a7b3252818080b817/coverage-7.10.5-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:c6a5c3414bfc7451b879141ce772c546985163cf553f08e0f135f0699a911801", size = 216774, upload-time = "2025-08-23T14:40:26.301Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/91/08/2a79de5ecf37ee40f2d898012306f11c161548753391cec763f92647837b/coverage-7.10.5-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:bc8e4d99ce82f1710cc3c125adc30fd1487d3cf6c2cd4994d78d68a47b16989a", size = 217175, upload-time = "2025-08-23T14:40:29.142Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/64/57/0171d69a699690149a6ba6a4eb702814448c8d617cf62dbafa7ce6bfdf63/coverage-7.10.5-cp310-cp310-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:02252dc1216e512a9311f596b3169fad54abcb13827a8d76d5630c798a50a754", size = 243931, upload-time = "2025-08-23T14:40:30.735Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/15/06/3a67662c55656702bd398a727a7f35df598eb11104fcb34f1ecbb070291a/coverage-7.10.5-cp310-cp310-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:73269df37883e02d460bee0cc16be90509faea1e3bd105d77360b512d5bb9c33", size = 245740, upload-time = "2025-08-23T14:40:32.302Z" },
|
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{ url = "https://files.pythonhosted.org/packages/20/9c/56f869d314edaa9fc1f491706d1d8a47747b9d714130368fbd69ce9024e9/ruff-0.12.9-py3-none-musllinux_1_2_i686.whl", hash = "sha256:f5cd34fabfdea3933ab85d72359f118035882a01bff15bd1d2b15261d85d5f66", size = 12534346, upload-time = "2025-08-14T16:08:43.39Z" },
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{ url = "https://files.pythonhosted.org/packages/bd/4b/d8b95c6795a6c93b439bc913ee7a94fda42bb30a79285d47b80074003ee7/ruff-0.12.9-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:f6be1d2ca0686c54564da8e7ee9e25f93bdd6868263805f8c0b8fc6a449db6d7", size = 13017021, upload-time = "2025-08-14T16:08:45.889Z" },
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{ url = "https://files.pythonhosted.org/packages/c7/c1/5f9a839a697ce1acd7af44836f7c2181cdae5accd17a5cb85fcbd694075e/ruff-0.12.9-py3-none-win32.whl", hash = "sha256:cc7a37bd2509974379d0115cc5608a1a4a6c4bff1b452ea69db83c8855d53f93", size = 11734785, upload-time = "2025-08-14T16:08:48.062Z" },
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{ url = "https://files.pythonhosted.org/packages/fa/66/cdddc2d1d9a9f677520b7cfc490d234336f523d4b429c1298de359a3be08/ruff-0.12.9-py3-none-win_amd64.whl", hash = "sha256:6fb15b1977309741d7d098c8a3cb7a30bc112760a00fb6efb7abc85f00ba5908", size = 12840654, upload-time = "2025-08-14T16:08:50.158Z" },
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{ url = "https://files.pythonhosted.org/packages/ac/fd/669816bc6b5b93b9586f3c1d87cd6bc05028470b3ecfebb5938252c47a35/ruff-0.12.9-py3-none-win_arm64.whl", hash = "sha256:63c8c819739d86b96d500cce885956a1a48ab056bbcbc61b747ad494b2485089", size = 11949623, upload-time = "2025-08-14T16:08:52.233Z" },
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||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -3106,15 +3106,15 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "starlette"
|
||||
version = "0.47.3"
|
||||
version = "0.47.2"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "anyio", marker = "python_full_version >= '3.11'" },
|
||||
{ name = "typing-extensions", marker = "python_full_version >= '3.11' and python_full_version < '3.13'" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/15/b9/cc3017f9a9c9b6e27c5106cc10cc7904653c3eec0729793aec10479dd669/starlette-0.47.3.tar.gz", hash = "sha256:6bc94f839cc176c4858894f1f8908f0ab79dfec1a6b8402f6da9be26ebea52e9", size = 2584144, upload-time = "2025-08-24T13:36:42.122Z" }
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||||
sdist = { url = "https://files.pythonhosted.org/packages/04/57/d062573f391d062710d4088fa1369428c38d51460ab6fedff920efef932e/starlette-0.47.2.tar.gz", hash = "sha256:6ae9aa5db235e4846decc1e7b79c4f346adf41e9777aebeb49dfd09bbd7023d8", size = 2583948, upload-time = "2025-07-20T17:31:58.522Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/ce/fd/901cfa59aaa5b30a99e16876f11abe38b59a1a2c51ffb3d7142bb6089069/starlette-0.47.3-py3-none-any.whl", hash = "sha256:89c0778ca62a76b826101e7c709e70680a1699ca7da6b44d38eb0a7e61fe4b51", size = 72991, upload-time = "2025-08-24T13:36:40.887Z" },
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||||
{ url = "https://files.pythonhosted.org/packages/f7/1f/b876b1f83aef204198a42dc101613fefccb32258e5428b5f9259677864b4/starlette-0.47.2-py3-none-any.whl", hash = "sha256:c5847e96134e5c5371ee9fac6fdf1a67336d5815e09eb2a01fdb57a351ef915b", size = 72984, upload-time = "2025-07-20T17:31:56.738Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -3251,11 +3251,11 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "types-python-dateutil"
|
||||
version = "2.9.0.20250822"
|
||||
version = "2.9.0.20250809"
|
||||
source = { registry = "https://pypi.org/simple" }
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||||
sdist = { url = "https://files.pythonhosted.org/packages/0c/0a/775f8551665992204c756be326f3575abba58c4a3a52eef9909ef4536428/types_python_dateutil-2.9.0.20250822.tar.gz", hash = "sha256:84c92c34bd8e68b117bff742bc00b692a1e8531262d4507b33afcc9f7716cd53", size = 16084, upload-time = "2025-08-22T03:02:00.613Z" }
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||||
sdist = { url = "https://files.pythonhosted.org/packages/a3/53/07dac71db45fb6b3c71c2fd29a87cada2239eac7ecfb318e6ebc7da00a3b/types_python_dateutil-2.9.0.20250809.tar.gz", hash = "sha256:69cbf8d15ef7a75c3801d65d63466e46ac25a0baa678d89d0a137fc31a608cc1", size = 15820, upload-time = "2025-08-09T03:14:14.109Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/ab/d9/a29dfa84363e88b053bf85a8b7f212a04f0d7343a4d24933baa45c06e08b/types_python_dateutil-2.9.0.20250822-py3-none-any.whl", hash = "sha256:849d52b737e10a6dc6621d2bd7940ec7c65fcb69e6aa2882acf4e56b2b508ddc", size = 17892, upload-time = "2025-08-22T03:01:59.436Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/43/5e/67312e679f612218d07fcdbd14017e6d571ce240a5ba1ad734f15a8523cc/types_python_dateutil-2.9.0.20250809-py3-none-any.whl", hash = "sha256:768890cac4f2d7fd9e0feb6f3217fce2abbfdfc0cadd38d11fba325a815e4b9f", size = 17707, upload-time = "2025-08-09T03:14:13.314Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -3272,11 +3272,11 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "typing-extensions"
|
||||
version = "4.15.0"
|
||||
version = "4.14.1"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/72/94/1a15dd82efb362ac84269196e94cf00f187f7ed21c242792a923cdb1c61f/typing_extensions-4.15.0.tar.gz", hash = "sha256:0cea48d173cc12fa28ecabc3b837ea3cf6f38c6d1136f85cbaaf598984861466", size = 109391, upload-time = "2025-08-25T13:49:26.313Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/98/5a/da40306b885cc8c09109dc2e1abd358d5684b1425678151cdaed4731c822/typing_extensions-4.14.1.tar.gz", hash = "sha256:38b39f4aeeab64884ce9f74c94263ef78f3c22467c8724005483154c26648d36", size = 107673, upload-time = "2025-07-04T13:28:34.16Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl", hash = "sha256:f0fa19c6845758ab08074a0cfa8b7aecb71c999ca73d62883bc25cc018c4e548", size = 44614, upload-time = "2025-08-25T13:49:24.86Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/b5/00/d631e67a838026495268c2f6884f3711a15a9a2a96cd244fdaea53b823fb/typing_extensions-4.14.1-py3-none-any.whl", hash = "sha256:d1e1e3b58374dc93031d6eda2420a48ea44a36c2b4766a4fdeb3710755731d76", size = 43906, upload-time = "2025-07-04T13:28:32.743Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
||||
@@ -38,6 +38,7 @@ from typing_extensions import Annotated, NotRequired, TypedDict
|
||||
|
||||
from langgraph._internal._runnable import RunnableCallable, RunnableLike
|
||||
from langgraph._internal._typing import MISSING
|
||||
from langgraph.agent.types import AgentMiddleware
|
||||
from langgraph.errors import ErrorCode, create_error_message
|
||||
from langgraph.graph import END, StateGraph
|
||||
from langgraph.graph.message import add_messages
|
||||
@@ -261,6 +262,7 @@ def create_react_agent(
|
||||
],
|
||||
tools: Union[Sequence[Union[BaseTool, Callable, dict[str, Any]]], ToolNode],
|
||||
*,
|
||||
middleware: Sequence[AgentMiddleware] = (),
|
||||
prompt: Optional[Prompt] = None,
|
||||
response_format: Optional[
|
||||
Union[StructuredResponseSchema, tuple[str, StructuredResponseSchema]]
|
||||
@@ -462,6 +464,32 @@ def create_react_agent(
|
||||
print(chunk)
|
||||
```
|
||||
"""
|
||||
if middleware:
|
||||
assert isinstance(model, str | BaseChatModel)
|
||||
assert isinstance(prompt, str | None)
|
||||
assert not isinstance(response_format, tuple)
|
||||
assert pre_model_hook is None
|
||||
assert post_model_hook is None
|
||||
assert state_schema is None
|
||||
|
||||
from langgraph.agent import create_agent
|
||||
|
||||
return create_agent(
|
||||
model=model,
|
||||
tools=tools,
|
||||
system_prompt=prompt,
|
||||
middleware=middleware,
|
||||
response_format=response_format,
|
||||
context_schema=context_schema,
|
||||
).compile(
|
||||
checkpointer=checkpointer,
|
||||
store=store,
|
||||
name=name,
|
||||
interrupt_after=interrupt_after,
|
||||
interrupt_before=interrupt_before,
|
||||
debug=debug,
|
||||
)
|
||||
|
||||
if (
|
||||
config_schema := deprecated_kwargs.pop("config_schema", MISSING)
|
||||
) is not MISSING:
|
||||
|
||||
@@ -443,12 +443,7 @@ class ToolNode(RunnableCallable):
|
||||
return invalid_tool_message
|
||||
try:
|
||||
call_args = {**call, **{"type": "tool_call"}}
|
||||
tool = self.tools_by_name[call["name"]]
|
||||
|
||||
try:
|
||||
response = tool.invoke(call_args, config)
|
||||
except NotImplementedError:
|
||||
response = asyncio.run(tool.ainvoke(call_args, config))
|
||||
response = self.tools_by_name[call["name"]].invoke(call_args, config)
|
||||
|
||||
# GraphInterrupt is a special exception that will always be raised.
|
||||
# It can be triggered in the following scenarios,
|
||||
|
||||
@@ -1156,36 +1156,3 @@ async def test_tool_node_command_remove_all_messages():
|
||||
command = result[0]
|
||||
assert isinstance(command, Command)
|
||||
assert command.update == {"messages": [RemoveMessage(id=REMOVE_ALL_MESSAGES)]}
|
||||
|
||||
|
||||
async def test_async_tool_called_syncly() -> None:
|
||||
"""Confirm that async tools can be called synchronously."""
|
||||
|
||||
@dec_tool
|
||||
async def async_tool():
|
||||
"""An async tool."""
|
||||
return "async tool"
|
||||
|
||||
tool_node = ToolNode([async_tool])
|
||||
result = tool_node.invoke(
|
||||
{
|
||||
"messages": [
|
||||
AIMessage(
|
||||
content="",
|
||||
tool_calls=[
|
||||
{
|
||||
"name": "async_tool",
|
||||
"args": {},
|
||||
"id": "1",
|
||||
"type": "tool_call",
|
||||
}
|
||||
],
|
||||
)
|
||||
]
|
||||
}
|
||||
)
|
||||
assert result == {
|
||||
"messages": [
|
||||
ToolMessage(content="async tool", name="async_tool", tool_call_id="1")
|
||||
]
|
||||
}
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
from langgraph_sdk.auth import Auth
|
||||
from langgraph_sdk.client import get_client, get_sync_client
|
||||
|
||||
__version__ = "0.2.4"
|
||||
__version__ = "0.2.3"
|
||||
|
||||
__all__ = ["Auth", "get_client", "get_sync_client"]
|
||||
|
||||
@@ -15,7 +15,6 @@ import logging
|
||||
import os
|
||||
import re
|
||||
import sys
|
||||
import warnings
|
||||
from collections.abc import AsyncIterator, Iterator, Mapping, Sequence
|
||||
from types import TracebackType
|
||||
from typing import (
|
||||
@@ -46,7 +45,6 @@ from langgraph_sdk.schema import (
|
||||
CronSelectField,
|
||||
CronSortBy,
|
||||
DisconnectMode,
|
||||
Durability,
|
||||
GraphSchema,
|
||||
IfNotExists,
|
||||
Item,
|
||||
@@ -71,7 +69,6 @@ from langgraph_sdk.schema import (
|
||||
ThreadSortBy,
|
||||
ThreadState,
|
||||
ThreadStatus,
|
||||
ThreadStreamMode,
|
||||
ThreadUpdateStateResponse,
|
||||
)
|
||||
from langgraph_sdk.sse import SSEDecoder, aiter_lines_raw, iter_lines_raw
|
||||
@@ -1685,53 +1682,6 @@ class ThreadsClient:
|
||||
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:
|
||||
Iterator[StreamPart]: 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)
|
||||
```
|
||||
|
||||
""" # noqa: E501
|
||||
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,
|
||||
)
|
||||
|
||||
|
||||
class RunsClient:
|
||||
"""Client for managing runs in LangGraph.
|
||||
@@ -1822,7 +1772,7 @@ class RunsClient:
|
||||
context: Context | None = None,
|
||||
checkpoint: Checkpoint | None = None,
|
||||
checkpoint_id: str | None = None,
|
||||
checkpoint_during: bool | None = None, # deprecated
|
||||
checkpoint_during: bool | None = None,
|
||||
interrupt_before: All | Sequence[str] | None = None,
|
||||
interrupt_after: All | Sequence[str] | None = None,
|
||||
feedback_keys: Sequence[str] | None = None,
|
||||
@@ -1835,7 +1785,6 @@ class RunsClient:
|
||||
headers: Mapping[str, str] | None = None,
|
||||
params: QueryParamTypes | None = None,
|
||||
on_run_created: Callable[[RunCreateMetadata], None] | None = None,
|
||||
durability: Durability | None = None,
|
||||
) -> AsyncIterator[StreamPart]:
|
||||
"""Create a run and stream the results.
|
||||
|
||||
@@ -1855,7 +1804,7 @@ class RunsClient:
|
||||
context: Static context to add to the assistant.
|
||||
!!! version-added "Supported with langgraph>=0.6.0"
|
||||
checkpoint: The checkpoint to resume from.
|
||||
checkpoint_during: (deprecated) Whether to checkpoint during the run (or only at the end/interruption).
|
||||
checkpoint_during: 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.
|
||||
feedback_keys: Feedback keys to assign to run.
|
||||
@@ -1873,10 +1822,6 @@ class RunsClient:
|
||||
headers: Optional custom headers to include with the request.
|
||||
params: Optional query parameters to include with the request.
|
||||
on_run_created: Callback when a run is created.
|
||||
durability: The durability to use for the run. Values are "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
|
||||
|
||||
Returns:
|
||||
AsyncIterator[StreamPart]: Asynchronous iterator of stream results.
|
||||
@@ -1912,13 +1857,6 @@ class RunsClient:
|
||||
```
|
||||
|
||||
""" # noqa: E501
|
||||
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 = {
|
||||
"input": input,
|
||||
"command": (
|
||||
@@ -1943,7 +1881,6 @@ class RunsClient:
|
||||
"on_disconnect": on_disconnect,
|
||||
"on_completion": on_completion,
|
||||
"after_seconds": after_seconds,
|
||||
"durability": durability,
|
||||
}
|
||||
endpoint = (
|
||||
f"/threads/{thread_id}/runs/stream"
|
||||
@@ -2034,7 +1971,7 @@ class RunsClient:
|
||||
context: Context | None = None,
|
||||
checkpoint: Checkpoint | None = None,
|
||||
checkpoint_id: str | None = None,
|
||||
checkpoint_during: bool | None = None, # deprecated
|
||||
checkpoint_during: bool | None = None,
|
||||
interrupt_before: All | Sequence[str] | None = None,
|
||||
interrupt_after: All | Sequence[str] | None = None,
|
||||
webhook: str | None = None,
|
||||
@@ -2045,7 +1982,6 @@ class RunsClient:
|
||||
headers: Mapping[str, str] | None = None,
|
||||
params: QueryParamTypes | None = None,
|
||||
on_run_created: Callable[[RunCreateMetadata], None] | None = None,
|
||||
durability: Durability | None = None,
|
||||
) -> Run:
|
||||
"""Create a background run.
|
||||
|
||||
@@ -2065,7 +2001,7 @@ class RunsClient:
|
||||
context: Static context to add to the assistant.
|
||||
!!! version-added "Supported with langgraph>=0.6.0"
|
||||
checkpoint: The checkpoint to resume from.
|
||||
checkpoint_during: (deprecated) Whether to checkpoint during the run (or only at the end/interruption).
|
||||
checkpoint_during: 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.
|
||||
@@ -2079,10 +2015,6 @@ class RunsClient:
|
||||
Use to schedule future runs.
|
||||
headers: Optional custom headers to include with the request.
|
||||
on_run_created: Optional callback to call when a run is created.
|
||||
durability: The durability to use for the run. Values are "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
|
||||
|
||||
Returns:
|
||||
Run: The created background run.
|
||||
@@ -2158,12 +2090,6 @@ class RunsClient:
|
||||
}
|
||||
```
|
||||
""" # noqa: E501
|
||||
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 = {
|
||||
"input": input,
|
||||
"command": (
|
||||
@@ -2186,7 +2112,6 @@ class RunsClient:
|
||||
"if_not_exists": if_not_exists,
|
||||
"on_completion": on_completion,
|
||||
"after_seconds": after_seconds,
|
||||
"durability": durability,
|
||||
}
|
||||
payload = {k: v for k, v in payload.items() if v is not None}
|
||||
|
||||
@@ -2284,7 +2209,7 @@ class RunsClient:
|
||||
context: Context | None = None,
|
||||
checkpoint: Checkpoint | None = None,
|
||||
checkpoint_id: str | None = None,
|
||||
checkpoint_during: bool | None = None, # deprecated
|
||||
checkpoint_during: bool | None = None,
|
||||
interrupt_before: All | Sequence[str] | None = None,
|
||||
interrupt_after: All | Sequence[str] | None = None,
|
||||
webhook: str | None = None,
|
||||
@@ -2297,7 +2222,6 @@ class RunsClient:
|
||||
headers: Mapping[str, str] | None = None,
|
||||
params: QueryParamTypes | None = None,
|
||||
on_run_created: Callable[[RunCreateMetadata], None] | None = None,
|
||||
durability: Durability | None = None,
|
||||
) -> list[dict] | dict[str, Any]:
|
||||
"""Create a run, wait until it finishes and return the final state.
|
||||
|
||||
@@ -2313,7 +2237,7 @@ class RunsClient:
|
||||
context: Static context to add to the assistant.
|
||||
!!! version-added "Supported with langgraph>=0.6.0"
|
||||
checkpoint: The checkpoint to resume from.
|
||||
checkpoint_during: (deprecated) Whether to checkpoint during the run (or only at the end/interruption).
|
||||
checkpoint_during: 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.
|
||||
@@ -2329,10 +2253,6 @@ class RunsClient:
|
||||
Use to schedule future runs.
|
||||
headers: Optional custom headers to include with the request.
|
||||
on_run_created: Optional callback to call when a run is created.
|
||||
durability: The durability to use for the run. Values are "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
|
||||
|
||||
Returns:
|
||||
Union[list[dict], dict[str, Any]]: The output of the run.
|
||||
@@ -2386,12 +2306,6 @@ class RunsClient:
|
||||
```
|
||||
|
||||
""" # noqa: E501
|
||||
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 = {
|
||||
"input": input,
|
||||
"command": (
|
||||
@@ -2412,7 +2326,6 @@ class RunsClient:
|
||||
"on_disconnect": on_disconnect,
|
||||
"on_completion": on_completion,
|
||||
"after_seconds": after_seconds,
|
||||
"durability": durability,
|
||||
}
|
||||
endpoint = (
|
||||
f"/threads/{thread_id}/runs/wait" if thread_id is not None else "/runs/wait"
|
||||
@@ -4820,54 +4733,6 @@ class SyncThreadsClient:
|
||||
params=params,
|
||||
)
|
||||
|
||||
def join_stream(
|
||||
self,
|
||||
thread_id: str,
|
||||
*,
|
||||
stream_mode: ThreadStreamMode | Sequence[ThreadStreamMode] = "run_modes",
|
||||
last_event_id: str | None = None,
|
||||
headers: Mapping[str, str] | None = None,
|
||||
params: QueryParamTypes | None = None,
|
||||
) -> Iterator[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:
|
||||
Iterator[StreamPart]: 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",
|
||||
stream_mode="run_modes",
|
||||
):
|
||||
print(chunk)
|
||||
```
|
||||
|
||||
""" # noqa: E501
|
||||
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,
|
||||
)
|
||||
|
||||
|
||||
class SyncRunsClient:
|
||||
"""Synchronous client for managing runs in LangGraph.
|
||||
@@ -4958,7 +4823,7 @@ class SyncRunsClient:
|
||||
context: Context | None = None,
|
||||
checkpoint: Checkpoint | None = None,
|
||||
checkpoint_id: str | None = None,
|
||||
checkpoint_during: bool | None = None, # deprecated
|
||||
checkpoint_during: bool | None = None,
|
||||
interrupt_before: All | Sequence[str] | None = None,
|
||||
interrupt_after: All | Sequence[str] | None = None,
|
||||
feedback_keys: Sequence[str] | None = None,
|
||||
@@ -4971,7 +4836,6 @@ class SyncRunsClient:
|
||||
headers: Mapping[str, str] | None = None,
|
||||
params: QueryParamTypes | None = None,
|
||||
on_run_created: Callable[[RunCreateMetadata], None] | None = None,
|
||||
durability: Durability | None = None,
|
||||
) -> Iterator[StreamPart]:
|
||||
"""Create a run and stream the results.
|
||||
|
||||
@@ -4991,7 +4855,7 @@ class SyncRunsClient:
|
||||
context: Static context to add to the assistant.
|
||||
!!! version-added "Supported with langgraph>=0.6.0"
|
||||
checkpoint: The checkpoint to resume from.
|
||||
checkpoint_during: (deprecated) Whether to checkpoint during the run (or only at the end/interruption).
|
||||
checkpoint_during: 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.
|
||||
feedback_keys: Feedback keys to assign to run.
|
||||
@@ -5008,11 +4872,6 @@ class SyncRunsClient:
|
||||
Use to schedule future runs.
|
||||
headers: Optional custom headers to include with the request.
|
||||
on_run_created: Optional callback to call when a run is created.
|
||||
durability: The durability to use for the run. Values are "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
|
||||
|
||||
|
||||
Returns:
|
||||
Iterator[StreamPart]: Iterator of stream results.
|
||||
@@ -5045,12 +4904,6 @@ class SyncRunsClient:
|
||||
StreamPart(event='end', data=None)
|
||||
```
|
||||
""" # noqa: E501
|
||||
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 = {
|
||||
"input": input,
|
||||
"command": (
|
||||
@@ -5075,7 +4928,6 @@ class SyncRunsClient:
|
||||
"on_disconnect": on_disconnect,
|
||||
"on_completion": on_completion,
|
||||
"after_seconds": after_seconds,
|
||||
"durability": durability,
|
||||
}
|
||||
endpoint = (
|
||||
f"/threads/{thread_id}/runs/stream"
|
||||
@@ -5166,7 +5018,7 @@ class SyncRunsClient:
|
||||
context: Context | None = None,
|
||||
checkpoint: Checkpoint | None = None,
|
||||
checkpoint_id: str | None = None,
|
||||
checkpoint_during: bool | None = None, # deprecated
|
||||
checkpoint_during: bool | None = None,
|
||||
interrupt_before: All | Sequence[str] | None = None,
|
||||
interrupt_after: All | Sequence[str] | None = None,
|
||||
webhook: str | None = None,
|
||||
@@ -5177,7 +5029,6 @@ class SyncRunsClient:
|
||||
headers: Mapping[str, str] | None = None,
|
||||
params: QueryParamTypes | None = None,
|
||||
on_run_created: Callable[[RunCreateMetadata], None] | None = None,
|
||||
durability: Durability | None = None,
|
||||
) -> Run:
|
||||
"""Create a background run.
|
||||
|
||||
@@ -5197,7 +5048,7 @@ class SyncRunsClient:
|
||||
context: Static context to add to the assistant.
|
||||
!!! version-added "Supported with langgraph>=0.6.0"
|
||||
checkpoint: The checkpoint to resume from.
|
||||
checkpoint_during: (deprecated) Whether to checkpoint during the run (or only at the end/interruption).
|
||||
checkpoint_during: 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.
|
||||
@@ -5211,10 +5062,6 @@ class SyncRunsClient:
|
||||
Use to schedule future runs.
|
||||
headers: Optional custom headers to include with the request.
|
||||
on_run_created: Optional callback to call when a run is created.
|
||||
durability: The durability to use for the run. Values are "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
|
||||
|
||||
Returns:
|
||||
Run: The created background run.
|
||||
@@ -5290,12 +5137,6 @@ class SyncRunsClient:
|
||||
}
|
||||
```
|
||||
""" # noqa: E501
|
||||
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 = {
|
||||
"input": input,
|
||||
"command": (
|
||||
@@ -5318,7 +5159,6 @@ class SyncRunsClient:
|
||||
"if_not_exists": if_not_exists,
|
||||
"on_completion": on_completion,
|
||||
"after_seconds": after_seconds,
|
||||
"durability": durability,
|
||||
}
|
||||
payload = {k: v for k, v in payload.items() if v is not None}
|
||||
|
||||
@@ -5414,7 +5254,7 @@ class SyncRunsClient:
|
||||
metadata: Mapping[str, Any] | None = None,
|
||||
config: Config | None = None,
|
||||
context: Context | None = None,
|
||||
checkpoint_during: bool | None = None, # deprecated
|
||||
checkpoint_during: bool | None = None,
|
||||
checkpoint: Checkpoint | None = None,
|
||||
checkpoint_id: str | None = None,
|
||||
interrupt_before: All | Sequence[str] | None = None,
|
||||
@@ -5429,7 +5269,6 @@ class SyncRunsClient:
|
||||
headers: Mapping[str, str] | None = None,
|
||||
params: QueryParamTypes | None = None,
|
||||
on_run_created: Callable[[RunCreateMetadata], None] | None = None,
|
||||
durability: Durability | None = None,
|
||||
) -> list[dict] | dict[str, Any]:
|
||||
"""Create a run, wait until it finishes and return the final state.
|
||||
|
||||
@@ -5445,7 +5284,7 @@ class SyncRunsClient:
|
||||
context: Static context to add to the assistant.
|
||||
!!! version-added "Supported with langgraph>=0.6.0"
|
||||
checkpoint: The checkpoint to resume from.
|
||||
checkpoint_during: (deprecated) Whether to checkpoint during the run (or only at the end/interruption).
|
||||
checkpoint_during: 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.
|
||||
@@ -5462,10 +5301,6 @@ class SyncRunsClient:
|
||||
raise_error: Whether to raise an error if the run fails.
|
||||
headers: Optional custom headers to include with the request.
|
||||
on_run_created: Optional callback to call when a run is created.
|
||||
durability: The durability to use for the run. Values are "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
|
||||
|
||||
Returns:
|
||||
Union[list[dict], dict[str, Any]]: The output of the run.
|
||||
@@ -5520,12 +5355,6 @@ class SyncRunsClient:
|
||||
```
|
||||
|
||||
""" # noqa: E501
|
||||
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 = {
|
||||
"input": input,
|
||||
"command": (
|
||||
@@ -5547,7 +5376,6 @@ class SyncRunsClient:
|
||||
"on_completion": on_completion,
|
||||
"after_seconds": after_seconds,
|
||||
"raise_error": raise_error,
|
||||
"durability": durability,
|
||||
}
|
||||
|
||||
def on_response(res: httpx.Response):
|
||||
|
||||
@@ -38,14 +38,6 @@ Represents the status of a thread:
|
||||
- "error": An exception occurred during task processing.
|
||||
"""
|
||||
|
||||
ThreadStreamMode = Literal["run_modes", "lifecycle", "state_update"]
|
||||
"""
|
||||
Defines the mode of streaming:
|
||||
- "run_modes": Stream the same events as the runs on thread, as well as run_done events.
|
||||
- "lifecycle": Stream only run start/end events.
|
||||
- "state_update": Stream state updates on the thread.
|
||||
"""
|
||||
|
||||
StreamMode = Literal[
|
||||
"values",
|
||||
"messages",
|
||||
@@ -99,12 +91,6 @@ Defines action after completion:
|
||||
- "keep": Retain resources after completion.
|
||||
"""
|
||||
|
||||
Durability = Literal["sync", "async", "exit"]
|
||||
"""Durability mode for the graph execution.
|
||||
- `"sync"`: Changes are persisted synchronously before the next step starts.
|
||||
- `"async"`: Changes are persisted asynchronously while the next step executes.
|
||||
- `"exit"`: Changes are persisted only when the graph exits."""
|
||||
|
||||
All = Literal["*"]
|
||||
"""Represents a wildcard or 'all' selector."""
|
||||
|
||||
|
||||
Reference in New Issue
Block a user