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Author SHA1 Message Date
Sydney Runkle 9aab70bd73 experimental stop when 2025-08-12 16:19:16 -04:00
Sydney Runkle aaea76b475 hacky solution for now 2025-08-11 19:44:02 -04:00
61 changed files with 2148 additions and 6298 deletions
+2 -7
View File
@@ -1,15 +1,10 @@
import ast
import os
from itertools import filterfalse
from typing import Dict, List, Tuple
from typing import List, Tuple
ROOT_PATH = os.path.abspath(os.path.join(__file__, "..", "..", ".."))
CLIENT_PATH = os.path.join(ROOT_PATH, "libs", "sdk-py", "langgraph_sdk", "client.py")
ASYNC_TO_SYNC_METHOD_MAP: Dict[str, str] = {
"aclose": "close",
"__aenter__": "__enter__",
"__aexit__": "__exit__",
}
def get_class_methods(node: ast.ClassDef) -> List[str]:
@@ -27,7 +22,7 @@ def find_classes(tree: ast.AST) -> List[Tuple[str, List[str]]]:
def compare_sync_async_methods(sync_methods: List[str], async_methods: List[str]) -> List[str]:
sync_set = set(sync_methods)
async_set = {ASYNC_TO_SYNC_METHOD_MAP.get(async_method, async_method) for async_method in async_methods}
async_set = set(async_methods)
missing_in_sync = list(async_set - sync_set)
missing_in_async = list(sync_set - async_set)
return missing_in_sync + missing_in_async
+86 -124
View File
@@ -1,145 +1,107 @@
import asyncio
import json
import os
import pathlib
import sys
import time
from urllib import request, error
import langgraph_cli
import langgraph_cli.config
import langgraph_cli.docker
from langgraph_cli.cli import prepare_args_and_stdin
from langgraph_cli.constants import DEFAULT_PORT
import langgraph_cli.config
from langgraph_cli.exec import Runner, subp_exec
from langgraph_cli.progress import Progress
from langgraph_cli.constants import DEFAULT_PORT
def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
"""Spin up API with Postgres/Redis via docker compose and wait until ready."""
def test(
config: pathlib.Path,
port: int,
tag: str,
verbose: bool,
):
with Runner() as runner, Progress(message="Pulling...") as set:
# Detect docker/compose capabilities
# check docker available
capabilities = langgraph_cli.docker.check_capabilities(runner)
# Validate config and prepare compose stdin/args using built image
# open config
config_json = langgraph_cli.config.validate_config_file(config)
args, stdin = prepare_args_and_stdin(
capabilities=capabilities,
config_path=config,
config=config_json,
docker_compose=None,
port=port,
watch=False,
debugger_port=None,
debugger_base_url=f"http://127.0.0.1:{port}",
postgres_uri=None,
api_version=None,
image=tag,
base_image=None,
)
# Compose up with wait (implies detach), similar to `langgraph up --wait`
args_up = [*args, "up", "--remove-orphans", "--wait"]
set("Running...")
args = [
"run",
"--rm",
"-p",
f"{port}:8000",
]
if isinstance(config_json["env"], str):
args.extend(
[
"--env-file",
str(config.parent / config_json["env"]),
]
)
else:
for k, v in config_json["env"].items():
args.extend(
[
"-e",
f"{k}={v}",
]
)
if capabilities.healthcheck_start_interval:
args.extend(
[
"--health-interval",
"5s",
"--health-retries",
"1",
"--health-start-period",
"10s",
"--health-start-interval",
"1s",
]
)
else:
args.extend(
[
"--health-interval",
"5s",
"--health-retries",
"2",
]
)
compose_cmd = ["docker", "compose"]
if capabilities.compose_type == "standalone":
compose_cmd = ["docker-compose"]
_task = None
def on_stdout(line: str):
nonlocal _task
if "GET /ok" in line or "Uvicorn running on" in line:
set("")
sys.stdout.write(
f"""Ready!
- API: http://localhost:{port}
"""
)
sys.stdout.flush()
_task.cancel()
return True
return False
async def subp_exec_task(*args, **kwargs):
nonlocal _task
_task = asyncio.create_task(subp_exec(*args, **kwargs))
await _task
set("Starting...")
try:
runner.run(
subp_exec(
*compose_cmd,
*args_up,
input=stdin,
subp_exec_task(
"docker",
*args,
tag,
verbose=verbose,
on_stdout=on_stdout,
)
)
except Exception as e: # noqa: BLE001
# On failure, show diagnostics then ensure clean teardown
sys.stderr.write(f"docker compose up failed: {e}\n")
try:
sys.stderr.write("\n== docker compose ps ==\n")
runner.run(subp_exec(*compose_cmd, *args, "ps", input=stdin, verbose=False))
except Exception:
pass
try:
sys.stderr.write("\n== docker compose logs (api) ==\n")
runner.run(
subp_exec(
*compose_cmd,
*args,
"logs",
"langgraph-api",
input=stdin,
verbose=False,
)
)
except Exception:
pass
finally:
try:
runner.run(
subp_exec(
*compose_cmd,
*args,
"down",
"-v",
"--remove-orphans",
input=stdin,
verbose=False,
)
)
finally:
raise
set("")
base_url = f"http://localhost:{port}"
ok_url = f"{base_url}/ok"
print(f"Waiting for {ok_url} to respond with 200...")
deadline = time.time() + 30
last_err: Exception | None = None
while time.time() < deadline:
try:
with request.urlopen(ok_url, timeout=2) as resp:
if resp.status == 200:
sys.stdout.write(
f"""Ready!\n- API: {base_url}\n- /ok: 200 OK\n"""
)
sys.stdout.flush()
break
else:
last_err = RuntimeError(f"Unexpected status: {resp.status}")
print(f"Unexpected status: {resp.status}")
except error.URLError as e:
last_err = e
except Exception as e: # noqa: BLE001
last_err = e
time.sleep(0.5)
else:
# Bring stack down before raising
args_down = [*args, "down", "-v", "--remove-orphans"]
try:
runner.run(
subp_exec(
*compose_cmd,
*args_down,
input=stdin,
verbose=verbose,
)
)
finally:
raise SystemExit(
f"/ok did not return 202 within timeout. Last error: {last_err}"
)
# Clean up: bring compose stack down to free ports for next test
args_down = [*args, "down", "-v", "--remove-orphans"]
runner.run(
subp_exec(
*compose_cmd,
*args_down,
input=stdin,
verbose=verbose,
)
)
except asyncio.CancelledError:
pass
if __name__ == "__main__":
@@ -148,6 +110,6 @@ if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("-t", "--tag", type=str)
parser.add_argument("-c", "--config", type=str, default="./langgraph.json")
parser.add_argument("-p", "--port", type=int, default=DEFAULT_PORT)
parser.add_argument("-p", "--port", default=DEFAULT_PORT)
args = parser.parse_args()
test(pathlib.Path(args.config), args.port, args.tag, verbose=True)
+5 -20
View File
@@ -43,43 +43,28 @@ jobs:
- name: Build and test service A
if: steps.changed-files.outputs.all
working-directory: libs/cli/examples
env:
LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
run: |
# The build-arg isn't used; just testing that we accept other args
langgraph build -t langgraph-test-a
cp .env.example .env
if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
langgraph build -t langgraph-test-a --base-image "langchain/langgraph-trial"
cp .env.example .envg
timeout 60 python ../../../.github/scripts/run_langgraph_cli_test.py -c langgraph.json -t langgraph-test-a
- name: Build and test service B
if: steps.changed-files.outputs.all
working-directory: libs/cli/examples/graphs
env:
LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
run: |
langgraph build -t langgraph-test-b
cp ../.env.example .env
if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
langgraph build -t langgraph-test-b --base-image "langchain/langgraph-trial"
timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-b
- name: Build and test service C
if: steps.changed-files.outputs.all
working-directory: libs/cli/examples/graphs_reqs_a
env:
LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
run: |
langgraph build -t langgraph-test-c
cp ../.env.example .env
if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
langgraph build -t langgraph-test-c --base-image "langchain/langgraph-trial"
timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-c
- name: Build and test service D
if: steps.changed-files.outputs.all
working-directory: libs/cli/examples/graphs_reqs_b
env:
LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
run: |
langgraph build -t langgraph-test-d
cp ../.env.example .env
if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
langgraph build -t langgraph-test-d --base-image "langchain/langgraph-trial"
timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-d
- name: Build JS service
+1
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@@ -17,6 +17,7 @@ jobs:
strategy:
matrix:
python-version:
- "3.9"
- "3.10"
- "3.11"
- "3.12"
+1
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@@ -12,6 +12,7 @@ jobs:
strategy:
matrix:
python-version:
- "3.9"
- "3.10"
- "3.11"
- "3.12"
+1
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@@ -16,6 +16,7 @@ permissions:
jobs:
build:
if: github.ref == 'refs/heads/main'
runs-on: ubuntu-latest
outputs:
-1
View File
@@ -78,7 +78,6 @@ jobs:
"libs/checkpoint-sqlite",
"libs/checkpoint-postgres",
"libs/prebuilt",
"libs/sdk-py",
]
if: needs.changes.outputs.python == 'true' || needs.changes.outputs.deps == 'true'
uses: ./.github/workflows/_test.yml
+2 -7
View File
@@ -16,6 +16,7 @@ env:
jobs:
build:
if: github.ref == 'refs/heads/main'
runs-on: ubuntu-latest
outputs:
@@ -61,13 +62,7 @@ jobs:
working-directory: ${{ inputs.working-directory }}
run: |
PKG_NAME=$(grep -m 1 "^name = " pyproject.toml | cut -d '"' -f 2)
if grep -q 'dynamic.*=.*\[.*"version".*\]' pyproject.toml; then
# handle dynamic versioning
DIR_NAME=$(echo "$PKG_NAME" | tr '-' '_')
VERSION=$(grep -m 1 '^__version__' "${DIR_NAME}/__init__.py" | cut -d '"' -f 2)
else
VERSION=$(grep -m 1 "^version = " pyproject.toml | cut -d '"' -f 2)
fi
VERSION=$(grep -m 1 "^version = " pyproject.toml | cut -d '"' -f 2)
SHORT_PKG_NAME="$(echo "$PKG_NAME" | sed -e 's/langgraph//g' -e 's/-//g')"
if [ -z $SHORT_PKG_NAME ]; then
TAG="$VERSION"
+1 -1
View File
@@ -22,7 +22,7 @@ jobs:
uses: astral-sh/setup-uv@v6
with:
# use minimum supported Python version
python-version: "3.10"
python-version: "3.9"
enable-cache: true
cache-suffix: "uv-lock-upgrade"
+2 -2
View File
@@ -190,11 +190,11 @@ REDIRECT_MAP = {
"concepts/langgraph_cloud.md": "https://docs.langchain.com/langgraph-platform/cloud",
"concepts/langgraph_self_hosted_data_plane.md": "https://docs.langchain.com/langgraph-platform/hybrid",
"concepts/langgraph_self_hosted_control_plane.md": "https://docs.langchain.com/langgraph-platform/self-hosted",
"concepts/langgraph_standalone_container.md": "https://docs.langchain.com/langgraph-platform/self-hosted#standalone-server",
"concepts/langgraph_standalone_container.md": "https://docs.langchain.com/langgraph-platform/self-hosted#data-plane-only",
"cloud/deployment/cloud.md": "https://docs.langchain.com/langgraph-platform/cloud",
"cloud/deployment/self_hosted_data_plane.md": "https://docs.langchain.com/langgraph-platform/deploy-hybrid",
"cloud/deployment/self_hosted_control_plane.md": "https://docs.langchain.com/langgraph-platform/deploy-self-hosted-full-platform",
"cloud/deployment/standalone_container.md": "https://docs.langchain.com/langgraph-platform/deploy-standalone-server",
"cloud/deployment/standalone_container.md": "https://docs.langchain.com/langgraph-platform/deploy-data-plane-only",
"concepts/server-mcp.md": "https://docs.langchain.com/langgraph-platform/server-mcp",
"cloud/how-tos/human_in_the_loop_time_travel.md": "https://docs.langchain.com/langgraph-platform/human-in-the-loop-time-travel",
"cloud/how-tos/add-human-in-the-loop.md": "https://docs.langchain.com/langgraph-platform/add-human-in-the-loop",
+8 -9
View File
@@ -367,13 +367,13 @@ To implement handoffs with `createReactAgent`, you need to:
3. Define a parent graph that contains individual agents as nodes:
```typescript
import { StateGraph, MessagesZodState } from "@langchain/langgraph";
const multiAgentGraph = new StateGraph(MessagesZodState)
.addNode("flight_assistant", flightAssistant)
.addNode("hotel_assistant", hotelAssistant)
// ...
```
```typescript
import { StateGraph, MessagesZodState } from "@langchain/langgraph";
const multiAgentGraph = new StateGraph(MessagesZodState)
.addNode("flight_assistant", flightAssistant)
.addNode("hotel_assistant", hotelAssistant)
// ...
```
:::
@@ -619,8 +619,7 @@ for await (const chunk of multiAgentGraph.stream({
3. Name of the agent or node to hand off to.
4. Take the agent's messages and **add** them to the parent's **state** as part of the handoff. The next agent will see the parent state.
5. Indicate to LangGraph that we need to navigate to agent node in a **parent** multi-agent graph.
:::
:::
!!! Note
+2 -2
View File
@@ -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
+10 -644
View File
@@ -28,14 +28,6 @@
{
"name": "Store",
"description": "Store is an API for managing persistent key-value store (long-term memory) that is available from any thread."
},
{
"name": "MCP",
"description": "Model Context Protocol related endpoints for exposing an agent as an MCP server."
},
{
"name": "System",
"description": "System endpoints for health checks, metrics, and server information."
}
],
"paths": {
@@ -157,59 +149,6 @@
}
}
},
"/assistants/count": {
"post": {
"tags": [
"Assistants"
],
"summary": "Count Assistants",
"description": "Get the count of assistants matching the specified criteria.",
"operationId": "count_assistants_assistants_count_post",
"requestBody": {
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/AssistantCountRequest"
}
}
},
"required": true
},
"responses": {
"200": {
"description": "Success",
"content": {
"application/json": {
"schema": {
"type": "integer",
"title": "Count"
}
}
}
},
"404": {
"description": "Not Found",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/ErrorResponse"
}
}
}
},
"422": {
"description": "Validation Error",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/ErrorResponse"
}
}
}
}
}
}
},
"/assistants/{assistant_id}": {
"get": {
"tags": [
@@ -866,59 +805,6 @@
}
}
},
"/threads/count": {
"post": {
"tags": [
"Threads"
],
"summary": "Count Threads",
"description": "Get the count of threads matching the specified criteria.",
"operationId": "count_threads_threads_count_post",
"requestBody": {
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/ThreadCountRequest"
}
}
},
"required": true
},
"responses": {
"200": {
"description": "Success",
"content": {
"application/json": {
"schema": {
"type": "integer",
"title": "Count"
}
}
}
},
"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}/state": {
"get": {
"tags": [
@@ -1520,73 +1406,6 @@
}
}
},
"/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": [
@@ -1642,30 +1461,6 @@
},
"name": "status",
"in": "query"
},
{
"required": false,
"schema": {
"type": "array",
"items": {
"type": "string",
"enum": [
"run_id",
"thread_id",
"assistant_id",
"created_at",
"updated_at",
"status",
"metadata",
"kwargs",
"multitask_strategy"
]
},
"title": "Select",
"description": "Specify which fields to return. If not provided, all fields are returned."
},
"name": "select",
"in": "query"
}
],
"responses": {
@@ -2517,59 +2312,6 @@
}
}
},
"/runs/crons/count": {
"post": {
"tags": [
"Crons (Plus tier)"
],
"summary": "Count Crons",
"description": "Get the count of crons matching the specified criteria.",
"operationId": "count_crons_runs_crons_count_post",
"requestBody": {
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/CronCountRequest"
}
}
},
"required": true
},
"responses": {
"200": {
"description": "Success",
"content": {
"application/json": {
"schema": {
"type": "integer",
"title": "Count"
}
}
}
},
"404": {
"description": "Not Found",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/ErrorResponse"
}
}
}
},
"422": {
"description": "Validation Error",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/ErrorResponse"
}
}
}
}
}
}
},
"/runs/stream": {
"post": {
"tags": [
@@ -3254,153 +2996,6 @@
"MCP"
]
}
},
"/info": {
"get": {
"tags": [
"System"
],
"summary": "Server Information",
"description": "Get server version information, feature flags, and metadata.",
"operationId": "server_info_info_get",
"responses": {
"200": {
"description": "Success",
"content": {
"application/json": {
"schema": {
"type": "object",
"properties": {
"version": {
"type": "string",
"title": "Version",
"description": "LangGraph API version"
},
"langgraph_py_version": {
"type": "string",
"title": "LangGraph Python Version",
"description": "LangGraph Python library version"
},
"flags": {
"type": "object",
"title": "Feature Flags",
"description": "Enabled features and capabilities"
},
"metadata": {
"type": "object",
"title": "Metadata",
"description": "Server deployment metadata"
}
},
"required": ["version", "langgraph_py_version", "flags", "metadata"],
"title": "ServerInfo"
}
}
}
}
}
}
},
"/metrics": {
"get": {
"tags": [
"System"
],
"summary": "System Metrics",
"description": "Get system metrics in Prometheus or JSON format for monitoring and observability.",
"operationId": "system_metrics_metrics_get",
"parameters": [
{
"name": "format",
"in": "query",
"required": false,
"schema": {
"type": "string",
"enum": ["prometheus", "json"],
"default": "prometheus",
"title": "Output Format",
"description": "Response format: prometheus (default) or json"
}
}
],
"responses": {
"200": {
"description": "Success",
"content": {
"text/plain": {
"schema": {
"type": "string",
"title": "Prometheus Metrics",
"description": "Metrics in Prometheus exposition format"
}
},
"application/json": {
"schema": {
"type": "object",
"title": "JSON Metrics",
"description": "Metrics in JSON format including queue stats, worker stats, and HTTP metrics"
}
}
}
}
}
}
},
"/ok": {
"get": {
"tags": [
"System"
],
"summary": "Health Check",
"description": "Check the health status of the server. Optionally check database connectivity.",
"operationId": "health_check_ok_get",
"parameters": [
{
"name": "check_db",
"in": "query",
"required": false,
"schema": {
"type": "integer",
"enum": [0, 1],
"default": 0,
"title": "Check Database",
"description": "Whether to check database connectivity (0=false, 1=true)"
}
}
],
"responses": {
"200": {
"description": "Success",
"content": {
"application/json": {
"schema": {
"type": "object",
"properties": {
"ok": {
"type": "boolean",
"const": true,
"title": "OK",
"description": "Indicates the server is healthy"
}
},
"required": ["ok"],
"title": "HealthResponse"
}
}
}
},
"500": {
"description": "Internal Server Error",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/ErrorResponse"
}
}
}
}
}
}
}
},
"components": {
@@ -3440,11 +3035,6 @@
"title": "Config",
"description": "The assistant config."
},
"context": {
"type": "object",
"title": "Context",
"description": "Static context added to the assistant."
},
"created_at": {
"type": "string",
"format": "date-time",
@@ -3510,11 +3100,6 @@
"title": "Config",
"description": "Configuration to use for the graph. Useful when graph is configurable and you want to create different assistants based on different configurations."
},
"context": {
"type": "object",
"title": "Context",
"description": "Static context added to the assistant."
},
"metadata": {
"type": "object",
"title": "Metadata",
@@ -3563,11 +3148,6 @@
"title": "Config",
"description": "Configuration to use for the graph. Useful when graph is configurable and you want to update the assistant's configuration."
},
"context": {
"type": "object",
"title": "Context",
"description": "Static context added to the assistant."
},
"metadata": {
"type": "object",
"title": "Metadata",
@@ -3629,12 +3209,6 @@
"title": "Cron Id",
"description": "The ID of the cron."
},
"assistant_id": {
"type": ["string", "null"],
"format": "uuid",
"title": "Assistant Id",
"description": "The ID of the assistant."
},
"thread_id": {
"type": "string",
"format": "uuid",
@@ -3664,26 +3238,10 @@
"title": "Updated At",
"description": "The last time the cron was updated."
},
"user_id": {
"type": ["string", "null"],
"title": "User Id",
"description": "The ID of the user."
},
"payload": {
"type": "object",
"title": "Payload",
"description": "The run payload to use for creating new run."
},
"next_run_date": {
"type": ["string", "null"],
"format": "date-time",
"title": "Next Run Date",
"description": "The next run date of the cron."
},
"metadata": {
"type": "object",
"title": "Metadata",
"description": "The cron metadata."
}
},
"type": "object",
@@ -3768,11 +3326,6 @@
"title": "Config",
"description": "The configuration for the assistant."
},
"context": {
"type": "object",
"title": "Context",
"description": "Static context added to the assistant."
},
"webhook": {
"type": "string",
"maxLength": 65536,
@@ -3827,7 +3380,7 @@
],
"title": "Multitask Strategy",
"description": "Multitask strategy to use. Must be one of 'reject', 'interrupt', 'rollback', or 'enqueue'.",
"default": "enqueue"
"default": "reject"
}
},
"type": "object",
@@ -3844,7 +3397,7 @@
"type": "string",
"format": "uuid",
"title": "Assistant Id",
"description": "The assistant ID or graph name to filter by using exact match."
"description": "The assistant ID or graph name to search for."
},
"thread_id": {
"type": "string",
@@ -3880,28 +3433,6 @@
"description": "The order to sort by.",
"default": "desc",
"enum": ["asc", "desc"]
},
"select": {
"type": "array",
"items": {
"type": "string",
"enum": [
"cron_id",
"assistant_id",
"thread_id",
"end_time",
"schedule",
"created_at",
"updated_at",
"user_id",
"payload",
"next_run_date",
"metadata",
"now"
]
},
"title": "Select",
"description": "Specify which fields to return. If not provided, all fields are returned."
}
},
"type": "object",
@@ -3909,25 +3440,6 @@
"title": "CronSearch",
"description": "Payload for listing crons"
},
"CronCountRequest": {
"properties": {
"assistant_id": {
"type": "string",
"format": "uuid",
"title": "Assistant Id",
"description": "The assistant ID or graph name to search for."
},
"thread_id": {
"type": "string",
"format": "uuid",
"title": "Thread Id",
"description": "The thread ID to search for."
}
},
"type": "object",
"title": "CronCountRequest",
"description": "Payload for counting crons"
},
"GraphSchema": {
"properties": {
"graph_id": {
@@ -3954,17 +3466,13 @@
"type": "object",
"title": "Config Schema",
"description": "The schema for the graph config. Missing if unable to generate JSON schema from graph."
},
"context_schema": {
"type": "object",
"title": "Context Schema",
"description": "The schema for the graph context. Missing if unable to generate JSON schema from graph."
}
},
"type": "object",
"required": [
"graph_id",
"state_schema"
"state_schema",
"config_schema"
],
"title": "GraphSchema",
"description": "Defines the structure and properties of a graph."
@@ -3990,18 +3498,14 @@
"type": "object",
"title": "Config Schema",
"description": "The schema for the graph config. Missing if unable to generate JSON schema from graph."
},
"context_schema": {
"type": "object",
"title": "Context Schema",
"description": "The schema for the graph context. Missing if unable to generate JSON schema from graph."
}
},
"type": "object",
"required": [
"input_schema",
"output_schema",
"state_schema"
"state_schema",
"config_schema"
],
"title": "GraphSchemaNoId",
"description": "Defines the structure and properties of a graph without an ID."
@@ -4012,7 +3516,7 @@
"$ref": "#/components/schemas/GraphSchemaNoId"
},
"title": "Subgraphs",
"description": "Map of graph name to graph schema metadata (`input_schema`, `output_schema`, `state_schema`, `config_schema`, `context_schema`)."
"description": "Map of graph name to graph schema metadata (`input_schema`, `output_schema`, `state_schema`, `config_schema`)."
},
"Run": {
"properties": {
@@ -4262,11 +3766,6 @@
"title": "Config",
"description": "The configuration for the assistant."
},
"context": {
"type": "object",
"title": "Context",
"description": "Static context added to the assistant."
},
"webhook": {
"type": "string",
"maxLength": 65536,
@@ -4320,8 +3819,6 @@
"values",
"messages",
"messages-tuple",
"tasks",
"checkpoints",
"updates",
"events",
"debug",
@@ -4336,8 +3833,6 @@
"values",
"messages",
"messages-tuple",
"tasks",
"checkpoints",
"updates",
"events",
"debug",
@@ -4391,7 +3886,7 @@
],
"title": "Multitask Strategy",
"description": "Multitask strategy to use. Must be one of 'reject', 'interrupt', 'rollback', or 'enqueue'.",
"default": "enqueue"
"default": "reject"
},
"if_not_exists": {
"type": "string",
@@ -4510,11 +4005,6 @@
"title": "Config",
"description": "The configuration for the assistant."
},
"context": {
"type": "object",
"title": "Context",
"description": "Static context added to the assistant."
},
"webhook": {
"type": "string",
"maxLength": 65536,
@@ -4568,8 +4058,6 @@
"values",
"messages",
"messages-tuple",
"tasks",
"checkpoints",
"updates",
"events",
"debug",
@@ -4584,8 +4072,6 @@
"values",
"messages",
"messages-tuple",
"tasks",
"checkpoints",
"updates",
"events",
"debug",
@@ -4705,49 +4191,12 @@
],
"title": "Sort Order",
"description": "The order to sort by."
},
"select": {
"type": "array",
"items": {
"type": "string",
"enum": [
"assistant_id",
"graph_id",
"name",
"description",
"config",
"context",
"created_at",
"updated_at",
"metadata",
"version"
]
},
"title": "Select",
"description": "Specify which fields to return. If not provided, all fields are returned."
}
},
"type": "object",
"title": "AssistantSearchRequest",
"description": "Payload for listing assistants."
},
"AssistantCountRequest": {
"properties": {
"metadata": {
"type": "object",
"title": "Metadata",
"description": "Metadata to filter by. Exact match filter for each KV pair."
},
"graph_id": {
"type": "string",
"title": "Graph Id",
"description": "The ID of the graph to filter by. The graph ID is normally set in your langgraph.json configuration."
}
},
"type": "object",
"title": "AssistantCountRequest",
"description": "Payload for counting assistants."
},
"AssistantVersionsSearchRequest": {
"properties": {
"metadata": {
@@ -4832,59 +4281,12 @@
],
"title": "Sort Order",
"description": "Sort order."
},
"select": {
"type": "array",
"items": {
"type": "string",
"enum": [
"thread_id",
"created_at",
"updated_at",
"metadata",
"config",
"context",
"status",
"values",
"interrupts"
]
},
"title": "Select",
"description": "Specify which fields to return. If not provided, all fields are returned."
}
},
"type": "object",
"title": "ThreadSearchRequest",
"description": "Payload for listing threads."
},
"ThreadCountRequest": {
"properties": {
"metadata": {
"type": "object",
"title": "Metadata",
"description": "Thread metadata to filter on."
},
"values": {
"type": "object",
"title": "Values",
"description": "State values to filter on."
},
"status": {
"type": "string",
"enum": [
"idle",
"busy",
"interrupted",
"error"
],
"title": "Status",
"description": "Thread status to filter on."
}
},
"type": "object",
"title": "ThreadCountRequest",
"description": "Payload for counting threads."
},
"Thread": {
"properties": {
"thread_id": {
@@ -4910,11 +4312,6 @@
"title": "Metadata",
"description": "The thread metadata."
},
"config": {
"type": "object",
"title": "Config",
"description": "The thread config."
},
"status": {
"type": "string",
"enum": [
@@ -4930,11 +4327,6 @@
"type": "object",
"title": "Values",
"description": "The current state of the thread."
},
"interrupts": {
"type": "object",
"title": "Interrupts",
"description": "The current interrupts of the thread."
}
},
"type": "object",
@@ -5084,9 +4476,7 @@
},
"interrupts": {
"type": "array",
"items": {
"$ref": "#/components/schemas/Interrupt"
}
"items": {}
},
"checkpoint": {
"$ref": "#/components/schemas/CheckpointConfig",
@@ -5119,12 +4509,6 @@
"parent_checkpoint": {
"type": "object",
"title": "Parent Checkpoint"
},
"interrupts": {
"type": "array",
"items": {
"$ref": "#/components/schemas/Interrupt"
}
}
},
"type": "object",
@@ -5143,7 +4527,7 @@
"type": "integer",
"title": "Limit",
"description": "The maximum number of states to return.",
"default": 1,
"default": 10,
"maximum": 1000,
"minimum": 1
},
@@ -5570,24 +4954,6 @@
}
}
}
},
"Interrupt": {
"type": "object",
"properties": {
"id": {
"type": [
"string",
"null"
]
},
"value": {
"type": "object"
}
},
"title": "Interrupt",
"required": [
"value"
]
}
}
}
-7
View File
@@ -6,14 +6,7 @@
Install the `langchain-mcp-adapters` library to use MCP tools in LangGraph:
:::python
```bash
pip install langchain-mcp-adapters
```
:::
:::js
```bash
npm install @langchain/mcp-adapters
```
:::
+1 -2
View File
@@ -315,8 +315,7 @@ In our example, the output of `get_state_history` will look like this:
tasks=(),
),
StateSnapshot(
values={'foo': 'a', 'bar': ['a']},
next=('node_b',),
values={'foo': 'a', 'bar': ['a']}, next=('node_b',),
config={'configurable': {'thread_id': '1', 'checkpoint_ns': '', 'checkpoint_id': '1ef663ba-28f9-6ec4-8001-31981c2c39f8'}},
metadata={'source': 'loop', 'writes': {'node_a': {'foo': 'a', 'bar': ['a']}}, 'step': 1},
created_at='2024-08-29T19:19:38.819946+00:00',
+1 -1
View File
@@ -12,7 +12,7 @@ There are three different plans for using it.
- **Developer**: All [LangSmith](https://smith.langchain.com/) users have access to this plan. You can sign up for this plan simply by creating a LangSmith account. This gives you access to the [local deployment](./deployment_options.md#free-deployment) option.
- **Plus**: All [LangSmith](https://smith.langchain.com/) users with a [Plus account](https://docs.smith.langchain.com/administration/pricing) have access to this plan. You can sign up for this plan simply by upgrading your LangSmith account to the Plus plan type. This gives you access to the [Cloud](./deployment_options.md#cloud-saas) deployment option.
- **Enterprise**: This is separate from LangSmith plans. You can sign up for this plan by [contacting our sales team](https://www.langchain.com/contact-sales). This gives you access to all [deployment options](./deployment_options.md).
- **Enterprise**: This is separate from LangSmith plans. You can sign up for this plan by contacting sales@langchain.dev. This gives you access to all [deployment options](./deployment_options.md).
## Plan Details
File diff suppressed because it is too large Load Diff
+11 -684
View File
@@ -22,7 +22,6 @@ To set up communication between the agents in a multi-agent system you can use [
To implement handoffs, you can return `Command` objects from your agent nodes or tools:
:::python
```python
from typing import Annotated
from langchain_core.tools import tool, InjectedToolCallId
@@ -74,109 +73,25 @@ def create_handoff_tool(*, agent_name: str, description: str | None = None):
commands = [tools_by_name[tool_call["name"]].invoke(tool_call) for tool_call in tool_calls]
return commands
```
:::
:::js
```typescript
import { tool } from "@langchain/core/tools";
import { Command, MessagesZodState } from "@langchain/langgraph";
import { z } from "zod";
function createHandoffTool({
agentName,
description,
}: {
agentName: string;
description?: string;
}) {
const name = `transfer_to_${agentName}`;
const toolDescription = description || `Transfer to ${agentName}`;
return tool(
async (_, config) => {
// (1)!
const state = config.state;
const toolCallId = config.toolCall.id;
const toolMessage = {
role: "tool" as const,
content: `Successfully transferred to ${agentName}`,
name: name,
tool_call_id: toolCallId,
};
return new Command({
// (3)!
goto: agentName,
// (4)!
update: { messages: [...state.messages, toolMessage] },
// (5)!
graph: Command.PARENT,
});
},
{
name,
description: toolDescription,
schema: z.object({}),
}
);
}
```
1. Access the [state](../concepts/low_level.md#state) of the agent that is calling the handoff tool through the `config` parameter.
2. The `Command` primitive allows specifying a state update and a node transition as a single operation, making it useful for implementing handoffs.
3. Name of the agent or node to hand off to.
4. Take the agent's messages and **add** them to the parent's **state** as part of the handoff. The next agent will see the parent state.
5. Indicate to LangGraph that we need to navigate to agent node in a **parent** multi-agent graph.
!!! tip
If you want to use tools that return `Command`, you can either use prebuilt @[`create_react_agent`][create_react_agent] / @[`ToolNode`][ToolNode] components, or implement your own tool-executing node that collects `Command` objects returned by the tools and returns a list of them, e.g.:
```typescript
const callTools = async (state) => {
// ...
const commands = await Promise.all(
toolCalls.map(toolCall => toolsByName[toolCall.name].invoke(toolCall))
);
return commands;
};
```
:::
!!! Important
This handoff implementation assumes that:
- each agent receives overall message history (across all agents) in the multi-agent system as its input. If you want more control over agent inputs, see [this section](#control-agent-inputs)
- each agent outputs its internal messages history to the overall message history of the multi-agent system. If you want more control over **how agent outputs are added**, wrap the agent in a separate node function:
- each agent receives overall message history (across all agents) in the multi-agent system as its input. If you want more control over agent inputs, see [this section](#control-agent-inputs)
- each agent outputs its internal messages history to the overall message history of the multi-agent system. If you want more control over **how agent outputs are added**, wrap the agent in a separate node function:
:::python
```python
def call_hotel_assistant(state):
# return agent's final response,
# excluding inner monologue
response = hotel_assistant.invoke(state)
# highlight-next-line
return {"messages": response["messages"][-1]}
```
:::
:::js
```typescript
const callHotelAssistant = async (state) => {
// return agent's final response,
// excluding inner monologue
const response = await hotelAssistant.invoke(state);
// highlight-next-line
return { messages: [response.messages.at(-1)] };
};
```
:::
```python
def call_hotel_assistant(state):
# return agent's final response,
# excluding inner monologue
response = hotel_assistant.invoke(state)
# highlight-next-line
return {"messages": response["messages"][-1]}
```
### Control agent inputs
:::python
You can use the @[`Send()`][Send] primitive to directly send data to the worker agents during the handoff. For example, you can request that the calling agent populate a task description for the next agent:
```python
@@ -214,63 +129,6 @@ def create_task_description_handoff_tool(
return handoff_tool
```
:::
:::js
You can use the @[`Send()`][Send] primitive to directly send data to the worker agents during the handoff. For example, you can request that the calling agent populate a task description for the next agent:
```typescript
import { tool } from "@langchain/core/tools";
import { Command, Send, MessagesZodState } from "@langchain/langgraph";
import { z } from "zod";
function createTaskDescriptionHandoffTool({
agentName,
description,
}: {
agentName: string;
description?: string;
}) {
const name = `transfer_to_${agentName}`;
const toolDescription = description || `Ask ${agentName} for help.`;
return tool(
async (
{ taskDescription },
config
) => {
const state = config.state;
const taskDescriptionMessage = {
role: "user" as const,
content: taskDescription,
};
const agentInput = {
...state,
messages: [taskDescriptionMessage],
};
return new Command({
// highlight-next-line
goto: [new Send(agentName, agentInput)],
graph: Command.PARENT,
});
},
{
name,
description: toolDescription,
schema: z.object({
taskDescription: z
.string()
.describe(
"Description of what the next agent should do, including all of the relevant context."
),
}),
}
);
}
```
:::
See the multi-agent [supervisor](../tutorials/multi_agent/agent_supervisor.md#4-create-delegation-tasks) example for a full example of using @[`Send()`][Send] in handoffs.
@@ -278,7 +136,6 @@ See the multi-agent [supervisor](../tutorials/multi_agent/agent_supervisor.md#4-
You can use handoffs in any agents built with LangGraph. We recommend using the prebuilt [agent](../agents/overview.md) or [`ToolNode`](./tool-calling.md#toolnode), as they natively support handoffs tools returning `Command`. Below is an example of how you can implement a multi-agent system for booking travel using handoffs:
:::python
```python
from langgraph.prebuilt import create_react_agent
from langgraph.graph import StateGraph, START, MessagesState
@@ -319,65 +176,9 @@ multi_agent_graph = (
.compile()
)
```
:::
:::js
```typescript
import { createReactAgent } from "@langchain/langgraph/prebuilt";
import { StateGraph, START, MessagesZodState } from "@langchain/langgraph";
import { z } from "zod";
function createHandoffTool({
agentName,
description,
}: {
agentName: string;
description?: string;
}) {
// same implementation as above
// ...
return new Command(/* ... */);
}
// Handoffs
const transferToHotelAssistant = createHandoffTool({
agentName: "hotel_assistant",
});
const transferToFlightAssistant = createHandoffTool({
agentName: "flight_assistant",
});
// Define agents
const flightAssistant = createReactAgent({
llm: model,
// highlight-next-line
tools: [/* ... */, transferToHotelAssistant],
// highlight-next-line
name: "flight_assistant",
});
const hotelAssistant = createReactAgent({
llm: model,
// highlight-next-line
tools: [/* ... */, transferToFlightAssistant],
// highlight-next-line
name: "hotel_assistant",
});
// Define multi-agent graph
const multiAgentGraph = new StateGraph(MessagesZodState)
// highlight-next-line
.addNode("flight_assistant", flightAssistant)
// highlight-next-line
.addNode("hotel_assistant", hotelAssistant)
.addEdge(START, "flight_assistant")
.compile();
```
:::
??? example "Full example: Multi-agent system for booking travel"
:::python
```python
from typing import Annotated
from langchain_core.messages import convert_to_messages
@@ -522,183 +323,6 @@ const multiAgentGraph = new StateGraph(MessagesZodState)
3. Name of the agent or node to hand off to.
4. Take the agent's messages and **add** them to the parent's **state** as part of the handoff. The next agent will see the parent state.
5. Indicate to LangGraph that we need to navigate to agent node in a **parent** multi-agent graph.
:::
:::js
```typescript
import { tool } from "@langchain/core/tools";
import { createReactAgent } from "@langchain/langgraph/prebuilt";
import { StateGraph, START, MessagesZodState, Command } from "@langchain/langgraph";
import { ChatAnthropic } from "@langchain/anthropic";
import { isBaseMessage } from "@langchain/core/messages";
import { z } from "zod";
// We'll use a helper to render the streamed agent outputs nicely
const prettyPrintMessages = (update: Record<string, any>) => {
// Handle tuple case with namespace
if (Array.isArray(update)) {
const [ns, updateData] = update;
// Skip parent graph updates in the printouts
if (ns.length === 0) {
return;
}
const graphId = ns[ns.length - 1].split(":")[0];
console.log(`Update from subgraph ${graphId}:\n`);
update = updateData;
}
for (const [nodeName, updateValue] of Object.entries(update)) {
console.log(`Update from node ${nodeName}:\n`);
const messages = updateValue.messages || [];
for (const message of messages) {
if (isBaseMessage(message)) {
const textContent =
typeof message.content === "string"
? message.content
: JSON.stringify(message.content);
console.log(`${message.getType()}: ${textContent}`);
}
}
console.log("\n");
}
};
function createHandoffTool({
agentName,
description,
}: {
agentName: string;
description?: string;
}) {
const name = `transfer_to_${agentName}`;
const toolDescription = description || `Transfer to ${agentName}`;
return tool(
async (_, config) => {
// highlight-next-line
const state = config.state; // (1)!
const toolCallId = config.toolCall.id;
const toolMessage = {
role: "tool" as const,
content: `Successfully transferred to ${agentName}`,
name: name,
tool_call_id: toolCallId,
};
return new Command({
// highlight-next-line
goto: agentName, // (3)!
// highlight-next-line
update: { messages: [...state.messages, toolMessage] }, // (4)!
// highlight-next-line
graph: Command.PARENT, // (5)!
});
},
{
name,
description: toolDescription,
schema: z.object({}),
}
);
}
// Handoffs
const transferToHotelAssistant = createHandoffTool({
agentName: "hotel_assistant",
description: "Transfer user to the hotel-booking assistant.",
});
const transferToFlightAssistant = createHandoffTool({
agentName: "flight_assistant",
description: "Transfer user to the flight-booking assistant.",
});
// Simple agent tools
const bookHotel = tool(
async ({ hotelName }) => {
return `Successfully booked a stay at ${hotelName}.`;
},
{
name: "book_hotel",
description: "Book a hotel",
schema: z.object({
hotelName: z.string(),
}),
}
);
const bookFlight = tool(
async ({ fromAirport, toAirport }) => {
return `Successfully booked a flight from ${fromAirport} to ${toAirport}.`;
},
{
name: "book_flight",
description: "Book a flight",
schema: z.object({
fromAirport: z.string(),
toAirport: z.string(),
}),
}
);
const model = new ChatAnthropic({
model: "claude-3-5-sonnet-latest",
});
// Define agents
const flightAssistant = createReactAgent({
llm: model,
// highlight-next-line
tools: [bookFlight, transferToHotelAssistant],
prompt: "You are a flight booking assistant",
// highlight-next-line
name: "flight_assistant",
});
const hotelAssistant = createReactAgent({
llm: model,
// highlight-next-line
tools: [bookHotel, transferToFlightAssistant],
prompt: "You are a hotel booking assistant",
// highlight-next-line
name: "hotel_assistant",
});
// Define multi-agent graph
const multiAgentGraph = new StateGraph(MessagesZodState)
.addNode("flight_assistant", flightAssistant)
.addNode("hotel_assistant", hotelAssistant)
.addEdge(START, "flight_assistant")
.compile();
// Run the multi-agent graph
const stream = await multiAgentGraph.stream(
{
messages: [
{
role: "user",
content: "book a flight from BOS to JFK and a stay at McKittrick Hotel",
},
],
},
// highlight-next-line
{ subgraphs: true }
);
for await (const chunk of stream) {
prettyPrintMessages(chunk);
}
```
1. Access agent's state
2. The `Command` primitive allows specifying a state update and a node transition as a single operation, making it useful for implementing handoffs.
3. Name of the agent or node to hand off to.
4. Take the agent's messages and **add** them to the parent's **state** as part of the handoff. The next agent will see the parent state.
5. Indicate to LangGraph that we need to navigate to agent node in a **parent** multi-agent graph.
:::
## Multi-turn conversation
@@ -709,7 +333,6 @@ The agents can then be implemented as nodes in a graph that executes agent steps
1. **Wait for user input** to continue the conversation, or
2. **Route to another agent** (or back to itself, such as in a loop) via a [handoff](#handoffs)
:::python
```python
def human(state) -> Command[Literal["agent", "another_agent"]]:
"""A node for collecting user input."""
@@ -737,44 +360,6 @@ def agent(state) -> Command[Literal["agent", "another_agent", "human"]]:
else:
return Command(goto="human") # Go to human node
```
:::
:::js
```typescript
import { interrupt, Command } from "@langchain/langgraph";
function human(state: MessagesState): Command {
const userInput: string = interrupt("Ready for user input.");
// Determine the active agent
const activeAgent = /* ... */;
return new Command({
update: {
messages: [{
role: "human",
content: userInput,
}]
},
goto: activeAgent,
});
}
function agent(state: MessagesState): Command {
// The condition for routing/halting can be anything, e.g. LLM tool call / structured output, etc.
const goto = getNextAgent(/* ... */); // 'agent' / 'anotherAgent'
if (goto) {
return new Command({
goto,
update: { myStateKey: "myStateValue" }
});
}
return new Command({ goto: "human" });
}
```
:::
??? example "Full example: multi-agent system for travel recommendations"
@@ -785,7 +370,6 @@ function agent(state: MessagesState): Command {
* travel_advisor: can help with travel destination recommendations. Can ask hotel_advisor for help.
* hotel_advisor: can help with hotel recommendations. Can ask travel_advisor for help.
:::python
```python
from langchain_anthropic import ChatAnthropic
from langgraph.graph import MessagesState, StateGraph, START
@@ -987,267 +571,10 @@ function agent(state: MessagesState): Command {
Would you like more specific information about any of these activities or would you like to know about other options in the area?
```
:::
:::js
```typescript
import { ChatAnthropic } from "@langchain/anthropic";
import { StateGraph, START, MessagesZodState, Command, interrupt, MemorySaver } from "@langchain/langgraph";
import { createReactAgent } from "@langchain/langgraph/prebuilt";
import { tool } from "@langchain/core/tools";
import { z } from "zod";
const model = new ChatAnthropic({ model: "claude-3-5-sonnet-latest" });
const MultiAgentState = MessagesZodState.extend({
lastActiveAgent: z.string().optional(),
});
// Define travel advisor tools
const getTravelRecommendations = tool(
async () => {
// Placeholder implementation
return "Based on current trends, I recommend visiting Japan, Portugal, or New Zealand.";
},
{
name: "get_travel_recommendations",
description: "Get current travel destination recommendations",
schema: z.object({}),
}
);
const makeHandoffTool = (agentName: string) => {
return tool(
async (_, config) => {
const state = config.state;
const toolCallId = config.toolCall.id;
const toolMessage = {
role: "tool" as const,
content: `Successfully transferred to ${agentName}`,
name: `transfer_to_${agentName}`,
tool_call_id: toolCallId,
};
return new Command({
goto: agentName,
update: { messages: [...state.messages, toolMessage] },
graph: Command.PARENT,
});
},
{
name: `transfer_to_${agentName}`,
description: `Transfer to ${agentName}`,
schema: z.object({}),
}
);
};
const travelAdvisorTools = [
getTravelRecommendations,
makeHandoffTool("hotel_advisor"),
];
const travelAdvisor = createReactAgent({
llm: model,
tools: travelAdvisorTools,
prompt: [
"You are a general travel expert that can recommend travel destinations (e.g. countries, cities, etc). ",
"If you need hotel recommendations, ask 'hotel_advisor' for help. ",
"You MUST include human-readable response before transferring to another agent."
].join("")
});
const callTravelAdvisor = async (
state: z.infer<typeof MultiAgentState>
): Promise<Command> => {
const response = await travelAdvisor.invoke(state);
const update = { ...response, lastActiveAgent: "travel_advisor" };
return new Command({ update, goto: "human" });
};
// Define hotel advisor tools
const getHotelRecommendations = tool(
async () => {
// Placeholder implementation
return "I recommend the Ritz-Carlton for luxury stays or boutique hotels for unique experiences.";
},
{
name: "get_hotel_recommendations",
description: "Get hotel recommendations for destinations",
schema: z.object({}),
}
);
const hotelAdvisorTools = [
getHotelRecommendations,
makeHandoffTool("travel_advisor"),
];
const hotelAdvisor = createReactAgent({
llm: model,
tools: hotelAdvisorTools,
prompt: [
"You are a hotel expert that can provide hotel recommendations for a given destination. ",
"If you need help picking travel destinations, ask 'travel_advisor' for help.",
"You MUST include human-readable response before transferring to another agent."
].join("")
});
const callHotelAdvisor = async (
state: z.infer<typeof MultiAgentState>
): Promise<Command> => {
const response = await hotelAdvisor.invoke(state);
const update = { ...response, lastActiveAgent: "hotel_advisor" };
return new Command({ update, goto: "human" });
};
const humanNode = async (
state: z.infer<typeof MultiAgentState>
): Promise<Command> => {
const userInput: string = interrupt("Ready for user input.");
const activeAgent = state.lastActiveAgent || "travel_advisor";
return new Command({
update: {
messages: [
{
role: "human",
content: userInput,
}
]
},
goto: activeAgent,
});
};
const builder = new StateGraph(MultiAgentState)
.addNode("travel_advisor", callTravelAdvisor)
.addNode("hotel_advisor", callHotelAdvisor)
.addNode("human", humanNode)
.addEdge(START, "travel_advisor");
const checkpointer = new MemorySaver();
const graph = builder.compile({ checkpointer });
```
Let's test a multi turn conversation with this application.
```typescript
import { v4 as uuidv4 } from "uuid";
import { Command } from "@langchain/langgraph";
const threadConfig = { configurable: { thread_id: uuidv4() } };
const inputs = [
// 1st round of conversation
{
messages: [
{ role: "user", content: "i wanna go somewhere warm in the caribbean" }
]
},
// Since we're using `interrupt`, we'll need to resume using the Command primitive.
// 2nd round of conversation
new Command({
resume: "could you recommend a nice hotel in one of the areas and tell me which area it is."
}),
// 3rd round of conversation
new Command({
resume: "i like the first one. could you recommend something to do near the hotel?"
}),
];
for (const [idx, userInput] of inputs.entries()) {
console.log();
console.log(`--- Conversation Turn ${idx + 1} ---`);
console.log();
console.log(`User: ${JSON.stringify(userInput)}`);
console.log();
for await (const update of await graph.stream(
userInput,
{ ...threadConfig, streamMode: "updates" }
)) {
for (const [nodeId, value] of Object.entries(update)) {
if (value?.messages?.length) {
const lastMessage = value.messages.at(-1);
if (lastMessage?.getType?.() === "ai") {
console.log(`${nodeId}: ${lastMessage.content}`);
}
}
}
}
}
```
```
--- Conversation Turn 1 ---
User: {"messages":[{"role":"user","content":"i wanna go somewhere warm in the caribbean"}]}
travel_advisor: Based on the recommendations, Aruba would be an excellent choice for your Caribbean getaway! Aruba is known as "One Happy Island" and offers:
- Year-round warm weather with consistent temperatures around 82°F (28°C)
- Beautiful white sand beaches like Eagle Beach and Palm Beach
- Clear turquoise waters perfect for swimming and snorkeling
- Minimal rainfall and location outside the hurricane belt
- A blend of Caribbean and Dutch culture
- Great dining options and nightlife
- Various water sports and activities
Would you like me to get some specific hotel recommendations in Aruba for your stay? I can transfer you to our hotel advisor who can help with accommodations.
--- Conversation Turn 2 ---
User: Command { resume: 'could you recommend a nice hotel in one of the areas and tell me which area it is.' }
hotel_advisor: Based on the recommendations, I can suggest two excellent options:
1. The Ritz-Carlton, Aruba - Located in Palm Beach
- This luxury resort is situated in the vibrant Palm Beach area
- Known for its exceptional service and amenities
- Perfect if you want to be close to dining, shopping, and entertainment
- Features multiple restaurants, a casino, and a world-class spa
- Located on a pristine stretch of Palm Beach
2. Bucuti & Tara Beach Resort - Located in Eagle Beach
- An adults-only boutique resort on Eagle Beach
- Known for being more intimate and peaceful
- Award-winning for its sustainability practices
- Perfect for a romantic getaway or peaceful vacation
- Located on one of the most beautiful beaches in the Caribbean
Would you like more specific information about either of these properties or their locations?
--- Conversation Turn 3 ---
User: Command { resume: 'i like the first one. could you recommend something to do near the hotel?' }
travel_advisor: Near the Ritz-Carlton in Palm Beach, here are some highly recommended activities:
1. Visit the Palm Beach Plaza Mall - Just a short walk from the hotel, featuring shopping, dining, and entertainment
2. Try your luck at the Stellaris Casino - It's right in the Ritz-Carlton
3. Take a sunset sailing cruise - Many depart from the nearby pier
4. Visit the California Lighthouse - A scenic landmark just north of Palm Beach
5. Enjoy water sports at Palm Beach:
- Jet skiing
- Parasailing
- Snorkeling
- Stand-up paddleboarding
Would you like more specific information about any of these activities or would you like to know about other options in the area?
```
:::
## Prebuilt implementations
LangGraph comes with prebuilt implementations of two of the most popular multi-agent architectures:
:::python
- [supervisor](../agents/multi-agent.md#supervisor) — individual agents are coordinated by a central supervisor agent. The supervisor controls all communication flow and task delegation, making decisions about which agent to invoke based on the current context and task requirements. You can use [`langgraph-supervisor`](https://github.com/langchain-ai/langgraph-supervisor-py) library to create a supervisor multi-agent systems.
- [swarm](../agents/multi-agent.md#supervisor) — agents dynamically hand off control to one another based on their specializations. The system remembers which agent was last active, ensuring that on subsequent interactions, the conversation resumes with that agent. You can use [`langgraph-swarm`](https://github.com/langchain-ai/langgraph-swarm-py) library to create a swarm multi-agent systems.
:::
:::js
- [supervisor](../agents/multi-agent.md#supervisor) — individual agents are coordinated by a central supervisor agent. The supervisor controls all communication flow and task delegation, making decisions about which agent to invoke based on the current context and task requirements. You can use [`langgraph-supervisor`](https://github.com/langchain-ai/langgraph-supervisor-js) library to create a supervisor multi-agent systems.
- [swarm](../agents/multi-agent.md#supervisor) — agents dynamically hand off control to one another based on their specializations. The system remembers which agent was last active, ensuring that on subsequent interactions, the conversation resumes with that agent. You can use [`langgraph-swarm`](https://github.com/langchain-ai/langgraph-swarm-js) library to create a swarm multi-agent systems.
:::
- [swarm](../agents/multi-agent.md#supervisor) — agents dynamically hand off control to one another based on their specializations. The system remembers which agent was last active, ensuring that on subsequent interactions, the conversation resumes with that agent. You can use [`langgraph-swarm`](https://github.com/langchain-ai/langgraph-swarm-py) library to create a swarm multi-agent systems.
+8 -465
View File
@@ -9,20 +9,11 @@ When adding subgraphs, you need to define how the parent graph and the subgraph
## Setup
:::python
```bash
pip install -U langgraph
```
:::
:::js
```bash
npm install @langchain/langgraph
```
:::
!!! tip "Set up LangSmith for LangGraph development"
Sign up for [LangSmith](https://smith.langchain.com) to quickly spot issues and improve the performance of your LangGraph projects. LangSmith lets you use trace data to debug, test, and monitor your LLM apps built with LangGraph — read more about how to get started [here](https://docs.smith.langchain.com).
## Shared state schemas
@@ -31,7 +22,6 @@ A common case is for the parent graph and subgraph to communicate over a shared
If your subgraph shares state keys with the parent graph, you can follow these steps to add it to your graph:
:::python
1. Define the subgraph workflow (`subgraph_builder` in the example below) and compile it
2. Pass compiled subgraph to the `.add_node` method when defining the parent graph workflow
@@ -59,41 +49,9 @@ builder.add_node("node_1", subgraph)
builder.add_edge(START, "node_1")
graph = builder.compile()
```
:::
:::js
1. Define the subgraph workflow (`subgraphBuilder` in the example below) and compile it
2. Pass compiled subgraph to the `.addNode` method when defining the parent graph workflow
```typescript
import { StateGraph, START } from "@langchain/langgraph";
import { z } from "zod";
const State = z.object({
foo: z.string(),
});
// Subgraph
const subgraphBuilder = new StateGraph(State)
.addNode("subgraphNode1", (state) => {
return { foo: "hi! " + state.foo };
})
.addEdge(START, "subgraphNode1");
const subgraph = subgraphBuilder.compile();
// Parent graph
const builder = new StateGraph(State)
.addNode("node1", subgraph)
.addEdge(START, "node1");
const graph = builder.compile();
```
:::
??? example "Full example: shared state schemas"
:::python
```python
from typing_extensions import TypedDict
from langgraph.graph.state import StateGraph, START
@@ -143,61 +101,6 @@ const graph = builder.compile();
{'node_1': {'foo': 'hi! foo'}}
{'node_2': {'foo': 'hi! foobar'}}
```
:::
:::js
```typescript
import { StateGraph, START } from "@langchain/langgraph";
import { z } from "zod";
// Define subgraph
const SubgraphState = z.object({
foo: z.string(), // (1)!
bar: z.string(), // (2)!
});
const subgraphBuilder = new StateGraph(SubgraphState)
.addNode("subgraphNode1", (state) => {
return { bar: "bar" };
})
.addNode("subgraphNode2", (state) => {
// note that this node is using a state key ('bar') that is only available in the subgraph
// and is sending update on the shared state key ('foo')
return { foo: state.foo + state.bar };
})
.addEdge(START, "subgraphNode1")
.addEdge("subgraphNode1", "subgraphNode2");
const subgraph = subgraphBuilder.compile();
// Define parent graph
const ParentState = z.object({
foo: z.string(),
});
const builder = new StateGraph(ParentState)
.addNode("node1", (state) => {
return { foo: "hi! " + state.foo };
})
.addNode("node2", subgraph)
.addEdge(START, "node1")
.addEdge("node1", "node2");
const graph = builder.compile();
for await (const chunk of await graph.stream({ foo: "foo" })) {
console.log(chunk);
}
```
3. This key is shared with the parent graph state
4. This key is private to the `SubgraphState` and is not visible to the parent graph
```
{ node1: { foo: 'hi! foo' } }
{ node2: { foo: 'hi! foobar' } }
```
:::
## Different state schemas
@@ -205,7 +108,6 @@ For more complex systems you might want to define subgraphs that have a **comple
If that's the case for your application, you need to define a node **function that invokes the subgraph**. This function needs to transform the input (parent) state to the subgraph state before invoking the subgraph, and transform the results back to the parent state before returning the state update from the node.
:::python
```python
from typing_extensions import TypedDict
from langgraph.graph.state import StateGraph, START
@@ -240,48 +142,9 @@ graph = builder.compile()
1. Transform the state to the subgraph state
2. Transform response back to the parent state
:::
:::js
```typescript
import { StateGraph, START } from "@langchain/langgraph";
import { z } from "zod";
const SubgraphState = z.object({
bar: z.string(),
});
// Subgraph
const subgraphBuilder = new StateGraph(SubgraphState)
.addNode("subgraphNode1", (state) => {
return { bar: "hi! " + state.bar };
})
.addEdge(START, "subgraphNode1");
const subgraph = subgraphBuilder.compile();
// Parent graph
const State = z.object({
foo: z.string(),
});
const builder = new StateGraph(State)
.addNode("node1", async (state) => {
const subgraphOutput = await subgraph.invoke({ bar: state.foo }); // (1)!
return { foo: subgraphOutput.bar }; // (2)!
})
.addEdge(START, "node1");
const graph = builder.compile();
```
1. Transform the state to the subgraph state
2. Transform response back to the parent state
:::
??? example "Full example: different state schemas"
:::python
```python
from typing_extensions import TypedDict
from langgraph.graph.state import StateGraph, START
@@ -337,74 +200,11 @@ const graph = builder.compile();
(('node_2:9c36dd0f-151a-cb42-cbad-fa2f851f9ab7',), {'grandchild_2': {'bar': 'hi! foobaz'}})
((), {'node_2': {'foo': 'hi! foobaz'}})
```
:::
:::js
```typescript
import { StateGraph, START } from "@langchain/langgraph";
import { z } from "zod";
// Define subgraph
const SubgraphState = z.object({
// note that none of these keys are shared with the parent graph state
bar: z.string(),
baz: z.string(),
});
const subgraphBuilder = new StateGraph(SubgraphState)
.addNode("subgraphNode1", (state) => {
return { baz: "baz" };
})
.addNode("subgraphNode2", (state) => {
return { bar: state.bar + state.baz };
})
.addEdge(START, "subgraphNode1")
.addEdge("subgraphNode1", "subgraphNode2");
const subgraph = subgraphBuilder.compile();
// Define parent graph
const ParentState = z.object({
foo: z.string(),
});
const builder = new StateGraph(ParentState)
.addNode("node1", (state) => {
return { foo: "hi! " + state.foo };
})
.addNode("node2", async (state) => {
const response = await subgraph.invoke({ bar: state.foo }); // (1)!
return { foo: response.bar }; // (2)!
})
.addEdge(START, "node1")
.addEdge("node1", "node2");
const graph = builder.compile();
for await (const chunk of await graph.stream(
{ foo: "foo" },
{ subgraphs: true }
)) {
console.log(chunk);
}
```
3. Transform the state to the subgraph state
4. Transform response back to the parent state
```
[[], { node1: { foo: 'hi! foo' } }]
[['node2:9c36dd0f-151a-cb42-cbad-fa2f851f9ab7'], { subgraphNode1: { baz: 'baz' } }]
[['node2:9c36dd0f-151a-cb42-cbad-fa2f851f9ab7'], { subgraphNode2: { bar: 'hi! foobaz' } }]
[[], { node2: { foo: 'hi! foobaz' } }]
```
:::
??? example "Full example: different state schemas (two levels of subgraphs)"
This is an example with two levels of subgraphs: parent -> child -> grandchild.
:::python
```python
# Grandchild graph
from typing_extensions import TypedDict
@@ -488,102 +288,14 @@ const graph = builder.compile();
((), {'child': {'my_key': 'hi Bob, how are you today?'}})
((), {'parent_2': {'my_key': 'hi Bob, how are you today? bye!'}})
```
:::
:::js
```typescript
import { StateGraph, START, END } from "@langchain/langgraph";
import { z } from "zod";
// Grandchild graph
const GrandChildState = z.object({
myGrandchildKey: z.string(),
});
const grandchild = new StateGraph(GrandChildState)
.addNode("grandchild1", (state) => {
// NOTE: child or parent keys will not be accessible here
return { myGrandchildKey: state.myGrandchildKey + ", how are you" };
})
.addEdge(START, "grandchild1")
.addEdge("grandchild1", END);
const grandchildGraph = grandchild.compile();
// Child graph
const ChildState = z.object({
myChildKey: z.string(),
});
const child = new StateGraph(ChildState)
.addNode("child1", async (state) => {
// NOTE: parent or grandchild keys won't be accessible here
const grandchildGraphInput = { myGrandchildKey: state.myChildKey }; // (1)!
const grandchildGraphOutput = await grandchildGraph.invoke(grandchildGraphInput);
return { myChildKey: grandchildGraphOutput.myGrandchildKey + " today?" }; // (2)!
}) // (3)!
.addEdge(START, "child1")
.addEdge("child1", END);
const childGraph = child.compile();
// Parent graph
const ParentState = z.object({
myKey: z.string(),
});
const parent = new StateGraph(ParentState)
.addNode("parent1", (state) => {
// NOTE: child or grandchild keys won't be accessible here
return { myKey: "hi " + state.myKey };
})
.addNode("child", async (state) => {
const childGraphInput = { myChildKey: state.myKey }; // (4)!
const childGraphOutput = await childGraph.invoke(childGraphInput);
return { myKey: childGraphOutput.myChildKey }; // (5)!
}) // (6)!
.addNode("parent2", (state) => {
return { myKey: state.myKey + " bye!" };
})
.addEdge(START, "parent1")
.addEdge("parent1", "child")
.addEdge("child", "parent2")
.addEdge("parent2", END);
const parentGraph = parent.compile();
for await (const chunk of await parentGraph.stream(
{ myKey: "Bob" },
{ subgraphs: true }
)) {
console.log(chunk);
}
```
7. We're transforming the state from the child state channels (`myChildKey`) to the grandchild state channels (`myGrandchildKey`)
8. We're transforming the state from the grandchild state channels (`myGrandchildKey`) back to the child state channels (`myChildKey`)
9. We're passing a function here instead of just compiled graph (`grandchildGraph`)
10. We're transforming the state from the parent state channels (`myKey`) to the child state channels (`myChildKey`)
11. We're transforming the state from the child state channels (`myChildKey`) back to the parent state channels (`myKey`)
12. We're passing a function here instead of just a compiled graph (`childGraph`)
```
[[], { parent1: { myKey: 'hi Bob' } }]
[['child:2e26e9ce-602f-862c-aa66-1ea5a4655e3b', 'child1:781bb3b1-3971-84ce-810b-acf819a03f9c'], { grandchild1: { myGrandchildKey: 'hi Bob, how are you' } }]
[['child:2e26e9ce-602f-862c-aa66-1ea5a4655e3b'], { child1: { myChildKey: 'hi Bob, how are you today?' } }]
[[], { child: { myKey: 'hi Bob, how are you today?' } }]
[[], { parent2: { myKey: 'hi Bob, how are you today? bye!' } }]
```
:::
## Add persistence
You only need to **provide the checkpointer when compiling the parent graph**. LangGraph will automatically propagate the checkpointer to the child subgraphs.
:::python
```python
from langgraph.graph import START, StateGraph
from langgraph.checkpoint.memory import MemorySaver
from langgraph.checkpoint.memory import InMemorySaver
from typing_extensions import TypedDict
class State(TypedDict):
@@ -605,66 +317,20 @@ builder = StateGraph(State)
builder.add_node("node_1", subgraph)
builder.add_edge(START, "node_1")
checkpointer = MemorySaver()
checkpointer = InMemorySaver()
graph = builder.compile(checkpointer=checkpointer)
```
:::
:::js
```typescript
import { StateGraph, START, MemorySaver } from "@langchain/langgraph";
import { z } from "zod";
If you want the subgraph to **have its own memory**, you can compile it `with checkpointer=True`. This is useful in [multi-agent](../concepts/multi_agent.md) systems, if you want agents to keep track of their internal message histories:
const State = z.object({
foo: z.string(),
});
// Subgraph
const subgraphBuilder = new StateGraph(State)
.addNode("subgraphNode1", (state) => {
return { foo: state.foo + "bar" };
})
.addEdge(START, "subgraphNode1");
const subgraph = subgraphBuilder.compile();
// Parent graph
const builder = new StateGraph(State)
.addNode("node1", subgraph)
.addEdge(START, "node1");
const checkpointer = new MemorySaver();
const graph = builder.compile({ checkpointer });
```
:::
If you want the subgraph to **have its own memory**, you can compile it with the appropriate checkpointer option. This is useful in [multi-agent](../concepts/multi_agent.md) systems, if you want agents to keep track of their internal message histories:
:::python
```python
subgraph_builder = StateGraph(...)
subgraph = subgraph_builder.compile(checkpointer=True)
```
:::
:::js
```typescript
const subgraphBuilder = new StateGraph(...)
const subgraph = subgraphBuilder.compile({ checkpointer: true });
```
:::
## View subgraph state
When you enable [persistence](../concepts/persistence.md), you can [inspect the graph state](../concepts/persistence.md#checkpoints) (checkpoint) via the appropriate method. To view the subgraph state, you can use the subgraphs option.
:::python
You can inspect the graph state via `graph.get_state(config)`. To view the subgraph state, you can use `graph.get_state(config, subgraphs=True)`.
:::
:::js
You can inspect the graph state via `graph.getState(config)`. To view the subgraph state, you can use `graph.getState(config, { subgraphs: true })`.
:::
When you enable [persistence](../concepts/persistence.md), you can [inspect the graph state](../concepts/persistence.md#checkpoints) (checkpoint) via `graph.get_state(config)`. To view the subgraph state, you can use `graph.get_state(config, subgraphs=True)`.
!!! important "Available **only** when interrupted"
@@ -672,10 +338,9 @@ You can inspect the graph state via `graph.getState(config)`. To view the subgra
??? example "View interrupted subgraph state"
:::python
```python
from langgraph.graph import START, StateGraph
from langgraph.checkpoint.memory import MemorySaver
from langgraph.checkpoint.memory import InMemorySaver
from langgraph.types import interrupt, Command
from typing_extensions import TypedDict
@@ -700,7 +365,7 @@ You can inspect the graph state via `graph.getState(config)`. To view the subgra
builder.add_node("node_1", subgraph)
builder.add_edge(START, "node_1")
checkpointer = MemorySaver()
checkpointer = InMemorySaver()
graph = builder.compile(checkpointer=checkpointer)
config = {"configurable": {"thread_id": "1"}}
@@ -714,53 +379,11 @@ You can inspect the graph state via `graph.getState(config)`. To view the subgra
```
1. This will be available only when the subgraph is interrupted. Once you resume the graph, you won't be able to access the subgraph state.
:::
:::js
```typescript
import { StateGraph, START, MemorySaver, interrupt, Command } from "@langchain/langgraph";
import { z } from "zod";
const State = z.object({
foo: z.string(),
});
// Subgraph
const subgraphBuilder = new StateGraph(State)
.addNode("subgraphNode1", (state) => {
const value = interrupt("Provide value:");
return { foo: state.foo + value };
})
.addEdge(START, "subgraphNode1");
const subgraph = subgraphBuilder.compile();
// Parent graph
const builder = new StateGraph(State)
.addNode("node1", subgraph)
.addEdge(START, "node1");
const checkpointer = new MemorySaver();
const graph = builder.compile({ checkpointer });
const config = { configurable: { thread_id: "1" } };
await graph.invoke({ foo: "" }, config);
const parentState = await graph.getState(config);
const subgraphState = (await graph.getState(config, { subgraphs: true })).tasks[0].state; // (1)!
// resume the subgraph
await graph.invoke(new Command({ resume: "bar" }), config);
```
2. This will be available only when the subgraph is interrupted. Once you resume the graph, you won't be able to access the subgraph state.
:::
## Stream subgraph outputs
To include outputs from subgraphs in the streamed outputs, you can set the subgraphs option in the stream method of the parent graph. This will stream outputs from both the parent graph and any subgraphs.
To include outputs from subgraphs in the streamed outputs, you can set `subgraphs=True` in the `.stream()` method of the parent graph. This will stream outputs from both the parent graph and any subgraphs.
:::python
```python
for chunk in graph.stream(
{"foo": "foo"},
@@ -771,27 +394,9 @@ for chunk in graph.stream(
```
1. Set `subgraphs=True` to stream outputs from subgraphs.
:::
:::js
```typescript
for await (const chunk of await graph.stream(
{ foo: "foo" },
{
subgraphs: true, // (1)!
streamMode: "updates",
}
)) {
console.log(chunk);
}
```
1. Set `subgraphs: true` to stream outputs from subgraphs.
:::
??? example "Stream from subgraphs"
:::python
```python
from typing_extensions import TypedDict
from langgraph.graph.state import StateGraph, START
@@ -845,66 +450,4 @@ for await (const chunk of await graph.stream(
(('node_2:e58e5673-a661-ebb0-70d4-e298a7fc28b7',), {'subgraph_node_1': {'bar': 'bar'}})
(('node_2:e58e5673-a661-ebb0-70d4-e298a7fc28b7',), {'subgraph_node_2': {'foo': 'hi! foobar'}})
((), {'node_2': {'foo': 'hi! foobar'}})
```
:::
:::js
```typescript
import { StateGraph, START } from "@langchain/langgraph";
import { z } from "zod";
// Define subgraph
const SubgraphState = z.object({
foo: z.string(),
bar: z.string(),
});
const subgraphBuilder = new StateGraph(SubgraphState)
.addNode("subgraphNode1", (state) => {
return { bar: "bar" };
})
.addNode("subgraphNode2", (state) => {
// note that this node is using a state key ('bar') that is only available in the subgraph
// and is sending update on the shared state key ('foo')
return { foo: state.foo + state.bar };
})
.addEdge(START, "subgraphNode1")
.addEdge("subgraphNode1", "subgraphNode2");
const subgraph = subgraphBuilder.compile();
// Define parent graph
const ParentState = z.object({
foo: z.string(),
});
const builder = new StateGraph(ParentState)
.addNode("node1", (state) => {
return { foo: "hi! " + state.foo };
})
.addNode("node2", subgraph)
.addEdge(START, "node1")
.addEdge("node1", "node2");
const graph = builder.compile();
for await (const chunk of await graph.stream(
{ foo: "foo" },
{
streamMode: "updates",
subgraphs: true, // (1)!
}
)) {
console.log(chunk);
}
```
2. Set `subgraphs: true` to stream outputs from subgraphs.
```
[[], { node1: { foo: 'hi! foo' } }]
[['node2:e58e5673-a661-ebb0-70d4-e298a7fc28b7'], { subgraphNode1: { bar: 'bar' } }]
[['node2:e58e5673-a661-ebb0-70d4-e298a7fc28b7'], { subgraphNode2: { foo: 'hi! foobar' } }]
[[], { node2: { foo: 'hi! foobar' } }]
```
:::
+1 -1
View File
@@ -360,5 +360,5 @@ j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src=
{% endblock %}
{% block announce %}
Our new LangChain Academy Course Deep Research with LangGraph is now live! <a href="https://academy.langchain.com/courses/deep-research-with-langgraph/?utm_medium=internal&utm_source=docs&utm_campaign=q3-2025_deep-research-course_co" target="_blank">Enroll for free</a>.
<strong>LangGraph Platform docs have moved!</strong> Find the LangGraph Platform docs at the new <a href="https://docs.langchain.com/langgraph-platform" target="_blank">LangChain Docs</a> site.
{% endblock %}
+6 -2
View File
@@ -161,7 +161,9 @@ class TestRedisCache:
async def test_async_operations(self):
"""Test async set and get operations with sync Redis client."""
# Create sync Redis client and cache (like main integration tests)
client = redis.Redis(host="localhost", port=6379, db=1, decode_responses=False)
client = redis.Redis(
host="localhost", port=6379, db=1, decode_responses=False
)
try:
client.ping()
except Exception:
@@ -187,7 +189,9 @@ class TestRedisCache:
async def test_async_clear(self):
"""Test async clear operations with sync Redis client."""
# Create sync Redis client and cache (like main integration tests)
client = redis.Redis(host="localhost", port=6379, db=1, decode_responses=False)
client = redis.Redis(
host="localhost", port=6379, db=1, decode_responses=False
)
try:
client.ping()
except Exception:
+1 -2
View File
@@ -4,9 +4,8 @@
# TESTING AND COVERAGE
######################
TEST?= "tests/unit_tests"
test:
uv run pytest $(TEST)
uv run pytest tests/unit_tests
test-integration:
uv run pytest tests/integration_tests
+7
View File
@@ -1,3 +1,10 @@
OPENAI_API_KEY=placeholder
ANTHROPIC_API_KEY=placeholder
TAVILY_API_KEY=placeholder
LANGCHAIN_TRACING_V2=false
LANGCHAIN_ENDPOINT=placeholder
LANGCHAIN_API_KEY=placeholder
LANGCHAIN_PROJECT=placeholder
LANGGRAPH_AUTH_TYPE=noop
LANGSMITH_AUTH_ENDPOINT=placeholder
LANGSMITH_TENANT_ID=placeholder
+8 -1
View File
@@ -163,7 +163,14 @@ def generate_schema():
# Add enum constraint for python_version
if "python_version" in python_schema["properties"]:
python_schema["properties"]["python_version"]["enum"] = ["3.11", "3.12", "3.13"]
python_schema["properties"]["python_version"]["enum"] = ["3.11", "3.12"]
# Add enum constraint for image_distro
if "image_distro" in python_schema["properties"]:
python_schema["properties"]["image_distro"]["anyOf"] = [
{"type": "string", "enum": ["debian", "wolfi"]},
{"type": "null"},
]
# Create Node.js schema with node_version
node_schema = {
-1
View File
@@ -1 +0,0 @@
__version__ = "0.4.0"
+9 -39
View File
@@ -17,9 +17,6 @@ DEFAULT_PYTHON_VERSION = "3.11"
DEFAULT_IMAGE_DISTRO = "debian"
Distros = Literal["debian", "wolfi", "bullseye", "bookworm"]
class TTLConfig(TypedDict, total=False):
"""Configuration for TTL (time-to-live) behavior in the store."""
@@ -372,13 +369,6 @@ class Config(TypedDict, total=False):
Must be >= 20 if provided.
"""
api_version: Optional[str]
"""Optional. Which semantic version of the LangGraph API server to use.
Defaults to latest. Check the
[changelog](https://docs.langchain.com/langgraph-platform/langgraph-server-changelog)
for more information."""
_INTERNAL_docker_tag: Optional[str]
"""Optional. Internal use only.
"""
@@ -388,11 +378,10 @@ class Config(TypedDict, total=False):
Defaults to langchain/langgraph-api or langchain/langgraphjs-api."""
image_distro: Optional[Distros]
image_distro: Optional[str]
"""Optional. Linux distribution for the base image.
Must be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.
If omitted, defaults to 'debian' ('latest').
Must be either 'debian' or 'wolfi'. If omitted, defaults to 'debian'.
"""
pip_config_file: Optional[str]
@@ -598,28 +587,13 @@ def validate_config(config: Config) -> Config:
)
image_distro = config.get("image_distro", DEFAULT_IMAGE_DISTRO)
internal_docker_tag = config.get("_INTERNAL_docker_tag")
api_version = config.get("api_version")
if internal_docker_tag:
if api_version:
raise click.UsageError(
"Cannot specify both _INTERNAL_docker_tag and api_version."
)
if api_version:
try:
parts = tuple(map(int, api_version.split("-")[0].split(".")))
if len(parts) > 3:
raise ValueError(
"Version must be major or major.minor or major.minor.patch."
)
except TypeError:
raise click.UsageError(f"Invalid version format: {api_version}") from None
config = {
"node_version": node_version,
"python_version": python_version,
"pip_config_file": config.get("pip_config_file"),
"pip_installer": config.get("pip_installer", "auto"),
"_INTERNAL_docker_tag": config.get("_INTERNAL_docker_tag"),
"base_image": config.get("base_image"),
"image_distro": image_distro,
"dependencies": config.get("dependencies", []),
@@ -634,10 +608,6 @@ def validate_config(config: Config) -> Config:
"ui_config": config.get("ui_config"),
"keep_pkg_tools": config.get("keep_pkg_tools"),
}
if internal_docker_tag:
config["_INTERNAL_docker_tag"] = internal_docker_tag
if api_version:
config["api_version"] = api_version
if config.get("node_version"):
node_version = config["node_version"]
@@ -674,17 +644,17 @@ def validate_config(config: Config) -> Config:
"Add at least one dependency to 'dependencies' list."
)
if not config.get("graphs"):
if not config["graphs"]:
raise click.UsageError(
"No graphs found in config. Add at least one graph to 'graphs' dictionary."
)
# Validate image_distro config
if image_distro := config.get("image_distro"):
if image_distro not in Distros.__args__:
if image_distro not in ["debian", "wolfi"]:
raise click.UsageError(
f"Invalid image_distro: '{image_distro}'. "
"Must be one of 'debian', 'bullseye', or 'bookworm'."
"Must be either 'debian' or 'wolfi'."
)
if pip_installer := config.get("pip_installer"):
@@ -1495,7 +1465,6 @@ def docker_tag(
base_image: Optional[str] = None,
api_version: Optional[str] = None,
) -> str:
api_version = api_version or config.get("api_version")
base_image = base_image or default_base_image(config)
image_distro = config.get("image_distro")
@@ -1504,6 +1473,9 @@ def docker_tag(
if config.get("_INTERNAL_docker_tag"):
return f"{base_image}:{config['_INTERNAL_docker_tag']}"
if "/langgraph-server" in base_image:
return f"{base_image}-py{config['python_version']}"
# Build the standard tag format
language, version = None, None
if config.get("node_version") and not config.get("python_version"):
@@ -1516,8 +1488,6 @@ def docker_tag(
# Prepend API version if provided
if api_version:
full_tag = f"{api_version}-{language}{version_distro_tag}"
elif "/langgraph-server" in base_image and version_distro_tag not in base_image:
return f"{base_image}-{language}{version_distro_tag}"
else:
full_tag = version_distro_tag
+4 -5
View File
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
[project]
name = "langgraph-cli"
dynamic = ["version"]
version = "0.3.6"
description = "CLI for interacting with LangGraph API"
authors = []
requires-python = ">=3.9"
@@ -15,12 +15,11 @@ dependencies = [
"click>=8.1.7",
"langgraph-sdk>=0.1.0 ; python_version >= '3.11'",
]
[tool.hatch.version]
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>=0.2.67,<0.3.0 ; python_version >= '3.11'",
"langgraph-runtime-inmem>=0.6.0 ; python_version >= '3.11'",
"python-dotenv>=0.8.0",
]
+4 -28
View File
@@ -15,8 +15,7 @@
"description": "Optional. Python version in 'major.minor' format (e.g. '3.11').\nMust be at least 3.11 or greater for this deployment to function properly.\n",
"enum": [
"3.11",
"3.12",
"3.13"
"3.12"
]
},
"pip_config_file": {
@@ -41,17 +40,6 @@
],
"description": "Optional. Internal use only.\n"
},
"api_version": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"description": "Optional. Which semantic version of the LangGraph API server to use.\n\nDefaults to latest. Check the\nfor more information.\n"
},
"auth": {
"anyOf": [
{
@@ -134,9 +122,8 @@
"image_distro": {
"anyOf": [
{
"type": "string",
"enum": [
"bookworm",
"bullseye",
"debian",
"wolfi"
]
@@ -145,7 +132,7 @@
"type": "null"
}
],
"description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
"description": "Optional. Linux distribution for the base image.\n\nMust be either 'debian' or 'wolfi'. If omitted, defaults to 'debian'.\n"
},
"keep_pkg_tools": {
"anyOf": [
@@ -234,17 +221,6 @@
],
"description": "Optional. Internal use only.\n"
},
"api_version": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"description": "Optional. Which semantic version of the LangGraph API server to use.\n\nDefaults to latest. Check the\nfor more information.\n"
},
"auth": {
"anyOf": [
{
@@ -337,7 +313,7 @@
"type": "null"
}
],
"description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
"description": "Optional. Linux distribution for the base image.\n\nMust be either 'debian' or 'wolfi'. If omitted, defaults to 'debian'.\n"
},
"keep_pkg_tools": {
"anyOf": [
+4 -28
View File
@@ -15,8 +15,7 @@
"description": "Optional. Python version in 'major.minor' format (e.g. '3.11').\nMust be at least 3.11 or greater for this deployment to function properly.\n",
"enum": [
"3.11",
"3.12",
"3.13"
"3.12"
]
},
"pip_config_file": {
@@ -41,17 +40,6 @@
],
"description": "Optional. Internal use only.\n"
},
"api_version": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"description": "Optional. Which semantic version of the LangGraph API server to use.\n\nDefaults to latest. Check the\nfor more information.\n"
},
"auth": {
"anyOf": [
{
@@ -134,9 +122,8 @@
"image_distro": {
"anyOf": [
{
"type": "string",
"enum": [
"bookworm",
"bullseye",
"debian",
"wolfi"
]
@@ -145,7 +132,7 @@
"type": "null"
}
],
"description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
"description": "Optional. Linux distribution for the base image.\n\nMust be either 'debian' or 'wolfi'. If omitted, defaults to 'debian'.\n"
},
"keep_pkg_tools": {
"anyOf": [
@@ -234,17 +221,6 @@
],
"description": "Optional. Internal use only.\n"
},
"api_version": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"description": "Optional. Which semantic version of the LangGraph API server to use.\n\nDefaults to latest. Check the\nfor more information.\n"
},
"auth": {
"anyOf": [
{
@@ -337,7 +313,7 @@
"type": "null"
}
],
"description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
"description": "Optional. Linux distribution for the base image.\n\nMust be either 'debian' or 'wolfi'. If omitted, defaults to 'debian'.\n"
},
"keep_pkg_tools": {
"anyOf": [
+1 -3
View File
@@ -381,9 +381,7 @@ def test_dockerfile_command_with_base_image() -> None:
assert save_path.exists()
with open(save_path) as f:
dockerfile = f.read()
assert re.match("FROM langchain/langgraph-server:0.2-py3.*", dockerfile), (
"\n".join(dockerfile.splitlines()[:3])
)
assert re.match("FROM langchain/langgraph-server:0.2-py3.*", dockerfile)
def test_dockerfile_command_with_docker_compose() -> None:
+20 -33
View File
@@ -38,6 +38,7 @@ def test_validate_config():
}
actual_config = validate_config(expected_config)
expected_config = {
"_INTERNAL_docker_tag": None,
"base_image": None,
"python_version": "3.11",
"node_version": None,
@@ -60,6 +61,7 @@ def test_validate_config():
# full config
env = ".env"
expected_config = {
"_INTERNAL_docker_tag": None,
"base_image": None,
"python_version": "3.12",
"node_version": None,
@@ -188,6 +190,7 @@ def test_validate_config_image_distro():
}
)
assert "Invalid image_distro: 'ubuntu'" in str(exc_info.value)
assert "Must be either 'debian' or 'wolfi'" in str(exc_info.value)
with pytest.raises(click.UsageError) as exc_info:
validate_config(
@@ -1336,22 +1339,19 @@ def test_docker_tag_different_node_versions_with_distro():
assert tag == expected_tag, f"Failed for Node.js {node_version}"
@pytest.mark.parametrize("in_config", [False, True])
def test_docker_tag_with_api_version(in_config: bool):
def test_docker_tag_with_api_version():
"""Test docker_tag function with api_version parameter."""
# Test 1: Python config with api_version and default distro
version = "0.2.74"
config = validate_config(
{
"python_version": "3.11",
"dependencies": ["."],
"graphs": {"agent": "./agent.py:graph"},
"api_version": version if in_config else None,
}
)
tag = docker_tag(config, api_version=version if not in_config else None)
assert tag == f"langchain/langgraph-api:{version}-py3.11"
tag = docker_tag(config, api_version="0.2.74")
assert tag == "langchain/langgraph-api:0.2.74-py3.11"
# Test 2: Python config with api_version and wolfi distro
config = validate_config(
@@ -1360,22 +1360,20 @@ def test_docker_tag_with_api_version(in_config: bool):
"dependencies": ["."],
"graphs": {"agent": "./agent.py:graph"},
"image_distro": "wolfi",
"api_version": version if in_config else None,
}
)
tag = docker_tag(config, api_version=version if not in_config else None)
assert tag == f"langchain/langgraph-api:{version}-py3.12-wolfi"
tag = docker_tag(config, api_version="0.2.74")
assert tag == "langchain/langgraph-api:0.2.74-py3.12-wolfi"
# Test 3: Node.js config with api_version and default distro
config = validate_config(
{
"node_version": "20",
"graphs": {"agent": "./agent.js:graph"},
"api_version": version if in_config else None,
}
)
tag = docker_tag(config, api_version=version if not in_config else None)
assert tag == f"langchain/langgraphjs-api:{version}-node20"
tag = docker_tag(config, api_version="0.2.74")
assert tag == "langchain/langgraphjs-api:0.2.74-node20"
# Test 4: Node.js config with api_version and wolfi distro
config = validate_config(
@@ -1383,11 +1381,10 @@ def test_docker_tag_with_api_version(in_config: bool):
"node_version": "20",
"graphs": {"agent": "./agent.js:graph"},
"image_distro": "wolfi",
"api_version": version if in_config else None,
}
)
tag = docker_tag(config, api_version=version if not in_config else None)
assert tag == f"langchain/langgraphjs-api:{version}-node20-wolfi"
tag = docker_tag(config, api_version="0.2.74")
assert tag == "langchain/langgraphjs-api:0.2.74-node20-wolfi"
# Test 5: Custom base image with api_version
config = validate_config(
@@ -1396,15 +1393,10 @@ def test_docker_tag_with_api_version(in_config: bool):
"dependencies": ["."],
"graphs": {"agent": "./agent.py:graph"},
"base_image": "my-registry/custom-image",
"api_version": version if in_config else None,
}
)
tag = docker_tag(
config,
base_image="my-registry/custom-image",
api_version=version if not in_config else None,
)
assert tag == f"my-registry/custom-image:{version}-py3.11"
tag = docker_tag(config, base_image="my-registry/custom-image", api_version="1.0.0")
assert tag == "my-registry/custom-image:1.0.0-py3.11"
# Test 6: api_version with different Python versions
for python_version in ["3.11", "3.12", "3.13"]:
@@ -1413,11 +1405,10 @@ def test_docker_tag_with_api_version(in_config: bool):
"python_version": python_version,
"dependencies": ["."],
"graphs": {"agent": "./agent.py:graph"},
"api_version": version if in_config else None,
}
)
tag = docker_tag(config, api_version=version if not in_config else None)
assert tag == f"langchain/langgraph-api:{version}-py{python_version}"
tag = docker_tag(config, api_version="0.2.74")
assert tag == f"langchain/langgraph-api:0.2.74-py{python_version}"
# Test 7: Without api_version should work as before
config = validate_config(
@@ -1437,11 +1428,10 @@ def test_docker_tag_with_api_version(in_config: bool):
"node_version": "20",
"dependencies": ["."],
"graphs": {"python": "./agent.py:graph", "js": "./agent.js:graph"},
"api_version": version if in_config else None,
}
)
tag = docker_tag(config, api_version=version if not in_config else None)
assert tag == f"langchain/langgraph-api:{version}-py3.11"
tag = docker_tag(config, api_version="0.2.74")
assert tag == "langchain/langgraph-api:0.2.74-py3.11"
# Test 9: api_version with _INTERNAL_docker_tag should ignore api_version
config = validate_config(
@@ -1461,15 +1451,12 @@ def test_docker_tag_with_api_version(in_config: bool):
"python_version": "3.11",
"dependencies": ["."],
"graphs": {"agent": "./agent.py:graph"},
"api_version": version if in_config else None,
}
)
tag = docker_tag(
config,
base_image="langchain/langgraph-server",
api_version=version if not in_config else None,
config, base_image="langchain/langgraph-server:0.2", api_version="0.2.74"
)
assert tag == f"langchain/langgraph-server:{version}-py3.11"
assert tag == "langchain/langgraph-server:0.2-py3.11"
def test_config_to_docker_with_api_version():
+321 -354
View File
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{ name = "sniffio", marker = "python_full_version >= '3.11'" },
{ name = "typing-extensions", marker = "python_full_version >= '3.11' and python_full_version < '3.13'" },
]
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+14 -76
View File
@@ -25,17 +25,9 @@ from langgraph_sdk.client import (
get_client,
get_sync_client,
)
from langgraph_sdk.schema import (
Checkpoint,
QueryParamTypes,
ThreadState,
)
from langgraph_sdk.schema import (
Command as CommandSDK,
)
from langgraph_sdk.schema import (
StreamMode as StreamModeSDK,
)
from langgraph_sdk.schema import Checkpoint, ThreadState
from langgraph_sdk.schema import Command as CommandSDK
from langgraph_sdk.schema import StreamMode as StreamModeSDK
from typing_extensions import Self
from langgraph._internal._config import merge_configs
@@ -216,8 +208,6 @@ class RemoteGraph(PregelProtocol):
config: RunnableConfig | None = None,
*,
xray: int | bool = False,
headers: dict[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> DrawableGraph:
"""Get graph by graph name.
@@ -236,8 +226,6 @@ class RemoteGraph(PregelProtocol):
graph = sync_client.assistants.get_graph(
assistant_id=self.assistant_id,
xray=xray,
headers=headers,
params=params,
)
return DrawableGraph(
nodes=self._get_drawable_nodes(graph),
@@ -249,8 +237,6 @@ class RemoteGraph(PregelProtocol):
config: RunnableConfig | None = None,
*,
xray: int | bool = False,
headers: dict[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> DrawableGraph:
"""Get graph by graph name.
@@ -269,8 +255,6 @@ class RemoteGraph(PregelProtocol):
graph = await client.assistants.get_graph(
assistant_id=self.assistant_id,
xray=xray,
headers=headers,
params=params,
)
return DrawableGraph(
nodes=self._get_drawable_nodes(graph),
@@ -392,12 +376,7 @@ class RemoteGraph(PregelProtocol):
return sanitized
def get_state(
self,
config: RunnableConfig,
*,
subgraphs: bool = False,
headers: dict[str, str] | None = None,
params: QueryParamTypes | None = None,
self, config: RunnableConfig, *, subgraphs: bool = False
) -> StateSnapshot:
"""Get the state of a thread.
@@ -409,8 +388,6 @@ class RemoteGraph(PregelProtocol):
config: A `RunnableConfig` that includes `thread_id` in the
`configurable` field.
subgraphs: Include subgraphs in the state.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
The latest state of the thread.
@@ -422,18 +399,11 @@ class RemoteGraph(PregelProtocol):
thread_id=merged_config["configurable"]["thread_id"],
checkpoint=self._get_checkpoint(merged_config),
subgraphs=subgraphs,
headers=headers,
params=params,
)
return self._create_state_snapshot(state)
async def aget_state(
self,
config: RunnableConfig,
*,
subgraphs: bool = False,
headers: dict[str, str] | None = None,
params: QueryParamTypes | None = None,
self, config: RunnableConfig, *, subgraphs: bool = False
) -> StateSnapshot:
"""Get the state of a thread.
@@ -445,8 +415,6 @@ class RemoteGraph(PregelProtocol):
config: A `RunnableConfig` that includes `thread_id` in the
`configurable` field.
subgraphs: Include subgraphs in the state.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
The latest state of the thread.
@@ -458,8 +426,6 @@ class RemoteGraph(PregelProtocol):
thread_id=merged_config["configurable"]["thread_id"],
checkpoint=self._get_checkpoint(merged_config),
subgraphs=subgraphs,
headers=headers,
params=params,
)
return self._create_state_snapshot(state)
@@ -470,8 +436,6 @@ class RemoteGraph(PregelProtocol):
filter: dict[str, Any] | None = None,
before: RunnableConfig | None = None,
limit: int | None = None,
headers: dict[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> Iterator[StateSnapshot]:
"""Get the state history of a thread.
@@ -496,8 +460,6 @@ class RemoteGraph(PregelProtocol):
before=self._get_checkpoint(before),
metadata=filter,
checkpoint=self._get_checkpoint(merged_config),
headers=headers,
params=params,
)
for state in states:
yield self._create_state_snapshot(state)
@@ -509,8 +471,6 @@ class RemoteGraph(PregelProtocol):
filter: dict[str, Any] | None = None,
before: RunnableConfig | None = None,
limit: int | None = None,
headers: dict[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> AsyncIterator[StateSnapshot]:
"""Get the state history of a thread.
@@ -522,8 +482,6 @@ class RemoteGraph(PregelProtocol):
filter: Metadata to filter on.
before: A `RunnableConfig` that includes checkpoint metadata.
limit: Max number of states to return.
headers: Optional custom headers to include with the request.
params: Optional query parameters to include with the request.
Returns:
States of the thread.
@@ -537,8 +495,6 @@ class RemoteGraph(PregelProtocol):
before=self._get_checkpoint(before),
metadata=filter,
checkpoint=self._get_checkpoint(merged_config),
headers=headers,
params=params,
)
for state in states:
yield self._create_state_snapshot(state)
@@ -562,9 +518,6 @@ class RemoteGraph(PregelProtocol):
config: RunnableConfig,
values: dict[str, Any] | Any | None,
as_node: str | None = None,
*,
headers: dict[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> RunnableConfig:
"""Update the state of a thread.
@@ -587,8 +540,6 @@ class RemoteGraph(PregelProtocol):
values=values,
as_node=as_node,
checkpoint=self._get_checkpoint(merged_config),
headers=headers,
params=params,
)
return self._get_config(response["checkpoint"])
@@ -597,9 +548,6 @@ class RemoteGraph(PregelProtocol):
config: RunnableConfig,
values: dict[str, Any] | Any | None,
as_node: str | None = None,
*,
headers: dict[str, str] | None = None,
params: QueryParamTypes | None = None,
) -> RunnableConfig:
"""Update the state of a thread.
@@ -622,8 +570,6 @@ class RemoteGraph(PregelProtocol):
values=values,
as_node=as_node,
checkpoint=self._get_checkpoint(merged_config),
headers=headers,
params=params,
)
return self._get_config(response["checkpoint"])
@@ -688,7 +634,6 @@ class RemoteGraph(PregelProtocol):
interrupt_after: All | Sequence[str] | None = None,
subgraphs: bool = False,
headers: dict[str, str] | None = None,
params: QueryParamTypes | None = None,
**kwargs: Any,
) -> Iterator[dict[str, Any] | Any]:
"""Create a run and stream the results.
@@ -733,10 +678,9 @@ class RemoteGraph(PregelProtocol):
interrupt_after=interrupt_after,
stream_subgraphs=subgraphs or stream is not None,
if_not_exists="create",
headers=(
_merge_tracing_headers(headers) if self.distributed_tracing else headers
),
params=params,
headers=_merge_tracing_headers(headers)
if self.distributed_tracing
else headers,
**kwargs,
):
# split mode and ns
@@ -797,7 +741,6 @@ class RemoteGraph(PregelProtocol):
interrupt_after: All | Sequence[str] | None = None,
subgraphs: bool = False,
headers: dict[str, str] | None = None,
params: QueryParamTypes | None = None,
**kwargs: Any,
) -> AsyncIterator[dict[str, Any] | Any]:
"""Create a run and stream the results.
@@ -842,10 +785,9 @@ class RemoteGraph(PregelProtocol):
interrupt_after=interrupt_after,
stream_subgraphs=subgraphs or stream is not None,
if_not_exists="create",
headers=(
_merge_tracing_headers(headers) if self.distributed_tracing else headers
),
params=params,
headers=_merge_tracing_headers(headers)
if self.distributed_tracing
else headers,
**kwargs,
):
# split mode and ns
@@ -920,7 +862,6 @@ class RemoteGraph(PregelProtocol):
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
headers: dict[str, str] | None = None,
params: QueryParamTypes | None = None,
**kwargs: Any,
) -> dict[str, Any] | Any:
"""Create a run, wait until it finishes and return the final state.
@@ -943,7 +884,6 @@ class RemoteGraph(PregelProtocol):
interrupt_after=interrupt_after,
headers=headers,
stream_mode="values",
params=params,
**kwargs,
):
pass
@@ -960,7 +900,6 @@ class RemoteGraph(PregelProtocol):
interrupt_before: All | Sequence[str] | None = None,
interrupt_after: All | Sequence[str] | None = None,
headers: dict[str, str] | None = None,
params: QueryParamTypes | None = None,
**kwargs: Any,
) -> dict[str, Any] | Any:
"""Create a run, wait until it finishes and return the final state.
@@ -983,7 +922,6 @@ class RemoteGraph(PregelProtocol):
interrupt_after=interrupt_after,
headers=headers,
stream_mode="values",
params=params,
**kwargs,
):
pass
@@ -996,11 +934,11 @@ class RemoteGraph(PregelProtocol):
def _merge_tracing_headers(headers: dict[str, str] | None) -> dict[str, str] | None:
if rt := ls.get_current_run_tree():
tracing_headers = rt.to_headers()
baggage = tracing_headers.pop("baggage")
if headers:
if "baggage" in headers:
tracing_headers["baggage"] = (
f"{headers['baggage']},{tracing_headers['baggage']}"
)
baggage = headers["baggage"] + "," + baggage
tracing_headers["baggage"] = baggage
headers.update(tracing_headers)
else:
headers = tracing_headers
-1
View File
@@ -507,7 +507,6 @@ def interrupt(value: Any) -> Any:
# find previous resume values
if scratchpad.resume:
if idx < len(scratchpad.resume):
conf[CONFIG_KEY_SEND]([(RESUME, scratchpad.resume)])
return scratchpad.resume[idx]
# find current resume value
v = scratchpad.get_null_resume(True)
+4 -5
View File
@@ -4,18 +4,18 @@ build-backend = "hatchling.build"
[project]
name = "langgraph"
version = "1.0.0a2"
version = "0.6.4"
description = "Building stateful, multi-actor applications with LLMs"
authors = []
requires-python = ">=3.10"
requires-python = ">=3.9"
readme = "README.md"
license = "MIT"
license-files = ['LICENSE']
dependencies = [
"langchain-core>=0.1",
"langgraph-checkpoint>=2.1.0,<3.0.0",
"langgraph-sdk>=0.2.2,<0.3.0",
"langgraph-prebuilt==0.7.0a2",
"langgraph-sdk>=0.2.0,<0.3.0",
"langgraph-prebuilt>=0.6.0,<0.7.0",
"xxhash>=3.5.0",
"pydantic>=2.7.4",
]
@@ -37,7 +37,6 @@ dev = [
"jupyter",
"pytest-xdist[psutil]",
"pytest-repeat",
"langchain-core==1.0.0a1",
"langgraph-prebuilt",
"langgraph-checkpoint",
"langgraph-checkpoint-sqlite",
File diff suppressed because one or more lines are too long
+1 -1
View File
@@ -69,7 +69,7 @@ def cache(request: pytest.FixtureRequest) -> Iterator[BaseCache]:
elif request.param == "redis":
# Get worker ID for parallel test isolation
worker_id = getattr(request.config, "workerinput", {}).get("workerid", "master")
redis_client = redis.Redis(
host="localhost", port=6379, db=0, decode_responses=False
)
+10 -29
View File
@@ -74,26 +74,17 @@ class FakeChatModel(GenericFakeChatModel):
assert isinstance(content, str)
content_chunks = cast(list[str], re.split(r"(\s)", content))
for i, token in enumerate(content_chunks):
if i == len(content_chunks) - 1:
chunk = ChatGenerationChunk(
message=AIMessageChunk(
content=token, id=message.id, chunk_position="last"
)
)
else:
chunk = ChatGenerationChunk(
message=AIMessageChunk(content=token, id=message.id)
)
for token in content_chunks:
chunk = ChatGenerationChunk(
message=AIMessageChunk(content=token, id=message.id)
)
if run_manager:
run_manager.on_llm_new_token(token, chunk=chunk)
yield chunk
else:
args = message.__dict__
args.pop("type")
chunk = ChatGenerationChunk(
message=AIMessageChunk(**args, chunk_position="last")
)
chunk = ChatGenerationChunk(message=AIMessageChunk(**args))
if run_manager:
run_manager.on_llm_new_token("", chunk=chunk)
yield chunk
@@ -131,27 +122,17 @@ class FakeChatModel(GenericFakeChatModel):
assert isinstance(content, str)
content_chunks = cast(list[str], re.split(r"(\s)", content))
for i, token in enumerate(content_chunks):
if i == len(content_chunks) - 1:
chunk = ChatGenerationChunk(
message=AIMessageChunk(
content=token, id=message.id, chunk_position="last"
)
)
else:
chunk = ChatGenerationChunk(
message=AIMessageChunk(content=token, id=message.id)
)
for token in content_chunks:
chunk = ChatGenerationChunk(
message=AIMessageChunk(content=token, id=message.id)
)
if run_manager:
run_manager.on_llm_new_token(token, chunk=chunk)
yield chunk
else:
args = message.__dict__
args.pop("type")
chunk = ChatGenerationChunk(
message=AIMessageChunk(**args, chunk_position="last")
)
chunk = ChatGenerationChunk(message=AIMessageChunk(**args))
if run_manager:
await run_manager.on_llm_new_token("", chunk=chunk)
yield chunk
-3
View File
@@ -1387,7 +1387,6 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
"type": "tool_call_chunk",
}
],
chunk_position="last",
),
{
"langgraph_step": 1,
@@ -1447,7 +1446,6 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
"type": "tool_call_chunk",
},
],
chunk_position="last",
),
{
"langgraph_step": 3,
@@ -1496,7 +1494,6 @@ def test_prebuilt_tool_chat(snapshot: SnapshotAssertion) -> None:
(
_AnyIdAIMessageChunk(
content="answer",
chunk_position="last",
),
{
"langgraph_step": 5,
@@ -1140,7 +1140,6 @@ async def test_prebuilt_tool_chat() -> None:
"type": "tool_call_chunk",
}
],
chunk_position="last",
),
{
"langgraph_step": 1,
@@ -1200,7 +1199,6 @@ async def test_prebuilt_tool_chat() -> None:
"type": "tool_call_chunk",
},
],
chunk_position="last",
),
{
"langgraph_step": 3,
@@ -1249,7 +1247,6 @@ async def test_prebuilt_tool_chat() -> None:
(
_AnyIdAIMessageChunk(
content="answer",
chunk_position="last",
),
{
"langgraph_step": 5,
+1 -4
View File
@@ -20,10 +20,7 @@ from langgraph.graph.message import REMOVE_ALL_MESSAGES, MessagesState, push_mes
from langgraph.graph.state import StateGraph
from tests.messages import _AnyIdHumanMessage
_, CORE_MINOR, CORE_PATCH = (
int("".join(c for c in v if c.isdigit()))
for v in langchain_core.__version__.split(".")
)
_, CORE_MINOR, CORE_PATCH = (int(v) for v in langchain_core.__version__.split("."))
def test_add_single_message():
+7 -24
View File
@@ -4805,10 +4805,7 @@ def test_interrupt_subgraph(sync_checkpointer: BaseCheckpointSaver):
assert graph.invoke(Command(resume="bar"), thread1)
@pytest.mark.parametrize("resume_style", ["null", "map"])
def test_interrupt_multiple(
sync_checkpointer: BaseCheckpointSaver, resume_style: Literal["null", "map"]
):
def test_interrupt_multiple(sync_checkpointer: BaseCheckpointSaver):
class State(TypedDict):
my_key: Annotated[str, operator.add]
@@ -4824,8 +4821,7 @@ def test_interrupt_multiple(
graph = builder.compile(checkpointer=sync_checkpointer)
thread1 = {"configurable": {"thread_id": "1"}}
result = [e for e in graph.stream({"my_key": "DE", "market": "DE"}, thread1)]
assert result == [
assert [e for e in graph.stream({"my_key": "DE", "market": "DE"}, thread1)] == [
{
"__interrupt__": (
Interrupt(
@@ -4836,19 +4832,12 @@ def test_interrupt_multiple(
}
]
result = [
assert [
event
for event in graph.stream(
Command(
resume="answer 1"
if resume_style == "null"
else {result[0]["__interrupt__"][0].id: "answer 1"},
update={"my_key": " foofoo "},
),
thread1,
Command(resume="answer 1", update={"my_key": " foofoo "}), thread1
)
]
assert result == [
] == [
{
"__interrupt__": (
Interrupt(
@@ -4862,13 +4851,7 @@ def test_interrupt_multiple(
assert [
event
for event in graph.stream(
Command(
resume="answer 2"
if resume_style == "null"
else {result[0]["__interrupt__"][0].id: "answer 2"}
),
thread1,
stream_mode="values",
Command(resume="answer 2"), thread1, stream_mode="values"
)
] == [
{"my_key": "DE foofoo "},
@@ -6597,7 +6580,7 @@ def test_tags_stream_mode_messages() -> None:
)
) == [
(
_AnyIdAIMessageChunk(content="foo", chunk_position="last"),
_AnyIdAIMessageChunk(content="foo"),
{
"langgraph_step": 1,
"langgraph_node": "call_model",
+1 -1
View File
@@ -7547,7 +7547,7 @@ async def test_tags_stream_mode_messages() -> None:
)
] == [
(
_AnyIdAIMessageChunk(content="foo", chunk_position="last"),
_AnyIdAIMessageChunk(content="foo"),
{
"langgraph_step": 1,
"langgraph_node": "call_model",
+8 -13
View File
@@ -1,6 +1,6 @@
import re
import sys
from typing import Annotated, Optional, Union
from typing import Annotated, Union
from unittest.mock import AsyncMock, MagicMock
import langsmith as ls
@@ -1183,10 +1183,7 @@ async def test_remote_graph_stream_messages_tuple(
@pytest.mark.anyio
@pytest.mark.parametrize("distributed_tracing", [False, True])
@pytest.mark.parametrize("stream", [False, True])
@pytest.mark.parametrize("headers", [None, {"foo": "bar"}])
async def test_include_headers(
distributed_tracing: bool, stream: bool, headers: Optional[dict[str, str]]
):
async def test_include_headers(distributed_tracing: bool, stream: bool):
mock_async_client = MagicMock()
async_iter = MagicMock()
return_value = [
@@ -1216,7 +1213,7 @@ async def test_include_headers(
async for _ in remote_pregel.astream(
{"input": {"messages": [{"type": "human", "content": "hello"}]}},
config,
headers=headers,
headers={"foo": "bar"},
):
pass
@@ -1224,14 +1221,12 @@ async def test_include_headers(
await remote_pregel.ainvoke(
{"input": {"messages": [{"type": "human", "content": "hello"}]}},
config,
headers=headers,
headers={"foo": "bar"},
)
expected = headers.copy() if headers else None
expected = {"foo": "bar"}
if distributed_tracing:
if expected is None:
expected = {}
expected["langsmith-trace"] = AnyStr()
expected["baggage"] = AnyStr("langsmith-metadata=")
expected["baggage"] = AnyStr()
assert astream_mock.call_args.kwargs["headers"] == expected
stream_mock.assert_not_called()
@@ -1242,7 +1237,7 @@ async def test_include_headers(
for _ in remote_pregel.stream(
{"input": {"messages": [{"type": "human", "content": "hello"}]}},
config,
headers=headers,
headers={"foo": "bar"},
):
pass
@@ -1250,6 +1245,6 @@ async def test_include_headers(
remote_pregel.invoke(
{"input": {"messages": [{"type": "human", "content": "hello"}]}},
config,
headers=headers,
headers={"foo": "bar"},
)
assert stream_mock.call_args.kwargs["headers"] == expected
+929 -759
View File
File diff suppressed because it is too large Load Diff
@@ -12,6 +12,7 @@ from typing import (
cast,
get_type_hints,
)
from operator import add
from warnings import warn
from langchain_core.language_models import (
@@ -34,7 +35,7 @@ from langchain_core.runnables import (
)
from langchain_core.tools import BaseTool
from pydantic import BaseModel
from typing_extensions import Annotated, NotRequired, TypedDict, deprecated
from typing_extensions import Annotated, NotRequired, TypedDict
from langgraph._internal._runnable import RunnableCallable, RunnableLike
from langgraph._internal._typing import MISSING
@@ -46,18 +47,19 @@ from langgraph.managed import RemainingSteps
from langgraph.prebuilt.tool_node import ToolNode
from langgraph.runtime import Runtime
from langgraph.store.base import BaseStore
from langgraph.types import Checkpointer, Send
from langgraph.types import Checkpointer, Command, Send
from langgraph.typing import ContextT
from langgraph.warnings import LangGraphDeprecatedSinceV10
StructuredResponse = Union[dict, BaseModel]
StructuredResponseSchema = Union[dict, type[BaseModel]]
F = TypeVar("F", bound=Callable[..., Any])
@deprecated(
"AgentState has been moved to langchain.agents. Please update your import to 'from langchain.agents import AgentState'.",
category=LangGraphDeprecatedSinceV10,
)
# We create the AgentState that we will pass around
# This simply involves a list of messages
# We want steps to return messages to append to the list
# So we annotate the messages attribute with `add_messages` reducer
class AgentState(TypedDict):
"""The state of the agent."""
@@ -65,11 +67,9 @@ class AgentState(TypedDict):
remaining_steps: NotRequired[RemainingSteps]
model_calls: Annotated[NotRequired[int], add]
@deprecated(
"AgentStatePydantic has been moved to langchain.agents. Please update your import to 'from langchain.agents import AgentStatePydantic'.",
category=LangGraphDeprecatedSinceV10,
)
class AgentStatePydantic(BaseModel):
"""The state of the agent."""
@@ -78,20 +78,12 @@ class AgentStatePydantic(BaseModel):
remaining_steps: RemainingSteps = 25
@deprecated(
"AgentStateWithStructuredResponse has been moved to langchain.agents. Please update your import to 'from langchain.agents import AgentStateWithStructuredResponse'.",
category=LangGraphDeprecatedSinceV10,
)
class AgentStateWithStructuredResponse(AgentState):
"""The state of the agent with a structured response."""
structured_response: StructuredResponse
@deprecated(
"AgentStateWithStructuredResponsePydantic has been moved to langchain.agents. Please update your import to 'from langchain.agents import AgentStateWithStructuredResponsePydantic'.",
category=LangGraphDeprecatedSinceV10,
)
class AgentStateWithStructuredResponsePydantic(AgentStatePydantic):
"""The state of the agent with a structured response."""
@@ -202,29 +194,6 @@ def _should_bind_tools(
return False
def _get_model(model: LanguageModelLike) -> BaseChatModel:
"""Get the underlying model from a RunnableBinding or return the model itself."""
if isinstance(model, RunnableSequence):
model = next(
(
step
for step in model.steps
if isinstance(step, (RunnableBinding, BaseChatModel))
),
model,
)
if isinstance(model, RunnableBinding):
model = model.bound
if not isinstance(model, BaseChatModel):
raise TypeError(
f"Expected `model` to be a ChatModel or RunnableBinding (e.g. model.bind_tools(...)), got {type(model)}"
)
return model
def _validate_chat_history(
messages: Sequence[BaseMessage],
) -> None:
@@ -256,10 +225,10 @@ def _validate_chat_history(
raise ValueError(error_message)
@deprecated(
"create_react_agent has been moved to langchain.agents. Please update your import to 'from langchain.agents import create_agent'.",
category=LangGraphDeprecatedSinceV10,
)
class StepCountIs(BaseModel):
count: int
def create_react_agent(
model: Union[
str,
@@ -291,6 +260,7 @@ def create_react_agent(
debug: bool = False,
version: Literal["v1", "v2"] = "v2",
name: Optional[str] = None,
stop_when: Optional[Callable[[StateSchema], bool]] | StepCountIs = None,
**deprecated_kwargs: Any,
) -> CompiledStateGraph:
"""Creates an agent graph that calls tools in a loop until a stopping condition is met.
@@ -514,13 +484,19 @@ def create_react_agent(
else AgentState
)
structured_output_tools: list[type] = []
llm_builtin_tools: list[dict] = []
if isinstance(tools, ToolNode):
tool_classes = list(tools.tools_by_name.values())
tool_node = tools
else:
llm_builtin_tools = [t for t in tools if isinstance(t, dict)]
tool_node = ToolNode([t for t in tools if not isinstance(t, dict)])
structured_output_tools = (
[response_format] if response_format is not None else []
)
tool_node = ToolNode(
[t for t in [*tools, *structured_output_tools] if not isinstance(t, dict)]
)
tool_classes = list(tool_node.tools_by_name.values())
is_dynamic_model = not isinstance(model, (str, Runnable)) and callable(model)
@@ -542,12 +518,19 @@ def create_react_agent(
model = cast(BaseChatModel, init_chat_model(model))
# Add structured output tool if response_format is provided
structured_output_tools = (
[response_format] if response_format is not None else []
)
if (
_should_bind_tools(model, tool_classes, num_builtin=len(llm_builtin_tools)) # type: ignore[arg-type]
and len(tool_classes + llm_builtin_tools) > 0
):
model = cast(BaseChatModel, model).bind_tools(
tool_classes + llm_builtin_tools # type: ignore[operator]
tool_classes + llm_builtin_tools + structured_output_tools, # type: ignore[operator],
tool_choice="any",
parallel_tool_calls=False,
)
static_model: Optional[Runnable] = _get_prompt_runnable(prompt) | model # type: ignore[operator]
@@ -557,7 +540,11 @@ def create_react_agent(
# If any of the tools are configured to return_directly after running,
# our graph needs to check if these were called
should_return_direct = {t.name for t in tool_classes if t.return_direct}
should_return_direct = {
t.name for t in tool_classes if getattr(t, "return_direct", False)
}
if response_format is not None:
should_return_direct.add(response_format.__name__)
def _resolve_model(
state: StateSchema, runtime: Runtime[ContextT]
@@ -623,7 +610,7 @@ def create_react_agent(
# Define the function that calls the model
def call_model(
state: StateSchema, runtime: Runtime[ContextT], config: RunnableConfig
) -> StateSchema:
) -> dict[str, list[AIMessage]] | Command:
if is_async_dynamic_model:
msg = (
"Async model callable provided but agent invoked synchronously. "
@@ -634,11 +621,25 @@ def create_react_agent(
model_input = _get_model_input_state(state)
if stop_when is not None:
post_model_node = "post_model_hook" if post_model_hook is not None else END
if isinstance(stop_when, StepCountIs):
if (model_calls := _get_state_value(state, "model_calls", 0)) == (stop_when.count - 1):
# set tool_choice to structured output tool if response_format is provided
# though we don't currently expose support for that binding here.
...
elif model_calls == stop_when.count:
return Command(goto=post_model_node)
else:
if stop_when(state):
return Command(goto=post_model_node)
if is_dynamic_model:
# Resolve dynamic model at runtime and apply prompt
dynamic_model = _resolve_model(state, runtime)
response = cast(AIMessage, dynamic_model.invoke(model_input, config)) # type: ignore[arg-type]
else:
else:
response = cast(AIMessage, static_model.invoke(model_input, config)) # type: ignore[union-attr]
# add agent name to the AIMessage
@@ -653,12 +654,12 @@ def create_react_agent(
)
]
}
# We return a list, because this will get added to the existing list
return {"messages": [response]}
return {"messages": [response], "model_calls": 1}
async def acall_model(
state: StateSchema, runtime: Runtime[ContextT], config: RunnableConfig
) -> StateSchema:
) -> dict[str, list[AIMessage]]:
model_input = _get_model_input_state(state)
if is_dynamic_model:
@@ -704,49 +705,6 @@ def create_react_agent(
else:
input_schema = state_schema
def generate_structured_response(
state: StateSchema, runtime: Runtime[ContextT], config: RunnableConfig
) -> StateSchema:
if is_async_dynamic_model:
msg = (
"Async model callable provided but agent invoked synchronously. "
"Use agent.ainvoke() or agent.astream(), or provide a sync model callable."
)
raise RuntimeError(msg)
messages = _get_state_value(state, "messages")
structured_response_schema = response_format
if isinstance(response_format, tuple):
system_prompt, structured_response_schema = response_format
messages = [SystemMessage(content=system_prompt)] + list(messages)
resolved_model = _resolve_model(state, runtime)
model_with_structured_output = _get_model(
resolved_model
).with_structured_output(
cast(StructuredResponseSchema, structured_response_schema)
)
response = model_with_structured_output.invoke(messages, config)
return {"structured_response": response}
async def agenerate_structured_response(
state: StateSchema, runtime: Runtime[ContextT], config: RunnableConfig
) -> StateSchema:
messages = _get_state_value(state, "messages")
structured_response_schema = response_format
if isinstance(response_format, tuple):
system_prompt, structured_response_schema = response_format
messages = [SystemMessage(content=system_prompt)] + list(messages)
resolved_model = await _aresolve_model(state, runtime)
model_with_structured_output = _get_model(
resolved_model
).with_structured_output(
cast(StructuredResponseSchema, structured_response_schema)
)
response = await model_with_structured_output.ainvoke(messages, config)
return {"structured_response": response}
if not tool_calling_enabled:
# Define a new graph
workflow = StateGraph(state_schema=state_schema, context_schema=context_schema)
@@ -768,19 +726,6 @@ def create_react_agent(
workflow.add_node("post_model_hook", post_model_hook) # type: ignore[arg-type]
workflow.add_edge("agent", "post_model_hook")
if response_format is not None:
workflow.add_node(
"generate_structured_response",
RunnableCallable(
generate_structured_response,
agenerate_structured_response,
),
)
if post_model_hook is not None:
workflow.add_edge("post_model_hook", "generate_structured_response")
else:
workflow.add_edge("agent", "generate_structured_response")
return workflow.compile(
checkpointer=checkpointer,
store=store,
@@ -792,16 +737,14 @@ def create_react_agent(
# Define the function that determines whether to continue or not
def should_continue(state: StateSchema) -> Union[str, list[Send]]:
post_model_node = "post_model_hook" if post_model_hook is not None else END
messages = _get_state_value(state, "messages")
last_message = messages[-1]
# If there is no function call, then we finish
if not isinstance(last_message, AIMessage) or not last_message.tool_calls:
if post_model_hook is not None:
return "post_model_hook"
elif response_format is not None:
return "generate_structured_response"
else:
return END
return post_model_node
# Otherwise if there is, we continue
else:
if version == "v1":
@@ -840,45 +783,19 @@ def create_react_agent(
# Set the entrypoint as `agent`
# This means that this node is the first one called
workflow.set_entry_point(entrypoint)
agent_paths = []
post_model_hook_paths = [entrypoint, "tools"]
# Add a post model hook node if post_model_hook is provided
if post_model_hook is not None:
workflow.add_node("post_model_hook", post_model_hook) # type: ignore[arg-type]
agent_paths.append("post_model_hook")
workflow.add_edge("agent", "post_model_hook")
else:
agent_paths.append("tools")
# Add a structured output node if response_format is provided
if response_format is not None:
workflow.add_node(
"generate_structured_response",
RunnableCallable(
generate_structured_response,
agenerate_structured_response,
),
)
if post_model_hook is not None:
post_model_hook_paths.append("generate_structured_response")
else:
agent_paths.append("generate_structured_response")
else:
if post_model_hook is not None:
post_model_hook_paths.append(END)
else:
agent_paths.append(END)
if post_model_hook is not None:
def post_model_hook_router(state: StateSchema) -> Union[str, list[Send]]:
"""Route to the next node after post_model_hook.
Routes to one of:
* "tools": if there are pending tool calls without a corresponding message.
* "generate_structured_response": if no pending tool calls exist and response_format is specified.
* END: if no pending tool calls exist and no response_format is specified.
"""
@@ -901,16 +818,17 @@ def create_react_agent(
return [Send("tools", [tool_call]) for tool_call in pending_tool_calls]
elif isinstance(messages[-1], ToolMessage):
return entrypoint
elif response_format is not None:
return "generate_structured_response"
else:
return END
workflow.add_conditional_edges(
"post_model_hook",
post_model_hook_router,
path_map=post_model_hook_paths,
path_map=[entrypoint, "tools", END],
)
else:
agent_paths.append("tools")
agent_paths.append(END)
workflow.add_conditional_edges(
"agent",
@@ -918,7 +836,7 @@ def create_react_agent(
path_map=agent_paths,
)
def route_tool_responses(state: StateSchema) -> str:
def route_tool_responses(state: StateSchema) -> str | Command:
for m in reversed(_get_state_value(state, "messages")):
if not isinstance(m, ToolMessage):
break
+1 -15
View File
@@ -1,14 +1,8 @@
from typing import Literal, Optional, Union
from typing_extensions import TypedDict, deprecated
from langgraph.warnings import LangGraphDeprecatedSinceV10
from typing_extensions import TypedDict
@deprecated(
"HumanInterruptConfig has been moved to langchain.agents.interrupt. Please update your import to 'from langchain.agents.interrupt import HumanInterruptConfig'.",
category=LangGraphDeprecatedSinceV10,
)
class HumanInterruptConfig(TypedDict):
"""Configuration that defines what actions are allowed for a human interrupt.
@@ -27,10 +21,6 @@ class HumanInterruptConfig(TypedDict):
allow_accept: bool
@deprecated(
"ActionRequest has been moved to langchain.agents.interrupt. Please update your import to 'from langchain.agents.interrupt import ActionRequest'.",
category=LangGraphDeprecatedSinceV10,
)
class ActionRequest(TypedDict):
"""Represents a request for human action within the graph execution.
@@ -45,10 +35,6 @@ class ActionRequest(TypedDict):
args: dict
@deprecated(
"HumanInterrupt has been moved to langchain.agents.interrupt. Please update your import to 'from langchain.agents.interrupt import HumanInterrupt'.",
category=LangGraphDeprecatedSinceV10,
)
class HumanInterrupt(TypedDict):
"""Represents an interrupt triggered by the graph that requires human intervention.
+26 -16
View File
@@ -69,14 +69,13 @@ from langchain_core.tools.base import (
get_all_basemodel_annotations,
)
from pydantic import BaseModel
from typing_extensions import Annotated, deprecated, get_args, get_origin
from typing_extensions import Annotated, get_args, get_origin
from langgraph._internal._runnable import RunnableCallable
from langgraph.errors import GraphBubbleUp
from langgraph.graph.message import REMOVE_ALL_MESSAGES
from langgraph.store.base import BaseStore
from langgraph.types import Command, Send
from langgraph.warnings import LangGraphDeprecatedSinceV10
INVALID_TOOL_NAME_ERROR_TEMPLATE = (
"Error: {requested_tool} is not a valid tool, try one of [{available_tools}]."
@@ -237,10 +236,6 @@ def _infer_handled_types(handler: Callable[..., str]) -> tuple[type[Exception],
return (Exception,)
@deprecated(
"ToolNode has been moved to langchain.agents.tool_node. Please update your import to 'from langchain.agents.tool_node import ToolNode'.",
category=LangGraphDeprecatedSinceV10,
)
class ToolNode(RunnableCallable):
"""A node that runs the tools called in the last AIMessage.
@@ -345,11 +340,19 @@ class ToolNode(RunnableCallable):
self.tools_by_name: dict[str, BaseTool] = {}
self.tool_to_state_args: dict[str, dict[str, Optional[str]]] = {}
self.tool_to_store_arg: dict[str, Optional[str]] = {}
self.structured_output_tools: list[str] = []
self.handle_tool_errors = handle_tool_errors
self.messages_key = messages_key
for tool_ in tools:
if not isinstance(tool_, BaseTool):
if issubclass(tool_, BaseModel):
self.tools_by_name[tool_.__name__] = tool_
self.tool_to_state_args[tool_.__name__] = {}
self.tool_to_store_arg[tool_.__name__] = None
self.structured_output_tools.append(tool_.__name__)
continue
elif not isinstance(tool_, BaseTool):
tool_ = create_tool(tool_)
self.tools_by_name[tool_.name] = tool_
self.tool_to_state_args[tool_.name] = _get_state_args(tool_)
self.tool_to_store_arg[tool_.name] = _get_store_arg(tool_)
@@ -442,11 +445,26 @@ class ToolNode(RunnableCallable):
call: ToolCall,
input_type: Literal["list", "dict", "tool_calls"],
config: RunnableConfig,
) -> ToolMessage:
) -> ToolMessage | Command:
"""Run a single tool call synchronously."""
if invalid_tool_message := self._validate_tool_call(call):
return invalid_tool_message
try:
if call["name"] in self.structured_output_tools:
response_schema = self.tools_by_name[call["name"]]
return Command(
update={
"messages": [
ToolMessage(
content="structured output generated",
name="structured_output",
tool_call_id=call["id"],
status="success",
),
],
"structured_response": response_schema(**call["args"]),
}
)
call_args = {**call, **{"type": "tool_call"}}
response = self.tools_by_name[call["name"]].invoke(call_args, config)
@@ -856,10 +874,6 @@ def tools_condition(
return "__end__"
@deprecated(
"InjectedState has been moved to langchain.agents.tool_node. Please update your import to 'from langchain.agents.tool_node import InjectedState'.",
category=LangGraphDeprecatedSinceV10,
)
class InjectedState(InjectedToolArg):
"""Annotation for injecting graph state into tool arguments.
@@ -934,10 +948,6 @@ class InjectedState(InjectedToolArg):
self.field = field
@deprecated(
"InjectedStore has been moved to langchain.agents.tool_node. Please update your import to 'from langchain.agents.tool_node import InjectedStore'.",
category=LangGraphDeprecatedSinceV10,
)
class InjectedStore(InjectedToolArg):
"""Annotation for injecting persistent store into tool arguments.
@@ -32,10 +32,8 @@ from langchain_core.utils.pydantic import is_basemodel_subclass
from pydantic import BaseModel, ValidationError
from pydantic.v1 import BaseModel as BaseModelV1
from pydantic.v1 import ValidationError as ValidationErrorV1
from typing_extensions import deprecated
from langgraph._internal._runnable import RunnableCallable
from langgraph.warnings import LangGraphDeprecatedSinceV10
def _default_format_error(
@@ -47,10 +45,6 @@ def _default_format_error(
return f"{repr(error)}\n\nRespond after fixing all validation errors."
@deprecated(
"ValidationNode is deprecated. Please use create_react_agent from langchain.agents with custom tool error handling.",
category=LangGraphDeprecatedSinceV10,
)
class ValidationNode(RunnableCallable):
"""A node that validates all tools requests from the last AIMessage.
+2 -3
View File
@@ -4,10 +4,10 @@ build-backend = "hatchling.build"
[project]
name = "langgraph-prebuilt"
version = "0.7.0a2"
version = "0.6.4"
description = "Library with high-level APIs for creating and executing LangGraph agents and tools."
authors = []
requires-python = ">=3.10"
requires-python = ">=3.9"
readme = "README.md"
license = "MIT"
license-files = ['LICENSE']
@@ -28,7 +28,6 @@ dev = [
"pytest-mock",
"pytest-watcher",
"mypy",
"langchain-core",
"langgraph",
"langgraph-checkpoint",
"langgraph-checkpoint-sqlite",
+132 -9
View File
@@ -1,6 +1,6 @@
version = 1
revision = 2
requires-python = ">=3.10"
requires-python = ">=3.9"
[[package]]
name = "aiosqlite"
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+3 -3
View File
@@ -1,7 +1,7 @@
.PHONY: lint format test
.PHONY: lint format
test:
uv run pytest tests
echo "No tests to run"
######################
# LINTING AND FORMATTING
@@ -17,7 +17,7 @@ lint lint_diff:
uv run ruff check .
[ "$(PYTHON_FILES)" = "" ] || uv run ruff format $(PYTHON_FILES) --diff
[ "$(PYTHON_FILES)" = "" ] || uv run ruff check --select I $(PYTHON_FILES)
uvx ty check .
[ "$(PYTHON_FILES)" = "" ] || mkdir -p $(MYPY_CACHE) || uv run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE)
format format_diff:
uv run ruff check --select I --fix $(PYTHON_FILES)
+6 -1
View File
@@ -1,6 +1,11 @@
from langgraph_sdk.auth import Auth
from langgraph_sdk.client import get_client, get_sync_client
__version__ = "0.2.3"
try:
from importlib import metadata
__version__ = metadata.version(__package__)
except metadata.PackageNotFoundError:
__version__ = "unknown"
__all__ = ["Auth", "get_client", "get_sync_client"]
+4 -8
View File
@@ -385,8 +385,6 @@ class _ResourceOn(typing.Generic[VCreate, VRead, VUpdate, VDelete, VSearch]):
_register_handler(self.auth, self.resource, "*", handler),
)
# Accept keyword-only parameters for future filtering behavior; referenced to satisfy linters.
_ = resources, actions
return decorator
@@ -703,7 +701,7 @@ def _validate_handler(fn: Callable[..., typing.Any]) -> None:
"""
if not inspect.iscoroutinefunction(fn):
raise ValueError(
f"Auth handler '{getattr(fn, '__name__', fn)}' must be an async function. "
f"Auth handler '{fn.__name__}' must be an async function. "
"Add 'async' before 'def' to make it asynchronous and ensure"
" any IO operations are non-blocking."
)
@@ -711,20 +709,18 @@ def _validate_handler(fn: Callable[..., typing.Any]) -> None:
sig = inspect.signature(fn)
if "ctx" not in sig.parameters:
raise ValueError(
f"Auth handler '{getattr(fn, '__name__', fn)}' must have a 'ctx: AuthContext' parameter. "
f"Auth handler '{fn.__name__}' must have a 'ctx: AuthContext' parameter. "
"Update the function signature to include this required parameter."
)
if "value" not in sig.parameters:
raise ValueError(
f"Auth handler '{getattr(fn, '__name__', fn)}' must have a 'value' parameter. "
f"Auth handler '{fn.__name__}' must have a 'value' parameter. "
" The value contains the mutable data being sent to the endpoint."
"Update the function signature to include this required parameter."
)
def is_studio_user(
user: types.MinimalUser | types.BaseUser | types.MinimalUserDict,
) -> bool:
def is_studio_user(user: types.MinimalUser | types.User | types.UserDict) -> bool:
return (
isinstance(user, types.StudioUser)
or isinstance(user, dict)
File diff suppressed because it is too large Load Diff
+1 -68
View File
@@ -2,7 +2,7 @@
from __future__ import annotations
from collections.abc import Mapping, Sequence
from collections.abc import Sequence
from datetime import datetime
from typing import (
Any,
@@ -10,7 +10,6 @@ from typing import (
NamedTuple,
Optional,
TypedDict,
Union,
)
from typing_extensions import TypeAlias
@@ -349,72 +348,6 @@ class Cron(TypedDict):
"""The metadata of the cron."""
# Select field aliases for client-side typing of `select` parameters.
# These mirror the server's allowed field sets.
AssistantSelectField = Literal[
"assistant_id",
"graph_id",
"name",
"description",
"config",
"context",
"created_at",
"updated_at",
"metadata",
"version",
]
ThreadSelectField = Literal[
"thread_id",
"created_at",
"updated_at",
"metadata",
"config",
"context",
"status",
"values",
"interrupts",
]
RunSelectField = Literal[
"run_id",
"thread_id",
"assistant_id",
"created_at",
"updated_at",
"status",
"metadata",
"kwargs",
"multitask_strategy",
]
CronSelectField = Literal[
"cron_id",
"assistant_id",
"thread_id",
"end_time",
"schedule",
"created_at",
"updated_at",
"user_id",
"payload",
"next_run_date",
"metadata",
"now",
]
PrimitiveData = Optional[Union[str, int, float, bool]]
QueryParamTypes = Union[
Mapping[str, Union[PrimitiveData, Sequence[PrimitiveData]]],
list[tuple[str, PrimitiveData]],
tuple[tuple[str, PrimitiveData], ...],
str,
bytes,
]
class RunCreate(TypedDict):
"""Defines the parameters for initiating a background run."""
+1 -1
View File
@@ -95,7 +95,7 @@ class SSEDecoder:
sse = StreamPart(
event=self._event,
data=orjson.loads(self._data) if self._data else None, # type: ignore[invalid-argument-type]
data=orjson.loads(self._data) if self._data else None,
)
# NOTE: as per the SSE spec, do not reset last_event_id.
+1 -5
View File
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
[project]
name = "langgraph-sdk"
dynamic = ["version"]
version = "0.2.0"
description = "SDK for interacting with LangGraph API"
authors = []
requires-python = ">=3.9"
@@ -16,9 +16,6 @@ dependencies = [
"orjson>=3.10.1",
]
[tool.hatch.version]
path = "langgraph_sdk/__init__.py"
[project.urls]
Repository = "https://www.github.com/langchain-ai/langgraph"
@@ -50,6 +47,5 @@ lint.select = [
"UP", # pyupgrade
"B", # flake8-bugbear
"I", # isort
"ARG", # flake8-unused-arguments
]
lint.ignore = ["E501", "B008"]
-120
View File
@@ -1,120 +0,0 @@
from __future__ import annotations
import inspect
import re
import pytest
from langgraph_sdk.client import (
AssistantsClient,
CronClient,
RunsClient,
StoreClient,
SyncAssistantsClient,
SyncCronClient,
SyncRunsClient,
SyncStoreClient,
SyncThreadsClient,
ThreadsClient,
)
def _public_methods(cls) -> dict[str, object]:
methods: dict[str, object] = {}
# Use the raw class dict to avoid runtime wrappers from plugins/decorators
for name, member in cls.__dict__.items():
if name.startswith("_"):
continue
if inspect.isfunction(member):
methods[name] = member
return methods
def _strip_self(sig: inspect.Signature) -> inspect.Signature:
params = list(sig.parameters.values())
if params and params[0].name == "self":
params = params[1:]
return sig.replace(parameters=params)
def _normalize_return_annotation(ann: object) -> str:
s = str(ann)
s = re.sub(r"\s+", "", s)
s = s.replace("typing.", "").replace("collections.abc.", "")
s = re.sub(r"AsyncGenerator\[([^,\]]+)(?:,[^\]]*)?\]", r"Iterator[\1]", s)
s = re.sub(r"Generator\[([^,\]]+)(?:,[^\]]*)?\]", r"Iterator[\1]", s)
s = re.sub(r"AsyncIterator\[(.+)\]", r"Iterator[\1]", s)
s = re.sub(r"AsyncIterable\[(.+)\]", r"Iterable[\1]", s)
return s
@pytest.mark.parametrize(
"async_cls,sync_cls",
[
(AssistantsClient, SyncAssistantsClient),
(ThreadsClient, SyncThreadsClient),
(RunsClient, SyncRunsClient),
(CronClient, SyncCronClient),
(StoreClient, SyncStoreClient),
],
)
def test_sync_api_matches_async(async_cls, sync_cls):
async_methods = _public_methods(async_cls)
sync_methods = _public_methods(sync_cls)
# Method name parity
assert set(sync_methods.keys()) == set(async_methods.keys()), (
f"Method sets differ: async-only={set(async_methods) - set(sync_methods)}, sync-only={set(sync_methods) - set(async_methods)}"
)
for name, async_fn in async_methods.items():
sync_fn = sync_methods[name]
# Use inspect.signature for parameter names (robust across versions)
async_sig = _strip_self(inspect.signature(async_fn))
sync_sig = _strip_self(inspect.signature(sync_fn))
a_names = list(async_sig.parameters.keys())
s_names = list(sync_sig.parameters.keys())
assert set(a_names) == set(s_names), (
f"Parameter names differ for {async_cls.__name__}.{name}: "
f"async={a_names}, sync={s_names}"
)
# Compare default presence and parameter kinds (with some tolerance)
a_params = async_sig.parameters
s_params = sync_sig.parameters
def kinds_compatible(
akind: inspect._ParameterKind, skind: inspect._ParameterKind
) -> bool:
if akind == skind:
return True
return {
inspect.Parameter.KEYWORD_ONLY,
inspect.Parameter.POSITIONAL_OR_KEYWORD,
} == {akind, skind}
for pname in set(a_names) & set(s_names):
apar = a_params[pname]
spar = s_params[pname]
assert kinds_compatible(apar.kind, spar.kind), (
f"Parameter kind mismatch for {async_cls.__name__}.{name}.{pname}: "
f"async={apar.kind}, sync={spar.kind}"
)
assert (apar.default is inspect._empty) == (
spar.default is inspect._empty
), (
f"Default presence mismatch for {async_cls.__name__}.{name}.{pname}: "
f"async_has_default={apar.default is not inspect._empty}, "
f"sync_has_default={spar.default is not inspect._empty}"
)
# Return annotations must match or be iterator-equivalent
a_ret = _normalize_return_annotation(async_sig.return_annotation)
s_ret = _normalize_return_annotation(sync_sig.return_annotation)
assert a_ret == s_ret, (
f"Return annotation mismatch for {async_cls.__name__}.{name}: "
f"async={a_ret}, sync={s_ret}"
)
@@ -1,76 +0,0 @@
import functools
import json
import os
from pathlib import Path
from typing import get_args
from langgraph_sdk.schema import (
AssistantSelectField,
CronSelectField,
RunSelectField,
ThreadSelectField,
)
current_dir = os.path.dirname(os.path.abspath(__file__))
@functools.cache
def _load_spec() -> dict:
with (
Path(current_dir).parents[2]
/ "docs"
/ "docs"
/ "cloud"
/ "reference"
/ "api"
/ "openapi.json"
).open() as f:
return json.load(f)
def _enum_from_request_select(spec: dict, path: str, method: str) -> set[str]:
schema = spec["paths"][path][method]["requestBody"]["content"]["application/json"][
"schema"
]
if "properties" in schema:
props = schema["properties"]
elif "$ref" in schema:
component = spec
index = schema["$ref"].split("/")[1:]
for part in index:
component = component[part]
props = component["properties"]
else:
raise ValueError(f"Unknown schema: {schema}")
sel = props["select"]
return set(sel["items"]["enum"])
def _enum_from_query_select(spec: dict, path: str, method: str) -> set[str]:
params = spec["paths"][path][method]["parameters"]
sel = next(p for p in params if p["name"] == "select")
return set(sel["schema"]["items"]["enum"])
def test_assistants_select_enum_matches_sdk():
spec = _load_spec()
expected = set(get_args(AssistantSelectField))
assert _enum_from_request_select(spec, "/assistants/search", "post") == expected
def test_threads_select_enum_matches_sdk():
spec = _load_spec()
expected = set(get_args(ThreadSelectField))
assert _enum_from_request_select(spec, "/threads/search", "post") == expected
def test_runs_select_enum_matches_sdk():
spec = _load_spec()
expected = set(get_args(RunSelectField))
assert _enum_from_query_select(spec, "/threads/{thread_id}/runs", "get") == expected
def test_crons_select_enum_matches_sdk():
spec = _load_spec()
expected = set(get_args(CronSelectField))
assert _enum_from_request_select(spec, "/runs/crons/search", "post") == expected
+135 -162
View File
@@ -4,7 +4,7 @@ requires-python = ">=3.9"
[[package]]
name = "anyio"
version = "4.10.0"
version = "4.9.0"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "exceptiongroup", marker = "python_full_version < '3.11'" },
@@ -12,27 +12,18 @@ dependencies = [
{ name = "sniffio" },
{ name = "typing-extensions", marker = "python_full_version < '3.13'" },
]
sdist = { url = "https://files.pythonhosted.org/packages/f1/b4/636b3b65173d3ce9a38ef5f0522789614e590dab6a8d505340a4efe4c567/anyio-4.10.0.tar.gz", hash = "sha256:3f3fae35c96039744587aa5b8371e7e8e603c0702999535961dd336026973ba6", size = 213252, upload-time = "2025-08-04T08:54:26.451Z" }
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[[package]]
@@ -128,6 +119,7 @@ wheels = [
[[package]]
name = "langgraph-sdk"
version = "0.2.0"
source = { editable = "." }
dependencies = [
{ name = "httpx" },
@@ -164,7 +156,7 @@ dev = [
[[package]]
name = "mypy"
version = "1.17.1"
version = "1.17.0"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "mypy-extensions" },
@@ -172,45 +164,39 @@ dependencies = [
{ name = "tomli", marker = "python_full_version < '3.11'" },
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