Compare commits

..
Author SHA1 Message Date
Sydney Runkle f26ca07716 minimalistic tool registration 2025-09-04 16:05:08 -04:00
Sydney Runkle b250823532 tool and model calls 2025-09-04 10:15:03 -04:00
Sydney Runkle 120d34303d adding model calls 2025-09-04 09:59:45 -04:00
Sydney Runkle 6ff9e4a764 limiting calls 2025-09-04 09:43:53 -04:00
Sydney Runkle 3c36d2e2c8 initial test for swarm 2025-09-03 15:27:13 -04:00
Sydney Runkle f6d0382d66 more swarm progress 2025-09-03 15:14:33 -04:00
Sydney Runkle 0386fe5f6a swarm 2025-09-03 13:43:47 -04:00
Sydney Runkle b11ece823b first pass at modify as new node 2025-09-03 13:06:26 -04:00
Nuno Campos 46ce6ad927 Add State property 2025-09-03 14:43:46 +01:00
Nuno Campos 0c929e62eb Rename to AgentJump 2025-09-01 09:57:52 +01:00
Nuno Campos 88c434048f Add middleware arg to create_react_agent 2025-08-29 17:07:50 +01:00
Nuno Campos f67a089a68 Rename goto to jump_to 2025-08-27 15:52:01 +01:00
Harrison Chase cc97fad7e5 cr 2025-08-26 20:26:34 -07:00
Nuno Campos 75c73369a3 Add structured response to agent output 2025-08-26 10:03:12 +01:00
Nuno Campos fdbcc07381 Adding ability to skip to model, tools or END 2025-08-26 09:57:32 +01:00
Harrison Chase 80e19ecf4d cr 2025-08-25 19:14:24 -07:00
Nuno Campos 54272afe01 Add response_format arg 2025-08-25 21:20:26 +01:00
Nuno Campos e1aeb24a4e Add state arg to modify hook 2025-08-25 21:08:38 +01:00
Nuno Campos a51c0bfa31 Boom 2025-08-25 17:36:16 +01:00
295 changed files with 12397 additions and 25916 deletions
+5 -5
View File
@@ -1,21 +1,21 @@
name: "\U0001F41B Bug Report"
description: Report a bug in LangGraph. To report a security issue, please instead use the security option below. For questions, please use the LangChain Forum at forum.langchain.com.
labels: [pending, bug]
labels: [pending,bug]
body:
- type: markdown
attributes:
value: |
Thank you for taking the time to file a bug report.
Use this to report BUGS in LangGraph. For usage questions, feature requests and general design questions, please use the [LangChain Forum](https://forum.langchain.com/).
Relevant links to check before filing a bug report to see if your issue has already been reported, fixed or
if there's another way to solve your problem:
* [LangChain Forum](https://forum.langchain.com/),
* [LangGraph Github Issues](https://github.com/langchain-ai/langgraph/issues),
* [LangGraph how-to guides](https://langchain-ai.github.io/langgraph/how-tos/).
* [LangChain documentation with the integrated search](https://docs.langchain.com/),
* [LangChain documentation with the integrated search](https://python.langchain.com/docs/get_started/introduction),
* [GitHub search](https://github.com/langchain-ai/langgraph),
- type: checkboxes
id: checks
+1 -4
View File
@@ -1,9 +1,6 @@
blank_issues_enabled: false
version: 2.1
contact_links:
- name: Documentation
url: https://github.com/langchain-ai/docs/issues/new?template=langgraph.yml
about: Report an issue related to the LangGraph documentation
- name: LangChain Forum
url: https://forum.langchain.com/
about: General community discussions and support
about: General community discussions, support, and feature requests
+19
View File
@@ -0,0 +1,19 @@
name: Documentation
description: Report an issue related to the LangGraph documentation.
title: "DOC: <Please write a comprehensive title after the 'DOC: ' prefix>"
labels: [documentation]
body:
- type: textarea
attributes:
label: "Issue with current documentation:"
description: >
Please make sure to leave a reference to the document/code you're
referring to.
- type: textarea
attributes:
label: "Idea or request for content:"
description: >
Please describe as clearly as possible what topics you think are missing
from the current documentation.
+1 -1
View File
@@ -38,7 +38,7 @@ def main():
tree = ast.parse(file.read())
classes = find_classes(tree)
def is_sync(class_spec: Tuple[str, List[str]]) -> bool:
return class_spec[0].startswith("Sync")
+13 -37
View File
@@ -1,8 +1,7 @@
import logging
import pathlib
import sys
import time
from urllib import error, request
from urllib import request, error
import langgraph_cli
import langgraph_cli.config
@@ -12,13 +11,9 @@ from langgraph_cli.constants import DEFAULT_PORT
from langgraph_cli.exec import Runner, subp_exec
from langgraph_cli.progress import Progress
logger = logging.getLogger(__name__)
logging.basicConfig(level=logging.INFO)
def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
"""Spin up API with Postgres/Redis via docker compose and wait until ready."""
logger.info("Starting test...")
with Runner() as runner, Progress(message="Pulling...") as set:
# Detect docker/compose capabilities
capabilities = langgraph_cli.docker.check_capabilities(runner)
@@ -62,9 +57,7 @@ def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
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)
)
runner.run(subp_exec(*compose_cmd, *args, "ps", input=stdin, verbose=False))
except Exception:
pass
try:
@@ -100,7 +93,7 @@ def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
set("")
base_url = f"http://localhost:{port}"
ok_url = f"{base_url}/ok"
logger.info(f"Waiting for {ok_url} to respond with 200...")
print(f"Waiting for {ok_url} to respond with 200...")
deadline = time.time() + 30
last_err: Exception | None = None
while time.time() < deadline:
@@ -114,16 +107,13 @@ def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
break
else:
last_err = RuntimeError(f"Unexpected status: {resp.status}")
logger.error(f"Unexpected status: {resp.status}")
print(f"Unexpected status: {resp.status}")
except error.URLError as e:
logger.error(f"URLError: {e}")
last_err = e
except Exception as e: # noqa: BLE001
logger.error(f"Exception: {e}")
last_err = e
time.sleep(0.5)
else:
logger.error("Timeout waiting for /ok to return 200")
# Bring stack down before raising
args_down = [*args, "down", "-v", "--remove-orphans"]
try:
@@ -141,23 +131,15 @@ def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
)
# Clean up: bring compose stack down to free ports for next test
logger.info("Test succeeded. Bringing down compose stack...")
try:
args_down = [*args, "down", "-v", "--remove-orphans"]
runner.run(
subp_exec(
*compose_cmd,
*args_down,
input=stdin,
verbose=verbose,
)
args_down = [*args, "down", "-v", "--remove-orphans"]
runner.run(
subp_exec(
*compose_cmd,
*args_down,
input=stdin,
verbose=verbose,
)
logger.info("Compose stack down. Finishing...")
except Exception:
logger.exception("Failed to bring down compose stack")
pass
logger.info("Test finished")
)
if __name__ == "__main__":
@@ -168,10 +150,4 @@ if __name__ == "__main__":
parser.add_argument("-c", "--config", type=str, default="./langgraph.json")
parser.add_argument("-p", "--port", type=int, default=DEFAULT_PORT)
args = parser.parse_args()
try:
test(pathlib.Path(args.config), args.port, args.tag, verbose=True)
except BaseException:
logger.exception("Test failed")
raise
logger.info("Test execution finished")
test(pathlib.Path(args.config), args.port, args.tag, verbose=True)
+45 -74
View File
@@ -13,26 +13,13 @@ jobs:
matrix:
python-version:
- "3.10"
- "3.14"
example:
- name: A
workdir: libs/cli/examples
tag: langgraph-test-a
- name: B
workdir: libs/cli/examples/graphs
tag: langgraph-test-b
- name: C
workdir: libs/cli/examples/graphs_reqs_a
tag: langgraph-test-c
- name: D
workdir: libs/cli/examples/graphs_reqs_b
tag: langgraph-test-d
- "3.11"
name: "CLI integration test"
defaults:
run:
working-directory: libs/cli
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- name: Get changed files
id: changed-files
uses: Ana06/get-changed-files@v2.3.0
@@ -40,79 +27,63 @@ jobs:
filter: "libs/cli/**"
- name: Set up Python ${{ matrix.python-version }}
if: steps.changed-files.outputs.all
uses: astral-sh/setup-uv@v7
uses: astral-sh/setup-uv@v6
with:
python-version: ${{ matrix.python-version }}
enable-cache: true
cache-suffix: "cli-integration-test"
ignore-nothing-to-cache: true
- name: Setup env
if: steps.changed-files.outputs.all
working-directory: libs/cli/examples
run: cat .env.example > .env
- name: Install cli globally
if: steps.changed-files.outputs.all
run: pip install -e .
- name: Build and test service ${{ matrix.example.name }}
- name: Build and test service A
if: steps.changed-files.outputs.all
working-directory: ${{ matrix.example.workdir }}
working-directory: libs/cli/examples
env:
LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
run: |
# Build the image for this example
langgraph build -t ${{ matrix.example.tag }}
# Prepare environment file from local or parent example directory
if [ -f .env.example ]; then cp .env.example .env; elif [ -f ../.env.example ]; then cp ../.env.example .env && cp ../.env.example ../.env; fi
if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; if [ -f ../.env ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> ../.env; fi; fi
# Run the integration test using the built tag
# Compute repo root to reference the shared script robustly
REPO_ROOT=$(git rev-parse --show-toplevel)
timeout 60 python "$REPO_ROOT/.github/scripts/run_langgraph_cli_test.py" -t ${{ matrix.example.tag }}
# The build-arg isn't used; just testing that we accept other args
langgraph build -t langgraph-test-a
cp .env.example .env
if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
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
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
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
timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-d
- name: Build JS service
if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' }}
if: steps.changed-files.outputs.all
working-directory: libs/cli/js-examples
run: |
langgraph build -t langgraph-test-e
- name: Build JS monorepo service
if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' }}
working-directory: libs/cli/js-monorepo-example
run: |
langgraph build -t langgraph-test-f -c apps/agent/langgraph.json --build-command "yarn run turbo build" --install-command "yarn install"
- name: Build Python monorepo service
if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' }}
working-directory: libs/cli/python-monorepo-example
run: |
langgraph build -t langgraph-test-g -c apps/agent/langgraph.json
cp apps/agent/.env.example apps/agent/.env
if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> apps/agent/.env; fi
timeout 60 python ../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-g -c apps/agent/langgraph.json
- name: Build and test prerelease reqs service
if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' }}
working-directory: libs/cli/examples/graph_prerelease_reqs
run: |
langgraph build -t langgraph-test-h
cp ../.env.example .env
if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
timeout 60 python ../../../../.github/scripts/run_langgraph_cli_test.py -t langgraph-test-h
echo "Finished starting up langgraph-test-h"
LANGGRAPH_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langgraph'); print(v);")
if [ "$LANGGRAPH_VERSION" != "1.0.2" ]; then
echo "LANGGRAPH_VERSION != 1.0.2; $LANGGRAPH_VERSION"
exit 1
fi
LANGCHAIN_OPENAI_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langchain-openai'); print(v);")
if [ "$LANGCHAIN_OPENAI_VERSION" != "1.0.1" ]; then
echo "LANGCHAIN_OPENAI_VERSION != 1.0.1; $LANGCHAIN_OPENAI_VERSION"
exit 1
fi
LANGCHAIN_ANTHROPIC_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langchain-anthropic'); print(v);")
if [ "$LANGCHAIN_ANTHROPIC_VERSION" != "1.0.0a5" ]; then
echo "LANGCHAIN_ANTHROPIC_VERSION != 1.0.0a5; $LANGCHAIN_ANTHROPIC_VERSION"
exit 1
fi
- name: Build and test prerelease reqs fail service
if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' }}
working-directory: libs/cli/examples/graph_prerelease_reqs_fail
run: |
langgraph build -t langgraph-test-i || [ $? -eq 1 ]
+4 -4
View File
@@ -31,7 +31,7 @@ jobs:
- "3.12"
name: "lint #${{ matrix.python-version }}"
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- name: Get changed files
id: changed-files
uses: Ana06/get-changed-files@v2.3.0
@@ -39,7 +39,7 @@ jobs:
filter: "${{ inputs.working-directory }}/**"
- name: Set up Python ${{ matrix.python-version }}
if: steps.changed-files.outputs.all
uses: astral-sh/setup-uv@v7
uses: astral-sh/setup-uv@v6
with:
python-version: ${{ matrix.python-version }}
enable-cache: true
@@ -48,7 +48,7 @@ jobs:
- name: Install dependencies
if: steps.changed-files.outputs.all
working-directory: ${{ inputs.working-directory }}
run: uv sync --frozen --group lint
run: uv sync --frozen --group dev
- name: Get .mypy_cache to speed up mypy
if: steps.changed-files.outputs.all
@@ -74,7 +74,7 @@ jobs:
- name: Install test dependencies
if: steps.changed-files.outputs.all
working-directory: ${{ inputs.working-directory }}
run: uv sync --group lint
run: uv sync --group dev
- name: Get .mypy_cache_test to speed up mypy
if: steps.changed-files.outputs.all
+4 -4
View File
@@ -17,17 +17,17 @@ jobs:
strategy:
matrix:
python-version:
- "3.9"
- "3.10"
- "3.11"
- "3.12"
- "3.13"
- "3.14"
name: "test #${{ matrix.python-version }}"
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- name: Set up Python ${{ matrix.python-version }}
uses: astral-sh/setup-uv@v7
uses: astral-sh/setup-uv@v6
with:
python-version: ${{ matrix.python-version }}
enable-cache: true
@@ -42,7 +42,7 @@ jobs:
- name: Install dependencies
shell: bash
working-directory: ${{ inputs.working-directory }}
run: uv sync --frozen --group test --no-dev
run: uv sync --frozen --group dev
- name: Run tests
shell: bash
+4 -4
View File
@@ -12,20 +12,20 @@ jobs:
strategy:
matrix:
python-version:
- "3.9"
- "3.10"
- "3.11"
- "3.12"
- "3.13"
- "3.14"
defaults:
run:
working-directory: libs/langgraph
name: "test #${{ matrix.python-version }}"
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- name: Set up Python ${{ matrix.python-version }}
uses: astral-sh/setup-uv@v7
uses: astral-sh/setup-uv@v6
with:
python-version: ${{ matrix.python-version }}
enable-cache: true
@@ -39,7 +39,7 @@ jobs:
- name: Install dependencies
shell: bash
run: uv sync --frozen --group test --no-dev
run: uv sync --frozen --group dev
- name: Run tests
shell: bash
+6 -5
View File
@@ -16,6 +16,7 @@ permissions:
jobs:
build:
if: github.ref == 'refs/heads/main'
runs-on: ubuntu-latest
outputs:
@@ -23,10 +24,10 @@ jobs:
version: ${{ steps.check-version.outputs.version }}
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- name: Set up Python $${ env.PYTHON_VERSION }}
uses: astral-sh/setup-uv@v7
uses: astral-sh/setup-uv@v6
with:
python-version: ${{ env.PYTHON_VERSION }}
enable-cache: true
@@ -48,7 +49,7 @@ jobs:
working-directory: ${{ inputs.working-directory }}
- name: Upload build
uses: actions/upload-artifact@v5
uses: actions/upload-artifact@v4
with:
name: test-dist
path: ${{ inputs.working-directory }}/dist/
@@ -74,9 +75,9 @@ jobs:
id-token: write
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- uses: actions/download-artifact@v6
- uses: actions/download-artifact@v4
with:
name: test-dist
path: ${{ inputs.working-directory }}/dist/
+3 -3
View File
@@ -17,16 +17,16 @@ jobs:
run:
working-directory: libs/langgraph
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- run: SHA=$(git rev-parse HEAD) && echo "SHA=$SHA" >> $GITHUB_ENV
- name: Set up Python 3.11
uses: astral-sh/setup-uv@v7
uses: astral-sh/setup-uv@v6
with:
python-version: "3.11"
enable-cache: true
cache-suffix: "bench"
- name: Install dependencies
run: uv sync --group test
run: uv sync --group dev
- name: Run benchmarks
run: OUTPUT=out/benchmark-baseline.json make -s benchmark
- name: Save outputs
+4 -4
View File
@@ -15,20 +15,20 @@ jobs:
run:
working-directory: libs/langgraph
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- id: files
name: Get changed files
uses: Ana06/get-changed-files@v2.3.0
with:
format: json
- name: Set up Python 3.11
uses: astral-sh/setup-uv@v7
uses: astral-sh/setup-uv@v6
with:
python-version: "3.11"
enable-cache: true
cache-suffix: "bench"
- name: Install dependencies
run: uv sync --group test
run: uv sync --group dev
- name: Download baseline
uses: actions/cache/restore@v4
with:
@@ -57,7 +57,7 @@ jobs:
echo EOF
} >> "$GITHUB_OUTPUT"
- name: Annotation
uses: actions/github-script@v8
uses: actions/github-script@v7
with:
script: |
const file = JSON.parse(`${{ steps.files.outputs.added_modified_renamed }}`)[0]
+7 -7
View File
@@ -27,7 +27,7 @@ jobs:
python: ${{ steps.filter.outputs.python }}
deps: ${{ steps.filter.outputs.deps }}
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- uses: dorny/paths-filter@v3
id: filter
with:
@@ -100,9 +100,9 @@ jobs:
name: "Check SDK methods matching"
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v6
uses: actions/setup-python@v5
with:
python-version: "3.11"
- name: Run check_sdk_methods script
@@ -116,13 +116,13 @@ jobs:
strategy:
matrix:
python-version:
- "3.13"
- "3.11"
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- name: Set up Python ${{ matrix.python-version }}
uses: astral-sh/setup-uv@v7
uses: astral-sh/setup-uv@v6
with:
python-version: "3.13"
python-version: "3.11"
enable-cache: true
cache-suffix: "schema-check-cli"
- name: Install CLI dependencies
+1 -1
View File
@@ -21,7 +21,7 @@
steps:
- name: Checkout
uses: actions/checkout@v6
uses: actions/checkout@v4
- name: Install Dependencies
run: |
+150
View File
@@ -0,0 +1,150 @@
name: Deploy Docs
on:
push:
branches:
- main
pull_request:
branches:
- main
workflow_dispatch:
permissions:
contents: read
pages: write
id-token: write
concurrency:
group: "pages"
cancel-in-progress: false
defaults:
run:
working-directory: docs
jobs:
get-changed-files:
runs-on: ubuntu-latest
outputs:
changed-files: ${{ steps.changed-files.outputs.added_modified }}
steps:
- uses: actions/checkout@v4
- name: Get changed files
id: changed-files
uses: Ana06/get-changed-files@v2.3.0
with:
filter: "docs/docs/**"
deploy:
runs-on: ubuntu-latest
timeout-minutes: 10 # Job will be cancelled if it runs for more than 10 minutes
env:
GITHUB_TOKEN: ${{ secrets.MKDOCS_GITHUB_TOKEN }}
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Set up Python
uses: astral-sh/setup-uv@v6
with:
python-version: "3.12"
enable-cache: true
cache-suffix: "docs"
- name: Install dependencies
run: |
yarn
uv sync --all-groups
# we run this installation only for internal PRs
# as GITHUB_TOKEN is not available for PRs from outside contributors
if [ -n "${GITHUB_TOKEN}" ]; then
uv run pip install "git+https://${GITHUB_TOKEN}@github.com/langchain-ai/mkdocs-material-insiders.git"
fi
- name: Run unit tests
# Run unit tests on the docs build pipeline
run: make tests
- name: Lint Docs
# This step lints the docs using the existing linting set up.
# It should be very fast and should not require any external services.
run: make lint-docs
- name: Build llms-text
run: make llms-text
- name: Build site
run: |
# If this is main branch, then we want to download stats. we do this
# with the env variable DOWNLOAD_STATS=true
if [ "${{ github.ref }}" == "refs/heads/main" ]; then
DOWNLOAD_STATS=true make build-docs
else
make build-docs
fi
env:
MKDOCS_GIT_COMMITTERS_APIKEY: ${{ secrets.MKDOCS_GIT_COMMITTERS_APIKEY }}
OPENAI_API_KEY: sf-proj-1234567890 # fake placeholder, shouldn't actually be used
ANTHROPIC_API_KEY: sk-ant-api03-1234567890 # fake placeholder, shouldn't actually be used
- name: Check links in notebooks
env:
LANGCHAIN_API_KEY: test
if: github.event_name == 'schedule'
run: |
if [ "${{ github.event_name }}" == "schedule" ]; then
echo "Running link check on all HTML files matching notebooks in docs directory..."
uv run pytest -v \
--check-links-ignore "https://(api|web|docs)\.smith\.langchain\.com/.*" \
--check-links-ignore "https://academy\.langchain\.com/.*" \
--check-links-ignore "https://x.com/.*" \
--check-links-ignore "https://twitter.com/.*" \
--check-links-ignore "https://github\.com/.*" \
--check-links-ignore "http://localhost:8123/.*" \
--check-links-ignore "http://localhost:2024.*" \
--check-links-ignore "http://127.0.0.1:.*" \
--check-links-ignore "/.*\.(ipynb|html)$" \
--check-links-ignore "https://python\.langchain\.com/.*" \
--check-links-ignore "https://openai\.com/.*" \
--check-links-ignore "https://www\.uber\.com/.*" \
--check-links-ignore "https://pepy\.tech/.*" \
--check-links-ignore "docs/docs/static/wordmark_*" \
--check-links $(find site -name "index.html" | grep -v 'storm/index.html')
else
echo "Fetching changes from origin/main..."
git fetch origin main
echo "Checking for changed notebook files..."
CHANGED_FILES=$(git diff --name-only --diff-filter=d origin/main | grep 'docs/docs/.*\.ipynb$' | grep -v 'storm.ipynb' | sed -E 's|^docs/docs/|site/|; s/\.ipynb$/\/index.html/' || true)
echo "Changed files: ${CHANGED_FILES}"
if [ -n "${CHANGED_FILES}" ]; then
echo "Running link check on HTML files matching changed notebook files..."
uv run pytest -v \
--check-links-ignore "https://(api|web|docs)\.smith\.langchain\.com/.*" \
--check-links-ignore "https://academy\.langchain\.com/.*" \
--check-links-ignore "http://localhost:8123/.*" \
--check-links-ignore "http://localhost:2024.*" \
--check-links-ignore "http://127.0.0.1:.*" \
--check-links-ignore "https://x.com/.*" \
--check-links-ignore "https://twitter.com/.*" \
--check-links-ignore "https://github\.com/.*" \
--check-links-ignore "/.*\.(ipynb|html)$" \
--check-links-ignore "docs/docs/static/wordmark_*" \
--check-links ${CHANGED_FILES} \
|| ([ $? = 5 ] && exit 0 || exit $?)
else
echo "No notebook files changed."
fi
fi
- name: Configure GitHub Pages
if: github.ref == 'refs/heads/main'
uses: actions/configure-pages@v5
- name: Upload Pages Artifact
# if: github.ref == 'refs/heads/main'
uses: actions/upload-pages-artifact@v3
with:
path: ./docs/site/
- name: Deploy to GitHub Pages
if: github.ref == 'refs/heads/main'
id: deployment
uses: actions/deploy-pages@v4
+2 -2
View File
@@ -19,7 +19,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
fetch-depth: 0
@@ -36,7 +36,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
fetch-depth: 1
+1 -2
View File
@@ -12,7 +12,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Validate PR Title
uses: amannn/action-semantic-pull-request@v6
uses: amannn/action-semantic-pull-request@v5
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
with:
@@ -40,7 +40,6 @@ jobs:
sdk-py
docs
ci
deps
requireScope: false
ignoreLabels: |
ignore-lint-pr-title
+14 -14
View File
@@ -16,6 +16,7 @@ env:
jobs:
build:
if: github.ref == 'refs/heads/main'
runs-on: ubuntu-latest
outputs:
@@ -25,10 +26,10 @@ jobs:
tag: ${{ steps.check-version.outputs.tag }}
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- name: Set up Python
uses: astral-sh/setup-uv@v7
uses: astral-sh/setup-uv@v6
with:
python-version: ${{ env.PYTHON_VERSION }}
enable-cache: true
@@ -50,7 +51,7 @@ jobs:
working-directory: ${{ inputs.working-directory }}
- name: Upload build
uses: actions/upload-artifact@v5
uses: actions/upload-artifact@v4
with:
name: dist
path: ${{ inputs.working-directory }}/dist/
@@ -86,7 +87,7 @@ jobs:
outputs:
release-body: ${{ steps.generate-release-body.outputs.release-body }}
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
with:
repository: langchain-ai/langgraph
path: langgraph
@@ -157,7 +158,7 @@ jobs:
- test-pypi-publish
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
# We explicitly *don't* set up caching here. This ensures our tests are
# maximally sensitive to catching breakage.
@@ -173,7 +174,7 @@ jobs:
# used in the real world.
- name: Set up Python
uses: astral-sh/setup-uv@v7
uses: astral-sh/setup-uv@v6
with:
python-version: ${{ env.PYTHON_VERSION }}
enable-cache: true
@@ -221,7 +222,7 @@ jobs:
uv run python -c "import $IMPORT_NAME; print(dir($IMPORT_NAME))"
- name: Import test dependencies
run: uv sync --group test
run: uv sync --group dev
working-directory: ${{ inputs.working-directory }}
# Overwrite the local version of the package with the test PyPI version.
@@ -260,16 +261,16 @@ jobs:
working-directory: ${{ inputs.working-directory }}
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- name: Set up Python
uses: astral-sh/setup-uv@v7
uses: astral-sh/setup-uv@v6
with:
python-version: ${{ env.PYTHON_VERSION }}
enable-cache: true
cache-suffix: "release"
- uses: actions/download-artifact@v6
- uses: actions/download-artifact@v4
with:
name: dist
path: ${{ inputs.working-directory }}/dist/
@@ -301,16 +302,16 @@ jobs:
working-directory: ${{ inputs.working-directory }}
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- name: Set up Python
uses: astral-sh/setup-uv@v7
uses: astral-sh/setup-uv@v6
with:
python-version: ${{ env.PYTHON_VERSION }}
enable-cache: true
cache-suffix: "release"
- uses: actions/download-artifact@v6
- uses: actions/download-artifact@v4
with:
name: dist
path: ${{ inputs.working-directory }}/dist/
@@ -322,6 +323,5 @@ jobs:
token: ${{ secrets.GITHUB_TOKEN }}
generateReleaseNotes: false
tag: ${{needs.build.outputs.tag}}
name: ${{ needs.build.outputs.pkg-name }}==${{ needs.build.outputs.version }}
body: ${{ needs.release-notes.outputs.release-body }}
commit: ${{ github.sha }}
+2 -2
View File
@@ -28,9 +28,9 @@ jobs:
- "latest"
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- name: Set up Python + Poetry
uses: astral-sh/setup-uv@v7
uses: astral-sh/setup-uv@v6
with:
python-version: "3.11"
enable-cache: true
+5 -5
View File
@@ -16,13 +16,13 @@ jobs:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- name: Set up uv
uses: astral-sh/setup-uv@v7
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"
@@ -33,8 +33,8 @@ jobs:
uses: peter-evans/create-pull-request@v7
with:
token: ${{ secrets.GITHUB_TOKEN }}
commit-message: "chore(deps): upgrade dependencies with `uv lock --upgrade`"
title: "chore(deps): upgrade dependencies with `uv lock --upgrade`"
commit-message: "chore[deps]: upgrade dependencies with `uv lock --upgrade`"
title: "chore[deps]: upgrade dependencies with `uv lock --upgrade`"
body: |
This PR updates the dependencies in all Python packages using `uv lock --upgrade`.
+1 -1
View File
@@ -28,7 +28,7 @@ Below is a high-level overview:
- **langgraph** core framework for building stateful, multi-actor agents.
- **prebuilt** high-level APIs for creating and running agents and tools.
- **sdk-js** JS/TS SDK for interacting with the LangGraph REST API.
- **sdk-py** Python SDK for the LangGraph Server API.
- **sdk-py** Python SDK for the LangGraph Platform API.
### Dependency map
+3 -3
View File
@@ -277,9 +277,9 @@ def my_function(arg1: int, arg2: str) -> float:
Examples:
This is a section for examples of how to use the function.
```python
my_function(1, "hello")
\```
.. code-block:: python
my_function(1, "hello")
Args:
arg1: This is a description of arg1. We do not need to specify the type since
+5 -5
View File
@@ -63,15 +63,15 @@ LangGraph provides low-level supporting infrastructure for *any* long-running, s
While LangGraph can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools for building agents. To improve your LLM application development, pair LangGraph with:
- [LangSmith](http://www.langchain.com/langsmith) — Helpful for agent evals and observability. Debug poor-performing LLM app runs, evaluate agent trajectories, gain visibility in production, and improve performance over time.
- [LangSmith Deployment](https://langchain-ai.github.io/langgraph/concepts/langgraph_platform/) — Deploy and scale agents effortlessly with a purpose-built deployment platform for long running, stateful workflows. Discover, reuse, configure, and share agents across teams — and iterate quickly with visual prototyping in [LangGraph Studio](https://langchain-ai.github.io/langgraph/concepts/langgraph_studio/).
- [LangChain](https://docs.langchain.com/oss/python/langchain/overview) Provides integrations and composable components to streamline LLM application development.
- [LangGraph Platform](https://langchain-ai.github.io/langgraph/concepts/langgraph_platform/) — Deploy and scale agents effortlessly with a purpose-built deployment platform for long running, stateful workflows. Discover, reuse, configure, and share agents across teams — and iterate quickly with visual prototyping in [LangGraph Studio](https://langchain-ai.github.io/langgraph/concepts/langgraph_studio/).
- [LangChain](https://python.langchain.com/docs/introduction/) Provides integrations and composable components to streamline LLM application development.
> [!NOTE]
> Looking for the JS version of LangGraph? See the [JS repo](https://github.com/langchain-ai/langgraphjs) and the [JS docs](https://docs.langchain.com/oss/javascript/langgraph/overview).
> Looking for the JS version of LangGraph? See the [JS repo](https://github.com/langchain-ai/langgraphjs) and the [JS docs](https://langchain-ai.github.io/langgraphjs/).
## Additional resources
- [Guides](https://langchain-ai.github.io/langgraph/guides/): Quick, actionable code snippets for topics such as streaming, adding memory & persistence, and design patterns (e.g. branching, subgraphs, etc.).
- [Guides](https://langchain-ai.github.io/langgraph/how-tos/): Quick, actionable code snippets for topics such as streaming, adding memory & persistence, and design patterns (e.g. branching, subgraphs, etc.).
- [Reference](https://langchain-ai.github.io/langgraph/reference/graphs/): Detailed reference on core classes, methods, how to use the graph and checkpointing APIs, and higher-level prebuilt components.
- [Examples](https://langchain-ai.github.io/langgraph/examples/): Guided examples on getting started with LangGraph.
- [LangChain Forum](https://forum.langchain.com/): Connect with the community and share all of your technical questions, ideas, and feedback.
@@ -81,4 +81,4 @@ While LangGraph can be used standalone, it also integrates seamlessly with any L
## Acknowledgements
LangGraph is inspired by [Pregel](https://research.google/pubs/pub37252/) and [Apache Beam](https://beam.apache.org/). The public interface draws inspiration from [NetworkX](https://networkx.org/documentation/latest/). LangGraph is built by LangChain Inc, the creators of LangChain, but can be used without LangChain.
LangGraph is inspired by [Pregel](https://research.google/pubs/pub37252/) and [Apache Beam](https://beam.apache.org/). The public interface draws inspiration from [NetworkX](https://networkx.org/documentation/latest/). LangGraph is built by LangChain Inc, the creators of LangChain, but can be used without LangChain.
+14 -117
View File
@@ -1,126 +1,24 @@
# LangGraph Documentation
# Setup
For more information on contributing to our documentation, see the [Contributing Guide](../CONTRIBUTING.md).
## Structure
The primary documentation is located in the `docs/` directory. This directory contains both the source files for the main documentation as well as the API reference doc build process.
### Main Documentation
Main documentation files are located in `docs/docs/` and are written in Markdown format. The site uses [**MkDocs**](https://www.mkdocs.org/) with the [Material theme](https://squidfunk.github.io/mkdocs-material/) and includes:
- **Concepts**: Core LangGraph concepts and explanations
- **Tutorials**: Step-by-step learning guides
- **How-tos**: Task-focused guides for specific use cases
- **Examples**: Real-world applications and use cases
- **Jupyter Notebooks**: Interactive tutorials that are automatically converted to markdown
### API Reference
API reference documentation is defined in `docs/docs/reference/`. Each `.md` file outlines the "template" that each page is built from. Reference content is automatically generated from docstrings in the codebase using the **mkdocstrings** plugin. Once generated, the content is plugged into the corresponding markdown file where it is referenced by using manual directives to specify which classes and/or functions are documented:
```markdown
::: langgraph.graph.state.StateGraph
options:
show_if_no_docstring: true
show_root_heading: true
show_root_full_path: false
members:
- add_node
- add_edge
- add_conditional_edges
- add_sequence
- compile
```
## Build Process
Docs are built following these steps:
1. **Content Processing:**
- `_scripts/notebook_hooks.py` - Main processing pipeline that:
- Converts how-tos/tutorial Jupyter notebooks to markdown using `notebook_convert.py`
- Adds automatic API reference links to code blocks using `generate_api_reference_links.py`
- Handles conditional rendering for Python/JS versions
- Processes highlight comments and custom syntax
2. **API Reference Generation:**
- **mkdocstrings** plugin extracts docstrings from Python source code
- Manual `::: module.Class` directives in reference pages (`/docs/docs/*`) specify what to document
- Cross-references are automatically generated between docs and API
3. **Site Generation:**
- **MkDocs** processes all markdown files and generates static HTML
- Custom hooks handle redirects and inject additional functionality
4. **Deployment:**
- Site is deployed with Vercel
- `make build-docs` generates production build (also usable for local testing)
- Automatic redirects handle URL changes between versions
### Local Development
For local development, use the Makefile targets:
To setup requirements for building docs you can run:
```bash
uv sync --group test
```
## Serving documentation locally
To run the documentation server locally you can run:
```bash
# Serve docs locally with hot reloading
make serve-docs
# Clean build for production testing
make build-docs
# Serve with clean build
make serve-clean-docs
```
The `serve-docs` command:
- Watches source files for changes
- Includes dirty builds for faster iteration
- Serves on [http://127.0.0.1:8000/langgraph/](http://127.0.0.1:8000/langgraph/)
## Standards
**Docstring Format:**
The API reference uses **Google-style docstrings** with Markdown markup. The `mkdocstrings` plugin processes these to generate documentation.
**Required format:**
```python
def example_function(param1: str, param2: int = 5) -> bool:
"""Brief description of the function.
Longer description can go here. Use Markdown syntax for
rich formatting like **bold** and *italic*.
Args:
param1: Description of the first parameter.
param2: Description of the second parameter with default value.
Returns:
Description of the return value.
Raises:
ValueError: When param1 is empty.
TypeError: When param2 is not an integer.
!!! warning
This function is experimental and may change.
!!! version-added "Added in version 0.2.0"
"""
```
**Special Markers:**
- **MkDocs admonitions**: `!!! warning`, `!!! note`, `!!! version-added`
- **Code blocks**: Standard markdown ``` syntax
- **Cross-references**: Automatic linking via `generate_api_reference_links.py`
This will start the documentation server on [http://127.0.0.1:8000/langgraph/](http://127.0.0.1:8000/langgraph/).
## Execute notebooks
If you would like to automatically execute all of the notebooks, to mimic the "Run notebooks" GitHub action, you can run:
If you would like to automatically execute all of the notebooks, to mimic the "Run notebooks" GHA, you can run:
```bash
python _scripts/prepare_notebooks_for_ci.py
@@ -135,9 +33,8 @@ python _scripts/prepare_notebooks_for_ci.py --comment-install-cells
```
`prepare_notebooks_for_ci.py` script will add VCR cassette context manager for each cell in the notebook, so that:
- when the notebook is run for the first time, cells with network requests will be recorded to a VCR cassette file
- when the notebook is run subsequently, the cells with network requests will be replayed from the cassettes
* when the notebook is run for the first time, cells with network requests will be recorded to a VCR cassette file
* when the notebook is run subsequently, the cells with network requests will be replayed from the cassettes
## Adding new notebooks
+2 -14
View File
@@ -1,5 +1,3 @@
"""Generate API reference links for imports in Python code blocks within markdown files."""
import ast
import importlib
import logging
@@ -72,18 +70,8 @@ MANUAL_API_REFERENCES_LANGGRAPH = [
([], "langgraph.checkpoint.postgres.aio", "AsyncPostgresSaver", "checkpoints"),
([], "langgraph.checkpoint.postgres", "PostgresSaver", "checkpoints"),
# other prebuilts
(
["langgraph_supervisor"],
"langgraph_supervisor.supervisor",
"create_supervisor",
"supervisor",
),
(
["langgraph_supervisor"],
"langgraph_supervisor.handoff",
"create_handoff_tool",
"supervisor",
),
(["langgraph_supervisor"], "langgraph_supervisor.supervisor", "create_supervisor", "supervisor"),
(["langgraph_supervisor"], "langgraph_supervisor.handoff", "create_handoff_tool", "supervisor"),
([], "langgraph_supervisor.handoff", "create_forward_message_tool", "supervisor"),
(["langgraph_swarm"], "langgraph_swarm.swarm", "create_swarm", "swarm"),
(["langgraph_swarm"], "langgraph_swarm.swarm", "add_active_agent_router", "swarm"),
+4 -10
View File
@@ -29,11 +29,7 @@ logger = logging.getLogger(__name__)
def _transform_link(
link_name: str,
scope: str,
file_path: str,
line_number: int,
custom_title: Optional[str] = None,
link_name: str, scope: str, file_path: str, line_number: int, custom_title: Optional[str] = None
) -> Optional[str]:
"""Transform a cross-reference link based on the current scope.
@@ -42,7 +38,7 @@ def _transform_link(
scope: The current scope context ("global", "python", "js", etc.).
file_path: The file path for error reporting.
line_number: The line number for error reporting.
custom_title: Optional custom title for the link. If `None`, uses link_name.
custom_title: Optional custom title for the link. If None, uses link_name.
Returns:
A formatted markdown link if the link is found in the scope mapping,
@@ -121,9 +117,7 @@ CROSS_REFERENCE_PATTERN = re.compile(
)
def _replace_autolinks(
markdown: str, file_path: str, *, default_scope: str = "python"
) -> str:
def _replace_autolinks(markdown: str, file_path: str, *, default_scope: str = "python") -> str:
"""Preprocess markdown lines to handle @[links] with conditional fence scopes.
This function processes markdown content to transform @[link_name] references
@@ -175,7 +169,7 @@ def _replace_autolinks(
# This is @[ref] format
link_name = match.group("link_name")
custom_title = None
transformed = _transform_link(
link_name, current_scope, file_path, line_number, custom_title
)
@@ -2108,9 +2108,9 @@ __metadata:
linkType: hard
"hono@npm:^4.5.4":
version: 4.10.3
resolution: "hono@npm:4.10.3"
checksum: 10c0/bdcc4c7066c74ba7cfa63ed6550768a0f43a420286c8f8f74b7012ea4901b8b06778fa8e98264b46f1a86920f056b7ede1f07814da4934912f9945def4977c29
version: 4.8.9
resolution: "hono@npm:4.8.9"
checksum: 10c0/385539d1787fdc747bc869ef0e5ccc9f39cbe40289b94f23eecfc82c6ca440f059704647cd6381a5066d2cf7baa43ab25184c78d44af4c5c98a5c5b07670059e
languageName: node
linkType: hard
@@ -2340,13 +2340,13 @@ __metadata:
linkType: hard
"js-yaml@npm:^4.1.0":
version: 4.1.1
resolution: "js-yaml@npm:4.1.1"
version: 4.1.0
resolution: "js-yaml@npm:4.1.0"
dependencies:
argparse: "npm:^2.0.1"
bin:
js-yaml: bin/js-yaml.js
checksum: 10c0/561c7d7088c40a9bb53cc75becbfb1df6ae49b34b5e6e5a81744b14ae8667ec564ad2527709d1a6e7d5e5fa6d483aa0f373a50ad98d42fde368ec4a190d4fae7
checksum: 10c0/184a24b4eaacfce40ad9074c64fd42ac83cf74d8c8cd137718d456ced75051229e5061b8633c3366b8aada17945a7a356b337828c19da92b51ae62126575018f
languageName: node
linkType: hard
-2
View File
@@ -1,5 +1,3 @@
"""Convert Jupyter notebooks to markdown with custom processing."""
import ast
import os
import re
+170 -494
View File
@@ -27,430 +27,185 @@ DISABLED = os.getenv("DISABLE_NOTEBOOK_CONVERT") in ("1", "true", "True")
REDIRECT_MAP = {
# lib redirects
"how-tos/stream-values.ipynb": "https://docs.langchain.com/oss/python/langgraph/streaming",
"how-tos/stream-updates.ipynb": "https://docs.langchain.com/oss/python/langgraph/streaming",
"how-tos/streaming-content.ipynb": "https://docs.langchain.com/oss/python/langgraph/streaming",
"how-tos/stream-multiple.ipynb": "https://docs.langchain.com/oss/python/langgraph/streaming",
"how-tos/streaming-tokens-without-langchain.ipynb": "https://docs.langchain.com/oss/python/langgraph/streaming",
"how-tos/streaming-from-final-node.ipynb": "https://docs.langchain.com/oss/python/langgraph/streaming",
"how-tos/streaming-events-from-within-tools-without-langchain.ipynb": "https://docs.langchain.com/oss/python/langgraph/streaming",
"how-tos/stream-values.ipynb": "how-tos/streaming.md#stream-graph-state",
"how-tos/stream-updates.ipynb": "how-tos/streaming.md#stream-graph-state",
"how-tos/streaming-content.ipynb": "how-tos/streaming.md",
"how-tos/stream-multiple.ipynb": "how-tos/streaming.md#stream-multiple-nodes",
"how-tos/streaming-tokens-without-langchain.ipynb": "how-tos/streaming.md#use-with-any-llm",
"how-tos/streaming-from-final-node.ipynb": "how-tos/streaming-specific-nodes.ipynb",
"how-tos/streaming-events-from-within-tools-without-langchain.ipynb": "how-tos/streaming-events-from-within-tools.ipynb#example-without-langchain",
# graph-api
"how-tos/state-reducers.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#define-and-update-state",
"how-tos/sequence.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#create-a-sequence-of-steps",
"how-tos/branching.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#create-branches",
"how-tos/recursion-limit.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#create-and-control-loops",
"how-tos/visualization.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#visualize-your-graph",
"how-tos/input_output_schema.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#define-input-and-output-schemas",
"how-tos/pass_private_state.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#pass-private-state-between-nodes",
"how-tos/state-model.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#use-pydantic-models-for-graph-state",
"how-tos/map-reduce.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#map-reduce-and-the-send-api",
"how-tos/command.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#combine-control-flow-and-state-updates-with-command",
"how-tos/configuration.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#add-runtime-configuration",
"how-tos/node-retries.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#add-retry-policies",
"how-tos/return-when-recursion-limit-hits.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#impose-a-recursion-limit",
"how-tos/async.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api#async",
"how-tos/state-reducers.ipynb": "how-tos/graph-api.md#define-and-update-state",
"how-tos/sequence.ipynb": "how-tos/graph-api.md#create-a-sequence-of-steps",
"how-tos/branching.ipynb": "how-tos/graph-api.md#create-branches",
"how-tos/recursion-limit.ipynb": "how-tos/graph-api.md#create-and-control-loops",
"how-tos/visualization.ipynb": "how-tos/graph-api.md#visualize-your-graph",
"how-tos/input_output_schema.ipynb": "how-tos/graph-api.md#define-input-and-output-schemas",
"how-tos/pass_private_state.ipynb": "how-tos/graph-api.md#pass-private-state-between-nodes",
"how-tos/state-model.ipynb": "how-tos/graph-api.md#use-pydantic-models-for-graph-state",
"how-tos/map-reduce.ipynb": "how-tos/graph-api.md#map-reduce-and-the-send-api",
"how-tos/command.ipynb": "how-tos/graph-api.md#combine-control-flow-and-state-updates-with-command",
"how-tos/configuration.ipynb": "how-tos/graph-api.md#add-runtime-configuration",
"how-tos/node-retries.ipynb": "how-tos/graph-api.md#add-retry-policies",
"how-tos/return-when-recursion-limit-hits.ipynb": "how-tos/graph-api.md#impose-a-recursion-limit",
"how-tos/async.ipynb": "how-tos/graph-api.md#async",
# memory how-tos
"how-tos/memory/manage-conversation-history.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory",
"how-tos/memory/delete-messages.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory#delete-messages",
"how-tos/memory/add-summary-conversation-history.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory#summarize-messages",
"how-tos/memory.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory",
"agents/memory.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory",
"how-tos/memory/manage-conversation-history.ipynb": "how-tos/memory/add-memory.md",
"how-tos/memory/delete-messages.ipynb": "how-tos/memory/add-memory.md#delete-messages",
"how-tos/memory/add-summary-conversation-history.ipynb": "how-tos/memory/add-memory.md#summarize-messages",
"how-tos/memory.ipynb": "how-tos/memory/add-memory.md",
"agents/memory.ipynb": "how-tos/memory/add-memory.md",
# subgraph how-tos
"how-tos/subgraph-transform-state.ipynb": "https://docs.langchain.com/oss/python/langgraph/use-subgraphs#different-state-schemas",
"how-tos/subgraphs-manage-state.ipynb": "https://docs.langchain.com/oss/python/langgraph/use-subgraphs#add-persistence",
"how-tos/subgraph-transform-state.ipynb": "how-tos/subgraph.md#different-state-schemas",
"how-tos/subgraphs-manage-state.ipynb": "how-tos/subgraph.md#add-persistence",
# persistence how-tos
"how-tos/persistence_postgres.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory#use-in-production",
"how-tos/persistence_mongodb.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory#use-in-production",
"how-tos/persistence_redis.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory#use-in-production",
"how-tos/subgraph-persistence.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory#use-with-subgraphs",
"how-tos/cross-thread-persistence.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory#add-long-term-memory",
"cloud/how-tos/copy_threads": "https://docs.langchain.com/langsmith/use-threads",
"cloud/how-tos/check-thread-status": "https://docs.langchain.com/langsmith/use-threads",
"cloud/concepts/threads.md": "https://docs.langchain.com/oss/python/langgraph/persistence#threads",
"how-tos/persistence.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory",
"how-tos/persistence_postgres.ipynb": "how-tos/memory/add-memory.md#use-in-production",
"how-tos/persistence_mongodb.ipynb": "how-tos/memory/add-memory.md#use-in-production",
"how-tos/persistence_redis.ipynb": "how-tos/memory/add-memory.md#use-in-production",
"how-tos/subgraph-persistence.ipynb": "how-tos/memory/add-memory.md#use-with-subgraphs",
"how-tos/cross-thread-persistence.ipynb": "how-tos/memory/add-memory.md#add-long-term-memory",
"cloud/how-tos/copy_threads": "cloud/how-tos/use_threads",
"cloud/how-tos/check-thread-status": "cloud/how-tos/use_threads",
"cloud/concepts/threads.md": "concepts/persistence.md#threads",
"how-tos/persistence.ipynb": "how-tos/memory/add-memory.md",
# tool calling how-tos
"how-tos/tool-calling-errors.ipynb": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
"how-tos/pass-config-to-tools.ipynb": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
"how-tos/pass-run-time-values-to-tools.ipynb": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
"how-tos/update-state-from-tools.ipynb": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
"agents/tools.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
"how-tos/tool-calling-errors.ipynb": "how-tos/tool-calling.ipynb#handle-errors",
"how-tos/pass-config-to-tools.ipynb": "how-tos/tool-calling.ipynb#access-config",
"how-tos/pass-run-time-values-to-tools.ipynb": "how-tos/tool-calling.ipynb#read-state",
"how-tos/update-state-from-tools.ipynb": "how-tos/tool-calling.ipynb#update-state",
"agents/tools.md": "how-tos/tool-calling.md",
# multi-agent how-tos
"how-tos/agent-handoffs.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api",
"how-tos/multi-agent-network.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api",
"how-tos/multi-agent-multi-turn-convo.ipynb": "https://docs.langchain.com/oss/python/langgraph/graph-api",
"how-tos/agent-handoffs.ipynb": "how-tos/multi_agent.md#handoffs",
"how-tos/multi-agent-network.ipynb": "how-tos/multi_agent.md#use-in-a-multi-agent-system",
"how-tos/multi-agent-multi-turn-convo.ipynb": "how-tos/multi_agent.md#multi-turn-conversation",
# cloud redirects
"cloud/index.md": "https://docs.langchain.com/oss/python/langgraph/overview",
"cloud/how-tos/index.md": "https://docs.langchain.com/langsmith/home",
"cloud/concepts/api.md": "https://docs.langchain.com/langsmith/agent-server",
"cloud/concepts/cloud.md": "https://docs.langchain.com/langsmith/cloud",
"cloud/faq/studio.md": "https://docs.langchain.com/langsmith/studio",
"cloud/how-tos/human_in_the_loop_edit_state.md": "https://docs.langchain.com/langsmith/add-human-in-the-loop",
"cloud/how-tos/human_in_the_loop_user_input.md": "https://docs.langchain.com/langsmith/add-human-in-the-loop",
"concepts/platform_architecture.md": "https://docs.langchain.com/langsmith/cloud#architecture",
"cloud/index.md": "index.md",
"cloud/how-tos/index.md": "concepts/langgraph_platform",
"cloud/concepts/api.md": "concepts/langgraph_server.md",
"cloud/concepts/cloud.md": "concepts/langgraph_cloud.md",
"cloud/faq/studio.md": "concepts/langgraph_studio.md#studio-faqs",
"cloud/how-tos/human_in_the_loop_edit_state.md": "cloud/how-tos/add-human-in-the-loop.md",
"cloud/how-tos/human_in_the_loop_user_input.md": "cloud/how-tos/add-human-in-the-loop.md",
"concepts/platform_architecture.md": "concepts/langgraph_cloud#architecture",
# cloud streaming redirects
"cloud/how-tos/stream_values.md": "https://docs.langchain.com/langsmith/streaming",
"cloud/how-tos/stream_updates.md": "https://docs.langchain.com/langsmith/streaming",
"cloud/how-tos/stream_messages.md": "https://docs.langchain.com/langsmith/streaming",
"cloud/how-tos/stream_events.md": "https://docs.langchain.com/langsmith/streaming",
"cloud/how-tos/stream_debug.md": "https://docs.langchain.com/langsmith/streaming",
"cloud/how-tos/stream_multiple.md": "https://docs.langchain.com/langsmith/streaming",
"cloud/concepts/streaming.md": "https://docs.langchain.com/oss/python/langgraph/streaming",
"agents/streaming.md": "https://docs.langchain.com/oss/python/langgraph/streaming",
"cloud/how-tos/stream_values.md": "https://docs.langchain.com/langgraph-platform/streaming",
"cloud/how-tos/stream_updates.md": "https://docs.langchain.com/langgraph-platform/streaming",
"cloud/how-tos/stream_messages.md": "https://docs.langchain.com/langgraph-platform/streaming",
"cloud/how-tos/stream_events.md": "https://docs.langchain.com/langgraph-platform/streaming",
"cloud/how-tos/stream_debug.md": "https://docs.langchain.com/langgraph-platform/streaming",
"cloud/how-tos/stream_multiple.md": "https://docs.langchain.com/langgraph-platform/streaming",
"cloud/concepts/streaming.md": "concepts/streaming.md",
"agents/streaming.md": "how-tos/streaming.md",
# prebuilt redirects
"how-tos/create-react-agent.ipynb": "https://docs.langchain.com/oss/python/langchain/agents#basic-configuration",
"how-tos/create-react-agent-memory.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory",
"how-tos/create-react-agent-system-prompt.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory",
"how-tos/create-react-agent-structured-output.ipynb": "https://docs.langchain.com/oss/python/langchain/agents#structured-output",
"how-tos/create-react-agent.ipynb": "agents/agents.md#basic-configuration",
"how-tos/create-react-agent-memory.ipynb": "agents/memory.md",
"how-tos/create-react-agent-system-prompt.ipynb": "agents/context.md#prompts",
"how-tos/create-react-agent-structured-output.ipynb": "agents/agents.md#structured-output",
# misc
"prebuilt.md": "https://docs.langchain.com/oss/python/langchain/agents",
"reference/prebuilt.md": "https://reference.langchain.com/python/langgraph/agents/",
"concepts/high_level.md": "https://docs.langchain.com/oss/python/langgraph/overview",
"concepts/index.md": "https://docs.langchain.com/oss/python/langgraph/overview",
"concepts/v0-human-in-the-loop.md": "https://docs.langchain.com/oss/python/langgraph/interrupts",
"how-tos/index.md": "https://docs.langchain.com/oss/python/langgraph/overview",
"tutorials/introduction.ipynb": "https://docs.langchain.com/oss/python/langgraph/overview",
"agents/deployment.md": "https://docs.langchain.com/oss/python/langgraph/local-server",
"prebuilt.md": "agents/prebuilt.md",
"reference/prebuilt.md": "reference/agents.md",
"concepts/high_level.md": "index.md",
"concepts/index.md": "index.md",
"concepts/v0-human-in-the-loop.md": "concepts/human-in-the-loop.md",
"how-tos/index.md": "index.md",
"tutorials/introduction.ipynb": "concepts/why-langgraph.md",
"agents/deployment.md": "tutorials/langgraph-platform/local-server.md",
# deployment redirects
"how-tos/deploy-self-hosted.md": "https://docs.langchain.com/langsmith/platform-setup",
"concepts/self_hosted.md": "https://docs.langchain.com/langsmith/platform-setup",
"tutorials/deployment.md": "https://docs.langchain.com/langsmith/deployments",
"how-tos/deploy-self-hosted.md": "cloud/deployment/self_hosted_data_plane.md",
"concepts/self_hosted.md": "concepts/langgraph_self_hosted_data_plane.md",
"tutorials/deployment.md": "concepts/deployment_options.md",
# assistant redirects
"cloud/how-tos/assistant_versioning.md": "https://docs.langchain.com/langsmith/configuration-cloud",
"cloud/concepts/runs.md": "https://docs.langchain.com/langsmith/assistants#execution",
"cloud/how-tos/assistant_versioning.md": "cloud/how-tos/configuration_cloud.md",
"cloud/concepts/runs.md": "concepts/assistants.md#execution",
# hitl redirects
"how-tos/wait-user-input-functional.ipynb": "https://docs.langchain.com/oss/python/langgraph/functional-api",
"how-tos/review-tool-calls-functional.ipynb": "https://docs.langchain.com/oss/python/langgraph/functional-api",
"how-tos/create-react-agent-hitl.ipynb": "https://docs.langchain.com/oss/python/langgraph/interrupts",
"agents/human-in-the-loop.md": "https://docs.langchain.com/oss/python/langgraph/interrupts",
"how-tos/human_in_the_loop/dynamic_breakpoints.ipynb": "https://docs.langchain.com/oss/python/langgraph/interrupts",
"concepts/breakpoints.md": "https://docs.langchain.com/oss/python/langgraph/interrupts",
"how-tos/human_in_the_loop/breakpoints.md": "https://docs.langchain.com/oss/python/langgraph/interrupts",
"cloud/how-tos/human_in_the_loop_breakpoint.md": "https://docs.langchain.com/langsmith/add-human-in-the-loop",
"how-tos/human_in_the_loop/edit-graph-state.ipynb": "https://docs.langchain.com/oss/python/langgraph/use-time-travel",
"how-tos/wait-user-input-functional.ipynb": "how-tos/use-functional-api.md",
"how-tos/review-tool-calls-functional.ipynb": "how-tos/use-functional-api.md",
"how-tos/create-react-agent-hitl.ipynb": "how-tos/human_in_the_loop/add-human-in-the-loop.md",
"agents/human-in-the-loop.md": "how-tos/human_in_the_loop/add-human-in-the-loop.md",
"how-tos/human_in_the_loop/dynamic_breakpoints.ipynb": "how-tos/human_in_the_loop/breakpoints.md",
"concepts/breakpoints.md": "concepts/human_in_the_loop.md",
"how-tos/human_in_the_loop/breakpoints.md": "how-tos/human_in_the_loop/add-human-in-the-loop.md",
"cloud/how-tos/human_in_the_loop_breakpoint.md": "cloud/how-tos/add-human-in-the-loop.md",
"how-tos/human_in_the_loop/edit-graph-state.ipynb": "how-tos/human_in_the_loop/time-travel.md",
# LGP mintlify migration redirects
"examples/index.md": "https://docs.langchain.com/oss/python/learn",
"guides/index.md": "https://docs.langchain.com/oss/python/langgraph/overview",
"concepts/index.md": "https://docs.langchain.com/oss/python/langgraph/overview",
"tutorials/index.md": "https://docs.langchain.com/oss/python/learn",
"llms-txt-overview.md": "https://docs.langchain.com/llms.txt",
"tutorials/rag/langgraph_adaptive_rag.md": "https://docs.langchain.com/oss/python/langgraph/agentic-rag",
"tutorials/multi_agent/multi-agent-collaboration.ipynb": "https://docs.langchain.com/oss/python/langchain/multi-agent",
"how-tos/create-react-agent-manage-message-history.ipynb": "https://docs.langchain.com/oss/python/langgraph/add-memory",
"how-tos/many-tools.ipynb": "https://docs.langchain.com/oss/python/langchain/tools",
"tutorials/customer-support/customer-support.ipynb": "https://docs.langchain.com/oss/python/langgraph/agentic-rag",
"how-tos/react-agent-structured-output.ipynb": "https://docs.langchain.com/oss/python/langchain/agents#structured-output",
"tutorials/code_assistant/langgraph_code_assistant.ipynb": "https://docs.langchain.com/oss/python/langgraph/agentic-rag",
"tutorials/multi_agent/hierarchical_agent_teams.ipynb": "https://docs.langchain.com/oss/python/langchain/supervisor",
"tutorials/auth/getting_started.md": "https://docs.langchain.com/langsmith/auth",
"tutorials/auth/resource_auth.md": "https://docs.langchain.com/langsmith/resource-auth",
"tutorials/auth/add_auth_server.md": "https://docs.langchain.com/langsmith/add-auth-server",
"how-tos/use-remote-graph.md": "https://docs.langchain.com/langsmith/use-remote-graph",
"how-tos/autogen-integration.md": "https://docs.langchain.com/langsmith/autogen-integration",
"how-tos/human_in_the_loop/wait-user-input.ipynb": "https://docs.langchain.com/oss/python/langgraph/interrupts",
"cloud/how-tos/use_stream_react.md": "https://docs.langchain.com/langsmith/use-stream-react",
"cloud/how-tos/generative_ui_react.md": "https://docs.langchain.com/langsmith/generative-ui-react",
"concepts/langgraph_platform.md": "https://docs.langchain.com/langsmith/deployments",
"concepts/langgraph_components.md": "https://docs.langchain.com/langsmith/components",
"concepts/langgraph_server.md": "https://docs.langchain.com/langsmith/agent-server",
"concepts/langgraph_data_plane.md": "https://docs.langchain.com/langsmith/data-plane",
"concepts/langgraph_control_plane.md": "https://docs.langchain.com/langsmith/control-plane",
"concepts/langgraph_cli.md": "https://docs.langchain.com/langsmith/cli",
"concepts/langgraph_studio.md": "https://docs.langchain.com/langsmith/studio",
"cloud/how-tos/studio/quick_start.md": "https://docs.langchain.com/langsmith/quick-start-studio",
"cloud/how-tos/invoke_studio.md": "https://docs.langchain.com/langsmith/use-studio#run-application",
"cloud/how-tos/studio/manage_assistants.md": "https://docs.langchain.com/langsmith/use-studio#manage-assistants",
"cloud/how-tos/threads_studio.md": "https://docs.langchain.com/langsmith/use-studio#manage-threads",
"cloud/how-tos/iterate_graph_studio.md": "https://docs.langchain.com/langsmith/observability-studio#iterate-on-prompts",
"cloud/how-tos/studio/run_evals.md": "https://docs.langchain.com/langsmith/observability-studio#run-experiments-over-a-dataset",
"cloud/how-tos/clone_traces_studio.md": "https://docs.langchain.com/langsmith/observability-studio#debug-langsmith-traces",
"cloud/how-tos/datasets_studio.md": "https://docs.langchain.com/langsmith/observability-studio#add-node-to-dataset",
"concepts/sdk.md": "https://docs.langchain.com/langsmith/sdk",
"concepts/plans.md": "https://langchain.com/pricing",
"concepts/application_structure.md": "https://docs.langchain.com/langsmith/application-structure",
"concepts/scalability_and_resilience.md": "https://docs.langchain.com/langsmith/scalability-and-resilience",
"concepts/auth.md": "https://docs.langchain.com/langsmith/authentication-methods",
"how-tos/auth/custom_auth.md": "https://docs.langchain.com/langsmith/custom-auth",
"how-tos/auth/openapi_security.md": "https://docs.langchain.com/langsmith/openapi-security",
"concepts/assistants.md": "https://docs.langchain.com/langsmith/assistants",
"cloud/how-tos/configuration_cloud.md": "https://docs.langchain.com/langsmith/cloud",
"cloud/how-tos/use_threads.md": "https://docs.langchain.com/langsmith/use-threads",
"cloud/how-tos/background_run.md": "https://docs.langchain.com/langsmith/background-run",
"cloud/how-tos/same-thread.md": "https://docs.langchain.com/langsmith/same-thread",
"cloud/how-tos/stateless_runs.md": "https://docs.langchain.com/langsmith/stateless-runs",
"cloud/how-tos/configurable_headers.md": "https://docs.langchain.com/langsmith/configurable-headers",
"concepts/double_texting.md": "https://docs.langchain.com/langsmith/double-texting",
"cloud/how-tos/interrupt_concurrent.md": "https://docs.langchain.com/langsmith/interrupt-concurrent",
"cloud/how-tos/rollback_concurrent.md": "https://docs.langchain.com/langsmith/rollback-concurrent",
"cloud/how-tos/reject_concurrent.md": "https://docs.langchain.com/langsmith/reject-concurrent",
"cloud/how-tos/enqueue_concurrent.md": "https://docs.langchain.com/langsmith/enqueue-concurrent",
"cloud/concepts/webhooks.md": "https://docs.langchain.com/langsmith/use-webhooks",
"cloud/how-tos/webhooks.md": "https://docs.langchain.com/langsmith/use-webhooks",
"cloud/concepts/cron_jobs.md": "https://docs.langchain.com/langsmith/cron-jobs",
"cloud/how-tos/cron_jobs.md": "https://docs.langchain.com/langsmith/cron-jobs",
"how-tos/http/custom_lifespan.md": "https://docs.langchain.com/langsmith/custom-lifespan",
"how-tos/http/custom_middleware.md": "https://docs.langchain.com/langsmith/custom-middleware",
"how-tos/http/custom_routes.md": "https://docs.langchain.com/langsmith/custom-routes",
"cloud/concepts/data_storage_and_privacy.md": "https://docs.langchain.com/langsmith/data-storage-and-privacy",
"cloud/deployment/semantic_search.md": "https://docs.langchain.com/langsmith/semantic-search",
"how-tos/ttl/configure_ttl.md": "https://docs.langchain.com/langsmith/configure-ttl",
"concepts/deployment_options.md": "https://docs.langchain.com/langsmith/platform-setup",
"cloud/quick_start.md": "https://docs.langchain.com/langsmith/deployment-quickstart",
"cloud/deployment/setup.md": "https://docs.langchain.com/langsmith/setup-app-requirements-txt",
"cloud/deployment/setup_pyproject.md": "https://docs.langchain.com/langsmith/setup-pyproject",
"cloud/deployment/setup_javascript.md": "https://docs.langchain.com/langsmith/setup-javascript",
"cloud/deployment/custom_docker.md": "https://docs.langchain.com/langsmith/custom-docker",
"cloud/deployment/graph_rebuild.md": "https://docs.langchain.com/langsmith/graph-rebuild",
"concepts/langgraph_cloud.md": "https://docs.langchain.com/langsmith/cloud",
"concepts/langgraph_self_hosted_data_plane.md": "https://docs.langchain.com/langsmith/hybrid",
"concepts/langgraph_self_hosted_control_plane.md": "https://docs.langchain.com/langsmith/self-hosted",
"concepts/langgraph_standalone_container.md": "https://docs.langchain.com/langsmith/self-hosted#standalone-server",
"cloud/deployment/cloud.md": "https://docs.langchain.com/langsmith/cloud",
"cloud/deployment/self_hosted_data_plane.md": "https://docs.langchain.com/langsmith/deploy-hybrid",
"cloud/deployment/self_hosted_control_plane.md": "https://docs.langchain.com/langsmith/deploy-self-hosted-full-platform",
"cloud/deployment/standalone_container.md": "https://docs.langchain.com/langsmith/deploy-standalone-server",
"concepts/server-mcp.md": "https://docs.langchain.com/langsmith/server-mcp",
"cloud/how-tos/human_in_the_loop_time_travel.md": "https://docs.langchain.com/langsmith/human-in-the-loop-time-travel",
"cloud/how-tos/add-human-in-the-loop.md": "https://docs.langchain.com/langsmith/add-human-in-the-loop",
"cloud/deployment/egress.md": "https://docs.langchain.com/langsmith/env-var",
"cloud/how-tos/streaming.md": "https://docs.langchain.com/langsmith/streaming",
"cloud/reference/api/api_ref.md": "https://docs.langchain.com/langsmith/server-api-ref",
"cloud/reference/langgraph_server_changelog.md": "https://docs.langchain.com/langsmith/agent-server-changelog",
"cloud/reference/api/api_ref_control_plane.md": "https://docs.langchain.com/langsmith/api-ref-control-plane",
"cloud/reference/cli.md": "https://docs.langchain.com/langsmith/cli",
"cloud/reference/env_var.md": "https://docs.langchain.com/langsmith/env-var",
"troubleshooting/studio.md": "https://docs.langchain.com/langsmith/troubleshooting-studio",
# LangGraph mintlify migration redirects
"index.md": "https://docs.langchain.com/oss/python/langgraph/overview",
"agents/agents.md": "https://docs.langchain.com/oss/python/langchain/agents",
"concepts/why-langgraph.md": "https://docs.langchain.com/oss/python/langgraph/overview",
"tutorials/get-started/1-build-basic-chatbot.md": "https://docs.langchain.com/oss/python/langgraph/quickstart",
"tutorials/get-started/2-add-tools.md": "https://docs.langchain.com/oss/python/langgraph/quickstart",
"tutorials/get-started/3-add-memory.md": "https://docs.langchain.com/oss/python/langgraph/quickstart",
"tutorials/get-started/4-human-in-the-loop.md": "https://docs.langchain.com/oss/python/langgraph/quickstart",
"tutorials/get-started/5-customize-state.md": "https://docs.langchain.com/oss/python/langgraph/quickstart",
"tutorials/get-started/6-time-travel.md": "https://docs.langchain.com/oss/python/langgraph/quickstart",
"tutorials/langsmith/local-server.md": "https://docs.langchain.com/oss/python/langgraph/local-server",
"tutorials/workflows.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
"tutorials/plan-and-execute/plan-and-execute.ipynb": "https://docs.langchain.com/oss/python/langchain/middleware/built-in#to-do-list",
"tutorials/langgraph-platform/local-server/local-server.md": "https://docs.langchain.com/langsmith/local-server",
"concepts/agentic_concepts.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
"guides/index.md": "https://docs.langchain.com/oss/python/langchain/overview",
"agents/overview.md": "https://docs.langchain.com/oss/python/langchain/agents",
"agents/run_agents.md": "https://docs.langchain.com/oss/python/langgraph/quickstart",
"concepts/low_level.md": "https://docs.langchain.com/oss/python/langgraph/graph-api",
"how-tos/graph-api.md": "https://docs.langchain.com/oss/python/langgraph/graph-api",
"how-tos/react-agent-from-scratch.ipynb": "https://docs.langchain.com/oss/python/langchain/quickstart",
"concepts/functional_api.md": "https://docs.langchain.com/oss/python/langgraph/functional-api",
"how-tos/use-functional-api.md": "https://docs.langchain.com/oss/python/langgraph/functional-api",
"concepts/pregel.md": "https://docs.langchain.com/oss/python/langgraph/pregel",
"concepts/streaming.md": "https://docs.langchain.com/oss/python/langgraph/streaming",
"how-tos/streaming.md": "https://docs.langchain.com/oss/python/langgraph/streaming",
"concepts/persistence.md": "https://docs.langchain.com/oss/python/langgraph/persistence",
"concepts/durable_execution.md": "https://docs.langchain.com/oss/python/langgraph/durable-execution",
"concepts/memory.md": "https://docs.langchain.com/oss/python/langgraph/memory",
"how-tos/memory/add-memory.md": "https://docs.langchain.com/oss/python/langgraph/add-memory",
"agents/context.md": "https://docs.langchain.com/oss/python/langgraph/add-memory",
"agents/models.md": "https://docs.langchain.com/oss/python/langgraph/overview",
"concepts/tools.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
"how-tos/tool-calling.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
"concepts/human_in_the_loop.md": "https://docs.langchain.com/oss/python/langgraph/interrupts",
"how-tos/human_in_the_loop/add-human-in-the-loop.md": "https://docs.langchain.com/oss/python/langgraph/interrupts",
"concepts/time-travel.md": "https://docs.langchain.com/oss/python/langgraph/persistence",
"how-tos/human_in_the_loop/time-travel.md": "https://docs.langchain.com/oss/python/langgraph/use-time-travel",
"concepts/subgraphs.md": "https://docs.langchain.com/oss/python/langgraph/use-subgraphs",
"how-tos/subgraph.md": "https://docs.langchain.com/oss/python/langgraph/use-subgraphs",
"concepts/multi_agent.md": "https://docs.langchain.com/oss/python/langgraph/graph-api",
"agents/multi-agent.md": "https://docs.langchain.com/oss/python/langchain/multi-agent",
"how-tos/multi_agent.md": "https://docs.langchain.com/oss/python/langgraph/graph-api",
"concepts/mcp.md": "https://docs.langchain.com/oss/python/langgraph/overview",
"agents/mcp.md": "https://docs.langchain.com/oss/python/langgraph/overview",
"concepts/tracing.md": "https://docs.langchain.com/oss/python/langgraph/observability",
"how-tos/enable-tracing.md": "https://docs.langchain.com/oss/python/langgraph/observability",
"agents/evals.md": "https://docs.langchain.com/oss/python/langgraph/overview",
"examples/index.md": "https://docs.langchain.com/oss/python/langgraph/case-studies",
"concepts/template_applications.md": "https://docs.langchain.com/oss/python/langgraph/overview",
"tutorials/rag/langgraph_agentic_rag.md": "https://docs.langchain.com/oss/python/langgraph/agentic-rag",
"tutorials/multi_agent/agent_supervisor.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
"tutorials/sql/sql-agent.md": "https://docs.langchain.com/oss/python/langgraph/sql-agent",
"agents/ui.md": "https://docs.langchain.com/oss/python/langgraph/ui",
"how-tos/run-id-langsmith.md": "https://docs.langchain.com/oss/python/langgraph/observability",
"troubleshooting/errors/index.md": "https://docs.langchain.com/oss/python/langgraph/common-errors",
"troubleshooting/errors/INVALID_CHAT_HISTORY.md": "https://docs.langchain.com/oss/python/langgraph/INVALID_CHAT_HISTORY",
"troubleshooting/errors/INVALID_LICENSE.md": "https://docs.langchain.com/oss/python/langgraph/common-errors",
"adopters.md": "https://docs.langchain.com/oss/python/langgraph/case-studies",
"concepts/faq.md": "https://docs.langchain.com/oss/python/langgraph/overview",
"agents/prebuilt.md": "https://docs.langchain.com/oss/python/langchain/agents",
"reference/index.md": "https://reference.langchain.com/python/langgraph/",
"reference/graphs.md": "https://reference.langchain.com/python/langgraph/graphs/",
"reference/func.md": "https://reference.langchain.com/python/langgraph/func/",
"reference/pregel.md": "https://reference.langchain.com/python/langgraph/pregel/",
"reference/checkpoints.md": "https://reference.langchain.com/python/langgraph/checkpoints/",
"reference/store.md": "https://reference.langchain.com/python/langgraph/store/",
"reference/cache.md": "https://reference.langchain.com/python/langgraph/cache/",
"reference/types.md": "https://reference.langchain.com/python/langgraph/types/",
"reference/runtime.md": "https://reference.langchain.com/python/langgraph/runtime/",
"reference/config.md": "https://reference.langchain.com/python/langgraph/config/",
"reference/errors.md": "https://reference.langchain.com/python/langgraph/errors/",
"reference/constants.md": "https://reference.langchain.com/python/langgraph/constants/",
"reference/channels.md": "https://reference.langchain.com/python/langgraph/channels/",
"reference/agents.md": "https://reference.langchain.com/python/langgraph/agents/",
"reference/supervisor.md": "https://reference.langchain.com/python/langgraph/supervisor/",
"reference/swarm.md": "https://reference.langchain.com/python/langgraph/swarm/",
"reference/mcp.md": "https://reference.langchain.com/python/langgraph/mcp/",
"cloud/reference/sdk/python_sdk_ref.md": "https://reference.langchain.com/python/langsmith/deployment/sdk/",
"reference/remote_graph.md": "https://reference.langchain.com/python/langsmith/deployment/remote_graph/",
# additional exclude-search entries from mkdocs.yml
"additional-resources/index.md": "https://docs.langchain.com/oss/python/langchain/overview",
"cloud/concepts/cron_jobs.md": "https://docs.langchain.com/langsmith/cron-jobs",
"cloud/concepts/data_storage_and_privacy.md": "https://docs.langchain.com/langsmith/data-storage-and-privacy",
"cloud/concepts/webhooks.md": "https://docs.langchain.com/langsmith/use-webhooks",
"cloud/deployment/cloud.md": "https://docs.langchain.com/langsmith/cloud",
"cloud/deployment/custom_docker.md": "https://docs.langchain.com/langsmith/custom-docker",
"cloud/deployment/egress.md": "https://docs.langchain.com/langsmith/env-var",
"cloud/deployment/graph_rebuild.md": "https://docs.langchain.com/langsmith/graph-rebuild",
"cloud/deployment/self_hosted_control_plane.md": "https://docs.langchain.com/langsmith/platform-setup",
"cloud/deployment/self_hosted_data_plane.md": "https://docs.langchain.com/langsmith/platform-setup",
"cloud/deployment/semantic_search.md": "https://docs.langchain.com/langsmith/semantic-search",
"cloud/deployment/setup_javascript.md": "https://docs.langchain.com/langsmith/setup-javascript",
"cloud/deployment/setup_pyproject.md": "https://docs.langchain.com/langsmith/setup-pyproject",
"cloud/deployment/setup.md": "https://docs.langchain.com/langsmith/setup-app-requirements-txt",
"cloud/deployment/standalone_container.md": "https://docs.langchain.com/langsmith/docker",
"cloud/how-tos/add-human-in-the-loop.md": "https://docs.langchain.com/langsmith/add-human-in-the-loop",
"cloud/how-tos/background_run.md": "https://docs.langchain.com/langsmith/background-run",
"cloud/how-tos/clone_traces_studio.md": "https://docs.langchain.com/langsmith/observability",
"cloud/how-tos/configurable_headers.md": "https://docs.langchain.com/langsmith/configurable-headers",
"cloud/how-tos/configuration_cloud.md": "https://docs.langchain.com/langsmith/configuration-cloud",
"cloud/how-tos/cron_jobs.md": "https://docs.langchain.com/langsmith/cron-jobs",
"cloud/how-tos/datasets_studio.md": "https://docs.langchain.com/langsmith/use-studio",
"cloud/how-tos/enqueue_concurrent.md": "https://docs.langchain.com/langsmith/enqueue-concurrent",
"cloud/how-tos/generative_ui_react.md": "https://docs.langchain.com/langsmith/generative-ui-react",
"cloud/how-tos/human_in_the_loop_time_travel.md": "https://docs.langchain.com/langsmith/human-in-the-loop-time-travel",
"cloud/how-tos/interrupt_concurrent.md": "https://docs.langchain.com/langsmith/interrupt-concurrent",
"cloud/how-tos/invoke_studio.md": "https://docs.langchain.com/langsmith/use-studio",
"cloud/how-tos/iterate_graph_studio.md": "https://docs.langchain.com/langsmith/use-studio",
"cloud/how-tos/reject_concurrent.md": "https://docs.langchain.com/langsmith/reject-concurrent",
"cloud/how-tos/rollback_concurrent.md": "https://docs.langchain.com/langsmith/rollback-concurrent",
"cloud/how-tos/same-thread.md": "https://docs.langchain.com/langsmith/same-thread",
"cloud/how-tos/stateless_runs.md": "https://docs.langchain.com/langsmith/stateless-runs",
"cloud/how-tos/streaming.md": "https://docs.langchain.com/langsmith/streaming",
"cloud/how-tos/studio/manage_assistants.md": "https://docs.langchain.com/langsmith/use-studio",
"cloud/how-tos/studio/quick_start.md": "https://docs.langchain.com/langsmith/quick-start-studio",
"cloud/how-tos/studio/run_evals.md": "https://docs.langchain.com/langsmith/observability",
"cloud/how-tos/threads_studio.md": "https://docs.langchain.com/langsmith/use-threads",
"cloud/how-tos/use_stream_react.md": "https://docs.langchain.com/langsmith/use-stream-react",
"cloud/how-tos/use_threads.md": "https://docs.langchain.com/langsmith/use-threads",
"cloud/how-tos/webhooks.md": "https://docs.langchain.com/langsmith/use-webhooks",
"cloud/quick_start.md": "https://docs.langchain.com/langsmith/deployment-quickstart",
"cloud/reference/api/api_ref_control_plane.md": "https://docs.langchain.com/langsmith/api-ref-control-plane",
"cloud/reference/api/api_ref.md": "https://docs.langchain.com/langsmith/server-api-ref",
"cloud/reference/cli.md": "https://docs.langchain.com/langsmith/cli",
"cloud/reference/env_var.md": "https://docs.langchain.com/langsmith/env-var",
"cloud/reference/langgraph_server_changelog.md": "https://docs.langchain.com/langsmith/agent-server-changelog",
"cloud/reference/sdk/js_ts_sdk_ref.md": "https://reference.langchain.com/javascript/modules/langsmith.html",
"concepts/application_structure.md": "https://docs.langchain.com/langsmith/application-structure",
"concepts/assistants.md": "https://docs.langchain.com/langsmith/assistants",
"concepts/auth.md": "https://docs.langchain.com/langsmith/auth",
"concepts/deployment_options.md": "https://docs.langchain.com/langsmith/deployments",
"concepts/double_texting.md": "https://docs.langchain.com/langsmith/double-texting",
"concepts/faq.md": "https://docs.langchain.com/langsmith/faq",
"concepts/langgraph_cli.md": "https://docs.langchain.com/langsmith/cli",
"concepts/langgraph_cloud.md": "https://docs.langchain.com/langsmith/cloud",
"concepts/langgraph_components.md": "https://docs.langchain.com/langsmith/components",
"concepts/langgraph_control_plane.md": "https://docs.langchain.com/langsmith/control-plane",
"concepts/langgraph_data_plane.md": "https://docs.langchain.com/langsmith/data-plane",
"concepts/langgraph_platform.md": "https://docs.langchain.com/langsmith/home",
"concepts/langgraph_self_hosted_control_plane.md": "https://docs.langchain.com/langsmith/platform-setup",
"concepts/langgraph_self_hosted_data_plane.md": "https://docs.langchain.com/langsmith/platform-setup",
"concepts/langgraph_server.md": "https://docs.langchain.com/langsmith/agent-server",
"concepts/langgraph_standalone_container.md": "https://docs.langchain.com/langsmith/docker",
"concepts/langgraph_studio.md": "https://docs.langchain.com/langsmith/studio",
"concepts/plans.md": "https://docs.langchain.com/langsmith/home",
"concepts/scalability_and_resilience.md": "https://docs.langchain.com/langsmith/scalability-and-resilience",
"concepts/sdk.md": "https://docs.langchain.com/langsmith/sdk",
"concepts/server-mcp.md": "https://docs.langchain.com/langsmith/server-mcp",
"concepts/template_applications.md": "https://docs.langchain.com/oss/python/langgraph/overview",
"concepts/why-langgraph.md": "https://docs.langchain.com/oss/python/langgraph/overview",
"examples/index.md": "https://docs.langchain.com/oss/python/langgraph/case-studies",
"guides/index.md": "https://docs.langchain.com/oss/python/langchain/overview",
"how-tos/auth/custom_auth.md": "https://docs.langchain.com/langsmith/custom-auth",
"how-tos/auth/openapi_security.md": "https://docs.langchain.com/langsmith/openapi-security",
"how-tos/autogen-integration.md": "https://docs.langchain.com/langsmith/autogen-integration",
"how-tos/http/custom_lifespan.md": "https://docs.langchain.com/langsmith/custom-lifespan",
"how-tos/http/custom_middleware.md": "https://docs.langchain.com/langsmith/custom-middleware",
"how-tos/http/custom_routes.md": "https://docs.langchain.com/langsmith/custom-routes",
"how-tos/ttl/configure_ttl.md": "https://docs.langchain.com/langsmith/configure-ttl",
"how-tos/use-remote-graph.md": "https://docs.langchain.com/langsmith/use-remote-graph",
"index.md": "https://docs.langchain.com/oss/python/langgraph/overview",
"snippets/chat_model_tabs.md": "https://docs.langchain.com/oss/python/langchain/overview",
"troubleshooting/errors/GRAPH_RECURSION_LIMIT.md": "https://docs.langchain.com/oss/python/langgraph/GRAPH_RECURSION_LIMIT",
"troubleshooting/errors/index.md": "https://docs.langchain.com/oss/python/langgraph/common-errors",
"troubleshooting/errors/INVALID_CHAT_HISTORY.md": "https://docs.langchain.com/oss/python/langgraph/INVALID_CHAT_HISTORY",
"troubleshooting/errors/INVALID_CONCURRENT_GRAPH_UPDATE.md": "https://docs.langchain.com/oss/python/langgraph/INVALID_CONCURRENT_GRAPH_UPDATE",
"troubleshooting/errors/INVALID_GRAPH_NODE_RETURN_VALUE.md": "https://docs.langchain.com/oss/python/langgraph/INVALID_GRAPH_NODE_RETURN_VALUE",
"troubleshooting/errors/INVALID_LICENSE.md": "https://docs.langchain.com/oss/python/langgraph/common-errors",
"troubleshooting/errors/MULTIPLE_SUBGRAPHS.md": "https://docs.langchain.com/oss/python/langgraph/MULTIPLE_SUBGRAPHS",
"troubleshooting/studio.md": "https://docs.langchain.com/langsmith/troubleshooting-studio",
"tutorials/auth/add_auth_server.md": "https://docs.langchain.com/langsmith/add-auth-server",
"tutorials/auth/getting_started.md": "https://docs.langchain.com/langsmith/auth",
"tutorials/auth/resource_auth.md": "https://docs.langchain.com/langsmith/resource-auth",
"agents/agents.md": "https://docs.langchain.com/oss/python/langchain/agents",
"concepts/why-langgraph.md": "https://docs.langchain.com/oss/python/langgraph/overview",
"tutorials/langsmith/local-server.md": "https://docs.langchain.com/oss/python/langgraph/local-server",
"tutorials/workflows.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
"concepts/agentic_concepts.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
"guides/index.md": "https://docs.langchain.com/oss/python/langchain/overview",
"agents/overview.md": "https://docs.langchain.com/oss/python/langchain/agents",
"concepts/agentic_concepts.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
"agents/run_agents.md": "https://docs.langchain.com/oss/python/langgraph/quickstart",
"concepts/low_level.md": "https://docs.langchain.com/oss/python/langgraph/graph-api",
"how-tos/graph-api.md": "https://docs.langchain.com/oss/python/langgraph/graph-api",
"concepts/functional_api.md": "https://docs.langchain.com/oss/python/langgraph/functional-api",
"how-tos/use-functional-api.md": "https://docs.langchain.com/oss/python/langgraph/functional-api",
"concepts/pregel.md": "https://docs.langchain.com/oss/python/langgraph/pregel",
"concepts/streaming.md": "https://docs.langchain.com/oss/python/langgraph/streaming",
"how-tos/streaming.md": "https://docs.langchain.com/oss/python/langgraph/streaming",
"concepts/persistence.md": "https://docs.langchain.com/oss/python/langgraph/persistence",
"concepts/durable_execution.md": "https://docs.langchain.com/oss/python/langgraph/durable-execution",
"concepts/memory.md": "https://docs.langchain.com/oss/python/langgraph/memory",
"how-tos/memory/add-memory.md": "https://docs.langchain.com/oss/python/langgraph/add-memory",
"agents/context.md": "https://docs.langchain.com/oss/python/langgraph/add-memory",
"agents/models.md": "https://docs.langchain.com/oss/python/langgraph/overview",
"concepts/tools.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
"how-tos/tool-calling.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
"concepts/human_in_the_loop.md": "https://docs.langchain.com/oss/python/langgraph/interrupts",
"how-tos/human_in_the_loop/add-human-in-the-loop.md": "https://docs.langchain.com/oss/python/langgraph/interrupts",
"concepts/time-travel.md": "https://docs.langchain.com/oss/python/langgraph/persistence",
"how-tos/human_in_the_loop/time-travel.md": "https://docs.langchain.com/oss/python/langgraph/use-time-travel",
"concepts/subgraphs.md": "https://docs.langchain.com/oss/python/langgraph/use-subgraphs",
"how-tos/subgraph.md": "https://docs.langchain.com/oss/python/langgraph/use-subgraphs",
"concepts/multi_agent.md": "https://docs.langchain.com/oss/python/langgraph/graph-api",
"agents/multi-agent.md": "https://docs.langchain.com/oss/python/langchain/multi-agent",
"how-tos/multi_agent.md": "https://docs.langchain.com/oss/python/langgraph/graph-api",
"concepts/mcp.md": "https://docs.langchain.com/oss/python/langgraph/overview",
"agents/mcp.md": "https://docs.langchain.com/oss/python/langgraph/overview",
"concepts/tracing.md": "https://docs.langchain.com/oss/python/langgraph/observability",
"how-tos/enable-tracing.md": "https://docs.langchain.com/oss/python/langgraph/observability",
"agents/evals.md": "https://docs.langchain.com/oss/python/langgraph/overview",
"examples/index.md": "https://docs.langchain.com/oss/python/langgraph/case-studies",
"concepts/template_applications.md": "https://docs.langchain.com/oss/python/langgraph/overview",
"tutorials/rag/langgraph_agentic_rag.md": "https://docs.langchain.com/oss/python/langgraph/agentic-rag",
"tutorials/multi_agent/agent_supervisor.md": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
"tutorials/sql/sql-agent.md": "https://docs.langchain.com/oss/python/langgraph/sql-agent",
"agents/ui.md": "https://docs.langchain.com/oss/python/langgraph/ui",
"how-tos/run-id-langsmith.md": "https://docs.langchain.com/oss/python/langgraph/observability",
"troubleshooting/errors/index.md": "https://docs.langchain.com/oss/python/langgraph/common-errors",
"troubleshooting/errors/GRAPH_RECURSION_LIMIT.md": "https://docs.langchain.com/oss/python/langgraph/GRAPH_RECURSION_LIMIT",
"troubleshooting/errors/INVALID_CONCURRENT_GRAPH_UPDATE.md": "https://docs.langchain.com/oss/python/langgraph/INVALID_CONCURRENT_GRAPH_UPDATE",
"troubleshooting/errors/INVALID_GRAPH_NODE_RETURN_VALUE.md": "https://docs.langchain.com/oss/python/langgraph/INVALID_GRAPH_NODE_RETURN_VALUE",
"troubleshooting/errors/MULTIPLE_SUBGRAPHS.md": "https://docs.langchain.com/oss/python/langgraph/MULTIPLE_SUBGRAPHS",
"troubleshooting/errors/INVALID_CHAT_HISTORY.md": "https://docs.langchain.com/oss/python/langgraph/INVALID_CHAT_HISTORY",
"troubleshooting/errors/INVALID_LICENSE.md": "https://docs.langchain.com/oss/python/langgraph/common-errors",
"adopters.md": "https://docs.langchain.com/oss/python/langgraph/case-studies",
"concepts/faq.md": "https://docs.langchain.com/oss/python/langgraph/overview",
"agents/prebuilt.md": "https://docs.langchain.com/oss/python/langchain/agents",
"tutorials/auth/getting_started.md": "https://docs.langchain.com/langgraph-platform/auth",
"tutorials/auth/resource_auth.md": "https://docs.langchain.com/langgraph-platform/resource-auth",
"tutorials/auth/add_auth_server.md": "https://docs.langchain.com/langgraph-platform/add-auth-server",
"how-tos/use-remote-graph.md": "https://docs.langchain.com/langgraph-platform/use-remote-graph",
"how-tos/autogen-integration.md": "https://docs.langchain.com/langgraph-platform/autogen-integration",
"cloud/how-tos/use_stream_react.md": "https://docs.langchain.com/langgraph-platform/use-stream-react",
"cloud/how-tos/generative_ui_react.md": "https://docs.langchain.com/langgraph-platform/generative-ui-react",
"concepts/langgraph_platform.md": "https://docs.langchain.com/langgraph-platform/index",
"concepts/langgraph_components.md": "https://docs.langchain.com/langgraph-platform/components",
"concepts/langgraph_server.md": "https://docs.langchain.com/langgraph-platform/langgraph-server",
"concepts/langgraph_data_plane.md": "https://docs.langchain.com/langgraph-platform/data-plane",
"concepts/langgraph_control_plane.md": "https://docs.langchain.com/langgraph-platform/control-plane",
"concepts/langgraph_cli.md": "https://docs.langchain.com/langgraph-platform/langgraph-cli",
"concepts/langgraph_studio.md": "https://docs.langchain.com/langgraph-platform/langgraph-studio",
"cloud/how-tos/studio/quick_start.md": "https://docs.langchain.com/langgraph-platform/quick-start-studio",
"cloud/how-tos/invoke_studio.md": "https://docs.langchain.com/langgraph-platform/invoke-studio",
"cloud/how-tos/studio/manage_assistants.md": "https://docs.langchain.com/langgraph-platform/manage-assistants-studio",
"cloud/how-tos/threads_studio.md": "https://docs.langchain.com/langgraph-platform/threads-studio",
"cloud/how-tos/iterate_graph_studio.md": "https://docs.langchain.com/langgraph-platform/iterate-graph-studio",
"cloud/how-tos/studio/run_evals.md": "https://docs.langchain.com/langgraph-platform/run-evals-studio",
"cloud/how-tos/clone_traces_studio.md": "https://docs.langchain.com/langgraph-platform/clone-traces-studio",
"cloud/how-tos/datasets_studio.md": "https://docs.langchain.com/langgraph-platform/datasets-studio",
"concepts/sdk.md": "https://docs.langchain.com/langgraph-platform/sdk",
"concepts/plans.md": "https://docs.langchain.com/langgraph-platform/plans",
"concepts/application_structure.md": "https://docs.langchain.com/langgraph-platform/application-structure",
"concepts/scalability_and_resilience.md": "https://docs.langchain.com/langgraph-platform/scalability-and-resilience",
"concepts/auth.md": "https://docs.langchain.com/langgraph-platform/auth",
"how-tos/auth/custom_auth.md": "https://docs.langchain.com/langgraph-platform/custom-auth",
"how-tos/auth/openapi_security.md": "https://docs.langchain.com/langgraph-platform/openapi-security",
"concepts/assistants.md": "https://docs.langchain.com/langgraph-platform/assistants",
"cloud/how-tos/configuration_cloud.md": "https://docs.langchain.com/langgraph-platform/configuration-cloud",
"cloud/how-tos/use_threads.md": "https://docs.langchain.com/langgraph-platform/use-threads",
"cloud/how-tos/background_run.md": "https://docs.langchain.com/langgraph-platform/background-run",
"cloud/how-tos/same-thread.md": "https://docs.langchain.com/langgraph-platform/same-thread",
"cloud/how-tos/stateless_runs.md": "https://docs.langchain.com/langgraph-platform/stateless-runs",
"cloud/how-tos/configurable_headers.md": "https://docs.langchain.com/langgraph-platform/configurable-headers",
"concepts/double_texting.md": "https://docs.langchain.com/langgraph-platform/double-texting",
"cloud/how-tos/interrupt_concurrent.md": "https://docs.langchain.com/langgraph-platform/interrupt-concurrent",
"cloud/how-tos/rollback_concurrent.md": "https://docs.langchain.com/langgraph-platform/rollback-concurrent",
"cloud/how-tos/reject_concurrent.md": "https://docs.langchain.com/langgraph-platform/reject-concurrent",
"cloud/how-tos/enqueue_concurrent.md": "https://docs.langchain.com/langgraph-platform/enqueue-concurrent",
"cloud/concepts/webhooks.md": "https://docs.langchain.com/langgraph-platform/use-webhooks",
"cloud/how-tos/webhooks.md": "https://docs.langchain.com/langgraph-platform/use-webhooks",
"cloud/concepts/cron_jobs.md": "https://docs.langchain.com/langgraph-platform/cron-jobs",
"cloud/how-tos/cron_jobs.md": "https://docs.langchain.com/langgraph-platform/cron-jobs",
"how-tos/http/custom_lifespan.md": "https://docs.langchain.com/langgraph-platform/custom-lifespan",
"how-tos/http/custom_middleware.md": "https://docs.langchain.com/langgraph-platform/custom-middleware",
"how-tos/http/custom_routes.md": "https://docs.langchain.com/langgraph-platform/custom-routes",
"cloud/concepts/data_storage_and_privacy.md": "https://docs.langchain.com/langgraph-platform/data-storage-and-privacy",
"cloud/deployment/semantic_search.md": "https://docs.langchain.com/langgraph-platform/semantic-search",
"how-tos/ttl/configure_ttl.md": "https://docs.langchain.com/langgraph-platform/configure-ttl",
"concepts/deployment_options.md": "https://docs.langchain.com/langgraph-platform/deployment-options",
"cloud/quick_start.md": "https://docs.langchain.com/langgraph-platform/deployment-quickstart",
"cloud/deployment/setup.md": "https://docs.langchain.com/langgraph-platform/setup-app-requirements-txt",
"cloud/deployment/setup_pyproject.md": "https://docs.langchain.com/langgraph-platform/setup-pyproject",
"cloud/deployment/setup_javascript.md": "https://docs.langchain.com/langgraph-platform/setup-javascript",
"cloud/deployment/custom_docker.md": "https://docs.langchain.com/langgraph-platform/custom-docker",
"cloud/deployment/graph_rebuild.md": "https://docs.langchain.com/langgraph-platform/graph-rebuild",
"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",
"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",
"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",
"cloud/deployment/egress.md": "https://docs.langchain.com/langgraph-platform/env-var",
"cloud/how-tos/streaming.md": "https://docs.langchain.com/langgraph-platform/streaming",
"cloud/reference/api/api_ref.md": "https://docs.langchain.com/langgraph-platform/server-api-ref",
"cloud/reference/langgraph_server_changelog.md": "https://docs.langchain.com/langgraph-platform/langgraph-server-changelog",
"cloud/reference/api/api_ref_control_plane.md": "https://docs.langchain.com/langgraph-platform/api-ref-control-plane",
"cloud/reference/cli.md": "https://docs.langchain.com/langgraph-platform/cli",
"cloud/reference/env_var.md": "https://docs.langchain.com/langgraph-platform/env-var",
"troubleshooting/studio.md": "https://docs.langchain.com/langgraph-platform/troubleshooting-studio",
}
@@ -805,27 +560,10 @@ def on_post_page(html: str, page: Page, config: MkDocsConfig) -> str:
# Create HTML files for redirects after site dir has been built
def on_post_build(config):
use_directory_urls = config.get("use_directory_urls")
site_dir = config["site_dir"]
# Track which paths have explicit redirects
redirected_paths = set()
# Collect all existing HTML files in the site
all_html_files = set()
for root, dirs, files in os.walk(site_dir):
for file in files:
if file.endswith(".html"):
# Get relative path from site_dir
html_path = os.path.relpath(os.path.join(root, file), site_dir)
# Normalize path separators to forward slashes
html_path = html_path.replace(os.sep, "/")
all_html_files.add(html_path)
# Process explicit redirects from REDIRECT_MAP
for page_old, page_new in REDIRECT_MAP.items():
# Convert .ipynb to .md for path calculation
page_old = page_old.replace(".ipynb", ".md")
# Calculate the HTML path for the old page (whether it exists or not)
if use_directory_urls:
# With directory URLs: /path/to/page/ becomes /path/to/page/index.html
@@ -839,18 +577,15 @@ def on_post_build(config):
old_html_path = page_old[:-3] + ".html"
else:
old_html_path = page_old + ".html"
# Track this path as redirected
redirected_paths.add(old_html_path)
if isinstance(page_new, str) and page_new.startswith("http"):
# Handle external redirects
_write_html(site_dir, old_html_path, page_new)
_write_html(config["site_dir"], old_html_path, page_new)
else:
# Handle internal redirects
page_new = page_new.replace(".ipynb", ".md")
page_new_before_hash, hash, suffix = page_new.partition("#")
# Try to get the new path using File class, but fallback to manual calculation
try:
new_html_path = File(page_new_before_hash, "", "", True).url
@@ -872,64 +607,5 @@ def on_post_build(config):
else:
new_html_path = page_new_before_hash + ".html"
new_html_path += hash + suffix
_write_html(site_dir, old_html_path, new_html_path)
# Create catch-all redirects for any HTML files not explicitly redirected
catchall_url = "https://docs.langchain.com/oss/python/langgraph/overview"
for html_file in all_html_files:
# Skip if this file is already explicitly redirected
if html_file in redirected_paths:
continue
# Skip the root index.html (we handle that separately)
if html_file == "index.html":
continue
# Skip reference documentation (keep those accessible)
if html_file.startswith("reference/"):
continue
# Create redirect for this unmapped file
_write_html(site_dir, html_file, catchall_url)
# Create root index.html redirect
root_redirect_html = """<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8">
<title>Redirecting to LangGraph Documentation</title>
<link rel="canonical" href="https://docs.langchain.com/oss/python/langgraph/overview">
<meta name="robots" content="noindex">
<script>var anchor=window.location.hash.substr(1);location.href="https://docs.langchain.com/oss/python/langgraph/overview"+(anchor?"#"+anchor:"")</script>
<meta http-equiv="refresh" content="0; url=https://docs.langchain.com/oss/python/langgraph/overview">
</head>
<body>
<h1>Documentation has moved</h1>
<p>The LangGraph documentation has moved to <a href="https://docs.langchain.com/oss/python/langgraph/overview">docs.langchain.com</a>.</p>
<p>Redirecting you now...</p>
</body>
</html>
"""
root_index_path = os.path.join(site_dir, "index.html")
with open(root_index_path, "w", encoding="utf-8") as f:
f.write(root_redirect_html)
# Create server-side catch-all redirect file for Netlify/Cloudflare Pages
# This handles any pages not explicitly mapped in REDIRECT_MAP
# Note: This won't work on GitHub Pages, but kept for potential future use
redirects_content = """# Netlify/Cloudflare Pages redirect rules
# Specific redirects are handled by individual HTML redirect pages
# This is the catch-all for any unmapped pages
# Exclude reference docs from catch-all
/reference/* 200
# Catch-all: redirect any page not explicitly mapped
/* https://docs.langchain.com/oss/python/langgraph/overview 301
"""
redirects_path = os.path.join(site_dir, "_redirects")
with open(redirects_path, "w", encoding="utf-8") as f:
f.write(redirects_content)
_write_html(config["site_dir"], old_html_path, new_html_path)
@@ -20,19 +20,16 @@ class Package(TypedDict):
description: str
"""A brief description of what the package does."""
class ResolvedPackage(Package):
weekly_downloads: int | None
"""The weekly download count of the package."""
language: str
"""The language of the package. (either 'python' or 'js')"""
HERE = pathlib.Path(__file__).parent
PACKAGES_FILE = HERE / "packages.yml"
PACKAGES = yaml.safe_load(PACKAGES_FILE.read_text())["packages"]
def _get_pypi_downloads(package: Package) -> int:
"""Retrieve the weekly download count for a package from PyPIStats."""
@@ -75,8 +72,7 @@ def _get_pypi_downloads(package: Package) -> int:
return sum(entry["downloads"] for entry in sorted_data[:7])
else:
return None
def _get_npm_downloads(package: Package) -> int:
"""Retrieve the weekly download count for a package on the npm registry."""
@@ -86,18 +82,14 @@ def _get_npm_downloads(package: Package) -> int:
npm_response = requests.get(npm_url)
npm_response.raise_for_status()
except requests.exceptions.HTTPError:
raise AssertionError(
f"Package {package['name']} does not exist on npm registry"
)
raise AssertionError(f"Package {package['name']} does not exist on npm registry")
npm_data = npm_response.json()
# Retrieve the first publish date using the 'created' timestamp from the 'time' field.
created_str = npm_data.get("time", {}).get("created")
if created_str is None:
raise AssertionError(
f"Package {package['name']} has no creation time in registry data"
)
raise AssertionError(f"Package {package['name']} has no creation time in registry data")
# Remove the trailing 'Z' if present and parse the ISO format timestamp
first_publish_date = datetime.fromisoformat(created_str.rstrip("Z"))
@@ -111,10 +103,7 @@ def _get_npm_downloads(package: Package) -> int:
else:
return None
def _get_weekly_downloads(
packages: dict[str, list[Package]], fake: bool
) -> list[ResolvedPackage]:
def _get_weekly_downloads(packages: dict[str, list[Package]], fake: bool) -> list[ResolvedPackage]:
"""Retrieve the weekly download count for a dictionary of python or js packages."""
resolved_packages: list[ResolvedPackage] = []
@@ -142,7 +131,7 @@ def _get_weekly_downloads(
num_downloads = _get_npm_downloads(package)
else:
num_downloads = None
resolved_packages.append(
{
"name": package["name"],
@@ -156,13 +145,12 @@ def _get_weekly_downloads(
return resolved_packages
def main(output_file: str, fake: bool) -> None:
"""Main function to generate package download information.
Args:
output_file: Path to the output YAML file.
fake: If `True`, use fake download counts for testing purposes.
fake: If True, use fake download counts for testing purposes.
"""
resolved_packages: list[ResolvedPackage] = _get_weekly_downloads(PACKAGES, fake)
+2 -2
View File
@@ -33,7 +33,7 @@ LangGraph provides three ways to manage context, which combines the mutability a
**Static runtime context** represents immutable data like user metadata, tools, and database connections that are passed to an application at the start of a run via the `context` argument to `invoke`/`stream`. This data does not change during execution.
!!! version-added "Added in version 0.6.0: `context` replaces `config['configurable']`"
!!! version-added "New in LangGraph v0.6: `context` replaces `config['configurable']`"
Runtime context is now passed to the `context` argument of `invoke`/`stream`,
which replaces the previous pattern of passing application configuration to `config['configurable']`.
@@ -90,7 +90,7 @@ graph.invoke( # (1)!
from langgraph.runtime import Runtime
# highlight-next-line
def node(state: State, runtime: Runtime[ContextSchema]):
def node(state: State, config: Runtime[ContextSchema]):
user_name = runtime.context.user_name
...
```
+1 -5
View File
@@ -211,7 +211,7 @@ output = agent.invoke(
print(output["messages"][-1].text())
```
!!! version-added "Added in version 0.6.0"
!!! version-added "New in LangGraph v0.6"
:::
@@ -351,13 +351,11 @@ If your desired LLM isn't officially supported by LangChain, consider these opti
:::python
1. **Implement a custom LangChain chat model**: Create a model conforming to the [LangChain chat model interface](https://python.langchain.com/docs/how_to/custom_chat_model/). This enables full compatibility with LangGraph's agents and workflows but requires understanding of the LangChain framework.
:::
:::js
1. **Implement a custom LangChain chat model**: Create a model conforming to the [LangChain chat model interface](https://js.langchain.com/docs/how_to/custom_chat/). This enables full compatibility with LangGraph's agents and workflows but requires understanding of the LangChain framework.
:::
2. **Direct invocation with custom streaming**: Use your model directly by [adding custom streaming logic](../how-tos/streaming.md#use-with-any-llm) with `StreamWriter`.
@@ -373,7 +371,6 @@ If your desired LLM isn't officially supported by LangChain, consider these opti
- [Force model to call a specific tool](https://python.langchain.com/docs/how_to/tool_choice/)
- [All chat model how-to guides](https://python.langchain.com/docs/how_to/#chat-models)
- [Chat model integrations](https://python.langchain.com/docs/integrations/chat/)
:::
:::js
@@ -384,5 +381,4 @@ If your desired LLM isn't officially supported by LangChain, consider these opti
- [Force model to call a specific tool](https://js.langchain.com/docs/how_to/tool_choice/)
- [All chat model how-to guides](https://js.langchain.com/docs/how_to/#chat-models)
- [Chat model integrations](https://js.langchain.com/docs/integrations/chat/)
:::
+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
File diff suppressed because it is too large Load Diff
+3 -3
View File
@@ -483,19 +483,19 @@ The LangGraph CLI requires a JSON configuration file that follows this [schema](
RUN PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 pip install --no-cache-dir -c /api/constraints.txt langchain_community langchain_anthropic langchain_openai wikipedia scikit-learn
ADD ./graphs /deps/outer-graphs/src
ADD ./graphs /deps/__outer_graphs/src
RUN set -ex && \
for line in '[project]' \
'name = "graphs"' \
'version = "0.1"' \
'[tool.setuptools.package-data]' \
'"*" = ["**/*"]'; do \
echo "$line" >> /deps/outer-graphs/pyproject.toml; \
echo "$line" >> /deps/__outer_graphs/pyproject.toml; \
done
RUN PIP_CONFIG_FILE=/pipconfig.txt PYTHONDONTWRITEBYTECODE=1 pip install --no-cache-dir -c /api/constraints.txt -e /deps/*
ENV LANGSERVE_GRAPHS='{"agent": "/deps/outer-graphs/src/agent.py:graph", "storm": "/deps/outer-graphs/src/storm.py:graph"}'
ENV LANGSERVE_GRAPHS='{"agent": "/deps/__outer_graphs/src/agent.py:graph", "storm": "/deps/__outer_graphs/src/storm.py:graph"}'
```
???+ note "Updating your langgraph.json file"
+4 -14
View File
@@ -21,16 +21,12 @@ To leverage durable execution in LangGraph, you need to:
1. Enable [persistence](./persistence.md) in your workflow by specifying a [checkpointer](./persistence.md#checkpointer-libraries) that will save workflow progress.
2. Specify a [thread identifier](./persistence.md#threads) when executing a workflow. This will track the execution history for a particular instance of the workflow.
:::python
:::python
3. Wrap any non-deterministic operations (e.g., random number generation) or operations with side effects (e.g., file writes, API calls) inside @[tasks][task] to ensure that when a workflow is resumed, these operations are not repeated for the particular run, and instead their results are retrieved from the persistence layer. For more information, see [Determinism and Consistent Replay](#determinism-and-consistent-replay).
:::
:::js
:::js
3. Wrap any non-deterministic operations (e.g., random number generation) or operations with side effects (e.g., file writes, API calls) inside @[tasks][task] to ensure that when a workflow is resumed, these operations are not repeated for the particular run, and instead their results are retrieved from the persistence layer. For more information, see [Determinism and Consistent Replay](#determinism-and-consistent-replay).
:::
## Determinism and Consistent Replay
@@ -65,7 +61,7 @@ LangGraph supports three durability modes that allow you to balance performance
A higher durability mode add more overhead to the workflow execution.
!!! version-added "Added in version 0.6.0"
!!! version-added "Added in v0.6.0"
Use the `durability` parameter instead of `checkpoint_during` (deprecated in v0.6.0) for persistence policy management:
@@ -77,16 +73,14 @@ A higher durability mode add more overhead to the workflow execution.
* `checkpoint_during=True` -> `durability="async"`
* `checkpoint_during=False` -> `durability="exit"`
### `"exit"`
### `"exit"`
Changes are persisted only when graph execution completes (either successfully or with an error). This provides the best performance for long-running graphs but means intermediate state is not saved, so you cannot recover from mid-execution failures or interrupt the graph execution.
### `"async"`
Changes are persisted asynchronously while the next step executes. This provides good performance and durability, but there's a small risk that checkpoints might not be written if the process crashes during execution.
### `"sync"`
Changes are persisted synchronously before the next step starts. This ensures that every checkpoint is written before continuing execution, providing high durability at the cost of some performance overhead.
You can specify the durability mode when calling any graph execution method:
@@ -316,14 +310,12 @@ Once you have enabled durable execution in your workflow, you can resume executi
- **Pausing and Resuming Workflows:** Use the @[interrupt][interrupt] function to pause a workflow at specific points and the @[Command] primitive to resume it with updated state. See [**Human-in-the-Loop**](./human_in_the_loop.md) for more details.
- **Recovering from Failures:** Automatically resume workflows from the last successful checkpoint after an exception (e.g., LLM provider outage). This involves executing the workflow with the same thread identifier by providing it with a `None` as the input value (see this [example](../how-tos/use-functional-api.md#resuming-after-an-error) with the functional API).
:::
:::js
- **Pausing and Resuming Workflows:** Use the @[interrupt][interrupt] function to pause a workflow at specific points and the @[Command] primitive to resume it with updated state. See [**Human-in-the-Loop**](./human_in_the_loop.md) for more details.
- **Recovering from Failures:** Automatically resume workflows from the last successful checkpoint after an exception (e.g., LLM provider outage). This involves executing the workflow with the same thread identifier by providing it with a `null` as the input value (see this [example](../how-tos/use-functional-api.md#resuming-after-an-error) with the functional API).
:::
## Starting Points for Resuming Workflows
@@ -334,7 +326,6 @@ Once you have enabled durable execution in your workflow, you can resume executi
- If you're making a subgraph call inside a node, the starting point will be the **parent** node that called the subgraph that was halted.
Inside the subgraph, the starting point will be the specific [**node**](./low_level.md#nodes) where execution stopped.
- If you're using the Functional API, the starting point is the beginning of the [**entrypoint**](./functional_api.md#entrypoint) where execution stopped.
:::
:::js
@@ -343,5 +334,4 @@ Once you have enabled durable execution in your workflow, you can resume executi
- If you're making a subgraph call inside a node, the starting point will be the **parent** node that called the subgraph that was halted.
Inside the subgraph, the starting point will be the specific [**node**](./low_level.md#nodes) where execution stopped.
- If you're using the Functional API, the starting point is the beginning of the [**entrypoint**](./functional_api.md#entrypoint) where execution stopped.
:::
+1 -1
View File
@@ -1040,7 +1040,7 @@ def node_a(state: State, runtime: Runtime[ContextSchema]):
...
```
See [this guide](../how-tos/graph-api.md#add-runtime-configuration) for a full breakdown on configuration.
See [this guide](../how-tos/graph-api.ipynb#add-runtime-configuration) for a full breakdown on configuration.
:::
:::js
+2 -2
View File
@@ -134,7 +134,7 @@ def update_instructions(state: State, store: BaseStore):
namespace = ("instructions",)
current_instructions = store.search(namespace)[0]
# Memory logic
prompt = prompt_template.format(instructions=current_instructions.value["instructions"], conversation=state["messages"])
prompt = prompt_template.format(instructions=instructions.value["instructions"], conversation=state["messages"])
output = llm.invoke(prompt)
new_instructions = output['new_instructions']
store.put(("agent_instructions",), "agent_a", {"instructions": new_instructions})
@@ -278,4 +278,4 @@ const items = await store.search(
```
:::
For more information about the memory store, see the [Persistence](persistence.md#memory-store) guide.
For more information about the memory store, see the [Persistence](persistence.md#memory-store) guide.
+2 -2
View File
@@ -897,5 +897,5 @@ There are two high-level approaches to achieve that:
An agent might need to have a different state schema from the rest of the agents. For example, a search agent might only need to keep track of queries and retrieved documents. There are two ways to achieve this in LangGraph:
- Define [subgraph](./subgraphs.md) agents with a separate state schema. If there are no shared state keys (channels) between the subgraph and the parent graph, it's important to [add input / output transformations](../how-tos/subgraph.md#different-state-schemas) so that the parent graph knows how to communicate with the subgraphs.
- Define agent node functions with a [private input state schema](../how-tos/graph-api.md#pass-private-state-between-nodes) that is distinct from the overall graph state schema. This allows passing information that is only needed for executing that particular agent.
- Define [subgraph](./subgraphs.md) agents with a separate state schema. If there are no shared state keys (channels) between the subgraph and the parent graph, it's important to [add input / output transformations](../how-tos/subgraph.ipynb#different-state-schemas) so that the parent graph knows how to communicate with the subgraphs.
- Define agent node functions with a [private input state schema](../how-tos/graph-api.ipynb#pass-private-state-between-nodes) that is distinct from the overall graph state schema. This allows passing information that is only needed for executing that particular agent.
+14 -13
View File
@@ -1019,7 +1019,7 @@ console.log(await graph.invoke({}, { configurable: { myRuntimeValue: "b" } }));
# Usage
input_message = {"role": "user", "content": "hi"}
# With no configuration, uses default (Anthropic)
response_1 = graph.invoke({"messages": [input_message]}, context=ContextSchema())["messages"][-1]
response_1 = graph.invoke({"messages": [input_message]})["messages"][-1]
# Or, can set OpenAI
response_2 = graph.invoke({"messages": [input_message]}, context={"model_provider": "openai"})["messages"][-1]
@@ -1205,7 +1205,7 @@ There are many use cases where you may wish for your node to have a custom retry
To configure a retry policy, pass the `retry_policy` parameter to the [add_node](../reference/graphs.md#langgraph.graph.state.StateGraph.add_node). The `retry_policy` parameter takes in a `RetryPolicy` named tuple object. Below we instantiate a `RetryPolicy` object with the default parameters and associate it with a node:
```python
from langgraph.types import RetryPolicy
from langgraph.pregel import RetryPolicy
builder.add_node(
"node_name",
@@ -1260,7 +1260,7 @@ By default, the retry policy retries on any exception except for the following:
from typing_extensions import TypedDict
from langchain.chat_models import init_chat_model
from langgraph.graph import END, MessagesState, StateGraph, START
from langgraph.types import RetryPolicy
from langgraph.pregel import RetryPolicy
from langchain_community.utilities import SQLDatabase
from langchain_core.messages import AIMessage
@@ -1422,15 +1422,15 @@ const builder = new StateGraph(State)
:::
??? info "Why split application steps into a sequence with LangGraph?"
LangGraph makes it easy to add an underlying persistence layer to your application.
This allows state to be checkpointed in between the execution of nodes, so your LangGraph nodes govern:
LangGraph makes it easy to add an underlying persistence layer to your application.
This allows state to be checkpointed in between the execution of nodes, so your LangGraph nodes govern:
- How state updates are [checkpointed](../concepts/persistence.md)
- How interruptions are resumed in [human-in-the-loop](../concepts/human_in_the_loop.md) workflows
- How we can "rewind" and branch-off executions using LangGraph's [time travel](../concepts/time-travel.md) features
- How state updates are [checkpointed](../concepts/persistence.md)
- How interruptions are resumed in [human-in-the-loop](../concepts/human_in_the_loop.md) workflows
- How we can "rewind" and branch-off executions using LangGraph's [time travel](../concepts/time-travel.md) features
They also determine how execution steps are [streamed](../concepts/streaming.md), and how your application is visualized
and debugged using [LangGraph Studio](../concepts/langgraph_studio.md).
They also determine how execution steps are [streamed](../concepts/streaming.md), and how your application is visualized
and debugged using [LangGraph Studio](../concepts/langgraph_studio.md).
Let's demonstrate an end-to-end example. We will create a sequence of three steps:
@@ -2110,6 +2110,7 @@ builder.add_edge(START, "generate_topics")
builder.add_conditional_edges("generate_topics", continue_to_jokes, ["generate_joke"])
builder.add_edge("generate_joke", "best_joke")
builder.add_edge("best_joke", END)
builder.add_edge("generate_topics", END)
graph = builder.compile()
```
@@ -2332,7 +2333,7 @@ from IPython.display import Image, display
display(Image(graph.get_graph().draw_mermaid_png()))
```
![Simple loop graph](assets/graph_api_image_7.png)
![Simple loop graph](assets/graph_api_image_3.png)
:::
:::js
@@ -3271,7 +3272,7 @@ from langchain_core.runnables.graph import CurveStyle, MermaidDrawMethod, NodeSt
display(Image(app.get_graph().draw_mermaid_png()))
```
![Fractal graph visualization](assets/graph_api_image_10.png)
![Fractal graph visualization](assets/graph_api_image_5.png)
**Using Mermaid + Pyppeteer**
@@ -3319,4 +3320,4 @@ const imageBuffer = new Uint8Array(await image.arrayBuffer());
await fs.writeFile("graph.png", imageBuffer);
```
:::
:::
@@ -366,8 +366,8 @@ result = graph.invoke(
# Resume with mapping of interrupt IDs to values
resume_map = {
i.id: f"edited text for {i.value['text_to_revise']}"
for i in graph.get_state(config).interrupts
i.interrupt_id: f"human input for prompt {i.value}"
for i in parent.get_state(thread_config).interrupts
}
print(graph.invoke(Command(resume=resume_map), config=config))
# > {'text_1': 'edited text for original text 1', 'text_2': 'edited text for original text 2'}
+1 -1
View File
@@ -244,7 +244,7 @@ output = agent.invoke(
print(output["messages"][-1].text())
```
!!! version-added "Added in version 0.6.0"
!!! version-added "New in langgraph>=0.6"
:::
+1 -1
View File
@@ -2,4 +2,4 @@
::: langgraph.cache.base
::: langgraph.cache.memory
::: langgraph.cache.sqlite
::: langgraph.cache.sqlite
+1 -1
View File
@@ -68,7 +68,7 @@ The server will start and open the studio in your browser:
> - 📚 API Docs: http://127.0.0.1:2024/docs
>
> This in-memory server is designed for development and testing.
> For production use, please use LangSmith Deployment.
> For production use, please use LangGraph Platform.
```
If you were to self-host this on the public internet, anyone could access it!
@@ -294,9 +294,9 @@ Now that you have a LangGraph app running locally, take your journey further by
:::python
- [Python SDK Reference](../../cloud/reference/sdk/python_sdk_ref.md): Explore the Python SDK API Reference.
:::
:::
:::js
- [JS/TS SDK Reference](../../cloud/reference/sdk/js_ts_sdk_ref.md): Explore the JS/TS SDK API Reference.
:::
:::
+1 -1
View File
@@ -1948,7 +1948,7 @@ const llmWithTools = llm.bindTools(tools);
# Conditional edge function to route to the tool node or end based upon whether the LLM made a tool call
def should_continue(state: MessagesState) -> Literal["Action", END]:
def should_continue(state: MessagesState) -> Literal["environment", END]:
"""Decide if we should continue the loop or stop based upon whether the LLM made a tool call"""
messages = state["messages"]
+98 -62
View File
@@ -149,67 +149,6 @@ plugins:
- tutorials/auth/add_auth_server.md
- tutorials/auth/getting_started.md
- tutorials/auth/resource_auth.md
- agents/agents.md
- concepts/why-langgraph.md
- tutorials/get-started/1-build-basic-chatbot.md
- tutorials/get-started/2-add-tools.md
- tutorials/get-started/3-add-memory.md
- tutorials/get-started/4-human-in-the-loop.md
- tutorials/get-started/5-customize-state.md
- tutorials/get-started/6-time-travel.md
- tutorials/langgraph-platform/local-server.md
- tutorials/workflows.md
- concepts/agentic_concepts.md
- guides/index.md
- agents/overview.md
- agents/run_agents.md
- concepts/low_level.md
- how-tos/graph-api.md
- concepts/functional_api.md
- how-tos/use-functional-api.md
- concepts/pregel.md
- concepts/streaming.md
- how-tos/streaming.md
- concepts/persistence.md
- concepts/durable_execution.md
- concepts/memory.md
- how-tos/memory/add-memory.md
- agents/context.md
- agents/models.md
- concepts/tools.md
- how-tos/tool-calling.md
- concepts/human_in_the_loop.md
- how-tos/human_in_the_loop/add-human-in-the-loop.md
- concepts/time-travel.md
- how-tos/human_in_the_loop/time-travel.md
- concepts/subgraphs.md
- how-tos/subgraph.md
- concepts/multi_agent.md
- agents/multi-agent.md
- how-tos/multi_agent.md
- concepts/mcp.md
- agents/mcp.md
- concepts/tracing.md
- how-tos/enable-tracing.md
- agents/evals.md
- examples/index.md
- concepts/template_applications.md # TODO: make tutorial
- tutorials/rag/langgraph_agentic_rag.md
- tutorials/multi_agent/agent_supervisor.md
- tutorials/sql/sql-agent.md
- agents/ui.md
- how-tos/run-id-langsmith.md
- troubleshooting/errors/index.md
- troubleshooting/errors/GRAPH_RECURSION_LIMIT.md
- troubleshooting/errors/INVALID_CONCURRENT_GRAPH_UPDATE.md
- troubleshooting/errors/INVALID_GRAPH_NODE_RETURN_VALUE.md
- troubleshooting/errors/MULTIPLE_SUBGRAPHS.md
- troubleshooting/errors/INVALID_CHAT_HISTORY.md
- troubleshooting/errors/INVALID_LICENSE.md
- adopters.md
- concepts/faq.md
- agents/prebuilt.md # NOTE: prebuilt.md is auto-generated by `make build-prebuilt`
- tags
- include-markdown
- mkdocstrings:
@@ -247,6 +186,75 @@ plugins:
- "!^_"
nav:
- Get started:
- index.md
- Quickstarts:
- Start with a prebuilt agent: agents/agents.md
- Build a custom workflow:
- concepts/why-langgraph.md
- 1. Build a basic chatbot: tutorials/get-started/1-build-basic-chatbot.md
- 2. Add tools: tutorials/get-started/2-add-tools.md
- 3. Add memory: tutorials/get-started/3-add-memory.md
- 4. Add human-in-the-loop: tutorials/get-started/4-human-in-the-loop.md
- 5. Customize state: tutorials/get-started/5-customize-state.md
- 6. Time travel: tutorials/get-started/6-time-travel.md
- Run a local server: tutorials/langgraph-platform/local-server.md
- General concepts:
- Workflows & agents: tutorials/workflows.md
- Agent architectures: concepts/agentic_concepts.md
- Guides:
- guides/index.md
- Agent development:
- Overview: agents/overview.md
- Run an agent: agents/run_agents.md
- LangGraph APIs:
- Graph API:
- Overview: concepts/low_level.md
- Use the Graph API: how-tos/graph-api.md
- Functional API:
- Overview: concepts/functional_api.md
- Use the Functional API: how-tos/use-functional-api.md
- Runtime: concepts/pregel.md
- Core capabilities:
- Streaming:
- Overview: concepts/streaming.md
- Stream outputs: how-tos/streaming.md
- Persistence:
- Overview: concepts/persistence.md
- Durable execution:
- Overview: concepts/durable_execution.md
- Memory:
- Overview: concepts/memory.md
- Add memory: how-tos/memory/add-memory.md
- Context:
- Add context: agents/context.md
- Models:
- Configure model: agents/models.md
- Tools:
- Overview: concepts/tools.md
- Call tools: how-tos/tool-calling.md
- Human-in-the-loop:
- Overview: concepts/human_in_the_loop.md
- Add human intervention: how-tos/human_in_the_loop/add-human-in-the-loop.md
- Time travel:
- Overview: concepts/time-travel.md
- Use time travel: how-tos/human_in_the_loop/time-travel.md
- Subgraphs:
- Overview: concepts/subgraphs.md
- Use subgraphs: how-tos/subgraph.md
- Multi-agent:
- Overview: concepts/multi_agent.md
- Prebuilt implementation: agents/multi-agent.md
- Custom implementation: how-tos/multi_agent.md
- MCP:
- Overview: concepts/mcp.md
- Use MCP: agents/mcp.md
- Tracing:
- Overview: concepts/tracing.md
- Enable tracing: how-tos/enable-tracing.md
- Evaluate performance: agents/evals.md
- Reference:
- reference/index.md
- LangGraph:
@@ -270,7 +278,35 @@ nav:
- LangGraph Platform:
- SDK (Python): cloud/reference/sdk/python_sdk_ref.md
- SDK (JS/TS): https://langchain-ai.github.io/langgraphjs/reference/modules/sdk.html
- RemoteGraph: reference/remote_graph.md
- RemoteGraph: reference/remote_graph.md
- Examples:
- examples/index.md
- Template applications: concepts/template_applications.md # TODO: make tutorial
- Agentic RAG: tutorials/rag/langgraph_agentic_rag.md
- Agent Supervisor: tutorials/multi_agent/agent_supervisor.md
- SQL agent: tutorials/sql/sql-agent.md
- Prebuilt chat UI: agents/ui.md
- Graph runs in LangSmith: how-tos/run-id-langsmith.md
- Additional resources:
- additional-resources/index.md
- agents/prebuilt.md # NOTE: prebuilt.md is auto-generated by `make build-prebuilt`
- LangGraph Academy course: https://academy.langchain.com/courses/intro-to-langgraph
- Case studies: adopters.md
- concepts/faq.md
- llms.txt: llms-txt-overview.md
- LangChain Forum: https://forum.langchain.com/
- Troubleshooting:
- Errors:
- troubleshooting/errors/index.md
- troubleshooting/errors/GRAPH_RECURSION_LIMIT.md
- troubleshooting/errors/INVALID_CONCURRENT_GRAPH_UPDATE.md
- troubleshooting/errors/INVALID_GRAPH_NODE_RETURN_VALUE.md
- troubleshooting/errors/MULTIPLE_SUBGRAPHS.md
- troubleshooting/errors/INVALID_CHAT_HISTORY.md
- troubleshooting/errors/INVALID_LICENSE.md
markdown_extensions:
- abbr
+2 -2
View File
@@ -291,7 +291,7 @@ j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src=
}
.md-banner {
background-color: #FFAE42;
background-color: #CFC9FA;
color: #000000;
}
@@ -360,5 +360,5 @@ j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src=
{% endblock %}
{% block announce %}
These docs will be deprecated and removed with the release of LangGraph v1.0 in October 2025. <a href="https://docs.langchain.com/oss/python/langgraph/overview" target="_blank">Visit the v1.0 alpha docs</a>
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>.
{% endblock %}
+4 -4
View File
@@ -7,14 +7,14 @@ name = "langgraph-docs"
version = "0.0.1"
description = "LangGraph docs"
authors = []
requires-python = ">=3.11.0,<4.0.0"
requires-python = "~=3.11"
readme = "README.md"
license = "MIT"
dependencies = [
"aiohappyeyeballs==2.4.3",
"hub>=3.0.1,<4.0.0",
"xxhash>=3.5.0,<4.0.0",
"black>=25.1.0,<26.0.0",
"hub>=3.0.1,<4",
"xxhash>=3.5.0,<4",
"black>=25.1.0,<26",
]
[dependency-groups]
Generated
+4 -5
View File
@@ -1,5 +1,5 @@
version = 1
revision = 3
revision = 2
requires-python = ">=3.11, <4"
resolution-markers = [
"python_full_version >= '3.13' and platform_python_implementation != 'PyPy'",
@@ -2337,7 +2337,7 @@ wheels = [
[[package]]
name = "langgraph"
version = "0.6.7"
version = "0.6.2"
source = { editable = "../libs/langgraph" }
dependencies = [
{ name = "langchain-core" },
@@ -2380,7 +2380,6 @@ dev = [
{ name = "pytest-repeat" },
{ name = "pytest-watcher" },
{ name = "pytest-xdist", extras = ["psutil"] },
{ name = "redis" },
{ name = "ruff" },
{ name = "syrupy" },
{ name = "types-requests" },
@@ -2414,7 +2413,6 @@ dev = [
{ name = "pytest-asyncio" },
{ name = "pytest-mock" },
{ name = "pytest-watcher" },
{ name = "redis" },
{ name = "ruff" },
]
@@ -2645,7 +2643,7 @@ test = [
[[package]]
name = "langgraph-prebuilt"
version = "0.6.4"
version = "0.6.2"
source = { editable = "../libs/prebuilt" }
dependencies = [
{ name = "langchain-core" },
@@ -2676,6 +2674,7 @@ dev = [
[[package]]
name = "langgraph-sdk"
version = "0.2.0"
source = { editable = "../libs/sdk-py" }
dependencies = [
{ name = "httpx" },
+1 -1
View File
@@ -5,7 +5,7 @@
"id": "18526f23",
"metadata": {},
"source": [
"This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/memory/add-memory.md"
"This file has been moved to https://github.com/langchain-ai/langgraph/blob/main/docs/docs/how-tos/persistence_postgres.ipynb"
]
}
],
+1 -3
View File
@@ -707,9 +707,7 @@
" \"\"\"\n",
" Find all tool calls in the messages returned\n",
" \"\"\"\n",
" tool_calls = [\n",
" tc[\"name\"] for m in messages[\"messages\"] for tc in getattr(m, \"tool_calls\", [])\n",
" ]\n",
" tool_calls = [tc['name'] for m in messages['messages'] for tc in getattr(m, 'tool_calls', [])]\n",
" return tool_calls\n",
"\n",
"\n",
-21
View File
@@ -1,21 +0,0 @@
MIT License
Copyright (c) 2024 LangChain, Inc.
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
@@ -7,6 +7,11 @@ from contextlib import contextmanager
from typing import Any
from langchain_core.runnables import RunnableConfig
from psycopg import Capabilities, Connection, Cursor, Pipeline
from psycopg.rows import DictRow, dict_row
from psycopg.types.json import Jsonb
from psycopg_pool import ConnectionPool
from langgraph.checkpoint.base import (
WRITES_IDX_MAP,
ChannelVersions,
@@ -14,17 +19,12 @@ from langgraph.checkpoint.base import (
CheckpointMetadata,
CheckpointTuple,
get_checkpoint_id,
get_serializable_checkpoint_metadata,
get_checkpoint_metadata,
)
from langgraph.checkpoint.serde.base import SerializerProtocol
from psycopg import Capabilities, Connection, Cursor, Pipeline
from psycopg.rows import DictRow, dict_row
from psycopg.types.json import Jsonb
from psycopg_pool import ConnectionPool
from langgraph.checkpoint.postgres import _internal
from langgraph.checkpoint.postgres.base import BasePostgresSaver
from langgraph.checkpoint.postgres.shallow import ShallowPostgresSaver
from langgraph.checkpoint.serde.base import SerializerProtocol
Conn = _internal.Conn # For backward compatibility
@@ -94,10 +94,9 @@ class PostgresSaver(BasePostgresSaver):
for v, migration in zip(
range(version + 1, len(self.MIGRATIONS)),
self.MIGRATIONS[version + 1 :],
strict=False,
):
cur.execute(migration)
cur.execute("INSERT INTO checkpoint_migrations (v) VALUES (%s)", (v,))
cur.execute(f"INSERT INTO checkpoint_migrations (v) VALUES ({v})")
if self.pipe:
self.pipe.sync()
@@ -116,12 +115,12 @@ class PostgresSaver(BasePostgresSaver):
Args:
config: The config to use for listing the checkpoints.
filter: Additional filtering criteria for metadata.
before: If provided, only checkpoints before the specified checkpoint ID are returned.
limit: The maximum number of checkpoints to return.
filter: Additional filtering criteria for metadata. Defaults to None.
before: If provided, only checkpoints before the specified checkpoint ID are returned. Defaults to None.
limit: The maximum number of checkpoints to return. Defaults to None.
Yields:
An iterator of checkpoint tuples.
Iterator[CheckpointTuple]: An iterator of checkpoint tuples.
Examples:
>>> from langgraph.checkpoint.postgres import PostgresSaver
@@ -183,7 +182,7 @@ class PostgresSaver(BasePostgresSaver):
"""Get a checkpoint tuple from the database.
This method retrieves a checkpoint tuple from the Postgres database based on the
provided config. If the config contains a `checkpoint_id` key, the checkpoint with
provided config. If the config contains a "checkpoint_id" key, the checkpoint with
the matching thread ID and timestamp is retrieved. Otherwise, the latest checkpoint
for the given thread ID is retrieved.
@@ -191,7 +190,7 @@ class PostgresSaver(BasePostgresSaver):
config: The config to use for retrieving the checkpoint.
Returns:
The retrieved checkpoint tuple, or None if no matching checkpoint was found.
Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found.
Examples:
@@ -326,7 +325,7 @@ class PostgresSaver(BasePostgresSaver):
checkpoint["id"],
checkpoint_id,
Jsonb(copy),
Jsonb(get_serializable_checkpoint_metadata(config, metadata)),
Jsonb(get_checkpoint_metadata(config, metadata)),
),
)
return next_config
@@ -451,7 +450,7 @@ class PostgresSaver(BasePostgresSaver):
{
**value["checkpoint"],
"channel_values": {
**(value["checkpoint"].get("channel_values") or {}),
**value["checkpoint"].get("channel_values"),
**self._load_blobs(value["channel_values"]),
},
},
@@ -2,12 +2,13 @@
from collections.abc import AsyncIterator
from contextlib import asynccontextmanager
from typing import Union
from psycopg import AsyncConnection
from psycopg.rows import DictRow
from psycopg_pool import AsyncConnectionPool
Conn = AsyncConnection[DictRow] | AsyncConnectionPool[AsyncConnection[DictRow]]
Conn = Union[AsyncConnection[DictRow], AsyncConnectionPool[AsyncConnection[DictRow]]]
@asynccontextmanager
@@ -2,12 +2,13 @@
from collections.abc import Iterator
from contextlib import contextmanager
from typing import Union
from psycopg import Connection
from psycopg.rows import DictRow
from psycopg_pool import ConnectionPool
Conn = Connection[DictRow] | ConnectionPool[Connection[DictRow]]
Conn = Union[Connection[DictRow], ConnectionPool[Connection[DictRow]]]
@contextmanager
@@ -7,6 +7,11 @@ from contextlib import asynccontextmanager
from typing import Any
from langchain_core.runnables import RunnableConfig
from psycopg import AsyncConnection, AsyncCursor, AsyncPipeline, Capabilities
from psycopg.rows import DictRow, dict_row
from psycopg.types.json import Jsonb
from psycopg_pool import AsyncConnectionPool
from langgraph.checkpoint.base import (
WRITES_IDX_MAP,
ChannelVersions,
@@ -14,17 +19,12 @@ from langgraph.checkpoint.base import (
CheckpointMetadata,
CheckpointTuple,
get_checkpoint_id,
get_serializable_checkpoint_metadata,
get_checkpoint_metadata,
)
from langgraph.checkpoint.serde.base import SerializerProtocol
from psycopg import AsyncConnection, AsyncCursor, AsyncPipeline, Capabilities
from psycopg.rows import DictRow, dict_row
from psycopg.types.json import Jsonb
from psycopg_pool import AsyncConnectionPool
from langgraph.checkpoint.postgres import _ainternal
from langgraph.checkpoint.postgres.base import BasePostgresSaver
from langgraph.checkpoint.postgres.shallow import AsyncShallowPostgresSaver
from langgraph.checkpoint.serde.base import SerializerProtocol
Conn = _ainternal.Conn # For backward compatibility
@@ -99,12 +99,9 @@ class AsyncPostgresSaver(BasePostgresSaver):
for v, migration in zip(
range(version + 1, len(self.MIGRATIONS)),
self.MIGRATIONS[version + 1 :],
strict=False,
):
await cur.execute(migration)
await cur.execute(
"INSERT INTO checkpoint_migrations (v) VALUES (%s)", (v,)
)
await cur.execute(f"INSERT INTO checkpoint_migrations (v) VALUES ({v})")
if self.pipe:
await self.pipe.sync()
@@ -124,11 +121,11 @@ class AsyncPostgresSaver(BasePostgresSaver):
Args:
config: Base configuration for filtering checkpoints.
filter: Additional filtering criteria for metadata.
before: If provided, only checkpoints before the specified checkpoint ID are returned.
before: If provided, only checkpoints before the specified checkpoint ID are returned. Defaults to None.
limit: Maximum number of checkpoints to return.
Yields:
An asynchronous iterator of matching checkpoint tuples.
AsyncIterator[CheckpointTuple]: An asynchronous iterator of matching checkpoint tuples.
"""
where, args = self._search_where(config, filter, before)
query = self.SELECT_SQL + where + " ORDER BY checkpoint_id DESC"
@@ -172,7 +169,7 @@ class AsyncPostgresSaver(BasePostgresSaver):
"""Get a checkpoint tuple from the database asynchronously.
This method retrieves a checkpoint tuple from the Postgres database based on the
provided config. If the config contains a `checkpoint_id` key, the checkpoint with
provided config. If the config contains a "checkpoint_id" key, the checkpoint with
the matching thread ID and "checkpoint_id" is retrieved. Otherwise, the latest checkpoint
for the given thread ID is retrieved.
@@ -180,7 +177,7 @@ class AsyncPostgresSaver(BasePostgresSaver):
config: The config to use for retrieving the checkpoint.
Returns:
The retrieved checkpoint tuple, or None if no matching checkpoint was found.
Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found.
"""
thread_id = config["configurable"]["thread_id"]
checkpoint_id = get_checkpoint_id(config)
@@ -286,7 +283,7 @@ class AsyncPostgresSaver(BasePostgresSaver):
checkpoint["id"],
checkpoint_id,
Jsonb(copy),
Jsonb(get_serializable_checkpoint_metadata(config, metadata)),
Jsonb(get_checkpoint_metadata(config, metadata)),
),
)
return next_config
@@ -412,7 +409,7 @@ class AsyncPostgresSaver(BasePostgresSaver):
{
**value["checkpoint"],
"channel_values": {
**(value["checkpoint"].get("channel_values") or {}),
**value["checkpoint"].get("channel_values"),
**self._load_blobs(value["channel_values"]),
},
},
@@ -447,11 +444,11 @@ class AsyncPostgresSaver(BasePostgresSaver):
Args:
config: Base configuration for filtering checkpoints.
filter: Additional filtering criteria for metadata.
before: If provided, only checkpoints before the specified checkpoint ID are returned.
before: If provided, only checkpoints before the specified checkpoint ID are returned. Defaults to None.
limit: Maximum number of checkpoints to return.
Yields:
An iterator of matching checkpoint tuples.
Iterator[CheckpointTuple]: An iterator of matching checkpoint tuples.
"""
try:
# check if we are in the main thread, only bg threads can block
@@ -479,7 +476,7 @@ class AsyncPostgresSaver(BasePostgresSaver):
"""Get a checkpoint tuple from the database.
This method retrieves a checkpoint tuple from the Postgres database based on the
provided config. If the config contains a `checkpoint_id` key, the checkpoint with
provided config. If the config contains a "checkpoint_id" key, the checkpoint with
the matching thread ID and "checkpoint_id" is retrieved. Otherwise, the latest checkpoint
for the given thread ID is retrieved.
@@ -487,7 +484,7 @@ class AsyncPostgresSaver(BasePostgresSaver):
config: The config to use for retrieving the checkpoint.
Returns:
The retrieved checkpoint tuple, or None if no matching checkpoint was found.
Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found.
"""
try:
# check if we are in the main thread, only bg threads can block
@@ -1,12 +1,12 @@
from __future__ import annotations
import random
import warnings
from collections.abc import Sequence
from importlib.metadata import version as get_version
from typing import Any, cast
from typing import Any, Optional, cast
from langchain_core.runnables import RunnableConfig
from psycopg.types.json import Jsonb
from langgraph.checkpoint.base import (
WRITES_IDX_MAP,
BaseCheckpointSaver,
@@ -14,21 +14,8 @@ from langgraph.checkpoint.base import (
get_checkpoint_id,
)
from langgraph.checkpoint.serde.types import TASKS
from psycopg.types.json import Jsonb
MetadataInput = dict[str, Any] | None
try:
major, minor = get_version("langgraph").split(".")[:2]
if int(major) == 0 and int(minor) < 5:
warnings.warn(
"You're using incompatible versions of langgraph and checkpoint-postgres. Please upgrade langgraph to avoid unexpected behavior.",
DeprecationWarning,
stacklevel=2,
)
except Exception:
# skip version check if running from source
pass
MetadataInput = Optional[dict[str, Any]]
"""
To add a new migration, add a new string to the MIGRATIONS list.
@@ -81,7 +68,7 @@ MIGRATIONS = [
"""
CREATE INDEX CONCURRENTLY IF NOT EXISTS checkpoint_writes_thread_id_idx ON checkpoint_writes(thread_id);
""",
"""ALTER TABLE checkpoint_writes ADD COLUMN IF NOT EXISTS task_path TEXT NOT NULL DEFAULT '';""",
"""ALTER TABLE checkpoint_writes ADD COLUMN task_path TEXT NOT NULL DEFAULT '';""",
]
SELECT_SQL = """
@@ -3,19 +3,9 @@ import threading
import warnings
from collections.abc import AsyncIterator, Iterator, Sequence
from contextlib import asynccontextmanager, contextmanager
from typing import Any
from typing import Any, Optional
from langchain_core.runnables import RunnableConfig
from langgraph.checkpoint.base import (
WRITES_IDX_MAP,
ChannelVersions,
Checkpoint,
CheckpointMetadata,
CheckpointTuple,
get_serializable_checkpoint_metadata,
)
from langgraph.checkpoint.serde.base import SerializerProtocol
from langgraph.checkpoint.serde.types import TASKS
from psycopg import (
AsyncConnection,
AsyncCursor,
@@ -29,8 +19,18 @@ from psycopg.rows import DictRow, dict_row
from psycopg.types.json import Jsonb
from psycopg_pool import AsyncConnectionPool, ConnectionPool
from langgraph.checkpoint.base import (
WRITES_IDX_MAP,
ChannelVersions,
Checkpoint,
CheckpointMetadata,
CheckpointTuple,
get_checkpoint_metadata,
)
from langgraph.checkpoint.postgres import _ainternal, _internal
from langgraph.checkpoint.postgres.base import BasePostgresSaver
from langgraph.checkpoint.serde.base import SerializerProtocol
from langgraph.checkpoint.serde.types import TASKS
"""
To add a new migration, add a new string to the MIGRATIONS list.
@@ -77,7 +77,7 @@ MIGRATIONS = [
CREATE INDEX CONCURRENTLY IF NOT EXISTS checkpoint_writes_thread_id_idx ON checkpoint_writes(thread_id);
""",
"""
ALTER TABLE checkpoint_writes ADD COLUMN IF NOT EXISTS task_path TEXT NOT NULL DEFAULT '';
ALTER TABLE checkpoint_writes ADD COLUMN task_path TEXT NOT NULL DEFAULT '';
""",
]
@@ -151,7 +151,7 @@ def _dump_blobs(
checkpoint_ns: str,
values: dict[str, Any],
versions: ChannelVersions,
) -> list[tuple[str, str, str, str, bytes | None]]:
) -> list[tuple[str, str, str, str, Optional[bytes]]]:
if not versions:
return []
@@ -186,8 +186,8 @@ class ShallowPostgresSaver(BasePostgresSaver):
def __init__(
self,
conn: _internal.Conn,
pipe: Pipeline | None = None,
serde: SerializerProtocol | None = None,
pipe: Optional[Pipeline] = None,
serde: Optional[SerializerProtocol] = None,
) -> None:
warnings.warn(
"ShallowPostgresSaver is deprecated as of version 2.0.20 and will be removed in 3.0.0. "
@@ -249,20 +249,19 @@ class ShallowPostgresSaver(BasePostgresSaver):
for v, migration in zip(
range(version + 1, len(self.MIGRATIONS)),
self.MIGRATIONS[version + 1 :],
strict=False,
):
cur.execute(migration)
cur.execute("INSERT INTO checkpoint_migrations (v) VALUES (%s)", (v,))
cur.execute(f"INSERT INTO checkpoint_migrations (v) VALUES ({v})")
if self.pipe:
self.pipe.sync()
def list(
self,
config: RunnableConfig | None,
config: Optional[RunnableConfig],
*,
filter: dict[str, Any] | None = None,
before: RunnableConfig | None = None,
limit: int | None = None,
filter: Optional[dict[str, Any]] = None,
before: Optional[RunnableConfig] = None,
limit: Optional[int] = None,
) -> Iterator[CheckpointTuple]:
"""List checkpoints from the database.
@@ -300,7 +299,7 @@ class ShallowPostgresSaver(BasePostgresSaver):
pending_writes=self._load_writes(value["pending_writes"]),
)
def get_tuple(self, config: RunnableConfig) -> CheckpointTuple | None:
def get_tuple(self, config: RunnableConfig) -> Optional[CheckpointTuple]:
"""Get a checkpoint tuple from the database.
This method retrieves a checkpoint tuple from the Postgres database based on the
@@ -310,7 +309,7 @@ class ShallowPostgresSaver(BasePostgresSaver):
config: The config to use for retrieving the checkpoint.
Returns:
The retrieved checkpoint tuple, or None if no matching checkpoint was found.
Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found.
Examples:
@@ -442,7 +441,7 @@ class ShallowPostgresSaver(BasePostgresSaver):
thread_id,
checkpoint_ns,
Jsonb(copy),
Jsonb(get_serializable_checkpoint_metadata(config, metadata)),
Jsonb(get_checkpoint_metadata(config, metadata)),
),
)
return next_config
@@ -543,8 +542,8 @@ class AsyncShallowPostgresSaver(BasePostgresSaver):
def __init__(
self,
conn: _ainternal.Conn,
pipe: AsyncPipeline | None = None,
serde: SerializerProtocol | None = None,
pipe: Optional[AsyncPipeline] = None,
serde: Optional[SerializerProtocol] = None,
) -> None:
warnings.warn(
"AsyncShallowPostgresSaver is deprecated as of version 2.0.20 and will be removed in 3.0.0. "
@@ -571,7 +570,7 @@ class AsyncShallowPostgresSaver(BasePostgresSaver):
conn_string: str,
*,
pipeline: bool = False,
serde: SerializerProtocol | None = None,
serde: Optional[SerializerProtocol] = None,
) -> AsyncIterator["AsyncShallowPostgresSaver"]:
"""Create a new AsyncShallowPostgresSaver instance from a connection string.
@@ -611,22 +610,19 @@ class AsyncShallowPostgresSaver(BasePostgresSaver):
for v, migration in zip(
range(version + 1, len(self.MIGRATIONS)),
self.MIGRATIONS[version + 1 :],
strict=False,
):
await cur.execute(migration)
await cur.execute(
"INSERT INTO checkpoint_migrations (v) VALUES (%s)", (v,)
)
await cur.execute(f"INSERT INTO checkpoint_migrations (v) VALUES ({v})")
if self.pipe:
await self.pipe.sync()
async def alist(
self,
config: RunnableConfig | None,
config: Optional[RunnableConfig],
*,
filter: dict[str, Any] | None = None,
before: RunnableConfig | None = None,
limit: int | None = None,
filter: Optional[dict[str, Any]] = None,
before: Optional[RunnableConfig] = None,
limit: Optional[int] = None,
) -> AsyncIterator[CheckpointTuple]:
"""List checkpoints from the database asynchronously.
@@ -666,7 +662,7 @@ class AsyncShallowPostgresSaver(BasePostgresSaver):
),
)
async def aget_tuple(self, config: RunnableConfig) -> CheckpointTuple | None:
async def aget_tuple(self, config: RunnableConfig) -> Optional[CheckpointTuple]:
"""Get a checkpoint tuple from the database asynchronously.
This method retrieves a checkpoint tuple from the Postgres database based on the
@@ -676,7 +672,7 @@ class AsyncShallowPostgresSaver(BasePostgresSaver):
config: The config to use for retrieving the checkpoint.
Returns:
The retrieved checkpoint tuple, or None if no matching checkpoint was found.
Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found.
"""
thread_id = config["configurable"]["thread_id"]
checkpoint_ns = config["configurable"].get("checkpoint_ns", "")
@@ -778,7 +774,7 @@ class AsyncShallowPostgresSaver(BasePostgresSaver):
thread_id,
checkpoint_ns,
Jsonb(copy),
Jsonb(get_serializable_checkpoint_metadata(config, metadata)),
Jsonb(get_checkpoint_metadata(config, metadata)),
),
)
return next_config
@@ -865,11 +861,11 @@ class AsyncShallowPostgresSaver(BasePostgresSaver):
def list(
self,
config: RunnableConfig | None,
config: Optional[RunnableConfig],
*,
filter: dict[str, Any] | None = None,
before: RunnableConfig | None = None,
limit: int | None = None,
filter: Optional[dict[str, Any]] = None,
before: Optional[RunnableConfig] = None,
limit: Optional[int] = None,
) -> Iterator[CheckpointTuple]:
"""List checkpoints from the database.
@@ -887,7 +883,7 @@ class AsyncShallowPostgresSaver(BasePostgresSaver):
except StopAsyncIteration:
break
def get_tuple(self, config: RunnableConfig) -> CheckpointTuple | None:
def get_tuple(self, config: RunnableConfig) -> Optional[CheckpointTuple]:
"""Get a checkpoint tuple from the database.
This method retrieves a checkpoint tuple from the Postgres database based on the
@@ -897,7 +893,7 @@ class AsyncShallowPostgresSaver(BasePostgresSaver):
config: The config to use for retrieving the checkpoint.
Returns:
The retrieved checkpoint tuple, or None if no matching checkpoint was found.
Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found.
"""
try:
# check if we are in the main thread, only bg threads can block
@@ -1,4 +1,4 @@
from langgraph.store.postgres.aio import AsyncPostgresStore
from langgraph.store.postgres.base import PoolConfig, PostgresStore
from langgraph.store.postgres.base import PostgresStore
__all__ = ["AsyncPostgresStore", "PoolConfig", "PostgresStore"]
__all__ = ["AsyncPostgresStore", "PostgresStore"]
@@ -2,12 +2,17 @@ from __future__ import annotations
import asyncio
import logging
from collections.abc import AsyncIterator, Callable, Iterable, Sequence
from collections.abc import AsyncIterator, Iterable, Sequence
from contextlib import asynccontextmanager
from types import TracebackType
from typing import Any, cast
from typing import Any, Callable, cast
import orjson
from psycopg import AsyncConnection, AsyncCursor, AsyncPipeline, Capabilities
from psycopg.rows import DictRow, dict_row
from psycopg_pool import AsyncConnectionPool
from langgraph.checkpoint.postgres import _ainternal
from langgraph.store.base import (
GetOp,
ListNamespacesOp,
@@ -17,11 +22,6 @@ from langgraph.store.base import (
SearchOp,
)
from langgraph.store.base.batch import AsyncBatchedBaseStore
from psycopg import AsyncConnection, AsyncCursor, AsyncPipeline, Capabilities
from psycopg.rows import DictRow, dict_row
from psycopg_pool import AsyncConnectionPool
from langgraph.checkpoint.postgres import _ainternal
from langgraph.store.postgres.base import (
PLACEHOLDER,
BasePostgresStore,
@@ -339,7 +339,7 @@ class AsyncPostgresStore(AsyncBatchedBaseStore, BasePostgresStore[_ainternal.Con
Args:
timeout: Maximum time to wait for the task to stop, in seconds.
If `None`, wait indefinitely.
If None, wait indefinitely.
Returns:
bool: True if the task was successfully stopped or wasn't running,
@@ -465,9 +465,7 @@ class AsyncPostgresStore(AsyncBatchedBaseStore, BasePostgresStore[_ainternal.Con
query,
[
p
for (ns, k, pathname, _), vector in zip(
txt_params, vectors, strict=False
)
for (ns, k, pathname, _), vector in zip(txt_params, vectors)
for p in (ns, k, pathname, vector)
],
)
@@ -488,13 +486,13 @@ class AsyncPostgresStore(AsyncBatchedBaseStore, BasePostgresStore[_ainternal.Con
vectors = await self.embeddings.aembed_documents(
[query for _, query in embedding_requests]
)
for (idx, _), vector in zip(embedding_requests, vectors, strict=False):
for (idx, _), vector in zip(embedding_requests, vectors):
_paramslist = queries[idx][1]
for i in range(len(_paramslist)):
if _paramslist[i] is PLACEHOLDER:
_paramslist[i] = vector
for (idx, _), (query, params) in zip(search_ops, queries, strict=False):
for (idx, _), (query, params) in zip(search_ops, queries):
await cur.execute(query, params)
rows = cast(list[Row], await cur.fetchall())
items = [
@@ -512,7 +510,7 @@ class AsyncPostgresStore(AsyncBatchedBaseStore, BasePostgresStore[_ainternal.Con
cur: AsyncCursor[DictRow],
) -> None:
queries = self._get_batch_list_namespaces_queries(list_ops)
for (query, params), (idx, _) in zip(queries, list_ops, strict=False):
for (query, params), (idx, _) in zip(queries, list_ops):
await cur.execute(query, params)
rows = cast(list[dict], await cur.fetchall())
namespaces = [_decode_ns_bytes(row["truncated_prefix"]) for row in rows]
@@ -6,20 +6,30 @@ import json
import logging
import threading
from collections import defaultdict
from collections.abc import Callable, Iterable, Iterator, Sequence
from collections.abc import Iterable, Iterator, Sequence
from contextlib import contextmanager
from datetime import datetime
from typing import (
TYPE_CHECKING,
Any,
Callable,
Generic,
Literal,
NamedTuple,
TypeVar,
Union,
cast,
)
import orjson
from psycopg import Capabilities, Connection, Cursor, Pipeline
from psycopg.rows import DictRow, dict_row
from psycopg.types.json import Jsonb
from psycopg_pool import ConnectionPool
from typing_extensions import TypedDict
from langgraph.checkpoint.postgres import _ainternal as _ainternal
from langgraph.checkpoint.postgres import _internal as _pg_internal
from langgraph.store.base import (
BaseStore,
GetOp,
@@ -36,14 +46,6 @@ from langgraph.store.base import (
get_text_at_path,
tokenize_path,
)
from psycopg import Capabilities, Connection, Cursor, Pipeline
from psycopg.rows import DictRow, dict_row
from psycopg.types.json import Jsonb
from psycopg_pool import ConnectionPool
from typing_extensions import TypedDict
from langgraph.checkpoint.postgres import _ainternal as _ainternal
from langgraph.checkpoint.postgres import _internal as _pg_internal
if TYPE_CHECKING:
from langchain_core.embeddings import Embeddings
@@ -91,12 +93,7 @@ WHERE expires_at IS NOT NULL;
VECTOR_MIGRATIONS: Sequence[Migration] = [
Migration(
"""
DO $$
BEGIN
IF NOT EXISTS (SELECT 1 FROM pg_extension WHERE extname = 'vector') THEN
CREATE EXTENSION vector;
END IF;
END $$;
CREATE EXTENSION IF NOT EXISTS vector;
""",
),
Migration(
@@ -144,7 +141,7 @@ CREATE INDEX CONCURRENTLY IF NOT EXISTS store_vectors_embedding_idx ON store_vec
]
C = TypeVar("C", bound=_pg_internal.Conn | _ainternal.Conn)
C = TypeVar("C", bound=Union[_pg_internal.Conn, _ainternal.Conn])
class PoolConfig(TypedDict, total=False):
@@ -258,7 +255,7 @@ class BasePostgresStore(Generic[C]):
results = []
for namespace, items in namespace_groups.items():
_, keys = zip(*items, strict=False)
_, keys = zip(*items)
this_refresh_ttls = refresh_ttls[namespace]
query = """
@@ -871,7 +868,7 @@ class PostgresStore(BaseStore, BasePostgresStore[_pg_internal.Conn]):
Args:
timeout: Maximum time to wait for the thread to stop, in seconds.
If `None`, wait indefinitely.
If None, wait indefinitely.
Returns:
bool: True if the thread was successfully stopped or wasn't running,
@@ -1017,9 +1014,7 @@ class PostgresStore(BaseStore, BasePostgresStore[_pg_internal.Conn]):
query,
[
p
for (ns, k, pathname, _), vector in zip(
txt_params, vectors, strict=False
)
for (ns, k, pathname, _), vector in zip(txt_params, vectors)
for p in (ns, k, pathname, vector)
],
)
@@ -1040,15 +1035,13 @@ class PostgresStore(BaseStore, BasePostgresStore[_pg_internal.Conn]):
embeddings = self.embeddings.embed_documents(
[query for _, query in embedding_requests]
)
for (idx, _), embedding in zip(
embedding_requests, embeddings, strict=False
):
for (idx, _), embedding in zip(embedding_requests, embeddings):
_paramslist = queries[idx][1]
for i in range(len(_paramslist)):
if _paramslist[i] is PLACEHOLDER:
_paramslist[i] = embedding
for (idx, _), (query, params) in zip(search_ops, queries, strict=False):
for (idx, _), (query, params) in zip(search_ops, queries):
cur.execute(query, params)
rows = cast(list[Row], cur.fetchall())
results[idx] = [
@@ -1065,7 +1058,7 @@ class PostgresStore(BaseStore, BasePostgresStore[_pg_internal.Conn]):
cur: Cursor[DictRow],
) -> None:
for (query, params), (idx, _) in zip(
self._get_batch_list_namespaces_queries(list_ops), list_ops, strict=False
self._get_batch_list_namespaces_queries(list_ops), list_ops
):
cur.execute(query, params)
results[idx] = [_decode_ns_bytes(row["truncated_prefix"]) for row in cur]
+8 -19
View File
@@ -4,45 +4,36 @@ build-backend = "hatchling.build"
[project]
name = "langgraph-checkpoint-postgres"
version = "3.0.1"
version = "2.0.23"
description = "Library with a Postgres implementation of LangGraph checkpoint saver."
authors = []
requires-python = ">=3.10"
requires-python = ">=3.9"
readme = "README.md"
license = "MIT"
license-files = ['LICENSE']
dependencies = [
"langgraph-checkpoint>=2.1.2,<4.0.0",
"langgraph-checkpoint>=2.0.21,<3.0.0",
"orjson>=3.10.1",
"psycopg>=3.2.0",
"psycopg-pool>=3.2.0",
]
[project.urls]
Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/checkpoint-postgres"
Twitter = "https://x.com/LangChainAI"
Slack = "https://www.langchain.com/join-community"
Reddit = "https://www.reddit.com/r/LangChain/"
Repository = "https://www.github.com/langchain-ai/langgraph"
[dependency-groups]
test = [
dev = [
"ruff",
"codespell",
"pytest",
"anyio",
"pytest-asyncio",
"pytest-mock",
"mypy",
"psycopg[binary]",
"langgraph-checkpoint",
"pytest-watcher",
]
lint = [
"ruff",
"codespell",
"mypy",
]
dev = [
{include-group = "test"},
{include-group = "lint"},
]
[tool.uv]
default-groups = ['dev']
@@ -64,10 +55,8 @@ lint.select = [
"UP", # pyupgrade
"B", # flake8-bugbear
"I", # isort
"UP", # pyupgrade
]
lint.ignore = ["E501", "B008"]
target-version = "py310"
[tool.mypy]
# https://mypy.readthedocs.io/en/stable/config_file.html
+9 -36
View File
@@ -6,6 +6,10 @@ from uuid import uuid4
import pytest
from langchain_core.runnables import RunnableConfig
from psycopg import AsyncConnection
from psycopg.rows import dict_row
from psycopg_pool import AsyncConnectionPool
from langgraph.checkpoint.base import (
EXCLUDED_METADATA_KEYS,
Checkpoint,
@@ -13,15 +17,11 @@ from langgraph.checkpoint.base import (
create_checkpoint,
empty_checkpoint,
)
from langgraph.checkpoint.serde.types import TASKS
from psycopg import AsyncConnection
from psycopg.rows import dict_row
from psycopg_pool import AsyncConnectionPool
from langgraph.checkpoint.postgres.aio import (
AsyncPostgresSaver,
AsyncShallowPostgresSaver,
)
from langgraph.checkpoint.serde.types import TASKS
from tests.conftest import DEFAULT_POSTGRES_URI
@@ -187,11 +187,13 @@ def test_data():
metadata_1: CheckpointMetadata = {
"source": "input",
"step": 2,
"writes": {},
"score": 1,
}
metadata_2: CheckpointMetadata = {
"source": "loop",
"step": 1,
"writes": {"foo": "bar"},
"score": None,
}
metadata_3: CheckpointMetadata = {}
@@ -218,6 +220,7 @@ async def test_combined_metadata(saver_name: str, test_data) -> None:
metadata: CheckpointMetadata = {
"source": "loop",
"step": 1,
"writes": {"foo": "bar"},
"score": None,
}
await saver.aput(config, chkpnt, metadata, {})
@@ -243,6 +246,7 @@ async def test_asearch(saver_name: str, test_data) -> None:
query_1 = {"source": "input"} # search by 1 key
query_2 = {
"step": 1,
"writes": {"foo": "bar"},
} # search by multiple keys
query_3: dict[str, Any] = {} # search by no keys, return all checkpoints
query_4 = {"source": "update", "step": 1} # no match
@@ -340,34 +344,3 @@ async def test_pending_sends_migration(saver_name: str) -> None:
TASKS: ["send-1", "send-2", "send-3"]
}
assert TASKS in search_results[0].checkpoint["channel_versions"]
@pytest.mark.parametrize("saver_name", ["base", "pool", "pipe"])
async def test_get_checkpoint_no_channel_values(
monkeypatch, saver_name: str, test_data
) -> None:
"""Backwards compatibility test that verifies a checkpoint with no channel_values key can be retrieved without throwing an error."""
async with _saver(saver_name) as saver:
config = {
"configurable": {
"thread_id": "thread-2",
"checkpoint_ns": "",
"__super_private_key": "super_private_value",
},
"metadata": {"run_id": "my_run_id"},
}
chkpnt: Checkpoint = create_checkpoint(empty_checkpoint(), {}, 1)
await saver.aput(config, chkpnt, {}, {})
load_checkpoint_tuple = saver._load_checkpoint_tuple
def patched_load_checkpoint_tuple(value):
value["checkpoint"].pop("channel_values", None)
return load_checkpoint_tuple(value)
monkeypatch.setattr(
saver, "_load_checkpoint_tuple", patched_load_checkpoint_tuple
)
checkpoint = await saver.aget_tuple(config)
assert checkpoint.checkpoint["channel_values"] == {}
@@ -3,6 +3,7 @@ from __future__ import annotations
import asyncio
import itertools
import sys
import uuid
from collections.abc import AsyncIterator
from concurrent.futures import ThreadPoolExecutor
@@ -11,6 +12,8 @@ from typing import Any
import pytest
from langchain_core.embeddings import Embeddings
from psycopg import AsyncConnection
from langgraph.store.base import (
GetOp,
Item,
@@ -18,8 +21,6 @@ from langgraph.store.base import (
PutOp,
SearchOp,
)
from psycopg import AsyncConnection
from langgraph.store.postgres import AsyncPostgresStore
from tests.conftest import (
DEFAULT_URI,
@@ -33,6 +34,9 @@ TTL_MINUTES = TTL_SECONDS / 60
@pytest.fixture(scope="function", params=["default", "pipe", "pool"])
async def store(request) -> AsyncIterator[AsyncPostgresStore]:
if sys.version_info < (3, 10):
pytest.skip("Async Postgres tests require Python 3.10+")
database = f"test_{uuid.uuid4().hex[:16]}"
uri_parts = DEFAULT_URI.split("/")
uri_base = "/".join(uri_parts[:-1])
@@ -354,6 +358,8 @@ async def _create_vector_store(
text_fields: list[str] | None = None,
) -> AsyncIterator[AsyncPostgresStore]:
"""Create a store with vector search enabled."""
if sys.version_info < (3, 10):
pytest.skip("Async Postgres tests require Python 3.10+")
database = f"test_{uuid.uuid4().hex[:16]}"
uri_parts = DEFAULT_URI.split("/")
+5 -43
View File
@@ -9,6 +9,8 @@ from uuid import uuid4
import pytest
from langchain_core.embeddings import Embeddings
from psycopg import Connection
from langgraph.store.base import (
GetOp,
Item,
@@ -17,8 +19,6 @@ from langgraph.store.base import (
PutOp,
SearchOp,
)
from psycopg import Connection
from langgraph.store.postgres import PostgresStore
from tests.conftest import (
DEFAULT_URI,
@@ -754,7 +754,7 @@ def _cosine_similarity(X: list[float], Y: list[list[float]]) -> list[float]:
similarities = []
for y in Y:
dot_product = sum(a * b for a, b in zip(X, y, strict=False))
dot_product = sum(a * b for a, b in zip(X, y))
norm1 = sum(a * a for a in X) ** 0.5
norm2 = sum(a * a for a in y) ** 0.5
similarity = dot_product / (norm1 * norm2) if norm1 > 0 and norm2 > 0 else 0.0
@@ -771,7 +771,7 @@ def _inner_product(X: list[float], Y: list[list[float]]) -> list[float]:
similarities = []
for y in Y:
similarity = sum(a * b for a, b in zip(X, y, strict=False))
similarity = sum(a * b for a, b in zip(X, y))
similarities.append(similarity)
return similarities
@@ -785,7 +785,7 @@ def _neg_l2_distance(X: list[float], Y: list[list[float]]) -> list[float]:
similarities = []
for y in Y:
similarity = sum((a - b) ** 2 for a, b in zip(X, y, strict=False)) ** 0.5
similarity = sum((a - b) ** 2 for a, b in zip(X, y)) ** 0.5
similarities.append(-similarity)
return similarities
@@ -861,41 +861,3 @@ def test_store_ttl(store):
# Now has been (TTL_SECONDS-2)*2 > TTL_SECONDS + TTL_SECONDS/2
res = store.search(ns, query="bar", refresh_ttl=False)
assert len(res) == 0
@pytest.mark.parametrize(
"vector_type,distance_type",
[
("vector", "cosine"),
("vector", "inner_product"),
("halfvec", "cosine"),
("halfvec", "inner_product"),
],
)
def test_non_ascii(
request: Any,
fake_embeddings: CharacterEmbeddings,
vector_type: str,
distance_type: str,
) -> None:
"""Test support for non-ascii characters"""
with _create_vector_store(vector_type, distance_type, fake_embeddings) as store:
store.put(("user_123", "memories"), "1", {"text": "这是中文"}) # Chinese
store.put(
("user_123", "memories"), "2", {"text": "これは日本語です"}
) # Japanese
store.put(("user_123", "memories"), "3", {"text": "이건 한국어야"}) # Korean
store.put(("user_123", "memories"), "4", {"text": "Это русский"}) # Russian
store.put(("user_123", "memories"), "5", {"text": "यह रूसी है"}) # Hindi
result1 = store.search(("user_123", "memories"), query="这是中文")
result2 = store.search(("user_123", "memories"), query="これは日本語です")
result3 = store.search(("user_123", "memories"), query="이건 한국어야")
result4 = store.search(("user_123", "memories"), query="Это русский")
result5 = store.search(("user_123", "memories"), query="यह रूसी है")
assert result1[0].key == "1"
assert result2[0].key == "2"
assert result3[0].key == "3"
assert result4[0].key == "4"
assert result5[0].key == "5"
+9 -35
View File
@@ -7,6 +7,10 @@ from uuid import uuid4
import pytest
from langchain_core.runnables import RunnableConfig
from psycopg import Connection
from psycopg.rows import dict_row
from psycopg_pool import ConnectionPool
from langgraph.checkpoint.base import (
EXCLUDED_METADATA_KEYS,
Checkpoint,
@@ -14,12 +18,8 @@ from langgraph.checkpoint.base import (
create_checkpoint,
empty_checkpoint,
)
from langgraph.checkpoint.serde.types import TASKS
from psycopg import Connection
from psycopg.rows import dict_row
from psycopg_pool import ConnectionPool
from langgraph.checkpoint.postgres import PostgresSaver, ShallowPostgresSaver
from langgraph.checkpoint.serde.types import TASKS
from tests.conftest import DEFAULT_POSTGRES_URI
@@ -169,11 +169,13 @@ def test_data():
metadata_1: CheckpointMetadata = {
"source": "input",
"step": 2,
"writes": {},
"score": 1,
}
metadata_2: CheckpointMetadata = {
"source": "loop",
"step": 1,
"writes": {"foo": "bar"},
"score": None,
}
metadata_3: CheckpointMetadata = {}
@@ -200,6 +202,7 @@ def test_combined_metadata(saver_name: str, test_data) -> None:
metadata: CheckpointMetadata = {
"source": "loop",
"step": 1,
"writes": {"foo": "bar"},
"score": None,
}
saver.put(config, chkpnt, metadata, {})
@@ -225,6 +228,7 @@ def test_search(saver_name: str, test_data) -> None:
query_1 = {"source": "input"} # search by 1 key
query_2 = {
"step": 1,
"writes": {"foo": "bar"},
} # search by multiple keys
query_3: dict[str, Any] = {} # search by no keys, return all checkpoints
query_4 = {"source": "update", "step": 1} # no match
@@ -328,33 +332,3 @@ def test_pending_sends_migration(saver_name: str) -> None:
TASKS: ["send-1", "send-2", "send-3"]
}
assert TASKS in search_results[0].checkpoint["channel_versions"]
@pytest.mark.parametrize("saver_name", ["base", "pool", "pipe"])
def test_get_checkpoint_no_channel_values(
monkeypatch, saver_name: str, test_data
) -> None:
"""Backwards compatibility test that verifies a checkpoint with no channel_values key can be retrieved without throwing an error."""
with _saver(saver_name) as saver:
config = {
"configurable": {
"thread_id": "thread-2",
"checkpoint_ns": "",
"__super_private_key": "super_private_value",
},
}
chkpnt: Checkpoint = create_checkpoint(empty_checkpoint(), {}, 1)
saver.put(config, chkpnt, {}, {})
load_checkpoint_tuple = saver._load_checkpoint_tuple
def patched_load_checkpoint_tuple(value):
value["checkpoint"].pop("channel_values", None)
return load_checkpoint_tuple(value)
monkeypatch.setattr(
saver, "_load_checkpoint_tuple", patched_load_checkpoint_tuple
)
checkpoint = saver.get_tuple(config)
assert checkpoint.checkpoint["channel_values"] == {}
+652 -624
View File
File diff suppressed because it is too large Load Diff
-21
View File
@@ -1,21 +0,0 @@
MIT License
Copyright (c) 2024 LangChain, Inc.
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
@@ -1,6 +1,5 @@
from __future__ import annotations
import json
import random
import sqlite3
import threading
@@ -9,6 +8,7 @@ from contextlib import closing, contextmanager
from typing import Any, cast
from langchain_core.runnables import RunnableConfig
from langgraph.checkpoint.base import (
WRITES_IDX_MAP,
BaseCheckpointSaver,
@@ -21,7 +21,6 @@ from langgraph.checkpoint.base import (
get_checkpoint_metadata,
)
from langgraph.checkpoint.serde.jsonplus import JsonPlusSerializer
from langgraph.checkpoint.sqlite.utils import search_where
_AIO_ERROR_MSG = (
@@ -185,7 +184,7 @@ class SqliteSaver(BaseCheckpointSaver[str]):
"""Get a checkpoint tuple from the database.
This method retrieves a checkpoint tuple from the SQLite database based on the
provided config. If the config contains a `checkpoint_id` key, the checkpoint with
provided config. If the config contains a "checkpoint_id" key, the checkpoint with
the matching thread ID and checkpoint ID is retrieved. Otherwise, the latest checkpoint
for the given thread ID is retrieved.
@@ -193,7 +192,7 @@ class SqliteSaver(BaseCheckpointSaver[str]):
config: The config to use for retrieving the checkpoint.
Returns:
The retrieved checkpoint tuple, or None if no matching checkpoint was found.
Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found.
Examples:
@@ -266,7 +265,9 @@ class SqliteSaver(BaseCheckpointSaver[str]):
self.serde.loads_typed((type, checkpoint)),
cast(
CheckpointMetadata,
json.loads(metadata) if metadata is not None else {},
self.jsonplus_serde.loads(metadata)
if metadata is not None
else {},
),
(
{
@@ -300,12 +301,12 @@ class SqliteSaver(BaseCheckpointSaver[str]):
Args:
config: The config to use for listing the checkpoints.
filter: Additional filtering criteria for metadata.
before: If provided, only checkpoints before the specified checkpoint ID are returned.
limit: The maximum number of checkpoints to return.
filter: Additional filtering criteria for metadata. Defaults to None.
before: If provided, only checkpoints before the specified checkpoint ID are returned. Defaults to None.
limit: The maximum number of checkpoints to return. Defaults to None.
Yields:
An iterator of checkpoint tuples.
Iterator[CheckpointTuple]: An iterator of checkpoint tuples.
Examples:
>>> from langgraph.checkpoint.sqlite import SqliteSaver
@@ -357,7 +358,9 @@ class SqliteSaver(BaseCheckpointSaver[str]):
self.serde.loads_typed((type, checkpoint)),
cast(
CheckpointMetadata,
json.loads(metadata) if metadata is not None else {},
self.jsonplus_serde.loads(metadata)
if metadata is not None
else {},
),
(
{
@@ -410,9 +413,9 @@ class SqliteSaver(BaseCheckpointSaver[str]):
thread_id = config["configurable"]["thread_id"]
checkpoint_ns = config["configurable"]["checkpoint_ns"]
type_, serialized_checkpoint = self.serde.dumps_typed(checkpoint)
serialized_metadata = json.dumps(
get_checkpoint_metadata(config, metadata), ensure_ascii=False
).encode("utf-8", "ignore")
serialized_metadata = self.jsonplus_serde.dumps(
get_checkpoint_metadata(config, metadata)
)
with self.cursor() as cur:
cur.execute(
"INSERT OR REPLACE INTO checkpoints (thread_id, checkpoint_ns, checkpoint_id, parent_checkpoint_id, type, checkpoint, metadata) VALUES (?, ?, ?, ?, ?, ?, ?)",
@@ -1,14 +1,14 @@
from __future__ import annotations
import asyncio
import json
import random
from collections.abc import AsyncIterator, Callable, Iterator, Sequence
from collections.abc import AsyncIterator, Iterator, Sequence
from contextlib import asynccontextmanager
from typing import Any, TypeVar, cast
from typing import Any, Callable, TypeVar, cast
import aiosqlite
from langchain_core.runnables import RunnableConfig
from langgraph.checkpoint.base import (
WRITES_IDX_MAP,
BaseCheckpointSaver,
@@ -21,7 +21,6 @@ from langgraph.checkpoint.base import (
get_checkpoint_metadata,
)
from langgraph.checkpoint.serde.jsonplus import JsonPlusSerializer
from langgraph.checkpoint.sqlite.utils import search_where
T = TypeVar("T", bound=Callable)
@@ -140,7 +139,7 @@ class AsyncSqliteSaver(BaseCheckpointSaver[str]):
"""Get a checkpoint tuple from the database.
This method retrieves a checkpoint tuple from the SQLite database based on the
provided config. If the config contains a `checkpoint_id` key, the checkpoint with
provided config. If the config contains a "checkpoint_id" key, the checkpoint with
the matching thread ID and checkpoint ID is retrieved. Otherwise, the latest checkpoint
for the given thread ID is retrieved.
@@ -148,7 +147,7 @@ class AsyncSqliteSaver(BaseCheckpointSaver[str]):
config: The config to use for retrieving the checkpoint.
Returns:
The retrieved checkpoint tuple, or None if no matching checkpoint was found.
Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found.
"""
try:
# check if we are in the main thread, only bg threads can block
@@ -182,11 +181,11 @@ class AsyncSqliteSaver(BaseCheckpointSaver[str]):
Args:
config: Base configuration for filtering checkpoints.
filter: Additional filtering criteria for metadata.
before: If provided, only checkpoints before the specified checkpoint ID are returned.
before: If provided, only checkpoints before the specified checkpoint ID are returned. Defaults to None.
limit: Maximum number of checkpoints to return.
Yields:
An iterator of matching checkpoint tuples.
Iterator[CheckpointTuple]: An iterator of matching checkpoint tuples.
"""
try:
# check if we are in the main thread, only bg threads can block
@@ -317,7 +316,7 @@ class AsyncSqliteSaver(BaseCheckpointSaver[str]):
"""Get a checkpoint tuple from the database asynchronously.
This method retrieves a checkpoint tuple from the SQLite database based on the
provided config. If the config contains a `checkpoint_id` key, the checkpoint with
provided config. If the config contains a "checkpoint_id" key, the checkpoint with
the matching thread ID and checkpoint ID is retrieved. Otherwise, the latest checkpoint
for the given thread ID is retrieved.
@@ -325,7 +324,7 @@ class AsyncSqliteSaver(BaseCheckpointSaver[str]):
config: The config to use for retrieving the checkpoint.
Returns:
The retrieved checkpoint tuple, or None if no matching checkpoint was found.
Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found.
"""
await self.setup()
checkpoint_ns = config["configurable"].get("checkpoint_ns", "")
@@ -378,7 +377,9 @@ class AsyncSqliteSaver(BaseCheckpointSaver[str]):
self.serde.loads_typed((type, checkpoint)),
cast(
CheckpointMetadata,
(json.loads(metadata) if metadata is not None else {}),
self.jsonplus_serde.loads(metadata)
if metadata is not None
else {},
),
(
{
@@ -413,11 +414,11 @@ class AsyncSqliteSaver(BaseCheckpointSaver[str]):
Args:
config: Base configuration for filtering checkpoints.
filter: Additional filtering criteria for metadata.
before: If provided, only checkpoints before the specified checkpoint ID are returned.
before: If provided, only checkpoints before the specified checkpoint ID are returned. Defaults to None.
limit: Maximum number of checkpoints to return.
Yields:
An asynchronous iterator of matching checkpoint tuples.
AsyncIterator[CheckpointTuple]: An asynchronous iterator of matching checkpoint tuples.
"""
await self.setup()
where, params = search_where(config, filter, before)
@@ -456,7 +457,9 @@ class AsyncSqliteSaver(BaseCheckpointSaver[str]):
self.serde.loads_typed((type, checkpoint)),
cast(
CheckpointMetadata,
(json.loads(metadata) if metadata is not None else {}),
self.jsonplus_serde.loads(metadata)
if metadata is not None
else {},
),
(
{
@@ -500,9 +503,9 @@ class AsyncSqliteSaver(BaseCheckpointSaver[str]):
thread_id = config["configurable"]["thread_id"]
checkpoint_ns = config["configurable"]["checkpoint_ns"]
type_, serialized_checkpoint = self.serde.dumps_typed(checkpoint)
serialized_metadata = json.dumps(
get_checkpoint_metadata(config, metadata), ensure_ascii=False
).encode("utf-8", "ignore")
serialized_metadata = self.jsonplus_serde.dumps(
get_checkpoint_metadata(config, metadata)
)
async with (
self.lock,
self.conn.execute(
@@ -5,6 +5,7 @@ from collections.abc import Sequence
from typing import Any
from langchain_core.runnables import RunnableConfig
from langgraph.checkpoint.base import get_checkpoint_id
@@ -3,14 +3,15 @@ from __future__ import annotations
import asyncio
import logging
from collections import defaultdict
from collections.abc import AsyncIterator, Callable, Iterable, Sequence
from collections.abc import AsyncIterator, Iterable, Sequence
from contextlib import asynccontextmanager
from types import TracebackType
from typing import Any, cast
from typing import Any, Callable, cast
import aiosqlite
import orjson
import sqlite_vec # type: ignore[import-untyped]
from langgraph.store.base import (
GetOp,
ListNamespacesOp,
@@ -21,7 +22,6 @@ from langgraph.store.base import (
TTLConfig,
)
from langgraph.store.base.batch import AsyncBatchedBaseStore
from langgraph.store.sqlite.base import (
_PLACEHOLDER,
BaseSqliteStore,
@@ -303,7 +303,7 @@ class AsyncSqliteStore(AsyncBatchedBaseStore, BaseSqliteStore):
Args:
timeout: Maximum time to wait for the task to stop, in seconds.
If `None`, wait indefinitely.
If None, wait indefinitely.
Returns:
bool: True if the task was successfully stopped or wasn't running,
@@ -484,7 +484,7 @@ class AsyncSqliteStore(AsyncBatchedBaseStore, BaseSqliteStore):
# Convert vectors to SQLite-friendly format
vector_params = []
for (ns, k, pathname, _), vector in zip(txt_params, vectors, strict=False):
for (ns, k, pathname, _), vector in zip(txt_params, vectors):
vector_params.extend(
[ns, k, pathname, sqlite_vec.serialize_float32(vector)]
)
@@ -507,9 +507,7 @@ class AsyncSqliteStore(AsyncBatchedBaseStore, BaseSqliteStore):
results: List to store results in.
cur: Database cursor.
"""
prepared_queries, embedding_requests = self._prepare_batch_search_queries(
search_ops
)
queries, embedding_requests = self._prepare_batch_search_queries(search_ops)
# Setup dot_product function if it doesn't exist
if embedding_requests and self.embeddings:
@@ -517,62 +515,23 @@ class AsyncSqliteStore(AsyncBatchedBaseStore, BaseSqliteStore):
[query for _, query in embedding_requests]
)
for (embed_req_idx, _), embedding in zip(
embedding_requests, vectors, strict=False
):
# Find the corresponding query in prepared_queries
# The embed_req_idx is the original index in search_ops, which should map to prepared_queries
if embed_req_idx < len(prepared_queries):
_params_list: list = prepared_queries[embed_req_idx][1]
for i, param in enumerate(_params_list):
if param is _PLACEHOLDER:
_params_list[i] = sqlite_vec.serialize_float32(embedding)
else:
logger.warning(
f"Embedding request index {embed_req_idx} out of bounds for prepared_queries."
)
for (idx, _), embedding in zip(embedding_requests, vectors):
_params_list: list = queries[idx][1]
for i, param in enumerate(_params_list):
if param is _PLACEHOLDER:
_params_list[i] = sqlite_vec.serialize_float32(embedding)
for (original_op_idx, _), (query, params, needs_refresh) in zip(
search_ops, prepared_queries, strict=False
):
for (idx, _), (query, params) in zip(search_ops, queries):
await cur.execute(query, params)
rows = await cur.fetchall()
if needs_refresh and rows and self.ttl_config:
keys_to_refresh = []
for row_data in rows:
# Assuming row_data[0] is prefix (text), row_data[1] is key (text)
# These are raw text values directly from the DB.
keys_to_refresh.append((row_data[0], row_data[1]))
if keys_to_refresh:
updates_by_prefix = defaultdict(list)
for prefix_text, key_text in keys_to_refresh:
updates_by_prefix[prefix_text].append(key_text)
for prefix_text, key_list in updates_by_prefix.items():
placeholders = ",".join(["?"] * len(key_list))
update_query = f"""
UPDATE store
SET expires_at = DATETIME(CURRENT_TIMESTAMP, '+' || ttl_minutes || ' minutes')
WHERE prefix = ? AND key IN ({placeholders}) AND ttl_minutes IS NOT NULL
"""
update_params = (prefix_text, *key_list)
try:
await cur.execute(update_query, update_params)
except Exception as e:
logger.error(
f"Error during TTL refresh update for search: {e}"
)
# Process rows into items
if "score" in query: # Vector search query
if "score" in query:
items = [
_row_to_search_item(
_decode_ns_text(row[0]), # prefix
_decode_ns_text(row[0]),
{
"key": row[1], # key
"value": row[2], # value
"key": row[1],
"value": row[2],
"created_at": row[3],
"updated_at": row[4],
"expires_at": row[5] if len(row) > 5 else None,
@@ -586,10 +545,10 @@ class AsyncSqliteStore(AsyncBatchedBaseStore, BaseSqliteStore):
else: # Regular search query
items = [
_row_to_search_item(
_decode_ns_text(row[0]), # prefix
_decode_ns_text(row[0]),
{
"key": row[1], # key
"value": row[2], # value
"key": row[1],
"value": row[2],
"created_at": row[3],
"updated_at": row[4],
"expires_at": row[5] if len(row) > 5 else None,
@@ -600,7 +559,7 @@ class AsyncSqliteStore(AsyncBatchedBaseStore, BaseSqliteStore):
for row in rows
]
results[original_op_idx] = items
results[idx] = items
async def _batch_list_namespaces_ops(
self,
@@ -616,7 +575,7 @@ class AsyncSqliteStore(AsyncBatchedBaseStore, BaseSqliteStore):
cur: Database cursor.
"""
queries = self._get_batch_list_namespaces_queries(list_ops)
for (query, params), (idx, _) in zip(queries, list_ops, strict=False):
for (query, params), (idx, _) in zip(queries, list_ops):
await cur.execute(query, params)
rows = await cur.fetchall()
@@ -7,12 +7,13 @@ import re
import sqlite3
import threading
from collections import defaultdict
from collections.abc import Callable, Iterable, Iterator, Sequence
from collections.abc import Iterable, Iterator, Sequence
from contextlib import contextmanager
from typing import Any, Literal, NamedTuple, cast
from typing import Any, Callable, Literal, NamedTuple, cast
import orjson
import sqlite_vec # type: ignore[import-untyped]
from langgraph.store.base import (
BaseStore,
GetOp,
@@ -232,7 +233,7 @@ class BaseSqliteStore:
results = []
for namespace, items in namespace_groups.items():
_, keys = zip(*items, strict=False)
_, keys = zip(*items)
this_refresh_ttls = refresh_ttls[namespace]
refresh_ttl_any = any(this_refresh_ttls)
@@ -371,15 +372,13 @@ class BaseSqliteStore:
def _prepare_batch_search_queries(
self, search_ops: Sequence[tuple[int, SearchOp]]
) -> tuple[
list[
tuple[str, list[None | str | list[float]], bool]
], # queries, params, needs_refresh
list[tuple[str, list[None | str | list[float]]]], # queries, params
list[tuple[int, str]], # idx, query_text pairs to embed
]:
"""
Build per-SearchOp SQL queries (with optional TTL refresh flag) plus embedding requests.
Build per-SearchOp SQL queries (with optional TTL refresh) plus embedding requests.
Returns:
- queries: list of (SQL, param_list, needs_ttl_refresh_flag)
- queries: list of (SQL, param_list)
- embedding_requests: list of (original_index_in_search_ops, text_query)
"""
queries = []
@@ -520,18 +519,30 @@ class BaseSqliteStore:
logger.debug(f"Search query: {base_query}")
logger.debug(f"Search params: {params}")
# Determine if TTL refresh is needed
needs_ttl_refresh = bool(
# Handle TTL refresh if requested
if (
op.refresh_ttl
and self.ttl_config
and self.ttl_config.get("refresh_on_read", False)
)
):
final_sql = f"""
WITH search_results AS (
{base_query}
),
updated AS (
UPDATE store
SET expires_at = DATETIME(CURRENT_TIMESTAMP, '+' || ttl_minutes || ' minutes')
WHERE (prefix, key) IN (SELECT prefix, key FROM search_results)
AND ttl_minutes IS NOT NULL
)
SELECT * FROM search_results
"""
final_params = params[:] # copy params
else:
final_sql = base_query
final_params = params
# The base_query is now the final_sql, and we pass the refresh flag
final_sql = base_query
final_params = params
queries.append((final_sql, final_params, needs_ttl_refresh))
queries.append((final_sql, final_params))
return queries, embedding_requests
@@ -829,7 +840,7 @@ class SqliteStore(BaseSqliteStore, BaseStore):
results = []
for namespace, items in namespace_groups.items():
_, keys = zip(*items, strict=False)
_, keys = zip(*items)
this_refresh_ttls = refresh_ttls[namespace]
refresh_ttl_any = any(this_refresh_ttls)
@@ -1156,7 +1167,7 @@ class SqliteStore(BaseSqliteStore, BaseStore):
Args:
timeout: Maximum time to wait for the thread to stop, in seconds.
If `None`, wait indefinitely.
If None, wait indefinitely.
Returns:
bool: True if the thread was successfully stopped or wasn't running,
@@ -1304,7 +1315,7 @@ class SqliteStore(BaseSqliteStore, BaseStore):
# Convert vectors to SQLite-friendly format
vector_params = []
for (ns, k, pathname, _), vector in zip(txt_params, vectors, strict=False):
for (ns, k, pathname, _), vector in zip(txt_params, vectors):
vector_params.extend(
[ns, k, pathname, sqlite_vec.serialize_float32(vector)]
)
@@ -1320,9 +1331,7 @@ class SqliteStore(BaseSqliteStore, BaseStore):
results: list[Result],
cur: sqlite3.Cursor,
) -> None:
prepared_queries, embedding_requests = self._prepare_batch_search_queries(
search_ops
)
queries, embedding_requests = self._prepare_batch_search_queries(search_ops)
# Setup similarity functions if they don't exist
if embedding_requests and self.embeddings:
@@ -1332,50 +1341,16 @@ class SqliteStore(BaseSqliteStore, BaseStore):
)
# Replace placeholders with actual embeddings
for (embed_req_idx, _), embedding in zip(
embedding_requests, embeddings, strict=False
):
if embed_req_idx < len(prepared_queries):
_params_list: list = prepared_queries[embed_req_idx][1]
for i, param in enumerate(_params_list):
if param is _PLACEHOLDER:
_params_list[i] = sqlite_vec.serialize_float32(embedding)
else:
logger.warning(
f"Embedding request index {embed_req_idx} out of bounds for prepared_queries."
)
for (idx, _), embedding in zip(embedding_requests, embeddings):
_params_list: list = queries[idx][1]
for i, param in enumerate(_params_list):
if param is _PLACEHOLDER:
_params_list[i] = sqlite_vec.serialize_float32(embedding)
for (original_op_idx, _), (query, params, needs_refresh) in zip(
search_ops, prepared_queries, strict=False
):
for (idx, _), (query, params) in zip(search_ops, queries):
cur.execute(query, params)
rows = cur.fetchall()
if needs_refresh and rows and self.ttl_config:
keys_to_refresh = []
for row_data in rows:
keys_to_refresh.append((row_data[0], row_data[1]))
if keys_to_refresh:
updates_by_prefix = defaultdict(list)
for prefix_text, key_text in keys_to_refresh:
updates_by_prefix[prefix_text].append(key_text)
for prefix_text, key_list in updates_by_prefix.items():
placeholders = ",".join(["?"] * len(key_list))
update_query = f"""
UPDATE store
SET expires_at = DATETIME(CURRENT_TIMESTAMP, '+' || ttl_minutes || ' minutes')
WHERE prefix = ? AND key IN ({placeholders}) AND ttl_minutes IS NOT NULL
"""
update_params = (prefix_text, *key_list)
try:
cur.execute(update_query, update_params)
except Exception as e:
logger.error(
f"Error during TTL refresh update for search: {e}"
)
if "score" in query: # Vector search query
items = [
_row_to_search_item(
@@ -1410,7 +1385,7 @@ class SqliteStore(BaseSqliteStore, BaseStore):
for row in rows
]
results[original_op_idx] = items
results[idx] = items
def _batch_list_namespaces_ops(
self,
@@ -1419,7 +1394,7 @@ class SqliteStore(BaseSqliteStore, BaseStore):
cur: sqlite3.Cursor,
) -> None:
queries = self._get_batch_list_namespaces_queries(list_ops)
for (query, params), (idx, _) in zip(queries, list_ops, strict=False):
for (query, params), (idx, _) in zip(queries, list_ops):
cur.execute(query, params)
results[idx] = [_decode_ns_text(row[0]) for row in cur.fetchall()]
+8 -19
View File
@@ -4,43 +4,34 @@ build-backend = "hatchling.build"
[project]
name = "langgraph-checkpoint-sqlite"
version = "3.0.0"
version = "2.0.11"
description = "Library with a SQLite implementation of LangGraph checkpoint saver."
authors = []
requires-python = ">=3.10"
requires-python = ">=3.9"
readme = "README.md"
license = "MIT"
license-files = ['LICENSE']
dependencies = [
"langgraph-checkpoint>=3,<4.0.0",
"langgraph-checkpoint>=2.0.21,<3.0.0",
"aiosqlite>=0.20",
"sqlite-vec>=0.1.6",
]
[project.urls]
Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/checkpoint-sqlite"
Twitter = "https://x.com/LangChainAI"
Slack = "https://www.langchain.com/join-community"
Reddit = "https://www.reddit.com/r/LangChain/"
Repository = "https://www.github.com/langchain-ai/langgraph"
[dependency-groups]
test = [
dev = [
"ruff",
"codespell",
"pytest",
"pytest-asyncio",
"pytest-mock",
"pytest-watcher",
"mypy",
"langgraph-checkpoint",
"pytest-retry>=1.7.0",
]
lint = [
"ruff",
"codespell",
"mypy",
]
dev = [
{include-group = "test"},
{include-group = "lint"},
]
[tool.uv]
default-groups = ['dev']
@@ -62,10 +53,8 @@ lint.select = [
"UP", # pyupgrade
"B", # flake8-bugbear
"I", # isort
"UP", # pyupgrade
]
lint.ignore = ["E501", "B008"]
target-version = "py310"
[tool.pytest-watcher]
now = true
@@ -2,13 +2,13 @@ from typing import Any
import pytest
from langchain_core.runnables import RunnableConfig
from langgraph.checkpoint.base import (
Checkpoint,
CheckpointMetadata,
create_checkpoint,
empty_checkpoint,
)
from langgraph.checkpoint.sqlite.aio import AsyncSqliteSaver
@@ -5,9 +5,10 @@ import tempfile
import uuid
from collections.abc import AsyncIterator, Generator, Iterable
from contextlib import asynccontextmanager
from typing import cast
from typing import Optional, Union, cast
import pytest
from langgraph.store.base import (
GetOp,
Item,
@@ -15,7 +16,6 @@ from langgraph.store.base import (
PutOp,
SearchOp,
)
from langgraph.store.sqlite import AsyncSqliteStore
from langgraph.store.sqlite.base import SqliteIndexConfig
from tests.test_store import CharacterEmbeddings
@@ -51,7 +51,7 @@ def fake_embeddings() -> CharacterEmbeddings:
async def create_vector_store(
fake_embeddings: CharacterEmbeddings,
conn_string: str = ":memory:",
text_fields: list[str] | None = None,
text_fields: Optional[list[str]] = None,
) -> AsyncIterator[AsyncSqliteStore]:
"""Create an AsyncSqliteStore with vector search capabilities."""
index_config: SqliteIndexConfig = {
@@ -168,7 +168,7 @@ async def test_abatch_order(store: AsyncSqliteStore) -> None:
]
results = await store.abatch(
cast(Iterable[GetOp | PutOp | SearchOp | ListNamespacesOp], ops)
cast(Iterable[Union[GetOp, PutOp, SearchOp, ListNamespacesOp]], ops)
)
assert len(results) == 5
assert isinstance(results[0], Item)
@@ -193,7 +193,7 @@ async def test_abatch_order(store: AsyncSqliteStore) -> None:
]
results_reordered = await store.abatch(
cast(Iterable[GetOp | PutOp | SearchOp | ListNamespacesOp], ops_reordered)
cast(Iterable[Union[GetOp, PutOp, SearchOp, ListNamespacesOp]], ops_reordered)
)
assert len(results_reordered) == 5
assert isinstance(results_reordered[0], list)
@@ -681,7 +681,7 @@ async def test_search_items(
fake_embeddings, text_fields=["key0", "key1", "key3"]
) as store:
# Insert test data
for ns, item in zip(test_namespaces, test_items, strict=False):
for ns, item in zip(test_namespaces, test_items):
key = f"item_{ns[-1]}"
await store.aput(ns, key, item)
+2 -12
View File
@@ -2,13 +2,13 @@ from typing import Any, cast
import pytest
from langchain_core.runnables import RunnableConfig
from langgraph.checkpoint.base import (
Checkpoint,
CheckpointMetadata,
create_checkpoint,
empty_checkpoint,
)
from langgraph.checkpoint.sqlite import SqliteSaver
from langgraph.checkpoint.sqlite.utils import _metadata_predicate, search_where
@@ -116,17 +116,7 @@ class TestSqliteSaver:
search_results_5[1].config["configurable"]["checkpoint_ns"],
} == {"", "inner"}
# search with before param
search_results_6 = list(saver.list(None, before=search_results_5[1].config))
assert len(search_results_6) == 1
assert search_results_6[0].config["configurable"]["thread_id"] == "thread-1"
# search with limit param
search_results_7 = list(
saver.list({"configurable": {"thread_id": "thread-2"}}, limit=1)
)
assert len(search_results_7) == 1
assert search_results_7[0].config["configurable"]["thread_id"] == "thread-2"
# TODO: test before and limit params
def test_search_where(self) -> None:
# call method / assertions
+8 -36
View File
@@ -5,10 +5,11 @@ import tempfile
import uuid
from collections.abc import Generator, Iterable
from contextlib import contextmanager
from typing import Any, Literal, cast
from typing import Any, Literal, Optional, Union, cast
import pytest
from langchain_core.embeddings import Embeddings
from langgraph.store.base import (
GetOp,
Item,
@@ -17,7 +18,6 @@ from langgraph.store.base import (
PutOp,
SearchOp,
)
from langgraph.store.sqlite import SqliteStore
from langgraph.store.sqlite.base import SqliteIndexConfig
@@ -110,7 +110,7 @@ VECTOR_TYPES = ["cosine"] # SQLite only supports cosine similarity
@contextmanager
def create_vector_store(
fake_embeddings: CharacterEmbeddings,
text_fields: list[str] | None = None,
text_fields: Optional[list[str]] = None,
distance_type: str = "cosine",
conn_type: Literal["memory", "file"] = "memory",
) -> Generator[SqliteStore, None, None]:
@@ -153,7 +153,7 @@ def test_batch_order(store: SqliteStore) -> None:
]
results = store.batch(
cast(Iterable[GetOp | PutOp | SearchOp | ListNamespacesOp], ops)
cast(Iterable[Union[GetOp, PutOp, SearchOp, ListNamespacesOp]], ops)
)
assert len(results) == 5
assert isinstance(results[0], Item)
@@ -182,7 +182,7 @@ def test_batch_order(store: SqliteStore) -> None:
]
results_reordered = store.batch(
cast(Iterable[GetOp | PutOp | SearchOp | ListNamespacesOp], ops_reordered)
cast(Iterable[Union[GetOp, PutOp, SearchOp, ListNamespacesOp]], ops_reordered)
)
assert len(results_reordered) == 5
assert isinstance(results_reordered[0], list)
@@ -301,7 +301,7 @@ def test_batch_list_namespaces_ops(store: SqliteStore) -> None:
]
results = store.batch(
cast(Iterable[GetOp | PutOp | SearchOp | ListNamespacesOp], ops)
cast(Iterable[Union[GetOp, PutOp, SearchOp, ListNamespacesOp]], ops)
)
assert len(results) == 3
@@ -778,7 +778,7 @@ def _cosine_similarity(X: list[float], Y: list[list[float]]) -> list[float]:
similarities = []
for y in Y:
dot_product = sum(a * b for a, b in zip(X, y, strict=False))
dot_product = sum(a * b for a, b in zip(X, y))
norm1 = sum(a * a for a in X) ** 0.5
norm2 = sum(a * a for a in y) ** 0.5
similarity = dot_product / (norm1 * norm2) if norm1 > 0 and norm2 > 0 else 0.0
@@ -1011,7 +1011,7 @@ def test_search_items(
fake_embeddings, text_fields=["key0", "key1", "key3"]
) as store:
# Insert test data
for ns, item in zip(test_namespaces, test_items, strict=False):
for ns, item in zip(test_namespaces, test_items):
key = f"item_{ns[-1]}"
store.put(ns, key, item)
@@ -1067,31 +1067,3 @@ def test_sql_injection_vulnerability(store: SqliteStore) -> None:
with pytest.raises(ValueError, match="Invalid filter key"):
store.search(("docs",), filter={malicious_key: "dummy"})
@pytest.mark.parametrize("distance_type", VECTOR_TYPES)
def test_non_ascii(
fake_embeddings: CharacterEmbeddings,
distance_type: str,
) -> None:
"""Test support for non-ascii characters"""
with create_vector_store(fake_embeddings, distance_type=distance_type) as store:
store.put(("user_123", "memories"), "1", {"text": "这是中文"}) # Chinese
store.put(
("user_123", "memories"), "2", {"text": "これは日本語です"}
) # Japanese
store.put(("user_123", "memories"), "3", {"text": "이건 한국어야"}) # Korean
store.put(("user_123", "memories"), "4", {"text": "Это русский"}) # Russian
store.put(("user_123", "memories"), "5", {"text": "यह रूसी है"}) # Hindi
result1 = store.search(("user_123", "memories"), query="这是中文")
result2 = store.search(("user_123", "memories"), query="これは日本語です")
result3 = store.search(("user_123", "memories"), query="이건 한국어야")
result4 = store.search(("user_123", "memories"), query="Это русский")
result5 = store.search(("user_123", "memories"), query="यह रूसी है")
assert result1[0].key == "1"
assert result2[0].key == "2"
assert result3[0].key == "3"
assert result4[0].key == "4"
assert result5[0].key == "5"
+2 -76
View File
@@ -7,7 +7,6 @@ import time
from collections.abc import Generator
import pytest
from langgraph.store.base import TTLConfig
from langgraph.store.sqlite import SqliteStore
from langgraph.store.sqlite.aio import AsyncSqliteStore
@@ -94,13 +93,9 @@ def test_ttl_sweeper(temp_db_file: str) -> None:
ttl_seconds = 2
ttl_minutes = ttl_seconds / 60
ttl_config: TTLConfig = {
"default_ttl": ttl_minutes,
"sweep_interval_minutes": ttl_minutes / 2,
}
with SqliteStore.from_conn_string(
temp_db_file,
ttl=ttl_config,
ttl={"default_ttl": ttl_minutes, "sweep_interval_minutes": ttl_minutes / 2},
) as store:
store.setup()
@@ -303,14 +298,9 @@ async def test_async_ttl_sweeper(temp_db_file: str) -> None:
ttl_seconds = 2
ttl_minutes = ttl_seconds / 60
ttl_config: TTLConfig = {
"default_ttl": ttl_minutes,
"sweep_interval_minutes": ttl_minutes / 2,
}
async with AsyncSqliteStore.from_conn_string(
temp_db_file,
ttl=ttl_config,
ttl={"default_ttl": ttl_minutes, "sweep_interval_minutes": ttl_minutes / 2},
) as store:
await store.setup()
@@ -363,67 +353,3 @@ async def test_async_search_with_ttl(temp_db_file: str) -> None:
# Search after expiration
results = await store.asearch(("test",), filter={"value": "apple"})
assert len(results) == 0
@pytest.mark.asyncio
@pytest.mark.flaky(retries=3)
async def test_async_asearch_refresh_ttl(temp_db_file: str) -> None:
"""Test TTL refresh on asearch with async API."""
ttl_seconds = 4.0 # Increased TTL for less sensitivity to timing
ttl_minutes = ttl_seconds / 60.0
async with AsyncSqliteStore.from_conn_string(
temp_db_file, ttl={"default_ttl": ttl_minutes, "refresh_on_read": True}
) as store:
await store.setup()
namespace = ("docs", "user1")
# t=0: items put, expire at t=4.0s
await store.aput(namespace, "item1", {"text": "content1", "id": 1})
await store.aput(namespace, "item2", {"text": "content2", "id": 2})
# t=3.0s: (after sleep ttl_seconds * 0.75 = 3s)
await asyncio.sleep(ttl_seconds * 0.75)
# Perform asearch with refresh_ttl=True for item1.
# item1's TTL should be refreshed. New expiry: t=3.0s + 4.0s = t=7.0s.
# item2's TTL is not affected. Expires at t=4.0s.
searched_items = await store.asearch(
namespace, filter={"id": 1}, refresh_ttl=True
)
assert len(searched_items) == 1
assert searched_items[0].key == "item1"
# t=5.0s: (after sleep ttl_seconds * 0.5 = 2s more. Total elapsed: 3s + 2s = 5s)
await asyncio.sleep(ttl_seconds * 0.5)
# At this point:
# - item1 (refreshed by asearch) should expire at t=7.0s. Should be ALIVE.
# - item2 (original TTL) should have expired at t=4.0s. Should be GONE after sweep.
await store.sweep_ttl()
# Check item1 (should exist due to asearch refresh)
item1_check1 = await store.aget(namespace, "item1", refresh_ttl=False)
assert item1_check1 is not None, (
"Item1 should exist after asearch refresh and first sweep"
)
assert item1_check1.value["text"] == "content1"
# Check item2 (should be gone)
item2_check1 = await store.aget(namespace, "item2", refresh_ttl=False)
assert item2_check1 is None, (
"Item2 should be gone after its original TTL expired"
)
# t=7.5s: (after sleep ttl_seconds * 0.625 = 2.5s more. Total elapsed: 5s + 2.5s = 7.5s)
await asyncio.sleep(ttl_seconds * 0.625)
# At this point:
# - item1 (refreshed by asearch, expired at t=7.0s) should be GONE after sweep.
await store.sweep_ttl()
# Check item1 again (should be gone now)
item1_final_check = await store.aget(namespace, "item1", refresh_ttl=False)
assert item1_final_check is None, (
"Item1 should be gone after its refreshed TTL expired"
)
+593 -573
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File diff suppressed because it is too large Load Diff
+1 -3
View File
@@ -38,10 +38,8 @@ Each checkpointer should conform to `langgraph.checkpoint.base.BaseCheckpointSav
- `.put_writes` - Store intermediate writes linked to a checkpoint (i.e. pending writes).
- `.get_tuple` - Fetch a checkpoint tuple using for a given configuration (`thread_id` and `checkpoint_id`).
- `.list` - List checkpoints that match a given configuration and filter criteria.
- `.delete_thread()` - Delete all checkpoints and writes associated with a thread.
- `.get_next_version()` - Generate the next version ID for a channel.
If the checkpointer will be used with asynchronous graph execution (i.e. executing the graph via `.ainvoke`, `.astream`, `.abatch`), checkpointer must implement asynchronous versions of the above methods (`.aput`, `.aput_writes`, `.aget_tuple`, `.alist`). Similarly, the checkpointer must implement `.adelete_thread()` if asynchronous thread cleanup is desired. The base class provides a default implementation of `.get_next_version()` that generates an integer sequence starting from 1, but this method should be overridden for custom versioning schemes.
If the checkpointer will be used with asynchronous graph execution (i.e. executing the graph via `.ainvoke`, `.astream`, `.abatch`), checkpointer must implement asynchronous versions of the above methods (`.aput`, `.aput_writes`, `.aget_tuple`, `.alist`).
## Usage
@@ -8,6 +8,7 @@ from typing import ( # noqa: UP035
NamedTuple,
TypedDict,
TypeVar,
Union,
)
from langchain_core.runnables import RunnableConfig
@@ -34,17 +35,17 @@ class CheckpointMetadata(TypedDict, total=False):
source: Literal["input", "loop", "update", "fork"]
"""The source of the checkpoint.
- `"input"`: The checkpoint was created from an input to invoke/stream/batch.
- `"loop"`: The checkpoint was created from inside the pregel loop.
- `"update"`: The checkpoint was created from a manual state update.
- `"fork"`: The checkpoint was created as a copy of another checkpoint.
- "input": The checkpoint was created from an input to invoke/stream/batch.
- "loop": The checkpoint was created from inside the pregel loop.
- "update": The checkpoint was created from a manual state update.
- "fork": The checkpoint was created as a copy of another checkpoint.
"""
step: int
"""The step number of the checkpoint.
`-1` for the first `"input"` checkpoint.
`0` for the first `"loop"` checkpoint.
`...` for the `nth` checkpoint afterwards.
-1 for the first "input" checkpoint.
0 for the first "loop" checkpoint.
... for the nth checkpoint afterwards.
"""
parents: dict[str, str]
"""The IDs of the parent checkpoints.
@@ -53,35 +54,30 @@ class CheckpointMetadata(TypedDict, total=False):
"""
ChannelVersions = dict[str, str | int | float]
ChannelVersions = dict[str, Union[str, int, float]]
class Checkpoint(TypedDict):
"""State snapshot at a given point in time."""
v: int
"""The version of the checkpoint format. Currently `1`."""
"""The version of the checkpoint format. Currently 1."""
id: str
"""The ID of the checkpoint.
This is both unique and monotonically increasing, so can be used for sorting
checkpoints from first to last."""
"""The ID of the checkpoint. This is both unique and monotonically
increasing, so can be used for sorting checkpoints from first to last."""
ts: str
"""The timestamp of the checkpoint in ISO 8601 format."""
channel_values: dict[str, Any]
"""The values of the channels at the time of the checkpoint.
Mapping from channel name to deserialized channel snapshot value.
"""
channel_versions: ChannelVersions
"""The versions of the channels at the time of the checkpoint.
The keys are channel names and the values are monotonically increasing
version strings for each channel.
"""
versions_seen: dict[str, ChannelVersions]
"""Map from node ID to map from channel name to version seen.
This keeps track of the versions of the channels that each node has seen.
Used to determine which nodes to execute next.
"""
@@ -152,7 +148,7 @@ class BaseCheckpointSaver(Generic[V]):
config: Configuration specifying which checkpoint to retrieve.
Returns:
The requested checkpoint, or `None` if not found.
Optional[Checkpoint]: The requested checkpoint, or None if not found.
"""
if value := self.get_tuple(config):
return value.checkpoint
@@ -164,7 +160,7 @@ class BaseCheckpointSaver(Generic[V]):
config: Configuration specifying which checkpoint to retrieve.
Returns:
The requested checkpoint tuple, or `None` if not found.
Optional[CheckpointTuple]: The requested checkpoint tuple, or None if not found.
Raises:
NotImplementedError: Implement this method in your custom checkpoint saver.
@@ -188,7 +184,7 @@ class BaseCheckpointSaver(Generic[V]):
limit: Maximum number of checkpoints to return.
Returns:
Iterator of matching checkpoint tuples.
Iterator[CheckpointTuple]: Iterator of matching checkpoint tuples.
Raises:
NotImplementedError: Implement this method in your custom checkpoint saver.
@@ -256,7 +252,7 @@ class BaseCheckpointSaver(Generic[V]):
config: Configuration specifying which checkpoint to retrieve.
Returns:
The requested checkpoint, or `None` if not found.
Optional[Checkpoint]: The requested checkpoint, or None if not found.
"""
if value := await self.aget_tuple(config):
return value.checkpoint
@@ -268,7 +264,7 @@ class BaseCheckpointSaver(Generic[V]):
config: Configuration specifying which checkpoint to retrieve.
Returns:
The requested checkpoint tuple, or `None` if not found.
Optional[CheckpointTuple]: The requested checkpoint tuple, or None if not found.
Raises:
NotImplementedError: Implement this method in your custom checkpoint saver.
@@ -292,7 +288,7 @@ class BaseCheckpointSaver(Generic[V]):
limit: Maximum number of checkpoints to return.
Returns:
Async iterator of matching checkpoint tuples.
AsyncIterator[CheckpointTuple]: Async iterator of matching checkpoint tuples.
Raises:
NotImplementedError: Implement this method in your custom checkpoint saver.
@@ -357,12 +353,11 @@ class BaseCheckpointSaver(Generic[V]):
def get_next_version(self, current: V | None, channel: None) -> V:
"""Generate the next version ID for a channel.
Default is to use integer versions, incrementing by `1`.
If you override, you can use `str`/`int`/`float` versions, as long as they are monotonically increasing.
Default is to use integer versions, incrementing by 1. If you override, you can use str/int/float versions,
as long as they are monotonically increasing.
Args:
current: The current version identifier (`int`, `float`, or `str`).
current: The current version identifier (int, float, or str).
channel: Deprecated argument, kept for backwards compatibility.
Returns:
@@ -409,16 +404,6 @@ def get_checkpoint_metadata(
return metadata
def get_serializable_checkpoint_metadata(
config: RunnableConfig, metadata: CheckpointMetadata
) -> CheckpointMetadata:
"""Get checkpoint metadata in a backwards-compatible manner."""
checkpoint_metadata = get_checkpoint_metadata(config, metadata)
if "writes" in checkpoint_metadata:
checkpoint_metadata.pop("writes")
return checkpoint_metadata
"""
Mapping from error type to error index.
Regular writes just map to their index in the list of writes being saved.
@@ -33,34 +33,33 @@ class InMemorySaver(
):
"""An in-memory checkpoint saver.
This checkpoint saver stores checkpoints in memory using a `defaultdict`.
This checkpoint saver stores checkpoints in memory using a defaultdict.
Note:
Only use `InMemorySaver` for debugging or testing purposes.
For production use cases we recommend installing [langgraph-checkpoint-postgres](https://pypi.org/project/langgraph-checkpoint-postgres/) and using `PostgresSaver` / `AsyncPostgresSaver`.
If you are using LangSmith Deployment, no checkpointer needs to be specified. The correct managed checkpointer will be used automatically.
If you are using the LangGraph Platform, no checkpointer needs to be specified. The correct managed checkpointer will be used automatically.
Args:
serde: The serializer to use for serializing and deserializing checkpoints.
serde: The serializer to use for serializing and deserializing checkpoints. Defaults to None.
Example:
```python
import asyncio
Examples:
from langgraph.checkpoint.memory import InMemorySaver
from langgraph.graph import StateGraph
import asyncio
builder = StateGraph(int)
builder.add_node("add_one", lambda x: x + 1)
builder.set_entry_point("add_one")
builder.set_finish_point("add_one")
from langgraph.checkpoint.memory import InMemorySaver
from langgraph.graph import StateGraph
memory = InMemorySaver()
graph = builder.compile(checkpointer=memory)
coro = graph.ainvoke(1, {"configurable": {"thread_id": "thread-1"}})
asyncio.run(coro) # Output: 2
```
builder = StateGraph(int)
builder.add_node("add_one", lambda x: x + 1)
builder.set_entry_point("add_one")
builder.set_finish_point("add_one")
memory = InMemorySaver()
graph = builder.compile(checkpointer=memory)
coro = graph.ainvoke(1, {"configurable": {"thread_id": "thread-1"}})
asyncio.run(coro) # Output: 2
"""
# thread ID -> checkpoint NS -> checkpoint ID -> checkpoint mapping
@@ -97,8 +96,7 @@ class InMemorySaver(
self.stack.enter_context(self.blobs) # type: ignore[arg-type]
def __enter__(self) -> InMemorySaver:
self.stack.__enter__()
return self
return self.stack.__enter__()
def __exit__(
self,
@@ -109,8 +107,7 @@ class InMemorySaver(
return self.stack.__exit__(exc_type, exc_value, traceback)
async def __aenter__(self) -> InMemorySaver:
self.stack.__enter__()
return self
return self.stack.__enter__()
async def __aexit__(
self,
@@ -136,7 +133,7 @@ class InMemorySaver(
"""Get a checkpoint tuple from the in-memory storage.
This method retrieves a checkpoint tuple from the in-memory storage based on the
provided config. If the config contains a `checkpoint_id` key, the checkpoint with
provided config. If the config contains a "checkpoint_id" key, the checkpoint with
the matching thread ID and timestamp is retrieved. Otherwise, the latest checkpoint
for the given thread ID is retrieved.
@@ -144,7 +141,7 @@ class InMemorySaver(
config: The config to use for retrieving the checkpoint.
Returns:
The retrieved checkpoint tuple, or None if no matching checkpoint was found.
Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found.
"""
thread_id: str = config["configurable"]["thread_id"]
checkpoint_ns: str = config["configurable"].get("checkpoint_ns", "")
@@ -234,7 +231,7 @@ class InMemorySaver(
limit: Maximum number of checkpoints to return.
Yields:
An iterator of matching checkpoint tuples.
Iterator[CheckpointTuple]: An iterator of matching checkpoint tuples.
"""
thread_ids = (config["configurable"]["thread_id"],) if config else self.storage
config_checkpoint_ns = (
@@ -426,16 +423,16 @@ class InMemorySaver(
del self.blobs[k]
async def aget_tuple(self, config: RunnableConfig) -> CheckpointTuple | None:
"""Asynchronous version of `get_tuple`.
"""Asynchronous version of get_tuple.
This method is an asynchronous wrapper around `get_tuple` that runs the synchronous
This method is an asynchronous wrapper around get_tuple that runs the synchronous
method in a separate thread using asyncio.
Args:
config: The config to use for retrieving the checkpoint.
Returns:
The retrieved checkpoint tuple, or None if no matching checkpoint was found.
Optional[CheckpointTuple]: The retrieved checkpoint tuple, or None if no matching checkpoint was found.
"""
return self.get_tuple(config)
@@ -447,16 +444,16 @@ class InMemorySaver(
before: RunnableConfig | None = None,
limit: int | None = None,
) -> AsyncIterator[CheckpointTuple]:
"""Asynchronous version of `list`.
"""Asynchronous version of list.
This method is an asynchronous wrapper around `list` that runs the synchronous
This method is an asynchronous wrapper around list that runs the synchronous
method in a separate thread using asyncio.
Args:
config: The config to use for listing the checkpoints.
Yields:
An asynchronous iterator of checkpoint tuples.
AsyncIterator[CheckpointTuple]: An asynchronous iterator of checkpoint tuples.
"""
for item in self.list(config, filter=filter, before=before, limit=limit):
yield item
@@ -468,7 +465,7 @@ class InMemorySaver(
metadata: CheckpointMetadata,
new_versions: ChannelVersions,
) -> RunnableConfig:
"""Asynchronous version of `put`.
"""Asynchronous version of put.
Args:
config: The config to associate with the checkpoint.
@@ -488,9 +485,9 @@ class InMemorySaver(
task_id: str,
task_path: str = "",
) -> None:
"""Asynchronous version of `put_writes`.
"""Asynchronous version of put_writes.
This method is an asynchronous wrapper around `put_writes` that runs the synchronous
This method is an asynchronous wrapper around put_writes that runs the synchronous
method in a separate thread using asyncio.
Args:
@@ -1,6 +1,6 @@
from __future__ import annotations
from typing import Any, Protocol, runtime_checkable
from typing import Any, Protocol
class UntypedSerializerProtocol(Protocol):
@@ -11,12 +11,13 @@ class UntypedSerializerProtocol(Protocol):
def loads(self, data: bytes) -> Any: ...
@runtime_checkable
class SerializerProtocol(Protocol):
class SerializerProtocol(UntypedSerializerProtocol, Protocol):
"""Protocol for serialization and deserialization of objects.
- `dumps_typed`: Serialize an object to a tuple `(type, bytes)`.
- `loads_typed`: Deserialize an object from a tuple `(type, bytes)`.
- `dumps`: Serialize an object to bytes.
- `dumps_typed`: Serialize an object to a tuple (type, bytes).
- `loads`: Deserialize an object from bytes.
- `loads_typed`: Deserialize an object from a tuple (type, bytes).
Valid implementations include the `pickle`, `json` and `orjson` modules.
"""
@@ -30,6 +31,12 @@ class SerializerCompat(SerializerProtocol):
def __init__(self, serde: UntypedSerializerProtocol) -> None:
self.serde = serde
def dumps(self, obj: Any) -> bytes:
return self.serde.dumps(obj)
def loads(self, data: bytes) -> Any:
return self.serde.loads(data)
def dumps_typed(self, obj: Any) -> tuple[str, bytes]:
return type(obj).__name__, self.serde.dumps(obj)
@@ -42,7 +49,7 @@ def maybe_add_typed_methods(
) -> SerializerProtocol:
"""Wrap serde old serde implementations in a class with loads_typed and dumps_typed for backwards compatibility."""
if not isinstance(serde, SerializerProtocol):
if not hasattr(serde, "loads_typed") or not hasattr(serde, "dumps_typed"):
return SerializerCompat(serde)
return serde
@@ -50,13 +57,12 @@ def maybe_add_typed_methods(
class CipherProtocol(Protocol):
"""Protocol for encryption and decryption of data.
- `encrypt`: Encrypt plaintext.
- `decrypt`: Decrypt ciphertext.
"""
def encrypt(self, plaintext: bytes) -> tuple[str, bytes]:
"""Encrypt plaintext. Returns a tuple `(cipher name, ciphertext)`."""
"""Encrypt plaintext. Returns a tuple (cipher name, ciphertext)."""
...
def decrypt(self, ciphername: str, ciphertext: bytes) -> bytes:
@@ -14,8 +14,14 @@ class EncryptedSerializer(SerializerProtocol):
self.cipher = cipher
self.serde = serde
def dumps(self, obj: Any) -> bytes:
return self.serde.dumps(obj)
def loads(self, data: bytes) -> Any:
return self.serde.loads(data)
def dumps_typed(self, obj: Any) -> tuple[str, bytes]:
"""Serialize an object to a tuple `(type, bytes)` and encrypt the bytes."""
"""Serialize an object to a tuple (type, bytes) and encrypt the bytes."""
# serialize data
typ, data = self.serde.dumps_typed(obj)
# encrypt data
@@ -39,7 +45,7 @@ class EncryptedSerializer(SerializerProtocol):
def from_pycryptodome_aes(
cls, serde: SerializerProtocol = JsonPlusSerializer(), **kwargs: Any
) -> "EncryptedSerializer":
"""Create an `EncryptedSerializer` using AES encryption."""
"""Create an EncryptedSerializer using AES encryption."""
try:
from Crypto.Cipher import AES # type: ignore
except ImportError:
@@ -4,13 +4,12 @@ import dataclasses
import decimal
import importlib
import json
import logging
import pathlib
import pickle
import re
import sys
from collections import deque
from collections.abc import Callable, Sequence
from collections.abc import Sequence
from datetime import date, datetime, time, timedelta, timezone
from enum import Enum
from inspect import isclass
@@ -22,12 +21,13 @@ from ipaddress import (
IPv6Interface,
IPv6Network,
)
from typing import Any, Literal
from typing import Any, Callable, cast
from uuid import UUID
from zoneinfo import ZoneInfo
import ormsgpack
from langchain_core.load.load import Reviver
from langchain_core.load.serializable import Serializable
from langgraph.checkpoint.serde.base import SerializerProtocol
from langgraph.checkpoint.serde.types import SendProtocol
@@ -35,33 +35,18 @@ from langgraph.store.base import Item
LC_REVIVER = Reviver()
EMPTY_BYTES = b""
logger = logging.getLogger(__name__)
class JsonPlusSerializer(SerializerProtocol):
"""Serializer that uses ormsgpack, with optional fallbacks.
!!! warning
Security note: This serializer is intended for use within the `BaseCheckpointSaver`
class and called within the Pregel loop. It should not be used on untrusted
python objects. If an attacker can write directly to your checkpoint database,
they may be able to trigger code execution when data is deserialized.
"""
"""Serializer that uses ormsgpack, with a fallback to extended JSON serializer."""
def __init__(
self,
*,
pickle_fallback: bool = False,
allowed_json_modules: Sequence[tuple[str, ...]] | Literal[True] | None = None,
__unpack_ext_hook__: Callable[[int, bytes], Any] | None = None,
) -> None:
self.pickle_fallback = pickle_fallback
self._allowed_modules = (
{mod_and_name for mod_and_name in allowed_json_modules}
if allowed_json_modules and allowed_json_modules is not True
else (allowed_json_modules if allowed_json_modules is True else None)
)
self._unpack_ext_hook = (
__unpack_ext_hook__
if __unpack_ext_hook__ is not None
@@ -89,90 +74,134 @@ class JsonPlusSerializer(SerializerProtocol):
out["kwargs"] = kwargs
return out
def _default(self, obj: Any) -> str | dict[str, Any]:
if isinstance(obj, Serializable):
return cast(dict[str, Any], obj.to_json())
elif hasattr(obj, "model_dump") and callable(obj.model_dump):
return self._encode_constructor_args(
obj.__class__, method=(None, "model_construct"), kwargs=obj.model_dump()
)
elif hasattr(obj, "dict") and callable(obj.dict):
return self._encode_constructor_args(
obj.__class__, method=(None, "construct"), kwargs=obj.dict()
)
elif hasattr(obj, "_asdict") and callable(obj._asdict):
return self._encode_constructor_args(obj.__class__, kwargs=obj._asdict())
elif isinstance(obj, pathlib.Path):
return self._encode_constructor_args(pathlib.Path, args=obj.parts)
elif isinstance(obj, re.Pattern):
return self._encode_constructor_args(
re.compile, args=(obj.pattern, obj.flags)
)
elif isinstance(obj, UUID):
return self._encode_constructor_args(UUID, args=(obj.hex,))
elif isinstance(obj, decimal.Decimal):
return self._encode_constructor_args(decimal.Decimal, args=(str(obj),))
elif isinstance(obj, (set, frozenset, deque)):
return self._encode_constructor_args(type(obj), args=(tuple(obj),))
elif isinstance(obj, (IPv4Address, IPv4Interface, IPv4Network)):
return self._encode_constructor_args(obj.__class__, args=(str(obj),))
elif isinstance(obj, (IPv6Address, IPv6Interface, IPv6Network)):
return self._encode_constructor_args(obj.__class__, args=(str(obj),))
elif isinstance(obj, datetime):
return self._encode_constructor_args(
datetime, method="fromisoformat", args=(obj.isoformat(),)
)
elif isinstance(obj, timezone):
return self._encode_constructor_args(
timezone,
args=obj.__getinitargs__(), # type: ignore[attr-defined]
)
elif isinstance(obj, ZoneInfo):
return self._encode_constructor_args(ZoneInfo, args=(obj.key,))
elif isinstance(obj, timedelta):
return self._encode_constructor_args(
timedelta, args=(obj.days, obj.seconds, obj.microseconds)
)
elif isinstance(obj, date):
return self._encode_constructor_args(
date, args=(obj.year, obj.month, obj.day)
)
elif isinstance(obj, time):
return self._encode_constructor_args(
time,
args=(obj.hour, obj.minute, obj.second, obj.microsecond, obj.tzinfo),
kwargs={"fold": obj.fold},
)
elif dataclasses.is_dataclass(obj):
return self._encode_constructor_args(
obj.__class__,
kwargs={
field.name: getattr(obj, field.name)
for field in dataclasses.fields(obj)
},
)
elif isinstance(obj, Enum):
return self._encode_constructor_args(obj.__class__, args=(obj.value,))
elif isinstance(obj, SendProtocol):
return self._encode_constructor_args(
obj.__class__, kwargs={"node": obj.node, "arg": obj.arg}
)
elif isinstance(obj, (bytes, bytearray)):
return self._encode_constructor_args(
obj.__class__, method="fromhex", args=(obj.hex(),)
)
elif isinstance(obj, BaseException):
return repr(obj)
else:
raise TypeError(
f"Object of type {obj.__class__.__name__} is not JSON serializable"
)
def _reviver(self, value: dict[str, Any]) -> Any:
if self._allowed_modules and (
if (
value.get("lc", None) == 2
and value.get("type", None) == "constructor"
and value.get("id", None) is not None
):
try:
return self._revive_lc2(value)
except InvalidModuleError as e:
logger.warning(
"Object %s is not in the deserialization allowlist.\n%s",
value["id"],
e.message,
)
# Get module and class name
[*module, name] = value["id"]
# Import module
mod = importlib.import_module(".".join(module))
# Import class
cls = getattr(mod, name)
# Instantiate class
method = value.get("method")
if isinstance(method, str):
methods = [getattr(cls, method)]
elif isinstance(method, list):
methods = [
cls if method is None else getattr(cls, method)
for method in method
]
else:
methods = [cls]
args = value.get("args")
kwargs = value.get("kwargs")
for method in methods:
try:
if isclass(method) and issubclass(method, BaseException):
return None
if args and kwargs:
return method(*args, **kwargs)
elif args:
return method(*args)
elif kwargs:
return method(**kwargs)
else:
return method()
except Exception:
continue
except Exception:
return None
return LC_REVIVER(value)
def _revive_lc2(self, value: dict[str, Any]) -> Any:
self._check_allowed_modules(value)
[*module, name] = value["id"]
try:
mod = importlib.import_module(".".join(module))
cls = getattr(mod, name)
method = value.get("method")
if isinstance(method, str):
methods = [getattr(cls, method)]
elif isinstance(method, list):
methods = [cls if m is None else getattr(cls, m) for m in method]
else:
methods = [cls]
args = value.get("args")
kwargs = value.get("kwargs")
for method in methods:
try:
if isclass(method) and issubclass(method, BaseException):
return None
if args and kwargs:
return method(*args, **kwargs)
elif args:
return method(*args)
elif kwargs:
return method(**kwargs)
else:
return method()
except Exception:
continue
except Exception:
return None
def _check_allowed_modules(self, value: dict[str, Any]) -> None:
needed = tuple(value["id"])
method = value.get("method")
if isinstance(method, list):
method_display = ",".join(m or "<init>" for m in method)
elif isinstance(method, str):
method_display = method
else:
method_display = "<init>"
dotted = ".".join(needed)
if not self._allowed_modules:
raise InvalidModuleError(
f"Refused to deserialize JSON constructor: {dotted} (method: {method_display}). "
"No allowed_json_modules configured.\n\n"
"Unblock with ONE of:\n"
f" • JsonPlusSerializer(allowed_json_modules=[{needed!r}, ...])\n"
" • (DANGEROUS) JsonPlusSerializer(allowed_json_modules=True)\n\n"
"Note: Prefix allowlists are intentionally unsupported; prefer exact symbols "
"or plain-JSON representations revived without import-time side effects."
)
if self._allowed_modules is True:
return
if needed in self._allowed_modules:
return
raise InvalidModuleError(
f"Refused to deserialize JSON constructor: {dotted} (method: {method_display}). "
"Symbol is not in the deserialization allowlist.\n\n"
"Add exactly this symbol to unblock:\n"
f" JsonPlusSerializer(allowed_json_modules=[{needed!r}, ...])\n"
"Or, as a last resort (DANGEROUS):\n"
" JsonPlusSerializer(allowed_json_modules=True)"
def dumps(self, obj: Any) -> bytes:
return json.dumps(obj, default=self._default, ensure_ascii=False).encode(
"utf-8", "ignore"
)
def dumps_typed(self, obj: Any) -> tuple[str, bytes]:
@@ -186,10 +215,15 @@ class JsonPlusSerializer(SerializerProtocol):
try:
return "msgpack", _msgpack_enc(obj)
except ormsgpack.MsgpackEncodeError as exc:
if self.pickle_fallback:
if "valid UTF-8" in str(exc):
return "json", self.dumps(obj)
elif self.pickle_fallback:
return "pickle", pickle.dumps(obj)
raise exc
def loads(self, data: bytes) -> Any:
return json.loads(data, object_hook=self._reviver)
def loads_typed(self, data: tuple[str, bytes]) -> Any:
type_, data_ = data
if type_ == "null":
@@ -199,7 +233,7 @@ class JsonPlusSerializer(SerializerProtocol):
elif type_ == "bytearray":
return bytearray(data_)
elif type_ == "json":
return json.loads(data_, object_hook=self._reviver)
return self.loads(data_)
elif type_ == "msgpack":
return ormsgpack.unpackb(
data_, ext_hook=self._unpack_ext_hook, option=ormsgpack.OPT_NON_STR_KEYS
@@ -629,20 +663,12 @@ def _msgpack_ext_hook_to_json(code: int, data: bytes) -> Any:
return
class InvalidModuleError(Exception):
"""Exception raised when a module is not in the allowlist."""
def __init__(self, message: str):
self.message = message
_option = (
ormsgpack.OPT_NON_STR_KEYS
| ormsgpack.OPT_PASSTHROUGH_DATACLASS
| ormsgpack.OPT_PASSTHROUGH_DATETIME
| ormsgpack.OPT_PASSTHROUGH_ENUM
| ormsgpack.OPT_PASSTHROUGH_UUID
| ormsgpack.OPT_REPLACE_SURROGATES
)
@@ -1,6 +1,7 @@
from collections.abc import Sequence
from typing import (
Any,
Optional,
Protocol,
TypeVar,
runtime_checkable,
@@ -27,9 +28,9 @@ class ChannelProtocol(Protocol[Value, Update, C]):
@property
def UpdateType(self) -> Any: ...
def checkpoint(self) -> C | None: ...
def checkpoint(self) -> Optional[C]: ...
def from_checkpoint(self, checkpoint: C | None) -> Self: ...
def from_checkpoint(self, checkpoint: Optional[C]) -> Self: ...
def update(self, values: Sequence[Update]) -> bool: ...
+97 -146
View File
@@ -4,9 +4,9 @@ Stores provide long-term memory that persists across threads and conversations.
Supports hierarchical namespaces, key-value storage, and optional vector search.
Core types:
- `BaseStore`: Store interface with sync/async operations
- `Item`: Stored key-value pairs with metadata
- `Op`: Get/Put/Search/List operations
- BaseStore: Store interface with sync/async operations
- Item: Stored key-value pairs with metadata
- Op: Get/Put/Search/List operations
"""
from __future__ import annotations
@@ -19,6 +19,7 @@ from typing import (
Literal,
NamedTuple,
TypedDict,
Union,
cast,
)
@@ -56,7 +57,7 @@ class Item:
key: Unique identifier within the namespace.
namespace: Hierarchical path defining the collection in which this document resides.
Represented as a tuple of strings, allowing for nested categorization.
For example: `("documents", 'user123')`
For example: ("documents", 'user123')
created_at: Timestamp of item creation.
updated_at: Timestamp of last update.
"""
@@ -163,7 +164,6 @@ class GetOp(NamedTuple):
???+ example "Examples"
Basic item retrieval:
```python
GetOp(namespace=("users", "profiles"), key="user123")
GetOp(namespace=("cache", "embeddings"), key="doc456")
@@ -207,14 +207,11 @@ class SearchOp(NamedTuple):
within a given namespace prefix. It provides pagination through limit and offset
parameters.
!!! note
Note:
Natural language search support depends on your store implementation.
???+ example "Examples"
Search with filters and pagination:
```python
SearchOp(
namespace_prefix=("documents",),
@@ -225,7 +222,6 @@ class SearchOp(NamedTuple):
```
Natural language search:
```python
SearchOp(
namespace_prefix=("users", "content"),
@@ -253,15 +249,14 @@ class SearchOp(NamedTuple):
The filter supports both exact matches and operator-based comparisons.
Supported Operators:
- `$eq`: Equal to (same as direct value comparison)
- `$ne`: Not equal to
- `$gt`: Greater than
- `$gte`: Greater than or equal to
- `$lt`: Less than
- `$lte`: Less than or equal to
- $eq: Equal to (same as direct value comparison)
- $ne: Not equal to
- $gt: Greater than
- $gte: Greater than or equal to
- $lt: Less than
- $lte: Less than or equal to
???+ example "Examples"
Simple exact match:
```python
@@ -294,7 +289,6 @@ class SearchOp(NamedTuple):
"""Natural language search query for semantic search capabilities.
???+ example "Examples"
- "technical documentation about REST APIs"
- "machine learning papers from 2023"
"""
@@ -308,11 +302,10 @@ class SearchOp(NamedTuple):
# Type representing a namespace path that can include wildcards
NamespacePath = tuple[str | Literal["*"], ...]
NamespacePath = tuple[Union[str, Literal["*"]], ...]
"""A tuple representing a namespace path that can include wildcards.
???+ example "Examples"
```python
("users",) # Exact users namespace
("documents", "*") # Any sub-namespace under documents
@@ -338,21 +331,17 @@ class MatchCondition(NamedTuple):
hierarchies.
???+ example "Examples"
Prefix matching:
```python
MatchCondition(match_type="prefix", path=("users", "profiles"))
```
Suffix matching with wildcard:
```python
MatchCondition(match_type="suffix", path=("cache", "*"))
```
Simple suffix matching:
```python
MatchCondition(match_type="suffix", path=("v1",))
```
@@ -373,8 +362,7 @@ class ListNamespacesOp(NamedTuple):
???+ example "Examples"
List all namespaces under the `"documents"` path:
List all namespaces under the "documents" path:
```python
ListNamespacesOp(
match_conditions=(MatchCondition(match_type="prefix", path=("documents",)),),
@@ -382,8 +370,7 @@ class ListNamespacesOp(NamedTuple):
)
```
List all namespaces that end with `"v1"`:
List all namespaces that end with "v1":
```python
ListNamespacesOp(
match_conditions=(MatchCondition(match_type="suffix", path=("v1",)),),
@@ -397,15 +384,12 @@ class ListNamespacesOp(NamedTuple):
"""Optional conditions for filtering namespaces.
???+ example "Examples"
All user namespaces:
```python
(MatchCondition(match_type="prefix", path=("users",)),)
```
All namespaces that start with `"docs"` and end with `"draft"`:
All namespaces that start with "docs" and end with "draft":
```python
(
MatchCondition(match_type="prefix", path=("docs",)),
@@ -442,21 +426,17 @@ class PutOp(NamedTuple):
Each element in the tuple represents one level in the hierarchy.
???+ example "Examples"
Root level documents:
Root level documents
```python
("documents",)
```
User-specific documents:
User-specific documents
```python
("documents", "user123")
```
Nested cache structure:
Nested cache structure
```python
("cache", "embeddings", "v1")
```
@@ -469,15 +449,15 @@ class PutOp(NamedTuple):
Together with the namespace, it forms a complete path to the item.
Example:
If namespace is `("documents", "user123")` and key is `"report1"`,
the full path would effectively be `"documents/user123/report1"`
If namespace is ("documents", "user123") and key is "report1",
the full path would effectively be "documents/user123/report1"
"""
value: dict[str, Any] | None
"""The data to store, or `None` to mark the item for deletion.
"""The data to store, or None to mark the item for deletion.
The value must be a dictionary with string keys and JSON-serializable values.
Setting this to `None` signals that the item should be deleted.
Setting this to None signals that the item should be deleted.
Example:
{
@@ -491,26 +471,25 @@ class PutOp(NamedTuple):
"""Controls how the item's fields are indexed for search operations.
Indexing configuration determines how the item can be found through search:
- `None` (default): Uses the store's default indexing configuration (if provided)
- `False`: Disables indexing for this item
- `list[str]`: Specifies which json path fields to index for search
- None (default): Uses the store's default indexing configuration (if provided)
- False: Disables indexing for this item
- list[str]: Specifies which json path fields to index for search
The item remains accessible through direct get() operations regardless of indexing.
When indexed, fields can be searched using natural language queries through
vector similarity search (if supported by the store implementation).
Path Syntax:
- Simple field access: `"field"`
- Nested fields: `"parent.child.grandchild"`
- Simple field access: "field"
- Nested fields: "parent.child.grandchild"
- Array indexing:
- Specific index: `"array[0]"`
- Last element: `"array[-1]"`
- All elements (each individually): `"array[*]"`
- Specific index: "array[0]"
- Last element: "array[-1]"
- All elements (each individually): "array[*]"
???+ example "Examples"
- `None` - Use store defaults (whole item)
- `list[str]` - List of fields to index
- None - Use store defaults (whole item)
- list[str] - List of fields to index
```python
[
@@ -530,12 +509,12 @@ class PutOp(NamedTuple):
will expire this many minutes after it was last accessed. The expiration timer
refreshes on both read operations (get/search) and write operations (put/update).
When the TTL expires, the item will be scheduled for deletion on a best-effort basis.
Defaults to `None` (no expiration).
Defaults to None (no expiration).
"""
Op = GetOp | SearchOp | PutOp | ListNamespacesOp
Result = Item | list[Item] | list[SearchItem] | list[tuple[str, ...]] | None
Op = Union[GetOp, SearchOp, PutOp, ListNamespacesOp]
Result = Union[Item, list[Item], list[SearchItem], list[tuple[str, ...]], None]
class InvalidNamespaceError(ValueError):
@@ -546,18 +525,18 @@ class TTLConfig(TypedDict, total=False):
"""Configuration for TTL (time-to-live) behavior in the store."""
refresh_on_read: bool
"""Default behavior for refreshing TTLs on read operations (`GET` and `SEARCH`).
"""Default behavior for refreshing TTLs on read operations (GET and SEARCH).
If `True`, TTLs will be refreshed on read operations (get/search) by default.
This can be overridden per-operation by explicitly setting `refresh_ttl`.
Defaults to `True` if not configured.
If True, TTLs will be refreshed on read operations (get/search) by default.
This can be overridden per-operation by explicitly setting refresh_ttl.
Defaults to True if not configured.
"""
default_ttl: float | None
"""Default TTL (time-to-live) in minutes for new items.
If provided, new items will expire after this many minutes after their last access.
The expiration timer refreshes on both read and write operations.
Defaults to `None` (no expiration).
Defaults to None (no expiration).
"""
sweep_interval_minutes: int | None
"""Interval in minutes between TTL sweep operations.
@@ -571,35 +550,33 @@ class IndexConfig(TypedDict, total=False):
"""Configuration for indexing documents for semantic search in the store.
If not provided to the store, the store will not support vector search.
In that case, all `index` arguments to `put()` and `aput()` operations will be ignored.
In that case, all `index` arguments to put() and `aput()` operations will be ignored.
"""
dims: int
"""Number of dimensions in the embedding vectors.
Common embedding models have the following dimensions:
- `openai:text-embedding-3-large`: `3072`
- `openai:text-embedding-3-small`: `1536`
- `openai:text-embedding-ada-002`: `1536`
- `cohere:embed-english-v3.0`: `1024`
- `cohere:embed-english-light-v3.0`: `384`
- `cohere:embed-multilingual-v3.0`: `1024`
- `cohere:embed-multilingual-light-v3.0`: `384`
- openai:text-embedding-3-large: 3072
- openai:text-embedding-3-small: 1536
- openai:text-embedding-ada-002: 1536
- cohere:embed-english-v3.0: 1024
- cohere:embed-english-light-v3.0: 384
- cohere:embed-multilingual-v3.0: 1024
- cohere:embed-multilingual-light-v3.0: 384
"""
embed: Embeddings | EmbeddingsFunc | AEmbeddingsFunc | str
"""Optional function to generate embeddings from text.
Can be specified in three ways:
1. A LangChain `Embeddings` instance
2. A synchronous embedding function (`EmbeddingsFunc`)
3. An asynchronous embedding function (`AEmbeddingsFunc`)
4. A provider string (e.g., `"openai:text-embedding-3-small"`)
1. A LangChain Embeddings instance
2. A synchronous embedding function (EmbeddingsFunc)
3. An asynchronous embedding function (AEmbeddingsFunc)
4. A provider string (e.g., "openai:text-embedding-3-small")
???+ example "Examples"
Using LangChain's initialization with `InMemoryStore`:
Using LangChain's initialization with InMemoryStore:
```python
from langchain.embeddings import init_embeddings
from langgraph.store.memory import InMemoryStore
@@ -612,8 +589,7 @@ class IndexConfig(TypedDict, total=False):
)
```
Using a custom embedding function with `InMemoryStore`:
Using a custom embedding function with InMemoryStore:
```python
from openai import OpenAI
from langgraph.store.memory import InMemoryStore
@@ -635,8 +611,7 @@ class IndexConfig(TypedDict, total=False):
)
```
Using an asynchronous embedding function with `InMemoryStore`:
Using an asynchronous embedding function with InMemoryStore:
```python
from openai import AsyncOpenAI
from langgraph.store.memory import InMemoryStore
@@ -664,17 +639,16 @@ class IndexConfig(TypedDict, total=False):
Controls which parts of stored items are embedded for semantic search. Follows JSON path syntax:
- `["$"]`: Embeds the entire JSON object as one vector (default)
- `["field1", "field2"]`: Embeds specific top-level fields
- `["parent.child"]`: Embeds nested fields using dot notation
- `["array[*].field"]`: Embeds field from each array element separately
- ["$"]: Embeds the entire JSON object as one vector (default)
- ["field1", "field2"]: Embeds specific top-level fields
- ["parent.child"]: Embeds nested fields using dot notation
- ["array[*].field"]: Embeds field from each array element separately
Note:
You can always override this behavior when storing an item using the
`index` parameter in the `put` or `aput` operations.
???+ example "Examples"
```python
# Embed entire document (default)
fields=["$"]
@@ -693,7 +667,7 @@ class IndexConfig(TypedDict, total=False):
Note:
- Fields missing from a document are skipped
- Array notation creates separate embeddings for each element
- Complex nested paths are supported (e.g., `"a.b[*].c.d"`)
- Complex nested paths are supported (e.g., "a.b[*].c.d")
"""
@@ -758,11 +732,11 @@ class BaseStore(ABC):
namespace: Hierarchical path for the item.
key: Unique identifier within the namespace.
refresh_ttl: Whether to refresh TTLs for the returned item.
If `None`, uses the store's default `refresh_ttl` setting.
If None (default), uses the store's default refresh_ttl setting.
If no TTL is specified, this argument is ignored.
Returns:
The retrieved item or `None` if not found.
The retrieved item or None if not found.
"""
return self.batch(
[GetOp(namespace, str(key), _ensure_refresh(self.ttl_config, refresh_ttl))]
@@ -794,9 +768,7 @@ class BaseStore(ABC):
List of items matching the search criteria.
???+ example "Examples"
Basic filtering:
```python
# Search for documents with specific metadata
results = store.search(
@@ -806,7 +778,6 @@ class BaseStore(ABC):
```
Natural language search (requires vector store implementation):
```python
# Initialize store with embedding configuration
store = YourStore( # e.g., InMemoryStore, AsyncPostgresStore
@@ -818,7 +789,6 @@ class BaseStore(ABC):
)
# Search for semantically similar documents
results = store.search(
("docs",),
query="machine learning applications in healthcare",
@@ -827,10 +797,8 @@ class BaseStore(ABC):
)
```
!!! note
Natural language search support depends on your store implementation
and requires proper embedding configuration.
Note: Natural language search support depends on your store implementation
and requires proper embedding configuration.
"""
return self.batch(
[
@@ -858,7 +826,7 @@ class BaseStore(ABC):
Args:
namespace: Hierarchical path for the item, represented as a tuple of strings.
Example: `("documents", "user123")`
Example: ("documents", "user123")
key: Unique identifier within the namespace. Together with namespace forms
the complete path to the item.
value: Dictionary containing the item's data. Must contain string keys
@@ -869,10 +837,10 @@ class BaseStore(ABC):
If you do not initialize the store with indexing capabilities,
the `index` parameter will be ignored
- False: Disable indexing for this item
- `list[str]`: List of field paths to index, supporting:
- Nested fields: `"metadata.title"`
- Array access: `"chapters[*].content"` (each indexed separately)
- Specific indices: `"authors[0].name"`
- list[str]: List of field paths to index, supporting:
- Nested fields: "metadata.title"
- Array access: "chapters[*].content" (each indexed separately)
- Specific indices: "authors[0].name"
ttl: Time to live in minutes. Support for this argument depends on your store adapter.
If specified, the item will expire after this many minutes from when it was last accessed.
None means no expiration. Expired runs will be deleted opportunistically.
@@ -888,22 +856,18 @@ class BaseStore(ABC):
Some implementations may not support expiration of items.
???+ example "Examples"
Store item. Indexing depends on how you configure the store:
Store item. Indexing depends on how you configure the store.
```python
store.put(("docs",), "report", {"memory": "Will likes ai"})
```
Do not index item for semantic search. Still accessible through `get()`
and `search()` operations but won't have a vector representation.
Do not index item for semantic search. Still accessible through get()
and search() operations but won't have a vector representation.
```python
store.put(("docs",), "report", {"memory": "Will likes ai"}, index=False)
```
Index specific fields for search:
Index specific fields for search.
```python
store.put(("docs",), "report", {"memory": "Will likes ai"}, index=["memory"])
```
@@ -954,17 +918,15 @@ class BaseStore(ABC):
suffix: Filter namespaces that end with this path.
max_depth: Return namespaces up to this depth in the hierarchy.
Namespaces deeper than this level will be truncated.
limit: Maximum number of namespaces to return.
offset: Number of namespaces to skip for pagination.
limit: Maximum number of namespaces to return (default 100).
offset: Number of namespaces to skip for pagination (default 0).
Returns:
A list of namespace tuples that match the criteria. Each tuple represents a
full namespace path up to `max_depth`.
List[Tuple[str, ...]]: A list of namespace tuples that match the criteria.
Each tuple represents a full namespace path up to `max_depth`.
???+ example "Examples":
Setting `max_depth=3`. Given the namespaces:
Setting max_depth=3. Given the namespaces:
```python
# Example if you have the following namespaces:
# ("a", "b", "c")
@@ -1004,7 +966,7 @@ class BaseStore(ABC):
key: Unique identifier within the namespace.
Returns:
The retrieved item or `None` if not found.
The retrieved item or None if not found.
"""
return (
await self.abatch(
@@ -1038,16 +1000,14 @@ class BaseStore(ABC):
limit: Maximum number of items to return.
offset: Number of items to skip before returning results.
refresh_ttl: Whether to refresh TTLs for the returned items.
If `None`, uses the store's `TTLConfig.refresh_default` setting.
If `TTLConfig` is not provided or no TTL is specified, this argument is ignored.
If None (default), uses the store's TTLConfig.refresh_default setting.
If TTLConfig is not provided or no TTL is specified, this argument is ignored.
Returns:
List of items matching the search criteria.
???+ example "Examples"
Basic filtering:
```python
# Search for documents with specific metadata
results = await store.asearch(
@@ -1057,7 +1017,6 @@ class BaseStore(ABC):
```
Natural language search (requires vector store implementation):
```python
# Initialize store with embedding configuration
store = YourStore( # e.g., InMemoryStore, AsyncPostgresStore
@@ -1069,7 +1028,6 @@ class BaseStore(ABC):
)
# Search for semantically similar documents
results = await store.asearch(
("docs",),
query="machine learning applications in healthcare",
@@ -1078,10 +1036,8 @@ class BaseStore(ABC):
)
```
!!! note
Natural language search support depends on your store implementation
and requires proper embedding configuration.
Note: Natural language search support depends on your store implementation
and requires proper embedding configuration.
"""
return (
await self.abatch(
@@ -1111,7 +1067,7 @@ class BaseStore(ABC):
Args:
namespace: Hierarchical path for the item, represented as a tuple of strings.
Example: `("documents", "user123")`
Example: ("documents", "user123")
key: Unique identifier within the namespace. Together with namespace forms
the complete path to the item.
value: Dictionary containing the item's data. Must contain string keys
@@ -1122,10 +1078,10 @@ class BaseStore(ABC):
If you do not initialize the store with indexing capabilities,
the `index` parameter will be ignored
- False: Disable indexing for this item
- `list[str]`: List of field paths to index, supporting:
- Nested fields: `"metadata.title"`
- Array access: `"chapters[*].content"` (each indexed separately)
- Specific indices: `"authors[0].name"`
- list[str]: List of field paths to index, supporting:
- Nested fields: "metadata.title"
- Array access: "chapters[*].content" (each indexed separately)
- Specific indices: "authors[0].name"
ttl: Time to live in minutes. Support for this argument depends on your store adapter.
If specified, the item will expire after this many minutes from when it was last accessed.
None means no expiration. Expired runs will be deleted opportunistically.
@@ -1141,22 +1097,18 @@ class BaseStore(ABC):
Some implementations may not support expiration of items.
???+ example "Examples"
Store item. Indexing depends on how you configure the store:
Store item. Indexing depends on how you configure the store.
```python
await store.aput(("docs",), "report", {"memory": "Will likes ai"})
```
Do not index item for semantic search. Still accessible through `get()`
and `search()` operations but won't have a vector representation.
Do not index item for semantic search. Still accessible through get()
and search() operations but won't have a vector representation.
```python
await store.aput(("docs",), "report", {"memory": "Will likes ai"}, index=False)
```
Index specific fields for search (if store configured to index items):
```python
await store.aput(
("docs",),
@@ -1215,16 +1167,15 @@ class BaseStore(ABC):
suffix: Filter namespaces that end with this path.
max_depth: Return namespaces up to this depth in the hierarchy.
Namespaces deeper than this level will be truncated to this depth.
limit: Maximum number of namespaces to return.
offset: Number of namespaces to skip for pagination.
limit: Maximum number of namespaces to return (default 100).
offset: Number of namespaces to skip for pagination (default 0).
Returns:
A list of namespace tuples that match the criteria. Each tuple represents a
full namespace path up to `max_depth`.
List[Tuple[str, ...]]: A list of namespace tuples that match the criteria.
Each tuple represents a full namespace path up to `max_depth`.
???+ example "Examples"
Setting `max_depth=3` with existing namespaces:
Setting max_depth=3 with existing namespaces:
```python
# Given the following namespaces:
# ("a", "b", "c")
@@ -5,8 +5,8 @@ from __future__ import annotations
import asyncio
import functools
import weakref
from collections.abc import Callable, Iterable
from typing import Any, Literal, TypeVar
from collections.abc import Iterable
from typing import Any, Callable, Literal, TypeVar
from langgraph.store.base import (
NOT_PROVIDED,
@@ -349,7 +349,7 @@ async def _run(
results = [results[ix] for ix in listen]
# set the results of each operation
for fut, result in zip(futs, results, strict=False):
for fut, result in zip(futs, results):
# guard against future being done (e.g. cancelled)
if not fut.done():
fut.set_result(result)
+5 -16
View File
@@ -11,8 +11,8 @@ from __future__ import annotations
import asyncio
import functools
import json
from collections.abc import Awaitable, Callable, Sequence
from typing import Any
from collections.abc import Awaitable, Sequence
from typing import Any, Callable
from langchain_core.embeddings import Embeddings
@@ -49,9 +49,7 @@ def ensure_embeddings(
An Embeddings instance that wraps the provided function(s).
??? example "Examples"
Wrap a synchronous embedding function:
```python
def my_embed_fn(texts):
return [[0.1, 0.2] for _ in texts]
@@ -61,7 +59,6 @@ def ensure_embeddings(
```
Wrap an asynchronous embedding function:
```python
async def my_async_fn(texts):
return [[0.1, 0.2] for _ in texts]
@@ -71,7 +68,6 @@ def ensure_embeddings(
```
Initialize embeddings using a provider string:
```python
# Requires langchain>=0.3.9 and langgraph-checkpoint>=2.0.11
embeddings = ensure_embeddings("openai:text-embedding-3-small")
@@ -123,9 +119,7 @@ class EmbeddingsLambda(Embeddings):
will raise an error. If sync, it will be used for both sync and async operations.
??? example "Examples"
With a sync function:
```python
def my_embed_fn(texts):
# Return 2D embeddings for each text
@@ -137,7 +131,6 @@ class EmbeddingsLambda(Embeddings):
```
With an async function:
```python
async def my_async_fn(texts):
return [[0.1, 0.2] for _ in texts]
@@ -245,7 +238,7 @@ def get_text_at_path(obj: Any, path: str | list[str]) -> list[str]:
- Nested paths in multi-field: "{field1,nested.field2}"
"""
if not path or path == "$":
return [json.dumps(obj, sort_keys=True, ensure_ascii=False)]
return [json.dumps(obj, sort_keys=True)]
tokens = tokenize_path(path) if isinstance(path, str) else path
@@ -256,7 +249,7 @@ def get_text_at_path(obj: Any, path: str | list[str]) -> list[str]:
elif obj is None:
return []
elif isinstance(obj, (list, dict)):
return [json.dumps(obj, sort_keys=True, ensure_ascii=False)]
return [json.dumps(obj, sort_keys=True)]
return []
token = tokens[pos]
@@ -302,11 +295,7 @@ def get_text_at_path(obj: Any, path: str | list[str]) -> list[str]:
if isinstance(current_obj, (str, int, float, bool)):
results.append(str(current_obj))
elif isinstance(current_obj, (list, dict)):
results.append(
json.dumps(
current_obj, sort_keys=True, ensure_ascii=False
)
)
results.append(json.dumps(current_obj, sort_keys=True))
# Handle wildcard
elif token == "*":
@@ -295,7 +295,7 @@ class InMemoryStore(BaseStore):
if queries:
coros = [self.embeddings.aembed_query(q) for q in list(queries)]
results = await asyncio.gather(*coros)
queryinmem_store = dict(zip(queries, results, strict=False))
queryinmem_store = dict(zip(queries, results))
return queryinmem_store
@@ -323,9 +323,7 @@ class InMemoryStore(BaseStore):
scores = _cosine_similarity(query_embedding, flat_vectors)
sorted_results = sorted(
zip(scores, flat_items, strict=False),
key=lambda x: x[0],
reverse=True,
zip(scores, flat_items), key=lambda x: x[0], reverse=True
)
# max pooling
seen: set[tuple[tuple[str, ...], str]] = set()
@@ -454,7 +452,7 @@ class InMemoryStore(BaseStore):
f"Number of embeddings ({len(embeddings)}) does not"
f" match number of indices ({len(indices)})"
)
for embedding, (ns, key, path) in zip(embeddings, indices, strict=False):
for embedding, (ns, key, path) in zip(embeddings, indices):
self._vectors[ns][key][path] = embedding
def _handle_list_namespaces(self, op: ListNamespacesOp) -> list[tuple[str, ...]]:
@@ -513,7 +511,7 @@ def _cosine_similarity(X: list[float], Y: list[list[float]]) -> list[float]:
similarities = []
for y in Y:
dot_product = sum(a * b for a, b in zip(X, y, strict=False))
dot_product = sum(a * b for a, b in zip(X, y))
norm1 = sum(a * a for a in X) ** 0.5
norm2 = sum(a * a for a in y) ** 0.5
similarity = dot_product / (norm1 * norm2) if norm1 > 0 and norm2 > 0 else 0.0
@@ -531,14 +529,14 @@ def _does_match(match_condition: MatchCondition, key: tuple[str, ...]) -> bool:
return False
if match_type == "prefix":
for k_elem, p_elem in zip(key, path, strict=False):
for k_elem, p_elem in zip(key, path):
if p_elem == "*":
continue # Wildcard matches any element
if k_elem != p_elem:
return False
return True
elif match_type == "suffix":
for k_elem, p_elem in zip(reversed(key), reversed(path), strict=False):
for k_elem, p_elem in zip(reversed(key), reversed(path)):
if p_elem == "*":
continue # Wildcard matches any element
if k_elem != p_elem:
@@ -565,10 +563,7 @@ def _compare_values(item_value: Any, filter_value: Any) -> bool:
return (
isinstance(item_value, (list, tuple))
and len(item_value) == len(filter_value)
and all(
_compare_values(iv, fv)
for iv, fv in zip(item_value, filter_value, strict=False)
)
and all(_compare_values(iv, fv) for iv, fv in zip(item_value, filter_value))
)
else:
return item_value == filter_value
+8 -19
View File
@@ -4,45 +4,36 @@ build-backend = "hatchling.build"
[project]
name = "langgraph-checkpoint"
version = "3.0.1"
version = "2.1.1"
description = "Library with base interfaces for LangGraph checkpoint savers."
authors = []
requires-python = ">=3.10"
requires-python = ">=3.9"
readme = "README.md"
license = "MIT"
license-files = ['LICENSE']
dependencies = [
"langchain-core>=0.2.38",
"ormsgpack>=1.12.0",
"ormsgpack>=1.10.0",
]
[project.urls]
Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/checkpoint"
Twitter = "https://x.com/LangChainAI"
Slack = "https://www.langchain.com/join-community"
Reddit = "https://www.reddit.com/r/LangChain/"
Repository = "https://www.github.com/langchain-ai/langgraph"
[dependency-groups]
test = [
dev = [
"ruff",
"codespell",
"pytest",
"pytest-asyncio",
"pytest-mock",
"pytest-watcher",
"mypy",
"dataclasses-json",
"numpy",
"pandas",
"pandas-stubs>=2.2.2.240807",
"redis",
]
lint = [
"ruff",
"codespell",
"mypy",
]
dev = [
{include-group = "test"},
{include-group = "lint"},
]
[tool.hatch.build.targets.wheel]
include = ["langgraph"]
@@ -58,10 +49,8 @@ lint.select = [
"UP", # pyupgrade
"B", # flake8-bugbear
"I", # isort
"UP", # pyupgrade
]
lint.ignore = ["E501", "B008"]
target-version = "py310"
[tool.pytest-watcher]
now = true
+43 -88
View File
@@ -1,5 +1,4 @@
import dataclasses
import json
import pathlib
import re
import sys
@@ -20,7 +19,6 @@ from pydantic.v1 import BaseModel as BaseModelV1
from pydantic.v1 import SecretStr as SecretStrV1
from langgraph.checkpoint.serde.jsonplus import (
InvalidModuleError,
JsonPlusSerializer,
_msgpack_ext_hook_to_json,
)
@@ -62,15 +60,22 @@ class MyDataclass:
pass
@dataclasses.dataclass(slots=True)
class MyDataclassWSlots:
foo: str
bar: int
inner: InnerDataclass
if sys.version_info < (3, 10):
def something(self) -> None:
class MyDataclassWSlots(MyDataclass):
pass
else:
@dataclasses.dataclass(slots=True)
class MyDataclassWSlots:
foo: str
bar: int
inner: InnerDataclass
def something(self) -> None:
pass
class MyEnum(Enum):
FOO = "foo"
@@ -110,7 +115,11 @@ def test_serde_jsonplus() -> None:
"my_dataclass": MyDataclass("foo", 1, InnerDataclass("hello")),
"my_enum": MyEnum.FOO,
"my_pydantic": MyPydantic(foo="foo", bar=1, inner=InnerPydantic(hello="hello")),
"my_pydantic_v1": MyPydanticV1(
foo="foo", bar=1, inner=InnerPydanticV1(hello="hello")
),
"my_secret_str": SecretStr("meow"),
"my_secret_str_v1": SecretStrV1("meow"),
"person": Person(name="foo"),
"a_bool": True,
"a_none": None,
@@ -132,12 +141,6 @@ def test_serde_jsonplus() -> None:
),
}
if sys.version_info < (3, 14):
to_serialize["my_pydantic_v1"] = MyPydanticV1(
foo="foo", bar=1, inner=InnerPydanticV1(hello="hello")
)
to_serialize["my_secret_str_v1"] = SecretStrV1("meow")
serde = JsonPlusSerializer()
dumped = serde.dumps_typed(to_serialize)
@@ -149,22 +152,23 @@ def test_serde_jsonplus() -> None:
assert serde.loads_typed(serde.dumps_typed(value)) == value
surrogates = [
"Hello??",
"Python??",
"Surrogate??",
"Example??",
"String??",
"With??",
"Surrogates??",
"Embedded??",
"In??",
"The??",
"Text??",
"Hello\ud83d\ude00",
"Python\ud83d\udc0d",
"Surrogate\ud834\udd1e",
"Example\ud83c\udf89",
"String\ud83c\udfa7",
"With\ud83c\udf08",
"Surrogates\ud83d\ude0e",
"Embedded\ud83d\udcbb",
"In\ud83c\udf0e",
"The\ud83d\udcd6",
"Text\ud83d\udcac",
"收花🙄·到",
]
serde = JsonPlusSerializer(pickle_fallback=False)
assert serde.loads_typed(serde.dumps_typed(surrogates)) == surrogates
assert serde.loads_typed(serde.dumps_typed(surrogates)) == [
v.encode("utf-8", "ignore").decode() for v in surrogates
]
def test_serde_jsonplus_json_mode() -> None:
@@ -193,7 +197,11 @@ def test_serde_jsonplus_json_mode() -> None:
"my_dataclass": MyDataclass("foo", 1, InnerDataclass("hello")),
"my_enum": MyEnum.FOO,
"my_pydantic": MyPydantic(foo="foo", bar=1, inner=InnerPydantic(hello="hello")),
"my_pydantic_v1": MyPydanticV1(
foo="foo", bar=1, inner=InnerPydanticV1(hello="hello")
),
"my_secret_str": SecretStr("meow"),
"my_secret_str_v1": SecretStrV1("meow"),
"person": Person(name="foo"),
"a_bool": True,
"a_none": None,
@@ -215,20 +223,13 @@ def test_serde_jsonplus_json_mode() -> None:
),
}
if sys.version_info < (3, 14):
to_serialize["my_pydantic_v1"] = MyPydanticV1(
foo="foo", bar=1, inner=InnerPydanticV1(hello="hello")
)
to_serialize["my_secret_str_v1"] = SecretStrV1("meow")
serde = JsonPlusSerializer(__unpack_ext_hook__=_msgpack_ext_hook_to_json)
dumped = serde.dumps_typed(to_serialize)
assert dumped[0] == "msgpack"
result = serde.loads_typed(dumped)
expected_result = {
assert result == {
"path": ["foo", "bar"],
"re": ["foo", 48],
"decimal": "1.10101",
@@ -252,7 +253,9 @@ def test_serde_jsonplus_json_mode() -> None:
"my_dataclass": {"foo": "foo", "bar": 1, "inner": {"hello": "hello"}},
"my_enum": "foo",
"my_pydantic": {"foo": "foo", "bar": 1, "inner": {"hello": "hello"}},
"my_pydantic_v1": {"foo": "foo", "bar": 1, "inner": {"hello": "hello"}},
"my_secret_str": "meow",
"my_secret_str_v1": "meow",
"person": {"name": "foo"},
"a_bool": True,
"a_none": None,
@@ -274,16 +277,6 @@ def test_serde_jsonplus_json_mode() -> None:
},
}
if sys.version_info < (3, 14):
expected_result["my_pydantic_v1"] = {
"foo": "foo",
"bar": 1,
"inner": {"hello": "hello"},
}
expected_result["my_secret_str_v1"] = "meow"
assert result == expected_result
def test_serde_jsonplus_bytes() -> None:
serde = JsonPlusSerializer()
@@ -295,20 +288,6 @@ def test_serde_jsonplus_bytes() -> None:
assert serde.loads_typed(dumped) == some_bytes
def test_deserde_invalid_module() -> None:
serde = JsonPlusSerializer()
load = {
"lc": 2,
"type": "constructor",
"id": ["pprint", "pprint"],
"kwargs": {"object": "HELLO"},
}
with pytest.raises(InvalidModuleError):
serde._revive_lc2(load)
serde = JsonPlusSerializer(allowed_json_modules=[("pprint", "pprint")])
serde.loads_typed(("json", json.dumps(load).encode("utf-8")))
def test_serde_jsonplus_bytearray() -> None:
serde = JsonPlusSerializer()
@@ -385,12 +364,7 @@ def test_serde_jsonplus_numpy_array_json_hook(arr: np.ndarray) -> None:
"str_col": ["a", None, "c"],
}
),
pytest.param(
pd.DataFrame({"cat_col": pd.Categorical(["a", "b", "a", "c"])}),
marks=pytest.mark.skipif(
sys.version_info >= (3, 14), reason="NotImplementedError on Python 3.14"
),
),
pd.DataFrame({"cat_col": pd.Categorical(["a", "b", "a", "c"])}),
pd.DataFrame(
{
"int8": pd.array([1, 2, 3], dtype="int8"),
@@ -418,25 +392,11 @@ def test_serde_jsonplus_numpy_array_json_hook(arr: np.ndarray) -> None:
"col3": np.random.rand(1000),
}
),
pytest.param(
pd.DataFrame(
{
"tz_datetime": pd.date_range(
"2024-01-01", periods=3, freq="D", tz="UTC"
)
}
),
marks=pytest.mark.skipif(
sys.version_info >= (3, 14), reason="NotImplementedError on Python 3.14"
),
pd.DataFrame(
{"tz_datetime": pd.date_range("2024-01-01", periods=3, freq="D", tz="UTC")}
),
pd.DataFrame({"timedelta": pd.to_timedelta([1, 2, 3], unit="D")}),
pytest.param(
pd.DataFrame({"period": pd.period_range("2024-01", periods=3, freq="M")}),
marks=pytest.mark.skipif(
sys.version_info >= (3, 14), reason="NotImplementedError on Python 3.14"
),
),
pd.DataFrame({"period": pd.period_range("2024-01", periods=3, freq="M")}),
pd.DataFrame({"interval": pd.interval_range(start=0, end=3, periods=3)}),
pd.DataFrame({"unicode": ["Hello 🌍", "Python 🐍", "Data 📊"]}),
pd.DataFrame({"mixed": [1, "string", [1, 2, 3], {"key": "value"}]}),
@@ -473,12 +433,7 @@ def test_serde_jsonplus_pandas_dataframe(df: pd.DataFrame) -> None:
pd.Series([1, 2, None]),
pd.Series([1.1, None, 3.3]),
pd.Series(["a", None, "c"]),
pytest.param(
pd.Series(pd.Categorical(["a", "b", "a", "c"])),
marks=pytest.mark.skipif(
sys.version_info >= (3, 14), reason="NotImplementedError on Python 3.14"
),
),
pd.Series(pd.Categorical(["a", "b", "a", "c"])),
pd.Series([1, 2, 3], dtype="int8"),
pd.Series([10, 20, 30], dtype="int16"),
pd.Series([100, 200, 300], dtype="int32"),
+2 -9
View File
@@ -188,14 +188,7 @@ class TestMemorySaver:
assert len(search_results_4) == 0
async def test_memory_saver() -> None:
def test_memory_saver() -> None:
from langgraph.checkpoint.memory import InMemorySaver
memory_saver = InMemorySaver()
assert isinstance(memory_saver, InMemorySaver)
async with memory_saver as async_memory_saver:
assert async_memory_saver is memory_saver
with memory_saver as sync_memory_saver:
assert sync_memory_saver is memory_saver
assert isinstance(InMemorySaver(), InMemorySaver)
+42 -49
View File
@@ -5,13 +5,12 @@ import time
import pytest
import redis
from langgraph.cache.base import FullKey
from langgraph.cache.redis import RedisCache
class TestRedisCache:
@pytest.fixture(autouse=True)
def setup(self) -> None:
def setup(self):
"""Set up test Redis client and cache."""
self.client = redis.Redis(
host="localhost", port=6379, db=0, decode_responses=False
@@ -21,21 +20,21 @@ class TestRedisCache:
except redis.ConnectionError:
pytest.skip("Redis server not available")
self.cache: RedisCache = RedisCache(self.client, prefix="test:cache:")
self.cache = RedisCache(self.client, prefix="test:cache:")
# Clean up before each test
self.client.flushdb()
def teardown_method(self) -> None:
def teardown_method(self):
"""Clean up after each test."""
try:
self.client.flushdb()
except Exception:
pass
def test_basic_set_and_get(self) -> None:
def test_basic_set_and_get(self):
"""Test basic set and get operations."""
keys: list[FullKey] = [(("graph", "node"), "key1")]
keys = [(("graph", "node"), "key1")]
values = {keys[0]: ({"result": 42}, None)}
# Set value
@@ -46,9 +45,9 @@ class TestRedisCache:
assert len(result) == 1
assert result[keys[0]] == {"result": 42}
def test_batch_operations(self) -> None:
def test_batch_operations(self):
"""Test batch set and get operations."""
keys: list[FullKey] = [
keys = [
(("graph", "node1"), "key1"),
(("graph", "node2"), "key2"),
(("other", "node"), "key3"),
@@ -69,9 +68,9 @@ class TestRedisCache:
assert result[keys[1]] == {"result": 2}
assert result[keys[2]] == {"result": 3}
def test_ttl_behavior(self) -> None:
def test_ttl_behavior(self):
"""Test TTL (time-to-live) functionality."""
key: FullKey = (("graph", "node"), "ttl_key")
key = (("graph", "node"), "ttl_key")
values = {key: ({"data": "expires_soon"}, 1)} # 1 second TTL
# Set with TTL
@@ -89,10 +88,10 @@ class TestRedisCache:
result = self.cache.get([key])
assert len(result) == 0
def test_namespace_isolation(self) -> None:
def test_namespace_isolation(self):
"""Test that different namespaces are isolated."""
key1: FullKey = (("graph1", "node"), "same_key")
key2: FullKey = (("graph2", "node"), "same_key")
key1 = (("graph1", "node"), "same_key")
key2 = (("graph2", "node"), "same_key")
values = {key1: ({"graph": 1}, None), key2: ({"graph": 2}, None)}
@@ -102,12 +101,9 @@ class TestRedisCache:
assert result[key1] == {"graph": 1}
assert result[key2] == {"graph": 2}
def test_clear_all(self) -> None:
def test_clear_all(self):
"""Test clearing all cached values."""
keys: list[FullKey] = [
(("graph", "node1"), "key1"),
(("graph", "node2"), "key2"),
]
keys = [(("graph", "node1"), "key1"), (("graph", "node2"), "key2")]
values = {keys[0]: ({"result": 1}, None), keys[1]: ({"result": 2}, None)}
self.cache.set(values)
@@ -123,9 +119,9 @@ class TestRedisCache:
result = self.cache.get(keys)
assert len(result) == 0
def test_clear_by_namespace(self) -> None:
def test_clear_by_namespace(self):
"""Test clearing cached values by namespace."""
keys: list[FullKey] = [
keys = [
(("graph1", "node"), "key1"),
(("graph2", "node"), "key2"),
(("graph1", "other"), "key3"),
@@ -146,7 +142,7 @@ class TestRedisCache:
assert len(result) == 1
assert result[keys[1]] == {"result": 2}
def test_empty_operations(self) -> None:
def test_empty_operations(self):
"""Test behavior with empty keys/values."""
# Empty get
result = self.cache.get([])
@@ -155,14 +151,14 @@ class TestRedisCache:
# Empty set
self.cache.set({}) # Should not raise error
def test_nonexistent_keys(self) -> None:
def test_nonexistent_keys(self):
"""Test getting keys that don't exist."""
keys: list[FullKey] = [(("graph", "node"), "nonexistent")]
keys = [(("graph", "node"), "nonexistent")]
result = self.cache.get(keys)
assert len(result) == 0
@pytest.mark.asyncio
async def test_async_operations(self) -> None:
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)
@@ -171,9 +167,9 @@ class TestRedisCache:
except Exception:
pytest.skip("Redis not available")
cache: RedisCache = RedisCache(client, prefix="test:async:")
cache = RedisCache(client, prefix="test:async:")
keys: list[FullKey] = [(("graph", "node"), "async_key")]
keys = [(("graph", "node"), "async_key")]
values = {keys[0]: ({"async": True}, None)}
# Async set (delegates to sync)
@@ -188,7 +184,7 @@ class TestRedisCache:
client.flushdb()
@pytest.mark.asyncio
async def test_async_clear(self) -> None:
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)
@@ -197,9 +193,9 @@ class TestRedisCache:
except Exception:
pytest.skip("Redis not available")
cache: RedisCache = RedisCache(client, prefix="test:async:")
cache = RedisCache(client, prefix="test:async:")
keys: list[FullKey] = [(("graph", "node"), "key")]
keys = [(("graph", "node"), "key")]
values = {keys[0]: ({"data": "test"}, None)}
await cache.aset(values)
@@ -218,44 +214,44 @@ class TestRedisCache:
# Cleanup
client.flushdb()
def test_redis_unavailable_get(self) -> None:
def test_redis_unavailable_get(self):
"""Test behavior when Redis is unavailable during get operations."""
# Create cache with non-existent Redis server
bad_client = redis.Redis(
host="nonexistent", port=9999, socket_connect_timeout=0.1
)
cache: RedisCache = RedisCache(bad_client, prefix="test:cache:")
cache = RedisCache(bad_client, prefix="test:cache:")
keys: list[FullKey] = [(("graph", "node"), "key")]
keys = [(("graph", "node"), "key")]
result = cache.get(keys)
# Should return empty dict when Redis unavailable
assert result == {}
def test_redis_unavailable_set(self) -> None:
def test_redis_unavailable_set(self):
"""Test behavior when Redis is unavailable during set operations."""
# Create cache with non-existent Redis server
bad_client = redis.Redis(
host="nonexistent", port=9999, socket_connect_timeout=0.1
)
cache: RedisCache = RedisCache(bad_client, prefix="test:cache:")
cache = RedisCache(bad_client, prefix="test:cache:")
keys: list[FullKey] = [(("graph", "node"), "key")]
keys = [(("graph", "node"), "key")]
values = {keys[0]: ({"data": "test"}, None)}
# Should not raise exception when Redis unavailable
cache.set(values) # Should silently fail
@pytest.mark.asyncio
async def test_redis_unavailable_async(self) -> None:
async def test_redis_unavailable_async(self):
"""Test async behavior when Redis is unavailable."""
# Create sync cache with non-existent Redis server (like main integration tests)
bad_client = redis.Redis(
host="nonexistent", port=9999, socket_connect_timeout=0.1
)
cache: RedisCache = RedisCache(bad_client, prefix="test:cache:")
cache = RedisCache(bad_client, prefix="test:cache:")
keys: list[FullKey] = [(("graph", "node"), "key")]
keys = [(("graph", "node"), "key")]
values = {keys[0]: ({"data": "test"}, None)}
# Should return empty dict for get (delegates to sync)
@@ -265,10 +261,10 @@ class TestRedisCache:
# Should not raise exception for set (delegates to sync)
await cache.aset(values) # Should silently fail
def test_corrupted_data_handling(self) -> None:
def test_corrupted_data_handling(self):
"""Test handling of corrupted data in Redis."""
# Set some valid data first
keys: list[FullKey] = [(("graph", "node"), "valid_key")]
keys = [(("graph", "node"), "valid_key")]
values = {keys[0]: ({"data": "valid"}, None)}
self.cache.set(values)
@@ -277,36 +273,33 @@ class TestRedisCache:
self.client.set(corrupted_key, b"invalid:data:format:too:many:colons")
# Should skip corrupted entry and return only valid ones
all_keys: list[FullKey] = [keys[0], (("graph", "node"), "corrupted_key")]
all_keys = [keys[0], (("graph", "node"), "corrupted_key")]
result = self.cache.get(all_keys)
assert len(result) == 1
assert result[keys[0]] == {"data": "valid"}
def test_key_parsing_edge_cases(self) -> None:
def test_key_parsing_edge_cases(self):
"""Test key parsing with edge cases."""
# Test empty namespace
key1: FullKey = ((), "empty_ns")
key1 = ((), "empty_ns")
values = {key1: ({"data": "empty_ns"}, None)}
self.cache.set(values)
result = self.cache.get([key1])
assert result[key1] == {"data": "empty_ns"}
# Test namespace with special characters
key2: FullKey = (
("graph:with:colons", "node-with-dashes"),
"key_with_underscores",
)
key2 = (("graph:with:colons", "node-with-dashes"), "key_with_underscores")
values = {key2: ({"data": "special_chars"}, None)}
self.cache.set(values)
result = self.cache.get([key2])
assert result[key2] == {"data": "special_chars"}
def test_large_data_serialization(self) -> None:
def test_large_data_serialization(self):
"""Test handling of large data objects."""
# Create a large data structure
large_data = {"large_list": list(range(1000)), "nested": {"data": "x" * 1000}}
key: FullKey = (("graph", "node"), "large_key")
key = (("graph", "node"), "large_key")
values = {key: (large_data, None)}
self.cache.set(values)
+2 -26
View File
@@ -845,7 +845,7 @@ async def test_async_batched_vector_search_concurrent(
]
)
for results, (query, filter_) in zip(all_results, search_queries, strict=False):
for results, (query, filter_) in zip(all_results, search_queries):
assert len(results) > 0, f"No results for query '{query}' with filter {filter_}"
for result in results:
@@ -950,8 +950,8 @@ async def test_embed_with_path(fake_embeddings: CharacterEmbeddings) -> None:
assert results[0].key != results[1].key
ascore = results[0].score
bscore = results[1].score
assert ascore == bscore
assert ascore is not None and bscore is not None
assert ascore == pytest.approx(bscore, abs=1e-5)
results = await store.asearch(("test",), query="uuu")
assert len(results) == 2
@@ -1021,27 +1021,3 @@ async def test_embed_with_path(fake_embeddings: CharacterEmbeddings) -> None:
assert len(results) == 3
doc5_result = next(r for r in results if r.key == "doc5")
assert doc5_result.score is None
def test_non_ascii(fake_embeddings: CharacterEmbeddings) -> None:
"""Test support for non-ascii characters"""
store = InMemoryStore(
index={"dims": fake_embeddings.dims, "embed": fake_embeddings}
)
store.put(("user_123", "memories"), "1", {"text": "这是中文"}) # Chinese
store.put(("user_123", "memories"), "2", {"text": "これは日本語です"}) # Japanese
store.put(("user_123", "memories"), "3", {"text": "이건 한국어야"}) # Korean
store.put(("user_123", "memories"), "4", {"text": "Это русский"}) # Russian
store.put(("user_123", "memories"), "5", {"text": "यह रूसी है"}) # Hindi
result1 = store.search(("user_123", "memories"), query="这是中文")
result2 = store.search(("user_123", "memories"), query="これは日本語です")
result3 = store.search(("user_123", "memories"), query="이건 한국어야")
result4 = store.search(("user_123", "memories"), query="Это русский")
result5 = store.search(("user_123", "memories"), query="यह रूसी है")
assert result1[0].key == "1"
assert result2[0].key == "2"
assert result3[0].key == "3"
assert result4[0].key == "4"
assert result5[0].key == "5"
+822 -781
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@@ -1 +0,0 @@
.langgraph_api/

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