POC streaming hints

## Security Alert Patch

Resolves 1 Dependabot security alert (medium severity).

### Package Updated

| Package | Old Version | New Version | Strategy | CVE Resolved |
|---------|-------------|-------------|----------|--------------|
| `js-yaml` | 3.14.1 | 3.14.2 | Lockfile patch (within-range bump) |
CVE-2025-64718 |

### CVE Details

**CVE-2025-64718** /
[GHSA-mh29-5h37-fv8m](https://github.com/advisories/GHSA-mh29-5h37-fv8m)
— `js-yaml` prototype pollution via YAML merge keys (`<<`). Affects
versions < 3.14.2.

The vulnerable package is a transitive dev dependency pulled in by
`@istanbuljs/load-nyc-config@1.1.0` (a Jest internal). No runtime
impact.

### Fix Strategy

Lockfile-only patch in `libs/cli/js-examples/yarn.lock`. The `^3.13.1`
version range already allows 3.14.2, so no manifest changes were needed.
The `js-yaml@^4.1.1` entry (used by `@eslint/eslintrc`) is untouched.

### Verification

- [x] Lockfile updated — `js-yaml@^3.13.1` now resolves to `3.14.2`
- [x] `js-yaml@^4.1.1` entry unchanged (`4.1.1`)
- [x] `yarn install --frozen-lockfile` passes

🤖 Submitted by langster-patch

Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>

.github/CONTRIBUTING.md

@@ -1,6 +0,0 @@
-# Contributing to LangGraph
-
-Hi there! Thank you for even being interested in contributing to LangGraph.
-As an open-source project in a rapidly developing field, we are extremely open to contributions, whether they involve new features, improved infrastructure, better documentation, or bug fixes.
-
-To learn how to contribute to LangGraph, please follow the [contribution guide here](https://docs.langchain.com/oss/python/contributing).

.github/ISSUE_TEMPLATE/bug-report.yml

@@ -1,43 +1,60 @@
 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]
+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 (below).
+labels: ["bug"]
+type: bug
 body:
   - type: markdown
     attributes:
       value: |
-        Thank you for taking the time to file a bug report. 
+        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/).
+        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:
+        Check these before submitting 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),
-        * [LangChain documentation with the integrated search](https://docs.langchain.com/),
+        * [Documentation](https://docs.langchain.com/oss/python/langgraph/overview),
+        * [API Reference Documentation](https://reference.langchain.com/python/),
+        * [LangChain ChatBot](https://chat.langchain.com/)
         * [GitHub search](https://github.com/langchain-ai/langgraph),
+        * [LangChain Forum](https://forum.langchain.com/),
   - type: checkboxes
     id: checks
     attributes:
       label: Checked other resources
-      description: Before submitting this issue, please confirm that you have completed all the steps below by checking each option. These steps help ensure your issue is well-defined, relevant, and actionable.
+      description: Please confirm and check all the following options.
       options:
-        - label: This is a bug, not a usage question. For questions, please use the LangChain Forum (https://forum.langchain.com/).
+        - label: This is a bug, not a usage question.
           required: true
-        - label: I added a clear and detailed title that summarizes the issue.
+        - label: I added a clear and descriptive title that summarizes this issue.
           required: true
-        - label: I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
+        - label: I used the GitHub search to find a similar question and didn't find it.
           required: true
-        - label: I included a self-contained, minimal example that demonstrates the issue INCLUDING all the relevant imports. The code run AS IS to reproduce the issue.
+        - label: I am sure that this is a bug in LangGraph rather than my code.
+          required: true
+        - label: The bug is not resolved by updating to the latest stable version of LangGraph (or the specific integration package).
+          required: true
+        - label: This is not related to the langchain-community package.
+          required: true
+        - label: I posted a self-contained, minimal, reproducible example. A maintainer can copy it and run it AS IS.
           required: true
   - type: textarea
     id: reproduction
     validations:
       required: true
     attributes:
-      label: Example Code
+      label: Reproduction Steps / Example Code (Python)
       description: |
-        Please add a self-contained, [minimal, reproducible, example](https://stackoverflow.com/help/minimal-reproducible-example) with your use case. Replace this code with your own!
+        Please add a self-contained, [minimal, reproducible, example](https://stackoverflow.com/help/minimal-reproducible-example) with your use case.
+
+        If a maintainer can copy it, run it, and see it right away, there's a much higher chance that you'll be able to get help.
+
+        **Important!**
+
+        * Avoid screenshots, as they are hard to read and (more importantly) don't allow others to copy-and-paste your code.
+        * Reduce your code to the minimum required to reproduce the issue if possible.
+
+        (This will be automatically formatted into code, so no need for backticks.)
+      render: python
       placeholder: |
         from langgraph.graph import StateGraph
 
@@ -46,17 +63,13 @@ body:
           
         chain = StateGraph(list)
         chain.invoke('Hello!')
-      render: python
   - type: textarea
-    id: error
-    validations:
-      required: false
     attributes:
       label: Error Message and Stack Trace (if applicable)
       description: |
-        If you are reporting an error, please include the full error message and stack trace.
-      placeholder: |
-        Exception + full stack trace
+        If you are reporting an error, please copy and paste the full error message and
+        stack trace.
+        (This will be automatically formatted into code, so no need for backticks.)
       render: shell
   - type: textarea
     id: description
@@ -77,7 +90,18 @@ body:
     attributes:
       label: System Info
       description: |
-        Run on your machine: `python -m langchain_core.sys_info`
+        Please share your system info with us.
+
+        Run the following command in your terminal and paste the output here:
+
+        `python -m langchain_core.sys_info`
+
+        or if you have an existing python interpreter running:
+
+        ```python
+        from langchain_core import sys_info
+        sys_info.print_sys_info()
+        ```
       placeholder: |
         python -m langchain_core.sys_info
     validations:

.github/ISSUE_TEMPLATE/config.yml

@@ -1,9 +1,15 @@
 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
+  - name: 💬 LangChain Forum
     url:  https://forum.langchain.com/
     about: General community discussions and support
+  - name: 📚 LangGraph Documentation
+    url: https://docs.langchain.com/oss/python/langgraph/overview
+    about: View the official LangGraph documentation
+  - name: 📚 API Reference Documentation
+    url: https://reference.langchain.com/python/
+    about: View the official LangGraph API reference documentation
+  - name: 📚 Documentation issue
+    url: https://github.com/langchain-ai/docs/issues/new?template=02-langgraph.yml
+    about: Report an issue related to the LangGraph documentation

.github/PULL_REQUEST_TEMPLATE.md

@@ -21,7 +21,7 @@ Thank you for contributing to LangGraph! Follow these steps to mark your pull re
   1. A test for the integration, preferably unit tests that do not rely on network access,
   2. An example notebook showing its use. It lives in `docs/docs/integrations` directory.
 
-- [ ] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. We will not consider a PR unless these three are passing in CI. See [contribution guidelines](https://github.com/langchain-ai/langgraph/blob/main/CONTRIBUTING.md) for more.
+- [ ] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. We will not consider a PR unless these three are passing in CI. See [contribution guidelines](https://docs.langchain.com/oss/python/contributing/overview) for more.
 
 Additional guidelines:
 

.github/dependabot.yml

@@ -4,15 +4,108 @@ updates:
     directory: "/"
     schedule:
       interval: "weekly"
+      day: "monday"
+    groups:
+      all-dependencies:
+        patterns:
+          - "*"
 
-  - package-ecosystem: "pip"
-    directories:
-      - "libs/checkpoint"
-      - "libs/checkpoint-postgres"
-      - "libs/checkpoint-sqlite"
-      - "libs/cli"
-      - "libs/langgraph"
-      - "libs/prebuilt"
-      - "libs/sdk-py"
+  - package-ecosystem: "uv"
+    directory: "/libs/checkpoint"
     schedule:
       interval: "weekly"
+      day: "monday"
+    groups:
+      all-dependencies:
+        patterns:
+          - "*"
+  - package-ecosystem: "uv"
+    directory: "/libs/checkpoint-conformance"
+    schedule:
+      interval: "weekly"
+      day: "monday"
+    groups:
+      all-dependencies:
+        patterns:
+          - "*"
+
+
+  - package-ecosystem: "uv"
+    directory: "/libs/checkpoint-postgres"
+    schedule:
+      interval: "weekly"
+      day: "monday"
+    groups:
+      all-dependencies:
+        patterns:
+          - "*"
+
+  - package-ecosystem: "uv"
+    directory: "/libs/checkpoint-sqlite"
+    schedule:
+      interval: "weekly"
+      day: "monday"
+    groups:
+      all-dependencies:
+        patterns:
+          - "*"
+
+  - package-ecosystem: "uv"
+    directory: "/libs/cli"
+    schedule:
+      interval: "weekly"
+      day: "monday"
+    groups:
+      all-dependencies:
+        patterns:
+          - "*"
+
+  - package-ecosystem: "uv"
+    directory: "/libs/langgraph"
+    schedule:
+      interval: "weekly"
+      day: "monday"
+    groups:
+      all-dependencies:
+        patterns:
+          - "*"
+
+  - package-ecosystem: "uv"
+    directory: "/libs/prebuilt"
+    schedule:
+      interval: "weekly"
+      day: "monday"
+    groups:
+      all-dependencies:
+        patterns:
+          - "*"
+
+  - package-ecosystem: "uv"
+    directory: "/libs/sdk-py"
+    schedule:
+      interval: "weekly"
+      day: "monday"
+    groups:
+      all-dependencies:
+        patterns:
+          - "*"
+
+  - package-ecosystem: "npm"
+    directory: "/libs/cli/js-examples"
+    schedule:
+      interval: "weekly"
+      day: "monday"
+    groups:
+      all-dependencies:
+        patterns:
+          - "*"
+
+  - package-ecosystem: "npm"
+    directory: "/libs/cli/js-monorepo-example"
+    schedule:
+      interval: "weekly"
+      day: "monday"
+    groups:
+      all-dependencies:
+        patterns:
+          - "*"

.github/scripts/run_langgraph_cli_test.py

@@ -63,7 +63,7 @@ def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
             try:
                 sys.stderr.write("\n== docker compose ps ==\n")
                 runner.run(
-                    subp_exec(*compose_cmd, *args, "ps", input=stdin, verbose=False)
+                    subp_exec(*compose_cmd, *args, "ps", input=stdin, verbose=True)
                 )
             except Exception:
                 pass
@@ -76,7 +76,7 @@ def test(config: pathlib.Path, port: int, tag: str, verbose: bool):
                         "logs",
                         "langgraph-api",
                         input=stdin,
-                        verbose=False,
+                        verbose=True,
                     )
                 )
             except Exception:

.github/workflows/_integration_test.yml

@@ -2,6 +2,9 @@ name: CLI integration test
 
 on:
   workflow_call:
+    secrets:
+      LANGSMITH_API_KEY:
+        required: false
 
 permissions:
   contents: read
@@ -28,6 +31,8 @@ jobs:
             workdir: libs/cli/examples/graphs_reqs_b
             tag: langgraph-test-d
     name: "CLI integration test"
+    env:
+      HAS_LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY != '' }}
     defaults:
       run:
         working-directory: libs/cli
@@ -49,19 +54,22 @@ jobs:
       - name: Install cli globally
         if: steps.changed-files.outputs.all
         run: pip install -e .
-      - name: Build and test service ${{ matrix.example.name }}
+      - name: Build service ${{ matrix.example.name }}
         if: steps.changed-files.outputs.all
         working-directory: ${{ matrix.example.workdir }}
+        run: |
+          langgraph build -t ${{ matrix.example.tag }}
+      - name: Test service ${{ matrix.example.name }}
+        if: ${{ steps.changed-files.outputs.all && env.HAS_LANGSMITH_API_KEY == 'true' }}
+        working-directory: ${{ matrix.example.workdir }}
         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
+          echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env
+          if [ -f ../.env ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> ../.env; 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 }}
 
@@ -82,22 +90,34 @@ jobs:
         working-directory: libs/cli/python-monorepo-example
         run: |
           langgraph build -t langgraph-test-g -c apps/agent/langgraph.json
+      - name: Test Python monorepo service
+        if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' && env.HAS_LANGSMITH_API_KEY == 'true' }}
+        working-directory: libs/cli/python-monorepo-example
+        env:
+          LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
+        run: |
           cp apps/agent/.env.example apps/agent/.env
-          if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> apps/agent/.env; fi
+          echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> apps/agent/.env
           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
+      - name: Build 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
+      - name: Test prerelease reqs service
+        if: ${{ steps.changed-files.outputs.all && matrix.example.name == 'A' && env.HAS_LANGSMITH_API_KEY == 'true' }}
+        working-directory: libs/cli/examples/graph_prerelease_reqs
+        env:
+          LANGSMITH_API_KEY: ${{ secrets.LANGSMITH_API_KEY }}
+        run: |
           cp ../.env.example .env
-          if [ -n "${{ secrets.LANGSMITH_API_KEY }}" ]; then echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env; fi
+          echo "LANGSMITH_API_KEY=${{ secrets.LANGSMITH_API_KEY }}" >> .env
           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; $LANGGRAPH_VERSION"
+          if [ "$LANGGRAPH_VERSION" != "1.0.8" ]; then
+            echo "LANGGRAPH_VERSION != 1.0.8; $LANGGRAPH_VERSION"
             exit 1
           fi
           LANGCHAIN_OPENAI_VERSION=$(docker run --rm --entrypoint "" langgraph-test-h python -c "import sys; from importlib.metadata import version; v = version('langchain-openai'); print(v);")

.github/workflows/ci.yml

@@ -39,6 +39,7 @@ jobs:
               - 'libs/checkpoint/**'
               - 'libs/checkpoint-sqlite/**'
               - 'libs/checkpoint-postgres/**'
+              - 'libs/checkpoint-conformance/**'
               - 'libs/prebuilt/**'
             deps:
               - '**/pyproject.toml'
@@ -57,7 +58,7 @@ jobs:
             "libs/checkpoint",
             "libs/checkpoint-sqlite",
             "libs/checkpoint-postgres",
-
+            "libs/checkpoint-conformance",
             "libs/prebuilt",
           ]
     if: needs.changes.outputs.python == 'true' || needs.changes.outputs.deps == 'true'
@@ -77,6 +78,7 @@ jobs:
             "libs/checkpoint",
             "libs/checkpoint-sqlite",
             "libs/checkpoint-postgres",
+            "libs/checkpoint-conformance",
             "libs/prebuilt",
             "libs/sdk-py",
           ]

.github/workflows/deploy-redirects.yml

@@ -0,0 +1,49 @@
+name: Deploy Redirects to GitHub Pages
+
+on:
+  push:
+    branches:
+      - main
+    paths:
+      - 'docs/**'
+      - '.github/workflows/deploy-redirects.yml'
+  workflow_dispatch:
+
+permissions:
+  contents: read
+  pages: write
+  id-token: write
+
+concurrency:
+  group: "pages"
+  cancel-in-progress: false
+
+jobs:
+  deploy:
+    environment:
+      name: github-pages
+      url: ${{ steps.deployment.outputs.page_url }}
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Setup Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.11'
+
+      - name: Generate redirect files
+        run: python docs/generate_redirects.py
+
+      - name: Setup Pages
+        uses: actions/configure-pages@v4
+
+      - name: Upload artifact
+        uses: actions/upload-pages-artifact@v3
+        with:
+          path: 'docs/_site'
+
+      - name: Deploy to GitHub Pages
+        id: deployment
+        uses: actions/deploy-pages@v4

AGENTS.md

@@ -53,3 +53,5 @@ sdk-js (standalone)
 ```
 
 Changes to a library may impact all of its dependents shown above.
+
+- Do NOT use Sphinx-style double backtick formatting (` ``code`` `). Use single backticks (`` `code` ``) for inline code references in docstrings and comments.

CLAUDE.md

@@ -53,3 +53,5 @@ sdk-js (standalone)
 ```
 
 Changes to a library may impact all of its dependents shown above.
+
+- Do NOT use Sphinx-style double backtick formatting (` ``code`` `). Use single backticks (`` `code` ``) for inline code references in docstrings and comments.

README.md

@@ -79,7 +79,7 @@ While LangGraph can be used standalone, it also integrates seamlessly with any L
 
 ## Additional resources
 
-- [Guides](https://docs.langchain.com/oss/python/langgraph/guides): Quick, actionable code snippets for topics such as streaming, adding memory & persistence, and design patterns (e.g. branching, subgraphs, etc.).
+- [Guides](https://docs.langchain.com/oss/python/langgraph/overview): Quick, actionable code snippets for topics such as streaming, adding memory & persistence, and design patterns (e.g. branching, subgraphs, etc.).
 - [Reference](https://reference.langchain.com/python/langgraph/): Detailed reference on core classes, methods, how to use the graph and checkpointing APIs, and higher-level prebuilt components.
 - [Examples](https://docs.langchain.com/oss/python/langgraph/agentic-rag): Guided examples on getting started with LangGraph.
 - [LangChain Forum](https://forum.langchain.com/): Connect with the community and share all of your technical questions, ideas, and feedback.

docs/.gitignore

@@ -0,0 +1 @@
+_site/

docs/generate_redirects.py

@@ -0,0 +1,142 @@
+#!/usr/bin/env python3
+"""
+Generate HTML redirect files from redirects.json.
+
+Usage:
+    python generate_redirects.py
+
+This script reads redirects.json and generates individual HTML files
+for each redirect path. Each HTML file uses meta refresh (0 delay)
+which is SEO-friendly and treated similarly to 301 redirects by Google.
+
+To add new redirects, simply edit redirects.json and re-run this script.
+"""
+
+import json
+import os
+from pathlib import Path
+
+# Default fallback URL for any path not in the redirect map
+DEFAULT_REDIRECT = "https://docs.langchain.com/oss/python/langgraph/overview"
+
+HTML_TEMPLATE = """<!doctype html>
+<html lang="en">
+<head>
+    <meta charset="utf-8">
+    <title>Redirecting...</title>
+    <link rel="canonical" href="{url}">
+    <meta name="robots" content="noindex">
+    <script>var anchor=window.location.hash.substr(1);location.href="{url}"+(anchor?"#"+anchor:"")</script>
+    <meta http-equiv="refresh" content="0; url={url}">
+</head>
+<body>
+Redirecting...
+</body>
+</html>
+"""
+
+ROOT_HTML_TEMPLATE = """<!doctype html>
+<html lang="en">
+<head>
+    <meta charset="utf-8">
+    <title>Redirecting to LangGraph Documentation</title>
+    <link rel="canonical" href="{url}">
+    <meta name="robots" content="noindex">
+    <script>var anchor=window.location.hash.substr(1);location.href="{url}"+(anchor?"#"+anchor:"")</script>
+    <meta http-equiv="refresh" content="0; url={url}">
+</head>
+<body>
+<h1>Documentation has moved</h1>
+<p>The LangGraph documentation has moved to <a href="{url}">docs.langchain.com</a>.</p>
+<p>Redirecting you now...</p>
+</body>
+</html>
+"""
+
+CATCHALL_404_TEMPLATE = """<!doctype html>
+<html lang="en">
+<head>
+    <meta charset="utf-8">
+    <title>Redirecting to LangGraph Documentation</title>
+    <link rel="canonical" href="{default_url}">
+    <meta name="robots" content="noindex">
+    <script>
+        // Catchall redirect for any unmapped paths
+        window.location.replace("{default_url}");
+    </script>
+    <meta http-equiv="refresh" content="0; url={default_url}">
+</head>
+<body>
+<h1>Documentation has moved</h1>
+<p>The LangGraph documentation has moved to <a href="{default_url}">docs.langchain.com</a>.</p>
+<p>Redirecting you now...</p>
+</body>
+</html>
+"""
+
+
+def generate_redirects():
+    script_dir = Path(__file__).parent
+    output_dir = script_dir / "_site"
+
+    # Load redirects
+    with open(script_dir / "redirects.json") as f:
+        redirects = json.load(f)
+
+    # Clean output directory
+    if output_dir.exists():
+        import shutil
+        shutil.rmtree(output_dir)
+    output_dir.mkdir(parents=True)
+
+    # Generate individual HTML files for each redirect
+    for old_path, new_url in redirects.items():
+        # Remove leading slash and create directory structure
+        path = old_path.lstrip("/")
+
+        # Check if path has a file extension (e.g., .txt, .xml)
+        # If so, create the file directly instead of a directory with index.html
+        path_obj = Path(path)
+        has_extension = path_obj.suffix and len(path_obj.suffix) <= 5
+
+        if not path:
+            html_path = output_dir / "index.html"
+        elif has_extension:
+            # For files with extensions, create the file directly
+            html_path = output_dir / path
+        else:
+            # For directory-style URLs, create index.html inside
+            html_path = output_dir / path / "index.html"
+
+        # Create parent directories
+        html_path.parent.mkdir(parents=True, exist_ok=True)
+
+        # Write the redirect HTML
+        html_path.write_text(HTML_TEMPLATE.format(url=new_url))
+        print(f"Created: {html_path}")
+
+    # Create root index.html
+    root_index = output_dir / "index.html"
+    if not root_index.exists():
+        root_index.write_text(ROOT_HTML_TEMPLATE.format(url=DEFAULT_REDIRECT))
+        print(f"Created: {root_index}")
+
+    # Create 404.html for catchall
+    catchall_404 = output_dir / "404.html"
+    catchall_404.write_text(CATCHALL_404_TEMPLATE.format(default_url=DEFAULT_REDIRECT))
+    print(f"Created: {catchall_404}")
+
+    # Copy static files (like llms.txt) that can't be redirected via HTML
+    static_files = ["llms.txt"]
+    for static_file in static_files:
+        src = script_dir / static_file
+        if src.exists():
+            dst = output_dir / static_file
+            dst.write_text(src.read_text())
+            print(f"Copied: {dst}")
+
+    print(f"\nGenerated {len(redirects)} redirect files in {output_dir}")
+
+
+if __name__ == "__main__":
+    generate_redirects()

docs/llms.txt

@@ -0,0 +1,35 @@
+# LangGraph
+
+LangGraph documentation has moved to docs.langchain.com.
+
+## Overview
+
+- [LangGraph Overview](https://docs.langchain.com/oss/python/langgraph/overview): Introduction to LangGraph, a library for building stateful, multi-actor applications with LLMs.
+- [Why LangGraph?](https://docs.langchain.com/oss/python/langgraph/why-langgraph): Motivation for LangGraph and its key features.
+
+## Core Concepts
+
+- [Graph API](https://docs.langchain.com/oss/python/langgraph/graph-api): Learn how to define state, create nodes, and connect them with edges.
+- [Streaming](https://docs.langchain.com/oss/python/langgraph/streaming): Stream outputs from your graph for better UX.
+- [Persistence](https://docs.langchain.com/oss/python/langgraph/persistence): Add memory and checkpointing to your graphs.
+- [Add Memory](https://docs.langchain.com/oss/python/langgraph/add-memory): Implement short-term and long-term memory.
+- [Workflows & Agents](https://docs.langchain.com/oss/python/langgraph/workflows-agents): Build agents and workflows with LangGraph.
+
+## How-To Guides
+
+- [Use Subgraphs](https://docs.langchain.com/oss/python/langgraph/use-subgraphs): Compose graphs using subgraphs.
+- [Observability](https://docs.langchain.com/oss/python/langgraph/observability): Add tracing and debugging to your graphs.
+- [Common Errors](https://docs.langchain.com/oss/python/langgraph/common-errors): Troubleshoot common LangGraph errors.
+
+## Tutorials
+
+- [Agentic RAG](https://docs.langchain.com/oss/python/langgraph/agentic-rag): Build an agentic RAG system with LangGraph.
+- [SQL Agent](https://docs.langchain.com/oss/python/langgraph/sql-agent): Create a SQL agent with LangGraph.
+
+## Reference
+
+- [API Reference](https://reference.langchain.com/python/langgraph/): Complete API documentation for LangGraph.
+
+## LangGraph Platform
+
+For deploying LangGraph applications in production, see the [LangSmith documentation](https://docs.langchain.com/langsmith/agent-server).

docs/redirects.json

@@ -0,0 +1,296 @@
+{
+  "/how-tos/stream-values": "https://docs.langchain.com/oss/python/langgraph/streaming",
+  "/how-tos/stream-updates": "https://docs.langchain.com/oss/python/langgraph/streaming",
+  "/how-tos/streaming-content": "https://docs.langchain.com/oss/python/langgraph/streaming",
+  "/how-tos/stream-multiple": "https://docs.langchain.com/oss/python/langgraph/streaming",
+  "/how-tos/streaming-tokens-without-langchain": "https://docs.langchain.com/oss/python/langgraph/streaming",
+  "/how-tos/streaming-from-final-node": "https://docs.langchain.com/oss/python/langgraph/streaming",
+  "/how-tos/streaming-events-from-within-tools-without-langchain": "https://docs.langchain.com/oss/python/langgraph/streaming",
+  "/how-tos/state-reducers": "https://docs.langchain.com/oss/python/langgraph/graph-api#define-and-update-state",
+  "/how-tos/sequence": "https://docs.langchain.com/oss/python/langgraph/graph-api#create-a-sequence-of-steps",
+  "/how-tos/branching": "https://docs.langchain.com/oss/python/langgraph/graph-api#create-branches",
+  "/how-tos/recursion-limit": "https://docs.langchain.com/oss/python/langgraph/graph-api#create-and-control-loops",
+  "/how-tos/visualization": "https://docs.langchain.com/oss/python/langgraph/graph-api#visualize-your-graph",
+  "/how-tos/input_output_schema": "https://docs.langchain.com/oss/python/langgraph/graph-api#define-input-and-output-schemas",
+  "/how-tos/pass_private_state": "https://docs.langchain.com/oss/python/langgraph/graph-api#pass-private-state-between-nodes",
+  "/how-tos/state-model": "https://docs.langchain.com/oss/python/langgraph/graph-api#use-pydantic-models-for-graph-state",
+  "/how-tos/map-reduce": "https://docs.langchain.com/oss/python/langgraph/graph-api#map-reduce-and-the-send-api",
+  "/how-tos/command": "https://docs.langchain.com/oss/python/langgraph/graph-api#combine-control-flow-and-state-updates-with-command",
+  "/how-tos/configuration": "https://docs.langchain.com/oss/python/langgraph/graph-api#add-runtime-configuration",
+  "/how-tos/node-retries": "https://docs.langchain.com/oss/python/langgraph/graph-api#add-retry-policies",
+  "/how-tos/return-when-recursion-limit-hits": "https://docs.langchain.com/oss/python/langgraph/graph-api#impose-a-recursion-limit",
+  "/how-tos/async": "https://docs.langchain.com/oss/python/langgraph/graph-api#async",
+  "/how-tos/memory/manage-conversation-history": "https://docs.langchain.com/oss/python/langgraph/add-memory",
+  "/how-tos/memory/delete-messages": "https://docs.langchain.com/oss/python/langgraph/add-memory#delete-messages",
+  "/how-tos/memory/add-summary-conversation-history": "https://docs.langchain.com/oss/python/langgraph/add-memory#summarize-messages",
+  "/how-tos/memory": "https://docs.langchain.com/oss/python/langgraph/add-memory",
+  "/agents/memory": "https://docs.langchain.com/oss/python/langgraph/add-memory",
+  "/how-tos/subgraph-transform-state": "https://docs.langchain.com/oss/python/langgraph/use-subgraphs#different-state-schemas",
+  "/how-tos/subgraphs-manage-state": "https://docs.langchain.com/oss/python/langgraph/use-subgraphs#add-persistence",
+  "/how-tos/persistence_postgres": "https://docs.langchain.com/oss/python/langgraph/add-memory#use-in-production",
+  "/how-tos/persistence_mongodb": "https://docs.langchain.com/oss/python/langgraph/add-memory#use-in-production",
+  "/how-tos/persistence_redis": "https://docs.langchain.com/oss/python/langgraph/add-memory#use-in-production",
+  "/how-tos/subgraph-persistence": "https://docs.langchain.com/oss/python/langgraph/add-memory#use-with-subgraphs",
+  "/how-tos/cross-thread-persistence": "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": "https://docs.langchain.com/oss/python/langgraph/persistence#threads",
+  "/how-tos/persistence": "https://docs.langchain.com/oss/python/langgraph/add-memory",
+  "/how-tos/tool-calling-errors": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
+  "/how-tos/pass-config-to-tools": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
+  "/how-tos/pass-run-time-values-to-tools": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
+  "/how-tos/update-state-from-tools": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
+  "/agents/tools": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
+  "/how-tos/agent-handoffs": "https://docs.langchain.com/oss/python/langgraph/graph-api",
+  "/how-tos/multi-agent-network": "https://docs.langchain.com/oss/python/langgraph/graph-api",
+  "/how-tos/multi-agent-multi-turn-convo": "https://docs.langchain.com/oss/python/langgraph/graph-api",
+  "/cloud/index": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/cloud/how-tos/index": "https://docs.langchain.com/langsmith/home",
+  "/cloud/concepts/api": "https://docs.langchain.com/langsmith/agent-server",
+  "/cloud/concepts/cloud": "https://docs.langchain.com/langsmith/cloud",
+  "/cloud/faq/studio": "https://docs.langchain.com/langsmith/studio",
+  "/cloud/how-tos/human_in_the_loop_edit_state": "https://docs.langchain.com/langsmith/add-human-in-the-loop",
+  "/cloud/how-tos/human_in_the_loop_user_input": "https://docs.langchain.com/langsmith/add-human-in-the-loop",
+  "/concepts/platform_architecture": "https://docs.langchain.com/langsmith/cloud#architecture",
+  "/cloud/how-tos/stream_values": "https://docs.langchain.com/langsmith/streaming",
+  "/cloud/how-tos/stream_updates": "https://docs.langchain.com/langsmith/streaming",
+  "/cloud/how-tos/stream_messages": "https://docs.langchain.com/langsmith/streaming",
+  "/cloud/how-tos/stream_events": "https://docs.langchain.com/langsmith/streaming",
+  "/cloud/how-tos/stream_debug": "https://docs.langchain.com/langsmith/streaming",
+  "/cloud/how-tos/stream_multiple": "https://docs.langchain.com/langsmith/streaming",
+  "/cloud/concepts/streaming": "https://docs.langchain.com/oss/python/langgraph/streaming",
+  "/agents/streaming": "https://docs.langchain.com/oss/python/langgraph/streaming",
+  "/how-tos/create-react-agent": "https://docs.langchain.com/oss/python/langchain/agents#basic-configuration",
+  "/how-tos/create-react-agent-memory": "https://docs.langchain.com/oss/python/langgraph/add-memory",
+  "/how-tos/create-react-agent-system-prompt": "https://docs.langchain.com/oss/python/langgraph/add-memory",
+  "/how-tos/create-react-agent-structured-output": "https://docs.langchain.com/oss/python/langchain/agents#structured-output",
+  "/prebuilt": "https://docs.langchain.com/oss/python/langchain/agents",
+  "/reference/prebuilt": "https://reference.langchain.com/python/langgraph/agents/",
+  "/concepts/high_level": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/concepts/index": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/concepts/v0-human-in-the-loop": "https://docs.langchain.com/oss/python/langgraph/interrupts",
+  "/how-tos/index": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/tutorials/introduction": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/agents/deployment": "https://docs.langchain.com/oss/python/langgraph/local-server",
+  "/how-tos/deploy-self-hosted": "https://docs.langchain.com/langsmith/platform-setup",
+  "/concepts/self_hosted": "https://docs.langchain.com/langsmith/platform-setup",
+  "/tutorials/deployment": "https://docs.langchain.com/langsmith/deployments",
+  "/cloud/how-tos/assistant_versioning": "https://docs.langchain.com/langsmith/configuration-cloud",
+  "/cloud/concepts/runs": "https://docs.langchain.com/langsmith/assistants#execution",
+  "/how-tos/wait-user-input-functional": "https://docs.langchain.com/oss/python/langgraph/functional-api",
+  "/how-tos/review-tool-calls-functional": "https://docs.langchain.com/oss/python/langgraph/functional-api",
+  "/how-tos/create-react-agent-hitl": "https://docs.langchain.com/oss/python/langgraph/interrupts",
+  "/agents/human-in-the-loop": "https://docs.langchain.com/oss/python/langgraph/interrupts",
+  "/how-tos/human_in_the_loop/dynamic_breakpoints": "https://docs.langchain.com/oss/python/langgraph/interrupts",
+  "/concepts/breakpoints": "https://docs.langchain.com/oss/python/langgraph/interrupts",
+  "/how-tos/human_in_the_loop/breakpoints": "https://docs.langchain.com/oss/python/langgraph/interrupts",
+  "/cloud/how-tos/human_in_the_loop_breakpoint": "https://docs.langchain.com/langsmith/add-human-in-the-loop",
+  "/how-tos/human_in_the_loop/edit-graph-state": "https://docs.langchain.com/oss/python/langgraph/use-time-travel",
+  "/examples/index": "https://docs.langchain.com/oss/python/langgraph/case-studies",
+  "/guides/index": "https://docs.langchain.com/oss/python/langchain/overview",
+  "/tutorials/index": "https://docs.langchain.com/oss/python/learn",
+  "/llms-txt-overview": "https://docs.langchain.com/llms.txt",
+  "/tutorials/rag/langgraph_adaptive_rag": "https://docs.langchain.com/oss/python/langgraph/agentic-rag",
+  "/tutorials/multi_agent/multi-agent-collaboration": "https://docs.langchain.com/oss/python/langchain/multi-agent",
+  "/how-tos/create-react-agent-manage-message-history": "https://docs.langchain.com/oss/python/langgraph/add-memory",
+  "/how-tos/many-tools": "https://docs.langchain.com/oss/python/langchain/tools",
+  "/tutorials/customer-support/customer-support": "https://docs.langchain.com/oss/python/langgraph/agentic-rag",
+  "/how-tos/react-agent-structured-output": "https://docs.langchain.com/oss/python/langchain/agents#structured-output",
+  "/tutorials/code_assistant/langgraph_code_assistant": "https://docs.langchain.com/oss/python/langgraph/agentic-rag",
+  "/tutorials/multi_agent/hierarchical_agent_teams": "https://docs.langchain.com/oss/python/langchain/supervisor",
+  "/tutorials/auth/getting_started": "https://docs.langchain.com/langsmith/auth",
+  "/tutorials/auth/resource_auth": "https://docs.langchain.com/langsmith/resource-auth",
+  "/tutorials/auth/add_auth_server": "https://docs.langchain.com/langsmith/add-auth-server",
+  "/how-tos/use-remote-graph": "https://docs.langchain.com/langsmith/use-remote-graph",
+  "/how-tos/autogen-integration": "https://docs.langchain.com/langsmith/autogen-integration",
+  "/how-tos/human_in_the_loop/wait-user-input": "https://docs.langchain.com/oss/python/langgraph/interrupts",
+  "/cloud/how-tos/use_stream_react": "https://docs.langchain.com/langsmith/use-stream-react",
+  "/cloud/how-tos/generative_ui_react": "https://docs.langchain.com/langsmith/generative-ui-react",
+  "/concepts/langgraph_platform": "https://docs.langchain.com/langsmith/home",
+  "/concepts/langgraph_components": "https://docs.langchain.com/langsmith/components",
+  "/concepts/langgraph_server": "https://docs.langchain.com/langsmith/agent-server",
+  "/concepts/langgraph_data_plane": "https://docs.langchain.com/langsmith/data-plane",
+  "/concepts/langgraph_control_plane": "https://docs.langchain.com/langsmith/control-plane",
+  "/concepts/langgraph_cli": "https://docs.langchain.com/langsmith/cli",
+  "/concepts/langgraph_studio": "https://docs.langchain.com/langsmith/studio",
+  "/cloud/how-tos/studio/quick_start": "https://docs.langchain.com/langsmith/quick-start-studio",
+  "/cloud/how-tos/invoke_studio": "https://docs.langchain.com/langsmith/use-studio",
+  "/cloud/how-tos/studio/manage_assistants": "https://docs.langchain.com/langsmith/use-studio",
+  "/cloud/how-tos/threads_studio": "https://docs.langchain.com/langsmith/use-threads",
+  "/cloud/how-tos/iterate_graph_studio": "https://docs.langchain.com/langsmith/use-studio",
+  "/cloud/how-tos/studio/run_evals": "https://docs.langchain.com/langsmith/observability",
+  "/cloud/how-tos/clone_traces_studio": "https://docs.langchain.com/langsmith/observability",
+  "/cloud/how-tos/datasets_studio": "https://docs.langchain.com/langsmith/use-studio",
+  "/concepts/sdk": "https://docs.langchain.com/langsmith/sdk",
+  "/concepts/plans": "https://docs.langchain.com/langsmith/home",
+  "/concepts/application_structure": "https://docs.langchain.com/langsmith/application-structure",
+  "/concepts/scalability_and_resilience": "https://docs.langchain.com/langsmith/scalability-and-resilience",
+  "/concepts/auth": "https://docs.langchain.com/langsmith/auth",
+  "/how-tos/auth/custom_auth": "https://docs.langchain.com/langsmith/custom-auth",
+  "/how-tos/auth/openapi_security": "https://docs.langchain.com/langsmith/openapi-security",
+  "/concepts/assistants": "https://docs.langchain.com/langsmith/assistants",
+  "/cloud/how-tos/configuration_cloud": "https://docs.langchain.com/langsmith/configuration-cloud",
+  "/cloud/how-tos/use_threads": "https://docs.langchain.com/langsmith/use-threads",
+  "/cloud/how-tos/background_run": "https://docs.langchain.com/langsmith/background-run",
+  "/cloud/how-tos/same-thread": "https://docs.langchain.com/langsmith/same-thread",
+  "/cloud/how-tos/stateless_runs": "https://docs.langchain.com/langsmith/stateless-runs",
+  "/cloud/how-tos/configurable_headers": "https://docs.langchain.com/langsmith/configurable-headers",
+  "/concepts/double_texting": "https://docs.langchain.com/langsmith/double-texting",
+  "/cloud/how-tos/interrupt_concurrent": "https://docs.langchain.com/langsmith/interrupt-concurrent",
+  "/cloud/how-tos/rollback_concurrent": "https://docs.langchain.com/langsmith/rollback-concurrent",
+  "/cloud/how-tos/reject_concurrent": "https://docs.langchain.com/langsmith/reject-concurrent",
+  "/cloud/how-tos/enqueue_concurrent": "https://docs.langchain.com/langsmith/enqueue-concurrent",
+  "/cloud/concepts/webhooks": "https://docs.langchain.com/langsmith/use-webhooks",
+  "/cloud/how-tos/webhooks": "https://docs.langchain.com/langsmith/use-webhooks",
+  "/cloud/concepts/cron_jobs": "https://docs.langchain.com/langsmith/cron-jobs",
+  "/cloud/how-tos/cron_jobs": "https://docs.langchain.com/langsmith/cron-jobs",
+  "/how-tos/http/custom_lifespan": "https://docs.langchain.com/langsmith/custom-lifespan",
+  "/how-tos/http/custom_middleware": "https://docs.langchain.com/langsmith/custom-middleware",
+  "/how-tos/http/custom_routes": "https://docs.langchain.com/langsmith/custom-routes",
+  "/cloud/concepts/data_storage_and_privacy": "https://docs.langchain.com/langsmith/data-storage-and-privacy",
+  "/cloud/deployment/semantic_search": "https://docs.langchain.com/langsmith/semantic-search",
+  "/how-tos/ttl/configure_ttl": "https://docs.langchain.com/langsmith/configure-ttl",
+  "/concepts/deployment_options": "https://docs.langchain.com/langsmith/deployments",
+  "/cloud/quick_start": "https://docs.langchain.com/langsmith/deployment-quickstart",
+  "/cloud/deployment/setup": "https://docs.langchain.com/langsmith/setup-app-requirements-txt",
+  "/cloud/deployment/setup_pyproject": "https://docs.langchain.com/langsmith/setup-pyproject",
+  "/cloud/deployment/setup_javascript": "https://docs.langchain.com/langsmith/setup-javascript",
+  "/cloud/deployment/custom_docker": "https://docs.langchain.com/langsmith/custom-docker",
+  "/cloud/deployment/graph_rebuild": "https://docs.langchain.com/langsmith/graph-rebuild",
+  "/concepts/langgraph_cloud": "https://docs.langchain.com/langsmith/cloud",
+  "/concepts/langgraph_self_hosted_data_plane": "https://docs.langchain.com/langsmith/platform-setup",
+  "/concepts/langgraph_self_hosted_control_plane": "https://docs.langchain.com/langsmith/platform-setup",
+  "/concepts/langgraph_standalone_container": "https://docs.langchain.com/langsmith/docker",
+  "/cloud/deployment/cloud": "https://docs.langchain.com/langsmith/cloud",
+  "/cloud/deployment/self_hosted_data_plane": "https://docs.langchain.com/langsmith/platform-setup",
+  "/cloud/deployment/self_hosted_control_plane": "https://docs.langchain.com/langsmith/platform-setup",
+  "/cloud/deployment/standalone_container": "https://docs.langchain.com/langsmith/docker",
+  "/concepts/server-mcp": "https://docs.langchain.com/langsmith/server-mcp",
+  "/cloud/how-tos/human_in_the_loop_time_travel": "https://docs.langchain.com/langsmith/human-in-the-loop-time-travel",
+  "/cloud/how-tos/add-human-in-the-loop": "https://docs.langchain.com/langsmith/add-human-in-the-loop",
+  "/cloud/deployment/egress": "https://docs.langchain.com/langsmith/env-var",
+  "/cloud/how-tos/streaming": "https://docs.langchain.com/langsmith/streaming",
+  "/cloud/reference/api/api_ref": "https://docs.langchain.com/langsmith/server-api-ref",
+  "/cloud/reference/langgraph_server_changelog": "https://docs.langchain.com/langsmith/agent-server-changelog",
+  "/cloud/reference/api/api_ref_control_plane": "https://docs.langchain.com/langsmith/api-ref-control-plane",
+  "/cloud/reference/cli": "https://docs.langchain.com/langsmith/cli",
+  "/cloud/reference/env_var": "https://docs.langchain.com/langsmith/env-var",
+  "/troubleshooting/studio": "https://docs.langchain.com/langsmith/troubleshooting-studio",
+  "/index": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/agents/agents": "https://docs.langchain.com/oss/python/langchain/agents",
+  "/concepts/why-langgraph": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/tutorials/get-started/1-build-basic-chatbot": "https://docs.langchain.com/oss/python/langgraph/quickstart",
+  "/tutorials/get-started/2-add-tools": "https://docs.langchain.com/oss/python/langgraph/quickstart",
+  "/tutorials/get-started/3-add-memory": "https://docs.langchain.com/oss/python/langgraph/quickstart",
+  "/tutorials/get-started/4-human-in-the-loop": "https://docs.langchain.com/oss/python/langgraph/quickstart",
+  "/tutorials/get-started/5-customize-state": "https://docs.langchain.com/oss/python/langgraph/quickstart",
+  "/tutorials/get-started/6-time-travel": "https://docs.langchain.com/oss/python/langgraph/quickstart",
+  "/tutorials/langsmith/local-server": "https://docs.langchain.com/oss/python/langgraph/local-server",
+  "/tutorials/workflows": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
+  "/tutorials/plan-and-execute/plan-and-execute": "https://docs.langchain.com/oss/python/langchain/middleware/built-in#to-do-list",
+  "/tutorials/langgraph-platform/local-server/local-server": "https://docs.langchain.com/langsmith/local-server",
+  "/concepts/agentic_concepts": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
+  "/agents/overview": "https://docs.langchain.com/oss/python/langchain/agents",
+  "/agents/run_agents": "https://docs.langchain.com/oss/python/langgraph/quickstart",
+  "/concepts/low_level": "https://docs.langchain.com/oss/python/langgraph/graph-api",
+  "/how-tos/graph-api": "https://docs.langchain.com/oss/python/langgraph/graph-api",
+  "/how-tos/react-agent-from-scratch": "https://docs.langchain.com/oss/python/langchain/quickstart",
+  "/concepts/functional_api": "https://docs.langchain.com/oss/python/langgraph/functional-api",
+  "/how-tos/use-functional-api": "https://docs.langchain.com/oss/python/langgraph/functional-api",
+  "/concepts/pregel": "https://docs.langchain.com/oss/python/langgraph/pregel",
+  "/concepts/streaming": "https://docs.langchain.com/oss/python/langgraph/streaming",
+  "/how-tos/streaming": "https://docs.langchain.com/oss/python/langgraph/streaming",
+  "/concepts/persistence": "https://docs.langchain.com/oss/python/langgraph/persistence",
+  "/concepts/durable_execution": "https://docs.langchain.com/oss/python/langgraph/durable-execution",
+  "/concepts/memory": "https://docs.langchain.com/oss/python/langgraph/memory",
+  "/how-tos/memory/add-memory": "https://docs.langchain.com/oss/python/langgraph/add-memory",
+  "/agents/context": "https://docs.langchain.com/oss/python/langgraph/add-memory",
+  "/agents/models": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/concepts/tools": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
+  "/how-tos/tool-calling": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
+  "/concepts/human_in_the_loop": "https://docs.langchain.com/oss/python/langgraph/interrupts",
+  "/how-tos/human_in_the_loop/add-human-in-the-loop": "https://docs.langchain.com/oss/python/langgraph/interrupts",
+  "/concepts/time-travel": "https://docs.langchain.com/oss/python/langgraph/persistence",
+  "/how-tos/human_in_the_loop/time-travel": "https://docs.langchain.com/oss/python/langgraph/use-time-travel",
+  "/concepts/subgraphs": "https://docs.langchain.com/oss/python/langgraph/use-subgraphs",
+  "/how-tos/subgraph": "https://docs.langchain.com/oss/python/langgraph/use-subgraphs",
+  "/concepts/multi_agent": "https://docs.langchain.com/oss/python/langgraph/graph-api",
+  "/agents/multi-agent": "https://docs.langchain.com/oss/python/langchain/multi-agent",
+  "/how-tos/multi_agent": "https://docs.langchain.com/oss/python/langgraph/graph-api",
+  "/concepts/mcp": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/agents/mcp": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/concepts/tracing": "https://docs.langchain.com/oss/python/langgraph/observability",
+  "/how-tos/enable-tracing": "https://docs.langchain.com/oss/python/langgraph/observability",
+  "/agents/evals": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/concepts/template_applications": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/tutorials/rag/langgraph_agentic_rag": "https://docs.langchain.com/oss/python/langgraph/agentic-rag",
+  "/tutorials/multi_agent/agent_supervisor": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
+  "/tutorials/sql/sql-agent": "https://docs.langchain.com/oss/python/langgraph/sql-agent",
+  "/agents/ui": "https://docs.langchain.com/oss/python/langgraph/ui",
+  "/how-tos/run-id-langsmith": "https://docs.langchain.com/oss/python/langgraph/observability",
+  "/troubleshooting/errors/index": "https://docs.langchain.com/oss/python/langgraph/common-errors",
+  "/troubleshooting/errors/INVALID_CHAT_HISTORY": "https://docs.langchain.com/oss/python/langgraph/INVALID_CHAT_HISTORY",
+  "/troubleshooting/errors/INVALID_LICENSE": "https://docs.langchain.com/oss/python/langgraph/common-errors",
+  "/adopters": "https://docs.langchain.com/oss/python/langgraph/case-studies",
+  "/concepts/faq": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/agents/prebuilt": "https://docs.langchain.com/oss/python/langchain/agents",
+  "/reference/index": "https://reference.langchain.com/python/langgraph/",
+  "/reference/graphs": "https://reference.langchain.com/python/langgraph/graphs/",
+  "/reference/func": "https://reference.langchain.com/python/langgraph/func/",
+  "/reference/pregel": "https://reference.langchain.com/python/langgraph/pregel/",
+  "/reference/checkpoints": "https://reference.langchain.com/python/langgraph/checkpoints/",
+  "/reference/store": "https://reference.langchain.com/python/langgraph/store/",
+  "/reference/cache": "https://reference.langchain.com/python/langgraph/cache/",
+  "/reference/types": "https://reference.langchain.com/python/langgraph/types/",
+  "/reference/runtime": "https://reference.langchain.com/python/langgraph/runtime/",
+  "/reference/config": "https://reference.langchain.com/python/langgraph/config/",
+  "/reference/errors": "https://reference.langchain.com/python/langgraph/errors/",
+  "/reference/constants": "https://reference.langchain.com/python/langgraph/constants/",
+  "/reference/channels": "https://reference.langchain.com/python/langgraph/channels/",
+  "/reference/agents": "https://reference.langchain.com/python/langgraph/agents/",
+  "/reference/supervisor": "https://reference.langchain.com/python/langgraph/supervisor/",
+  "/reference/swarm": "https://reference.langchain.com/python/langgraph/swarm/",
+  "/reference/mcp": "https://reference.langchain.com/python/langgraph/mcp/",
+  "/cloud/reference/sdk/python_sdk_ref": "https://reference.langchain.com/python/langsmith/deployment/sdk/",
+  "/reference/remote_graph": "https://reference.langchain.com/python/langsmith/deployment/remote_graph/",
+  "/additional-resources/index": "https://docs.langchain.com/oss/python/langchain/overview",
+  "/cloud/reference/sdk/js_ts_sdk_ref": "https://reference.langchain.com/javascript/modules/langsmith.html",
+  "/snippets/chat_model_tabs": "https://docs.langchain.com/oss/python/langchain/overview",
+  "/troubleshooting/errors/GRAPH_RECURSION_LIMIT": "https://docs.langchain.com/oss/python/langgraph/GRAPH_RECURSION_LIMIT",
+  "/troubleshooting/errors/INVALID_CONCURRENT_GRAPH_UPDATE": "https://docs.langchain.com/oss/python/langgraph/INVALID_CONCURRENT_GRAPH_UPDATE",
+  "/troubleshooting/errors/INVALID_GRAPH_NODE_RETURN_VALUE": "https://docs.langchain.com/oss/python/langgraph/INVALID_GRAPH_NODE_RETURN_VALUE",
+  "/troubleshooting/errors/MULTIPLE_SUBGRAPHS": "https://docs.langchain.com/oss/python/langgraph/MULTIPLE_SUBGRAPHS",
+  "/tutorials/rag/langgraph_self_rag": "https://docs.langchain.com/oss/python/langgraph/agentic-rag",
+  "/additional-resources": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/examples": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/guides": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/how-tos/autogen-integration-functional": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/how-tos/cross-thread-persistence-functional": "https://docs.langchain.com/oss/python/langgraph/add-memory#add-long-term-memory",
+  "/how-tos/disable-streaming": "https://docs.langchain.com/oss/python/langgraph/streaming",
+  "/how-tos/memory/semantic-search": "https://docs.langchain.com/oss/python/langgraph/add-memory",
+  "/how-tos/multi-agent-multi-turn-convo-functional": "https://docs.langchain.com/oss/python/langgraph/graph-api",
+  "/how-tos/multi-agent-network-functional": "https://docs.langchain.com/oss/python/langgraph/graph-api",
+  "/how-tos/persistence-functional": "https://docs.langchain.com/oss/python/langgraph/add-memory",
+  "/how-tos/react-agent-from-scratch-functional": "https://docs.langchain.com/oss/python/langgraph/workflows-agents",
+  "/reference": "https://reference.langchain.com/python/langgraph/",
+  "/troubleshooting/errors": "https://docs.langchain.com/oss/python/langgraph/common-errors",
+  "/tutorials/chatbot-simulation-evaluation/agent-simulation-evaluation": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/tutorials/chatbot-simulation-evaluation/langsmith-agent-simulation-evaluation": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/tutorials/chatbots/information-gather-prompting": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/tutorials/extraction/retries": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/tutorials/langgraph-platform/local-server": "https://docs.langchain.com/langsmith/agent-server",
+  "/tutorials/lats/lats": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/tutorials/llm-compiler/LLMCompiler": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/tutorials/rag/langgraph_adaptive_rag_local": "https://docs.langchain.com/oss/python/langgraph/agentic-rag",
+  "/tutorials/rag/langgraph_crag": "https://docs.langchain.com/oss/python/langgraph/agentic-rag",
+  "/tutorials/rag/langgraph_crag_local": "https://docs.langchain.com/oss/python/langgraph/agentic-rag",
+  "/tutorials/rag/langgraph_self_rag_local": "https://docs.langchain.com/oss/python/langgraph/agentic-rag",
+  "/tutorials/reflection/reflection": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/tutorials/reflexion/reflexion": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/tutorials/rewoo/rewoo": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/tutorials/self-discover/self-discover": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/tutorials/tnt-llm/tnt-llm": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/tutorials/tot/tot": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/tutorials/usaco/usaco": "https://docs.langchain.com/oss/python/langgraph/overview",
+  "/tutorials/web-navigation/web_voyager": "https://docs.langchain.com/oss/python/langgraph/overview"
+}

examples/README.md

@@ -0,0 +1,3 @@
+# LangGraph examples
+
+This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview). Please refer to the LangChain docs for the most up-to-date examples and usage guidelines for LangGraph.

examples/chatbot-simulation-evaluation/agent-simulation-evaluation.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "10251c1c",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/chatbot-simulation-evaluation/agent-simulation-evaluation.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c5fc63df",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/chatbot-simulation-evaluation/langsmith-agent-simulation-evaluation.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "a4351a24",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/chatbot-simulation-evaluation/langsmith-agent-simulation-evaluation.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4cc9af1e",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/chatbot-simulation-evaluation/simulation_utils.py

@@ -0,0 +1,203 @@
+import functools
+from typing import Annotated, Any, Callable, Dict, List, Optional, Union
+
+from langchain_community.adapters.openai import convert_message_to_dict
+from langchain_core.messages import AIMessage, AnyMessage, BaseMessage, HumanMessage
+from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
+from langchain_core.runnables import Runnable, RunnableLambda
+from langchain_core.runnables import chain as as_runnable
+from langchain_openai import ChatOpenAI
+from typing_extensions import TypedDict
+
+from langgraph.graph import END, StateGraph, START
+
+
+def langchain_to_openai_messages(messages: List[BaseMessage]):
+    """
+    Convert a list of langchain base messages to a list of openai messages.
+
+    Parameters:
+        messages (List[BaseMessage]): A list of langchain base messages.
+
+    Returns:
+        List[dict]: A list of openai messages.
+    """
+
+    return [
+        convert_message_to_dict(m) if isinstance(m, BaseMessage) else m
+        for m in messages
+    ]
+
+
+def create_simulated_user(
+    system_prompt: str, llm: Runnable | None = None
+) -> Runnable[Dict, AIMessage]:
+    """
+    Creates a simulated user for chatbot simulation.
+
+    Args:
+        system_prompt (str): The system prompt to be used by the simulated user.
+        llm (Runnable | None, optional): The language model to be used for the simulation.
+            Defaults to gpt-3.5-turbo.
+
+    Returns:
+        Runnable[Dict, AIMessage]: The simulated user for chatbot simulation.
+    """
+    return ChatPromptTemplate.from_messages(
+        [
+            ("system", system_prompt),
+            MessagesPlaceholder(variable_name="messages"),
+        ]
+    ) | (llm or ChatOpenAI(model="gpt-3.5-turbo")).with_config(
+        run_name="simulated_user"
+    )
+
+
+Messages = Union[list[AnyMessage], AnyMessage]
+
+
+def add_messages(left: Messages, right: Messages) -> Messages:
+    if not isinstance(left, list):
+        left = [left]
+    if not isinstance(right, list):
+        right = [right]
+    return left + right
+
+
+class SimulationState(TypedDict):
+    """
+    Represents the state of a simulation.
+
+    Attributes:
+        messages (List[AnyMessage]): A list of messages in the simulation.
+        inputs (Optional[dict[str, Any]]): Optional inputs for the simulation.
+    """
+
+    messages: Annotated[List[AnyMessage], add_messages]
+    inputs: Optional[dict[str, Any]]
+
+
+def create_chat_simulator(
+    assistant: (
+        Callable[[List[AnyMessage]], str | AIMessage]
+        | Runnable[List[AnyMessage], str | AIMessage]
+    ),
+    simulated_user: Runnable[Dict, AIMessage],
+    *,
+    input_key: str,
+    max_turns: int = 6,
+    should_continue: Optional[Callable[[SimulationState], str]] = None,
+):
+    """Creates a chat simulator for evaluating a chatbot.
+
+    Args:
+        assistant: The chatbot assistant function or runnable object.
+        simulated_user: The simulated user object.
+        input_key: The key for the input to the chat simulation.
+        max_turns: The maximum number of turns in the chat simulation. Default is 6.
+        should_continue: Optional function to determine if the simulation should continue.
+            If not provided, a default function will be used.
+
+    Returns:
+        The compiled chat simulation graph.
+
+    """
+    graph_builder = StateGraph(SimulationState)
+    graph_builder.add_node(
+        "user",
+        _create_simulated_user_node(simulated_user),
+    )
+    graph_builder.add_node(
+        "assistant", _fetch_messages | assistant | _coerce_to_message
+    )
+    graph_builder.add_edge("assistant", "user")
+    graph_builder.add_conditional_edges(
+        "user",
+        should_continue or functools.partial(_should_continue, max_turns=max_turns),
+    )
+    # If your dataset has a 'leading question/input', then we route first to the assistant, otherwise, we let the user take the lead.
+    graph_builder.add_edge(START, "assistant" if input_key is not None else "user")
+
+    return (
+        RunnableLambda(_prepare_example).bind(input_key=input_key)
+        | graph_builder.compile()
+    )
+
+
+## Private methods
+
+
+def _prepare_example(inputs: dict[str, Any], input_key: Optional[str] = None):
+    if input_key is not None:
+        if input_key not in inputs:
+            raise ValueError(
+                f"Dataset's example input must contain the provided input key: '{input_key}'.\nFound: {list(inputs.keys())}"
+            )
+        messages = [HumanMessage(content=inputs[input_key])]
+        return {
+            "inputs": {k: v for k, v in inputs.items() if k != input_key},
+            "messages": messages,
+        }
+    return {"inputs": inputs, "messages": []}
+
+
+def _invoke_simulated_user(state: SimulationState, simulated_user: Runnable):
+    """Invoke the simulated user node."""
+    runnable = (
+        simulated_user
+        if isinstance(simulated_user, Runnable)
+        else RunnableLambda(simulated_user)
+    )
+    inputs = state.get("inputs", {})
+    inputs["messages"] = state["messages"]
+    return runnable.invoke(inputs)
+
+
+def _swap_roles(state: SimulationState):
+    new_messages = []
+    for m in state["messages"]:
+        if isinstance(m, AIMessage):
+            new_messages.append(HumanMessage(content=m.content))
+        else:
+            new_messages.append(AIMessage(content=m.content))
+    return {
+        "inputs": state.get("inputs", {}),
+        "messages": new_messages,
+    }
+
+
+@as_runnable
+def _fetch_messages(state: SimulationState):
+    """Invoke the simulated user node."""
+    return state["messages"]
+
+
+def _convert_to_human_message(message: BaseMessage):
+    return {"messages": [HumanMessage(content=message.content)]}
+
+
+def _create_simulated_user_node(simulated_user: Runnable):
+    """Simulated user accepts a {"messages": [...]} argument and returns a single message."""
+    return (
+        _swap_roles
+        | RunnableLambda(_invoke_simulated_user).bind(simulated_user=simulated_user)
+        | _convert_to_human_message
+    )
+
+
+def _coerce_to_message(assistant_output: str | BaseMessage):
+    if isinstance(assistant_output, str):
+        return {"messages": [AIMessage(content=assistant_output)]}
+    else:
+        return {"messages": [assistant_output]}
+
+
+def _should_continue(state: SimulationState, max_turns: int = 6):
+    messages = state["messages"]
+    # TODO support other stop criteria
+    if len(messages) > max_turns:
+        return END
+    elif messages[-1].content.strip() == "FINISHED":
+        return END
+    else:
+        return "assistant"

examples/chatbots/information-gather-prompting.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "a9014f94",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/chatbots/information-gather-prompting.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f47ce992",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/code_assistant/langgraph_code_assistant.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "1f2f13ca",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/code_assistant/langgraph_code_assistant.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5e4c9bfe",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/customer-support/customer-support.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "a8232bc9",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/customer-support/customer-support.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "63da8671",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/extraction/retries.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "8dbdba5b",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/extraction/retries.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1d444b7f",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/human_in_the_loop/wait-user-input.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "3ecab357",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/how-tos/human_in_the_loop/wait-user-input.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3f2866bd",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/lats/lats.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "09038b53",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/lats/lats.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b1669748",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/llm-compiler/LLMCompiler.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "85205e97",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/llm-compiler/LLMCompiler.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2fdab366",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/multi_agent/hierarchical_agent_teams.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "5cc8a2ad",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/multi_agent/hierarchical_agent_teams.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b9f3508a",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/multi_agent/multi-agent-collaboration.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "d2b507b9",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/multi_agent/multi-agent-collaboration.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "41a8f10a",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/plan-and-execute/plan-and-execute.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "9138f92e",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/plan-and-execute/plan-and-execute.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "093678ba",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/react-agent-from-scratch.ipynb

@@ -0,0 +1,40 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "294995c4",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/how-tos/react-agent-from-scratch.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

examples/react-agent-structured-output.ipynb

@@ -0,0 +1,40 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "40f0d107",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/how-tos/react-agent-structured-output.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

examples/reflection/reflection.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "658773a2",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/reflection/reflection.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1cb60657",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/reflexion/reflexion.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "caf07859",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/reflexion/reflexion.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cd1df0e0",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/rewoo/rewoo.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "961f43ec",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/rewoo/rewoo.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7f00c427",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/run-id-langsmith.ipynb

@@ -0,0 +1,40 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "bbd6e9b8",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/how-tos/run-id-langsmith.md)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

examples/self-discover/self-discover.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "f6db1873",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/self-discover/self-discover.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "219a78f9",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/subgraph.ipynb

@@ -0,0 +1,40 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "f49876e1",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/how-tos/subgraph.md)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

examples/tool-calling.ipynb

@@ -0,0 +1,40 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "7fd8bd65",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/how-tos/tool-calling.md)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

examples/tutorials/sql-agent.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "83c2223f",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/sql/sql-agent.md)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "57f924b1",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/tutorials/tnt-llm/tnt-llm.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "11140167",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/tnt-llm/tnt-llm.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1a2ba3e6",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/usaco/usaco.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "9dffdb54",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/usaco/usaco.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "579c9959",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/web-navigation/web_voyager.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "007ea2e9",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/web-navigation/web_voyager.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f0d7b895",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

libs/checkpoint-conformance/Makefile

@@ -0,0 +1,12 @@
+.PHONY: format lint test
+
+format:
+	uv run ruff format .
+	uv run ruff check --fix .
+
+lint:
+	uv run ruff check .
+	uv run ty check
+
+test:
+	uv run pytest $(TEST)

libs/checkpoint-conformance/README.md

@@ -0,0 +1,111 @@
+# langgraph-checkpoint-conformance
+
+Conformance test suite for [LangGraph](https://github.com/langchain-ai/langgraph) checkpointer implementations.
+
+Validates that a `BaseCheckpointSaver` subclass correctly implements the checkpoint storage contract — blob round-trips, metadata preservation, namespace isolation, incremental channel updates, and more.
+
+## Installation
+
+```bash
+pip install langgraph-checkpoint-conformance
+```
+
+## Quick start
+
+Register your checkpointer with `@checkpointer_test` and run `validate()`:
+
+```python
+import asyncio
+from langgraph.checkpoint.conformance import checkpointer_test, validate
+
+@checkpointer_test(name="MyCheckpointer")
+async def my_checkpointer():
+    saver = MyCheckpointer(...)
+    yield saver
+    # cleanup runs after yield
+
+async def main():
+    report = await validate(my_checkpointer)
+    report.print_report()
+    assert report.passed_all_base()
+
+asyncio.run(main())
+```
+
+Or in a pytest test:
+
+```python
+import pytest
+from langgraph.checkpoint.conformance import checkpointer_test, validate
+
+@checkpointer_test(name="MyCheckpointer")
+async def my_checkpointer():
+    yield MyCheckpointer(...)
+
+@pytest.mark.asyncio
+async def test_conformance():
+    report = await validate(my_checkpointer)
+    report.print_report()
+    assert report.passed_all_base()
+```
+
+## Capabilities
+
+The suite tests **base** capabilities (required) and **extended** capabilities (optional, auto-detected):
+
+| Capability | Required | Method |
+|---|---|---|
+| `put` | yes | `aput` |
+| `put_writes` | yes | `aput_writes` |
+| `get_tuple` | yes | `aget_tuple` |
+| `list` | yes | `alist` |
+| `delete_thread` | yes | `adelete_thread` |
+| `delete_for_runs` | no | `adelete_for_runs` |
+| `copy_thread` | no | `acopy_thread` |
+| `prune` | no | `aprune` |
+
+Extended capabilities are detected by checking whether the method is overridden from `BaseCheckpointSaver`. If not overridden, those tests are skipped.
+
+## Options
+
+### Progress output
+
+```python
+from langgraph.checkpoint.conformance.report import ProgressCallbacks
+
+# Dot-style progress (. per pass, F per fail)
+report = await validate(my_checkpointer, progress=ProgressCallbacks.default())
+
+# Verbose (per-test names + stacktraces on failure)
+report = await validate(my_checkpointer, progress=ProgressCallbacks.verbose())
+```
+
+### Skip capabilities
+
+```python
+@checkpointer_test(name="MyCheckpointer", skip_capabilities={"prune"})
+async def my_checkpointer():
+    yield MyCheckpointer(...)
+```
+
+### Run specific capabilities
+
+```python
+report = await validate(my_checkpointer, capabilities={"put", "list"})
+```
+
+### Lifespan (one-time setup/teardown)
+
+For expensive setup like database creation:
+
+```python
+async def db_lifespan():
+    await create_database()
+    yield
+    await drop_database()
+
+@checkpointer_test(name="PostgresSaver", lifespan=db_lifespan)
+async def pg_checkpointer():
+    async with PostgresSaver.from_conn_string(CONN_STRING) as saver:
+        yield saver
+```

libs/checkpoint-conformance/langgraph/checkpoint/conformance/__init__.py

@@ -0,0 +1,9 @@
+"""langgraph-checkpoint-conformance: conformance test suite for checkpointer implementations."""
+
+from langgraph.checkpoint.conformance.initializer import checkpointer_test
+from langgraph.checkpoint.conformance.validate import validate
+
+__all__ = [
+    "checkpointer_test",
+    "validate",
+]

libs/checkpoint-conformance/langgraph/checkpoint/conformance/capabilities.py

@@ -0,0 +1,93 @@
+"""Capability detection for checkpointer implementations."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from enum import Enum
+from typing import TYPE_CHECKING
+
+from langgraph.checkpoint.base import BaseCheckpointSaver
+
+if TYPE_CHECKING:
+    pass
+
+
+class Capability(str, Enum):
+    """Capabilities that a checkpointer may support."""
+
+    PUT = "put"
+    PUT_WRITES = "put_writes"
+    GET_TUPLE = "get_tuple"
+    LIST = "list"
+    DELETE_THREAD = "delete_thread"
+    DELETE_FOR_RUNS = "delete_for_runs"
+    COPY_THREAD = "copy_thread"
+    PRUNE = "prune"
+
+
+# Capabilities that every checkpointer must support.
+BASE_CAPABILITIES = frozenset(
+    {
+        Capability.PUT,
+        Capability.PUT_WRITES,
+        Capability.GET_TUPLE,
+        Capability.LIST,
+        Capability.DELETE_THREAD,
+    }
+)
+
+# Capabilities that are optional extensions.
+EXTENDED_CAPABILITIES = frozenset(
+    {
+        Capability.DELETE_FOR_RUNS,
+        Capability.COPY_THREAD,
+        Capability.PRUNE,
+    }
+)
+
+ALL_CAPABILITIES = BASE_CAPABILITIES | EXTENDED_CAPABILITIES
+
+# Maps capability to the async method name on BaseCheckpointSaver (or subclass).
+_CAPABILITY_METHOD_MAP: dict[Capability, str] = {
+    Capability.PUT: "aput",
+    Capability.PUT_WRITES: "aput_writes",
+    Capability.GET_TUPLE: "aget_tuple",
+    Capability.LIST: "alist",
+    Capability.DELETE_THREAD: "adelete_thread",
+    Capability.DELETE_FOR_RUNS: "adelete_for_runs",
+    Capability.COPY_THREAD: "acopy_thread",
+    Capability.PRUNE: "aprune",
+}
+
+
+@dataclass(frozen=True)
+class DetectedCapabilities:
+    """Result of capability detection for a checkpointer type."""
+
+    detected: frozenset[Capability]
+    missing: frozenset[Capability]
+
+    @classmethod
+    def from_instance(cls, saver: BaseCheckpointSaver) -> DetectedCapabilities:
+        """Detect capabilities from a checkpointer instance."""
+        inner_type = type(saver)
+        detected: set[Capability] = set()
+
+        for cap, method_name in _CAPABILITY_METHOD_MAP.items():
+            if _is_overridden(inner_type, method_name):
+                detected.add(cap)
+
+        detected_fs = frozenset(detected)
+        return cls(
+            detected=detected_fs,
+            missing=ALL_CAPABILITIES - detected_fs,
+        )
+
+
+def _is_overridden(inner_type: type, method: str) -> bool:
+    """Check if *method* on *inner_type* differs from the base class default."""
+    base = getattr(BaseCheckpointSaver, method, None)
+    impl = getattr(inner_type, method, None)
+    if base is None or impl is None:
+        return impl is not None
+    return impl is not base

libs/checkpoint-conformance/langgraph/checkpoint/conformance/initializer.py

@@ -0,0 +1,100 @@
+"""Checkpointer test registration and factory management."""
+
+from __future__ import annotations
+
+from collections.abc import AsyncGenerator, Callable
+from contextlib import asynccontextmanager
+from dataclasses import dataclass, field
+from typing import Any
+
+from langgraph.checkpoint.base import BaseCheckpointSaver
+
+# Type for the lifespan async context manager factory.
+LifespanFactory = Callable[[], AsyncGenerator[None, None]]
+
+# Module-level registry of decorated checkpointer factories.
+_REGISTRY: dict[str, RegisteredCheckpointer] = {}
+
+
+async def _noop_lifespan() -> AsyncGenerator[None, None]:
+    yield
+
+
+@dataclass
+class RegisteredCheckpointer:
+    """A registered checkpointer test factory."""
+
+    name: str
+    factory: Callable[[], AsyncGenerator[BaseCheckpointSaver, None]]
+    skip_capabilities: set[str] = field(default_factory=set)
+    lifespan: LifespanFactory = _noop_lifespan
+
+    @asynccontextmanager
+    async def create(self) -> AsyncGenerator[BaseCheckpointSaver, None]:
+        """Create a fresh checkpointer instance via the async generator."""
+        gen = self.factory()
+        try:
+            saver = await gen.__anext__()
+            yield saver
+        finally:
+            try:
+                await gen.__anext__()
+            except StopAsyncIteration:
+                pass
+
+    @asynccontextmanager
+    async def enter_lifespan(self) -> AsyncGenerator[None, None]:
+        """Enter the lifespan context (once per validation run)."""
+        gen = self.lifespan()
+        try:
+            await gen.__anext__()
+            yield
+        finally:
+            try:
+                await gen.__anext__()
+            except StopAsyncIteration:
+                pass
+
+
+def checkpointer_test(
+    name: str,
+    *,
+    skip_capabilities: set[str] | None = None,
+    lifespan: LifespanFactory | None = None,
+) -> Callable[[Any], RegisteredCheckpointer]:
+    """Register an async generator as a checkpointer test factory.
+
+    The factory is called once per capability suite to create a fresh
+    checkpointer.  The optional `lifespan` is an async generator that
+    runs once for the entire validation run (e.g. to create/destroy a
+    database).
+
+    Example::
+
+        @checkpointer_test(name="InMemorySaver")
+        async def memory_checkpointer():
+            yield InMemorySaver()
+
+    With lifespan::
+
+        async def pg_lifespan():
+            await create_database()
+            yield
+            await drop_database()
+
+        @checkpointer_test(name="PostgresSaver", lifespan=pg_lifespan)
+        async def pg_checkpointer():
+            yield PostgresSaver(conn_string="...")
+    """
+
+    def decorator(fn: Any) -> RegisteredCheckpointer:
+        registered = RegisteredCheckpointer(
+            name=name,
+            factory=fn,
+            skip_capabilities=skip_capabilities or set(),
+            lifespan=lifespan or _noop_lifespan,
+        )
+        _REGISTRY[name] = registered
+        return registered
+
+    return decorator

libs/checkpoint-conformance/langgraph/checkpoint/conformance/report.py

@@ -0,0 +1,198 @@
+"""Capability report: results, progress callbacks, and pretty-printing."""
+
+from __future__ import annotations
+
+from collections.abc import Callable
+from dataclasses import dataclass, field
+from typing import Any
+
+from langgraph.checkpoint.conformance.capabilities import (
+    BASE_CAPABILITIES,
+    EXTENDED_CAPABILITIES,
+    Capability,
+)
+
+# Callback type for per-test progress reporting.
+# (capability_name, test_name, passed, error_msg_or_None) -> None
+OnTestResult = Callable[[str, str, bool, str | None], None]
+
+# Callback type for capability-level events.
+# (capability_name, detected) -> None
+OnCapabilityStart = Callable[[str, bool], None]
+
+
+class ProgressCallbacks:
+    """Grouped callbacks for progress reporting during validation."""
+
+    def __init__(
+        self,
+        *,
+        on_capability_start: Callable[[str, bool], None] | None = None,
+        on_test_result: OnTestResult | None = None,
+        on_capability_end: Callable[[str], None] | None = None,
+    ) -> None:
+        self.on_capability_start = on_capability_start
+        self.on_test_result = on_test_result
+        self.on_capability_end = on_capability_end
+
+    @classmethod
+    def default(cls) -> ProgressCallbacks:
+        """Dot-style progress: ``.`` per pass, ``F`` per fail."""
+
+        def _cap_start(capability: str, detected: bool) -> None:
+            if detected:
+                print(f"  {capability}: ", end="", flush=True)
+            else:
+                print(f"  ⊘ {capability} (not implemented)")
+
+        def _test_result(
+            capability: str, test_name: str, passed: bool, error: str | None
+        ) -> None:
+            print("." if passed else "F", end="", flush=True)
+
+        def _cap_end(capability: str) -> None:
+            print()  # newline after dots
+
+        return cls(
+            on_capability_start=_cap_start,
+            on_test_result=_test_result,
+            on_capability_end=_cap_end,
+        )
+
+    @classmethod
+    def verbose(cls) -> ProgressCallbacks:
+        """Per-test output with names and errors."""
+
+        def _cap_start(capability: str, detected: bool) -> None:
+            if detected:
+                print(f"  {capability}:")
+            else:
+                print(f"  ⊘ {capability} (not implemented)")
+
+        def _test_result(
+            capability: str, test_name: str, passed: bool, error: str | None
+        ) -> None:
+            icon = "✓" if passed else "✗"
+            print(f"    {icon} {test_name}")
+            if error:
+                for line in error.rstrip().splitlines():
+                    print(f"      {line}")
+
+        return cls(
+            on_capability_start=_cap_start,
+            on_test_result=_test_result,
+        )
+
+    @classmethod
+    def quiet(cls) -> ProgressCallbacks:
+        """No progress output."""
+        return cls()
+
+
+@dataclass
+class CapabilityResult:
+    """Result of running a single capability's test suite."""
+
+    detected: bool = False
+    passed: bool | None = None  # None = skipped
+    tests_passed: int = 0
+    tests_failed: int = 0
+    tests_skipped: int = 0
+    failures: list[str] = field(default_factory=list)
+
+
+@dataclass
+class CapabilityReport:
+    """Aggregate report across all capabilities."""
+
+    checkpointer_name: str
+    results: dict[str, CapabilityResult] = field(default_factory=dict)
+
+    def passed_all_base(self) -> bool:
+        """Whether all base capability tests passed."""
+        for cap in BASE_CAPABILITIES:
+            result = self.results.get(cap.value)
+            if result is None or result.passed is not True:
+                return False
+        return True
+
+    def passed_all(self) -> bool:
+        """Whether every detected capability's tests passed."""
+        for result in self.results.values():
+            if result.detected and result.passed is not True:
+                return False
+        return True
+
+    def conformance_level(self) -> str:
+        """Return a human-readable conformance level string."""
+        if self.passed_all():
+            return "FULL"
+        if self.passed_all_base():
+            return "BASE+PARTIAL"
+        return "BASE" if self._any_base_passed() else "NONE"
+
+    def _any_base_passed(self) -> bool:
+        for cap in BASE_CAPABILITIES:
+            result = self.results.get(cap.value)
+            if result and result.passed is True:
+                return True
+        return False
+
+    def print_report(self) -> None:
+        """Pretty-print the report to stdout."""
+        width = 52
+        border = "=" * width
+        print(f"\n{'':>2}{border}")
+        print(f"{'':>2}  Checkpointer Validation: {self.checkpointer_name}")
+        print(f"{'':>2}{border}")
+
+        def _section(title: str, caps: frozenset[Capability]) -> None:
+            print(f"{'':>2}  {title}")
+            for cap in sorted(caps, key=lambda c: c.value):
+                result = self.results.get(cap.value)
+                if result is None:
+                    icon = "  "
+                    suffix = "(no tests)"
+                elif not result.detected:
+                    icon = "⊘ "
+                    suffix = "(not implemented)"
+                elif result.passed is True:
+                    icon = "✅"
+                    suffix = ""
+                elif result.passed is False:
+                    icon = "❌"
+                    suffix = f"({result.tests_failed} failed)"
+                else:
+                    icon = "⏭ "
+                    suffix = "(skipped)"
+                print(f"{'':>2}    {icon} {cap.value:20s} {suffix}")
+            print()
+
+        _section("BASE CAPABILITIES", BASE_CAPABILITIES)
+        _section("EXTENDED CAPABILITIES", EXTENDED_CAPABILITIES)
+
+        total = sum(1 for r in self.results.values() if r.detected)
+        passed = sum(
+            1 for r in self.results.values() if r.detected and r.passed is True
+        )
+        level = self.conformance_level()
+        print(f"{'':>2}  Result: {level} ({passed}/{total})")
+        print(f"{'':>2}{border}\n")
+
+    def to_dict(self) -> dict[str, Any]:
+        """Return a JSON-serializable dict."""
+        return {
+            "checkpointer_name": self.checkpointer_name,
+            "conformance_level": self.conformance_level(),
+            "results": {
+                name: {
+                    "detected": r.detected,
+                    "passed": r.passed,
+                    "tests_passed": r.tests_passed,
+                    "tests_failed": r.tests_failed,
+                    "tests_skipped": r.tests_skipped,
+                    "failures": r.failures,
+                }
+                for name, r in self.results.items()
+            },
+        }

libs/checkpoint-conformance/langgraph/checkpoint/conformance/spec/__init__.py

@@ -0,0 +1,27 @@
+"""Test spec modules for each checkpointer capability."""
+
+from langgraph.checkpoint.conformance.spec.test_copy_thread import (
+    run_copy_thread_tests,
+)
+from langgraph.checkpoint.conformance.spec.test_delete_for_runs import (
+    run_delete_for_runs_tests,
+)
+from langgraph.checkpoint.conformance.spec.test_delete_thread import (
+    run_delete_thread_tests,
+)
+from langgraph.checkpoint.conformance.spec.test_get_tuple import run_get_tuple_tests
+from langgraph.checkpoint.conformance.spec.test_list import run_list_tests
+from langgraph.checkpoint.conformance.spec.test_prune import run_prune_tests
+from langgraph.checkpoint.conformance.spec.test_put import run_put_tests
+from langgraph.checkpoint.conformance.spec.test_put_writes import run_put_writes_tests
+
+__all__ = [
+    "run_put_tests",
+    "run_put_writes_tests",
+    "run_get_tuple_tests",
+    "run_list_tests",
+    "run_delete_thread_tests",
+    "run_delete_for_runs_tests",
+    "run_copy_thread_tests",
+    "run_prune_tests",
+]

libs/checkpoint-conformance/langgraph/checkpoint/conformance/spec/test_copy_thread.py

@@ -0,0 +1,250 @@
+"""COPY_THREAD capability tests — acopy_thread."""
+
+from __future__ import annotations
+
+import traceback
+from collections.abc import Callable
+from uuid import uuid4
+
+from langgraph.checkpoint.base import BaseCheckpointSaver
+
+from langgraph.checkpoint.conformance.test_utils import (
+    generate_checkpoint,
+    generate_config,
+    generate_metadata,
+)
+
+
+async def _setup_source_thread(
+    saver: BaseCheckpointSaver,
+    tid: str,
+    *,
+    n: int = 3,
+    namespaces: list[str] | None = None,
+) -> list[dict]:
+    """Create n checkpoints on tid (optionally across namespaces). Returns stored configs."""
+    nss = namespaces or [""]
+    stored = []
+    for ns in nss:
+        parent_cfg = None
+        for i in range(n):
+            config = generate_config(tid, checkpoint_ns=ns)
+            if parent_cfg:
+                config["configurable"]["checkpoint_id"] = parent_cfg["configurable"][
+                    "checkpoint_id"
+                ]
+            cp = generate_checkpoint(channel_values={"step": i})
+            cp["channel_versions"] = {"step": 1}
+            parent_cfg = await saver.aput(
+                config, cp, generate_metadata(step=i), {"step": 1}
+            )
+            stored.append(parent_cfg)
+    return stored
+
+
+async def test_copy_thread_basic(saver: BaseCheckpointSaver) -> None:
+    """Checkpoints appear on target thread."""
+    src = str(uuid4())
+    dst = str(uuid4())
+    await _setup_source_thread(saver, src)
+
+    await saver.acopy_thread(src, dst)
+    results = []
+    async for tup in saver.alist(generate_config(dst)):
+        results.append(tup)
+    assert len(results) == 3, f"Expected 3 copied checkpoints, got {len(results)}"
+
+
+async def test_copy_thread_all_checkpoints(saver: BaseCheckpointSaver) -> None:
+    """All checkpoints copied, not just latest."""
+    src = str(uuid4())
+    dst = str(uuid4())
+    await _setup_source_thread(saver, src, n=3)
+
+    await saver.acopy_thread(src, dst)
+    src_results = []
+    async for tup in saver.alist(generate_config(src)):
+        src_results.append(tup)
+
+    dst_results = []
+    async for tup in saver.alist(generate_config(dst)):
+        dst_results.append(tup)
+
+    assert len(dst_results) == len(src_results)
+    # Verify content matches
+    for s, d in zip(
+        sorted(src_results, key=lambda t: t.checkpoint["id"]),
+        sorted(dst_results, key=lambda t: t.checkpoint["id"]),
+        strict=True,
+    ):
+        assert s.checkpoint["channel_values"] == d.checkpoint["channel_values"], (
+            f"channel_values mismatch for checkpoint {s.checkpoint['id']}"
+        )
+
+
+async def test_copy_thread_preserves_metadata(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Metadata intact on copied checkpoints."""
+    src = str(uuid4())
+    dst = str(uuid4())
+    await _setup_source_thread(saver, src, n=2)
+
+    await saver.acopy_thread(src, dst)
+    src_tuples = []
+    async for tup in saver.alist(generate_config(src)):
+        src_tuples.append(tup)
+
+    dst_tuples = []
+    async for tup in saver.alist(generate_config(dst)):
+        dst_tuples.append(tup)
+
+    for s, d in zip(
+        sorted(src_tuples, key=lambda t: t.metadata.get("step", 0)),
+        sorted(dst_tuples, key=lambda t: t.metadata.get("step", 0)),
+        strict=True,
+    ):
+        for key in s.metadata:
+            assert s.metadata.get(key) == d.metadata.get(key), (
+                f"metadata[{key!r}] mismatch: {s.metadata.get(key)!r} != {d.metadata.get(key)!r}"
+            )
+
+
+async def test_copy_thread_preserves_namespaces(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Root + child namespaces copied."""
+    src = str(uuid4())
+    dst = str(uuid4())
+    await _setup_source_thread(saver, src, n=1, namespaces=["", "child:1"])
+
+    await saver.acopy_thread(src, dst)
+    for ns in ["", "child:1"]:
+        results = []
+        async for tup in saver.alist(generate_config(dst, checkpoint_ns=ns)):
+            results.append(tup)
+        assert len(results) == 1, (
+            f"Expected 1 checkpoint in namespace '{ns}', got {len(results)}"
+        )
+
+
+async def test_copy_thread_preserves_writes(saver: BaseCheckpointSaver) -> None:
+    """Pending writes copied."""
+    src = str(uuid4())
+    dst = str(uuid4())
+    configs = await _setup_source_thread(saver, src, n=1)
+
+    # Add a write to the source
+    await saver.aput_writes(configs[-1], [("ch", "write_val")], str(uuid4()))
+
+    await saver.acopy_thread(src, dst)
+    tup = await saver.aget_tuple(generate_config(dst))
+    assert tup is not None
+    assert tup.pending_writes is not None
+    assert len(tup.pending_writes) == 1, (
+        f"Expected 1 write, got {len(tup.pending_writes)}"
+    )
+    assert tup.pending_writes[0][1] == "ch", (
+        f"channel mismatch: {tup.pending_writes[0][1]!r}"
+    )
+    assert tup.pending_writes[0][2] == "write_val", (
+        f"value mismatch: {tup.pending_writes[0][2]!r}"
+    )
+
+
+async def test_copy_thread_preserves_ordering(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Checkpoint order maintained."""
+    src = str(uuid4())
+    dst = str(uuid4())
+    await _setup_source_thread(saver, src, n=4)
+
+    await saver.acopy_thread(src, dst)
+    src_ids = []
+    async for tup in saver.alist(generate_config(src)):
+        src_ids.append(tup.checkpoint["id"])
+
+    dst_ids = []
+    async for tup in saver.alist(generate_config(dst)):
+        dst_ids.append(tup.checkpoint["id"])
+
+    # Order should match (both newest-first)
+    assert src_ids == dst_ids
+
+
+async def test_copy_thread_source_unchanged(saver: BaseCheckpointSaver) -> None:
+    """Source thread still intact after copy."""
+    src = str(uuid4())
+    dst = str(uuid4())
+    await _setup_source_thread(saver, src, n=2)
+
+    # Snapshot source before copy
+    src_before = []
+    async for tup in saver.alist(generate_config(src)):
+        src_before.append(tup.checkpoint["id"])
+
+    await saver.acopy_thread(src, dst)
+    # Source should be unchanged
+    src_after = []
+    async for tup in saver.alist(generate_config(src)):
+        src_after.append(tup.checkpoint["id"])
+
+    assert src_before == src_after
+
+
+async def test_copy_thread_nonexistent_source(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Graceful handling of non-existent source thread."""
+    src = str(uuid4())
+    dst = str(uuid4())
+
+    # Should not raise (or raise a known error)
+    try:
+        await saver.acopy_thread(src, dst)
+    except Exception:
+        pass  # Some implementations may raise; that's acceptable
+
+    # Destination should be empty
+    results = []
+    async for tup in saver.alist(generate_config(dst)):
+        results.append(tup)
+    assert len(results) == 0
+
+
+ALL_COPY_THREAD_TESTS = [
+    test_copy_thread_basic,
+    test_copy_thread_all_checkpoints,
+    test_copy_thread_preserves_metadata,
+    test_copy_thread_preserves_namespaces,
+    test_copy_thread_preserves_writes,
+    test_copy_thread_preserves_ordering,
+    test_copy_thread_source_unchanged,
+    test_copy_thread_nonexistent_source,
+]
+
+
+async def run_copy_thread_tests(
+    saver: BaseCheckpointSaver,
+    on_test_result: Callable[[str, str, bool, str | None], None] | None = None,
+) -> tuple[int, int, list[str]]:
+    """Run all copy_thread tests. Returns (passed, failed, failure_names)."""
+    passed = 0
+    failed = 0
+    failures: list[str] = []
+    for test_fn in ALL_COPY_THREAD_TESTS:
+        try:
+            await test_fn(saver)
+            passed += 1
+            if on_test_result:
+                on_test_result("copy_thread", test_fn.__name__, True, None)
+        except Exception as e:
+            failed += 1
+            msg = f"{test_fn.__name__}: {e}"
+            failures.append(msg)
+            if on_test_result:
+                on_test_result(
+                    "copy_thread", test_fn.__name__, False, traceback.format_exc()
+                )
+    return passed, failed, failures

libs/checkpoint-conformance/langgraph/checkpoint/conformance/spec/test_delete_for_runs.py

@@ -0,0 +1,218 @@
+"""DELETE_FOR_RUNS capability tests — adelete_for_runs."""
+
+from __future__ import annotations
+
+import traceback
+from collections.abc import Callable
+from uuid import uuid4
+
+from langgraph.checkpoint.base import BaseCheckpointSaver
+
+from langgraph.checkpoint.conformance.test_utils import (
+    generate_checkpoint,
+    generate_config,
+    generate_metadata,
+)
+
+
+async def _put_with_run_id(
+    saver: BaseCheckpointSaver,
+    tid: str,
+    run_id: str,
+    *,
+    checkpoint_ns: str = "",
+    parent_config: dict | None = None,
+) -> dict:
+    """Put a checkpoint with a run_id in metadata, return stored config."""
+    config = generate_config(tid, checkpoint_ns=checkpoint_ns)
+    if parent_config:
+        config["configurable"]["checkpoint_id"] = parent_config["configurable"][
+            "checkpoint_id"
+        ]
+    cp = generate_checkpoint()
+    md = generate_metadata(run_id=run_id)
+    return await saver.aput(config, cp, md, {})
+
+
+async def test_delete_for_runs_single(saver: BaseCheckpointSaver) -> None:
+    """One run_id removed."""
+    tid = str(uuid4())
+    run1, run2 = str(uuid4()), str(uuid4())
+
+    stored1 = await _put_with_run_id(saver, tid, run1)
+    await _put_with_run_id(saver, tid, run2, parent_config=stored1)
+
+    # Pre-delete: verify both runs exist
+    pre_results = []
+    async for tup in saver.alist(generate_config(tid)):
+        pre_results.append(tup)
+    pre_run_ids = {t.metadata.get("run_id") for t in pre_results}
+    assert run1 in pre_run_ids, "Pre-delete: run1 should exist"
+    assert run2 in pre_run_ids, "Pre-delete: run2 should exist"
+
+    await saver.adelete_for_runs([run1])
+    # run1's checkpoint should be gone; run2 should remain
+    results = []
+    async for tup in saver.alist(generate_config(tid)):
+        results.append(tup)
+
+    run_ids = {t.metadata.get("run_id") for t in results}
+    assert run1 not in run_ids
+    assert run2 in run_ids
+
+
+async def test_delete_for_runs_multiple(saver: BaseCheckpointSaver) -> None:
+    """List of run_ids removed."""
+    tid = str(uuid4())
+    run1, run2, run3 = str(uuid4()), str(uuid4()), str(uuid4())
+
+    s1 = await _put_with_run_id(saver, tid, run1)
+    s2 = await _put_with_run_id(saver, tid, run2, parent_config=s1)
+    await _put_with_run_id(saver, tid, run3, parent_config=s2)
+
+    # Pre-delete: verify all 3 runs exist
+    pre_results = []
+    async for tup in saver.alist(generate_config(tid)):
+        pre_results.append(tup)
+    pre_run_ids = {t.metadata.get("run_id") for t in pre_results}
+    assert run1 in pre_run_ids, "Pre-delete: run1 should exist"
+    assert run2 in pre_run_ids, "Pre-delete: run2 should exist"
+    assert run3 in pre_run_ids, "Pre-delete: run3 should exist"
+
+    await saver.adelete_for_runs([run1, run2])
+    results = []
+    async for tup in saver.alist(generate_config(tid)):
+        results.append(tup)
+
+    run_ids = {t.metadata.get("run_id") for t in results}
+    assert run1 not in run_ids
+    assert run2 not in run_ids
+    assert run3 in run_ids
+
+
+async def test_delete_for_runs_preserves_other_runs(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Unrelated runs untouched."""
+    tid = str(uuid4())
+    run_keep = str(uuid4())
+    run_delete = str(uuid4())
+
+    await _put_with_run_id(saver, tid, run_keep)
+    await _put_with_run_id(saver, tid, run_delete)
+
+    # Pre-delete: verify both runs exist
+    pre_results = []
+    async for tup in saver.alist(generate_config(tid)):
+        pre_results.append(tup)
+    pre_run_ids = {t.metadata.get("run_id") for t in pre_results}
+    assert run_keep in pre_run_ids, "Pre-delete: run_keep should exist"
+    assert run_delete in pre_run_ids, "Pre-delete: run_delete should exist"
+
+    await saver.adelete_for_runs([run_delete])
+    results = []
+    async for tup in saver.alist(generate_config(tid)):
+        results.append(tup)
+
+    run_ids = {t.metadata.get("run_id") for t in results}
+    assert run_keep in run_ids
+
+
+async def test_delete_for_runs_removes_writes(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Associated writes cleaned up."""
+    tid = str(uuid4())
+    run1 = str(uuid4())
+
+    stored = await _put_with_run_id(saver, tid, run1)
+    await saver.aput_writes(stored, [("ch", "val")], str(uuid4()))
+
+    # Pre-delete: verify writes exist
+    pre_tup = await saver.aget_tuple(stored)
+    assert pre_tup is not None, "Pre-delete: checkpoint should exist"
+    assert pre_tup.pending_writes is not None and len(pre_tup.pending_writes) == 1, (
+        f"Pre-delete: expected 1 write, got {len(pre_tup.pending_writes) if pre_tup.pending_writes else 0}"
+    )
+
+    await saver.adelete_for_runs([run1])
+    # The checkpoint (and its writes) should be gone
+    tup = await saver.aget_tuple(stored)
+    assert tup is None
+
+
+async def test_delete_for_runs_empty_list_noop(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Empty list no error."""
+    await saver.adelete_for_runs([])
+
+
+async def test_delete_for_runs_nonexistent_noop(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Missing run_ids no error."""
+    await saver.adelete_for_runs([str(uuid4())])
+
+
+async def test_delete_for_runs_across_namespaces(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """All namespaces cleaned."""
+    tid = str(uuid4())
+    run1 = str(uuid4())
+
+    await _put_with_run_id(saver, tid, run1, checkpoint_ns="")
+    await _put_with_run_id(saver, tid, run1, checkpoint_ns="child:1")
+
+    # Pre-delete: verify run1 present in both namespaces
+    for ns in ["", "child:1"]:
+        pre_results = []
+        async for tup in saver.alist(generate_config(tid, checkpoint_ns=ns)):
+            pre_results.append(tup)
+        pre_run_ids = {t.metadata.get("run_id") for t in pre_results}
+        assert run1 in pre_run_ids, f"Pre-delete: run1 should exist in ns='{ns}'"
+
+    await saver.adelete_for_runs([run1])
+    for ns in ["", "child:1"]:
+        results = []
+        async for tup in saver.alist(generate_config(tid, checkpoint_ns=ns)):
+            results.append(tup)
+        run_ids = {t.metadata.get("run_id") for t in results}
+        assert run1 not in run_ids
+
+
+ALL_DELETE_FOR_RUNS_TESTS = [
+    test_delete_for_runs_single,
+    test_delete_for_runs_multiple,
+    test_delete_for_runs_preserves_other_runs,
+    test_delete_for_runs_removes_writes,
+    test_delete_for_runs_empty_list_noop,
+    test_delete_for_runs_nonexistent_noop,
+    test_delete_for_runs_across_namespaces,
+]
+
+
+async def run_delete_for_runs_tests(
+    saver: BaseCheckpointSaver,
+    on_test_result: Callable[[str, str, bool, str | None], None] | None = None,
+) -> tuple[int, int, list[str]]:
+    """Run all delete_for_runs tests. Returns (passed, failed, failure_names)."""
+    passed = 0
+    failed = 0
+    failures: list[str] = []
+    for test_fn in ALL_DELETE_FOR_RUNS_TESTS:
+        try:
+            await test_fn(saver)
+            passed += 1
+            if on_test_result:
+                on_test_result("delete_for_runs", test_fn.__name__, True, None)
+        except Exception as e:
+            failed += 1
+            msg = f"{test_fn.__name__}: {e}"
+            failures.append(msg)
+            if on_test_result:
+                on_test_result(
+                    "delete_for_runs", test_fn.__name__, False, traceback.format_exc()
+                )
+    return passed, failed, failures

libs/checkpoint-conformance/langgraph/checkpoint/conformance/spec/test_delete_thread.py

@@ -0,0 +1,149 @@
+"""DELETE_THREAD capability tests — adelete_thread."""
+
+from __future__ import annotations
+
+import traceback
+from collections.abc import Callable
+from uuid import uuid4
+
+from langgraph.checkpoint.base import BaseCheckpointSaver
+
+from langgraph.checkpoint.conformance.test_utils import (
+    generate_checkpoint,
+    generate_config,
+    generate_metadata,
+)
+
+
+async def test_delete_thread_removes_checkpoints(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """All checkpoints gone after delete."""
+    tid = str(uuid4())
+    parent_cfg = None
+    for i in range(3):
+        config = generate_config(tid)
+        if parent_cfg:
+            config["configurable"]["checkpoint_id"] = parent_cfg["configurable"][
+                "checkpoint_id"
+            ]
+        cp = generate_checkpoint()
+        parent_cfg = await saver.aput(config, cp, generate_metadata(step=i), {})
+
+    # Pre-delete: verify data exists
+    assert await saver.aget_tuple(generate_config(tid)) is not None, (
+        "Pre-delete: checkpoint should exist"
+    )
+
+    await saver.adelete_thread(tid)
+
+    tup = await saver.aget_tuple(generate_config(tid))
+    assert tup is None
+
+    results = []
+    async for t in saver.alist(generate_config(tid)):
+        results.append(t)
+    assert len(results) == 0
+
+
+async def test_delete_thread_removes_writes(saver: BaseCheckpointSaver) -> None:
+    """Pending writes gone after delete."""
+    tid = str(uuid4())
+    config = generate_config(tid)
+    cp = generate_checkpoint()
+    stored = await saver.aput(config, cp, generate_metadata(), {})
+    await saver.aput_writes(stored, [("ch", "val")], str(uuid4()))
+
+    # Pre-delete: verify writes exist
+    pre_tup = await saver.aget_tuple(generate_config(tid))
+    assert pre_tup is not None, "Pre-delete: checkpoint should exist"
+    assert pre_tup.pending_writes is not None and len(pre_tup.pending_writes) == 1, (
+        f"Pre-delete: expected 1 write, got {len(pre_tup.pending_writes) if pre_tup.pending_writes else 0}"
+    )
+
+    await saver.adelete_thread(tid)
+
+    tup = await saver.aget_tuple(generate_config(tid))
+    assert tup is None
+
+
+async def test_delete_thread_removes_all_namespaces(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Root + child namespaces both removed."""
+    tid = str(uuid4())
+
+    for ns in ["", "child:1"]:
+        cfg = generate_config(tid, checkpoint_ns=ns)
+        cp = generate_checkpoint()
+        await saver.aput(cfg, cp, generate_metadata(), {})
+
+    # Pre-delete: verify each namespace has data
+    for ns in ["", "child:1"]:
+        pre = await saver.aget_tuple(generate_config(tid, checkpoint_ns=ns))
+        assert pre is not None, f"Pre-delete: namespace '{ns}' should have data"
+
+    await saver.adelete_thread(tid)
+
+    for ns in ["", "child:1"]:
+        tup = await saver.aget_tuple(generate_config(tid, checkpoint_ns=ns))
+        assert tup is None
+
+
+async def test_delete_thread_preserves_other_threads(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Other threads untouched."""
+    tid1, tid2 = str(uuid4()), str(uuid4())
+
+    for tid in (tid1, tid2):
+        cfg = generate_config(tid)
+        cp = generate_checkpoint()
+        await saver.aput(cfg, cp, generate_metadata(), {})
+
+    await saver.adelete_thread(tid1)
+
+    assert await saver.aget_tuple(generate_config(tid1)) is None
+    assert await saver.aget_tuple(generate_config(tid2)) is not None
+
+
+async def test_delete_thread_nonexistent_noop(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """No error for missing thread."""
+    # Should not raise
+    await saver.adelete_thread(str(uuid4()))
+
+
+ALL_DELETE_THREAD_TESTS = [
+    test_delete_thread_removes_checkpoints,
+    test_delete_thread_removes_writes,
+    test_delete_thread_removes_all_namespaces,
+    test_delete_thread_preserves_other_threads,
+    test_delete_thread_nonexistent_noop,
+]
+
+
+async def run_delete_thread_tests(
+    saver: BaseCheckpointSaver,
+    on_test_result: Callable[[str, str, bool, str | None], None] | None = None,
+) -> tuple[int, int, list[str]]:
+    """Run all delete_thread tests. Returns (passed, failed, failure_names)."""
+    passed = 0
+    failed = 0
+    failures: list[str] = []
+    for test_fn in ALL_DELETE_THREAD_TESTS:
+        try:
+            await test_fn(saver)
+            passed += 1
+            if on_test_result:
+                on_test_result("delete_thread", test_fn.__name__, True, None)
+        except Exception as e:
+            failed += 1
+            msg = f"{test_fn.__name__}: {e}"
+            failures.append(msg)
+            if on_test_result:
+                on_test_result(
+                    "delete_thread", test_fn.__name__, False, traceback.format_exc()
+                )
+    return passed, failed, failures

libs/checkpoint-conformance/langgraph/checkpoint/conformance/spec/test_get_tuple.py

@@ -0,0 +1,253 @@
+"""GET_TUPLE capability tests — aget_tuple retrieval."""
+
+from __future__ import annotations
+
+import traceback
+from collections.abc import Callable
+from uuid import uuid4
+
+from langgraph.checkpoint.base import BaseCheckpointSaver
+
+from langgraph.checkpoint.conformance.test_utils import (
+    generate_checkpoint,
+    generate_config,
+    generate_metadata,
+)
+
+
+async def test_get_tuple_nonexistent_returns_none(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Missing thread returns None."""
+    config = generate_config(str(uuid4()))
+    tup = await saver.aget_tuple(config)
+    assert tup is None
+
+
+async def test_get_tuple_latest_when_no_checkpoint_id(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Returns newest checkpoint when no checkpoint_id in config."""
+    tid = str(uuid4())
+    ids = []
+    parent_cfg = None
+    for i in range(3):
+        config = generate_config(tid)
+        if parent_cfg:
+            config["configurable"]["checkpoint_id"] = parent_cfg["configurable"][
+                "checkpoint_id"
+            ]
+        cp = generate_checkpoint()
+        parent_cfg = await saver.aput(config, cp, generate_metadata(step=i), {})
+        ids.append(cp["id"])
+
+    # Get without checkpoint_id — should return the latest
+    tup = await saver.aget_tuple(generate_config(tid))
+    assert tup is not None
+    assert tup.checkpoint["id"] == ids[-1]
+    assert tup.metadata["step"] == 2, (
+        f"Expected latest step=2, got {tup.metadata['step']}"
+    )
+
+
+async def test_get_tuple_specific_checkpoint_id(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Returns exact match when checkpoint_id specified."""
+    tid = str(uuid4())
+
+    config1 = generate_config(tid)
+    cp1 = generate_checkpoint()
+    stored1 = await saver.aput(config1, cp1, generate_metadata(step=0), {})
+
+    config2 = generate_config(tid)
+    config2["configurable"]["checkpoint_id"] = stored1["configurable"]["checkpoint_id"]
+    cp2 = generate_checkpoint()
+    await saver.aput(config2, cp2, generate_metadata(step=1), {})
+
+    # Fetch the first one specifically
+    tup = await saver.aget_tuple(stored1)
+    assert tup is not None
+    assert tup.checkpoint["id"] == cp1["id"]
+
+
+async def test_get_tuple_config_structure(saver: BaseCheckpointSaver) -> None:
+    """tuple.config has thread_id, checkpoint_ns, checkpoint_id."""
+    tid = str(uuid4())
+    config = generate_config(tid)
+    cp = generate_checkpoint()
+    stored = await saver.aput(config, cp, generate_metadata(), {})
+
+    tup = await saver.aget_tuple(stored)
+    assert tup is not None
+    conf = tup.config["configurable"]
+    assert conf["thread_id"] == tid
+    assert conf.get("checkpoint_ns", "") == "", (
+        f"Expected checkpoint_ns='', got {conf.get('checkpoint_ns')!r}"
+    )
+    assert conf["checkpoint_id"] == cp["id"]
+
+
+async def test_get_tuple_checkpoint_fields(saver: BaseCheckpointSaver) -> None:
+    """All Checkpoint fields present."""
+    tid = str(uuid4())
+    config = generate_config(tid)
+    cp = generate_checkpoint(channel_values={"k": "v"})
+    cp["channel_versions"] = {"k": 1}
+    stored = await saver.aput(config, cp, generate_metadata(), {"k": 1})
+
+    tup = await saver.aget_tuple(stored)
+    assert tup is not None
+    c = tup.checkpoint
+    assert c["id"] == cp["id"], f"id mismatch: {c['id']!r} != {cp['id']!r}"
+    assert c["v"] == 1, f"Expected v=1, got {c['v']!r}"
+    assert "ts" in c and c["ts"], "ts should be non-empty"
+    assert c["channel_values"] == {"k": "v"}, f"channel_values: {c['channel_values']!r}"
+    assert "channel_versions" in c
+    assert "versions_seen" in c
+
+
+async def test_get_tuple_metadata(saver: BaseCheckpointSaver) -> None:
+    """metadata populated correctly."""
+    tid = str(uuid4())
+    config = generate_config(tid)
+    cp = generate_checkpoint()
+    md = generate_metadata(source="input", step=-1)
+    stored = await saver.aput(config, cp, md, {})
+
+    tup = await saver.aget_tuple(stored)
+    assert tup is not None
+    assert tup.metadata["source"] == "input"
+    assert tup.metadata["step"] == -1
+
+
+async def test_get_tuple_parent_config(saver: BaseCheckpointSaver) -> None:
+    """parent_config when parent exists, None otherwise."""
+    tid = str(uuid4())
+
+    # First checkpoint — no parent
+    config1 = generate_config(tid)
+    cp1 = generate_checkpoint()
+    stored1 = await saver.aput(config1, cp1, generate_metadata(step=0), {})
+
+    tup1 = await saver.aget_tuple(stored1)
+    assert tup1 is not None
+    assert tup1.parent_config is None
+
+    # Second checkpoint — has parent
+    config2 = generate_config(tid)
+    config2["configurable"]["checkpoint_id"] = stored1["configurable"]["checkpoint_id"]
+    cp2 = generate_checkpoint()
+    stored2 = await saver.aput(config2, cp2, generate_metadata(step=1), {})
+
+    tup2 = await saver.aget_tuple(stored2)
+    assert tup2 is not None
+    assert tup2.parent_config is not None
+    assert (
+        tup2.parent_config["configurable"]["checkpoint_id"]
+        == stored1["configurable"]["checkpoint_id"]
+    )
+
+
+async def test_get_tuple_pending_writes(saver: BaseCheckpointSaver) -> None:
+    """pending_writes from put_writes visible."""
+    tid = str(uuid4())
+    config = generate_config(tid)
+    cp = generate_checkpoint()
+    stored = await saver.aput(config, cp, generate_metadata(), {})
+
+    task_id = str(uuid4())
+    await saver.aput_writes(stored, [("ch", "val")], task_id)
+
+    tup = await saver.aget_tuple(stored)
+    assert tup is not None
+    assert tup.pending_writes is not None
+    assert len(tup.pending_writes) == 1, (
+        f"Expected 1 write, got {len(tup.pending_writes)}"
+    )
+    assert tup.pending_writes[0][0] == task_id, (
+        f"task_id mismatch: {tup.pending_writes[0][0]!r}"
+    )
+    assert tup.pending_writes[0][1] == "ch", (
+        f"channel mismatch: {tup.pending_writes[0][1]!r}"
+    )
+    assert tup.pending_writes[0][2] == "val", (
+        f"value mismatch: {tup.pending_writes[0][2]!r}"
+    )
+
+
+async def test_get_tuple_respects_namespace(saver: BaseCheckpointSaver) -> None:
+    """checkpoint_ns filtering."""
+    tid = str(uuid4())
+
+    cfg_root = generate_config(tid, checkpoint_ns="")
+    cp_root = generate_checkpoint()
+    stored_root = await saver.aput(cfg_root, cp_root, generate_metadata(), {})
+
+    cfg_child = generate_config(tid, checkpoint_ns="child:1")
+    cp_child = generate_checkpoint()
+    stored_child = await saver.aput(cfg_child, cp_child, generate_metadata(), {})
+
+    tup_root = await saver.aget_tuple(stored_root)
+    assert tup_root is not None
+    assert tup_root.checkpoint["id"] == cp_root["id"]
+
+    tup_child = await saver.aget_tuple(stored_child)
+    assert tup_child is not None
+    assert tup_child.checkpoint["id"] == cp_child["id"]
+
+
+async def test_get_tuple_nonexistent_checkpoint_id(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Specific but missing checkpoint_id returns None."""
+    tid = str(uuid4())
+    nonexistent_id = str(uuid4())
+    # Put one checkpoint so the thread exists
+    config = generate_config(tid)
+    cp = generate_checkpoint()
+    await saver.aput(config, cp, generate_metadata(), {})
+
+    # Ask for a non-existent checkpoint_id
+    bad_cfg = generate_config(tid, checkpoint_id=nonexistent_id)
+    tup = await saver.aget_tuple(bad_cfg)
+    assert tup is None
+
+
+ALL_GET_TUPLE_TESTS = [
+    test_get_tuple_nonexistent_returns_none,
+    test_get_tuple_latest_when_no_checkpoint_id,
+    test_get_tuple_specific_checkpoint_id,
+    test_get_tuple_config_structure,
+    test_get_tuple_checkpoint_fields,
+    test_get_tuple_metadata,
+    test_get_tuple_parent_config,
+    test_get_tuple_pending_writes,
+    test_get_tuple_respects_namespace,
+    test_get_tuple_nonexistent_checkpoint_id,
+]
+
+
+async def run_get_tuple_tests(
+    saver: BaseCheckpointSaver,
+    on_test_result: Callable[[str, str, bool, str | None], None] | None = None,
+) -> tuple[int, int, list[str]]:
+    """Run all get_tuple tests. Returns (passed, failed, failure_names)."""
+    passed = 0
+    failed = 0
+    failures: list[str] = []
+    for test_fn in ALL_GET_TUPLE_TESTS:
+        try:
+            await test_fn(saver)
+            passed += 1
+            if on_test_result:
+                on_test_result("get_tuple", test_fn.__name__, True, None)
+        except Exception as e:
+            failed += 1
+            msg = f"{test_fn.__name__}: {e}"
+            failures.append(msg)
+            if on_test_result:
+                on_test_result(
+                    "get_tuple", test_fn.__name__, False, traceback.format_exc()
+                )
+    return passed, failed, failures

libs/checkpoint-conformance/langgraph/checkpoint/conformance/spec/test_list.py

@@ -0,0 +1,414 @@
+"""LIST capability tests — alist with various filters."""
+
+from __future__ import annotations
+
+import traceback
+from collections.abc import Callable
+from uuid import uuid4
+
+from langgraph.checkpoint.base import BaseCheckpointSaver
+
+from langgraph.checkpoint.conformance.test_utils import (
+    generate_checkpoint,
+    generate_config,
+    generate_metadata,
+)
+
+
+async def _setup_list_data(saver: BaseCheckpointSaver) -> dict:
+    """Populate saver with test data for list tests. Returns lookup info."""
+    tid = str(uuid4())
+    ids = []
+    parent_cfg = None
+    for i in range(4):
+        config = generate_config(tid)
+        if parent_cfg:
+            config["configurable"]["checkpoint_id"] = parent_cfg["configurable"][
+                "checkpoint_id"
+            ]
+        cp = generate_checkpoint()
+        source = "input" if i % 2 == 0 else "loop"
+        md = generate_metadata(source=source, step=i)
+        parent_cfg = await saver.aput(config, cp, md, {})
+        ids.append(cp["id"])
+
+    return {
+        "thread_id": tid,
+        "checkpoint_ids": ids,
+        "latest_config": parent_cfg,
+    }
+
+
+async def test_list_all(saver: BaseCheckpointSaver) -> None:
+    """No filters returns all checkpoints for the thread."""
+    data = await _setup_list_data(saver)
+    tid = data["thread_id"]
+
+    results = []
+    async for tup in saver.alist(generate_config(tid)):
+        results.append(tup)
+
+    assert len(results) == 4
+
+
+async def test_list_by_thread(saver: BaseCheckpointSaver) -> None:
+    """Filter by thread_id — other threads not returned."""
+    data = await _setup_list_data(saver)
+
+    # List for a non-existent thread
+    results = []
+    async for tup in saver.alist(generate_config(str(uuid4()))):
+        results.append(tup)
+    assert len(results) == 0
+
+    # List for actual thread
+    results = []
+    async for tup in saver.alist(generate_config(data["thread_id"])):
+        results.append(tup)
+    assert len(results) == 4
+
+
+async def test_list_by_namespace(saver: BaseCheckpointSaver) -> None:
+    """Filter by checkpoint_ns."""
+    tid = str(uuid4())
+
+    # Root namespace
+    cfg1 = generate_config(tid, checkpoint_ns="")
+    cp1 = generate_checkpoint()
+    await saver.aput(cfg1, cp1, generate_metadata(), {})
+
+    # Child namespace
+    cfg2 = generate_config(tid, checkpoint_ns="child:1")
+    cp2 = generate_checkpoint()
+    await saver.aput(cfg2, cp2, generate_metadata(), {})
+
+    root_results = []
+    async for tup in saver.alist(generate_config(tid, checkpoint_ns="")):
+        root_results.append(tup)
+    assert len(root_results) == 1
+
+    child_results = []
+    async for tup in saver.alist(generate_config(tid, checkpoint_ns="child:1")):
+        child_results.append(tup)
+    assert len(child_results) == 1
+
+
+async def test_list_ordering(saver: BaseCheckpointSaver) -> None:
+    """Newest first (descending checkpoint_id)."""
+    data = await _setup_list_data(saver)
+    ids = data["checkpoint_ids"]
+
+    results = []
+    async for tup in saver.alist(generate_config(data["thread_id"])):
+        results.append(tup.checkpoint["id"])
+
+    # Should be in reverse order (newest first)
+    assert results == list(reversed(ids))
+
+
+async def test_list_metadata_filter_single_key(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """filter={'source': 'input'} returns only input checkpoints."""
+    data = await _setup_list_data(saver)
+
+    results = []
+    async for tup in saver.alist(
+        generate_config(data["thread_id"]),
+        filter={"source": "input"},
+    ):
+        results.append(tup)
+
+    assert len(results) == 2, (
+        f"Expected 2 'input' checkpoints (steps 0,2), got {len(results)}"
+    )
+    for tup in results:
+        assert tup.metadata["source"] == "input"
+
+
+async def test_list_metadata_filter_step(saver: BaseCheckpointSaver) -> None:
+    """filter={'step': 1} returns matching checkpoints."""
+    data = await _setup_list_data(saver)
+
+    results = []
+    async for tup in saver.alist(
+        generate_config(data["thread_id"]),
+        filter={"step": 1},
+    ):
+        results.append(tup)
+
+    assert len(results) == 1
+    assert results[0].metadata["step"] == 1
+
+
+async def test_list_before(saver: BaseCheckpointSaver) -> None:
+    """Pagination cursor — only checkpoints before the given one."""
+    data = await _setup_list_data(saver)
+    ids = data["checkpoint_ids"]
+
+    # Use the 3rd checkpoint as the 'before' cursor (index 2)
+    before_cfg = generate_config(data["thread_id"], checkpoint_id=ids[2])
+    results = []
+    async for tup in saver.alist(
+        generate_config(data["thread_id"]),
+        before=before_cfg,
+    ):
+        results.append(tup)
+
+    # Should only include checkpoints before ids[2]
+    result_ids = [t.checkpoint["id"] for t in results]
+    assert ids[2] not in result_ids
+    assert ids[3] not in result_ids
+    assert set(result_ids) == {ids[0], ids[1]}, (
+        f"Expected {{ids[0], ids[1]}}, got {set(result_ids)}"
+    )
+
+
+async def test_list_limit(saver: BaseCheckpointSaver) -> None:
+    """limit=1, limit=N."""
+    data = await _setup_list_data(saver)
+
+    results = []
+    async for tup in saver.alist(generate_config(data["thread_id"]), limit=1):
+        results.append(tup)
+    assert len(results) == 1
+
+    results = []
+    async for tup in saver.alist(generate_config(data["thread_id"]), limit=2):
+        results.append(tup)
+    assert len(results) == 2
+
+
+async def test_list_limit_plus_before(saver: BaseCheckpointSaver) -> None:
+    """Pagination with limit."""
+    data = await _setup_list_data(saver)
+    ids = data["checkpoint_ids"]
+
+    before_cfg = generate_config(data["thread_id"], checkpoint_id=ids[3])
+    results = []
+    async for tup in saver.alist(
+        generate_config(data["thread_id"]),
+        before=before_cfg,
+        limit=1,
+    ):
+        results.append(tup)
+
+    assert len(results) == 1
+    assert results[0].checkpoint["id"] == ids[2]
+
+
+async def test_list_combined_thread_and_filter(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """thread_id + metadata filter combined."""
+    data = await _setup_list_data(saver)
+
+    results = []
+    async for tup in saver.alist(
+        generate_config(data["thread_id"]),
+        filter={"source": "loop"},
+    ):
+        results.append(tup)
+
+    assert len(results) == 2, (
+        f"Expected 2 'loop' checkpoints (steps 1,3), got {len(results)}"
+    )
+    for tup in results:
+        assert tup.metadata["source"] == "loop"
+
+
+async def test_list_empty_result(saver: BaseCheckpointSaver) -> None:
+    """No matches returns empty."""
+    results = []
+    async for tup in saver.alist(
+        generate_config(str(uuid4())),
+        filter={"source": "nonexistent"},
+    ):
+        results.append(tup)
+    assert len(results) == 0
+
+
+async def test_list_includes_pending_writes(saver: BaseCheckpointSaver) -> None:
+    """pending_writes in listed tuples."""
+    tid = str(uuid4())
+    config = generate_config(tid)
+    cp = generate_checkpoint()
+    stored = await saver.aput(config, cp, generate_metadata(), {})
+
+    await saver.aput_writes(stored, [("ch", "val")], str(uuid4()))
+
+    results = []
+    async for tup in saver.alist(generate_config(tid)):
+        results.append(tup)
+
+    assert len(results) == 1
+    assert results[0].pending_writes is not None
+    assert len(results[0].pending_writes) == 1, (
+        f"Expected 1 write, got {len(results[0].pending_writes)}"
+    )
+    assert results[0].pending_writes[0][1] == "ch", (
+        f"channel mismatch: {results[0].pending_writes[0][1]!r}"
+    )
+    assert results[0].pending_writes[0][2] == "val", (
+        f"value mismatch: {results[0].pending_writes[0][2]!r}"
+    )
+
+
+async def test_list_multiple_namespaces(saver: BaseCheckpointSaver) -> None:
+    """Root namespace checkpoint listed correctly."""
+    tid = str(uuid4())
+
+    for ns in ["", "child:1", "child:2"]:
+        cfg = generate_config(tid, checkpoint_ns=ns)
+        cp = generate_checkpoint()
+        await saver.aput(cfg, cp, generate_metadata(), {})
+
+    # List with root namespace filter — should return exactly the root checkpoint
+    results = []
+    async for tup in saver.alist(generate_config(tid, checkpoint_ns="")):
+        results.append(tup)
+    assert len(results) == 1, f"Expected 1 root checkpoint, got {len(results)}"
+
+
+async def test_list_metadata_filter_multiple_keys(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """filter with multiple keys — all must match."""
+    tid = str(uuid4())
+
+    # Create checkpoints with different metadata combos
+    for source, step in [("input", 1), ("loop", 1), ("input", 2)]:
+        cfg = generate_config(tid)
+        cp = generate_checkpoint()
+        await saver.aput(cfg, cp, generate_metadata(source=source, step=step), {})
+
+    results = []
+    async for tup in saver.alist(
+        generate_config(tid),
+        filter={"source": "input", "step": 2},
+    ):
+        results.append(tup)
+
+    assert len(results) == 1, (
+        f"Expected 1 match for source=input+step=2, got {len(results)}"
+    )
+    assert results[0].metadata["source"] == "input"
+    assert results[0].metadata["step"] == 2
+
+
+async def test_list_metadata_filter_no_match(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Multi-key filter that matches nothing returns empty."""
+    data = await _setup_list_data(saver)
+
+    results = []
+    async for tup in saver.alist(
+        generate_config(data["thread_id"]),
+        filter={"source": "update", "step": 99},
+    ):
+        results.append(tup)
+
+    assert len(results) == 0
+
+
+async def test_list_metadata_custom_keys(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Custom (non-standard) metadata keys are filterable."""
+    tid = str(uuid4())
+
+    cfg = generate_config(tid)
+    cp = generate_checkpoint()
+    await saver.aput(cfg, cp, generate_metadata(score=42, run_id="run-abc"), {})
+
+    cfg2 = generate_config(tid)
+    cp2 = generate_checkpoint()
+    await saver.aput(cfg2, cp2, generate_metadata(score=99, run_id="run-xyz"), {})
+
+    # Filter by custom key
+    results = []
+    async for tup in saver.alist(
+        generate_config(tid),
+        filter={"score": 42},
+    ):
+        results.append(tup)
+
+    assert len(results) == 1
+    assert results[0].metadata["score"] == 42
+    assert results[0].metadata["run_id"] == "run-abc"
+
+
+async def test_list_global_search(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """alist(None, filter=...) searches across all threads."""
+    tid1, tid2 = str(uuid4()), str(uuid4())
+
+    # Use a unique marker so we don't collide with other tests' data
+    marker = str(uuid4())
+
+    cfg1 = generate_config(tid1)
+    cp1 = generate_checkpoint()
+    await saver.aput(cfg1, cp1, generate_metadata(source="input", marker=marker), {})
+
+    cfg2 = generate_config(tid2)
+    cp2 = generate_checkpoint()
+    await saver.aput(cfg2, cp2, generate_metadata(source="loop", marker=marker), {})
+
+    # Search across all threads with filter
+    results = []
+    async for tup in saver.alist(None, filter={"source": "input", "marker": marker}):
+        results.append(tup)
+    assert len(results) == 1
+    assert results[0].config["configurable"]["thread_id"] == tid1
+
+    # Search with marker only — should find both
+    results = []
+    async for tup in saver.alist(None, filter={"marker": marker}):
+        results.append(tup)
+    assert len(results) == 2
+
+
+ALL_LIST_TESTS = [
+    test_list_all,
+    test_list_by_thread,
+    test_list_by_namespace,
+    test_list_ordering,
+    test_list_metadata_filter_single_key,
+    test_list_metadata_filter_step,
+    test_list_metadata_filter_multiple_keys,
+    test_list_metadata_filter_no_match,
+    test_list_metadata_custom_keys,
+    test_list_global_search,
+    test_list_before,
+    test_list_limit,
+    test_list_limit_plus_before,
+    test_list_combined_thread_and_filter,
+    test_list_empty_result,
+    test_list_includes_pending_writes,
+    test_list_multiple_namespaces,
+]
+
+
+async def run_list_tests(
+    saver: BaseCheckpointSaver,
+    on_test_result: Callable[[str, str, bool, str | None], None] | None = None,
+) -> tuple[int, int, list[str]]:
+    """Run all list tests. Returns (passed, failed, failure_names)."""
+    passed = 0
+    failed = 0
+    failures: list[str] = []
+    for test_fn in ALL_LIST_TESTS:
+        try:
+            await test_fn(saver)
+            passed += 1
+            if on_test_result:
+                on_test_result("list", test_fn.__name__, True, None)
+        except Exception as e:
+            failed += 1
+            msg = f"{test_fn.__name__}: {e}"
+            failures.append(msg)
+            if on_test_result:
+                on_test_result("list", test_fn.__name__, False, traceback.format_exc())
+    return passed, failed, failures

libs/checkpoint-conformance/langgraph/checkpoint/conformance/spec/test_prune.py

@@ -0,0 +1,217 @@
+"""PRUNE capability tests — aprune(strategy)."""
+
+from __future__ import annotations
+
+import traceback
+from collections.abc import Callable
+from uuid import uuid4
+
+from langgraph.checkpoint.base import BaseCheckpointSaver
+
+from langgraph.checkpoint.conformance.test_utils import (
+    generate_checkpoint,
+    generate_config,
+    generate_metadata,
+)
+
+
+async def _setup_thread(saver: BaseCheckpointSaver, tid: str, n: int = 3) -> list[dict]:
+    """Create n checkpoints on tid. Returns stored configs."""
+    stored = []
+    parent_cfg = None
+    for i in range(n):
+        config = generate_config(tid)
+        if parent_cfg:
+            config["configurable"]["checkpoint_id"] = parent_cfg["configurable"][
+                "checkpoint_id"
+            ]
+        cp = generate_checkpoint()
+        parent_cfg = await saver.aput(config, cp, generate_metadata(step=i), {})
+        stored.append(parent_cfg)
+    return stored
+
+
+async def test_prune_keep_latest_single_thread(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Only latest checkpoint survives."""
+    tid = str(uuid4())
+    configs = await _setup_thread(saver, tid, n=4)
+
+    await saver.aprune([tid], strategy="keep_latest")
+    results = []
+    async for tup in saver.alist(generate_config(tid)):
+        results.append(tup)
+
+    assert len(results) == 1
+    assert (
+        results[0].config["configurable"]["checkpoint_id"]
+        == configs[-1]["configurable"]["checkpoint_id"]
+    )
+
+
+async def test_prune_keep_latest_multiple_threads(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Each thread keeps its latest."""
+    tid1, tid2 = str(uuid4()), str(uuid4())
+    c1 = await _setup_thread(saver, tid1, n=3)
+    c2 = await _setup_thread(saver, tid2, n=2)
+
+    await saver.aprune([tid1, tid2], strategy="keep_latest")
+    for tid, expected_last in [(tid1, c1[-1]), (tid2, c2[-1])]:
+        results = []
+        async for tup in saver.alist(generate_config(tid)):
+            results.append(tup)
+        assert len(results) == 1
+        assert (
+            results[0].config["configurable"]["checkpoint_id"]
+            == expected_last["configurable"]["checkpoint_id"]
+        )
+
+
+async def test_prune_keep_latest_across_namespaces(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Latest per namespace kept."""
+    tid = str(uuid4())
+
+    # Root namespace: 3 checkpoints
+    parent = None
+    for i in range(3):
+        cfg = generate_config(tid, checkpoint_ns="")
+        if parent:
+            cfg["configurable"]["checkpoint_id"] = parent["configurable"][
+                "checkpoint_id"
+            ]
+        cp = generate_checkpoint()
+        parent = await saver.aput(cfg, cp, generate_metadata(step=i), {})
+    root_latest = parent
+
+    # Child namespace: 2 checkpoints
+    parent = None
+    for i in range(2):
+        cfg = generate_config(tid, checkpoint_ns="child:1")
+        if parent:
+            cfg["configurable"]["checkpoint_id"] = parent["configurable"][
+                "checkpoint_id"
+            ]
+        cp = generate_checkpoint()
+        parent = await saver.aput(cfg, cp, generate_metadata(step=i), {})
+    child_latest = parent
+
+    assert root_latest is not None
+    assert child_latest is not None
+    await saver.aprune([tid], strategy="keep_latest")
+    for ns, expected in [("", root_latest), ("child:1", child_latest)]:
+        results = []
+        async for tup in saver.alist(generate_config(tid, checkpoint_ns=ns)):
+            results.append(tup)
+        assert len(results) == 1
+        assert (
+            results[0].config["configurable"]["checkpoint_id"]
+            == expected["configurable"]["checkpoint_id"]
+        )
+
+
+async def test_prune_keep_latest_preserves_writes(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Latest checkpoint's writes kept."""
+    tid = str(uuid4())
+    configs = await _setup_thread(saver, tid, n=3)
+
+    # Add writes to the latest
+    await saver.aput_writes(configs[-1], [("ch", "val")], str(uuid4()))
+
+    await saver.aprune([tid], strategy="keep_latest")
+    tup = await saver.aget_tuple(generate_config(tid))
+    assert tup is not None
+    assert tup.pending_writes is not None
+    assert len(tup.pending_writes) == 1, (
+        f"Expected 1 write, got {len(tup.pending_writes)}"
+    )
+    assert tup.pending_writes[0][1] == "ch", (
+        f"channel mismatch: {tup.pending_writes[0][1]!r}"
+    )
+    assert tup.pending_writes[0][2] == "val", (
+        f"value mismatch: {tup.pending_writes[0][2]!r}"
+    )
+
+
+async def test_prune_delete_all(saver: BaseCheckpointSaver) -> None:
+    """delete_all strategy removes everything."""
+    tid = str(uuid4())
+    await _setup_thread(saver, tid, n=3)
+
+    await saver.aprune([tid], strategy="delete")
+    results = []
+    async for tup in saver.alist(generate_config(tid)):
+        results.append(tup)
+    assert len(results) == 0
+
+
+async def test_prune_preserves_other_threads(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Unlisted threads untouched."""
+    tid1, tid2 = str(uuid4()), str(uuid4())
+    await _setup_thread(saver, tid1, n=3)
+    await _setup_thread(saver, tid2, n=2)
+
+    # Snapshot tid2 before prune
+    pre_ids = []
+    async for tup in saver.alist(generate_config(tid2)):
+        pre_ids.append(tup.checkpoint["id"])
+
+    await saver.aprune([tid1], strategy="keep_latest")
+    # tid2 should be fully intact — same checkpoint IDs
+    post_ids = []
+    async for tup in saver.alist(generate_config(tid2)):
+        post_ids.append(tup.checkpoint["id"])
+    assert post_ids == pre_ids, f"tid2 changed: {pre_ids} -> {post_ids}"
+
+
+async def test_prune_empty_list_noop(saver: BaseCheckpointSaver) -> None:
+    """Empty thread_ids no error."""
+    await saver.aprune([], strategy="keep_latest")
+
+
+async def test_prune_nonexistent_noop(saver: BaseCheckpointSaver) -> None:
+    """Missing threads no error."""
+    await saver.aprune([str(uuid4())], strategy="keep_latest")
+
+
+ALL_PRUNE_TESTS = [
+    test_prune_keep_latest_single_thread,
+    test_prune_keep_latest_multiple_threads,
+    test_prune_keep_latest_across_namespaces,
+    test_prune_keep_latest_preserves_writes,
+    test_prune_delete_all,
+    test_prune_preserves_other_threads,
+    test_prune_empty_list_noop,
+    test_prune_nonexistent_noop,
+]
+
+
+async def run_prune_tests(
+    saver: BaseCheckpointSaver,
+    on_test_result: Callable[[str, str, bool, str | None], None] | None = None,
+) -> tuple[int, int, list[str]]:
+    """Run all prune tests. Returns (passed, failed, failure_names)."""
+    passed = 0
+    failed = 0
+    failures: list[str] = []
+    for test_fn in ALL_PRUNE_TESTS:
+        try:
+            await test_fn(saver)
+            passed += 1
+            if on_test_result:
+                on_test_result("prune", test_fn.__name__, True, None)
+        except Exception as e:
+            failed += 1
+            msg = f"{test_fn.__name__}: {e}"
+            failures.append(msg)
+            if on_test_result:
+                on_test_result("prune", test_fn.__name__, False, traceback.format_exc())
+    return passed, failed, failures

libs/checkpoint-conformance/langgraph/checkpoint/conformance/spec/test_put.py

@@ -0,0 +1,411 @@
+"""PUT capability tests — aput + aget_tuple round-trip."""
+
+from __future__ import annotations
+
+import traceback
+from collections.abc import Callable
+from typing import Any
+from uuid import uuid4
+
+from langgraph.checkpoint.base import (
+    BaseCheckpointSaver,
+    ChannelVersions,
+)
+
+from langgraph.checkpoint.conformance.test_utils import (
+    generate_checkpoint,
+    generate_config,
+    generate_metadata,
+)
+
+
+async def test_put_returns_config(saver: BaseCheckpointSaver) -> None:
+    """aput returns a RunnableConfig with thread_id, checkpoint_ns, checkpoint_id."""
+    config = generate_config()
+    cp = generate_checkpoint(channel_values={"k": "v"})
+    cp["channel_versions"] = {"k": 1}
+    md = generate_metadata()
+
+    result = await saver.aput(config, cp, md, {"k": 1})
+
+    assert "configurable" in result
+    conf = result["configurable"]
+    assert "thread_id" in conf
+    assert "checkpoint_ns" in conf
+    assert "checkpoint_id" in conf
+    assert conf["checkpoint_id"] == cp["id"]
+
+
+async def test_put_roundtrip(saver: BaseCheckpointSaver) -> None:
+    """put then get_tuple returns identical checkpoint."""
+    config = generate_config()
+    cp = generate_checkpoint(channel_values={"msg": "hello"})
+    cp["channel_versions"] = {"msg": 1}
+    md = generate_metadata(source="input", step=-1)
+
+    stored_config = await saver.aput(config, cp, md, {"msg": 1})
+
+    tup = await saver.aget_tuple(stored_config)
+    assert tup is not None
+    assert tup.checkpoint["id"] == cp["id"]
+    assert tup.checkpoint["channel_values"] == {"msg": "hello"}
+
+
+async def test_put_preserves_channel_values(saver: BaseCheckpointSaver) -> None:
+    """Various types (str, int, list, dict, bytes, None) round-trip correctly."""
+    values: dict[str, Any] = {
+        "str_val": "hello",
+        "int_val": 42,
+        "list_val": [1, 2, 3],
+        "dict_val": {"nested": True},
+    }
+    config = generate_config()
+    cp = generate_checkpoint(channel_values=values)
+    versions: ChannelVersions = {k: 1 for k in values}
+    cp["channel_versions"] = versions
+    md = generate_metadata()
+
+    stored = await saver.aput(config, cp, md, versions)
+    tup = await saver.aget_tuple(stored)
+    assert tup is not None
+    for k, v in values.items():
+        assert tup.checkpoint["channel_values"].get(k) == v, (
+            f"channel_values[{k}]: expected {v!r}, got {tup.checkpoint['channel_values'].get(k)!r}"
+        )
+
+
+async def test_put_preserves_channel_versions(saver: BaseCheckpointSaver) -> None:
+    """ChannelVersions round-trip correctly."""
+    versions: ChannelVersions = {"a": 1, "b": 2}
+    config = generate_config()
+    cp = generate_checkpoint(
+        channel_values={"a": "x", "b": "y"}, channel_versions=versions
+    )
+    md = generate_metadata()
+
+    stored = await saver.aput(config, cp, md, versions)
+    tup = await saver.aget_tuple(stored)
+    assert tup is not None
+    # Compare version values — checkpointers may convert int to str
+    for k, expected in versions.items():
+        actual = tup.checkpoint["channel_versions"].get(k)
+        assert actual is not None, f"channel_versions[{k}] missing"
+        assert str(actual).split(".")[0] == str(expected).split(".")[0], (
+            f"channel_versions[{k}]: expected {expected!r}, got {actual!r}"
+        )
+
+
+async def test_put_preserves_versions_seen(saver: BaseCheckpointSaver) -> None:
+    """versions_seen dict round-trips."""
+    vs: dict[str, ChannelVersions] = {"node1": {"ch": 1}, "node2": {"ch": 2}}
+    config = generate_config()
+    cp = generate_checkpoint(versions_seen=vs)
+    md = generate_metadata()
+
+    stored = await saver.aput(config, cp, md, {})
+    tup = await saver.aget_tuple(stored)
+    assert tup is not None
+    for node in vs:
+        assert node in tup.checkpoint["versions_seen"], f"versions_seen[{node}] missing"
+
+
+async def test_put_preserves_metadata(saver: BaseCheckpointSaver) -> None:
+    """Metadata source, step, parents, and custom keys round-trip."""
+    md = generate_metadata(source="loop", step=3, custom_key="custom_value")
+    config = generate_config()
+    cp = generate_checkpoint()
+
+    stored = await saver.aput(config, cp, md, {})
+    tup = await saver.aget_tuple(stored)
+    assert tup is not None
+    assert tup.metadata["source"] == "loop"
+    assert tup.metadata["step"] == 3
+    assert tup.metadata.get("custom_key") == "custom_value"
+
+
+async def test_put_root_namespace(saver: BaseCheckpointSaver) -> None:
+    """checkpoint_ns='' works."""
+    config = generate_config(checkpoint_ns="")
+    cp = generate_checkpoint()
+    md = generate_metadata()
+
+    stored = await saver.aput(config, cp, md, {})
+    tup = await saver.aget_tuple(stored)
+    assert tup is not None
+    assert tup.config["configurable"].get("checkpoint_ns", "") == ""
+
+
+async def test_put_child_namespace(saver: BaseCheckpointSaver) -> None:
+    """checkpoint_ns='child:abc' works."""
+    config = generate_config(checkpoint_ns="child:abc")
+    cp = generate_checkpoint()
+    md = generate_metadata()
+
+    stored = await saver.aput(config, cp, md, {})
+    tup = await saver.aget_tuple(stored)
+    assert tup is not None
+    assert tup.config["configurable"]["checkpoint_ns"] == "child:abc"
+
+
+async def test_put_default_namespace(saver: BaseCheckpointSaver) -> None:
+    """Config without checkpoint_ns defaults to ''."""
+    tid = str(uuid4())
+    config = {"configurable": {"thread_id": tid, "checkpoint_ns": ""}}
+    cp = generate_checkpoint()
+    md = generate_metadata()
+
+    stored = await saver.aput(config, cp, md, {})
+    tup = await saver.aget_tuple(stored)
+    assert tup is not None
+
+
+async def test_put_multiple_checkpoints_same_thread(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Sequential puts on same thread, all retrievable."""
+    tid = str(uuid4())
+    ids = []
+    parent_cfg = None
+    for i in range(3):
+        config = generate_config(tid)
+        if parent_cfg is not None:
+            config["configurable"]["checkpoint_id"] = parent_cfg["configurable"][
+                "checkpoint_id"
+            ]
+        cp = generate_checkpoint()
+        md = generate_metadata(step=i)
+        parent_cfg = await saver.aput(config, cp, md, {})
+        ids.append(cp["id"])
+
+    # All three should be retrievable
+    for cid in ids:
+        cfg = generate_config(tid, checkpoint_id=cid)
+        tup = await saver.aget_tuple(cfg)
+        assert tup is not None, f"checkpoint {cid} not found"
+        assert tup.checkpoint["id"] == cid
+
+
+async def test_put_multiple_threads_isolated(saver: BaseCheckpointSaver) -> None:
+    """Different thread_ids don't interfere."""
+    tid1, tid2 = str(uuid4()), str(uuid4())
+
+    config1 = generate_config(tid1)
+    cp1 = generate_checkpoint(channel_values={"x": "thread1"})
+    cp1["channel_versions"] = {"x": 1}
+    await saver.aput(config1, cp1, generate_metadata(), {"x": 1})
+
+    config2 = generate_config(tid2)
+    cp2 = generate_checkpoint(channel_values={"x": "thread2"})
+    cp2["channel_versions"] = {"x": 1}
+    await saver.aput(config2, cp2, generate_metadata(), {"x": 1})
+
+    tup1 = await saver.aget_tuple(generate_config(tid1))
+    tup2 = await saver.aget_tuple(generate_config(tid2))
+    assert tup1 is not None and tup2 is not None
+    assert tup1.checkpoint["channel_values"]["x"] == "thread1"
+    assert tup2.checkpoint["channel_values"]["x"] == "thread2"
+
+
+async def test_put_parent_config(saver: BaseCheckpointSaver) -> None:
+    """parent checkpoint_id tracked correctly."""
+    tid = str(uuid4())
+    config1 = generate_config(tid)
+    cp1 = generate_checkpoint()
+    stored1 = await saver.aput(config1, cp1, generate_metadata(step=0), {})
+
+    # Second checkpoint — its config carries the parent checkpoint_id
+    config2 = generate_config(tid)
+    config2["configurable"]["checkpoint_id"] = stored1["configurable"]["checkpoint_id"]
+    cp2 = generate_checkpoint()
+    stored2 = await saver.aput(config2, cp2, generate_metadata(step=1), {})
+
+    tup = await saver.aget_tuple(stored2)
+    assert tup is not None
+    assert tup.parent_config is not None
+    assert (
+        tup.parent_config["configurable"]["checkpoint_id"]
+        == stored1["configurable"]["checkpoint_id"]
+    )
+
+
+async def test_put_incremental_channel_update(saver: BaseCheckpointSaver) -> None:
+    """Only updated channels need new blobs; unchanged channels loaded from prior versions."""
+    tid = str(uuid4())
+
+    # Checkpoint 1: both channels are new
+    config1 = generate_config(tid)
+    cp1 = generate_checkpoint(
+        channel_values={"a": "v1", "b": "v2"},
+        channel_versions={"a": 1, "b": 1},
+    )
+    stored1 = await saver.aput(
+        config1, cp1, generate_metadata(step=0), {"a": 1, "b": 1}
+    )
+
+    # Checkpoint 2: only 'a' is updated
+    config2 = generate_config(tid)
+    config2["configurable"]["checkpoint_id"] = stored1["configurable"]["checkpoint_id"]
+    cp2 = generate_checkpoint(
+        channel_values={"a": "v1_updated", "b": "v2"},
+        channel_versions={"a": 2, "b": 1},
+    )
+    stored2 = await saver.aput(config2, cp2, generate_metadata(step=1), {"a": 2})
+
+    # cp2 should reconstruct full channel_values from blobs at mixed versions
+    tup2 = await saver.aget_tuple(stored2)
+    assert tup2 is not None
+    assert tup2.checkpoint["channel_values"].get("a") == "v1_updated", (
+        f"a: expected 'v1_updated', got {tup2.checkpoint['channel_values'].get('a')!r}"
+    )
+    assert tup2.checkpoint["channel_values"].get("b") == "v2", (
+        f"b: expected 'v2', got {tup2.checkpoint['channel_values'].get('b')!r}"
+    )
+
+    # cp1 should still return original values
+    tup1 = await saver.aget_tuple(stored1)
+    assert tup1 is not None
+    assert tup1.checkpoint["channel_values"].get("a") == "v1"
+    assert tup1.checkpoint["channel_values"].get("b") == "v2"
+
+
+async def test_put_new_channel_added(saver: BaseCheckpointSaver) -> None:
+    """A channel that appears for the first time in a later checkpoint."""
+    tid = str(uuid4())
+
+    config1 = generate_config(tid)
+    cp1 = generate_checkpoint(
+        channel_values={"a": "v1"},
+        channel_versions={"a": 1},
+    )
+    stored1 = await saver.aput(config1, cp1, generate_metadata(step=0), {"a": 1})
+
+    # Checkpoint 2: 'b' is brand new, 'a' is unchanged
+    config2 = generate_config(tid)
+    config2["configurable"]["checkpoint_id"] = stored1["configurable"]["checkpoint_id"]
+    cp2 = generate_checkpoint(
+        channel_values={"a": "v1", "b": "new_channel"},
+        channel_versions={"a": 1, "b": 1},
+    )
+    stored2 = await saver.aput(config2, cp2, generate_metadata(step=1), {"b": 1})
+
+    tup2 = await saver.aget_tuple(stored2)
+    assert tup2 is not None
+    assert tup2.checkpoint["channel_values"].get("a") == "v1", (
+        f"a: expected 'v1', got {tup2.checkpoint['channel_values'].get('a')!r}"
+    )
+    assert tup2.checkpoint["channel_values"].get("b") == "new_channel", (
+        f"b: expected 'new_channel', got {tup2.checkpoint['channel_values'].get('b')!r}"
+    )
+
+
+async def test_put_channel_removed(saver: BaseCheckpointSaver) -> None:
+    """Channel no longer in channel_versions should not appear in loaded values."""
+    tid = str(uuid4())
+
+    config1 = generate_config(tid)
+    cp1 = generate_checkpoint(
+        channel_values={"a": "v1", "b": "v2"},
+        channel_versions={"a": 1, "b": 1},
+    )
+    stored1 = await saver.aput(
+        config1, cp1, generate_metadata(step=0), {"a": 1, "b": 1}
+    )
+
+    # Checkpoint 2: 'b' dropped from channel_versions
+    config2 = generate_config(tid)
+    config2["configurable"]["checkpoint_id"] = stored1["configurable"]["checkpoint_id"]
+    cp2 = generate_checkpoint(
+        channel_values={"a": "v1_updated"},
+        channel_versions={"a": 2},
+    )
+    stored2 = await saver.aput(config2, cp2, generate_metadata(step=1), {"a": 2})
+
+    tup2 = await saver.aget_tuple(stored2)
+    assert tup2 is not None
+    assert tup2.checkpoint["channel_values"].get("a") == "v1_updated"
+    assert "b" not in tup2.checkpoint["channel_values"], (
+        f"'b' should not be present, got {tup2.checkpoint['channel_values']}"
+    )
+
+
+async def test_put_preserves_run_id(saver: BaseCheckpointSaver) -> None:
+    """run_id in metadata round-trips correctly."""
+    run_id = str(uuid4())
+    config = generate_config()
+    cp = generate_checkpoint()
+    md = generate_metadata(source="loop", step=0, run_id=run_id)
+
+    stored = await saver.aput(config, cp, md, {})
+    tup = await saver.aget_tuple(stored)
+    assert tup is not None
+    assert tup.metadata.get("run_id") == run_id, (
+        f"run_id: expected {run_id!r}, got {tup.metadata.get('run_id')!r}"
+    )
+
+
+async def test_put_preserves_versions_seen_values(saver: BaseCheckpointSaver) -> None:
+    """versions_seen values (not just keys) round-trip correctly."""
+    vs: dict[str, ChannelVersions] = {
+        "node1": {"ch_a": 1, "ch_b": 2},
+        "node2": {"ch_a": 3},
+    }
+    config = generate_config()
+    cp = generate_checkpoint(versions_seen=vs)
+    md = generate_metadata()
+
+    stored = await saver.aput(config, cp, md, {})
+    tup = await saver.aget_tuple(stored)
+    assert tup is not None
+    for node, expected_versions in vs.items():
+        assert node in tup.checkpoint["versions_seen"], f"versions_seen[{node}] missing"
+        actual_versions = tup.checkpoint["versions_seen"][node]
+        for ch, expected_v in expected_versions.items():
+            actual_v = actual_versions.get(ch)
+            assert actual_v is not None, f"versions_seen[{node}][{ch}] missing"
+            assert str(actual_v).split(".")[0] == str(expected_v).split(".")[0], (
+                f"versions_seen[{node}][{ch}]: expected {expected_v!r}, got {actual_v!r}"
+            )
+
+
+ALL_PUT_TESTS = [
+    test_put_returns_config,
+    test_put_roundtrip,
+    test_put_preserves_channel_values,
+    test_put_preserves_channel_versions,
+    test_put_preserves_versions_seen,
+    test_put_preserves_metadata,
+    test_put_root_namespace,
+    test_put_child_namespace,
+    test_put_default_namespace,
+    test_put_multiple_checkpoints_same_thread,
+    test_put_multiple_threads_isolated,
+    test_put_parent_config,
+    test_put_incremental_channel_update,
+    test_put_new_channel_added,
+    test_put_channel_removed,
+    test_put_preserves_run_id,
+    test_put_preserves_versions_seen_values,
+]
+
+
+async def run_put_tests(
+    saver: BaseCheckpointSaver,
+    on_test_result: Callable[[str, str, bool, str | None], None] | None = None,
+) -> tuple[int, int, list[str]]:
+    """Run all put tests. Returns (passed, failed, failure_names)."""
+    passed = 0
+    failed = 0
+    failures: list[str] = []
+    for test_fn in ALL_PUT_TESTS:
+        try:
+            await test_fn(saver)
+            passed += 1
+            if on_test_result:
+                on_test_result("put", test_fn.__name__, True, None)
+        except Exception as e:
+            failed += 1
+            msg = f"{test_fn.__name__}: {e}"
+            failures.append(msg)
+            if on_test_result:
+                on_test_result("put", test_fn.__name__, False, traceback.format_exc())
+    return passed, failed, failures

libs/checkpoint-conformance/langgraph/checkpoint/conformance/spec/test_put_writes.py

@@ -0,0 +1,302 @@
+"""PUT_WRITES capability tests — aput_writes + pending_writes retrieval."""
+
+from __future__ import annotations
+
+import traceback
+from collections.abc import Callable
+from uuid import uuid4
+
+from langgraph.checkpoint.base import BaseCheckpointSaver
+
+from langgraph.checkpoint.conformance.test_utils import (
+    generate_checkpoint,
+    generate_config,
+    generate_metadata,
+)
+
+
+async def test_put_writes_basic(saver: BaseCheckpointSaver) -> None:
+    """Write stored, visible in aget_tuple pending_writes."""
+    tid = str(uuid4())
+    config = generate_config(tid)
+    cp = generate_checkpoint()
+    stored = await saver.aput(config, cp, generate_metadata(), {})
+
+    task_id = str(uuid4())
+    await saver.aput_writes(stored, [("channel1", "value1")], task_id)
+
+    tup = await saver.aget_tuple(stored)
+    assert tup is not None
+    assert tup.pending_writes is not None
+    # Verify exact write tuple: (task_id, channel, value)
+    matching = [w for w in tup.pending_writes if w[0] == task_id and w[1] == "channel1"]
+    assert len(matching) == 1, f"Expected 1 write, got {len(matching)}"
+    assert matching[0][2] == "value1", f"Value mismatch: {matching[0][2]!r}"
+
+
+async def test_put_writes_multiple_writes_same_task(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Multiple (channel, value) pairs in a single call."""
+    tid = str(uuid4())
+    config = generate_config(tid)
+    cp = generate_checkpoint()
+    stored = await saver.aput(config, cp, generate_metadata(), {})
+
+    task_id = str(uuid4())
+    writes = [("ch1", "v1"), ("ch2", "v2"), ("ch3", "v3")]
+    await saver.aput_writes(stored, writes, task_id)
+
+    tup = await saver.aget_tuple(stored)
+    assert tup is not None
+    assert tup.pending_writes is not None
+    assert len(tup.pending_writes) == 3, (
+        f"Expected 3 writes, got {len(tup.pending_writes)}"
+    )
+    channels = {w[1] for w in tup.pending_writes}
+    assert channels == {"ch1", "ch2", "ch3"}, f"Expected exact channels, got {channels}"
+    # Verify values per channel
+    for expected_ch, expected_val in writes:
+        match = [
+            w for w in tup.pending_writes if w[0] == task_id and w[1] == expected_ch
+        ]
+        assert len(match) == 1, f"Expected 1 write for {expected_ch}, got {len(match)}"
+        assert match[0][2] == expected_val, (
+            f"Value mismatch for {expected_ch}: {match[0][2]!r}"
+        )
+
+
+async def test_put_writes_multiple_tasks(saver: BaseCheckpointSaver) -> None:
+    """Different task_ids produce separate writes."""
+    tid = str(uuid4())
+    config = generate_config(tid)
+    cp = generate_checkpoint()
+    stored = await saver.aput(config, cp, generate_metadata(), {})
+
+    t1, t2 = str(uuid4()), str(uuid4())
+    await saver.aput_writes(stored, [("ch", "from_t1")], t1)
+    await saver.aput_writes(stored, [("ch", "from_t2")], t2)
+
+    tup = await saver.aget_tuple(stored)
+    assert tup is not None
+    assert tup.pending_writes is not None
+    assert len(tup.pending_writes) == 2, (
+        f"Expected 2 writes, got {len(tup.pending_writes)}"
+    )
+    # Verify values per task
+    t1_writes = [w for w in tup.pending_writes if w[0] == t1 and w[1] == "ch"]
+    t2_writes = [w for w in tup.pending_writes if w[0] == t2 and w[1] == "ch"]
+    assert len(t1_writes) == 1, f"Expected 1 write from t1, got {len(t1_writes)}"
+    assert len(t2_writes) == 1, f"Expected 1 write from t2, got {len(t2_writes)}"
+    assert t1_writes[0][2] == "from_t1", f"t1 value: {t1_writes[0][2]!r}"
+    assert t2_writes[0][2] == "from_t2", f"t2 value: {t2_writes[0][2]!r}"
+
+
+async def test_put_writes_preserves_task_id(saver: BaseCheckpointSaver) -> None:
+    """task_id in pending_writes matches what was passed to aput_writes."""
+    tid = str(uuid4())
+    config = generate_config(tid)
+    cp = generate_checkpoint()
+    stored = await saver.aput(config, cp, generate_metadata(), {})
+
+    task_id = str(uuid4())
+    await saver.aput_writes(stored, [("ch", "val")], task_id)
+
+    tup = await saver.aget_tuple(stored)
+    assert tup is not None
+    assert tup.pending_writes is not None
+    assert any(w[0] == task_id for w in tup.pending_writes)
+
+
+async def test_put_writes_preserves_channel_and_value(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """Channel name + value round-trip."""
+    tid = str(uuid4())
+    config = generate_config(tid)
+    cp = generate_checkpoint()
+    stored = await saver.aput(config, cp, generate_metadata(), {})
+
+    task_id = str(uuid4())
+    await saver.aput_writes(stored, [("my_channel", {"data": 123})], task_id)
+
+    tup = await saver.aget_tuple(stored)
+    assert tup is not None
+    assert tup.pending_writes is not None
+    match = [w for w in tup.pending_writes if w[0] == task_id and w[1] == "my_channel"]
+    assert len(match) == 1, f"Expected 1 write, got {len(match)}"
+    assert match[0][2] == {"data": 123}, f"Value mismatch: {match[0][2]!r}"
+
+
+async def test_put_writes_task_path(saver: BaseCheckpointSaver) -> None:
+    """task_path parameter accepted without error."""
+    tid = str(uuid4())
+    config = generate_config(tid)
+    cp = generate_checkpoint()
+    stored = await saver.aput(config, cp, generate_metadata(), {})
+
+    task_id = str(uuid4())
+    # Should not raise
+    await saver.aput_writes(stored, [("ch", "v")], task_id, task_path="a:b:c")
+
+    tup = await saver.aget_tuple(stored)
+    assert tup is not None
+    assert tup.pending_writes is not None
+    assert len(tup.pending_writes) == 1
+
+
+async def test_put_writes_idempotent(saver: BaseCheckpointSaver) -> None:
+    """Duplicate (task_id, idx) doesn't duplicate writes."""
+    tid = str(uuid4())
+    config = generate_config(tid)
+    cp = generate_checkpoint()
+    stored = await saver.aput(config, cp, generate_metadata(), {})
+
+    task_id = str(uuid4())
+    await saver.aput_writes(stored, [("ch", "val")], task_id)
+    await saver.aput_writes(stored, [("ch", "val")], task_id)
+
+    tup = await saver.aget_tuple(stored)
+    assert tup is not None
+    assert tup.pending_writes is not None
+    assert len(tup.pending_writes) == 1, (
+        f"Expected exactly 1 write total, got {len(tup.pending_writes)}"
+    )
+    # Should not have duplicated
+    matching = [w for w in tup.pending_writes if w[0] == task_id and w[1] == "ch"]
+    assert len(matching) == 1
+
+
+async def test_put_writes_special_channels(saver: BaseCheckpointSaver) -> None:
+    """ERROR and INTERRUPT channels handled correctly."""
+    from langgraph.checkpoint.serde.types import ERROR, INTERRUPT
+
+    tid = str(uuid4())
+    config = generate_config(tid)
+    cp = generate_checkpoint()
+    stored = await saver.aput(config, cp, generate_metadata(), {})
+
+    task_id = str(uuid4())
+    await saver.aput_writes(
+        stored,
+        [(ERROR, "something went wrong"), (INTERRUPT, {"reason": "human_input"})],
+        task_id,
+    )
+
+    tup = await saver.aget_tuple(stored)
+    assert tup is not None
+    assert tup.pending_writes is not None
+    channels = {w[1] for w in tup.pending_writes}
+    assert ERROR in channels
+    assert INTERRUPT in channels
+    # Verify values
+    err_writes = [w for w in tup.pending_writes if w[0] == task_id and w[1] == ERROR]
+    assert len(err_writes) == 1, f"Expected 1 ERROR write, got {len(err_writes)}"
+    assert err_writes[0][2] == "something went wrong", (
+        f"ERROR value: {err_writes[0][2]!r}"
+    )
+    int_writes = [
+        w for w in tup.pending_writes if w[0] == task_id and w[1] == INTERRUPT
+    ]
+    assert len(int_writes) == 1, f"Expected 1 INTERRUPT write, got {len(int_writes)}"
+    assert int_writes[0][2] == {"reason": "human_input"}, (
+        f"INTERRUPT value: {int_writes[0][2]!r}"
+    )
+
+
+async def test_put_writes_across_namespaces(saver: BaseCheckpointSaver) -> None:
+    """Writes isolated by checkpoint_ns."""
+    tid = str(uuid4())
+
+    # Root namespace checkpoint + write
+    cfg_root = generate_config(tid, checkpoint_ns="")
+    cp_root = generate_checkpoint()
+    stored_root = await saver.aput(cfg_root, cp_root, generate_metadata(), {})
+    root_task = str(uuid4())
+    await saver.aput_writes(stored_root, [("ch", "root_val")], root_task)
+
+    # Child namespace checkpoint + write
+    cfg_child = generate_config(tid, checkpoint_ns="child:1")
+    cp_child = generate_checkpoint()
+    stored_child = await saver.aput(cfg_child, cp_child, generate_metadata(), {})
+    child_task = str(uuid4())
+    await saver.aput_writes(stored_child, [("ch", "child_val")], child_task)
+
+    # Verify isolation — root should have exactly 1 write with root_val
+    tup_root = await saver.aget_tuple(stored_root)
+    assert tup_root is not None
+    assert tup_root.pending_writes is not None
+    root_ch = [w for w in tup_root.pending_writes if w[1] == "ch"]
+    assert len(root_ch) == 1, f"Expected 1 root write, got {len(root_ch)}"
+    assert root_ch[0][2] == "root_val", f"Root value: {root_ch[0][2]!r}"
+
+    # Child should have exactly 1 write with child_val
+    tup_child = await saver.aget_tuple(stored_child)
+    assert tup_child is not None
+    assert tup_child.pending_writes is not None
+    child_ch = [w for w in tup_child.pending_writes if w[1] == "ch"]
+    assert len(child_ch) == 1, f"Expected 1 child write, got {len(child_ch)}"
+    assert child_ch[0][2] == "child_val", f"Child value: {child_ch[0][2]!r}"
+
+
+async def test_put_writes_cleared_on_next_checkpoint(
+    saver: BaseCheckpointSaver,
+) -> None:
+    """New checkpoint starts with fresh pending_writes."""
+    tid = str(uuid4())
+    config = generate_config(tid)
+    cp1 = generate_checkpoint()
+    stored1 = await saver.aput(config, cp1, generate_metadata(step=0), {})
+
+    await saver.aput_writes(stored1, [("ch", "old_write")], str(uuid4()))
+
+    # New checkpoint
+    config2 = generate_config(tid)
+    config2["configurable"]["checkpoint_id"] = stored1["configurable"]["checkpoint_id"]
+    cp2 = generate_checkpoint()
+    stored2 = await saver.aput(config2, cp2, generate_metadata(step=1), {})
+
+    tup = await saver.aget_tuple(stored2)
+    assert tup is not None
+    # New checkpoint should have no pending writes
+    writes = tup.pending_writes or []
+    assert len(writes) == 0
+
+
+ALL_PUT_WRITES_TESTS = [
+    test_put_writes_basic,
+    test_put_writes_multiple_writes_same_task,
+    test_put_writes_multiple_tasks,
+    test_put_writes_preserves_task_id,
+    test_put_writes_preserves_channel_and_value,
+    test_put_writes_task_path,
+    test_put_writes_idempotent,
+    test_put_writes_special_channels,
+    test_put_writes_across_namespaces,
+    test_put_writes_cleared_on_next_checkpoint,
+]
+
+
+async def run_put_writes_tests(
+    saver: BaseCheckpointSaver,
+    on_test_result: Callable[[str, str, bool, str | None], None] | None = None,
+) -> tuple[int, int, list[str]]:
+    """Run all put_writes tests. Returns (passed, failed, failure_names)."""
+    passed = 0
+    failed = 0
+    failures: list[str] = []
+    for test_fn in ALL_PUT_WRITES_TESTS:
+        try:
+            await test_fn(saver)
+            passed += 1
+            if on_test_result:
+                on_test_result("put_writes", test_fn.__name__, True, None)
+        except Exception as e:
+            failed += 1
+            msg = f"{test_fn.__name__}: {e}"
+            failures.append(msg)
+            if on_test_result:
+                on_test_result(
+                    "put_writes", test_fn.__name__, False, traceback.format_exc()
+                )
+    return passed, failed, failures

libs/checkpoint-conformance/langgraph/checkpoint/conformance/test_utils.py

@@ -0,0 +1,212 @@
+"""Test utilities: checkpoint generators, assertion helpers, bulk operations."""
+
+from __future__ import annotations
+
+from datetime import datetime, timezone
+from typing import Any
+from uuid import uuid4
+
+from langchain_core.runnables import RunnableConfig
+from langgraph.checkpoint.base import (
+    ChannelVersions,
+    Checkpoint,
+    CheckpointMetadata,
+    CheckpointTuple,
+)
+from langgraph.checkpoint.base.id import uuid6
+
+
+def generate_checkpoint(
+    *,
+    checkpoint_id: str | None = None,
+    channel_values: dict[str, Any] | None = None,
+    channel_versions: ChannelVersions | None = None,
+    versions_seen: dict[str, ChannelVersions] | None = None,
+) -> Checkpoint:
+    """Create a well-formed Checkpoint with sensible defaults."""
+    return Checkpoint(
+        v=1,
+        id=checkpoint_id or str(uuid6(clock_seq=-1)),
+        ts=datetime.now(timezone.utc).isoformat(),
+        channel_values=channel_values if channel_values is not None else {},
+        channel_versions=channel_versions if channel_versions is not None else {},
+        versions_seen=versions_seen if versions_seen is not None else {},
+        pending_sends=[],  # ty: ignore[invalid-key]
+        updated_channels=None,
+    )
+
+
+def generate_config(
+    thread_id: str | None = None,
+    *,
+    checkpoint_ns: str = "",
+    checkpoint_id: str | None = None,
+) -> RunnableConfig:
+    """Create a RunnableConfig targeting a specific thread / namespace / checkpoint."""
+    configurable: dict[str, Any] = {
+        "thread_id": thread_id or str(uuid4()),
+        "checkpoint_ns": checkpoint_ns,
+    }
+    if checkpoint_id is not None:
+        configurable["checkpoint_id"] = checkpoint_id
+    return {"configurable": configurable}
+
+
+def generate_metadata(
+    source: str = "loop",
+    step: int = 0,
+    **extra: Any,
+) -> CheckpointMetadata:
+    """Create CheckpointMetadata with defaults."""
+    md: dict[str, Any] = {"source": source, "step": step, "parents": {}}
+    md.update(extra)
+    return md
+
+
+async def put_test_checkpoint(
+    saver: Any,
+    *,
+    thread_id: str | None = None,
+    checkpoint_ns: str = "",
+    parent_config: RunnableConfig | None = None,
+    channel_values: dict[str, Any] | None = None,
+    channel_versions: ChannelVersions | None = None,
+    metadata: CheckpointMetadata | None = None,
+    new_versions: ChannelVersions | None = None,
+) -> RunnableConfig:
+    """Put a single test checkpoint and return the stored config.
+
+    Handles wiring up parent_config, channel_values -> new_versions, etc.
+    """
+    tid = thread_id or str(uuid4())
+    cp = generate_checkpoint(
+        channel_values=channel_values,
+        channel_versions=channel_versions,
+    )
+
+    # When channel_values are provided, ensure channel_versions + new_versions
+    # are consistent so the checkpointer stores the blobs correctly.
+    vals = channel_values or {}
+    cv = channel_versions
+    if cv is None and vals:
+        cv = {k: 1 for k in vals}
+        cp["channel_versions"] = cv
+    nv = new_versions
+    if nv is None:
+        nv = cv or {}
+
+    md = metadata or generate_metadata()
+
+    config = generate_config(tid, checkpoint_ns=checkpoint_ns)
+    if parent_config is not None:
+        config["configurable"]["checkpoint_id"] = parent_config["configurable"][
+            "checkpoint_id"
+        ]
+
+    return await saver.aput(config, cp, md, nv)
+
+
+async def put_test_checkpoints(
+    saver: Any,
+    *,
+    n_threads: int = 1,
+    n_checkpoints: int = 1,
+    namespaces: list[str] | None = None,
+    channel_values: dict[str, Any] | None = None,
+) -> list[RunnableConfig]:
+    """Convenience: put multiple checkpoints across threads/namespaces.
+
+    Returns the stored configs in insertion order.
+    """
+    nss = namespaces or [""]
+    stored: list[RunnableConfig] = []
+    for t in range(n_threads):
+        tid = f"thread-{t}"
+        for ns in nss:
+            parent: RunnableConfig | None = None
+            for _c in range(n_checkpoints):
+                cfg = await put_test_checkpoint(
+                    saver,
+                    thread_id=tid,
+                    checkpoint_ns=ns,
+                    parent_config=parent,
+                    channel_values=channel_values,
+                )
+                parent = cfg
+                stored.append(cfg)
+    return stored
+
+
+def assert_checkpoint_equal(
+    actual: Checkpoint,
+    expected: Checkpoint,
+    *,
+    check_channel_values: bool = True,
+) -> None:
+    """Assert two checkpoints are semantically equal."""
+    assert actual["v"] == expected["v"], f"v mismatch: {actual['v']} != {expected['v']}"
+    assert actual["id"] == expected["id"], (
+        f"id mismatch: {actual['id']} != {expected['id']}"
+    )
+    assert actual["channel_versions"] == expected["channel_versions"], (
+        "channel_versions mismatch"
+    )
+    assert actual["versions_seen"] == expected["versions_seen"], (
+        "versions_seen mismatch"
+    )
+    if check_channel_values:
+        assert actual["channel_values"] == expected["channel_values"], (
+            "channel_values mismatch"
+        )
+
+
+def assert_tuple_equal(
+    actual: CheckpointTuple,
+    expected: CheckpointTuple,
+    *,
+    check_writes: bool = True,
+    check_channel_values: bool = True,
+) -> None:
+    """Assert two CheckpointTuples are semantically equal."""
+    # Config
+    a_conf = actual.config["configurable"]
+    e_conf = expected.config["configurable"]
+    assert a_conf["thread_id"] == e_conf["thread_id"], (
+        f"thread_id mismatch: {a_conf['thread_id']} != {e_conf['thread_id']}"
+    )
+    assert a_conf.get("checkpoint_ns", "") == e_conf.get("checkpoint_ns", ""), (
+        "checkpoint_ns mismatch"
+    )
+    assert a_conf["checkpoint_id"] == e_conf["checkpoint_id"], "checkpoint_id mismatch"
+
+    # Checkpoint
+    assert_checkpoint_equal(
+        actual.checkpoint,
+        expected.checkpoint,
+        check_channel_values=check_channel_values,
+    )
+
+    # Metadata
+    for k, v in expected.metadata.items():
+        assert actual.metadata.get(k) == v, (
+            f"metadata[{k}] mismatch: {actual.metadata.get(k)} != {v}"
+        )
+
+    # Parent config
+    if expected.parent_config is not None:
+        assert actual.parent_config is not None, "expected parent_config, got None"
+        assert (
+            actual.parent_config["configurable"]["checkpoint_id"]
+            == expected.parent_config["configurable"]["checkpoint_id"]
+        ), "parent checkpoint_id mismatch"
+    else:
+        assert actual.parent_config is None, (
+            f"expected no parent_config, got {actual.parent_config}"
+        )
+
+    # Pending writes
+    if check_writes and expected.pending_writes is not None:
+        assert actual.pending_writes is not None
+        assert len(actual.pending_writes) == len(expected.pending_writes), (
+            f"pending_writes length mismatch: {len(actual.pending_writes)} != {len(expected.pending_writes)}"
+        )

libs/checkpoint-conformance/langgraph/checkpoint/conformance/validate.py

@@ -0,0 +1,124 @@
+"""Core conformance runner — detects capabilities, runs test suites, builds report."""
+
+from __future__ import annotations
+
+from langgraph.checkpoint.conformance.capabilities import (
+    Capability,
+    DetectedCapabilities,
+)
+from langgraph.checkpoint.conformance.initializer import RegisteredCheckpointer
+from langgraph.checkpoint.conformance.report import (
+    CapabilityReport,
+    CapabilityResult,
+    ProgressCallbacks,
+)
+from langgraph.checkpoint.conformance.spec.test_copy_thread import run_copy_thread_tests
+from langgraph.checkpoint.conformance.spec.test_delete_for_runs import (
+    run_delete_for_runs_tests,
+)
+from langgraph.checkpoint.conformance.spec.test_delete_thread import (
+    run_delete_thread_tests,
+)
+from langgraph.checkpoint.conformance.spec.test_get_tuple import run_get_tuple_tests
+from langgraph.checkpoint.conformance.spec.test_list import run_list_tests
+from langgraph.checkpoint.conformance.spec.test_prune import run_prune_tests
+from langgraph.checkpoint.conformance.spec.test_put import run_put_tests
+from langgraph.checkpoint.conformance.spec.test_put_writes import run_put_writes_tests
+
+# Maps capability to its runner function.
+_RUNNERS = {
+    Capability.PUT: run_put_tests,
+    Capability.PUT_WRITES: run_put_writes_tests,
+    Capability.GET_TUPLE: run_get_tuple_tests,
+    Capability.LIST: run_list_tests,
+    Capability.DELETE_THREAD: run_delete_thread_tests,
+    Capability.DELETE_FOR_RUNS: run_delete_for_runs_tests,
+    Capability.COPY_THREAD: run_copy_thread_tests,
+    Capability.PRUNE: run_prune_tests,
+}
+
+
+async def validate(
+    registered: RegisteredCheckpointer,
+    *,
+    capabilities: set[str] | None = None,
+    progress: ProgressCallbacks | None = None,
+) -> CapabilityReport:
+    """Run the validation suite against a registered checkpointer.
+
+    Args:
+        registered: A RegisteredCheckpointer (from @checkpointer_test decorator).
+        capabilities: If given, only run tests for these capability names.
+            Otherwise, auto-detect and run all applicable tests.
+        progress: Optional progress callbacks for incremental output.
+            Use ``ProgressCallbacks.default()`` for dot-style,
+            ``ProgressCallbacks.verbose()`` for per-test output, or
+            ``None`` / ``ProgressCallbacks.quiet()`` for silent mode.
+
+    Returns:
+        A CapabilityReport with per-capability results.
+    """
+    report = CapabilityReport(checkpointer_name=registered.name)
+
+    # Determine which capabilities to test.
+    caps_to_test: set[Capability]
+    if capabilities is not None:
+        caps_to_test = {Capability(c) for c in capabilities}
+    else:
+        caps_to_test = set(Capability)
+
+    async with registered.enter_lifespan():
+        for cap in Capability:
+            if cap in caps_to_test and cap.value not in registered.skip_capabilities:
+                # Create a fresh checkpointer for each capability suite.
+                async with registered.create() as saver:
+                    detected = DetectedCapabilities.from_instance(saver)
+                    is_detected = cap in detected.detected
+
+                    if not is_detected:
+                        if progress and progress.on_capability_start:
+                            progress.on_capability_start(cap.value, False)
+                        report.results[cap.value] = CapabilityResult(
+                            detected=False,
+                            passed=None,
+                            tests_skipped=1,
+                        )
+                        continue
+
+                    runner = _RUNNERS.get(cap)
+                    if runner is None:
+                        report.results[cap.value] = CapabilityResult(
+                            detected=True,
+                            passed=None,
+                            tests_skipped=1,
+                        )
+                        continue
+
+                    if progress and progress.on_capability_start:
+                        progress.on_capability_start(cap.value, True)
+
+                    passed, failed, failures = await runner(
+                        saver,
+                        on_test_result=progress.on_test_result if progress else None,
+                    )
+
+                    if progress and progress.on_capability_end:
+                        progress.on_capability_end(cap.value)
+
+                    report.results[cap.value] = CapabilityResult(
+                        detected=True,
+                        passed=failed == 0,
+                        tests_passed=passed,
+                        tests_failed=failed,
+                        failures=failures,
+                    )
+            else:
+                if progress and progress.on_capability_start:
+                    progress.on_capability_start(cap.value, False)
+                report.results[cap.value] = CapabilityResult(
+                    detected=False,
+                    passed=None,
+                    tests_skipped=1,
+                )
+
+    return report

libs/checkpoint-conformance/pyproject.toml

@@ -0,0 +1,65 @@
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[project]
+name = "langgraph-checkpoint-conformance"
+version = "0.0.1"
+description = "Conformance test suite for LangGraph checkpointer implementations."
+authors = [{name = "William FH", email = "13333726+hinthornw@users.noreply.github.com"}]
+requires-python = ">=3.10"
+readme = "README.md"
+license = "MIT"
+dependencies = [
+    "langgraph-checkpoint>=2.0.0",
+]
+
+[project.urls]
+Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/checkpoint-conformance"
+
+[dependency-groups]
+test = [
+  "pytest",
+  "pytest-asyncio",
+]
+lint = [
+  "ruff",
+  "ty",
+]
+dev = [
+  {include-group = "test"},
+  {include-group = "lint"},
+]
+
+[tool.hatch.build.targets.wheel]
+include = ["langgraph"]
+
+[tool.pytest.ini_options]
+addopts = "--strict-markers --strict-config --durations=5 -vv"
+testpaths = ["tests"]
+asyncio_mode = "auto"
+
+[tool.ty.rules]
+# The extended methods (acopy_thread, adelete_for_runs, aprune) are checked
+# at runtime via capability detection and may not exist on the installed
+# base class. Dict literal inference is also overly strict for RunnableConfig.
+unresolved-attribute = "ignore"
+invalid-argument-type = "ignore"
+invalid-return-type = "ignore"
+
+[tool.ruff]
+lint.select = [
+  "E",  # pycodestyle
+  "F",  # Pyflakes
+  "UP", # pyupgrade
+  "B",  # flake8-bugbear
+  "I",  # isort
+]
+lint.ignore = ["E501", "B008"]
+target-version = "py310"
+
+[[tool.uv.index]]
+name = "testpypi"
+url = "https://test.pypi.org/simple/"
+publish-url = "https://test.pypi.org/legacy/"
+explicit = true

libs/checkpoint-conformance/tests/test_validate_memory.py

@@ -0,0 +1,21 @@
+"""Self-tests: run the conformance suite against InMemorySaver."""
+
+from __future__ import annotations
+
+import pytest
+from langgraph.checkpoint.memory import InMemorySaver
+
+from langgraph.checkpoint.conformance import checkpointer_test, validate
+
+
+@checkpointer_test(name="InMemorySaver")
+async def memory_checkpointer():
+    yield InMemorySaver()
+
+
+@pytest.mark.asyncio
+async def test_validate_memory_base():
+    """InMemorySaver passes all base capability tests."""
+    report = await validate(memory_checkpointer)
+    report.print_report()
+    assert report.passed_all_base(), f"Base tests failed: {report.to_dict()}"

libs/checkpoint-postgres/langgraph/store/postgres/aio.py

@@ -550,6 +550,11 @@ class AsyncPostgresStore(AsyncBatchedBaseStore, BasePostgresStore[_ainternal.Con
                 Will be applied regardless of whether the PostgresStore instance was initialized with a pipeline.
                 If pipeline mode is not supported, will fall back to using transaction context manager.
         """
+        is_pooled_conn = isinstance(self.conn, AsyncConnectionPool)
+        # With AsyncConnectionPool, each _cursor() call checks out its own connection.
+        # The pool does not hand out the same connection concurrently, so a shared lock
+        # across calls is unnecessary here.
+        lock = asyncio.Lock() if is_pooled_conn else self.lock
         async with _ainternal.get_connection(self.conn) as conn:
             if self.pipe:
                 # a connection in pipeline mode can be used concurrently
@@ -566,21 +571,21 @@ class AsyncPostgresStore(AsyncBatchedBaseStore, BasePostgresStore[_ainternal.Con
                 # thread/coroutine at a time, so we acquire a lock
                 if self.supports_pipeline:
                     async with (
-                        self.lock,
+                        lock,
                         conn.pipeline(),
                         conn.cursor(binary=True, row_factory=dict_row) as cur,
                     ):
                         yield cur
                 else:
                     async with (
-                        self.lock,
+                        lock,
                         conn.transaction(),
                         conn.cursor(binary=True, row_factory=dict_row) as cur,
                     ):
                         yield cur
             else:
                 async with (
-                    self.lock,
+                    lock,
                     conn.cursor(binary=True, row_factory=dict_row) as cur,
                 ):
                     yield cur

libs/checkpoint-postgres/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-checkpoint-postgres"
-version = "3.0.3"
+version = "3.0.4"
 description = "Library with a Postgres implementation of LangGraph checkpoint saver."
 authors = []
 requires-python = ">=3.10"
@@ -13,14 +13,14 @@ license = "MIT"
 license-files = ['LICENSE']
 dependencies = [
   "langgraph-checkpoint>=2.1.2,<5.0.0",
-  "orjson>=3.10.1",
+  "orjson>=3.11.5",
   "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"
+Twitter = "https://x.com/LangChain"
 Slack = "https://www.langchain.com/join-community"
 Reddit = "https://www.reddit.com/r/LangChain/"
 

libs/checkpoint-postgres/uv.lock

@@ -13,16 +13,16 @@ wheels = [
 
 [[package]]
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+version = "4.12.1"
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@@ -36,11 +36,11 @@ wheels = [
 
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+    { url = "https://files.pythonhosted.org/packages/e6/ad/3cc14f097111b4de0040c83a525973216457bbeeb63739ef1ed275c1c021/certifi-2026.1.4-py3-none-any.whl", hash = "sha256:9943707519e4add1115f44c2bc244f782c0249876bf51b6599fee1ffbedd685c", size = 152900, upload-time = "2026-01-04T02:42:40.15Z" },
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@@ -240,7 +240,7 @@ wheels = [
 
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-version = "1.1.3"
+version = "1.2.11"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
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@@ -252,9 +252,9 @@ dependencies = [
     { name = "typing-extensions" },
     { name = "uuid-utils" },
 ]
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+    { url = "https://files.pythonhosted.org/packages/10/30/1f80e3fc674353cad975ed5294353d42512535d2094ef032c06454c2c873/langchain_core-1.2.11-py3-none-any.whl", hash = "sha256:ae11ceb8dda60d0b9d09e763116e592f1683327c17be5b715f350fd29aee65d3", size = 500062, upload-time = "2026-02-10T20:35:26.698Z" },
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 [[package]]
@@ -306,7 +306,7 @@ test = [
 
 [[package]]
 name = "langgraph-checkpoint-postgres"
-version = "3.0.3"
+version = "3.0.4"
 source = { editable = "." }
 dependencies = [
     { name = "langgraph-checkpoint" },
@@ -346,7 +346,7 @@ test = [
 [package.metadata]
 requires-dist = [
     { name = "langgraph-checkpoint", editable = "../checkpoint" },
-    { name = "orjson", specifier = ">=3.10.1" },
+    { name = "orjson", specifier = ">=3.11.5" },
     { name = "psycopg", specifier = ">=3.2.0" },
     { name = "psycopg-pool", specifier = ">=3.2.0" },
 ]
@@ -381,7 +381,7 @@ test = [
 
 [[package]]
 name = "langsmith"
-version = "0.4.57"
+version = "0.6.4"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
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 ]
 
 [[package]]

libs/checkpoint-sqlite/langgraph/checkpoint/sqlite/aio.py

@@ -3,6 +3,7 @@ from __future__ import annotations
 import asyncio
 import json
 import random
+import threading
 from collections.abc import AsyncIterator, Callable, Iterator, Sequence
 from contextlib import asynccontextmanager
 from typing import Any, TypeVar, cast
@@ -281,8 +282,7 @@ class AsyncSqliteSaver(BaseCheckpointSaver[str]):
         async with self.lock:
             if self.is_setup:
                 return
-            if not self.conn.is_alive():
-                await self.conn
+            await _ensure_connected(self.conn)
             async with self.conn.executescript(
                 """
                 PRAGMA journal_mode=WAL;
@@ -609,3 +609,23 @@ class AsyncSqliteSaver(BaseCheckpointSaver[str]):
         next_v = current_v + 1
         next_h = random.random()
         return f"{next_v:032}.{next_h:016}"
+
+
+async def _ensure_connected(conn: aiosqlite.Connection) -> None:
+    if not _CONN_STARTED_CHECK(conn):
+        await conn
+
+
+def _build_conn_started_check() -> Callable[[aiosqlite.Connection], bool]:
+    is_alive = getattr(aiosqlite.Connection, "is_alive", None)
+    if callable(is_alive):
+        return lambda conn: conn.is_alive()  # type: ignore[attr-defined]
+
+    def _started(conn: aiosqlite.Connection) -> bool:
+        thread: threading.Thread | None = getattr(conn, "_thread", None)
+        return False if thread is None else thread.is_alive()
+
+    return _started
+
+
+_CONN_STARTED_CHECK = _build_conn_started_check()

libs/checkpoint-sqlite/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-checkpoint-sqlite"
-version = "3.0.2"
+version = "3.0.3"
 description = "Library with a SQLite implementation of LangGraph checkpoint saver."
 authors = []
 requires-python = ">=3.10"
@@ -19,7 +19,7 @@ dependencies = [
 
 [project.urls]
 Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/checkpoint-sqlite"
-Twitter = "https://x.com/LangChainAI"
+Twitter = "https://x.com/LangChain"
 Slack = "https://www.langchain.com/join-community"
 Reddit = "https://www.reddit.com/r/LangChain/"
 

libs/checkpoint/langgraph/checkpoint/base/__init__.py

@@ -51,6 +51,8 @@ class CheckpointMetadata(TypedDict, total=False):
 
     Mapping from checkpoint namespace to checkpoint ID.
     """
+    run_id: str
+    """The ID of the run that created this checkpoint."""
 
 
 ChannelVersions = dict[str, str | int | float]
@@ -119,6 +121,25 @@ class BaseCheckpointSaver(Generic[V]):
     Checkpointers allow LangGraph agents to persist their state
     within and across multiple interactions.
 
+    When a checkpointer is configured, you should pass a `thread_id` in the config when
+    invoking the graph:
+
+    ```python
+    config = {"configurable": {"thread_id": "my-thread"}}
+    graph.invoke(inputs, config)
+    ```
+
+    The `thread_id` is the primary key used to store and retrieve checkpoints. Without
+    it, the checkpointer cannot save state, resume from interrupts, or enable
+    time-travel debugging.
+
+    How you choose ``thread_id`` depends on your use case:
+
+    - **Single-shot workflows**: Use a unique ID (e.g., uuid4) for each run when
+        executions are independent.
+    - **Conversational memory**: Reuse the same `thread_id` across invocations
+        to accumulate state (e.g., chat history) within a conversation.
+
     Attributes:
         serde (SerializerProtocol): Serializer for encoding/decoding checkpoints.
 
@@ -249,6 +270,45 @@ class BaseCheckpointSaver(Generic[V]):
         """
         raise NotImplementedError
 
+    def delete_for_runs(
+        self,
+        run_ids: Sequence[str],
+    ) -> None:
+        """Delete all checkpoints and writes associated with the given run IDs.
+
+        Args:
+            run_ids: The run IDs whose checkpoints should be deleted.
+        """
+        raise NotImplementedError
+
+    def copy_thread(
+        self,
+        source_thread_id: str,
+        target_thread_id: str,
+    ) -> None:
+        """Copy all checkpoints and writes from one thread to another.
+
+        Args:
+            source_thread_id: The thread ID to copy from.
+            target_thread_id: The thread ID to copy to.
+        """
+        raise NotImplementedError
+
+    def prune(
+        self,
+        thread_ids: Sequence[str],
+        *,
+        strategy: str = "keep_latest",
+    ) -> None:
+        """Prune checkpoints for the given threads.
+
+        Args:
+            thread_ids: The thread IDs to prune.
+            strategy: The pruning strategy. `"keep_latest"` retains only the most
+                recent checkpoint per namespace. `"delete"` removes all checkpoints.
+        """
+        raise NotImplementedError
+
     async def aget(self, config: RunnableConfig) -> Checkpoint | None:
         """Asynchronously fetch a checkpoint using the given configuration.
 
@@ -354,6 +414,45 @@ class BaseCheckpointSaver(Generic[V]):
         """
         raise NotImplementedError
 
+    async def adelete_for_runs(
+        self,
+        run_ids: Sequence[str],
+    ) -> None:
+        """Asynchronously delete all checkpoints and writes for the given run IDs.
+
+        Args:
+            run_ids: The run IDs whose checkpoints should be deleted.
+        """
+        raise NotImplementedError
+
+    async def acopy_thread(
+        self,
+        source_thread_id: str,
+        target_thread_id: str,
+    ) -> None:
+        """Asynchronously copy all checkpoints and writes from one thread to another.
+
+        Args:
+            source_thread_id: The thread ID to copy from.
+            target_thread_id: The thread ID to copy to.
+        """
+        raise NotImplementedError
+
+    async def aprune(
+        self,
+        thread_ids: Sequence[str],
+        *,
+        strategy: str = "keep_latest",
+    ) -> None:
+        """Asynchronously prune checkpoints for the given threads.
+
+        Args:
+            thread_ids: The thread IDs to prune.
+            strategy: The pruning strategy. `"keep_latest"` retains only the most
+                recent checkpoint per namespace. `"delete"` removes all checkpoints.
+        """
+        raise NotImplementedError
+
     def get_next_version(self, current: V | None, channel: None) -> V:
         """Generate the next version ID for a channel.
 

libs/checkpoint/pyproject.toml

@@ -18,7 +18,7 @@ dependencies = [
 
 [project.urls]
 Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/checkpoint"
-Twitter = "https://x.com/LangChainAI"
+Twitter = "https://x.com/LangChain"
 Slack = "https://www.langchain.com/join-community"
 Reddit = "https://www.reddit.com/r/LangChain/"
 

libs/cli/examples/graph_prerelease_reqs/deps/additional_deps/pyproject.toml

@@ -5,5 +5,5 @@ description = "Test for prerelease stuff"
 readme = "README.md"
 requires-python = ">=3.10"
 dependencies = [
-  "langgraph==1.0.2"
+  "langgraph==1.0.8"
 ]

libs/cli/examples/graph_prerelease_reqs/pyproject.toml

@@ -7,7 +7,7 @@ requires-python = ">=3.10"
 dependencies = [
   "langchain-openai==1.0.0a2",
   "langchain-anthropic==1.0.0a5",
-  "langgraph==1.0.2"
+  "langgraph==1.0.8"
 ]
 
 [tool.uv]

libs/cli/js-examples/package.json

@@ -21,25 +21,25 @@
     "test:all": "yarn test && yarn test:int && yarn lint:langgraph"
   },
   "dependencies": {
-    "@langchain/core": "^0.3.2",
-    "@langchain/langgraph": "^0.2.5"
+    "@langchain/core": "^1.1.24",
+    "@langchain/langgraph": "^1.1.4"
   },
   "devDependencies": {
-    "@eslint/eslintrc": "^3.1.0",
-    "@eslint/js": "^9.9.1",
-    "@tsconfig/recommended": "^1.0.7",
-    "@types/jest": "^29.5.0",
-    "@typescript-eslint/eslint-plugin": "^5.59.8",
-    "@typescript-eslint/parser": "^5.59.8",
-    "dotenv": "^16.4.5",
-    "eslint": "^8.41.0",
-    "eslint-config-prettier": "^8.8.0",
-    "eslint-plugin-import": "^2.27.5",
+    "@eslint/eslintrc": "^3.3.3",
+    "@eslint/js": "^10.0.1",
+    "@tsconfig/recommended": "^1.0.13",
+    "@types/jest": "^30.0.0",
+    "@typescript-eslint/eslint-plugin": "^8.56.0",
+    "@typescript-eslint/parser": "^8.56.0",
+    "dotenv": "^17.3.1",
+    "eslint": "^10.0.0",
+    "eslint-config-prettier": "^10.1.8",
+    "eslint-plugin-import": "^2.32.0",
     "eslint-plugin-no-instanceof": "^1.0.1",
-    "eslint-plugin-prettier": "^4.2.1",
-    "jest": "^29.7.0",
-    "prettier": "^3.3.3",
-    "ts-jest": "^29.1.0",
-    "typescript": "^5.3.3"
+    "eslint-plugin-prettier": "^5.5.5",
+    "jest": "^30.2.0",
+    "prettier": "^3.8.1",
+    "ts-jest": "^29.4.6",
+    "typescript": "^5.9.3"
   }
 }

libs/cli/js-monorepo-example/apps/agent/package.json

@@ -9,10 +9,10 @@
   },
   "dependencies": {
     "@js-monorepo-example/shared": "*",
-    "@langchain/core": "^0.3.2",
-    "@langchain/langgraph": "^0.2.5"
+    "@langchain/core": "^1.1.24",
+    "@langchain/langgraph": "^1.1.4"
   },
   "devDependencies": {
-    "typescript": "^5.3.3"
+    "typescript": "^5.9.3"
   }
 }

libs/cli/js-monorepo-example/libs/shared/package.json

@@ -9,6 +9,6 @@
     "clean": "rm -rf dist"
   },
   "devDependencies": {
-    "typescript": "^5.3.3"
+    "typescript": "^5.9.3"
   }
 }

libs/cli/js-monorepo-example/package.json

@@ -17,18 +17,18 @@
     "lint": "eslint 'apps/**/*.ts' 'libs/**/*.ts'"
   },
   "devDependencies": {
-    "turbo": "^2.5.0",
-    "typescript": "^5.3.3",
-    "@tsconfig/recommended": "^1.0.7",
-    "@eslint/eslintrc": "^3.1.0",
-    "@eslint/js": "^9.9.1",
-    "eslint": "^8.41.0",
-    "eslint-config-prettier": "^8.8.0",
+    "turbo": "^2.8.9",
+    "typescript": "^5.9.3",
+    "@tsconfig/recommended": "^1.0.13",
+    "@eslint/eslintrc": "^3.3.3",
+    "@eslint/js": "^10.0.1",
+    "eslint": "^10.0.0",
+    "eslint-config-prettier": "^10.1.8",
     "eslint-plugin-import": "^2.27.5",
     "eslint-plugin-no-instanceof": "^1.0.1",
-    "eslint-plugin-prettier": "^4.2.1",
-    "@typescript-eslint/eslint-plugin": "^5.59.8",
-    "@typescript-eslint/parser": "^5.59.8",
-    "prettier": "^3.3.3"
+    "eslint-plugin-prettier": "^5.5.5",
+    "@typescript-eslint/eslint-plugin": "^8.56.0",
+    "@typescript-eslint/parser": "^8.56.0",
+    "prettier": "^3.8.1"
   }
 }

libs/cli/langgraph_cli/__init__.py

@@ -1 +1 @@
-__version__ = "0.4.11"
+__version__ = "0.4.13"

libs/cli/langgraph_cli/config.py

@@ -196,6 +196,11 @@ def validate_config(config: Config) -> Config:
                 f"Python version {pyversion} is not supported. "
                 f"Minimum required version is {MIN_PYTHON_VERSION}."
             )
+        if "bullseye" in pyversion:
+            raise click.UsageError(
+                "Bullseye images were deprecated in version 0.4.13. "
+                "Please use 'bookworm' or 'debian' instead."
+            )
 
         if not config["dependencies"]:
             raise click.UsageError(
@@ -210,10 +215,15 @@ def validate_config(config: Config) -> Config:
 
     # Validate image_distro config
     if image_distro := config.get("image_distro"):
+        if image_distro == "bullseye":
+            raise click.UsageError(
+                "Bullseye images were deprecated in version 0.4.13. "
+                "Please use 'bookworm' or 'debian' instead."
+            )
         if image_distro not in Distros.__args__:
             raise click.UsageError(
                 f"Invalid image_distro: '{image_distro}'. "
-                "Must be one of 'debian', 'bullseye', or 'bookworm'."
+                "Must be one of 'debian', 'wolfi', or 'bookworm'."
             )
 
     if pip_installer := config.get("pip_installer"):
@@ -668,6 +678,51 @@ def _update_encryption_path(
     )
 
 
+def _update_checkpointer_path(
+    config_path: pathlib.Path, config: Config, local_deps: LocalDeps
+) -> None:
+    """Update checkpointer.path to use Docker container paths."""
+    checkpointer_conf = config.get("checkpointer")
+    if not checkpointer_conf or not isinstance(checkpointer_conf, dict):
+        return
+    if not (path_str := checkpointer_conf.get("path")):
+        return
+
+    module_str, sep, attr_str = path_str.partition(":")
+    if not sep or not module_str.startswith("."):
+        return  # Already validated or absolute path
+
+    resolved = config_path.parent / module_str
+    if not resolved.exists():
+        raise FileNotFoundError(
+            f"Checkpointer file not found: {resolved} (from {path_str})"
+        )
+    if not resolved.is_file():
+        raise IsADirectoryError(f"Checkpointer path must be a file: {resolved}")
+
+    # Check faux packages first (higher priority)
+    for faux_path, (_, destpath) in local_deps.faux_pkgs.items():
+        if resolved.is_relative_to(faux_path):
+            new_path = f"{destpath}/{resolved.relative_to(faux_path)}:{attr_str}"
+            checkpointer_conf["path"] = new_path
+            return
+
+    # Check real packages
+    for real_path in local_deps.real_pkgs:
+        if resolved.is_relative_to(real_path):
+            new_path = (
+                f"/deps/{real_path.name}/{resolved.relative_to(real_path)}:{attr_str}"
+            )
+            checkpointer_conf["path"] = new_path
+            return
+
+    raise ValueError(
+        f"Checkpointer file '{resolved}' not covered by dependencies.\n"
+        "Add its parent directory to the 'dependencies' array in your config.\n"
+        f"Current dependencies: {config['dependencies']}"
+    )
+
+
 def _update_http_app_path(
     config_path: pathlib.Path, config: Config, local_deps: LocalDeps
 ) -> None:
@@ -867,6 +922,8 @@ def python_config_to_docker(
     _update_auth_path(config_path, config, local_deps)
     # Rewrite encryption path, so it points to the correct location in the Docker container
     _update_encryption_path(config_path, config, local_deps)
+    # Rewrite checkpointer path, so it points to the correct location in the Docker container
+    _update_checkpointer_path(config_path, config, local_deps)
     # Rewrite HTTP app path, so it points to the correct location in the Docker container
     _update_http_app_path(config_path, config, local_deps)
 

libs/cli/langgraph_cli/schemas.py

@@ -1,6 +1,6 @@
 from typing import Any, Literal, TypedDict
 
-Distros = Literal["debian", "wolfi", "bullseye", "bookworm"]
+Distros = Literal["debian", "wolfi", "bookworm"]
 MiddlewareOrders = Literal["auth_first", "middleware_first"]
 
 
@@ -107,17 +107,19 @@ class StoreConfig(TypedDict, total=False):
 class ThreadTTLConfig(TypedDict, total=False):
     """Configure a default TTL for checkpointed data within threads."""
 
-    strategy: Literal["delete"]
-    """Strategy to use for deleting checkpointed data.
-    
-    Choices:
-      - "delete": Delete all checkpoints for a thread after TTL expires.
+    strategy: Literal["delete", "keep_latest"]
+    """Action taken when a thread exceeds its TTL.
+
+    - "delete": Remove the thread and all its data entirely.
+    - "keep_latest": Prune old checkpoints but keep the thread and its latest state.
     """
     default_ttl: float | None
     """Default TTL (time-to-live) in minutes for checkpointed data."""
     sweep_interval_minutes: int | None
     """Interval in minutes between sweep iterations.
     If omitted, a default interval will be used (typically ~ 5 minutes)."""
+    sweep_limit: int | None
+    """Maximum number of threads to process per sweep iteration. Defaults to 1000."""
 
 
 class SerdeConfig(TypedDict, total=False):
@@ -165,6 +167,26 @@ class CheckpointerConfig(TypedDict, total=False):
     If omitted, no checkpointer is set up (the object store will still be present, however).
     """
 
+    path: str
+    """Import path to an async context manager that yields a `BaseCheckpointSaver`
+    instance.
+
+    The referenced object should be an `@asynccontextmanager`-decorated function
+    so that the server can properly manage the checkpointer's lifecycle (e.g.
+    opening and closing connections).
+
+    Examples:
+    - "./my_checkpointer.py:create_checkpointer"
+    - "my_package.checkpointer:create_checkpointer"
+
+    When provided, this replaces the default checkpointer.
+
+    You can use the `langgraph-checkpoint-conformance` package
+    (https://pypi.org/project/langgraph-checkpoint-conformance/) to run simple
+    conformance tests against your custom checkpointer and catch
+    incompatibilities early.
+    """
+
     ttl: ThreadTTLConfig | None
     """Optional. Defines the TTL (time-to-live) behavior configuration.
     
@@ -173,7 +195,7 @@ class CheckpointerConfig(TypedDict, total=False):
     """
     serde: SerdeConfig | None
     """Optional. Defines the serde configuration.
-    
+
     If provided, the checkpointer will apply serde settings according to the configuration.
     If omitted, no serde behavior is configured.
 
@@ -557,7 +579,7 @@ class Config(TypedDict, total=False):
     image_distro: Distros | None
     """Optional. Linux distribution for the base image.
     
-    Must be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.
+    Must be one of 'wolfi', 'debian', or 'bookworm'.
     If omitted, defaults to 'debian' ('latest').
     """
 

libs/cli/pyproject.toml

@@ -19,14 +19,14 @@ dependencies = [
 path = "langgraph_cli/__init__.py"
 [project.optional-dependencies]
 inmem = [
-    "langgraph-api>=0.5.35,<0.7.0 ; python_version >= '3.11'",
+    "langgraph-api>=0.5.35,<0.8.0 ; python_version >= '3.11'",
     "langgraph-runtime-inmem>=0.7 ; python_version >= '3.11'",
     "python-dotenv>=0.8.0",
 ]
 
 [project.urls]
 Source = "https://github.com/langchain-ai/langgraph/tree/main/libs/cli"
-Twitter = "https://x.com/LangChainAI"
+Twitter = "https://x.com/LangChain"
 Slack = "https://www.langchain.com/join-community"
 Reddit = "https://www.reddit.com/r/LangChain/"
 

libs/cli/schemas/schema.json

@@ -147,7 +147,6 @@
                 {
                   "enum": [
                     "bookworm",
-                    "bullseye",
                     "debian",
                     "wolfi"
                   ]
@@ -156,7 +155,7 @@
                   "type": "null"
                 }
               ],
-              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
+              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
             },
             "keep_pkg_tools": {
               "anyOf": [
@@ -370,7 +369,7 @@
                   "type": "null"
                 }
               ],
-              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
+              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
             },
             "keep_pkg_tools": {
               "anyOf": [
@@ -543,6 +542,10 @@
       "description": "Configuration for the built-in checkpointer, which handles checkpointing of state.\n\nIf omitted, no checkpointer is set up (the object store will still be present, however).",
       "type": "object",
       "properties": {
+        "path": {
+          "type": "string",
+          "description": "Import path to an async context manager that yields a `BaseCheckpointSaver`\ninstance.\n\nThe referenced object should be an `@asynccontextmanager`-decorated function\nso that the server can properly manage the checkpointer's lifecycle (e.g.\nopening and closing connections).\n"
+        },
         "serde": {
           "anyOf": [
             {
@@ -618,9 +621,10 @@
         },
         "strategy": {
           "enum": [
-            "delete"
+            "delete",
+            "keep_latest"
           ],
-          "description": "Strategy to use for deleting checkpointed data.\n"
+          "description": "Action taken when a thread exceeds its TTL.\n\n"
         },
         "sweep_interval_minutes": {
           "anyOf": [
@@ -632,6 +636,17 @@
             }
           ],
           "description": "Interval in minutes between sweep iterations.\nIf omitted, a default interval will be used (typically ~ 5 minutes)."
+        },
+        "sweep_limit": {
+          "anyOf": [
+            {
+              "type": "integer"
+            },
+            {
+              "type": "null"
+            }
+          ],
+          "description": "Maximum number of threads to process per sweep iteration. Defaults to 1000."
         }
       },
       "required": []

libs/cli/schemas/schema.v0.json

@@ -147,7 +147,6 @@
                 {
                   "enum": [
                     "bookworm",
-                    "bullseye",
                     "debian",
                     "wolfi"
                   ]
@@ -156,7 +155,7 @@
                   "type": "null"
                 }
               ],
-              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
+              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
             },
             "keep_pkg_tools": {
               "anyOf": [
@@ -370,7 +369,7 @@
                   "type": "null"
                 }
               ],
-              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', 'bullseye', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
+              "description": "Optional. Linux distribution for the base image.\n\nMust be one of 'wolfi', 'debian', or 'bookworm'.\nIf omitted, defaults to 'debian' ('latest').\n"
             },
             "keep_pkg_tools": {
               "anyOf": [
@@ -543,6 +542,10 @@
       "description": "Configuration for the built-in checkpointer, which handles checkpointing of state.\n\nIf omitted, no checkpointer is set up (the object store will still be present, however).",
       "type": "object",
       "properties": {
+        "path": {
+          "type": "string",
+          "description": "Import path to an async context manager that yields a `BaseCheckpointSaver`\ninstance.\n\nThe referenced object should be an `@asynccontextmanager`-decorated function\nso that the server can properly manage the checkpointer's lifecycle (e.g.\nopening and closing connections).\n"
+        },
         "serde": {
           "anyOf": [
             {
@@ -618,9 +621,10 @@
         },
         "strategy": {
           "enum": [
-            "delete"
+            "delete",
+            "keep_latest"
           ],
-          "description": "Strategy to use for deleting checkpointed data.\n"
+          "description": "Action taken when a thread exceeds its TTL.\n\n"
         },
         "sweep_interval_minutes": {
           "anyOf": [
@@ -632,6 +636,17 @@
             }
           ],
           "description": "Interval in minutes between sweep iterations.\nIf omitted, a default interval will be used (typically ~ 5 minutes)."
+        },
+        "sweep_limit": {
+          "anyOf": [
+            {
+              "type": "integer"
+            },
+            {
+              "type": "null"
+            }
+          ],
+          "description": "Maximum number of threads to process per sweep iteration. Defaults to 1000."
         }
       },
       "required": []

libs/cli/tests/unit_tests/test_config.py

@@ -120,14 +120,14 @@ def test_validate_config():
         validate_config({"python_version": "3.10"})
     assert "Minimum required version" in str(exc_info.value)
 
-    config = validate_config(
-        {
-            "python_version": "3.11-bullseye",
-            "dependencies": ["."],
-            "graphs": {"agent": "./agent.py:graph"},
-        }
-    )
-    assert config["python_version"] == "3.11-bullseye"
+    with pytest.raises(click.UsageError, match="Bullseye images were deprecated"):
+        validate_config(
+            {
+                "python_version": "3.11-bullseye",
+                "dependencies": ["."],
+                "graphs": {"agent": "./agent.py:graph"},
+            }
+        )
 
     config = validate_config(
         {
@@ -181,6 +181,17 @@ def test_validate_config_image_distro():
     )
     assert config["image_distro"] == "debian"
 
+    # Bullseye should raise deprecation error
+    with pytest.raises(click.UsageError, match="Bullseye images were deprecated"):
+        validate_config(
+            {
+                "python_version": "3.11",
+                "dependencies": ["."],
+                "graphs": {"agent": "./agent.py:graph"},
+                "image_distro": "bullseye",
+            }
+        )
+
     # Invalid image_distro values should raise error
     with pytest.raises(click.UsageError) as exc_info:
         validate_config(

libs/langgraph/langgraph/_internal/_queue.py

@@ -25,7 +25,7 @@ class AsyncQueue(asyncio.Queue):
             self._getters.append(getter)
             try:
                 await getter
-            except:
+            except BaseException:
                 getter.cancel()  # Just in case getter is not done yet.
                 try:
                     # Clean self._getters from canceled getters.

libs/langgraph/langgraph/graph/state.py

@@ -300,7 +300,56 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
         **kwargs: Unpack[DeprecatedKwargs],
     ) -> Self:
         """Add a new node to the `StateGraph`, input schema is inferred as the state schema.
+
         Will take the name of the function/runnable as the node name.
+
+        Args:
+            node: The function or runnable this node will run.
+            defer: Whether to defer the execution of the node until the run is about to end.
+            metadata: The metadata associated with the node.
+            input_schema: The input schema for the node. (Default: the graph's state schema)
+            retry_policy: The retry policy for the node.
+
+                If a sequence is provided, the first matching policy will be applied.
+            cache_policy: The cache policy for the node.
+            destinations: Destinations that indicate where a node can route to.
+
+                Useful for edgeless graphs with nodes that return `Command` objects.
+
+                If a `dict` is provided, the keys will be used as the target node names and the values will be used as the labels for the edges.
+
+                If a `tuple` is provided, the values will be used as the target node names.
+
+                !!! warning
+
+                    This is only used for graph rendering and doesn't have any effect on the graph execution.
+
+        Example:
+            ```python
+            from typing_extensions import TypedDict
+
+            from langchain_core.runnables import RunnableConfig
+            from langgraph.graph import START, StateGraph
+
+
+            class State(TypedDict):
+                x: int
+
+
+            def my_node(state: State, config: RunnableConfig) -> State:
+                return {"x": state["x"] + 1}
+
+
+            builder = StateGraph(State)
+            builder.add_node(my_node)  # node name will be 'my_node'
+            builder.add_edge(START, "my_node")
+            graph = builder.compile()
+            graph.invoke({"x": 1})
+            # {'x': 2}
+            ```
+
+        Returns:
+            Self: The instance of the `StateGraph`, allowing for method chaining.
         """
         ...
 
@@ -317,8 +366,61 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
         destinations: dict[str, str] | tuple[str, ...] | None = None,
         **kwargs: Unpack[DeprecatedKwargs],
     ) -> Self:
-        """Add a new node to the `StateGraph`, input schema is specified.
+        """Add a new node to the `StateGraph` where input schema is specified.
+
         Will take the name of the function/runnable as the node name.
+
+        Args:
+            node: The function or runnable this node will run.
+            defer: Whether to defer the execution of the node until the run is about to end.
+            metadata: The metadata associated with the node.
+            input_schema: The input schema for the node.
+            retry_policy: The retry policy for the node.
+
+                If a sequence is provided, the first matching policy will be applied.
+            cache_policy: The cache policy for the node.
+            destinations: Destinations that indicate where a node can route to.
+
+                Useful for edgeless graphs with nodes that return `Command` objects.
+
+                If a `dict` is provided, the keys will be used as the target node names and the values will be used as the labels for the edges.
+
+                If a `tuple` is provided, the values will be used as the target node names.
+
+                !!! warning
+
+                    This is only used for graph rendering and doesn't have any effect on the graph execution.
+
+        Example:
+            ```python
+            from typing_extensions import TypedDict
+
+            from langchain_core.runnables import RunnableConfig
+            from langgraph.graph import START, StateGraph
+
+
+            class State(TypedDict):
+                x: int
+
+
+            class NodeInput(TypedDict):
+                x: int
+
+
+            def my_node(state: NodeInput, config: RunnableConfig) -> State:
+                return {"x": state["x"] + 1}
+
+
+            builder = StateGraph(State)
+            builder.add_node(my_node, input_schema=NodeInput)  # node name will be 'my_node'
+            builder.add_edge(START, "my_node")
+            graph = builder.compile()
+            graph.invoke({"x": 1})
+            # {'x': 2}
+            ```
+
+        Returns:
+            Self: The instance of the `StateGraph`, allowing for method chaining.
         """
         ...
 
@@ -336,7 +438,57 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
         destinations: dict[str, str] | tuple[str, ...] | None = None,
         **kwargs: Unpack[DeprecatedKwargs],
     ) -> Self:
-        """Add a new node to the `StateGraph`, input schema is inferred as the state schema."""
+        """Add a new node to the `StateGraph`, input schema is inferred as the state schema.
+
+        Args:
+            node: The name of the node.
+            action: The function or runnable this node will run.
+            defer: Whether to defer the execution of the node until the run is about to end.
+            metadata: The metadata associated with the node.
+            input_schema: The input schema for the node. (Default: the graph's state schema)
+            retry_policy: The retry policy for the node.
+
+                If a sequence is provided, the first matching policy will be applied.
+            cache_policy: The cache policy for the node.
+            destinations: Destinations that indicate where a node can route to.
+
+                Useful for edgeless graphs with nodes that return `Command` objects.
+
+                If a `dict` is provided, the keys will be used as the target node names and the values will be used as the labels for the edges.
+
+                If a `tuple` is provided, the values will be used as the target node names.
+
+                !!! warning
+
+                    This is only used for graph rendering and doesn't have any effect on the graph execution.
+
+        Example:
+            ```python
+            from typing_extensions import TypedDict
+
+            from langchain_core.runnables import RunnableConfig
+            from langgraph.graph import START, StateGraph
+
+
+            class State(TypedDict):
+                x: int
+
+
+            def my_node(state: State, config: RunnableConfig) -> State:
+                return {"x": state["x"] + 1}
+
+
+            builder = StateGraph(State)
+            builder.add_node("my_fair_node", my_node)
+            builder.add_edge(START, "my_fair_node")
+            graph = builder.compile()
+            graph.invoke({"x": 1})
+            # {'x': 2}
+            ```
+
+        Returns:
+            Self: The instance of the `StateGraph`, allowing for method chaining.
+        """
         ...
 
     @overload
@@ -353,7 +505,65 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
         destinations: dict[str, str] | tuple[str, ...] | None = None,
         **kwargs: Unpack[DeprecatedKwargs],
     ) -> Self:
-        """Add a new node to the `StateGraph`, input schema is specified."""
+        """Add a new node to the `StateGraph`, input schema is specified.
+
+        Args:
+            node: The function or runnable this node will run.
+
+                If a string is provided, it will be used as the node name, and action will be used as the function or runnable.
+            action: The action associated with the node.
+
+                Will be used as the node function or runnable if `node` is a string (node name).
+            defer: Whether to defer the execution of the node until the run is about to end.
+            metadata: The metadata associated with the node.
+            input_schema: The input schema for the node.
+            retry_policy: The retry policy for the node.
+
+                If a sequence is provided, the first matching policy will be applied.
+            cache_policy: The cache policy for the node.
+            destinations: Destinations that indicate where a node can route to.
+
+                Useful for edgeless graphs with nodes that return `Command` objects.
+
+                If a `dict` is provided, the keys will be used as the target node names and the values will be used as the labels for the edges.
+
+                If a `tuple` is provided, the values will be used as the target node names.
+
+                !!! warning
+
+                    This is only used for graph rendering and doesn't have any effect on the graph execution.
+
+        Example:
+            ```python
+            from typing_extensions import TypedDict
+
+            from langchain_core.runnables import RunnableConfig
+            from langgraph.graph import START, StateGraph
+
+
+            class State(TypedDict):
+                x: int
+
+
+            class NodeInput(TypedDict):
+                x: int
+
+
+            def my_node(state: NodeInput, config: RunnableConfig) -> State:
+                return {"x": state["x"] + 1}
+
+
+            builder = StateGraph(State)
+            builder.add_node("my_fair_node", my_node, input_schema=NodeInput)
+            builder.add_edge(START, "my_fair_node")
+            graph = builder.compile()
+            graph.invoke({"x": 1})
+            # {'x': 2}
+            ```
+
+        Returns:
+            Self: The instance of the `StateGraph`, allowing for method chaining.
+        """
         ...
 
     def add_node(
@@ -376,6 +586,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
 
                 If a string is provided, it will be used as the node name, and action will be used as the function or runnable.
             action: The action associated with the node.
+
                 Will be used as the node function or runnable if `node` is a string (node name).
             defer: Whether to defer the execution of the node until the run is about to end.
             metadata: The metadata associated with the node.
@@ -392,7 +603,7 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
 
                 If a `tuple` is provided, the values will be used as the target node names.
 
-                !!! note
+                !!! warning
 
                     This is only used for graph rendering and doesn't have any effect on the graph execution.
 
@@ -846,6 +1057,19 @@ class StateGraph(Generic[StateT, ContextT, InputT, OutputT]):
                 If `None`, it may inherit the parent graph's checkpointer when used as a subgraph.
 
                 If `False`, it will not use or inherit any checkpointer.
+
+                **Important**: When a checkpointer is enabled, you should pass a `thread_id`
+                in the config when invoking the graph:
+
+                ```python
+                config = {"configurable": {"thread_id": "my-thread"}}
+                graph.invoke(inputs, config)
+                ```
+
+                The `thread_id` is the key used to store and retrieve checkpoints. Use a
+                unique ID for independent runs, or reuse the same ID to accumulate state
+                across invocations (e.g., for conversation memory).
+
             interrupt_before: An optional list of node names to interrupt before.
             interrupt_after: An optional list of node names to interrupt after.
             debug: A flag indicating whether to enable debug mode.