release: langgraph + prebuilt (#6875)

Fixes https://github.com/langchain-ai/langchain/issues/35305

Co-authored-by: Shivangi Sharma <shivangi.sharma7004@gmail.com>

.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

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",
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+  "/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"
+}

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/pyproject.toml

@@ -13,7 +13,7 @@ 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",
 ]

libs/checkpoint-postgres/uv.lock

@@ -240,7 +240,7 @@ wheels = [
 
 [[package]]
 name = "langchain-core"
-version = "1.2.7"
+version = "1.2.11"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "jsonpatch" },
@@ -252,9 +252,9 @@ dependencies = [
     { name = "typing-extensions" },
     { name = "uuid-utils" },
 ]
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 wheels = [
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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" },
 ]
 
 [[package]]
@@ -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" },
 ]
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 [[package]]

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]
@@ -268,6 +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.
 
@@ -373,6 +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/uv.lock

@@ -267,7 +267,7 @@ wheels = [
 
 [[package]]
 name = "langchain-core"
-version = "1.2.7"
+version = "1.2.13"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "jsonpatch" },
@@ -279,9 +279,9 @@ dependencies = [
     { name = "typing-extensions" },
     { name = "uuid-utils" },
 ]
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 ]
 
 [[package]]

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__ = "0.4.12"
+__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"):

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):
@@ -173,14 +175,12 @@ 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.
 
     This configuration requires server version 0.5 or later to take effect.
     """
-    sweep_limit: int | None
-    """Maximum number of threads to process per sweep iteration. Defaults to 1000."""
 
 
 class SecurityConfig(TypedDict, total=False):
@@ -559,7 +559,7 @@ 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/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": [
@@ -554,17 +553,6 @@
           ],
           "description": "Optional. Defines the serde configuration.\n\nIf provided, the checkpointer will apply serde settings according to the configuration.\nIf omitted, no serde behavior is configured.\n\nThis configuration requires server version 0.5 or later to take effect.\n"
         },
-        "sweep_limit": {
-          "anyOf": [
-            {
-              "type": "integer"
-            },
-            {
-              "type": "null"
-            }
-          ],
-          "description": "Maximum number of threads to process per sweep iteration. Defaults to 1000."
-        },
         "ttl": {
           "anyOf": [
             {
@@ -629,9 +617,10 @@
         },
         "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": [
@@ -643,6 +632,17 @@
             }
           ],
           "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": [
@@ -554,17 +553,6 @@
           ],
           "description": "Optional. Defines the serde configuration.\n\nIf provided, the checkpointer will apply serde settings according to the configuration.\nIf omitted, no serde behavior is configured.\n\nThis configuration requires server version 0.5 or later to take effect.\n"
         },
-        "sweep_limit": {
-          "anyOf": [
-            {
-              "type": "integer"
-            },
-            {
-              "type": "null"
-            }
-          ],
-          "description": "Maximum number of threads to process per sweep iteration. Defaults to 1000."
-        },
         "ttl": {
           "anyOf": [
             {
@@ -629,9 +617,10 @@
         },
         "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": [
@@ -643,6 +632,17 @@
             }
           ],
           "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/cli/uv.lock

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 ]
 
 [[package]]

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/pregel/_messages.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 from collections.abc import AsyncIterator, Callable, Iterator, Sequence
+from dataclasses import fields, is_dataclass
 from typing import (
     Any,
     TypeVar,
@@ -11,6 +12,7 @@ from uuid import UUID, uuid4
 from langchain_core.callbacks import BaseCallbackHandler
 from langchain_core.messages import BaseMessage
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, LLMResult
+from pydantic import BaseModel
 
 from langgraph._internal._constants import NS_SEP
 from langgraph.constants import TAG_HIDDEN, TAG_NOSTREAM
@@ -26,6 +28,17 @@ T = TypeVar("T")
 Meta = tuple[tuple[str, ...], dict[str, Any]]
 
 
+def _state_values(obj: Any) -> Sequence[Any]:
+    """Extract top-level field values from a state object (dict, BaseModel, or dataclass)."""
+    if isinstance(obj, dict):
+        return list(obj.values())
+    elif isinstance(obj, BaseModel):
+        return [getattr(obj, k) for k in type(obj).model_fields]
+    elif is_dataclass(obj) and not isinstance(obj, type):
+        return [getattr(obj, f.name) for f in fields(obj)]
+    return ()
+
+
 class StreamMessagesHandler(BaseCallbackHandler, _StreamingCallbackHandler):
     """A callback handler that implements stream_mode=messages.
 
@@ -90,26 +103,14 @@ class StreamMessagesHandler(BaseCallbackHandler, _StreamingCallbackHandler):
             for value in response:
                 if isinstance(value, BaseMessage):
                     self._emit(meta, value, dedupe=True)
-        elif isinstance(response, dict):
-            for value in response.values():
+        else:
+            for value in _state_values(response):
                 if isinstance(value, BaseMessage):
                     self._emit(meta, value, dedupe=True)
                 elif isinstance(value, Sequence):
                     for item in value:
                         if isinstance(item, BaseMessage):
                             self._emit(meta, item, dedupe=True)
-        elif hasattr(response, "__dir__") and callable(response.__dir__):
-            for key in dir(response):
-                try:
-                    value = getattr(response, key)
-                    if isinstance(value, BaseMessage):
-                        self._emit(meta, value, dedupe=True)
-                    elif isinstance(value, Sequence):
-                        for item in value:
-                            if isinstance(item, BaseMessage):
-                                self._emit(meta, item, dedupe=True)
-                except AttributeError:
-                    pass
 
     def tap_output_aiter(
         self, run_id: UUID, output: AsyncIterator[T]
@@ -203,16 +204,15 @@ class StreamMessagesHandler(BaseCallbackHandler, _StreamingCallbackHandler):
             if not self.subgraphs and len(ns) > 0:
                 return
             self.metadata[run_id] = (ns, metadata)
-            if isinstance(inputs, dict):
-                for key, value in inputs.items():
-                    if isinstance(value, BaseMessage):
-                        if value.id is not None:
-                            self.seen.add(value.id)
-                    elif isinstance(value, Sequence) and not isinstance(value, str):
-                        for item in value:
-                            if isinstance(item, BaseMessage):
-                                if item.id is not None:
-                                    self.seen.add(item.id)
+            for value in _state_values(inputs):
+                if isinstance(value, BaseMessage):
+                    if value.id is not None:
+                        self.seen.add(value.id)
+                elif isinstance(value, Sequence) and not isinstance(value, str):
+                    for item in value:
+                        if isinstance(item, BaseMessage):
+                            if item.id is not None:
+                                self.seen.add(item.id)
 
     def on_chain_end(
         self,

libs/langgraph/langgraph/pregel/_runner.py

@@ -565,7 +565,7 @@ def _call(
         if fut := next(
             (
                 f
-                for f, t in futures().items()  # type: ignore[union-attr]
+                for f, t in list(futures().items())  # type: ignore[union-attr]
                 if t is not None and t == next_task.id
             ),
             None,
@@ -708,7 +708,7 @@ async def _acall_impl(
             if fut := next(
                 (
                     f
-                    for f, t in futures().items()  # type: ignore[union-attr]
+                    for f, t in list(futures().items())  # type: ignore[union-attr]
                     if t is not None and t == next_task.id
                 ),
                 None,
@@ -728,7 +728,6 @@ async def _acall_impl(
                     )
                 else:
                     fut.set_result(None)
-                futures()[fut] = next_task  # type: ignore[index]
             else:
                 # schedule the next task
                 fut = cast(

libs/langgraph/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph"
-version = "1.0.7"
+version = "1.0.9"
 description = "Building stateful, multi-actor applications with LLMs"
 authors = []
 requires-python = ">=3.10"
@@ -27,7 +27,7 @@ dependencies = [
     "langchain-core>=0.1",
     "langgraph-checkpoint>=2.1.0,<5.0.0",
     "langgraph-sdk>=0.3.0,<0.4.0",
-    "langgraph-prebuilt>=1.0.7,<1.1.0",
+    "langgraph-prebuilt>=1.0.8,<1.1.0",
     "xxhash>=3.5.0",
     "pydantic>=2.7.4",
 ]
@@ -60,7 +60,7 @@ test = [
     "langgraph-checkpoint-postgres",
     "langgraph-sdk",
     "psycopg[binary]",
-    "uvloop==0.21.0beta1",
+    "uvloop==0.22.1",
     "pyperf",
     "py-spy",
     "pycryptodome",

libs/langgraph/tests/test_pregel.py

@@ -16,7 +16,7 @@ from typing import Annotated, Any, Literal, get_type_hints
 
 import pytest
 from langchain_core.language_models import GenericFakeChatModel
-from langchain_core.messages import AnyMessage
+from langchain_core.messages import AIMessage, AnyMessage, HumanMessage
 from langchain_core.runnables import (
     RunnableConfig,
     RunnableLambda,
@@ -1264,18 +1264,20 @@ def test_imp_task(
     }
 
     thread1 = {"configurable": {"thread_id": "1"}}
-    assert [*graph.stream([0, 1], thread1, durability=durability)] == [
+    result = [*graph.stream([0, 1], thread1, durability=durability)]
+    # mapper tasks run concurrently so output order is non-deterministic
+    assert sorted(result[:-1], key=lambda d: str(d)) == [
         {"mapper": "00"},
         {"mapper": "11"},
-        {
-            "__interrupt__": (
-                Interrupt(
-                    value="question",
-                    id=AnyStr(),
-                ),
-            )
-        },
     ]
+    assert result[-1] == {
+        "__interrupt__": (
+            Interrupt(
+                value="question",
+                id=AnyStr(),
+            ),
+        )
+    }
     assert mapper_calls == 2
 
     assert graph.invoke(Command(resume="answer"), thread1, durability=durability) == [
@@ -5798,6 +5800,284 @@ def test_multiple_interrupts_functional_cache(
     assert counter == 6
 
 
+def test_task_before_interrupt_resume(
+    sync_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Test that Command(resume=value) works correctly when a @task runs
+    before interrupt-producing tasks in an @entrypoint.
+
+    The @task wrapper on both setup and ask is essential to reproduce the bug:
+    - @task on setup triggers a mid-step put_writes (creating a new pending_writes list)
+    - @task on ask means interrupt() runs in a child scratchpad that must
+      delegate to the parent for null resume consumption tracking
+    """
+
+    @entrypoint(checkpointer=sync_checkpointer)
+    def workflow(number_of_topics: int) -> dict:
+        @task
+        def setup() -> int:
+            return number_of_topics
+
+        @task
+        def ask(question: str) -> str:
+            return interrupt(question)
+
+        n = setup().result()
+
+        answers = []
+        for i in range(n):
+            q = f"Whats the answer for topic {i + 1}?"
+            answers.append(ask(q).result())
+
+        return {"answers": answers}
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # First invocation - should get first interrupt
+    result = workflow.invoke(2, config=config)
+    assert "__interrupt__" in result
+    assert len(result["__interrupt__"]) == 1
+    assert result["__interrupt__"][0].value == "Whats the answer for topic 1?"
+
+    # Resume with answer for topic 1 - should get second interrupt
+    result = workflow.invoke(Command(resume="answer1"), config=config)
+    assert "__interrupt__" in result, f"Expected interrupt for topic 2, got: {result}"
+    assert len(result["__interrupt__"]) == 1
+    assert result["__interrupt__"][0].value == "Whats the answer for topic 2?"
+
+    # Resume with answer for topic 2 - should get final result
+    result = workflow.invoke(Command(resume="answer2"), config=config)
+    assert result == {"answers": ["answer1", "answer2"]}
+
+
+def test_multiple_tasks_before_interrupt_resume(
+    sync_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Test that Command(resume=value) works correctly when multiple @tasks
+    run before an interrupt-producing task in an @entrypoint."""
+
+    @entrypoint(checkpointer=sync_checkpointer)
+    def workflow(inputs: dict) -> dict:
+        @task
+        def step_a(x: int) -> int:
+            return x + 1
+
+        @task
+        def step_b(x: int) -> int:
+            return x * 2
+
+        @task
+        def ask(question: str) -> str:
+            return interrupt(question)
+
+        a = step_a(inputs["x"]).result()
+        b = step_b(a).result()
+
+        answer = ask(f"Result so far is {b}. What next?").result()
+
+        return {"computed": b, "answer": answer}
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # First invocation - should get interrupt
+    result = workflow.invoke({"x": 5}, config=config)
+    assert "__interrupt__" in result
+    assert result["__interrupt__"][0].value == "Result so far is 12. What next?"
+
+    # Resume
+    result = workflow.invoke(Command(resume="continue"), config=config)
+    assert result == {"computed": 12, "answer": "continue"}
+
+
+def test_no_redundant_put_writes_for_cached_task(
+    sync_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Cached @tasks on resume must not trigger redundant put_writes."""
+    from unittest.mock import patch
+
+    from langgraph.pregel._loop import PregelLoop
+
+    @task
+    def setup(x: int) -> int:
+        return x
+
+    @task
+    def ask(question: str) -> str:
+        return interrupt(question)
+
+    @entrypoint(checkpointer=sync_checkpointer)
+    def workflow(x: int) -> dict:
+        n = setup(x).result()
+        answer = ask(f"q{n}").result()
+        return {"answer": answer}
+
+    config = {"configurable": {"thread_id": "1"}}
+    result = workflow.invoke(1, config=config)
+    assert "__interrupt__" in result
+
+    put_writes_task_ids: list[str] = []
+    orig = PregelLoop.put_writes
+
+    def spy(self, task_id, writes):
+        put_writes_task_ids.append(task_id)
+        return orig(self, task_id, writes)
+
+    with patch.object(PregelLoop, "put_writes", spy):
+        result = workflow.invoke(Command(resume="ans"), config=config)
+
+    assert result == {"answer": "ans"}
+    # Count unique non-null task IDs that got put_writes.
+    # Should be exactly 2: the ask task and the entrypoint task.
+    # If 3, the cached setup task is being redundantly re-committed.
+    non_null = set(tid for tid in put_writes_task_ids if not tid.startswith("00000000"))
+    assert len(non_null) == 2, (
+        f"Expected 2 task IDs in put_writes (ask + entrypoint), got {len(non_null)}"
+    )
+
+
+def test_node_before_interrupt_resume_graph_api(
+    sync_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Test that Command(resume=value) works correctly in a StateGraph when a
+    node runs before a node that calls interrupt(). This is the graph-API
+    analog of test_task_before_interrupt_resume (entrypoint API)."""
+
+    class State(TypedDict):
+        topics: list[str]
+        answers: Annotated[list[str], operator.add]
+
+    def setup(state: State) -> dict:
+        return {"topics": [f"topic {i + 1}" for i in range(len(state["topics"]))]}
+
+    def ask(state: State) -> dict:
+        answers = []
+        for topic in state["topics"]:
+            answer = interrupt(f"Whats the answer for {topic}?")
+            answers.append(answer)
+        return {"answers": answers}
+
+    graph = (
+        StateGraph(State)
+        .add_node("setup", setup)
+        .add_node("ask", ask)
+        .add_edge(START, "setup")
+        .add_edge("setup", "ask")
+        .add_edge("ask", END)
+        .compile(checkpointer=sync_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # First invocation - setup runs, then ask interrupts on the first topic
+    result = graph.invoke({"topics": ["a", "b"], "answers": []}, config=config)
+    assert "__interrupt__" in result
+    assert len(result["__interrupt__"]) == 1
+    assert result["__interrupt__"][0].value == "Whats the answer for topic 1?"
+
+    # Resume with answer for topic 1 - should get second interrupt
+    result = graph.invoke(Command(resume="answer1"), config=config)
+    assert "__interrupt__" in result, f"Expected interrupt for topic 2, got: {result}"
+    assert len(result["__interrupt__"]) == 1
+    assert result["__interrupt__"][0].value == "Whats the answer for topic 2?"
+
+    # Resume with answer for topic 2 - should complete
+    result = graph.invoke(Command(resume="answer2"), config=config)
+    assert result == {
+        "topics": ["topic 1", "topic 2"],
+        "answers": ["answer1", "answer2"],
+    }
+
+
+def test_multiple_nodes_before_interrupt_resume_graph_api(
+    sync_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Test that Command(resume=value) works correctly in a StateGraph when
+    multiple nodes run before a node that calls interrupt(). This is the
+    graph-API analog of test_multiple_tasks_before_interrupt_resume."""
+
+    class State(TypedDict):
+        value: int
+        answer: str
+
+    def step_a(state: State) -> dict:
+        return {"value": state["value"] + 1}
+
+    def step_b(state: State) -> dict:
+        return {"value": state["value"] * 2}
+
+    def ask(state: State) -> dict:
+        answer = interrupt(f"Result so far is {state['value']}. What next?")
+        return {"answer": answer}
+
+    graph = (
+        StateGraph(State)
+        .add_node("step_a", step_a)
+        .add_node("step_b", step_b)
+        .add_node("ask", ask)
+        .add_edge(START, "step_a")
+        .add_edge("step_a", "step_b")
+        .add_edge("step_b", "ask")
+        .add_edge("ask", END)
+        .compile(checkpointer=sync_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # First invocation - step_a and step_b run, then ask interrupts
+    result = graph.invoke({"value": 5, "answer": ""}, config=config)
+    assert "__interrupt__" in result
+    assert result["__interrupt__"][0].value == "Result so far is 12. What next?"
+
+    # Resume - should complete
+    result = graph.invoke(Command(resume="continue"), config=config)
+    assert result == {"value": 12, "answer": "continue"}
+
+
+def test_node_before_multiple_interrupt_cycles_graph_api(
+    sync_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Test that a node running before an interrupt node does not interfere
+    with multiple interrupt/resume cycles in a StateGraph."""
+
+    class State(TypedDict):
+        count: int
+        data: str
+
+    def prepare(state: State) -> dict:
+        return {"count": state["count"] + 10}
+
+    def multi_interrupt(state: State) -> dict:
+        first = interrupt("First question?")
+        second = interrupt("Second question?")
+        return {"data": f"{first},{second}"}
+
+    graph = (
+        StateGraph(State)
+        .add_node("prepare", prepare)
+        .add_node("multi_interrupt", multi_interrupt)
+        .add_edge(START, "prepare")
+        .add_edge("prepare", "multi_interrupt")
+        .add_edge("multi_interrupt", END)
+        .compile(checkpointer=sync_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # First invocation - prepare runs, multi_interrupt hits first interrupt
+    result = graph.invoke({"count": 0, "data": ""}, config=config)
+    assert "__interrupt__" in result
+    assert result["__interrupt__"][0].value == "First question?"
+
+    # Resume first interrupt - hits second interrupt
+    result = graph.invoke(Command(resume="first_answer"), config=config)
+    assert "__interrupt__" in result
+    assert result["__interrupt__"][0].value == "Second question?"
+
+    # Resume second interrupt - completes
+    result = graph.invoke(Command(resume="second_answer"), config=config)
+    assert result == {"count": 10, "data": "first_answer,second_answer"}
+
+
 def test_double_interrupt_subgraph(sync_checkpointer: BaseCheckpointSaver) -> None:
     class AgentState(TypedDict):
         input: str
@@ -6978,6 +7258,93 @@ def test_stream_messages_dedupe_state(sync_checkpointer: BaseCheckpointSaver) ->
     assert chunks[0][1]["langgraph_node"] == "call_model"
 
 
+def test_stream_messages_dedupe_pydantic_subgraph_interrupt(
+    sync_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Pydantic BaseModel state should not cause duplicate messages when
+    streaming from subgraphs that use interrupts. Regression test for a bug
+    where ``on_chain_start`` only populated the ``seen`` set for dict inputs,
+    skipping Pydantic model inputs entirely."""
+
+    class PydanticState(BaseModel):
+        messages: Annotated[list[AnyMessage], add_messages] = Field(
+            default_factory=list
+        )
+
+    def subgraph_proposal(state) -> Command[Literal["subgraph_approval"]]:
+        return Command(
+            goto="subgraph_approval",
+            update={"messages": [AIMessage(content="Proposal", id="proposal_msg")]},
+        )
+
+    def subgraph_approval(state) -> Command[Literal["__end__"]]:
+        resume_value = interrupt({"message": "Waiting for approval"})
+        user_msg = resume_value.get("user_message", "")
+        msgs = [HumanMessage(content=user_msg)] if user_msg else []
+        return Command(goto="__end__", update={"messages": msgs})
+
+    subgraph = (
+        StateGraph(PydanticState)
+        .add_node("proposal", subgraph_proposal)
+        .add_node("subgraph_approval", subgraph_approval)
+        .add_edge(START, "proposal")
+        .compile(checkpointer=sync_checkpointer)
+    )
+
+    def finalize(state) -> Command[Literal["__end__"]]:
+        return Command(
+            goto="__end__",
+            update={"messages": [AIMessage(content="Finalized", id="finalize_msg")]},
+        )
+
+    graph = (
+        StateGraph(PydanticState)
+        .add_node("subgraph", subgraph)
+        .add_node("finalize", finalize)
+        .add_edge(START, "subgraph")
+        .add_edge("subgraph", "finalize")
+        .compile(checkpointer=sync_checkpointer)
+    )
+
+    thread1 = {"configurable": {"thread_id": "1"}}
+
+    # First stream: should hit interrupt after proposal
+    chunks_req0 = [
+        (ns, chunk)
+        for ns, chunk in graph.stream(
+            {"messages": [HumanMessage(content="Create a proposal")]},
+            thread1,
+            stream_mode="messages",
+            subgraphs=True,
+        )
+    ]
+
+    msg_ids_req0 = {chunk[0].id for _, chunk in chunks_req0}
+    assert "proposal_msg" in msg_ids_req0
+
+    # Verify interrupted
+    state = graph.get_state(thread1)
+    assert state.next
+
+    # Second stream: resume — should NOT duplicate messages from first stream
+    chunks_req1 = [
+        (ns, chunk)
+        for ns, chunk in graph.stream(
+            Command(resume={"user_message": "Yes"}),
+            thread1,
+            stream_mode="messages",
+            subgraphs=True,
+        )
+    ]
+
+    msg_ids_req1 = {chunk[0].id for _, chunk in chunks_req1}
+    assert "finalize_msg" in msg_ids_req1
+
+    # The key assertion: no message IDs from request 0 should appear in request 1
+    duplicates = msg_ids_req0 & msg_ids_req1
+    assert not duplicates, f"Duplicate message IDs across requests: {duplicates}"
+
+
 def test_interrupt_subgraph_reenter_checkpointer_true(
     sync_checkpointer: BaseCheckpointSaver,
 ) -> None:

libs/langgraph/tests/test_pregel_async.py

@@ -2262,18 +2262,20 @@ async def test_imp_task(
 
     tracer = FakeTracer()
     thread1 = {"configurable": {"thread_id": "1"}, "callbacks": [tracer]}
-    assert [c async for c in graph.astream([0, 1], thread1, durability=durability)] == [
+    result = [c async for c in graph.astream([0, 1], thread1, durability=durability)]
+    # mapper tasks run concurrently so output order is non-deterministic
+    assert sorted(result[:-1], key=lambda d: str(d)) == [
         {"mapper": "00"},
         {"mapper": "11"},
-        {
-            "__interrupt__": (
-                Interrupt(
-                    value="question",
-                    id=AnyStr(),
-                ),
-            )
-        },
     ]
+    assert result[-1] == {
+        "__interrupt__": (
+            Interrupt(
+                value="question",
+                id=AnyStr(),
+            ),
+        )
+    }
     assert mapper_calls == 2
     assert len(tracer.runs) == 1
     assert len(tracer.runs[0].child_runs) == 1
@@ -7918,6 +7920,290 @@ async def test_interrupts_in_tasks_surfaced_once(
     assert result[1] == "Added Will!"
 
 
+@NEEDS_CONTEXTVARS
+async def test_task_before_interrupt_resume(
+    async_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Test that Command(resume=value) works correctly when a @task runs
+    before interrupt-producing tasks in an @entrypoint.
+
+    The @task wrapper on both setup and ask is essential to reproduce the bug:
+    - @task on setup triggers a mid-step put_writes (creating a new pending_writes list)
+    - @task on ask means interrupt() runs in a child scratchpad that must
+      delegate to the parent for null resume consumption tracking
+    """
+
+    @entrypoint(checkpointer=async_checkpointer)
+    async def workflow(number_of_topics: int) -> dict:
+        @task
+        async def setup() -> int:
+            return number_of_topics
+
+        @task
+        async def ask(question: str) -> str:
+            return interrupt(question)
+
+        n = await setup()
+
+        answers = []
+        for i in range(n):
+            q = f"Whats the answer for topic {i + 1}?"
+            answers.append(await ask(q))
+
+        return {"answers": answers}
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # First invocation - should get first interrupt
+    result = await workflow.ainvoke(2, config=config)
+    assert "__interrupt__" in result
+    assert len(result["__interrupt__"]) == 1
+    assert result["__interrupt__"][0].value == "Whats the answer for topic 1?"
+
+    # Resume with answer for topic 1 - should get second interrupt
+    result = await workflow.ainvoke(Command(resume="answer1"), config=config)
+    assert "__interrupt__" in result, f"Expected interrupt for topic 2, got: {result}"
+    assert len(result["__interrupt__"]) == 1
+    assert result["__interrupt__"][0].value == "Whats the answer for topic 2?"
+
+    # Resume with answer for topic 2 - should get final result
+    result = await workflow.ainvoke(Command(resume="answer2"), config=config)
+    assert result == {"answers": ["answer1", "answer2"]}
+
+
+@NEEDS_CONTEXTVARS
+async def test_multiple_tasks_before_interrupt_resume(
+    async_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Test that Command(resume=value) works correctly when multiple @tasks
+    run before an interrupt-producing task in an @entrypoint."""
+
+    @entrypoint(checkpointer=async_checkpointer)
+    async def workflow(inputs: dict) -> dict:
+        @task
+        async def step_a(x: int) -> int:
+            return x + 1
+
+        @task
+        async def step_b(x: int) -> int:
+            return x * 2
+
+        @task
+        async def ask(question: str) -> str:
+            return interrupt(question)
+
+        a = await step_a(inputs["x"])
+        b = await step_b(a)
+
+        answer = await ask(f"Result so far is {b}. What next?")
+
+        return {"computed": b, "answer": answer}
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # First invocation - should get interrupt
+    result = await workflow.ainvoke({"x": 5}, config=config)
+    assert "__interrupt__" in result
+    assert result["__interrupt__"][0].value == "Result so far is 12. What next?"
+
+    # Resume
+    result = await workflow.ainvoke(Command(resume="continue"), config=config)
+    assert result == {"computed": 12, "answer": "continue"}
+
+
+@NEEDS_CONTEXTVARS
+async def test_no_redundant_put_writes_for_cached_task(
+    async_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Cached @tasks on resume must not trigger redundant put_writes."""
+    from unittest.mock import patch
+
+    from langgraph.pregel._loop import PregelLoop
+
+    @task
+    async def setup(x: int) -> int:
+        return x
+
+    @task
+    async def ask(question: str) -> str:
+        return interrupt(question)
+
+    @entrypoint(checkpointer=async_checkpointer)
+    async def workflow(x: int) -> dict:
+        n = await setup(x)
+        answer = await ask(f"q{n}")
+        return {"answer": answer}
+
+    config = {"configurable": {"thread_id": "1"}}
+    result = await workflow.ainvoke(1, config=config)
+    assert "__interrupt__" in result
+
+    put_writes_task_ids: list[str] = []
+    orig = PregelLoop.put_writes
+
+    def spy(self, task_id, writes):
+        put_writes_task_ids.append(task_id)
+        return orig(self, task_id, writes)
+
+    with patch.object(PregelLoop, "put_writes", spy):
+        result = await workflow.ainvoke(Command(resume="ans"), config=config)
+
+    assert result == {"answer": "ans"}
+    # Count unique non-null task IDs that got put_writes.
+    # Should be exactly 2: the ask task and the entrypoint task.
+    # If 3, the cached setup task is being redundantly re-committed.
+    non_null = set(tid for tid in put_writes_task_ids if not tid.startswith("00000000"))
+    assert len(non_null) == 2, (
+        f"Expected 2 task IDs in put_writes (ask + entrypoint), got {len(non_null)}"
+    )
+
+
+@NEEDS_CONTEXTVARS
+async def test_node_before_interrupt_resume_graph_api(
+    async_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Test that Command(resume=value) works correctly in a StateGraph when a
+    node runs before a node that calls interrupt(). This is the graph-API
+    analog of test_task_before_interrupt_resume (entrypoint API)."""
+
+    class State(TypedDict):
+        topics: list[str]
+        answers: Annotated[list[str], operator.add]
+
+    def setup(state: State) -> dict:
+        return {"topics": [f"topic {i + 1}" for i in range(len(state["topics"]))]}
+
+    def ask(state: State) -> dict:
+        answers = []
+        for topic in state["topics"]:
+            answer = interrupt(f"Whats the answer for {topic}?")
+            answers.append(answer)
+        return {"answers": answers}
+
+    graph = (
+        StateGraph(State)
+        .add_node("setup", setup)
+        .add_node("ask", ask)
+        .add_edge(START, "setup")
+        .add_edge("setup", "ask")
+        .add_edge("ask", END)
+        .compile(checkpointer=async_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # First invocation - setup runs, then ask interrupts on the first topic
+    result = await graph.ainvoke({"topics": ["a", "b"], "answers": []}, config=config)
+    assert "__interrupt__" in result
+    assert len(result["__interrupt__"]) == 1
+    assert result["__interrupt__"][0].value == "Whats the answer for topic 1?"
+
+    # Resume with answer for topic 1 - should get second interrupt
+    result = await graph.ainvoke(Command(resume="answer1"), config=config)
+    assert "__interrupt__" in result, f"Expected interrupt for topic 2, got: {result}"
+    assert len(result["__interrupt__"]) == 1
+    assert result["__interrupt__"][0].value == "Whats the answer for topic 2?"
+
+    # Resume with answer for topic 2 - should complete
+    result = await graph.ainvoke(Command(resume="answer2"), config=config)
+    assert result == {
+        "topics": ["topic 1", "topic 2"],
+        "answers": ["answer1", "answer2"],
+    }
+
+
+@NEEDS_CONTEXTVARS
+async def test_multiple_nodes_before_interrupt_resume_graph_api(
+    async_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Test that Command(resume=value) works correctly in a StateGraph when
+    multiple nodes run before a node that calls interrupt(). This is the
+    graph-API analog of test_multiple_tasks_before_interrupt_resume."""
+
+    class State(TypedDict):
+        value: int
+        answer: str
+
+    def step_a(state: State) -> dict:
+        return {"value": state["value"] + 1}
+
+    def step_b(state: State) -> dict:
+        return {"value": state["value"] * 2}
+
+    def ask(state: State) -> dict:
+        answer = interrupt(f"Result so far is {state['value']}. What next?")
+        return {"answer": answer}
+
+    graph = (
+        StateGraph(State)
+        .add_node("step_a", step_a)
+        .add_node("step_b", step_b)
+        .add_node("ask", ask)
+        .add_edge(START, "step_a")
+        .add_edge("step_a", "step_b")
+        .add_edge("step_b", "ask")
+        .add_edge("ask", END)
+        .compile(checkpointer=async_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # First invocation - step_a and step_b run, then ask interrupts
+    result = await graph.ainvoke({"value": 5, "answer": ""}, config=config)
+    assert "__interrupt__" in result
+    assert result["__interrupt__"][0].value == "Result so far is 12. What next?"
+
+    # Resume - should complete
+    result = await graph.ainvoke(Command(resume="continue"), config=config)
+    assert result == {"value": 12, "answer": "continue"}
+
+
+@NEEDS_CONTEXTVARS
+async def test_node_before_multiple_interrupt_cycles_graph_api(
+    async_checkpointer: BaseCheckpointSaver,
+) -> None:
+    """Test that a node running before an interrupt node does not interfere
+    with multiple interrupt/resume cycles in a StateGraph."""
+
+    class State(TypedDict):
+        count: int
+        data: str
+
+    def prepare(state: State) -> dict:
+        return {"count": state["count"] + 10}
+
+    def multi_interrupt(state: State) -> dict:
+        first = interrupt("First question?")
+        second = interrupt("Second question?")
+        return {"data": f"{first},{second}"}
+
+    graph = (
+        StateGraph(State)
+        .add_node("prepare", prepare)
+        .add_node("multi_interrupt", multi_interrupt)
+        .add_edge(START, "prepare")
+        .add_edge("prepare", "multi_interrupt")
+        .add_edge("multi_interrupt", END)
+        .compile(checkpointer=async_checkpointer)
+    )
+
+    config = {"configurable": {"thread_id": "1"}}
+
+    # First invocation - prepare runs, multi_interrupt hits first interrupt
+    result = await graph.ainvoke({"count": 0, "data": ""}, config=config)
+    assert "__interrupt__" in result
+    assert result["__interrupt__"][0].value == "First question?"
+
+    # Resume first interrupt - hits second interrupt
+    result = await graph.ainvoke(Command(resume="first_answer"), config=config)
+    assert "__interrupt__" in result
+    assert result["__interrupt__"][0].value == "Second question?"
+
+    # Resume second interrupt - completes
+    result = await graph.ainvoke(Command(resume="second_answer"), config=config)
+    assert result == {"count": 10, "data": "first_answer,second_answer"}
+
+
 async def test_pregel_loop_refcount():
     gc.collect()
     try:

libs/langgraph/uv.lock

@@ -524,66 +524,61 @@ toml = [
 
 [[package]]
 name = "cryptography"
-version = "46.0.3"
+version = "46.0.5"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "cffi", marker = "python_full_version >= '3.11' and python_full_version < '3.14' and platform_python_implementation != 'PyPy'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/9f/33/c00162f49c0e2fe8064a62cb92b93e50c74a72bc370ab92f86112b33ff62/cryptography-46.0.3.tar.gz", hash = "sha256:a8b17438104fed022ce745b362294d9ce35b4c2e45c1d958ad4a4b019285f4a1", size = 749258, upload-time = "2025-10-15T23:18:31.74Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/60/04/ee2a9e8542e4fa2773b81771ff8349ff19cdd56b7258a0cc442639052edb/cryptography-46.0.5.tar.gz", hash = "sha256:abace499247268e3757271b2f1e244b36b06f8515cf27c4d49468fc9eb16e93d", size = 750064, upload-time = "2026-02-10T19:18:38.255Z" }
 wheels = [
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 ]
 
 [[package]]

libs/prebuilt/langgraph/prebuilt/chat_agent_executor.py

@@ -308,7 +308,13 @@ def create_react_agent(
 ) -> CompiledStateGraph:
     """Creates an agent graph that calls tools in a loop until a stopping condition is met.
 
-    For more details on using `create_react_agent`, visit [Agents](https://langchain-ai.github.io/langgraph/agents/overview/) documentation.
+    !!! warning
+
+        This function is deprecated in favor of
+        [`create_agent`][langchain.agents.create_agent] from the `langchain`
+        package, which provides an equivalent agent factory with a flexible
+        middleware system. For migration guidance, see
+        [Migrating from LangGraph v0](https://docs.langchain.com/oss/python/migrate/langgraph-v1).
 
     Args:
         model: The language model for the agent. Supports static and dynamic

libs/prebuilt/langgraph/prebuilt/tool_node.py

@@ -922,7 +922,7 @@ class ToolNode(RunnableCallable):
             raise TypeError(msg)
 
         # Inject state, store, and runtime right before invocation
-        injected_call = self._inject_tool_args(call, request.runtime)
+        injected_call = self._inject_tool_args(call, request.runtime, tool)
         call_args = {**injected_call, "type": "tool_call"}
 
         try:
@@ -1075,7 +1075,7 @@ class ToolNode(RunnableCallable):
             raise TypeError(msg)
 
         # Inject state, store, and runtime right before invocation
-        injected_call = self._inject_tool_args(call, request.runtime)
+        injected_call = self._inject_tool_args(call, request.runtime, tool)
         call_args = {**injected_call, "type": "tool_call"}
 
         try:
@@ -1281,6 +1281,7 @@ class ToolNode(RunnableCallable):
         self,
         tool_call: ToolCall,
         tool_runtime: ToolRuntime,
+        tool: BaseTool | None = None,
     ) -> ToolCall:
         """Inject graph state, store, and runtime into tool call arguments.
 
@@ -1299,6 +1300,9 @@ class ToolNode(RunnableCallable):
                 Must contain 'name', 'args', 'id', and 'type' fields.
             tool_runtime: The ToolRuntime instance containing all runtime context
                 (state, config, store, context, stream_writer) to inject into tools.
+            tool: Optional tool instance. When provided, allows injection for
+                dynamically registered tools that are not in self.tools_by_name
+                (e.g., tools added via middleware's wrap_tool_call).
 
         Returns:
             A new ToolCall dictionary with the same structure as the input but with
@@ -1312,10 +1316,12 @@ class ToolNode(RunnableCallable):
             This method is called automatically during tool execution. It should not
             be called from outside the `ToolNode`.
         """
-        if tool_call["name"] not in self.tools_by_name:
-            return tool_call
-
         injected = self._injected_args.get(tool_call["name"])
+        if not injected and tool is not None:
+            # For dynamically registered tools (e.g., added via middleware's
+            # wrap_tool_call), compute injected args on-the-fly since they
+            # were not present during ToolNode initialization.
+            injected = _get_all_injected_args(tool)
         if not injected:
             return tool_call
 

libs/prebuilt/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "langgraph-prebuilt"
-version = "1.0.7"
+version = "1.0.8"
 description = "Library with high-level APIs for creating and executing LangGraph agents and tools."
 authors = []
 requires-python = ">=3.10"

libs/prebuilt/tests/test_tool_node.py

@@ -1902,3 +1902,109 @@ async def test_tool_node_tool_runtime_generic() -> None:
     assert tool_message.type == "tool"
     assert tool_message.content == "test_info"
     assert tool_message.tool_call_id == "call_1"
+
+
+def test_tool_node_inject_runtime_dynamic_tool_via_wrap_tool_call() -> None:
+    """Test that ToolRuntime is injected for dynamically registered tools.
+
+    Regression test for https://github.com/langchain-ai/langchain/issues/35305.
+    When a tool is dynamically provided via wrap_tool_call (not registered at
+    ToolNode init time), ToolRuntime should still be injected into the tool.
+    """
+
+    @dec_tool
+    def static_tool(x: int) -> str:
+        """A static tool registered at init."""
+        return f"static: {x}"
+
+    @dec_tool
+    def dynamic_tool_with_runtime(x: int, runtime: ToolRuntime) -> str:
+        """A dynamic tool that needs ToolRuntime injection."""
+        return f"dynamic: x={x}, tool_call_id={runtime.tool_call_id}"
+
+    def wrap_tool_call(request, execute):
+        """Middleware that swaps in a dynamic tool."""
+        if request.tool_call["name"] == "dynamic_tool_with_runtime":
+            # Override tool to the dynamic one (not registered at init)
+            new_request = request.override(tool=dynamic_tool_with_runtime)
+            return execute(new_request)
+        return execute(request)
+
+    # ToolNode only knows about static_tool at init time
+    tool_node = ToolNode(
+        [static_tool],
+        wrap_tool_call=wrap_tool_call,
+    )
+
+    # Verify the dynamic tool is NOT in the tool node's registered tools
+    assert "dynamic_tool_with_runtime" not in tool_node.tools_by_name
+
+    # Call the dynamic tool
+    tool_call = {
+        "name": "dynamic_tool_with_runtime",
+        "args": {"x": 42},
+        "id": "call_dynamic_1",
+        "type": "tool_call",
+    }
+    msg = AIMessage("", tool_calls=[tool_call])
+    result = tool_node.invoke(
+        {"messages": [msg]},
+        config=_create_config_with_runtime(),
+    )
+
+    # ToolRuntime should be injected and the tool should execute successfully
+    tool_message = result["messages"][-1]
+    assert tool_message.content == "dynamic: x=42, tool_call_id=call_dynamic_1"
+    assert tool_message.tool_call_id == "call_dynamic_1"
+
+
+async def test_tool_node_inject_runtime_dynamic_tool_via_wrap_tool_call_async() -> None:
+    """Test that ToolRuntime is injected for dynamically registered tools (async).
+
+    Async version of the regression test for
+    https://github.com/langchain-ai/langchain/issues/35305.
+    """
+
+    @dec_tool
+    def static_tool(x: int) -> str:
+        """A static tool registered at init."""
+        return f"static: {x}"
+
+    @dec_tool
+    async def dynamic_tool_with_runtime(x: int, runtime: ToolRuntime) -> str:
+        """A dynamic async tool that needs ToolRuntime injection."""
+        return f"dynamic: x={x}, tool_call_id={runtime.tool_call_id}"
+
+    async def awrap_tool_call(request, execute):
+        """Async middleware that swaps in a dynamic tool."""
+        if request.tool_call["name"] == "dynamic_tool_with_runtime":
+            new_request = request.override(tool=dynamic_tool_with_runtime)
+            return await execute(new_request)
+        return await execute(request)
+
+    # ToolNode only knows about static_tool at init time
+    tool_node = ToolNode(
+        [static_tool],
+        awrap_tool_call=awrap_tool_call,
+    )
+
+    # Verify the dynamic tool is NOT in the tool node's registered tools
+    assert "dynamic_tool_with_runtime" not in tool_node.tools_by_name
+
+    # Call the dynamic tool
+    tool_call = {
+        "name": "dynamic_tool_with_runtime",
+        "args": {"x": 42},
+        "id": "call_dynamic_2",
+        "type": "tool_call",
+    }
+    msg = AIMessage("", tool_calls=[tool_call])
+    result = await tool_node.ainvoke(
+        {"messages": [msg]},
+        config=_create_config_with_runtime(),
+    )
+
+    # ToolRuntime should be injected and the tool should execute successfully
+    tool_message = result["messages"][-1]
+    assert tool_message.content == "dynamic: x=42, tool_call_id=call_dynamic_2"
+    assert tool_message.tool_call_id == "call_dynamic_2"

libs/prebuilt/uv.lock

@@ -249,7 +249,7 @@ wheels = [
 
 [[package]]
 name = "langchain-core"
-version = "1.2.7"
+version = "1.2.13"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "jsonpatch" },
@@ -261,14 +261,14 @@ dependencies = [
     { name = "typing-extensions" },
     { name = "uuid-utils" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/a2/0e/664d8d81b3493e09cbab72448d2f9d693d1fa5aa2bcc488602203a9b6da0/langchain_core-1.2.7.tar.gz", hash = "sha256:e1460639f96c352b4a41c375f25aeb8d16ffc1769499fb1c20503aad59305ced", size = 837039, upload-time = "2026-01-09T17:44:25.505Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/fb/bb/c501ca60556c11ac80d1454bdcac63cb33583ce4e64fc4535ad5a7d5c6ba/langchain_core-1.2.13.tar.gz", hash = "sha256:d2773d0d0130a356378db9a858cfeef64c3d64bc03722f1d4d6c40eb46fdf01b", size = 831612, upload-time = "2026-02-15T07:45:57.014Z" }
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/12/ab/60fd69e5d55f67d422baefddaaca523c42cd7510ab6aeb17db6ae57fb107/langchain_core-1.2.13-py3-none-any.whl", hash = "sha256:b31823e28d3eff1e237096d0bd3bf80c6f9624eb471a9496dbfbd427779f8d82", size = 500485, upload-time = "2026-02-15T07:45:55.422Z" },
 ]
 
 [[package]]
 name = "langgraph"
-version = "1.0.7"
+version = "1.0.9"
 source = { editable = "../langgraph" }
 dependencies = [
     { name = "langchain-core" },
@@ -317,7 +317,7 @@ dev = [
     { name = "ruff" },
     { name = "syrupy" },
     { name = "types-requests" },
-    { name = "uvloop", specifier = "==0.21.0b1" },
+    { name = "uvloop", specifier = "==0.22.1" },
 ]
 lint = [
     { name = "mypy" },
@@ -347,7 +347,7 @@ test = [
     { name = "pytest-xdist", extras = ["psutil"] },
     { name = "redis" },
     { name = "syrupy" },
-    { name = "uvloop", specifier = "==0.21.0b1" },
+    { name = "uvloop", specifier = "==0.22.1" },
 ]
 
 [[package]]
@@ -411,7 +411,7 @@ dependencies = [
 [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" },
 ]
@@ -489,7 +489,7 @@ test = [
 
 [[package]]
 name = "langgraph-prebuilt"
-version = "1.0.7"
+version = "1.0.8"
 source = { editable = "." }
 dependencies = [
     { name = "langchain-core" },
@@ -585,28 +585,29 @@ dependencies = [
 [package.metadata]
 requires-dist = [
     { name = "httpx", specifier = ">=0.25.2" },
-    { name = "orjson", specifier = ">=3.10.1" },
+    { name = "orjson", specifier = ">=3.11.5" },
 ]
 
 [package.metadata.requires-dev]
 dev = [
     { name = "codespell" },
-    { name = "mypy", specifier = "==1.19.0" },
+    { name = "langgraph", editable = "../langgraph" },
+    { name = "mypy", specifier = "==1.19.1" },
     { name = "pydantic", specifier = ">=2.12.4" },
     { name = "pytest" },
     { name = "pytest-asyncio" },
     { name = "pytest-mock" },
     { name = "pytest-watch" },
-    { name = "ruff", specifier = "==0.14.11" },
+    { name = "ruff", specifier = "==0.15.1" },
     { name = "starlette" },
-    { name = "ty", specifier = "==0.0.1a27" },
+    { name = "ty", specifier = "==0.0.17" },
 ]
 lint = [
     { name = "codespell" },
-    { name = "mypy", specifier = "==1.19.0" },
-    { name = "ruff", specifier = "==0.14.11" },
+    { name = "mypy", specifier = "==1.19.1" },
+    { name = "ruff", specifier = "==0.15.1" },
     { name = "starlette" },
-    { name = "ty", specifier = "==0.0.1a27" },
+    { name = "ty", specifier = "==0.0.17" },
 ]
 test = [
     { name = "pytest" },
@@ -1304,28 +1305,27 @@ wheels = [
 
 [[package]]
 name = "ruff"
-version = "0.14.13"
+version = "0.15.1"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/50/0a/1914efb7903174b381ee2ffeebb4253e729de57f114e63595114c8ca451f/ruff-0.14.13.tar.gz", hash = "sha256:83cd6c0763190784b99650a20fec7633c59f6ebe41c5cc9d45ee42749563ad47", size = 6059504, upload-time = "2026-01-15T20:15:16.918Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/04/dc/4e6ac71b511b141cf626357a3946679abeba4cf67bc7cc5a17920f31e10d/ruff-0.15.1.tar.gz", hash = "sha256:c590fe13fb57c97141ae975c03a1aedb3d3156030cabd740d6ff0b0d601e203f", size = 4540855, upload-time = "2026-02-12T23:09:09.998Z" }
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 [[package]]
 name = "syrupy"
-version = "5.0.0"
+version = "5.1.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "pytest" },
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+sdist = { url = "https://files.pythonhosted.org/packages/2e/b0/24bca682d6a6337854be37f242d116cceeda9942571d5804c44bc1bdd427/syrupy-5.1.0.tar.gz", hash = "sha256:df543c7aa50d3cf1246e83d58fe490afe5f7dab7b41e74ecc0d8d23ae19bd4b8", size = 50495, upload-time = "2026-01-25T14:53:06.2Z" }
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libs/sdk-py/langgraph_sdk/__init__.py

@@ -3,6 +3,6 @@ from langgraph_sdk.client import get_client, get_sync_client
 from langgraph_sdk.encryption import Encryption
 from langgraph_sdk.encryption.types import EncryptionContext
 
-__version__ = "0.3.4"
+__version__ = "0.3.7"
 
 __all__ = ["Auth", "Encryption", "EncryptionContext", "get_client", "get_sync_client"]

libs/sdk-py/langgraph_sdk/_async/__init__.py

@@ -0,0 +1,20 @@
+"""Async client exports."""
+
+from langgraph_sdk._async.assistants import AssistantsClient
+from langgraph_sdk._async.client import LangGraphClient, get_client
+from langgraph_sdk._async.cron import CronClient
+from langgraph_sdk._async.http import HttpClient
+from langgraph_sdk._async.runs import RunsClient
+from langgraph_sdk._async.store import StoreClient
+from langgraph_sdk._async.threads import ThreadsClient
+
+__all__ = [
+    "AssistantsClient",
+    "CronClient",
+    "HttpClient",
+    "LangGraphClient",
+    "RunsClient",
+    "StoreClient",
+    "ThreadsClient",
+    "get_client",
+]

libs/sdk-py/langgraph_sdk/_async/assistants.py

@@ -0,0 +1,733 @@
+"""Async client for managing assistants in LangGraph."""
+
+from __future__ import annotations
+
+from collections.abc import Mapping
+from typing import Any, Literal, cast, overload
+
+import httpx
+
+from langgraph_sdk._async.http import HttpClient
+from langgraph_sdk.schema import (
+    Assistant,
+    AssistantSelectField,
+    AssistantSortBy,
+    AssistantsSearchResponse,
+    AssistantVersion,
+    Config,
+    Context,
+    GraphSchema,
+    Json,
+    OnConflictBehavior,
+    QueryParamTypes,
+    SortOrder,
+    Subgraphs,
+)
+
+
+class AssistantsClient:
+    """Client for managing assistants in LangGraph.
+
+    This class provides methods to interact with assistants,
+    which are versioned configurations of your graph.
+
+    ???+ example "Example"
+
+        ```python
+        client = get_client(url="http://localhost:2024")
+        assistant = await client.assistants.get("assistant_id_123")
+        ```
+    """
+
+    def __init__(self, http: HttpClient) -> None:
+        self.http = http
+
+    async def get(
+        self,
+        assistant_id: str,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Assistant:
+        """Get an assistant by ID.
+
+        Args:
+            assistant_id: The ID of the assistant to get.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            Assistant: Assistant Object.
+
+        ???+ example "Example Usage"
+
+            ```python
+            assistant = await client.assistants.get(
+                assistant_id="my_assistant_id"
+            )
+            print(assistant)
+            ```
+
+            ```shell
+            ----------------------------------------------------
+
+            {
+                'assistant_id': 'my_assistant_id',
+                'graph_id': 'agent',
+                'created_at': '2024-06-25T17:10:33.109781+00:00',
+                'updated_at': '2024-06-25T17:10:33.109781+00:00',
+                'config': {},
+                'metadata': {'created_by': 'system'},
+                'version': 1,
+                'name': 'my_assistant'
+            }
+            ```
+        """
+        return await self.http.get(
+            f"/assistants/{assistant_id}", headers=headers, params=params
+        )
+
+    async def get_graph(
+        self,
+        assistant_id: str,
+        *,
+        xray: int | bool = False,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> dict[str, list[dict[str, Any]]]:
+        """Get the graph of an assistant by ID.
+
+        Args:
+            assistant_id: The ID of the assistant to get the graph of.
+            xray: Include graph representation of subgraphs. If an integer value is provided, only subgraphs with a depth less than or equal to the value will be included.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            Graph: The graph information for the assistant in JSON format.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            graph_info = await client.assistants.get_graph(
+                assistant_id="my_assistant_id"
+            )
+            print(graph_info)
+            ```
+
+            ```shell
+
+            --------------------------------------------------------------------------------------------------------------------------
+
+            {
+                'nodes':
+                    [
+                        {'id': '__start__', 'type': 'schema', 'data': '__start__'},
+                        {'id': '__end__', 'type': 'schema', 'data': '__end__'},
+                        {'id': 'agent','type': 'runnable','data': {'id': ['langgraph', 'utils', 'RunnableCallable'],'name': 'agent'}},
+                    ],
+                'edges':
+                    [
+                        {'source': '__start__', 'target': 'agent'},
+                        {'source': 'agent','target': '__end__'}
+                    ]
+            }
+            ```
+
+
+        """
+        query_params = {"xray": xray}
+        if params:
+            query_params.update(params)
+
+        return await self.http.get(
+            f"/assistants/{assistant_id}/graph", params=query_params, headers=headers
+        )
+
+    async def get_schemas(
+        self,
+        assistant_id: str,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> GraphSchema:
+        """Get the schemas of an assistant by ID.
+
+        Args:
+            assistant_id: The ID of the assistant to get the schema of.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            GraphSchema: The graph schema for the assistant.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            schema = await client.assistants.get_schemas(
+                assistant_id="my_assistant_id"
+            )
+            print(schema)
+            ```
+
+            ```shell
+
+            ----------------------------------------------------------------------------------------------------------------------------
+
+            {
+                'graph_id': 'agent',
+                'state_schema':
+                    {
+                        'title': 'LangGraphInput',
+                        '$ref': '#/definitions/AgentState',
+                        'definitions':
+                            {
+                                'BaseMessage':
+                                    {
+                                        'title': 'BaseMessage',
+                                        'description': 'Base abstract Message class. Messages are the inputs and outputs of ChatModels.',
+                                        'type': 'object',
+                                        'properties':
+                                            {
+                                             'content':
+                                                {
+                                                    'title': 'Content',
+                                                    'anyOf': [
+                                                        {'type': 'string'},
+                                                        {'type': 'array','items': {'anyOf': [{'type': 'string'}, {'type': 'object'}]}}
+                                                    ]
+                                                },
+                                            'additional_kwargs':
+                                                {
+                                                    'title': 'Additional Kwargs',
+                                                    'type': 'object'
+                                                },
+                                            'response_metadata':
+                                                {
+                                                    'title': 'Response Metadata',
+                                                    'type': 'object'
+                                                },
+                                            'type':
+                                                {
+                                                    'title': 'Type',
+                                                    'type': 'string'
+                                                },
+                                            'name':
+                                                {
+                                                    'title': 'Name',
+                                                    'type': 'string'
+                                                },
+                                            'id':
+                                                {
+                                                    'title': 'Id',
+                                                    'type': 'string'
+                                                }
+                                            },
+                                        'required': ['content', 'type']
+                                    },
+                                'AgentState':
+                                    {
+                                        'title': 'AgentState',
+                                        'type': 'object',
+                                        'properties':
+                                            {
+                                                'messages':
+                                                    {
+                                                        'title': 'Messages',
+                                                        'type': 'array',
+                                                        'items': {'$ref': '#/definitions/BaseMessage'}
+                                                    }
+                                            },
+                                        'required': ['messages']
+                                    }
+                            }
+                    },
+                'context_schema':
+                    {
+                        'title': 'Context',
+                        'type': 'object',
+                        'properties':
+                            {
+                                'model_name':
+                                    {
+                                        'title': 'Model Name',
+                                        'enum': ['anthropic', 'openai'],
+                                        'type': 'string'
+                                    }
+                            }
+                    }
+            }
+            ```
+
+        """
+        return await self.http.get(
+            f"/assistants/{assistant_id}/schemas", headers=headers, params=params
+        )
+
+    async def get_subgraphs(
+        self,
+        assistant_id: str,
+        namespace: str | None = None,
+        recurse: bool = False,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Subgraphs:
+        """Get the schemas of an assistant by ID.
+
+        Args:
+            assistant_id: The ID of the assistant to get the schema of.
+            namespace: Optional namespace to filter by.
+            recurse: Whether to recursively get subgraphs.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            Subgraphs: The graph schema for the assistant.
+
+        """
+        get_params = {"recurse": recurse}
+        if params:
+            get_params = {**get_params, **dict(params)}
+        if namespace is not None:
+            return await self.http.get(
+                f"/assistants/{assistant_id}/subgraphs/{namespace}",
+                params=get_params,
+                headers=headers,
+            )
+        else:
+            return await self.http.get(
+                f"/assistants/{assistant_id}/subgraphs",
+                params=get_params,
+                headers=headers,
+            )
+
+    async def create(
+        self,
+        graph_id: str | None,
+        config: Config | None = None,
+        *,
+        context: Context | None = None,
+        metadata: Json = None,
+        assistant_id: str | None = None,
+        if_exists: OnConflictBehavior | None = None,
+        name: str | None = None,
+        headers: Mapping[str, str] | None = None,
+        description: str | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Assistant:
+        """Create a new assistant.
+
+        Useful when graph is configurable and you want to create different assistants based on different configurations.
+
+        Args:
+            graph_id: The ID of the graph the assistant should use. The graph ID is normally set in your langgraph.json configuration.
+            config: Configuration to use for the graph.
+            metadata: Metadata to add to assistant.
+            context: Static context to add to the assistant.
+                !!! version-added "Added in version 0.6.0"
+            assistant_id: Assistant ID to use, will default to a random UUID if not provided.
+            if_exists: How to handle duplicate creation. Defaults to 'raise' under the hood.
+                Must be either 'raise' (raise error if duplicate), or 'do_nothing' (return existing assistant).
+            name: The name of the assistant. Defaults to 'Untitled' under the hood.
+            headers: Optional custom headers to include with the request.
+            description: Optional description of the assistant.
+                The description field is available for langgraph-api server version>=0.0.45
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            Assistant: The created assistant.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            assistant = await client.assistants.create(
+                graph_id="agent",
+                context={"model_name": "openai"},
+                metadata={"number":1},
+                assistant_id="my-assistant-id",
+                if_exists="do_nothing",
+                name="my_name"
+            )
+            ```
+        """
+        payload: dict[str, Any] = {
+            "graph_id": graph_id,
+        }
+        if config:
+            payload["config"] = config
+        if context:
+            payload["context"] = context
+        if metadata:
+            payload["metadata"] = metadata
+        if assistant_id:
+            payload["assistant_id"] = assistant_id
+        if if_exists:
+            payload["if_exists"] = if_exists
+        if name:
+            payload["name"] = name
+        if description:
+            payload["description"] = description
+        return await self.http.post(
+            "/assistants", json=payload, headers=headers, params=params
+        )
+
+    async def update(
+        self,
+        assistant_id: str,
+        *,
+        graph_id: str | None = None,
+        config: Config | None = None,
+        context: Context | None = None,
+        metadata: Json = None,
+        name: str | None = None,
+        headers: Mapping[str, str] | None = None,
+        description: str | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Assistant:
+        """Update an assistant.
+
+        Use this to point to a different graph, update the configuration, or change the metadata of an assistant.
+
+        Args:
+            assistant_id: Assistant to update.
+            graph_id: The ID of the graph the assistant should use.
+                The graph ID is normally set in your langgraph.json configuration. If `None`, assistant will keep pointing to same graph.
+            config: Configuration to use for the graph.
+            context: Static context to add to the assistant.
+                !!! version-added "Added in version 0.6.0"
+            metadata: Metadata to merge with existing assistant metadata.
+            name: The new name for the assistant.
+            headers: Optional custom headers to include with the request.
+            description: Optional description of the assistant.
+                The description field is available for langgraph-api server version>=0.0.45
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            The updated assistant.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            assistant = await client.assistants.update(
+                assistant_id='e280dad7-8618-443f-87f1-8e41841c180f',
+                graph_id="other-graph",
+                context={"model_name": "anthropic"},
+                metadata={"number":2}
+            )
+            ```
+
+        """
+        payload: dict[str, Any] = {}
+        if graph_id:
+            payload["graph_id"] = graph_id
+        if config is not None:
+            payload["config"] = config
+        if context is not None:
+            payload["context"] = context
+        if metadata:
+            payload["metadata"] = metadata
+        if name:
+            payload["name"] = name
+        if description:
+            payload["description"] = description
+        return await self.http.patch(
+            f"/assistants/{assistant_id}",
+            json=payload,
+            headers=headers,
+            params=params,
+        )
+
+    async def delete(
+        self,
+        assistant_id: str,
+        *,
+        delete_threads: bool = False,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> None:
+        """Delete an assistant.
+
+        Args:
+            assistant_id: The assistant ID to delete.
+            delete_threads: If true, delete all threads with `metadata.assistant_id`
+                matching this assistant, along with runs and checkpoints belonging to
+                those threads.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            `None`
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            await client.assistants.delete(
+                assistant_id="my_assistant_id"
+            )
+            ```
+
+        """
+        query_params: dict[str, Any] = {}
+        if delete_threads:
+            query_params["delete_threads"] = True
+        if params:
+            query_params.update(params)
+        await self.http.delete(
+            f"/assistants/{assistant_id}",
+            headers=headers,
+            params=query_params or None,
+        )
+
+    @overload
+    async def search(
+        self,
+        *,
+        metadata: Json = None,
+        graph_id: str | None = None,
+        name: str | None = None,
+        limit: int = 10,
+        offset: int = 0,
+        sort_by: AssistantSortBy | None = None,
+        sort_order: SortOrder | None = None,
+        select: list[AssistantSelectField] | None = None,
+        response_format: Literal["object"],
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> AssistantsSearchResponse: ...
+
+    @overload
+    async def search(
+        self,
+        *,
+        metadata: Json = None,
+        graph_id: str | None = None,
+        name: str | None = None,
+        limit: int = 10,
+        offset: int = 0,
+        sort_by: AssistantSortBy | None = None,
+        sort_order: SortOrder | None = None,
+        select: list[AssistantSelectField] | None = None,
+        response_format: Literal["array"] = "array",
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> list[Assistant]: ...
+
+    async def search(
+        self,
+        *,
+        metadata: Json = None,
+        graph_id: str | None = None,
+        name: str | None = None,
+        limit: int = 10,
+        offset: int = 0,
+        sort_by: AssistantSortBy | None = None,
+        sort_order: SortOrder | None = None,
+        select: list[AssistantSelectField] | None = None,
+        response_format: Literal["array", "object"] = "array",
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> AssistantsSearchResponse | list[Assistant]:
+        """Search for assistants.
+
+        Args:
+            metadata: Metadata to filter by. Exact match filter for each KV pair.
+            graph_id: The ID of the graph to filter by.
+                The graph ID is normally set in your langgraph.json configuration.
+            name: The name of the assistant to filter by.
+                The filtering logic will match assistants where 'name' is a substring (case insensitive) of the assistant name.
+            limit: The maximum number of results to return.
+            offset: The number of results to skip.
+            sort_by: The field to sort by.
+            sort_order: The order to sort by.
+            select: Specific assistant fields to include in the response.
+            response_format: Controls the response shape. Use `"array"` (default)
+                to return a bare list of assistants, or `"object"` to return
+                a mapping containing assistants plus pagination metadata.
+                Defaults to "array", though this default will be changed to "object" in a future release.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            A list of assistants (when `response_format="array"`) or a mapping
+            with the assistants and the next pagination cursor (when
+            `response_format="object"`).
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            response = await client.assistants.search(
+                metadata = {"name":"my_name"},
+                graph_id="my_graph_id",
+                limit=5,
+                offset=5,
+                response_format="object"
+            )
+            next_cursor = response["next"]
+            assistants = response["assistants"]
+            ```
+        """
+        if response_format not in ("array", "object"):
+            raise ValueError(
+                f"response_format must be 'array' or 'object', got {response_format!r}"
+            )
+        payload: dict[str, Any] = {
+            "limit": limit,
+            "offset": offset,
+        }
+        if metadata:
+            payload["metadata"] = metadata
+        if graph_id:
+            payload["graph_id"] = graph_id
+        if name:
+            payload["name"] = name
+        if sort_by:
+            payload["sort_by"] = sort_by
+        if sort_order:
+            payload["sort_order"] = sort_order
+        if select:
+            payload["select"] = select
+        next_cursor: str | None = None
+
+        def capture_pagination(response: httpx.Response) -> None:
+            nonlocal next_cursor
+            next_cursor = response.headers.get("X-Pagination-Next")
+
+        assistants = cast(
+            list[Assistant],
+            await self.http.post(
+                "/assistants/search",
+                json=payload,
+                headers=headers,
+                params=params,
+                on_response=capture_pagination if response_format == "object" else None,
+            ),
+        )
+        if response_format == "object":
+            return {"assistants": assistants, "next": next_cursor}
+        return assistants
+
+    async def count(
+        self,
+        *,
+        metadata: Json = None,
+        graph_id: str | None = None,
+        name: str | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> int:
+        """Count assistants matching filters.
+
+        Args:
+            metadata: Metadata to filter by. Exact match for each key/value.
+            graph_id: Optional graph id to filter by.
+            name: Optional name to filter by.
+                The filtering logic will match assistants where 'name' is a substring (case insensitive) of the assistant name.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            int: Number of assistants matching the criteria.
+        """
+        payload: dict[str, Any] = {}
+        if metadata:
+            payload["metadata"] = metadata
+        if graph_id:
+            payload["graph_id"] = graph_id
+        if name:
+            payload["name"] = name
+        return await self.http.post(
+            "/assistants/count", json=payload, headers=headers, params=params
+        )
+
+    async def get_versions(
+        self,
+        assistant_id: str,
+        metadata: Json = None,
+        limit: int = 10,
+        offset: int = 0,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> list[AssistantVersion]:
+        """List all versions of an assistant.
+
+        Args:
+            assistant_id: The assistant ID to get versions for.
+            metadata: Metadata to filter versions by. Exact match filter for each KV pair.
+            limit: The maximum number of versions to return.
+            offset: The number of versions to skip.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            A list of assistant versions.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            assistant_versions = await client.assistants.get_versions(
+                assistant_id="my_assistant_id"
+            )
+            ```
+        """
+
+        payload: dict[str, Any] = {
+            "limit": limit,
+            "offset": offset,
+        }
+        if metadata:
+            payload["metadata"] = metadata
+        return await self.http.post(
+            f"/assistants/{assistant_id}/versions",
+            json=payload,
+            headers=headers,
+            params=params,
+        )
+
+    async def set_latest(
+        self,
+        assistant_id: str,
+        version: int,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Assistant:
+        """Change the version of an assistant.
+
+        Args:
+            assistant_id: The assistant ID to delete.
+            version: The version to change to.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            Assistant Object.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            new_version_assistant = await client.assistants.set_latest(
+                assistant_id="my_assistant_id",
+                version=3
+            )
+            ```
+
+        """
+
+        payload: dict[str, Any] = {"version": version}
+
+        return await self.http.post(
+            f"/assistants/{assistant_id}/latest",
+            json=payload,
+            headers=headers,
+            params=params,
+        )

libs/sdk-py/langgraph_sdk/_async/client.py

@@ -0,0 +1,178 @@
+"""Async LangGraph client."""
+
+from __future__ import annotations
+
+import logging
+import os
+from collections.abc import Mapping
+from types import TracebackType
+
+import httpx
+
+from langgraph_sdk._async.assistants import AssistantsClient
+from langgraph_sdk._async.cron import CronClient
+from langgraph_sdk._async.http import HttpClient
+from langgraph_sdk._async.runs import RunsClient
+from langgraph_sdk._async.store import StoreClient
+from langgraph_sdk._async.threads import ThreadsClient
+from langgraph_sdk._shared.types import TimeoutTypes
+from langgraph_sdk._shared.utilities import (
+    NOT_PROVIDED,
+    _get_headers,
+    _registered_transports,
+    get_asgi_transport,
+)
+
+logger = logging.getLogger(__name__)
+
+
+def get_client(
+    *,
+    url: str | None = None,
+    api_key: str | None = NOT_PROVIDED,
+    headers: Mapping[str, str] | None = None,
+    timeout: TimeoutTypes | None = None,
+) -> LangGraphClient:
+    """Create and configure a LangGraphClient.
+
+    The client provides programmatic access to LangSmith Deployment. It supports
+    both remote servers and local in-process connections (when running inside a LangGraph server).
+
+    Args:
+        url:
+            Base URL of the LangGraph API.
+            - If `None`, the client first attempts an in-process connection via ASGI transport.
+              If that fails, it defers registration until after app initialization. This
+              only works if the client is used from within the Agent server.
+        api_key:
+            API key for authentication. Can be:
+              - A string: use this exact API key
+              - `None`: explicitly skip loading from environment variables
+              - Not provided (default): auto-load from environment in this order:
+                1. `LANGGRAPH_API_KEY`
+                2. `LANGSMITH_API_KEY`
+                3. `LANGCHAIN_API_KEY`
+        headers:
+            Additional HTTP headers to include in requests. Merged with authentication headers.
+        timeout:
+            HTTP timeout configuration. May be:
+              - `httpx.Timeout` instance
+              - float (total seconds)
+              - tuple `(connect, read, write, pool)` in seconds
+            Defaults: connect=5, read=300, write=300, pool=5.
+
+    Returns:
+        LangGraphClient:
+            A top-level client exposing sub-clients for assistants, threads,
+            runs, and cron operations.
+
+    ???+ example "Connect to a remote server:"
+
+        ```python
+        from langgraph_sdk import get_client
+
+        # get top-level LangGraphClient
+        client = get_client(url="http://localhost:8123")
+
+        # example usage: client.<model>.<method_name>()
+        assistants = await client.assistants.get(assistant_id="some_uuid")
+        ```
+
+    ???+ example "Connect in-process to a running LangGraph server:"
+
+        ```python
+        from langgraph_sdk import get_client
+
+        client = get_client(url=None)
+
+        async def my_node(...):
+            subagent_result = await client.runs.wait(
+                thread_id=None,
+                assistant_id="agent",
+                input={"messages": [{"role": "user", "content": "Foo"}]},
+            )
+        ```
+
+    ???+ example "Skip auto-loading API key from environment:"
+
+        ```python
+        from langgraph_sdk import get_client
+
+        # Don't load API key from environment variables
+        client = get_client(
+            url="http://localhost:8123",
+            api_key=None
+        )
+        ```
+    """
+
+    transport: httpx.AsyncBaseTransport | None = None
+    if url is None:
+        url = "http://api"
+        if os.environ.get("__LANGGRAPH_DEFER_LOOPBACK_TRANSPORT") == "true":
+            transport = get_asgi_transport()(app=None, root_path="/noauth")  # type: ignore[invalid-argument-type]
+            _registered_transports.append(transport)
+        else:
+            try:
+                from langgraph_api.server import app  # type: ignore
+
+                transport = get_asgi_transport()(app, root_path="/noauth")
+            except Exception:
+                logger.debug(
+                    "Failed to connect to in-process LangGraph server. Deferring configuration.",
+                    exc_info=True,
+                )
+                transport = get_asgi_transport()(app=None, root_path="/noauth")  # type: ignore[invalid-argument-type]
+                _registered_transports.append(transport)
+
+    if transport is None:
+        transport = httpx.AsyncHTTPTransport(retries=5)
+    client = httpx.AsyncClient(
+        base_url=url,
+        transport=transport,
+        timeout=(
+            httpx.Timeout(timeout)  # type: ignore[arg-type]
+            if timeout is not None
+            else httpx.Timeout(connect=5, read=300, write=300, pool=5)
+        ),
+        headers=_get_headers(api_key, headers),
+    )
+    return LangGraphClient(client)
+
+
+class LangGraphClient:
+    """Top-level client for LangGraph API.
+
+    Attributes:
+        assistants: Manages versioned configuration for your graphs.
+        threads: Handles (potentially) multi-turn interactions, such as conversational threads.
+        runs: Controls individual invocations of the graph.
+        crons: Manages scheduled operations.
+        store: Interfaces with persistent, shared data storage.
+    """
+
+    def __init__(self, client: httpx.AsyncClient) -> None:
+        self.http = HttpClient(client)
+        self.assistants = AssistantsClient(self.http)
+        self.threads = ThreadsClient(self.http)
+        self.runs = RunsClient(self.http)
+        self.crons = CronClient(self.http)
+        self.store = StoreClient(self.http)
+
+    async def __aenter__(self) -> LangGraphClient:
+        """Enter the async context manager."""
+        return self
+
+    async def __aexit__(
+        self,
+        exc_type: type[BaseException] | None,
+        exc_val: BaseException | None,
+        exc_tb: TracebackType | None,
+    ) -> None:
+        """Exit the async context manager."""
+        await self.aclose()
+
+    async def aclose(self) -> None:
+        """Close the underlying HTTP client."""
+        if hasattr(self, "http"):
+            await self.http.client.aclose()

libs/sdk-py/langgraph_sdk/_async/cron.py

@@ -0,0 +1,452 @@
+"""Async client for managing recurrent runs (cron jobs) in LangGraph."""
+
+from __future__ import annotations
+
+from collections.abc import Mapping
+from datetime import datetime
+from typing import Any
+
+from langgraph_sdk._async.http import HttpClient
+from langgraph_sdk.schema import (
+    All,
+    Config,
+    Context,
+    Cron,
+    CronSelectField,
+    CronSortBy,
+    Input,
+    OnCompletionBehavior,
+    QueryParamTypes,
+    Run,
+    SortOrder,
+)
+
+
+class CronClient:
+    """Client for managing recurrent runs (cron jobs) in LangGraph.
+
+    A run is a single invocation of an assistant with optional input, config, and context.
+    This client allows scheduling recurring runs to occur automatically.
+
+    ???+ example "Example Usage"
+
+        ```python
+        client = get_client(url="http://localhost:2024"))
+        cron_job = await client.crons.create_for_thread(
+            thread_id="thread_123",
+            assistant_id="asst_456",
+            schedule="0 9 * * *",
+            input={"message": "Daily update"}
+        )
+        ```
+
+    !!! note "Feature Availability"
+
+        The crons client functionality is not supported on all licenses.
+        Please check the relevant license documentation for the most up-to-date
+        details on feature availability.
+    """
+
+    def __init__(self, http_client: HttpClient) -> None:
+        self.http = http_client
+
+    async def create_for_thread(
+        self,
+        thread_id: str,
+        assistant_id: str,
+        *,
+        schedule: str,
+        input: Input | None = None,
+        metadata: Mapping[str, Any] | None = None,
+        config: Config | None = None,
+        context: Context | None = None,
+        checkpoint_during: bool | None = None,
+        interrupt_before: All | list[str] | None = None,
+        interrupt_after: All | list[str] | None = None,
+        webhook: str | None = None,
+        multitask_strategy: str | None = None,
+        end_time: datetime | None = None,
+        enabled: bool | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Run:
+        """Create a cron job for a thread.
+
+        Args:
+            thread_id: the thread ID to run the cron job on.
+            assistant_id: The assistant ID or graph name to use for the cron job.
+                If using graph name, will default to first assistant created from that graph.
+            schedule: The cron schedule to execute this job on.
+                Schedules are interpreted in UTC.
+            input: The input to the graph.
+            metadata: Metadata to assign to the cron job runs.
+            config: The configuration for the assistant.
+            context: Static context to add to the assistant.
+                !!! version-added "Added in version 0.6.0"
+            checkpoint_during: Whether to checkpoint during the run (or only at the end/interruption).
+            interrupt_before: Nodes to interrupt immediately before they get executed.
+
+            interrupt_after: Nodes to Nodes to interrupt immediately after they get executed.
+
+            webhook: Webhook to call after LangGraph API call is done.
+            multitask_strategy: Multitask strategy to use.
+                Must be one of 'reject', 'interrupt', 'rollback', or 'enqueue'.
+            end_time: The time to stop running the cron job. If not provided, the cron job will run indefinitely.
+            enabled: Whether the cron job is enabled or not.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            The cron run.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            cron_run = await client.crons.create_for_thread(
+                thread_id="my-thread-id",
+                assistant_id="agent",
+                schedule="27 15 * * *",
+                input={"messages": [{"role": "user", "content": "hello!"}]},
+                metadata={"name":"my_run"},
+                context={"model_name": "openai"},
+                interrupt_before=["node_to_stop_before_1","node_to_stop_before_2"],
+                interrupt_after=["node_to_stop_after_1","node_to_stop_after_2"],
+                webhook="https://my.fake.webhook.com",
+                multitask_strategy="interrupt",
+                enabled=True,
+            )
+            ```
+        """
+        payload = {
+            "schedule": schedule,
+            "input": input,
+            "config": config,
+            "metadata": metadata,
+            "context": context,
+            "assistant_id": assistant_id,
+            "checkpoint_during": checkpoint_during,
+            "interrupt_before": interrupt_before,
+            "interrupt_after": interrupt_after,
+            "webhook": webhook,
+            "end_time": end_time.isoformat() if end_time else None,
+            "enabled": enabled,
+        }
+        if multitask_strategy:
+            payload["multitask_strategy"] = multitask_strategy
+        payload = {k: v for k, v in payload.items() if v is not None}
+        return await self.http.post(
+            f"/threads/{thread_id}/runs/crons",
+            json=payload,
+            headers=headers,
+            params=params,
+        )
+
+    async def create(
+        self,
+        assistant_id: str,
+        *,
+        schedule: str,
+        input: Input | None = None,
+        metadata: Mapping[str, Any] | None = None,
+        config: Config | None = None,
+        context: Context | None = None,
+        checkpoint_during: bool | None = None,
+        interrupt_before: All | list[str] | None = None,
+        interrupt_after: All | list[str] | None = None,
+        webhook: str | None = None,
+        on_run_completed: OnCompletionBehavior | None = None,
+        multitask_strategy: str | None = None,
+        end_time: datetime | None = None,
+        enabled: bool | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Run:
+        """Create a cron run.
+
+        Args:
+            assistant_id: The assistant ID or graph name to use for the cron job.
+                If using graph name, will default to first assistant created from that graph.
+            schedule: The cron schedule to execute this job on.
+                Schedules are interpreted in UTC.
+            input: The input to the graph.
+            metadata: Metadata to assign to the cron job runs.
+            config: The configuration for the assistant.
+            context: Static context to add to the assistant.
+                !!! version-added "Added in version 0.6.0"
+            checkpoint_during: Whether to checkpoint during the run (or only at the end/interruption).
+            interrupt_before: Nodes to interrupt immediately before they get executed.
+            interrupt_after: Nodes to Nodes to interrupt immediately after they get executed.
+            webhook: Webhook to call after LangGraph API call is done.
+            on_run_completed: What to do with the thread after the run completes.
+                Must be one of 'delete' (default) or 'keep'. 'delete' removes the thread
+                after execution. 'keep' creates a new thread for each execution but does not
+                clean them up. Clients are responsible for cleaning up kept threads.
+            multitask_strategy: Multitask strategy to use.
+                Must be one of 'reject', 'interrupt', 'rollback', or 'enqueue'.
+            end_time: The time to stop running the cron job. If not provided, the cron job will run indefinitely.
+            enabled: Whether the cron job is enabled or not.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            The cron run.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            cron_run = client.crons.create(
+                assistant_id="agent",
+                schedule="27 15 * * *",
+                input={"messages": [{"role": "user", "content": "hello!"}]},
+                metadata={"name":"my_run"},
+                context={"model_name": "openai"},
+                interrupt_before=["node_to_stop_before_1","node_to_stop_before_2"],
+                interrupt_after=["node_to_stop_after_1","node_to_stop_after_2"],
+                webhook="https://my.fake.webhook.com",
+                multitask_strategy="interrupt",
+                enabled=True,
+            )
+            ```
+
+        """
+        payload = {
+            "schedule": schedule,
+            "input": input,
+            "config": config,
+            "metadata": metadata,
+            "context": context,
+            "assistant_id": assistant_id,
+            "checkpoint_during": checkpoint_during,
+            "interrupt_before": interrupt_before,
+            "interrupt_after": interrupt_after,
+            "webhook": webhook,
+            "on_run_completed": on_run_completed,
+            "end_time": end_time.isoformat() if end_time else None,
+            "enabled": enabled,
+        }
+        if multitask_strategy:
+            payload["multitask_strategy"] = multitask_strategy
+        payload = {k: v for k, v in payload.items() if v is not None}
+        return await self.http.post(
+            "/runs/crons", json=payload, headers=headers, params=params
+        )
+
+    async def delete(
+        self,
+        cron_id: str,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> None:
+        """Delete a cron.
+
+        Args:
+            cron_id: The cron ID to delete.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            `None`
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            await client.crons.delete(
+                cron_id="cron_to_delete"
+            )
+            ```
+
+        """
+        await self.http.delete(f"/runs/crons/{cron_id}", headers=headers, params=params)
+
+    async def update(
+        self,
+        cron_id: str,
+        *,
+        schedule: str | None = None,
+        end_time: datetime | None = None,
+        input: Input | None = None,
+        metadata: Mapping[str, Any] | None = None,
+        config: Config | None = None,
+        context: Context | None = None,
+        webhook: str | None = None,
+        interrupt_before: All | list[str] | None = None,
+        interrupt_after: All | list[str] | None = None,
+        on_run_completed: OnCompletionBehavior | None = None,
+        enabled: bool | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Cron:
+        """Update a cron job by ID.
+
+        Args:
+            cron_id: The cron ID to update.
+            schedule: The cron schedule to execute this job on.
+                Schedules are interpreted in UTC.
+            end_time: The end date to stop running the cron.
+            input: The input to the graph.
+            metadata: Metadata to assign to the cron job runs.
+            config: The configuration for the assistant.
+            context: Static context added to the assistant.
+            webhook: Webhook to call after LangGraph API call is done.
+            interrupt_before: Nodes to interrupt immediately before they get executed.
+            interrupt_after: Nodes to interrupt immediately after they get executed.
+            on_run_completed: What to do with the thread after the run completes.
+                Must be one of 'delete' or 'keep'. 'delete' removes the thread
+                after execution. 'keep' creates a new thread for each execution but does not
+                clean them up.
+            enabled: Enable or disable the cron job.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            The updated cron job.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            updated_cron = await client.crons.update(
+                cron_id="1ef3cefa-4c09-6926-96d0-3dc97fd5e39b",
+                schedule="0 10 * * *",
+                enabled=False,
+            )
+            ```
+
+        """
+        payload = {
+            "schedule": schedule,
+            "end_time": end_time.isoformat() if end_time else None,
+            "input": input,
+            "metadata": metadata,
+            "config": config,
+            "context": context,
+            "webhook": webhook,
+            "interrupt_before": interrupt_before,
+            "interrupt_after": interrupt_after,
+            "on_run_completed": on_run_completed,
+            "enabled": enabled,
+        }
+        payload = {k: v for k, v in payload.items() if v is not None}
+        return await self.http.patch(
+            f"/runs/crons/{cron_id}",
+            json=payload,
+            headers=headers,
+            params=params,
+        )
+
+    async def search(
+        self,
+        *,
+        assistant_id: str | None = None,
+        thread_id: str | None = None,
+        enabled: bool | None = None,
+        limit: int = 10,
+        offset: int = 0,
+        sort_by: CronSortBy | None = None,
+        sort_order: SortOrder | None = None,
+        select: list[CronSelectField] | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> list[Cron]:
+        """Get a list of cron jobs.
+
+        Args:
+            assistant_id: The assistant ID or graph name to search for.
+            thread_id: the thread ID to search for.
+            enabled: The enabled status to search for.
+            limit: The maximum number of results to return.
+            offset: The number of results to skip.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            The list of cron jobs returned by the search,
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            cron_jobs = await client.crons.search(
+                assistant_id="my_assistant_id",
+                thread_id="my_thread_id",
+                enabled=True,
+                limit=5,
+                offset=5,
+            )
+            print(cron_jobs)
+            ```
+            ```shell
+
+            ----------------------------------------------------------
+
+            [
+                {
+                    'cron_id': '1ef3cefa-4c09-6926-96d0-3dc97fd5e39b',
+                    'assistant_id': 'my_assistant_id',
+                    'thread_id': 'my_thread_id',
+                    'user_id': None,
+                    'payload':
+                        {
+                            'input': {'start_time': ''},
+                            'schedule': '4 * * * *',
+                            'assistant_id': 'my_assistant_id'
+                        },
+                    'schedule': '4 * * * *',
+                    'next_run_date': '2024-07-25T17:04:00+00:00',
+                    'end_time': None,
+                    'created_at': '2024-07-08T06:02:23.073257+00:00',
+                    'updated_at': '2024-07-08T06:02:23.073257+00:00'
+                }
+            ]
+            ```
+
+        """
+        payload = {
+            "assistant_id": assistant_id,
+            "thread_id": thread_id,
+            "enabled": enabled,
+            "limit": limit,
+            "offset": offset,
+        }
+        if sort_by:
+            payload["sort_by"] = sort_by
+        if sort_order:
+            payload["sort_order"] = sort_order
+        if select:
+            payload["select"] = select
+        payload = {k: v for k, v in payload.items() if v is not None}
+        return await self.http.post(
+            "/runs/crons/search", json=payload, headers=headers, params=params
+        )
+
+    async def count(
+        self,
+        *,
+        assistant_id: str | None = None,
+        thread_id: str | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> int:
+        """Count cron jobs matching filters.
+
+        Args:
+            assistant_id: Assistant ID to filter by.
+            thread_id: Thread ID to filter by.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            int: Number of crons matching the criteria.
+        """
+        payload: dict[str, Any] = {}
+        if assistant_id:
+            payload["assistant_id"] = assistant_id
+        if thread_id:
+            payload["thread_id"] = thread_id
+        return await self.http.post(
+            "/runs/crons/count", json=payload, headers=headers, params=params
+        )

libs/sdk-py/langgraph_sdk/_async/http.py

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

libs/sdk-py/langgraph_sdk/_async/store.py

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

libs/sdk-py/langgraph_sdk/_async/threads.py

@@ -0,0 +1,722 @@
+"""Async client for managing threads in LangGraph."""
+
+from __future__ import annotations
+
+from collections.abc import AsyncIterator, Mapping, Sequence
+from typing import Any
+
+from langgraph_sdk._async.http import HttpClient
+from langgraph_sdk.schema import (
+    Checkpoint,
+    Json,
+    OnConflictBehavior,
+    PruneStrategy,
+    QueryParamTypes,
+    SortOrder,
+    StreamPart,
+    Thread,
+    ThreadSelectField,
+    ThreadSortBy,
+    ThreadState,
+    ThreadStatus,
+    ThreadStreamMode,
+    ThreadUpdateStateResponse,
+)
+
+
+class ThreadsClient:
+    """Client for managing threads in LangGraph.
+
+    A thread maintains the state of a graph across multiple interactions/invocations (aka runs).
+    It accumulates and persists the graph's state, allowing for continuity between separate
+    invocations of the graph.
+
+    ???+ example "Example"
+
+        ```python
+        client = get_client(url="http://localhost:2024"))
+        new_thread = await client.threads.create(metadata={"user_id": "123"})
+        ```
+    """
+
+    def __init__(self, http: HttpClient) -> None:
+        self.http = http
+
+    async def get(
+        self,
+        thread_id: str,
+        *,
+        include: Sequence[str] | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Thread:
+        """Get a thread by ID.
+
+        Args:
+            thread_id: The ID of the thread to get.
+            include: Additional fields to include in the response.
+                Supported values: `"ttl"`.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            Thread object.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            thread = await client.threads.get(
+                thread_id="my_thread_id"
+            )
+            print(thread)
+            ```
+
+            ```shell
+            -----------------------------------------------------
+
+            {
+                'thread_id': 'my_thread_id',
+                'created_at': '2024-07-18T18:35:15.540834+00:00',
+                'updated_at': '2024-07-18T18:35:15.540834+00:00',
+                'metadata': {'graph_id': 'agent'}
+            }
+            ```
+
+        """
+        query_params: dict[str, Any] = {}
+        if include:
+            query_params["include"] = ",".join(include)
+        if params:
+            query_params.update(params)
+        return await self.http.get(
+            f"/threads/{thread_id}",
+            headers=headers,
+            params=query_params or None,
+        )
+
+    async def create(
+        self,
+        *,
+        metadata: Json = None,
+        thread_id: str | None = None,
+        if_exists: OnConflictBehavior | None = None,
+        supersteps: Sequence[dict[str, Sequence[dict[str, Any]]]] | None = None,
+        graph_id: str | None = None,
+        ttl: int | Mapping[str, Any] | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Thread:
+        """Create a new thread.
+
+        Args:
+            metadata: Metadata to add to thread.
+            thread_id: ID of thread.
+                If `None`, ID will be a randomly generated UUID.
+            if_exists: How to handle duplicate creation. Defaults to 'raise' under the hood.
+                Must be either 'raise' (raise error if duplicate), or 'do_nothing' (return existing thread).
+            supersteps: Apply a list of supersteps when creating a thread, each containing a sequence of updates.
+                Each update has `values` or `command` and `as_node`. Used for copying a thread between deployments.
+            graph_id: Optional graph ID to associate with the thread.
+            ttl: Optional time-to-live in minutes for the thread. You can pass an
+                integer (minutes) or a mapping with keys `ttl` and optional
+                `strategy` (defaults to "delete").
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            The created thread.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            thread = await client.threads.create(
+                metadata={"number":1},
+                thread_id="my-thread-id",
+                if_exists="raise"
+            )
+            ```
+        """
+        payload: dict[str, Any] = {}
+        if thread_id:
+            payload["thread_id"] = thread_id
+        if metadata or graph_id:
+            payload["metadata"] = {
+                **(metadata or {}),
+                **({"graph_id": graph_id} if graph_id else {}),
+            }
+        if if_exists:
+            payload["if_exists"] = if_exists
+        if supersteps:
+            payload["supersteps"] = [
+                {
+                    "updates": [
+                        {
+                            "values": u["values"],
+                            "command": u.get("command"),
+                            "as_node": u["as_node"],
+                        }
+                        for u in s["updates"]
+                    ]
+                }
+                for s in supersteps
+            ]
+        if ttl is not None:
+            if isinstance(ttl, (int, float)):
+                payload["ttl"] = {"ttl": ttl, "strategy": "delete"}
+            else:
+                payload["ttl"] = ttl
+
+        return await self.http.post(
+            "/threads", json=payload, headers=headers, params=params
+        )
+
+    async def update(
+        self,
+        thread_id: str,
+        *,
+        metadata: Mapping[str, Any],
+        ttl: int | Mapping[str, Any] | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Thread:
+        """Update a thread.
+
+        Args:
+            thread_id: ID of thread to update.
+            metadata: Metadata to merge with existing thread metadata.
+            ttl: Optional time-to-live in minutes for the thread. You can pass an
+                integer (minutes) or a mapping with keys `ttl` and optional
+                `strategy` (defaults to "delete").
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            The created thread.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            thread = await client.threads.update(
+                thread_id="my-thread-id",
+                metadata={"number":1},
+                ttl=43_200,
+            )
+            ```
+        """
+        payload: dict[str, Any] = {"metadata": metadata}
+        if ttl is not None:
+            if isinstance(ttl, (int, float)):
+                payload["ttl"] = {"ttl": ttl, "strategy": "delete"}
+            else:
+                payload["ttl"] = ttl
+        return await self.http.patch(
+            f"/threads/{thread_id}",
+            json=payload,
+            headers=headers,
+            params=params,
+        )
+
+    async def delete(
+        self,
+        thread_id: str,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> None:
+        """Delete a thread.
+
+        Args:
+            thread_id: The ID of the thread to delete.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            `None`
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost2024)
+            await client.threads.delete(
+                thread_id="my_thread_id"
+            )
+            ```
+
+        """
+        await self.http.delete(f"/threads/{thread_id}", headers=headers, params=params)
+
+    async def search(
+        self,
+        *,
+        metadata: Json = None,
+        values: Json = None,
+        ids: Sequence[str] | None = None,
+        status: ThreadStatus | None = None,
+        limit: int = 10,
+        offset: int = 0,
+        sort_by: ThreadSortBy | None = None,
+        sort_order: SortOrder | None = None,
+        select: list[ThreadSelectField] | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> list[Thread]:
+        """Search for threads.
+
+        Args:
+            metadata: Thread metadata to filter on.
+            values: State values to filter on.
+            ids: List of thread IDs to filter by.
+            status: Thread status to filter on.
+                Must be one of 'idle', 'busy', 'interrupted' or 'error'.
+            limit: Limit on number of threads to return.
+            offset: Offset in threads table to start search from.
+            sort_by: Sort by field.
+            sort_order: Sort order.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            List of the threads matching the search parameters.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            threads = await client.threads.search(
+                metadata={"number":1},
+                status="interrupted",
+                limit=15,
+                offset=5
+            )
+            ```
+
+        """
+        payload: dict[str, Any] = {
+            "limit": limit,
+            "offset": offset,
+        }
+        if metadata:
+            payload["metadata"] = metadata
+        if values:
+            payload["values"] = values
+        if ids:
+            payload["ids"] = ids
+        if status:
+            payload["status"] = status
+        if sort_by:
+            payload["sort_by"] = sort_by
+        if sort_order:
+            payload["sort_order"] = sort_order
+        if select:
+            payload["select"] = select
+        return await self.http.post(
+            "/threads/search",
+            json=payload,
+            headers=headers,
+            params=params,
+        )
+
+    async def count(
+        self,
+        *,
+        metadata: Json = None,
+        values: Json = None,
+        status: ThreadStatus | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> int:
+        """Count threads matching filters.
+
+        Args:
+            metadata: Thread metadata to filter on.
+            values: State values to filter on.
+            status: Thread status to filter on.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            int: Number of threads matching the criteria.
+        """
+        payload: dict[str, Any] = {}
+        if metadata:
+            payload["metadata"] = metadata
+        if values:
+            payload["values"] = values
+        if status:
+            payload["status"] = status
+        return await self.http.post(
+            "/threads/count", json=payload, headers=headers, params=params
+        )
+
+    async def copy(
+        self,
+        thread_id: str,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> None:
+        """Copy a thread.
+
+        Args:
+            thread_id: The ID of the thread to copy.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            `None`
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024)
+            await client.threads.copy(
+                thread_id="my_thread_id"
+            )
+            ```
+
+        """
+        return await self.http.post(
+            f"/threads/{thread_id}/copy", json=None, headers=headers, params=params
+        )
+
+    async def prune(
+        self,
+        thread_ids: Sequence[str],
+        *,
+        strategy: PruneStrategy = "delete",
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> dict[str, Any]:
+        """Prune threads by ID.
+
+        Args:
+            thread_ids: List of thread IDs to prune.
+            strategy: The prune strategy. `"delete"` removes threads entirely.
+                `"keep_latest"` prunes old checkpoints but keeps threads and their
+                latest state. Defaults to `"delete"`.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            A dict containing `pruned_count` (number of threads pruned).
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024")
+            result = await client.threads.prune(
+                thread_ids=["thread_1", "thread_2"],
+            )
+            print(result)  # {'pruned_count': 2}
+            ```
+
+        """
+        payload: dict[str, Any] = {
+            "thread_ids": thread_ids,
+        }
+        if strategy != "delete":
+            payload["strategy"] = strategy
+        return await self.http.post(
+            "/threads/prune", json=payload, headers=headers, params=params
+        )
+
+    async def get_state(
+        self,
+        thread_id: str,
+        checkpoint: Checkpoint | None = None,
+        checkpoint_id: str | None = None,  # deprecated
+        *,
+        subgraphs: bool = False,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> ThreadState:
+        """Get the state of a thread.
+
+        Args:
+            thread_id: The ID of the thread to get the state of.
+            checkpoint: The checkpoint to get the state of.
+            checkpoint_id: (deprecated) The checkpoint ID to get the state of.
+            subgraphs: Include subgraphs states.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            The thread of the state.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024)
+            thread_state = await client.threads.get_state(
+                thread_id="my_thread_id",
+                checkpoint_id="my_checkpoint_id"
+            )
+            print(thread_state)
+            ```
+
+            ```shell
+            ----------------------------------------------------------------------------------------------------------------------------------------------------------------------
+
+            {
+                'values': {
+                    'messages': [
+                        {
+                            'content': 'how are you?',
+                            'additional_kwargs': {},
+                            'response_metadata': {},
+                            'type': 'human',
+                            'name': None,
+                            'id': 'fe0a5778-cfe9-42ee-b807-0adaa1873c10',
+                            'example': False
+                        },
+                        {
+                            'content': "I'm doing well, thanks for asking! I'm an AI assistant created by Anthropic to be helpful, honest, and harmless.",
+                            'additional_kwargs': {},
+                            'response_metadata': {},
+                            'type': 'ai',
+                            'name': None,
+                            'id': 'run-159b782c-b679-4830-83c6-cef87798fe8b',
+                            'example': False,
+                            'tool_calls': [],
+                            'invalid_tool_calls': [],
+                            'usage_metadata': None
+                        }
+                    ]
+                },
+                'next': [],
+                'checkpoint':
+                    {
+                        'thread_id': 'e2496803-ecd5-4e0c-a779-3226296181c2',
+                        'checkpoint_ns': '',
+                        'checkpoint_id': '1ef4a9b8-e6fb-67b1-8001-abd5184439d1'
+                    }
+                'metadata':
+                    {
+                        'step': 1,
+                        'run_id': '1ef4a9b8-d7da-679a-a45a-872054341df2',
+                        'source': 'loop',
+                        'writes':
+                            {
+                                'agent':
+                                    {
+                                        'messages': [
+                                            {
+                                                'id': 'run-159b782c-b679-4830-83c6-cef87798fe8b',
+                                                'name': None,
+                                                'type': 'ai',
+                                                'content': "I'm doing well, thanks for asking! I'm an AI assistant created by Anthropic to be helpful, honest, and harmless.",
+                                                'example': False,
+                                                'tool_calls': [],
+                                                'usage_metadata': None,
+                                                'additional_kwargs': {},
+                                                'response_metadata': {},
+                                                'invalid_tool_calls': []
+                                            }
+                                        ]
+                                    }
+                            },
+                'user_id': None,
+                'graph_id': 'agent',
+                'thread_id': 'e2496803-ecd5-4e0c-a779-3226296181c2',
+                'created_by': 'system',
+                'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca'},
+                'created_at': '2024-07-25T15:35:44.184703+00:00',
+                'parent_config':
+                    {
+                        'thread_id': 'e2496803-ecd5-4e0c-a779-3226296181c2',
+                        'checkpoint_ns': '',
+                        'checkpoint_id': '1ef4a9b8-d80d-6fa7-8000-9300467fad0f'
+                    }
+            }
+            ```
+        """
+        if checkpoint:
+            return await self.http.post(
+                f"/threads/{thread_id}/state/checkpoint",
+                json={"checkpoint": checkpoint, "subgraphs": subgraphs},
+                headers=headers,
+                params=params,
+            )
+        elif checkpoint_id:
+            get_params = {"subgraphs": subgraphs}
+            if params:
+                get_params = {**get_params, **dict(params)}
+            return await self.http.get(
+                f"/threads/{thread_id}/state/{checkpoint_id}",
+                params=get_params,
+                headers=headers,
+            )
+        else:
+            get_params = {"subgraphs": subgraphs}
+            if params:
+                get_params = {**get_params, **dict(params)}
+            return await self.http.get(
+                f"/threads/{thread_id}/state",
+                params=get_params,
+                headers=headers,
+            )
+
+    async def update_state(
+        self,
+        thread_id: str,
+        values: dict[str, Any] | Sequence[dict] | None,
+        *,
+        as_node: str | None = None,
+        checkpoint: Checkpoint | None = None,
+        checkpoint_id: str | None = None,  # deprecated
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> ThreadUpdateStateResponse:
+        """Update the state of a thread.
+
+        Args:
+            thread_id: The ID of the thread to update.
+            values: The values to update the state with.
+            as_node: Update the state as if this node had just executed.
+            checkpoint: The checkpoint to update the state of.
+            checkpoint_id: (deprecated) The checkpoint ID to update the state of.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            Response after updating a thread's state.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024)
+            response = await client.threads.update_state(
+                thread_id="my_thread_id",
+                values={"messages":[{"role": "user", "content": "hello!"}]},
+                as_node="my_node",
+            )
+            print(response)
+            ```
+            ```shell
+
+            ----------------------------------------------------------------------------------------------------------------------------------------------------------------------
+
+            {
+                'checkpoint': {
+                    'thread_id': 'e2496803-ecd5-4e0c-a779-3226296181c2',
+                    'checkpoint_ns': '',
+                    'checkpoint_id': '1ef4a9b8-e6fb-67b1-8001-abd5184439d1',
+                    'checkpoint_map': {}
+                }
+            }
+            ```
+        """
+        payload: dict[str, Any] = {
+            "values": values,
+        }
+        if checkpoint_id:
+            payload["checkpoint_id"] = checkpoint_id
+        if checkpoint:
+            payload["checkpoint"] = checkpoint
+        if as_node:
+            payload["as_node"] = as_node
+        return await self.http.post(
+            f"/threads/{thread_id}/state", json=payload, headers=headers, params=params
+        )
+
+    async def get_history(
+        self,
+        thread_id: str,
+        *,
+        limit: int = 10,
+        before: str | Checkpoint | None = None,
+        metadata: Mapping[str, Any] | None = None,
+        checkpoint: Checkpoint | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> list[ThreadState]:
+        """Get the state history of a thread.
+
+        Args:
+            thread_id: The ID of the thread to get the state history for.
+            checkpoint: Return states for this subgraph. If empty defaults to root.
+            limit: The maximum number of states to return.
+            before: Return states before this checkpoint.
+            metadata: Filter states by metadata key-value pairs.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            The state history of the thread.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_client(url="http://localhost:2024)
+            thread_state = await client.threads.get_history(
+                thread_id="my_thread_id",
+                limit=5,
+            )
+            ```
+
+        """
+        payload: dict[str, Any] = {
+            "limit": limit,
+        }
+        if before:
+            payload["before"] = before
+        if metadata:
+            payload["metadata"] = metadata
+        if checkpoint:
+            payload["checkpoint"] = checkpoint
+        return await self.http.post(
+            f"/threads/{thread_id}/history",
+            json=payload,
+            headers=headers,
+            params=params,
+        )
+
+    async def join_stream(
+        self,
+        thread_id: str,
+        *,
+        last_event_id: str | None = None,
+        stream_mode: ThreadStreamMode | Sequence[ThreadStreamMode] = "run_modes",
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> AsyncIterator[StreamPart]:
+        """Get a stream of events for a thread.
+
+        Args:
+            thread_id: The ID of the thread to get the stream for.
+            last_event_id: The ID of the last event to get.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            An iterator of stream parts.
+
+        ???+ example "Example Usage"
+
+            ```python
+
+            for chunk in client.threads.join_stream(
+                thread_id="my_thread_id",
+                last_event_id="my_event_id",
+            ):
+                print(chunk)
+            ```
+
+        """
+        query_params = {
+            "stream_mode": stream_mode,
+        }
+        if params:
+            query_params.update(params)
+        return self.http.stream(
+            f"/threads/{thread_id}/stream",
+            "GET",
+            headers={
+                **({"Last-Event-ID": last_event_id} if last_event_id else {}),
+                **(headers or {}),
+            },
+            params=query_params,
+        )

libs/sdk-py/langgraph_sdk/_shared/__init__.py

@@ -0,0 +1 @@
+"""Shared utilities for async and sync clients."""

libs/sdk-py/langgraph_sdk/_shared/types.py

@@ -0,0 +1,10 @@
+"""Type aliases and constants."""
+
+from __future__ import annotations
+
+TimeoutTypes = (
+    None
+    | float
+    | tuple[float | None, float | None]
+    | tuple[float | None, float | None, float | None, float | None]
+)

libs/sdk-py/langgraph_sdk/_shared/utilities.py

@@ -0,0 +1,131 @@
+"""Shared utility functions for async and sync clients."""
+
+from __future__ import annotations
+
+import functools
+import os
+import re
+from collections.abc import Mapping
+from typing import Any, cast
+
+import httpx
+
+import langgraph_sdk
+from langgraph_sdk.schema import RunCreateMetadata
+
+RESERVED_HEADERS = ("x-api-key",)
+
+NOT_PROVIDED = cast(None, object())
+
+
+def _get_api_key(api_key: str | None = NOT_PROVIDED) -> str | None:
+    """Get the API key from the environment.
+    Precedence:
+        1. explicit string argument
+        2. LANGGRAPH_API_KEY (if api_key not provided)
+        3. LANGSMITH_API_KEY (if api_key not provided)
+        4. LANGCHAIN_API_KEY (if api_key not provided)
+
+    Args:
+        api_key: The API key to use. Can be:
+            - A string: use this exact API key
+            - None: explicitly skip loading from environment
+            - NOT_PROVIDED (default): auto-load from environment variables
+    """
+    if isinstance(api_key, str):
+        return api_key
+    if api_key is NOT_PROVIDED:
+        # api_key is not explicitly provided, try to load from environment
+        for prefix in ["LANGGRAPH", "LANGSMITH", "LANGCHAIN"]:
+            if env := os.getenv(f"{prefix}_API_KEY"):
+                return env.strip().strip('"').strip("'")
+    # api_key is explicitly None, don't load from environment
+    return None
+
+
+def _get_headers(
+    api_key: str | None,
+    custom_headers: Mapping[str, str] | None,
+) -> dict[str, str]:
+    """Combine api_key and custom user-provided headers."""
+    custom_headers = custom_headers or {}
+    for header in RESERVED_HEADERS:
+        if header in custom_headers:
+            raise ValueError(f"Cannot set reserved header '{header}'")
+
+    headers = {
+        "User-Agent": f"langgraph-sdk-py/{langgraph_sdk.__version__}",
+        **custom_headers,
+    }
+    resolved_api_key = _get_api_key(api_key)
+    if resolved_api_key:
+        headers["x-api-key"] = resolved_api_key
+
+    return headers
+
+
+def _orjson_default(obj: Any) -> Any:
+    is_class = isinstance(obj, type)
+    if hasattr(obj, "model_dump") and callable(obj.model_dump):
+        if is_class:
+            raise TypeError(
+                f"Cannot JSON-serialize type object: {obj!r}. Did you mean to pass an instance of the object instead?"
+                f"\nReceived type: {obj!r}"
+            )
+        return obj.model_dump()
+    elif hasattr(obj, "dict") and callable(obj.dict):
+        if is_class:
+            raise TypeError(
+                f"Cannot JSON-serialize type object: {obj!r}. Did you mean to pass an instance of the object instead?"
+                f"\nReceived type: {obj!r}"
+            )
+        return obj.dict()
+    elif isinstance(obj, (set, frozenset)):
+        return list(obj)
+    else:
+        raise TypeError(f"Object of type {type(obj)} is not JSON serializable")
+
+
+# Compiled regex pattern for extracting run metadata from Content-Location header
+_RUN_METADATA_PATTERN = re.compile(
+    r"(\/threads\/(?P<thread_id>.+))?\/runs\/(?P<run_id>.+)"
+)
+
+
+def _get_run_metadata_from_response(
+    response: httpx.Response,
+) -> RunCreateMetadata | None:
+    """Extract run metadata from the response headers."""
+    if (content_location := response.headers.get("Content-Location")) and (
+        match := _RUN_METADATA_PATTERN.search(content_location)
+    ):
+        return RunCreateMetadata(
+            run_id=match.group("run_id"),
+            thread_id=match.group("thread_id") or None,
+        )
+
+    return None
+
+
+def _provided_vals(d: Mapping[str, Any]) -> dict[str, Any]:
+    return {k: v for k, v in d.items() if v is not None}
+
+
+_registered_transports: list[httpx.ASGITransport] = []
+
+
+# Do not move; this is used in the server.
+def configure_loopback_transports(app: Any) -> None:
+    for transport in _registered_transports:
+        transport.app = app
+
+
+@functools.lru_cache(maxsize=1)
+def get_asgi_transport() -> type[httpx.ASGITransport]:
+    try:
+        from langgraph_api import asgi_transport  # type: ignore[unresolved-import]
+
+        return asgi_transport.ASGITransport
+    except ImportError:
+        # Older versions of the server
+        return httpx.ASGITransport

libs/sdk-py/langgraph_sdk/_sync/__init__.py

@@ -0,0 +1,20 @@
+"""Sync client exports."""
+
+from langgraph_sdk._sync.assistants import SyncAssistantsClient
+from langgraph_sdk._sync.client import SyncLangGraphClient, get_sync_client
+from langgraph_sdk._sync.cron import SyncCronClient
+from langgraph_sdk._sync.http import SyncHttpClient
+from langgraph_sdk._sync.runs import SyncRunsClient
+from langgraph_sdk._sync.store import SyncStoreClient
+from langgraph_sdk._sync.threads import SyncThreadsClient
+
+__all__ = [
+    "SyncAssistantsClient",
+    "SyncCronClient",
+    "SyncHttpClient",
+    "SyncLangGraphClient",
+    "SyncRunsClient",
+    "SyncStoreClient",
+    "SyncThreadsClient",
+    "get_sync_client",
+]

libs/sdk-py/langgraph_sdk/_sync/assistants.py

@@ -0,0 +1,731 @@
+"""Synchronous client for managing assistants in LangGraph."""
+
+from __future__ import annotations
+
+from collections.abc import Mapping
+from typing import Any, Literal, cast, overload
+
+import httpx
+
+from langgraph_sdk._sync.http import SyncHttpClient
+from langgraph_sdk.schema import (
+    Assistant,
+    AssistantSelectField,
+    AssistantSortBy,
+    AssistantsSearchResponse,
+    AssistantVersion,
+    Config,
+    Context,
+    GraphSchema,
+    Json,
+    OnConflictBehavior,
+    QueryParamTypes,
+    SortOrder,
+    Subgraphs,
+)
+
+
+class SyncAssistantsClient:
+    """Client for managing assistants in LangGraph synchronously.
+
+    This class provides methods to interact with assistants, which are versioned configurations of your graph.
+
+    ???+ example "Example"
+
+        ```python
+        client = get_sync_client(url="http://localhost:2024")
+        assistant = client.assistants.get("assistant_id_123")
+        ```
+    """
+
+    def __init__(self, http: SyncHttpClient) -> None:
+        self.http = http
+
+    def get(
+        self,
+        assistant_id: str,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Assistant:
+        """Get an assistant by ID.
+
+        Args:
+            assistant_id: The ID of the assistant to get OR the name of the graph (to use the default assistant).
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            `Assistant` Object.
+
+        ???+ example "Example Usage"
+
+            ```python
+            assistant = client.assistants.get(
+                assistant_id="my_assistant_id"
+            )
+            print(assistant)
+            ```
+
+            ```shell
+            ----------------------------------------------------
+
+            {
+                'assistant_id': 'my_assistant_id',
+                'graph_id': 'agent',
+                'created_at': '2024-06-25T17:10:33.109781+00:00',
+                'updated_at': '2024-06-25T17:10:33.109781+00:00',
+                'config': {},
+                'context': {},
+                'metadata': {'created_by': 'system'}
+            }
+            ```
+
+        """
+        return self.http.get(
+            f"/assistants/{assistant_id}", headers=headers, params=params
+        )
+
+    def get_graph(
+        self,
+        assistant_id: str,
+        *,
+        xray: int | bool = False,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> dict[str, list[dict[str, Any]]]:
+        """Get the graph of an assistant by ID.
+
+        Args:
+            assistant_id: The ID of the assistant to get the graph of.
+            xray: Include graph representation of subgraphs. If an integer value is provided, only subgraphs with a depth less than or equal to the value will be included.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            The graph information for the assistant in JSON format.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:2024")
+            graph_info = client.assistants.get_graph(
+                assistant_id="my_assistant_id"
+            )
+            print(graph_info)
+
+            --------------------------------------------------------------------------------------------------------------------------
+
+            {
+                'nodes':
+                    [
+                        {'id': '__start__', 'type': 'schema', 'data': '__start__'},
+                        {'id': '__end__', 'type': 'schema', 'data': '__end__'},
+                        {'id': 'agent','type': 'runnable','data': {'id': ['langgraph', 'utils', 'RunnableCallable'],'name': 'agent'}},
+                    ],
+                'edges':
+                    [
+                        {'source': '__start__', 'target': 'agent'},
+                        {'source': 'agent','target': '__end__'}
+                    ]
+            }
+            ```
+
+        """
+        query_params = {"xray": xray}
+        if params:
+            query_params.update(params)
+        return self.http.get(
+            f"/assistants/{assistant_id}/graph", params=query_params, headers=headers
+        )
+
+    def get_schemas(
+        self,
+        assistant_id: str,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> GraphSchema:
+        """Get the schemas of an assistant by ID.
+
+        Args:
+            assistant_id: The ID of the assistant to get the schema of.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            GraphSchema: The graph schema for the assistant.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:2024")
+            schema = client.assistants.get_schemas(
+                assistant_id="my_assistant_id"
+            )
+            print(schema)
+            ```
+            ```shell
+            ----------------------------------------------------------------------------------------------------------------------------
+
+            {
+                'graph_id': 'agent',
+                'state_schema':
+                    {
+                        'title': 'LangGraphInput',
+                        '$ref': '#/definitions/AgentState',
+                        'definitions':
+                            {
+                                'BaseMessage':
+                                    {
+                                        'title': 'BaseMessage',
+                                        'description': 'Base abstract Message class. Messages are the inputs and outputs of ChatModels.',
+                                        'type': 'object',
+                                        'properties':
+                                            {
+                                             'content':
+                                                {
+                                                    'title': 'Content',
+                                                    'anyOf': [
+                                                        {'type': 'string'},
+                                                        {'type': 'array','items': {'anyOf': [{'type': 'string'}, {'type': 'object'}]}}
+                                                    ]
+                                                },
+                                            'additional_kwargs':
+                                                {
+                                                    'title': 'Additional Kwargs',
+                                                    'type': 'object'
+                                                },
+                                            'response_metadata':
+                                                {
+                                                    'title': 'Response Metadata',
+                                                    'type': 'object'
+                                                },
+                                            'type':
+                                                {
+                                                    'title': 'Type',
+                                                    'type': 'string'
+                                                },
+                                            'name':
+                                                {
+                                                    'title': 'Name',
+                                                    'type': 'string'
+                                                },
+                                            'id':
+                                                {
+                                                    'title': 'Id',
+                                                    'type': 'string'
+                                                }
+                                            },
+                                        'required': ['content', 'type']
+                                    },
+                                'AgentState':
+                                    {
+                                        'title': 'AgentState',
+                                        'type': 'object',
+                                        'properties':
+                                            {
+                                                'messages':
+                                                    {
+                                                        'title': 'Messages',
+                                                        'type': 'array',
+                                                        'items': {'$ref': '#/definitions/BaseMessage'}
+                                                    }
+                                            },
+                                        'required': ['messages']
+                                    }
+                            }
+                    },
+                'config_schema':
+                    {
+                        'title': 'Configurable',
+                        'type': 'object',
+                        'properties':
+                            {
+                                'model_name':
+                                    {
+                                        'title': 'Model Name',
+                                        'enum': ['anthropic', 'openai'],
+                                        'type': 'string'
+                                    }
+                            }
+                    },
+                'context_schema':
+                    {
+                        'title': 'Context',
+                        'type': 'object',
+                        'properties':
+                            {
+                                'model_name':
+                                    {
+                                        'title': 'Model Name',
+                                        'enum': ['anthropic', 'openai'],
+                                        'type': 'string'
+                                    }
+                            }
+                    }
+            }
+            ```
+
+        """
+        return self.http.get(
+            f"/assistants/{assistant_id}/schemas", headers=headers, params=params
+        )
+
+    def get_subgraphs(
+        self,
+        assistant_id: str,
+        namespace: str | None = None,
+        recurse: bool = False,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Subgraphs:
+        """Get the schemas of an assistant by ID.
+
+        Args:
+            assistant_id: The ID of the assistant to get the schema of.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            Subgraphs: The graph schema for the assistant.
+
+        """
+        get_params = {"recurse": recurse}
+        if params:
+            get_params = {**get_params, **dict(params)}
+        if namespace is not None:
+            return self.http.get(
+                f"/assistants/{assistant_id}/subgraphs/{namespace}",
+                params=get_params,
+                headers=headers,
+            )
+        else:
+            return self.http.get(
+                f"/assistants/{assistant_id}/subgraphs",
+                params=get_params,
+                headers=headers,
+            )
+
+    def create(
+        self,
+        graph_id: str | None,
+        config: Config | None = None,
+        *,
+        context: Context | None = None,
+        metadata: Json = None,
+        assistant_id: str | None = None,
+        if_exists: OnConflictBehavior | None = None,
+        name: str | None = None,
+        headers: Mapping[str, str] | None = None,
+        description: str | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Assistant:
+        """Create a new assistant.
+
+        Useful when graph is configurable and you want to create different assistants based on different configurations.
+
+        Args:
+            graph_id: The ID of the graph the assistant should use. The graph ID is normally set in your langgraph.json configuration.
+            config: Configuration to use for the graph.
+            context: Static context to add to the assistant.
+                !!! version-added "Added in version 0.6.0"
+            metadata: Metadata to add to assistant.
+            assistant_id: Assistant ID to use, will default to a random UUID if not provided.
+            if_exists: How to handle duplicate creation. Defaults to 'raise' under the hood.
+                Must be either 'raise' (raise error if duplicate), or 'do_nothing' (return existing assistant).
+            name: The name of the assistant. Defaults to 'Untitled' under the hood.
+            headers: Optional custom headers to include with the request.
+            description: Optional description of the assistant.
+                The description field is available for langgraph-api server version>=0.0.45
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            The created assistant.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:2024")
+            assistant = client.assistants.create(
+                graph_id="agent",
+                context={"model_name": "openai"},
+                metadata={"number":1},
+                assistant_id="my-assistant-id",
+                if_exists="do_nothing",
+                name="my_name"
+            )
+            ```
+        """
+        payload: dict[str, Any] = {
+            "graph_id": graph_id,
+        }
+        if config:
+            payload["config"] = config
+        if context:
+            payload["context"] = context
+        if metadata:
+            payload["metadata"] = metadata
+        if assistant_id:
+            payload["assistant_id"] = assistant_id
+        if if_exists:
+            payload["if_exists"] = if_exists
+        if name:
+            payload["name"] = name
+        if description:
+            payload["description"] = description
+        return self.http.post(
+            "/assistants", json=payload, headers=headers, params=params
+        )
+
+    def update(
+        self,
+        assistant_id: str,
+        *,
+        graph_id: str | None = None,
+        config: Config | None = None,
+        context: Context | None = None,
+        metadata: Json = None,
+        name: str | None = None,
+        headers: Mapping[str, str] | None = None,
+        description: str | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Assistant:
+        """Update an assistant.
+
+        Use this to point to a different graph, update the configuration, or change the metadata of an assistant.
+
+        Args:
+            assistant_id: Assistant to update.
+            graph_id: The ID of the graph the assistant should use.
+                The graph ID is normally set in your langgraph.json configuration. If `None`, assistant will keep pointing to same graph.
+            config: Configuration to use for the graph.
+            context: Static context to add to the assistant.
+                !!! version-added "Added in version 0.6.0"
+            metadata: Metadata to merge with existing assistant metadata.
+            name: The new name for the assistant.
+            headers: Optional custom headers to include with the request.
+            description: Optional description of the assistant.
+                The description field is available for langgraph-api server version>=0.0.45
+
+        Returns:
+            The updated assistant.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:2024")
+            assistant = client.assistants.update(
+                assistant_id='e280dad7-8618-443f-87f1-8e41841c180f',
+                graph_id="other-graph",
+                context={"model_name": "anthropic"},
+                metadata={"number":2}
+            )
+            ```
+        """
+        payload: dict[str, Any] = {}
+        if graph_id:
+            payload["graph_id"] = graph_id
+        if config is not None:
+            payload["config"] = config
+        if context is not None:
+            payload["context"] = context
+        if metadata:
+            payload["metadata"] = metadata
+        if name:
+            payload["name"] = name
+        if description:
+            payload["description"] = description
+        return self.http.patch(
+            f"/assistants/{assistant_id}",
+            json=payload,
+            headers=headers,
+            params=params,
+        )
+
+    def delete(
+        self,
+        assistant_id: str,
+        *,
+        delete_threads: bool = False,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> None:
+        """Delete an assistant.
+
+        Args:
+            assistant_id: The assistant ID to delete.
+            delete_threads: If true, delete all threads with `metadata.assistant_id`
+                matching this assistant, along with runs and checkpoints belonging to
+                those threads.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            `None`
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:2024")
+            client.assistants.delete(
+                assistant_id="my_assistant_id"
+            )
+            ```
+
+        """
+        query_params: dict[str, Any] = {}
+        if delete_threads:
+            query_params["delete_threads"] = True
+        if params:
+            query_params.update(params)
+        self.http.delete(
+            f"/assistants/{assistant_id}",
+            headers=headers,
+            params=query_params or None,
+        )
+
+    @overload
+    def search(
+        self,
+        *,
+        metadata: Json = None,
+        graph_id: str | None = None,
+        name: str | None = None,
+        limit: int = 10,
+        offset: int = 0,
+        sort_by: AssistantSortBy | None = None,
+        sort_order: SortOrder | None = None,
+        select: list[AssistantSelectField] | None = None,
+        response_format: Literal["object"],
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> AssistantsSearchResponse: ...
+
+    @overload
+    def search(
+        self,
+        *,
+        metadata: Json = None,
+        graph_id: str | None = None,
+        name: str | None = None,
+        limit: int = 10,
+        offset: int = 0,
+        sort_by: AssistantSortBy | None = None,
+        sort_order: SortOrder | None = None,
+        select: list[AssistantSelectField] | None = None,
+        response_format: Literal["array"] = "array",
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> list[Assistant]: ...
+
+    def search(
+        self,
+        *,
+        metadata: Json = None,
+        graph_id: str | None = None,
+        name: str | None = None,
+        limit: int = 10,
+        offset: int = 0,
+        sort_by: AssistantSortBy | None = None,
+        sort_order: SortOrder | None = None,
+        select: list[AssistantSelectField] | None = None,
+        response_format: Literal["array", "object"] = "array",
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> AssistantsSearchResponse | list[Assistant]:
+        """Search for assistants.
+
+        Args:
+            metadata: Metadata to filter by. Exact match filter for each KV pair.
+            graph_id: The ID of the graph to filter by.
+                The graph ID is normally set in your langgraph.json configuration.
+            name: The name of the assistant to filter by.
+                The filtering logic will match assistants where 'name' is a substring (case insensitive) of the assistant name.
+            limit: The maximum number of results to return.
+            offset: The number of results to skip.
+            sort_by: The field to sort by.
+            sort_order: The order to sort by.
+            select: Specific assistant fields to include in the response.
+            response_format: Controls the response shape. Use `"array"` (default)
+                to return a bare list of assistants, or `"object"` to return
+                a mapping containing assistants plus pagination metadata.
+                Defaults to "array", though this default will be changed to "object" in a future release.
+            headers: Optional custom headers to include with the request.
+
+        Returns:
+            A list of assistants (when `response_format="array"`) or a mapping
+            with the assistants and the next pagination cursor (when
+            `response_format="object"`).
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:2024")
+            response = client.assistants.search(
+                metadata = {"name":"my_name"},
+                graph_id="my_graph_id",
+                limit=5,
+                offset=5,
+                response_format="object",
+            )
+            assistants = response["assistants"]
+            next_cursor = response["next"]
+            ```
+        """
+        if response_format not in ("array", "object"):
+            raise ValueError("response_format must be 'array' or 'object'")
+        payload: dict[str, Any] = {
+            "limit": limit,
+            "offset": offset,
+        }
+        if metadata:
+            payload["metadata"] = metadata
+        if graph_id:
+            payload["graph_id"] = graph_id
+        if name:
+            payload["name"] = name
+        if sort_by:
+            payload["sort_by"] = sort_by
+        if sort_order:
+            payload["sort_order"] = sort_order
+        if select:
+            payload["select"] = select
+        next_cursor: str | None = None
+
+        def capture_pagination(response: httpx.Response) -> None:
+            nonlocal next_cursor
+            next_cursor = response.headers.get("X-Pagination-Next")
+
+        assistants = cast(
+            list[Assistant],
+            self.http.post(
+                "/assistants/search",
+                json=payload,
+                headers=headers,
+                params=params,
+                on_response=capture_pagination if response_format == "object" else None,
+            ),
+        )
+        if response_format == "object":
+            return {"assistants": assistants, "next": next_cursor}
+        return assistants
+
+    def count(
+        self,
+        *,
+        metadata: Json = None,
+        graph_id: str | None = None,
+        name: str | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> int:
+        """Count assistants matching filters.
+
+        Args:
+            metadata: Metadata to filter by. Exact match for each key/value.
+            graph_id: Optional graph id to filter by.
+            name: Optional name to filter by.
+                The filtering logic will match assistants where 'name' is a substring (case insensitive) of the assistant name.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            int: Number of assistants matching the criteria.
+        """
+        payload: dict[str, Any] = {}
+        if metadata:
+            payload["metadata"] = metadata
+        if graph_id:
+            payload["graph_id"] = graph_id
+        if name:
+            payload["name"] = name
+        return self.http.post(
+            "/assistants/count", json=payload, headers=headers, params=params
+        )
+
+    def get_versions(
+        self,
+        assistant_id: str,
+        metadata: Json = None,
+        limit: int = 10,
+        offset: int = 0,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> list[AssistantVersion]:
+        """List all versions of an assistant.
+
+        Args:
+            assistant_id: The assistant ID to get versions for.
+            metadata: Metadata to filter versions by. Exact match filter for each KV pair.
+            limit: The maximum number of versions to return.
+            offset: The number of versions to skip.
+            headers: Optional custom headers to include with the request.
+
+        Returns:
+            A list of assistants.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:2024")
+            assistant_versions = client.assistants.get_versions(
+                assistant_id="my_assistant_id"
+            )
+            ```
+
+        """
+
+        payload: dict[str, Any] = {
+            "limit": limit,
+            "offset": offset,
+        }
+        if metadata:
+            payload["metadata"] = metadata
+        return self.http.post(
+            f"/assistants/{assistant_id}/versions",
+            json=payload,
+            headers=headers,
+            params=params,
+        )
+
+    def set_latest(
+        self,
+        assistant_id: str,
+        version: int,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Assistant:
+        """Change the version of an assistant.
+
+        Args:
+            assistant_id: The assistant ID to delete.
+            version: The version to change to.
+            headers: Optional custom headers to include with the request.
+
+        Returns:
+            `Assistant` Object.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:2024")
+            new_version_assistant = client.assistants.set_latest(
+                assistant_id="my_assistant_id",
+                version=3
+            )
+            ```
+
+        """
+
+        payload: dict[str, Any] = {"version": version}
+
+        return self.http.post(
+            f"/assistants/{assistant_id}/latest",
+            json=payload,
+            headers=headers,
+            params=params,
+        )

libs/sdk-py/langgraph_sdk/_sync/client.py

@@ -0,0 +1,127 @@
+"""Sync LangGraph client."""
+
+from __future__ import annotations
+
+from collections.abc import Mapping
+from types import TracebackType
+
+import httpx
+
+from langgraph_sdk._shared.types import TimeoutTypes
+from langgraph_sdk._shared.utilities import NOT_PROVIDED, _get_headers
+from langgraph_sdk._sync.assistants import SyncAssistantsClient
+from langgraph_sdk._sync.cron import SyncCronClient
+from langgraph_sdk._sync.http import SyncHttpClient
+from langgraph_sdk._sync.runs import SyncRunsClient
+from langgraph_sdk._sync.store import SyncStoreClient
+from langgraph_sdk._sync.threads import SyncThreadsClient
+
+
+def get_sync_client(
+    *,
+    url: str | None = None,
+    api_key: str | None = NOT_PROVIDED,
+    headers: Mapping[str, str] | None = None,
+    timeout: TimeoutTypes | None = None,
+) -> SyncLangGraphClient:
+    """Get a synchronous LangGraphClient instance.
+
+    Args:
+        url: The URL of the LangGraph API.
+        api_key: API key for authentication. Can be:
+            - A string: use this exact API key
+            - `None`: explicitly skip loading from environment variables
+            - Not provided (default): auto-load from environment in this order:
+                1. `LANGGRAPH_API_KEY`
+                2. `LANGSMITH_API_KEY`
+                3. `LANGCHAIN_API_KEY`
+        headers: Optional custom headers
+        timeout: Optional timeout configuration for the HTTP client.
+            Accepts an httpx.Timeout instance, a float (seconds), or a tuple of timeouts.
+            Tuple format is (connect, read, write, pool)
+            If not provided, defaults to connect=5s, read=300s, write=300s, and pool=5s.
+    Returns:
+        SyncLangGraphClient: The top-level synchronous client for accessing AssistantsClient,
+        ThreadsClient, RunsClient, and CronClient.
+
+    ???+ example "Example"
+
+        ```python
+        from langgraph_sdk import get_sync_client
+
+        # get top-level synchronous LangGraphClient
+        client = get_sync_client(url="http://localhost:8123")
+
+        # example usage: client.<model>.<method_name>()
+        assistant = client.assistants.get(assistant_id="some_uuid")
+        ```
+
+    ???+ example "Skip auto-loading API key from environment:"
+
+        ```python
+        from langgraph_sdk import get_sync_client
+
+        # Don't load API key from environment variables
+        client = get_sync_client(
+            url="http://localhost:8123",
+            api_key=None
+        )
+        ```
+    """
+
+    if url is None:
+        url = "http://localhost:8123"
+
+    transport = httpx.HTTPTransport(retries=5)
+    client = httpx.Client(
+        base_url=url,
+        transport=transport,
+        timeout=(
+            httpx.Timeout(timeout)  # type: ignore[arg-type]
+            if timeout is not None
+            else httpx.Timeout(connect=5, read=300, write=300, pool=5)
+        ),
+        headers=_get_headers(api_key, headers),
+    )
+    return SyncLangGraphClient(client)
+
+
+class SyncLangGraphClient:
+    """Synchronous client for interacting with the LangGraph API.
+
+    This class provides synchronous access to LangGraph API endpoints for managing
+    assistants, threads, runs, cron jobs, and data storage.
+
+    ???+ example "Example"
+
+        ```python
+        client = get_sync_client(url="http://localhost:2024")
+        assistant = client.assistants.get("asst_123")
+        ```
+    """
+
+    def __init__(self, client: httpx.Client) -> None:
+        self.http = SyncHttpClient(client)
+        self.assistants = SyncAssistantsClient(self.http)
+        self.threads = SyncThreadsClient(self.http)
+        self.runs = SyncRunsClient(self.http)
+        self.crons = SyncCronClient(self.http)
+        self.store = SyncStoreClient(self.http)
+
+    def __enter__(self) -> SyncLangGraphClient:
+        """Enter the sync context manager."""
+        return self
+
+    def __exit__(
+        self,
+        exc_type: type[BaseException] | None,
+        exc_val: BaseException | None,
+        exc_tb: TracebackType | None,
+    ) -> None:
+        """Exit the sync context manager."""
+        self.close()
+
+    def close(self) -> None:
+        """Close the underlying HTTP client."""
+        if hasattr(self, "http"):
+            self.http.client.close()

libs/sdk-py/langgraph_sdk/_sync/cron.py

@@ -0,0 +1,439 @@
+"""Synchronous cron client for LangGraph SDK."""
+
+from __future__ import annotations
+
+from collections.abc import Mapping
+from datetime import datetime
+from typing import Any
+
+from langgraph_sdk._sync.http import SyncHttpClient
+from langgraph_sdk.schema import (
+    All,
+    Config,
+    Context,
+    Cron,
+    CronSelectField,
+    CronSortBy,
+    Input,
+    OnCompletionBehavior,
+    QueryParamTypes,
+    Run,
+    SortOrder,
+)
+
+
+class SyncCronClient:
+    """Synchronous client for managing cron jobs in LangGraph.
+
+    This class provides methods to create and manage scheduled tasks (cron jobs) for automated graph executions.
+
+    ???+ example "Example"
+
+        ```python
+        client = get_sync_client(url="http://localhost:8123")
+        cron_job = client.crons.create_for_thread(thread_id="thread_123", assistant_id="asst_456", schedule="0 * * * *")
+        ```
+
+    !!! note "Feature Availability"
+
+        The crons client functionality is not supported on all licenses.
+        Please check the relevant license documentation for the most up-to-date
+        details on feature availability.
+    """
+
+    def __init__(self, http_client: SyncHttpClient) -> None:
+        self.http = http_client
+
+    def create_for_thread(
+        self,
+        thread_id: str,
+        assistant_id: str,
+        *,
+        schedule: str,
+        input: Input | None = None,
+        metadata: Mapping[str, Any] | None = None,
+        config: Config | None = None,
+        context: Context | None = None,
+        checkpoint_during: bool | None = None,
+        interrupt_before: All | list[str] | None = None,
+        interrupt_after: All | list[str] | None = None,
+        webhook: str | None = None,
+        multitask_strategy: str | None = None,
+        end_time: datetime | None = None,
+        enabled: bool | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Run:
+        """Create a cron job for a thread.
+
+        Args:
+            thread_id: the thread ID to run the cron job on.
+            assistant_id: The assistant ID or graph name to use for the cron job.
+                If using graph name, will default to first assistant created from that graph.
+            schedule: The cron schedule to execute this job on.
+                Schedules are interpreted in UTC.
+            input: The input to the graph.
+            metadata: Metadata to assign to the cron job runs.
+            config: The configuration for the assistant.
+            context: Static context to add to the assistant.
+                !!! version-added "Added in version 0.6.0"
+            checkpoint_during: Whether to checkpoint during the run (or only at the end/interruption).
+            interrupt_before: Nodes to interrupt immediately before they get executed.
+            interrupt_after: Nodes to Nodes to interrupt immediately after they get executed.
+            webhook: Webhook to call after LangGraph API call is done.
+            multitask_strategy: Multitask strategy to use.
+                Must be one of 'reject', 'interrupt', 'rollback', or 'enqueue'.
+            end_time: The time to stop running the cron job. If not provided, the cron job will run indefinitely.
+            enabled: Whether the cron job is enabled. By default, it is considered enabled.
+            headers: Optional custom headers to include with the request.
+
+        Returns:
+            The cron `Run`.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:8123")
+            cron_run = client.crons.create_for_thread(
+                thread_id="my-thread-id",
+                assistant_id="agent",
+                schedule="27 15 * * *",
+                input={"messages": [{"role": "user", "content": "hello!"}]},
+                metadata={"name":"my_run"},
+                context={"model_name": "openai"},
+                interrupt_before=["node_to_stop_before_1","node_to_stop_before_2"],
+                interrupt_after=["node_to_stop_after_1","node_to_stop_after_2"],
+                webhook="https://my.fake.webhook.com",
+                multitask_strategy="interrupt",
+                enabled=True
+            )
+            ```
+        """
+        payload = {
+            "schedule": schedule,
+            "input": input,
+            "config": config,
+            "metadata": metadata,
+            "context": context,
+            "assistant_id": assistant_id,
+            "interrupt_before": interrupt_before,
+            "interrupt_after": interrupt_after,
+            "checkpoint_during": checkpoint_during,
+            "webhook": webhook,
+            "multitask_strategy": multitask_strategy,
+            "end_time": end_time.isoformat() if end_time else None,
+            "enabled": enabled,
+        }
+        payload = {k: v for k, v in payload.items() if v is not None}
+        return self.http.post(
+            f"/threads/{thread_id}/runs/crons",
+            json=payload,
+            headers=headers,
+            params=params,
+        )
+
+    def create(
+        self,
+        assistant_id: str,
+        *,
+        schedule: str,
+        input: Input | None = None,
+        metadata: Mapping[str, Any] | None = None,
+        config: Config | None = None,
+        context: Context | None = None,
+        checkpoint_during: bool | None = None,
+        interrupt_before: All | list[str] | None = None,
+        interrupt_after: All | list[str] | None = None,
+        webhook: str | None = None,
+        on_run_completed: OnCompletionBehavior | None = None,
+        multitask_strategy: str | None = None,
+        end_time: datetime | None = None,
+        enabled: bool | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Run:
+        """Create a cron run.
+
+        Args:
+            assistant_id: The assistant ID or graph name to use for the cron job.
+                If using graph name, will default to first assistant created from that graph.
+            schedule: The cron schedule to execute this job on.
+                Schedules are interpreted in UTC.
+            input: The input to the graph.
+            metadata: Metadata to assign to the cron job runs.
+            config: The configuration for the assistant.
+            context: Static context to add to the assistant.
+                !!! version-added "Added in version 0.6.0"
+            checkpoint_during: Whether to checkpoint during the run (or only at the end/interruption).
+            interrupt_before: Nodes to interrupt immediately before they get executed.
+            interrupt_after: Nodes to Nodes to interrupt immediately after they get executed.
+            webhook: Webhook to call after LangGraph API call is done.
+            on_run_completed: What to do with the thread after the run completes.
+                Must be one of 'delete' (default) or 'keep'. 'delete' removes the thread
+                after execution. 'keep' creates a new thread for each execution but does not
+                clean them up. Clients are responsible for cleaning up kept threads.
+            multitask_strategy: Multitask strategy to use.
+                Must be one of 'reject', 'interrupt', 'rollback', or 'enqueue'.
+            end_time: The time to stop running the cron job. If not provided, the cron job will run indefinitely.
+            enabled: Whether the cron job is enabled. By default, it is considered enabled.
+            headers: Optional custom headers to include with the request.
+
+        Returns:
+            The cron `Run`.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:8123")
+            cron_run = client.crons.create(
+                assistant_id="agent",
+                schedule="27 15 * * *",
+                input={"messages": [{"role": "user", "content": "hello!"}]},
+                metadata={"name":"my_run"},
+                context={"model_name": "openai"},
+                checkpoint_during=True,
+                interrupt_before=["node_to_stop_before_1","node_to_stop_before_2"],
+                interrupt_after=["node_to_stop_after_1","node_to_stop_after_2"],
+                webhook="https://my.fake.webhook.com",
+                multitask_strategy="interrupt",
+                enabled=True
+            )
+            ```
+
+        """
+        payload = {
+            "schedule": schedule,
+            "input": input,
+            "config": config,
+            "metadata": metadata,
+            "context": context,
+            "assistant_id": assistant_id,
+            "interrupt_before": interrupt_before,
+            "interrupt_after": interrupt_after,
+            "webhook": webhook,
+            "checkpoint_during": checkpoint_during,
+            "on_run_completed": on_run_completed,
+            "multitask_strategy": multitask_strategy,
+            "end_time": end_time.isoformat() if end_time else None,
+            "enabled": enabled,
+        }
+        payload = {k: v for k, v in payload.items() if v is not None}
+        return self.http.post(
+            "/runs/crons", json=payload, headers=headers, params=params
+        )
+
+    def delete(
+        self,
+        cron_id: str,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> None:
+        """Delete a cron.
+
+        Args:
+            cron_id: The cron ID to delete.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            `None`
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:8123")
+            client.crons.delete(
+                cron_id="cron_to_delete"
+            )
+            ```
+
+        """
+        self.http.delete(f"/runs/crons/{cron_id}", headers=headers, params=params)
+
+    def update(
+        self,
+        cron_id: str,
+        *,
+        schedule: str | None = None,
+        end_time: datetime | None = None,
+        input: Input | None = None,
+        metadata: Mapping[str, Any] | None = None,
+        config: Config | None = None,
+        context: Context | None = None,
+        webhook: str | None = None,
+        interrupt_before: All | list[str] | None = None,
+        interrupt_after: All | list[str] | None = None,
+        on_run_completed: OnCompletionBehavior | None = None,
+        enabled: bool | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Cron:
+        """Update a cron job by ID.
+
+        Args:
+            cron_id: The cron ID to update.
+            schedule: The cron schedule to execute this job on.
+                Schedules are interpreted in UTC.
+            end_time: The end date to stop running the cron.
+            input: The input to the graph.
+            metadata: Metadata to assign to the cron job runs.
+            config: The configuration for the assistant.
+            context: Static context added to the assistant.
+            webhook: Webhook to call after LangGraph API call is done.
+            interrupt_before: Nodes to interrupt immediately before they get executed.
+            interrupt_after: Nodes to interrupt immediately after they get executed.
+            on_run_completed: What to do with the thread after the run completes.
+                Must be one of 'delete' or 'keep'. 'delete' removes the thread
+                after execution. 'keep' creates a new thread for each execution but does not
+                clean them up.
+            enabled: Enable or disable the cron job.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            The updated cron job.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:8123")
+            updated_cron = client.crons.update(
+                cron_id="1ef3cefa-4c09-6926-96d0-3dc97fd5e39b",
+                schedule="0 10 * * *",
+                enabled=False,
+            )
+            ```
+
+        """
+        payload = {
+            "schedule": schedule,
+            "end_time": end_time.isoformat() if end_time else None,
+            "input": input,
+            "metadata": metadata,
+            "config": config,
+            "context": context,
+            "webhook": webhook,
+            "interrupt_before": interrupt_before,
+            "interrupt_after": interrupt_after,
+            "on_run_completed": on_run_completed,
+            "enabled": enabled,
+        }
+        payload = {k: v for k, v in payload.items() if v is not None}
+        return self.http.patch(
+            f"/runs/crons/{cron_id}",
+            json=payload,
+            headers=headers,
+            params=params,
+        )
+
+    def search(
+        self,
+        *,
+        assistant_id: str | None = None,
+        thread_id: str | None = None,
+        enabled: bool | None = None,
+        limit: int = 10,
+        offset: int = 0,
+        sort_by: CronSortBy | None = None,
+        sort_order: SortOrder | None = None,
+        select: list[CronSelectField] | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> list[Cron]:
+        """Get a list of cron jobs.
+
+        Args:
+            assistant_id: The assistant ID or graph name to search for.
+            thread_id: the thread ID to search for.
+            enabled: Whether the cron job is enabled.
+            limit: The maximum number of results to return.
+            offset: The number of results to skip.
+            headers: Optional custom headers to include with the request.
+
+        Returns:
+            The list of cron jobs returned by the search,
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:8123")
+            cron_jobs = client.crons.search(
+                assistant_id="my_assistant_id",
+                thread_id="my_thread_id",
+                enabled=True,
+                limit=5,
+                offset=5,
+            )
+            print(cron_jobs)
+            ```
+
+            ```shell
+            ----------------------------------------------------------
+
+            [
+                {
+                    'cron_id': '1ef3cefa-4c09-6926-96d0-3dc97fd5e39b',
+                    'assistant_id': 'my_assistant_id',
+                    'thread_id': 'my_thread_id',
+                    'user_id': None,
+                    'payload':
+                        {
+                            'input': {'start_time': ''},
+                            'schedule': '4 * * * *',
+                            'assistant_id': 'my_assistant_id'
+                        },
+                    'schedule': '4 * * * *',
+                    'next_run_date': '2024-07-25T17:04:00+00:00',
+                    'end_time': None,
+                    'created_at': '2024-07-08T06:02:23.073257+00:00',
+                    'updated_at': '2024-07-08T06:02:23.073257+00:00'
+                }
+            ]
+            ```
+        """
+        payload = {
+            "assistant_id": assistant_id,
+            "thread_id": thread_id,
+            "enabled": enabled,
+            "limit": limit,
+            "offset": offset,
+        }
+        if sort_by:
+            payload["sort_by"] = sort_by
+        if sort_order:
+            payload["sort_order"] = sort_order
+        if select:
+            payload["select"] = select
+        payload = {k: v for k, v in payload.items() if v is not None}
+        return self.http.post(
+            "/runs/crons/search", json=payload, headers=headers, params=params
+        )
+
+    def count(
+        self,
+        *,
+        assistant_id: str | None = None,
+        thread_id: str | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> int:
+        """Count cron jobs matching filters.
+
+        Args:
+            assistant_id: Assistant ID to filter by.
+            thread_id: Thread ID to filter by.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            int: Number of crons matching the criteria.
+        """
+        payload: dict[str, Any] = {}
+        if assistant_id:
+            payload["assistant_id"] = assistant_id
+        if thread_id:
+            payload["thread_id"] = thread_id
+        return self.http.post(
+            "/runs/crons/count", json=payload, headers=headers, params=params
+        )

libs/sdk-py/langgraph_sdk/_sync/http.py

@@ -0,0 +1,296 @@
+"""Synchronous HTTP client for LangGraph API."""
+
+from __future__ import annotations
+
+import logging
+import sys
+import warnings
+from collections.abc import Callable, Iterator, Mapping
+from typing import Any, cast
+
+import httpx
+import orjson
+
+from langgraph_sdk._shared.utilities import _orjson_default
+from langgraph_sdk.errors import _raise_for_status_typed
+from langgraph_sdk.schema import QueryParamTypes, StreamPart
+from langgraph_sdk.sse import SSEDecoder, iter_lines_raw
+
+logger = logging.getLogger(__name__)
+
+
+class SyncHttpClient:
+    """Handle synchronous requests to the LangGraph API.
+
+    Provides error messaging and content handling enhancements above the
+    underlying httpx client, mirroring the interface of [HttpClient](#HttpClient)
+    but for sync usage.
+
+    Attributes:
+        client (httpx.Client): Underlying HTTPX sync client.
+    """
+
+    def __init__(self, client: httpx.Client) -> None:
+        self.client = client
+
+    def get(
+        self,
+        path: str,
+        *,
+        params: QueryParamTypes | None = None,
+        headers: Mapping[str, str] | None = None,
+        on_response: Callable[[httpx.Response], None] | None = None,
+    ) -> Any:
+        """Send a `GET` request."""
+        r = self.client.get(path, params=params, headers=headers)
+        if on_response:
+            on_response(r)
+        _raise_for_status_typed(r)
+        return _decode_json(r)
+
+    def post(
+        self,
+        path: str,
+        *,
+        json: dict[str, Any] | list | None,
+        params: QueryParamTypes | None = None,
+        headers: Mapping[str, str] | None = None,
+        on_response: Callable[[httpx.Response], None] | None = None,
+    ) -> Any:
+        """Send a `POST` request."""
+        if json is not None:
+            request_headers, content = _encode_json(json)
+        else:
+            request_headers, content = {}, b""
+        if headers:
+            request_headers.update(headers)
+        r = self.client.post(
+            path, headers=request_headers, content=content, params=params
+        )
+        if on_response:
+            on_response(r)
+        _raise_for_status_typed(r)
+        return _decode_json(r)
+
+    def put(
+        self,
+        path: str,
+        *,
+        json: dict,
+        params: QueryParamTypes | None = None,
+        headers: Mapping[str, str] | None = None,
+        on_response: Callable[[httpx.Response], None] | None = None,
+    ) -> Any:
+        """Send a `PUT` request."""
+        request_headers, content = _encode_json(json)
+        if headers:
+            request_headers.update(headers)
+
+        r = self.client.put(
+            path, headers=request_headers, content=content, params=params
+        )
+        if on_response:
+            on_response(r)
+        _raise_for_status_typed(r)
+        return _decode_json(r)
+
+    def patch(
+        self,
+        path: str,
+        *,
+        json: dict,
+        params: QueryParamTypes | None = None,
+        headers: Mapping[str, str] | None = None,
+        on_response: Callable[[httpx.Response], None] | None = None,
+    ) -> Any:
+        """Send a `PATCH` request."""
+        request_headers, content = _encode_json(json)
+        if headers:
+            request_headers.update(headers)
+        r = self.client.patch(
+            path, headers=request_headers, content=content, params=params
+        )
+        if on_response:
+            on_response(r)
+        _raise_for_status_typed(r)
+        return _decode_json(r)
+
+    def delete(
+        self,
+        path: str,
+        *,
+        json: Any | None = None,
+        params: QueryParamTypes | None = None,
+        headers: Mapping[str, str] | None = None,
+        on_response: Callable[[httpx.Response], None] | None = None,
+    ) -> None:
+        """Send a `DELETE` request."""
+        r = self.client.request(
+            "DELETE", path, json=json, params=params, headers=headers
+        )
+        if on_response:
+            on_response(r)
+        _raise_for_status_typed(r)
+
+    def request_reconnect(
+        self,
+        path: str,
+        method: str,
+        *,
+        json: dict[str, Any] | None = None,
+        params: QueryParamTypes | None = None,
+        headers: Mapping[str, str] | None = None,
+        on_response: Callable[[httpx.Response], None] | None = None,
+        reconnect_limit: int = 5,
+    ) -> Any:
+        """Send a request that automatically reconnects to Location header."""
+        request_headers, content = _encode_json(json)
+        if headers:
+            request_headers.update(headers)
+        with self.client.stream(
+            method, path, headers=request_headers, content=content, params=params
+        ) as r:
+            if on_response:
+                on_response(r)
+            try:
+                r.raise_for_status()
+            except httpx.HTTPStatusError as e:
+                body = r.read().decode()
+                if sys.version_info >= (3, 11):
+                    e.add_note(body)
+                else:
+                    logger.error(f"Error from langgraph-api: {body}", exc_info=e)
+                raise e
+            loc = r.headers.get("location")
+            if reconnect_limit <= 0 or not loc:
+                return _decode_json(r)
+            try:
+                return _decode_json(r)
+            except httpx.HTTPError:
+                warnings.warn(
+                    f"Request failed, attempting reconnect to Location: {loc}",
+                    stacklevel=2,
+                )
+                r.close()
+                return self.request_reconnect(
+                    loc,
+                    "GET",
+                    headers=request_headers,
+                    # don't pass on_response so it's only called once
+                    reconnect_limit=reconnect_limit - 1,
+                )
+
+    def stream(
+        self,
+        path: str,
+        method: str,
+        *,
+        json: dict[str, Any] | None = None,
+        params: QueryParamTypes | None = None,
+        headers: Mapping[str, str] | None = None,
+        on_response: Callable[[httpx.Response], None] | None = None,
+    ) -> Iterator[StreamPart]:
+        """Stream the results of a request using SSE."""
+        if json is not None:
+            request_headers, content = _encode_json(json)
+        else:
+            request_headers, content = {}, None
+        request_headers["Accept"] = "text/event-stream"
+        request_headers["Cache-Control"] = "no-store"
+        if headers:
+            request_headers.update(headers)
+
+        reconnect_headers = {
+            key: value
+            for key, value in request_headers.items()
+            if key.lower() not in {"content-length", "content-type"}
+        }
+
+        last_event_id: str | None = None
+        reconnect_path: str | None = None
+        reconnect_attempts = 0
+        max_reconnect_attempts = 5
+
+        while True:
+            current_headers = dict(
+                request_headers if reconnect_path is None else reconnect_headers
+            )
+            if last_event_id is not None:
+                current_headers["Last-Event-ID"] = last_event_id
+
+            current_method = method if reconnect_path is None else "GET"
+            current_content = content if reconnect_path is None else None
+            current_params = params if reconnect_path is None else None
+
+            retry = False
+            with self.client.stream(
+                current_method,
+                reconnect_path or path,
+                headers=current_headers,
+                content=current_content,
+                params=current_params,
+            ) as res:
+                if reconnect_path is None and on_response:
+                    on_response(res)
+                # check status
+                _raise_for_status_typed(res)
+                # check content type
+                content_type = res.headers.get("content-type", "").partition(";")[0]
+                if "text/event-stream" not in content_type:
+                    raise httpx.TransportError(
+                        "Expected response header Content-Type to contain 'text/event-stream', "
+                        f"got {content_type!r}"
+                    )
+
+                reconnect_location = res.headers.get("location")
+                if reconnect_location:
+                    reconnect_path = reconnect_location
+
+                decoder = SSEDecoder()
+                try:
+                    for line in iter_lines_raw(res):
+                        sse = decoder.decode(cast(bytes, line).rstrip(b"\n"))
+                        if sse is not None:
+                            if decoder.last_event_id is not None:
+                                last_event_id = decoder.last_event_id
+                            if sse.event or sse.data is not None:
+                                yield sse
+                except httpx.HTTPError:
+                    # httpx.TransportError inherits from HTTPError, so transient
+                    # disconnects during streaming land here.
+                    if reconnect_path is None:
+                        raise
+                    retry = True
+                else:
+                    if sse := decoder.decode(b""):
+                        if decoder.last_event_id is not None:
+                            last_event_id = decoder.last_event_id
+                        if sse.event or sse.data is not None:
+                            # See async stream implementation for rationale on
+                            # skipping empty flush events.
+                            yield sse
+            if retry:
+                reconnect_attempts += 1
+                if reconnect_attempts > max_reconnect_attempts:
+                    raise httpx.TransportError(
+                        "Exceeded maximum SSE reconnection attempts"
+                    )
+                continue
+            break
+
+
+def _encode_json(json: Any) -> tuple[dict[str, str], bytes]:
+    body = orjson.dumps(
+        json,
+        _orjson_default,
+        orjson.OPT_SERIALIZE_NUMPY | orjson.OPT_NON_STR_KEYS,
+    )
+    content_length = str(len(body))
+    content_type = "application/json"
+    headers = {"Content-Length": content_length, "Content-Type": content_type}
+    return headers, body
+
+
+def _decode_json(r: httpx.Response) -> Any:
+    body = r.read()
+    return orjson.loads(body) if body else None

libs/sdk-py/langgraph_sdk/_sync/store.py

@@ -0,0 +1,313 @@
+"""Synchronous store client for LangGraph SDK."""
+
+from __future__ import annotations
+
+from collections.abc import Mapping, Sequence
+from typing import Any, Literal
+
+from langgraph_sdk._shared.utilities import _provided_vals
+from langgraph_sdk._sync.http import SyncHttpClient
+from langgraph_sdk.schema import (
+    Item,
+    ListNamespaceResponse,
+    QueryParamTypes,
+    SearchItemsResponse,
+)
+
+
+class SyncStoreClient:
+    """A client for synchronous operations on a key-value store.
+
+    Provides methods to interact with a remote key-value store, allowing
+    storage and retrieval of items within namespaced hierarchies.
+
+    ???+ example "Example"
+
+        ```python
+        client = get_sync_client(url="http://localhost:2024"))
+        client.store.put_item(["users", "profiles"], "user123", {"name": "Alice", "age": 30})
+        ```
+    """
+
+    def __init__(self, http: SyncHttpClient) -> None:
+        self.http = http
+
+    def put_item(
+        self,
+        namespace: Sequence[str],
+        /,
+        key: str,
+        value: Mapping[str, Any],
+        index: Literal[False] | list[str] | None = None,
+        ttl: int | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> None:
+        """Store or update an item.
+
+        Args:
+            namespace: A list of strings representing the namespace path.
+            key: The unique identifier for the item within the namespace.
+            value: A dictionary containing the item's data.
+            index: Controls search indexing - None (use defaults), False (disable), or list of field paths to index.
+            ttl: Optional time-to-live in minutes for the item, or None for no expiration.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            `None`
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:8123")
+            client.store.put_item(
+                ["documents", "user123"],
+                key="item456",
+                value={"title": "My Document", "content": "Hello World"}
+            )
+            ```
+        """
+        for label in namespace:
+            if "." in label:
+                raise ValueError(
+                    f"Invalid namespace label '{label}'. Namespace labels cannot contain periods ('.')."
+                )
+        payload = {
+            "namespace": namespace,
+            "key": key,
+            "value": value,
+            "index": index,
+            "ttl": ttl,
+        }
+        self.http.put(
+            "/store/items", json=_provided_vals(payload), headers=headers, params=params
+        )
+
+    def get_item(
+        self,
+        namespace: Sequence[str],
+        /,
+        key: str,
+        *,
+        refresh_ttl: bool | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Item:
+        """Retrieve a single item.
+
+        Args:
+            key: The unique identifier for the item.
+            namespace: Optional list of strings representing the namespace path.
+            refresh_ttl: Whether to refresh the TTL on this read operation. If `None`, uses the store's default behavior.
+            headers: Optional custom headers to include with the request.
+
+        Returns:
+            The retrieved item.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:8123")
+            item = client.store.get_item(
+                ["documents", "user123"],
+                key="item456",
+            )
+            print(item)
+            ```
+
+            ```shell
+            ----------------------------------------------------------------
+
+            {
+                'namespace': ['documents', 'user123'],
+                'key': 'item456',
+                'value': {'title': 'My Document', 'content': 'Hello World'},
+                'created_at': '2024-07-30T12:00:00Z',
+                'updated_at': '2024-07-30T12:00:00Z'
+            }
+            ```
+        """
+        for label in namespace:
+            if "." in label:
+                raise ValueError(
+                    f"Invalid namespace label '{label}'. Namespace labels cannot contain periods ('.')."
+                )
+
+        query_params = {"key": key, "namespace": ".".join(namespace)}
+        if refresh_ttl is not None:
+            query_params["refresh_ttl"] = refresh_ttl
+        if params:
+            query_params.update(params)
+        return self.http.get("/store/items", params=query_params, headers=headers)
+
+    def delete_item(
+        self,
+        namespace: Sequence[str],
+        /,
+        key: str,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> None:
+        """Delete an item.
+
+        Args:
+            key: The unique identifier for the item.
+            namespace: Optional list of strings representing the namespace path.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            `None`
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:8123")
+            client.store.delete_item(
+                ["documents", "user123"],
+                key="item456",
+            )
+            ```
+        """
+        self.http.delete(
+            "/store/items",
+            json={"key": key, "namespace": namespace},
+            headers=headers,
+            params=params,
+        )
+
+    def search_items(
+        self,
+        namespace_prefix: Sequence[str],
+        /,
+        filter: Mapping[str, Any] | None = None,
+        limit: int = 10,
+        offset: int = 0,
+        query: str | None = None,
+        refresh_ttl: bool | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> SearchItemsResponse:
+        """Search for items within a namespace prefix.
+
+        Args:
+            namespace_prefix: List of strings representing the namespace prefix.
+            filter: Optional dictionary of key-value pairs to filter results.
+            limit: Maximum number of items to return (default is 10).
+            offset: Number of items to skip before returning results (default is 0).
+            query: Optional query for natural language search.
+            refresh_ttl: Whether to refresh the TTL on items returned by this search. If `None`, uses the store's default behavior.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            A list of items matching the search criteria.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:8123")
+            items = client.store.search_items(
+                ["documents"],
+                filter={"author": "John Doe"},
+                limit=5,
+                offset=0
+            )
+            print(items)
+            ```
+            ```shell
+            ----------------------------------------------------------------
+
+            {
+                "items": [
+                    {
+                        "namespace": ["documents", "user123"],
+                        "key": "item789",
+                        "value": {
+                            "title": "Another Document",
+                            "author": "John Doe"
+                        },
+                        "created_at": "2024-07-30T12:00:00Z",
+                        "updated_at": "2024-07-30T12:00:00Z"
+                    },
+                    # ... additional items ...
+                ]
+            }
+            ```
+        """
+        payload = {
+            "namespace_prefix": namespace_prefix,
+            "filter": filter,
+            "limit": limit,
+            "offset": offset,
+            "query": query,
+            "refresh_ttl": refresh_ttl,
+        }
+        return self.http.post(
+            "/store/items/search",
+            json=_provided_vals(payload),
+            headers=headers,
+            params=params,
+        )
+
+    def list_namespaces(
+        self,
+        prefix: list[str] | None = None,
+        suffix: list[str] | None = None,
+        max_depth: int | None = None,
+        limit: int = 100,
+        offset: int = 0,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> ListNamespaceResponse:
+        """List namespaces with optional match conditions.
+
+        Args:
+            prefix: Optional list of strings representing the prefix to filter namespaces.
+            suffix: Optional list of strings representing the suffix to filter namespaces.
+            max_depth: Optional integer specifying the maximum depth of namespaces to return.
+            limit: Maximum number of namespaces to return (default is 100).
+            offset: Number of namespaces to skip before returning results (default is 0).
+            headers: Optional custom headers to include with the request.
+
+        Returns:
+            A list of namespaces matching the criteria.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:8123")
+            namespaces = client.store.list_namespaces(
+                prefix=["documents"],
+                max_depth=3,
+                limit=10,
+                offset=0
+            )
+            print(namespaces)
+            ```
+
+            ```shell
+            ----------------------------------------------------------------
+
+            [
+                ["documents", "user123", "reports"],
+                ["documents", "user456", "invoices"],
+                ...
+            ]
+            ```
+        """
+        payload = {
+            "prefix": prefix,
+            "suffix": suffix,
+            "max_depth": max_depth,
+            "limit": limit,
+            "offset": offset,
+        }
+        return self.http.post(
+            "/store/namespaces",
+            json=_provided_vals(payload),
+            headers=headers,
+            params=params,
+        )

libs/sdk-py/langgraph_sdk/_sync/threads.py

@@ -0,0 +1,708 @@
+"""Synchronous client for managing threads in LangGraph."""
+
+from __future__ import annotations
+
+from collections.abc import Iterator, Mapping, Sequence
+from typing import Any
+
+from langgraph_sdk._sync.http import SyncHttpClient
+from langgraph_sdk.schema import (
+    Checkpoint,
+    Json,
+    OnConflictBehavior,
+    PruneStrategy,
+    QueryParamTypes,
+    SortOrder,
+    StreamPart,
+    Thread,
+    ThreadSelectField,
+    ThreadSortBy,
+    ThreadState,
+    ThreadStatus,
+    ThreadStreamMode,
+    ThreadUpdateStateResponse,
+)
+
+
+class SyncThreadsClient:
+    """Synchronous client for managing threads in LangGraph.
+
+    This class provides methods to create, retrieve, and manage threads,
+    which represent conversations or stateful interactions.
+
+    ???+ example "Example"
+
+        ```python
+        client = get_sync_client(url="http://localhost:2024")
+        thread = client.threads.create(metadata={"user_id": "123"})
+        ```
+    """
+
+    def __init__(self, http: SyncHttpClient) -> None:
+        self.http = http
+
+    def get(
+        self,
+        thread_id: str,
+        *,
+        include: Sequence[str] | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Thread:
+        """Get a thread by ID.
+
+        Args:
+            thread_id: The ID of the thread to get.
+            include: Additional fields to include in the response.
+                Supported values: `"ttl"`.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            `Thread` object.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:2024")
+            thread = client.threads.get(
+                thread_id="my_thread_id"
+            )
+            print(thread)
+            ```
+            ```shell
+            -----------------------------------------------------
+
+            {
+                'thread_id': 'my_thread_id',
+                'created_at': '2024-07-18T18:35:15.540834+00:00',
+                'updated_at': '2024-07-18T18:35:15.540834+00:00',
+                'metadata': {'graph_id': 'agent'}
+            }
+            ```
+
+        """
+        query_params: dict[str, Any] = {}
+        if include:
+            query_params["include"] = ",".join(include)
+        if params:
+            query_params.update(params)
+        return self.http.get(
+            f"/threads/{thread_id}",
+            headers=headers,
+            params=query_params or None,
+        )
+
+    def create(
+        self,
+        *,
+        metadata: Json = None,
+        thread_id: str | None = None,
+        if_exists: OnConflictBehavior | None = None,
+        supersteps: Sequence[dict[str, Sequence[dict[str, Any]]]] | None = None,
+        graph_id: str | None = None,
+        ttl: int | Mapping[str, Any] | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Thread:
+        """Create a new thread.
+
+        Args:
+            metadata: Metadata to add to thread.
+            thread_id: ID of thread.
+                If `None`, ID will be a randomly generated UUID.
+            if_exists: How to handle duplicate creation. Defaults to 'raise' under the hood.
+                Must be either 'raise' (raise error if duplicate), or 'do_nothing' (return existing thread).
+            supersteps: Apply a list of supersteps when creating a thread, each containing a sequence of updates.
+                Each update has `values` or `command` and `as_node`. Used for copying a thread between deployments.
+            graph_id: Optional graph ID to associate with the thread.
+            ttl: Optional time-to-live in minutes for the thread. You can pass an
+                integer (minutes) or a mapping with keys `ttl` and optional
+                `strategy` (defaults to "delete").
+            headers: Optional custom headers to include with the request.
+
+        Returns:
+            The created `Thread`.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:2024")
+            thread = client.threads.create(
+                metadata={"number":1},
+                thread_id="my-thread-id",
+                if_exists="raise"
+            )
+            ```
+            )
+        """
+        payload: dict[str, Any] = {}
+        if thread_id:
+            payload["thread_id"] = thread_id
+        if metadata or graph_id:
+            payload["metadata"] = {
+                **(metadata or {}),
+                **({"graph_id": graph_id} if graph_id else {}),
+            }
+        if if_exists:
+            payload["if_exists"] = if_exists
+        if supersteps:
+            payload["supersteps"] = [
+                {
+                    "updates": [
+                        {
+                            "values": u["values"],
+                            "command": u.get("command"),
+                            "as_node": u["as_node"],
+                        }
+                        for u in s["updates"]
+                    ]
+                }
+                for s in supersteps
+            ]
+        if ttl is not None:
+            if isinstance(ttl, (int, float)):
+                payload["ttl"] = {"ttl": ttl, "strategy": "delete"}
+            else:
+                payload["ttl"] = ttl
+
+        return self.http.post("/threads", json=payload, headers=headers, params=params)
+
+    def update(
+        self,
+        thread_id: str,
+        *,
+        metadata: Mapping[str, Any],
+        ttl: int | Mapping[str, Any] | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Thread:
+        """Update a thread.
+
+        Args:
+            thread_id: ID of thread to update.
+            metadata: Metadata to merge with existing thread metadata.
+            ttl: Optional time-to-live in minutes for the thread. You can pass an
+                integer (minutes) or a mapping with keys `ttl` and optional
+                `strategy` (defaults to "delete").
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            The created `Thread`.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:2024")
+            thread = client.threads.update(
+                thread_id="my-thread-id",
+                metadata={"number":1},
+                ttl=43_200,
+            )
+            ```
+        """
+        payload: dict[str, Any] = {"metadata": metadata}
+        if ttl is not None:
+            if isinstance(ttl, (int, float)):
+                payload["ttl"] = {"ttl": ttl, "strategy": "delete"}
+            else:
+                payload["ttl"] = ttl
+        return self.http.patch(
+            f"/threads/{thread_id}",
+            json=payload,
+            headers=headers,
+            params=params,
+        )
+
+    def delete(
+        self,
+        thread_id: str,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> None:
+        """Delete a thread.
+
+        Args:
+            thread_id: The ID of the thread to delete.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            `None`
+
+        ???+ example "Example Usage"
+
+            ```python
+            client.threads.delete(
+                thread_id="my_thread_id"
+            )
+            ```
+
+        """
+        self.http.delete(f"/threads/{thread_id}", headers=headers, params=params)
+
+    def search(
+        self,
+        *,
+        metadata: Json = None,
+        values: Json = None,
+        ids: Sequence[str] | None = None,
+        status: ThreadStatus | None = None,
+        limit: int = 10,
+        offset: int = 0,
+        sort_by: ThreadSortBy | None = None,
+        sort_order: SortOrder | None = None,
+        select: list[ThreadSelectField] | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> list[Thread]:
+        """Search for threads.
+
+        Args:
+            metadata: Thread metadata to filter on.
+            values: State values to filter on.
+            ids: List of thread IDs to filter by.
+            status: Thread status to filter on.
+                Must be one of 'idle', 'busy', 'interrupted' or 'error'.
+            limit: Limit on number of threads to return.
+            offset: Offset in threads table to start search from.
+            headers: Optional custom headers to include with the request.
+
+        Returns:
+            List of the threads matching the search parameters.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:2024")
+            threads = client.threads.search(
+                metadata={"number":1},
+                status="interrupted",
+                limit=15,
+                offset=5
+            )
+            ```
+        """
+        payload: dict[str, Any] = {
+            "limit": limit,
+            "offset": offset,
+        }
+        if metadata:
+            payload["metadata"] = metadata
+        if values:
+            payload["values"] = values
+        if ids:
+            payload["ids"] = ids
+        if status:
+            payload["status"] = status
+        if sort_by:
+            payload["sort_by"] = sort_by
+        if sort_order:
+            payload["sort_order"] = sort_order
+        if select:
+            payload["select"] = select
+        return self.http.post(
+            "/threads/search", json=payload, headers=headers, params=params
+        )
+
+    def count(
+        self,
+        *,
+        metadata: Json = None,
+        values: Json = None,
+        status: ThreadStatus | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> int:
+        """Count threads matching filters.
+
+        Args:
+            metadata: Thread metadata to filter on.
+            values: State values to filter on.
+            status: Thread status to filter on.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            int: Number of threads matching the criteria.
+        """
+        payload: dict[str, Any] = {}
+        if metadata:
+            payload["metadata"] = metadata
+        if values:
+            payload["values"] = values
+        if status:
+            payload["status"] = status
+        return self.http.post(
+            "/threads/count", json=payload, headers=headers, params=params
+        )
+
+    def copy(
+        self,
+        thread_id: str,
+        *,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> None:
+        """Copy a thread.
+
+        Args:
+            thread_id: The ID of the thread to copy.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            `None`
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:2024")
+            client.threads.copy(
+                thread_id="my_thread_id"
+            )
+            ```
+
+        """
+        return self.http.post(
+            f"/threads/{thread_id}/copy", json=None, headers=headers, params=params
+        )
+
+    def prune(
+        self,
+        thread_ids: Sequence[str],
+        *,
+        strategy: PruneStrategy = "delete",
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> dict[str, Any]:
+        """Prune threads by ID.
+
+        Args:
+            thread_ids: List of thread IDs to prune.
+            strategy: The prune strategy. `"delete"` removes threads entirely.
+                `"keep_latest"` prunes old checkpoints but keeps threads and their
+                latest state. Defaults to `"delete"`.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            A dict containing `pruned_count` (number of threads pruned).
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:2024")
+            result = client.threads.prune(
+                thread_ids=["thread_1", "thread_2"],
+            )
+            print(result)  # {'pruned_count': 2}
+            ```
+
+        """
+        payload: dict[str, Any] = {
+            "thread_ids": thread_ids,
+        }
+        if strategy != "delete":
+            payload["strategy"] = strategy
+        return self.http.post(
+            "/threads/prune", json=payload, headers=headers, params=params
+        )
+
+    def get_state(
+        self,
+        thread_id: str,
+        checkpoint: Checkpoint | None = None,
+        checkpoint_id: str | None = None,  # deprecated
+        *,
+        subgraphs: bool = False,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> ThreadState:
+        """Get the state of a thread.
+
+        Args:
+            thread_id: The ID of the thread to get the state of.
+            checkpoint: The checkpoint to get the state of.
+            subgraphs: Include subgraphs states.
+            headers: Optional custom headers to include with the request.
+
+        Returns:
+            The thread of the state.
+
+        ???+ example "Example Usage"
+
+            ```python
+            client = get_sync_client(url="http://localhost:2024")
+            thread_state = client.threads.get_state(
+                thread_id="my_thread_id",
+                checkpoint_id="my_checkpoint_id"
+            )
+            print(thread_state)
+            ```
+
+            ```shell
+            ----------------------------------------------------------------------------------------------------------------------------------------------------------------------
+
+            {
+                'values': {
+                    'messages': [
+                        {
+                            'content': 'how are you?',
+                            'additional_kwargs': {},
+                            'response_metadata': {},
+                            'type': 'human',
+                            'name': None,
+                            'id': 'fe0a5778-cfe9-42ee-b807-0adaa1873c10',
+                            'example': False
+                        },
+                        {
+                            'content': "I'm doing well, thanks for asking! I'm an AI assistant created by Anthropic to be helpful, honest, and harmless.",
+                            'additional_kwargs': {},
+                            'response_metadata': {},
+                            'type': 'ai',
+                            'name': None,
+                            'id': 'run-159b782c-b679-4830-83c6-cef87798fe8b',
+                            'example': False,
+                            'tool_calls': [],
+                            'invalid_tool_calls': [],
+                            'usage_metadata': None
+                        }
+                    ]
+                },
+                'next': [],
+                'checkpoint':
+                    {
+                        'thread_id': 'e2496803-ecd5-4e0c-a779-3226296181c2',
+                        'checkpoint_ns': '',
+                        'checkpoint_id': '1ef4a9b8-e6fb-67b1-8001-abd5184439d1'
+                    }
+                'metadata':
+                    {
+                        'step': 1,
+                        'run_id': '1ef4a9b8-d7da-679a-a45a-872054341df2',
+                        'source': 'loop',
+                        'writes':
+                            {
+                                'agent':
+                                    {
+                                        'messages': [
+                                            {
+                                                'id': 'run-159b782c-b679-4830-83c6-cef87798fe8b',
+                                                'name': None,
+                                                'type': 'ai',
+                                                'content': "I'm doing well, thanks for asking! I'm an AI assistant created by Anthropic to be helpful, honest, and harmless.",
+                                                'example': False,
+                                                'tool_calls': [],
+                                                'usage_metadata': None,
+                                                'additional_kwargs': {},
+                                                'response_metadata': {},
+                                                'invalid_tool_calls': []
+                                            }
+                                        ]
+                                    }
+                            },
+                'user_id': None,
+                'graph_id': 'agent',
+                'thread_id': 'e2496803-ecd5-4e0c-a779-3226296181c2',
+                'created_by': 'system',
+                'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca'},
+                'created_at': '2024-07-25T15:35:44.184703+00:00',
+                'parent_config':
+                    {
+                        'thread_id': 'e2496803-ecd5-4e0c-a779-3226296181c2',
+                        'checkpoint_ns': '',
+                        'checkpoint_id': '1ef4a9b8-d80d-6fa7-8000-9300467fad0f'
+                    }
+            }
+            ```
+
+        """
+        if checkpoint:
+            return self.http.post(
+                f"/threads/{thread_id}/state/checkpoint",
+                json={"checkpoint": checkpoint, "subgraphs": subgraphs},
+                headers=headers,
+                params=params,
+            )
+        elif checkpoint_id:
+            get_params = {"subgraphs": subgraphs}
+            if params:
+                get_params = {**get_params, **dict(params)}
+            return self.http.get(
+                f"/threads/{thread_id}/state/{checkpoint_id}",
+                params=get_params,
+                headers=headers,
+            )
+        else:
+            get_params = {"subgraphs": subgraphs}
+            if params:
+                get_params = {**get_params, **dict(params)}
+            return self.http.get(
+                f"/threads/{thread_id}/state",
+                params=get_params,
+                headers=headers,
+            )
+
+    def update_state(
+        self,
+        thread_id: str,
+        values: dict[str, Any] | Sequence[dict] | None,
+        *,
+        as_node: str | None = None,
+        checkpoint: Checkpoint | None = None,
+        checkpoint_id: str | None = None,  # deprecated
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> ThreadUpdateStateResponse:
+        """Update the state of a thread.
+
+        Args:
+            thread_id: The ID of the thread to update.
+            values: The values to update the state with.
+            as_node: Update the state as if this node had just executed.
+            checkpoint: The checkpoint to update the state of.
+            headers: Optional custom headers to include with the request.
+
+        Returns:
+            Response after updating a thread's state.
+
+        ???+ example "Example Usage"
+
+            ```python
+
+            response = await client.threads.update_state(
+                thread_id="my_thread_id",
+                values={"messages":[{"role": "user", "content": "hello!"}]},
+                as_node="my_node",
+            )
+            print(response)
+
+            ----------------------------------------------------------------------------------------------------------------------------------------------------------------------
+
+            {
+                'checkpoint': {
+                    'thread_id': 'e2496803-ecd5-4e0c-a779-3226296181c2',
+                    'checkpoint_ns': '',
+                    'checkpoint_id': '1ef4a9b8-e6fb-67b1-8001-abd5184439d1',
+                    'checkpoint_map': {}
+                }
+            }
+            ```
+
+        """
+        payload: dict[str, Any] = {
+            "values": values,
+        }
+        if checkpoint_id:
+            payload["checkpoint_id"] = checkpoint_id
+        if checkpoint:
+            payload["checkpoint"] = checkpoint
+        if as_node:
+            payload["as_node"] = as_node
+        return self.http.post(
+            f"/threads/{thread_id}/state", json=payload, headers=headers, params=params
+        )
+
+    def get_history(
+        self,
+        thread_id: str,
+        *,
+        limit: int = 10,
+        before: str | Checkpoint | None = None,
+        metadata: Mapping[str, Any] | None = None,
+        checkpoint: Checkpoint | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> list[ThreadState]:
+        """Get the state history of a thread.
+
+        Args:
+            thread_id: The ID of the thread to get the state history for.
+            checkpoint: Return states for this subgraph. If empty defaults to root.
+            limit: The maximum number of states to return.
+            before: Return states before this checkpoint.
+            metadata: Filter states by metadata key-value pairs.
+            headers: Optional custom headers to include with the request.
+
+        Returns:
+            The state history of the `Thread`.
+
+        ???+ example "Example Usage"
+
+            ```python
+
+            thread_state = client.threads.get_history(
+                thread_id="my_thread_id",
+                limit=5,
+                before="my_timestamp",
+                metadata={"name":"my_name"}
+            )
+            ```
+
+        """
+        payload: dict[str, Any] = {
+            "limit": limit,
+        }
+        if before:
+            payload["before"] = before
+        if metadata:
+            payload["metadata"] = metadata
+        if checkpoint:
+            payload["checkpoint"] = checkpoint
+        return self.http.post(
+            f"/threads/{thread_id}/history",
+            json=payload,
+            headers=headers,
+            params=params,
+        )
+
+    def join_stream(
+        self,
+        thread_id: str,
+        *,
+        stream_mode: ThreadStreamMode | Sequence[ThreadStreamMode] = "run_modes",
+        last_event_id: str | None = None,
+        headers: Mapping[str, str] | None = None,
+        params: QueryParamTypes | None = None,
+    ) -> Iterator[StreamPart]:
+        """Get a stream of events for a thread.
+
+        Args:
+            thread_id: The ID of the thread to get the stream for.
+            last_event_id: The ID of the last event to get.
+            headers: Optional custom headers to include with the request.
+            params: Optional query parameters to include with the request.
+
+        Returns:
+            An iterator of stream parts.
+
+        ???+ example "Example Usage"
+
+            ```python
+
+            for chunk in client.threads.join_stream(
+                thread_id="my_thread_id",
+                last_event_id="my_event_id",
+                stream_mode="run_modes",
+            ):
+                print(chunk)
+            ```
+
+        """
+        query_params = {
+            "stream_mode": stream_mode,
+        }
+        if params:
+            query_params.update(params)
+        return self.http.stream(
+            f"/threads/{thread_id}/stream",
+            "GET",
+            headers={
+                **({"Last-Event-ID": last_event_id} if last_event_id else {}),
+                **(headers or {}),
+            },
+            params=query_params,
+        )

libs/sdk-py/langgraph_sdk/auth/__init__.py

@@ -72,8 +72,13 @@ class Auth:
             assert params.get("metadata", {}).get("owner") == "allowed_user"
 
         @auth.on.store
-        async def authorize_store(ctx: Auth.types.AuthContext, value: Auth.types.on):
-            assert ctx.user.identity in value["namespace"], "Not authorized"
+        async def authorize_store(ctx: Auth.types.AuthContext, value: Auth.types.on.store.value):
+            # Automatically scope all store operations to the user's namespace.
+            namespace = tuple(value["namespace"]) if value.get("namespace") else ()
+            assert isinstance(namespace, tuple)
+            if not namespace or namespace[0] != ctx.user.identity:
+                namespace = (ctx.user.identity, *namespace)
+            value["namespace"] = namespace
         ```
 
     ???+ note "Request Processing Flow"
@@ -170,13 +175,32 @@ class Auth:
             ```
 
             Auth for the `store` resource is a bit different since its structure is developer defined.
-            You typically want to enforce user creds in the namespace.
+            You typically want to scope store operations by rewriting the namespace to include the user's identity.
+            The `value` dict is mutable — changes to `value["namespace"]` are used by the server for the actual operation.
 
             ```python
             @auth.on.store
-            async def check_store_access(ctx: AuthContext, value: Auth.types.on) -> bool:
-                # Assuming you structure your store like (store.aput((user_id, application_context), key, value))
-                assert value["namespace"][0] == ctx.user.identity
+            async def authorize_store(ctx: AuthContext, value: Auth.types.on.store.value):
+                # Automatically scope all store operations to the user's namespace.
+                namespace = tuple(value["namespace"]) if value.get("namespace") else ()
+                assert isinstance(namespace, tuple)
+                if not namespace or namespace[0] != ctx.user.identity:
+                    namespace = (ctx.user.identity, *namespace)
+                value["namespace"] = namespace
+            ```
+
+            You can also register handlers for specific store actions:
+
+            ```python
+            @auth.on.store.put
+            async def on_put(ctx: AuthContext, value: Auth.types.on.store.put.value):
+                # value has typed fields: namespace, key, value, index
+                ...
+
+            @auth.on.store.get
+            async def on_get(ctx: AuthContext, value: Auth.types.on.store.get.value):
+                # value has typed fields: namespace, key
+                ...
             ```
         """
         # These are accessed by the API. Changes to their names or types is
@@ -483,9 +507,85 @@ class _CronsOn(
     Search = types.CronsSearch
 
 
+class _StoreActionOn(typing.Generic[T]):
+    """Decorator for registering a handler for a specific store action."""
+
+    def __init__(
+        self,
+        auth: Auth,
+        action: typing.Literal["put", "get", "search", "delete", "list_namespaces"],
+        value: type[T],
+    ) -> None:
+        self.auth = auth
+        self.action = action
+        self.value = value
+
+    def __call__(self, fn: _ActionHandler[T]) -> _ActionHandler[T]:
+        _validate_handler(fn)
+        _register_handler(self.auth, "store", self.action, fn)
+        return fn
+
+
 class _StoreOn:
     def __init__(self, auth: Auth) -> None:
         self._auth = auth
+        self.put = _StoreActionOn(auth, "put", types.StorePut)
+        """Register a handler for store put operations.
+
+        ???+ example "Example"
+            ```python
+            @auth.on.store.put
+            async def on_store_put(ctx: Auth.types.AuthContext, value: Auth.types.on.store.put.value):
+                # Scope puts to user's namespace
+                ...
+            ```
+        """
+        self.get = _StoreActionOn(auth, "get", types.StoreGet)
+        """Register a handler for store get operations.
+
+        ???+ example "Example"
+            ```python
+            @auth.on.store.get
+            async def on_store_get(ctx: Auth.types.AuthContext, value: Auth.types.on.store.get.value):
+                # Scope gets to user's namespace
+                ...
+            ```
+        """
+        self.search = _StoreActionOn(auth, "search", types.StoreSearch)
+        """Register a handler for store search operations.
+
+        ???+ example "Example"
+            ```python
+            @auth.on.store.search
+            async def on_store_search(ctx: Auth.types.AuthContext, value: Auth.types.on.store.search.value):
+                # Scope searches to user's namespace
+                ...
+            ```
+        """
+        self.delete = _StoreActionOn(auth, "delete", types.StoreDelete)
+        """Register a handler for store delete operations.
+
+        ???+ example "Example"
+            ```python
+            @auth.on.store.delete
+            async def on_store_delete(ctx: Auth.types.AuthContext, value: Auth.types.on.store.delete.value):
+                # Scope deletes to user's namespace
+                ...
+            ```
+        """
+        self.list_namespaces = _StoreActionOn(
+            auth, "list_namespaces", types.StoreListNamespaces
+        )
+        """Register a handler for store list_namespaces operations.
+
+        ???+ example "Example"
+            ```python
+            @auth.on.store.list_namespaces
+            async def on_list_ns(ctx: Auth.types.AuthContext, value: Auth.types.on.store.list_namespaces.value):
+                # Scope namespace listing to user's prefix
+                ...
+            ```
+        """
 
     @typing.overload
     def __call__(

libs/sdk-py/langgraph_sdk/auth/types.py

@@ -402,7 +402,7 @@ class AuthContext(BaseAuthContext):
         "list_namespaces",
     ]
     """The action being performed on the resource.
-    
+
     Most resources support the following actions:
     - create: Create a new resource
     - read: Read information about a resource
@@ -411,8 +411,10 @@ class AuthContext(BaseAuthContext):
     - search: Search for resources
 
     The store supports the following actions:
-    - put: Add or update a document in the store
-    - get: Get a document from the store
+    - put: Add or update an item in the store
+    - get: Get an item from the store
+    - search: Search for items within a namespace prefix
+    - delete: Delete an item from the store
     - list_namespaces: List the namespaces in the store
     """
 
@@ -851,20 +853,34 @@ class CronsSearch(typing.TypedDict, total=False):
 
 
 class StoreGet(typing.TypedDict):
-    """Operation to retrieve a specific item by its namespace and key."""
+    """Operation to retrieve a specific item by its namespace and key.
+
+    This dict is mutable — auth handlers can modify `namespace` to enforce
+    access scoping (e.g., prepending the user's identity).
+    """
 
     namespace: tuple[str, ...]
-    """Hierarchical path that uniquely identifies the item's location."""
+    """Hierarchical path that uniquely identifies the item's location.
+
+    Auth handlers can modify this to enforce per-user scoping.
+    """
 
     key: str
     """Unique identifier for the item within its specific namespace."""
 
 
 class StoreSearch(typing.TypedDict):
-    """Operation to search for items within a specified namespace hierarchy."""
+    """Operation to search for items within a specified namespace hierarchy.
+
+    This dict is mutable — auth handlers can modify `namespace` to enforce
+    access scoping (e.g., prepending the user's identity).
+    """
 
     namespace: tuple[str, ...]
-    """Prefix filter for defining the search scope."""
+    """Prefix filter for defining the search scope.
+
+    Auth handlers can modify this to enforce per-user scoping.
+    """
 
     filter: dict[str, typing.Any] | None
     """Key-value pairs for filtering results based on exact matches or comparison operators."""
@@ -876,14 +892,22 @@ class StoreSearch(typing.TypedDict):
     """Number of matching items to skip for pagination."""
 
     query: str | None
-    """Naturalj language search query for semantic search capabilities."""
+    """Natural language search query for semantic search capabilities."""
 
 
 class StoreListNamespaces(typing.TypedDict):
-    """Operation to list and filter namespaces in the store."""
+    """Operation to list and filter namespaces in the store.
+
+    This dict is mutable — auth handlers can modify `namespace` (the prefix)
+    to enforce access scoping (e.g., prepending the user's identity).
+    """
 
     namespace: tuple[str, ...] | None
-    """Prefix filter namespaces."""
+    """Prefix filter for namespaces. Can be `None` if no prefix was provided.
+
+    Auth handlers can modify this to enforce per-user scoping. When `None`,
+    handlers should set it to `(user_id,)` to scope listing to the user's namespaces.
+    """
 
     suffix: tuple[str, ...] | None
     """Optional conditions for filtering namespaces."""
@@ -903,10 +927,17 @@ class StoreListNamespaces(typing.TypedDict):
 
 
 class StorePut(typing.TypedDict):
-    """Operation to store, update, or delete an item in the store."""
+    """Operation to store, update, or delete an item in the store.
+
+    This dict is mutable — auth handlers can modify `namespace` to enforce
+    access scoping (e.g., prepending the user's identity).
+    """
 
     namespace: tuple[str, ...]
-    """Hierarchical path that identifies the location of the item."""
+    """Hierarchical path that identifies the location of the item.
+
+    Auth handlers can modify this to enforce per-user scoping.
+    """
 
     key: str
     """Unique identifier for the item within its namespace."""
@@ -919,10 +950,17 @@ class StorePut(typing.TypedDict):
 
 
 class StoreDelete(typing.TypedDict):
-    """Operation to delete an item from the store."""
+    """Operation to delete an item from the store.
+
+    This dict is mutable — auth handlers can modify `namespace` to enforce
+    access scoping (e.g., prepending the user's identity).
+    """
 
     namespace: tuple[str, ...]
-    """Hierarchical path that uniquely identifies the item's location."""
+    """Hierarchical path that uniquely identifies the item's location.
+
+    Auth handlers can modify this to enforce per-user scoping.
+    """
 
     key: str
     """Unique identifier for the item within its specific namespace."""

libs/sdk-py/langgraph_sdk/runtime.py

@@ -0,0 +1,238 @@
+from __future__ import annotations
+
+import sys
+from dataclasses import dataclass, field
+from typing import TYPE_CHECKING, Generic, Literal, TypeVar
+
+if sys.version_info >= (3, 13):
+    ContextT = TypeVar("ContextT", default=None)
+else:
+    ContextT = TypeVar("ContextT")
+
+if sys.version_info >= (3, 12):
+    from typing import TypeAliasType
+else:
+    from typing_extensions import TypeAliasType
+
+from langgraph_sdk.auth.types import BaseUser
+
+if TYPE_CHECKING:
+    from langgraph.store.base import BaseStore
+
+__all__ = [
+    "AccessContext",
+    "ServerRuntime",
+]
+
+
+AccessContext = Literal[
+    "threads.create_run",
+    "threads.update",
+    "threads.read",
+    "assistants.read",
+]
+
+
+@dataclass(kw_only=True, slots=True, frozen=True)
+class _ServerRuntimeBase(Generic[ContextT]):
+    """Base for server runtime variants.
+
+    !!! warning "Beta"
+        This API is in beta and may change in future releases.
+    """
+
+    access_context: AccessContext
+    """Why the graph factory is being called.
+
+    The server accesses graphs in several contexts beyond just executing runs.
+    For example, it calls the graph factory to retrieve schemas, render the
+    graph structure, or read state history. This field tells you which
+    operation triggered the current call.
+
+    In all contexts, the returned graph must have the same topology (nodes,
+    edges, state schema) as the graph used for execution. Use
+    `.execution_runtime` to conditionally set up expensive *resources*
+    (MCP servers, DB connections) without changing the graph structure.
+
+    Write contexts (graph is used to write state):
+
+    - `threads.create_run` (`graph.astream`) — full graph execution
+      (nodes + edges). `context` is available (use `.execution_runtime`
+      to narrow).
+    - `threads.update` (`graph.aupdate_state`) — does NOT execute node
+      functions or evaluate edges. Only runs the node's channel writers
+      to apply the provided values to state channels as if the specified
+      node had returned them. Reducers are applied and channel triggers
+      are set, so the next `invoke`/`stream` call will evaluate edges
+      from that node to determine the next step. Does not need access to
+      external resources, but a different graph topology will apply
+      writes to the wrong channels.
+
+    Read state contexts (graph used to format the returned
+    `StateSnapshot`). A different topology may cause `get_state` to
+    report incorrect pending tasks. Note that `useStream` uses the state
+    history endpoint to render interrupts and support branching:
+
+    - `threads.read` (`graph.aget_state`, `graph.aget_state_history`) —
+      the graph structure informs which tasks to include in the prepared
+      view of the latest checkpoint and how to process subgraphs.
+
+    Introspection contexts (graph structure only, no execution).
+    A different topology may cause schemas and visualizations to not
+    match actual execution:
+
+    - `assistants.read` (`graph.aget_graph`, `graph.aget_subgraphs`,
+      `graph.aget_schemas`) — return the graph definition, subgraph
+      definitions, and input/output/config schemas. Used for
+      visualization in the studio UI and to populate schemas for MCP,
+      A2A, and other protocol integrations.
+    """
+
+    user: BaseUser | None = field(default=None)
+    """The authenticated user, or `None` if no custom auth is configured."""
+
+    store: BaseStore
+    """Store for the graph run, enabling persistence and memory."""
+
+    @property
+    def execution_runtime(self) -> _ExecutionRuntime[ContextT] | None:
+        """Narrow to the execution runtime, or `None` if not in an execution context.
+
+        When the server calls the graph factory for `threads.create_run`, the returned
+        object provides access to `context` (typed by the graph's
+        `context_schema`). For all other access contexts (introspection, state
+        reads, state updates), this returns `None`.
+
+        Use this to conditionally set up expensive resources (MCP tool servers,
+        database connections, etc.) that are only needed during execution:
+
+        ```python
+        import contextlib
+        from langgraph_sdk.runtime import ServerRuntime
+
+        @contextlib.asynccontextmanager
+        async def my_factory(runtime: ServerRuntime[MyCtx]):
+            if ert := runtime.execution_runtime:
+                # Only connect to MCP servers when actually executing a run.
+                # Introspection calls (get_schema, get_graph, ...) skip this.
+                mcp_tools = await connect_mcp(ert.context.mcp_endpoint)
+                yield create_agent(model, tools=mcp_tools)
+                await disconnect_mcp()
+            else:
+                yield create_agent(model, tools=[])
+        ```
+        """
+        if isinstance(self, _ExecutionRuntime):
+            return self
+        return None
+
+    def ensure_user(self) -> BaseUser:
+        """Return the authenticated user, or raise if not available.
+
+        When custom auth is configured, `user` is set for all access contexts
+        (the factory is only called from HTTP handlers where the auth
+        middleware has already run). This method raises only when no custom
+        auth is configured.
+
+        Raises:
+            PermissionError: If no user is authenticated.
+        """
+        if self.user is None:
+            raise PermissionError(
+                f"No authenticated user available in access_context='{self.access_context}'. "
+                "Ensure custom auth is configured for the server."
+            )
+        return self.user
+
+
+@dataclass(kw_only=True, slots=True, frozen=True)
+class _ExecutionRuntime(_ServerRuntimeBase[ContextT], Generic[ContextT]):
+    """Runtime for `threads.create_run` — the graph will be fully executed.
+
+    Access this via `.execution_runtime` on `ServerRuntime`. Do not
+    construct directly.
+
+    !!! warning "Beta"
+        This API is in beta and may change in future releases.
+    """
+
+    context: ContextT = field(default=None)  # type: ignore[assignment]
+    """The graph run context, typed by the graph's `context_schema`.
+
+    Only available during `threads.create_run`.
+    """
+
+
+@dataclass(kw_only=True, slots=True, frozen=True)
+class _ReadRuntime(_ServerRuntimeBase[ContextT], Generic[ContextT]):
+    """Runtime for non-execution access contexts.
+
+    Used for introspection (`assistants.read`), state operations
+    (`threads.read`), and state updates (`threads.update`).
+    No `context` is available.
+
+    !!! warning "Beta"
+        This API is in beta and may change in future releases.
+    """
+
+
+ServerRuntime = TypeAliasType(
+    "ServerRuntime",
+    _ExecutionRuntime[ContextT] | _ReadRuntime[ContextT],
+    type_params=(ContextT,),
+)
+"""Runtime context passed to graph builder factories within the Agent Server.
+
+Requires version 0.7.30 or later of the agent server.
+
+The server calls your graph factory in multiple contexts: executing runs,
+reading state, fetching schemas, and more. `ServerRuntime` provides
+the authenticated user, store, and access context for every call. Use
+`.execution_runtime` to narrow to the execution variant and access
+`context`.
+
+Example — conditionally initialize MCP tools only during execution:
+
+```python
+import contextlib
+from dataclasses import dataclass
+
+from langchain.agents import create_agent
+from langgraph_sdk.runtime import ServerRuntime
+from my_agent import connect_mcp, disconnect_mcp
+
+@dataclass
+class MyCtx:
+    mcp_endpoint: str
+
+_readonly_agent = create_agent("anthropic:claude-3-5-haiku", tools=[])
+
+@contextlib.asynccontextmanager
+async def my_factory(runtime: ServerRuntime[MyCtx]):
+    if ert := runtime.execution_runtime:
+        # Only connect to MCP servers for actual runs.
+        # Schema / graph introspection calls skip this.
+        user_id = runtime.ensure_user().identity
+        mcp_tools = await connect_mcp(ert.context.mcp_endpoint, user_id)
+        yield create_agent("anthropic:claude-3-5-haiku", tools=mcp_tools)
+        await disconnect_mcp()
+    else:
+        yield _readonly_agent
+```
+
+Example — simple factory that ignores context:
+
+```python
+from langgraph_sdk.runtime import ServerRuntime
+
+def build_graph(user: BaseUser) -> CompiledGraph:
+    ...
+
+async def my_factory(runtime: ServerRuntime) -> CompiledGraph:
+    # No generic needed if you don't use context.
+    return build_graph(runtime.ensure_user())
+```
+
+!!! warning "Beta"
+    This API is in beta and may change in future releases.
+"""

libs/sdk-py/langgraph_sdk/schema.py

@@ -117,6 +117,13 @@ Specifies behavior if the thread doesn't exist:
 - "reject": Reject the operation if the thread doesn't exist.
 """
 
+PruneStrategy = Literal["delete", "keep_latest"]
+"""
+Strategy for pruning threads:
+- "delete": Remove threads entirely.
+- "keep_latest": Prune old checkpoints but keep threads and their latest state.
+"""
+
 CancelAction = Literal["interrupt", "rollback"]
 """
 Action to take when cancelling the run.
@@ -124,6 +131,14 @@ Action to take when cancelling the run.
 - "rollback": Cancel the run. Then delete the run and associated checkpoints.
 """
 
+BulkCancelRunsStatus = Literal["pending", "running", "all"]
+"""
+Filter runs by status when bulk-cancelling:
+- "pending": Cancel only pending runs.
+- "running": Cancel only running runs.
+- "all": Cancel all runs regardless of status.
+"""
+
 AssistantSortBy = Literal[
     "assistant_id", "graph_id", "name", "created_at", "updated_at"
 ]
@@ -131,13 +146,21 @@ AssistantSortBy = Literal[
 The field to sort by.
 """
 
-ThreadSortBy = Literal["thread_id", "status", "created_at", "updated_at"]
+ThreadSortBy = Literal[
+    "thread_id", "status", "created_at", "updated_at", "state_updated_at"
+]
 """
 The field to sort by.
 """
 
 CronSortBy = Literal[
-    "cron_id", "assistant_id", "thread_id", "created_at", "updated_at", "next_run_date"
+    "cron_id",
+    "assistant_id",
+    "thread_id",
+    "created_at",
+    "updated_at",
+    "next_run_date",
+    "end_time",
 ]
 """
 The field to sort by.

libs/sdk-py/pyproject.toml

@@ -11,7 +11,7 @@ requires-python = ">=3.10"
 readme = "README.md"
 license = "MIT"
 license-files = ['LICENSE']
-dependencies = ["httpx>=0.25.2", "orjson>=3.10.1"]
+dependencies = ["httpx>=0.25.2", "orjson>=3.11.5"]
 
 [tool.hatch.version]
 path = "langgraph_sdk/__init__.py"
@@ -30,15 +30,16 @@ test = [
     "pytest-watch",
 ]
 lint = [
-    "ruff==0.14.11",
+    "ruff==0.15.1",
     "codespell",
-    "mypy==1.19.0",
-    "ty==0.0.1a27",
+    "mypy==1.19.1",
+    "ty==0.0.17",
     "starlette",
 ]
 dev = [
   { include-group = "test" },
   { include-group = "lint" },
+  "langgraph",
   "pydantic>=2.12.4",
 ]
 
@@ -52,6 +53,9 @@ asyncio_mode = "auto"
 [tool.uv]
 default-groups = ['dev']
 
+[tool.uv.sources]
+langgraph = { path = "../langgraph", editable = true }
+
 [tool.ruff]
 exclude = ["venv", ".venv", "build", "dist"]
 [tool.ruff.lint]

libs/sdk-py/tests/test_client_exports.py

@@ -0,0 +1,91 @@
+"""Test that all expected symbols are exported from langgraph_sdk.client.
+
+This test ensures backwards compatibility during refactoring.
+"""
+
+import httpx
+
+from langgraph_sdk import get_client as public_get_client
+from langgraph_sdk import get_sync_client as public_get_sync_client
+from langgraph_sdk.client import (
+    AssistantsClient,
+    CronClient,
+    HttpClient,
+    LangGraphClient,
+    RunsClient,
+    StoreClient,
+    SyncAssistantsClient,
+    SyncCronClient,
+    SyncHttpClient,
+    SyncLangGraphClient,
+    SyncRunsClient,
+    SyncStoreClient,
+    SyncThreadsClient,
+    ThreadsClient,
+    _adecode_json,
+    _aencode_json,
+    _decode_json,
+    _encode_json,
+    configure_loopback_transports,
+    get_client,
+    get_sync_client,
+)
+
+
+def test_client_exports():
+    """Verify all expected symbols can be imported from langgraph_sdk.client."""
+    # Factory functions (public API)
+    assert callable(get_client)
+    assert callable(get_sync_client)
+
+    # Top-level client classes
+    assert LangGraphClient is not None
+    assert SyncLangGraphClient is not None
+
+    # HTTP client classes
+    assert HttpClient is not None
+    assert SyncHttpClient is not None
+
+    # Resource client classes - Async
+    assert AssistantsClient is not None
+    assert ThreadsClient is not None
+    assert RunsClient is not None
+    assert CronClient is not None
+    assert StoreClient is not None
+
+    # Resource client classes - Sync
+    assert SyncAssistantsClient is not None
+    assert SyncThreadsClient is not None
+    assert SyncRunsClient is not None
+    assert SyncCronClient is not None
+    assert SyncStoreClient is not None
+
+    # Internal utilities (used by tests)
+    assert callable(_aencode_json)
+    assert callable(_adecode_json)
+
+    # Sync JSON utilities (might be used internally)
+    assert callable(_encode_json)
+    assert callable(_decode_json)
+
+    # Loopback transport configuration (used by langgraph-api)
+    assert callable(configure_loopback_transports)
+
+
+def test_public_api_exports():
+    """Verify public API exports from langgraph_sdk package."""
+    assert callable(public_get_client)
+    assert callable(public_get_sync_client)
+
+
+def test_client_instantiation():
+    """Verify that we can instantiate clients."""
+    # Test async client instantiation
+    async_http = httpx.AsyncClient(base_url="http://test.example.com")
+    async_client = HttpClient(async_http)
+    assert async_client is not None
+
+    # Test sync client instantiation
+    sync_http = httpx.Client(base_url="http://test.example.com")
+    sync_client = SyncHttpClient(sync_http)
+    assert sync_client is not None

libs/sdk-py/tests/test_client_stream.py

@@ -19,7 +19,7 @@ class AsyncListByteStream(httpx.AsyncByteStream):
         self._chunks = list(chunks)
         self._exc = exc
 
-    async def __aiter__(self):  # type: ignore[override]
+    async def __aiter__(self):
         for chunk in self._chunks:
             yield chunk
         if self._exc is not None:
@@ -34,7 +34,7 @@ class ListByteStream(httpx.ByteStream):
         self._chunks = list(chunks)
         self._exc = exc
 
-    def __iter__(self):  # type: ignore[override]
+    def __iter__(self):
         yield from self._chunks
         if self._exc is not None:
             raise self._exc

libs/sdk-py/tests/test_errors.py

@@ -65,7 +65,7 @@ def test_raise_for_status_typed_maps_exceptions_and_sets_status_code(
     with pytest.raises(exc_type) as ei:
         _raise_for_status_typed(r)
 
-    err = cast("APIStatusError", ei.value)
+    err = ei.value
     assert err.status_code == status
     # response attribute should be present and match
     assert err.response.status_code == status
@@ -113,7 +113,7 @@ def test_error_message_in_str_and_args() -> None:
     r = make_response(422, json_body={"message": "Validation failed"})
     with pytest.raises(UnprocessableEntityError) as ei:
         _raise_for_status_typed(r)
-    err = cast("UnprocessableEntityError", ei.value)
+    err = ei.value
     assert str(err) == "Validation failed"
     assert err.args == ("Validation failed",)
     assert err.message == "Validation failed"