checkpoint-postgres/sqlite 2.0.12/2.0.3

![Screenshot 2025-01-15 at 1 03
45 PM](https://github.com/user-attachments/assets/c7a6d5b7-cc42-4616-bba0-4352c2f922bc)

.github/workflows/_test_langgraph.yml

@@ -17,21 +17,11 @@ jobs:
           - "3.11"
           - "3.12"
           - "3.13"
-        core-version:
-          - "latest"
-        ff-send-v2:
-          - "false"
-        include:
-          - python-version: "3.11"
-            core-version: ">=0.2.42,<0.3.0"
-          - python-version: "3.11"
-            core-version: "latest"
-            ff-send-v2: "true"
 
     defaults:
       run:
         working-directory: libs/langgraph
-    name: "test #${{ matrix.python-version }} (langchain-core: ${{ matrix.core-version }}, ff-send-v2: ${{ matrix.ff-send-v2 }})"
+    name: "test #${{ matrix.python-version }}"
     steps:
       - uses: actions/checkout@v4
       - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
@@ -51,14 +41,9 @@ jobs:
         shell: bash
         run: |
           poetry install --with dev
-          if [ "${{ matrix.core-version }}" != "latest" ]; then
-            poetry run pip install "langchain-core${{ matrix.core-version }}"
-          fi
 
       - name: Run tests
         shell: bash
-        env:
-          LANGGRAPH_FF_SEND_V2: ${{ matrix.ff-send-v2 }}
         run: |
           make test_parallel
 

.github/workflows/ci.yml

@@ -31,7 +31,6 @@ jobs:
             "libs/cli",
             "libs/checkpoint",
             "libs/checkpoint-sqlite",
-            "libs/checkpoint-duckdb",
             "libs/checkpoint-postgres",
             "libs/scheduler-kafka",
           ]
@@ -44,12 +43,12 @@ jobs:
     name: cd ${{ matrix.working-directory }}
     strategy:
       matrix:
-        working-directory: [
+        working-directory:
+          [
             "libs/cli",
             "libs/checkpoint",
             "libs/checkpoint-sqlite",
-            "libs/checkpoint-duckdb",
-            "libs/checkpoint-postgres"
+            "libs/checkpoint-postgres",
           ]
     uses: ./.github/workflows/_test.yml
     with:
@@ -76,7 +75,7 @@ jobs:
       - name: Set up Python
         uses: actions/setup-python@v5
         with:
-          python-version: '3.11'
+          python-version: "3.11"
       - name: Run check_sdk_methods script
         run: python .github/scripts/check_sdk_methods.py
 
@@ -109,9 +108,40 @@ jobs:
       - name: Build
         run: yarn build
 
+  test-js:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        working-directory:
+          - "libs/sdk-js"
+    defaults:
+      run:
+        working-directory: ${{ matrix.working-directory }}
+    steps:
+      - uses: actions/checkout@v3
+      - name: Setup Node.js (LTS)
+        uses: actions/setup-node@v3
+        with:
+          node-version: "20"
+          cache: "yarn"
+          cache-dependency-path: ${{ matrix.working-directory }}/yarn.lock
+      - name: Install dependencies
+        run: yarn install
+      - name: Run tests
+        run: yarn test
+
   ci_success:
     name: "CI Success"
-    needs: [lint, lint-js, test, test-langgraph, test-scheduler-kafka, integration-test]
+    needs:
+      [
+        lint,
+        lint-js,
+        test,
+        test-langgraph,
+        test-scheduler-kafka,
+        integration-test,
+        test-js,
+      ]
     if: |
       always()
     runs-on: ubuntu-latest

.github/workflows/deploy_docs.yml

@@ -85,10 +85,12 @@ jobs:
           if [ "${{ github.event_name }}" == "schedule" ] || [ "${{ github.event_name }}" == "workflow_dispatch" ] || ([ "${{ github.event_name }}" == "push" ] && [ "${{ github.ref }}" == "refs/heads/main" ]); then
             echo "Running link check on all HTML files matching notebooks in docs directory..."
             poetry run pytest -v \
-              --check-links-ignore "https://(api|web|docs)\.smith\.langchain\.com/.*" \
+              --check-links-ignore "https://(api|web|docs|academy)\.smith\.langchain\.com/.*" \
               --check-links-ignore "https://x.com/.*" \
               --check-links-ignore "https://github\.com/.*" \
               --check-links-ignore "http://localhost:8123/.*" \
+              --check-links-ignore "http://localhost:2024.*" \
+              --check-links-ignore "http://127.0.0.1:.*" \
               --check-links-ignore "/.*\.(ipynb|html)$" \
               --check-links-ignore "https://python\.langchain\.com/.*" \
               --check-links-ignore "https://openai\.com/.*" \
@@ -104,8 +106,10 @@ jobs:
             if [ -n "${CHANGED_FILES}" ]; then
               echo "Running link check on HTML files matching changed notebook files..."
               poetry run pytest -v \
-                --check-links-ignore "https://(api|web|docs)\.smith\.langchain\.com/.*" \
+                --check-links-ignore "https://(api|web|docs|academy)\.smith\.langchain\.com/.*" \
                 --check-links-ignore "http://localhost:8123/.*" \
+                --check-links-ignore "http://localhost:2024.*" \
+                --check-links-ignore "http://127.0.0.1:.*" \
                 --check-links-ignore "https://x.com/.*" \
                 --check-links-ignore "https://github\.com/.*" \
                 --check-links-ignore "/.*\.(ipynb|html)$" \

Makefile

@@ -13,7 +13,7 @@ serve-clean-docs: clean-docs
 	poetry run python -m mkdocs serve -c -f docs/mkdocs.yml --strict -w ./libs/langgraph
 
 serve-docs: build-typedoc
-	poetry run python -m mkdocs serve -f docs/mkdocs.yml -w ./libs/langgraph  -w ./libs/checkpoint --dirty
+	poetry run python -m mkdocs serve -f docs/mkdocs.yml -w ./libs/langgraph  -w ./libs/checkpoint -w ./libs/sdk-py --dirty
 
 clean-docs:
 	find ./docs/docs -name "*.ipynb" -type f -delete

README.md

@@ -8,7 +8,7 @@
 ⚡ Building language agents as graphs ⚡
 
 > [!NOTE]
-> Looking for the JS version? Click [here](https://github.com/langchain-ai/langgraphjs) ([JS docs](https://langchain-ai.github.io/langgraphjs/)).
+> Looking for the JS version? See the [JS repo](https://github.com/langchain-ai/langgraphjs) and the [JS docs](https://langchain-ai.github.io/langgraphjs/).
 
 ## Overview
 

docs/_scripts/_patch.py

@@ -0,0 +1,93 @@
+import functools
+
+from urllib3 import __version__ as urllib3version  # type: ignore[import-untyped]
+from urllib3 import connection  # type: ignore[import-untyped]
+
+
+def _ensure_str(s, encoding="utf-8", errors="strict") -> str:
+    if isinstance(s, str):
+        return s
+
+    if isinstance(s, bytes):
+        return s.decode(encoding, errors)
+    return str(s)
+
+
+# Copied from https://github.com/urllib3/urllib3/blob/1c994dfc8c5d5ecaee8ed3eb585d4785f5febf6e/src/urllib3/connection.py#L231
+def request(self, method, url, body=None, headers=None):
+    """Make the request.
+
+    This function is based on the urllib3 request method, with modifications
+    to handle potential issues when using vcrpy in concurrent workloads.
+
+    Args:
+        self: The HTTPConnection instance.
+        method (str): The HTTP method (e.g., 'GET', 'POST').
+        url (str): The URL for the request.
+        body (Optional[Any]): The body of the request.
+        headers (Optional[dict]): Headers to send with the request.
+
+    Returns:
+        The result of calling the parent request method.
+    """
+    # Update the inner socket's timeout value to send the request.
+    # This only triggers if the connection is re-used.
+    if getattr(self, "sock", None) is not None:
+        self.sock.settimeout(self.timeout)
+
+    if headers is None:
+        headers = {}
+    else:
+        # Avoid modifying the headers passed into .request()
+        headers = headers.copy()
+    if "user-agent" not in (_ensure_str(k.lower()) for k in headers):
+        headers["User-Agent"] = connection._get_default_user_agent()
+    # The above is all the same ^^^
+    # The following is different:
+    return self._parent_request(method, url, body=body, headers=headers)
+
+
+_PATCHED = False
+
+
+def patch_urllib3():
+    """Patch the request method of urllib3 to avoid type errors when using vcrpy.
+
+    In concurrent workloads (such as the tracing background queue), the
+    connection pool can get in a state where an HTTPConnection is created
+    before vcrpy patches the HTTPConnection class. In urllib3 >= 2.0 this isn't
+    a problem since they use the proper super().request(...) syntax, but in older
+    versions, super(HTTPConnection, self).request is used, resulting in a TypeError
+    since self is no longer a subclass of "HTTPConnection" (which at this point
+    is vcr.stubs.VCRConnection).
+
+    This method patches the class to fix the super() syntax to avoid mixed inheritance.
+    In the case of the LangSmith tracing logic, it doesn't really matter since we always
+    exclude cache checks for calls to LangSmith.
+
+    The patch is only applied for urllib3 versions older than 2.0.
+    """
+    global _PATCHED
+    if _PATCHED:
+        return
+    from packaging import version
+
+    if version.parse(urllib3version) >= version.parse("2.0"):
+        _PATCHED = True
+        return
+
+    # Lookup the parent class and its request method
+    parent_class = connection.HTTPConnection.__bases__[0]
+    parent_request = parent_class.request
+
+    def new_request(self, *args, **kwargs):
+        """Handle parent request.
+
+        This method binds the parent's request method to self and then
+        calls our modified request function.
+        """
+        self._parent_request = functools.partial(parent_request, self)
+        return request(self, *args, **kwargs)
+
+    connection.HTTPConnection.request = new_request
+    _PATCHED = True

docs/_scripts/generate_api_reference_links.py

@@ -6,6 +6,9 @@ import re
 from typing import List, Literal, Optional
 from typing_extensions import TypedDict
 
+
+from functools import lru_cache
+
 import nbformat
 from nbconvert.preprocessors import Preprocessor
 
@@ -47,6 +50,8 @@ MANUAL_API_REFERENCES_LANGGRAPH = [
     (["langgraph.graph"], "langgraph.constants", "END", "constants"),
     (["langgraph.constants"], "langgraph.types", "Send", "types"),
     (["langgraph.constants"], "langgraph.types", "Interrupt", "types"),
+    (["langgraph.constants"], "langgraph.types", "interrupt", "types"),
+    (["langgraph.constants"], "langgraph.types", "Command", "types"),
     ([], "langgraph.types", "RetryPolicy", "types"),
     ([], "langgraph.checkpoint.base", "Checkpoint", "checkpoints"),
     ([], "langgraph.checkpoint.base", "CheckpointMetadata", "checkpoints"),
@@ -83,8 +88,11 @@ _IMPORT_LANGCHAIN_RE = _make_regular_expression("langchain")
 _IMPORT_LANGGRAPH_RE = _make_regular_expression("langgraph")
 
 
-def _get_full_module_name(module_path, class_name) -> Optional[str]:
-    """Get full module name using inspect"""
+
+
+@lru_cache(maxsize=10_000)
+def _get_full_module_name(module_path: str, class_name: str) -> Optional[str]:
+    """Get full module name using inspect, with LRU cache to memoize results."""
     try:
         module = importlib.import_module(module_path)
         class_ = getattr(module, class_name)
@@ -95,13 +103,12 @@ def _get_full_module_name(module_path, class_name) -> Optional[str]:
             return module_path
         return module.__name__
     except AttributeError as e:
-        logger.warning(f"Could not find module for {class_name}, {e}")
+        logger.warning(f"API Reference: Could not find module for {class_name}, {e}")
         return None
     except ImportError as e:
-        logger.warning(f"Failed to load for class {class_name}, {e}")
+        logger.warning(f"API Reference: Failed to load for class {class_name}, {e}")
         return None
 
-
 def _get_doc_title(data: str, file_name: str) -> str:
     try:
         return re.findall(r"^#\s*(.*)", data, re.MULTILINE)[0]
@@ -115,10 +122,10 @@ def _get_doc_title(data: str, file_name: str) -> str:
 
 
 class ImportInformation(TypedDict):
-    imported: str  # imported class name
-    source: str  # module path
-    docs: str  # URL to the documentation
-    title: str  # Title of the document
+    imported: str  # The name of the class that was imported.
+    source: str  # The full module path from which the class was imported.
+    docs: str  # The URL pointing to the class's documentation.
+    title: str  # The title of the document where the import is used.
 
 
 def _get_imports(
@@ -211,36 +218,73 @@ def _get_imports(
     return imports
 
 
-class ImportPreprocessor(Preprocessor):
-    """A preprocessor to replace imports in each Python code cell with links to their
-    documentation and append the import info in a comment."""
+def get_imports(code: str, doc_title: str) -> List[ImportInformation]:
+    """Retrieve all import references from the given code for specified ecosystems.
 
-    def preprocess(self, nb, resources):
-        self.all_imports = []
-        file_name = os.path.basename(resources.get("metadata", {}).get("name", ""))
-        _DOC_TITLE = _get_doc_title(nb.cells[0].source, file_name)
+    Args:
+        code: The source code from which to extract import references.
+        doc_title: The documentation title associated with the code.
 
-        cells = []
-        for cell in nb.cells:
-            if cell.cell_type == "code":
-                cells.append(cell)
-                imports = _get_imports(
-                    cell.source, _DOC_TITLE, "langchain"
-                ) + _get_imports(cell.source, _DOC_TITLE, "langgraph")
-                if not imports:
-                    continue
+    Returns:
+        A list of import information for each import found.
+    """
+    ecosystems = ["langchain", "langgraph"]
+    all_imports = []
+    for package_ecosystem in ecosystems:
+        all_imports.extend(_get_imports(code, doc_title, package_ecosystem))
+    return all_imports
 
-                cells.append(
-                    nbformat.v4.new_markdown_cell(
-                        source=f"""
-<div>
-<b>API Reference:</b>
-{' | '.join(f'<a href="{imp["docs"]}">{imp["imported"]}</a>' for imp in imports)}
-</div>
-                    """
-                    )
-                )
-            else:
-                cells.append(cell)
-        nb.cells = cells
-        return nb, resources
+
+def update_markdown_with_imports(markdown: str) -> str:
+    """Update markdown to include API reference links for imports in Python code blocks.
+
+    This function scans the markdown content for Python code blocks, extracts any imports, and appends links to their API documentation.
+
+    Args:
+        markdown: The markdown content to process.
+
+    Returns:
+        Updated markdown with API reference links appended to Python code blocks.
+
+    Example:
+        Given a markdown with a Python code block:
+
+        ```python
+        from langchain.nlp import TextGenerator
+        ```
+        This function will append an API reference link to the `TextGenerator` class from the `langchain.nlp` module if it's recognized.
+    """
+    code_block_pattern = re.compile(
+        r'(?P<indent>[ \t]*)```(?P<language>python|py)\n(?P<code>.*?)\n(?P=indent)```', re.DOTALL
+    )
+
+    def replace_code_block(match: re.Match) -> str:
+        """Replace the matched code block with additional API reference links if imports are found.
+
+        Args:
+            match (re.Match): The regex match object containing the code block.
+
+        Returns:
+            str: The modified code block with API reference links appended if applicable.
+        """
+        indent = match.group('indent')
+        code_block = match.group('code')
+        language = match.group('language')  # Preserve the language from the regex match
+        # Retrieve import information from the code block
+        imports = get_imports(code_block, "__unused__")
+
+        original_code_block = match.group(0)
+        # If no imports are found, return the original code block
+        if not imports:
+            return original_code_block
+
+        # Generate API reference links for each import
+        api_links = ' | '.join(
+            f'<a href="{imp["docs"]}">{imp["imported"]}</a>' for imp in imports
+        )
+        # Return the code block with appended API reference links
+        return f'{original_code_block}\n\n{indent}API Reference: {api_links}'
+
+    # Apply the replace_code_block function to all matches in the markdown
+    updated_markdown = code_block_pattern.sub(replace_code_block, markdown)
+    return updated_markdown

docs/_scripts/notebook_convert.py

@@ -6,8 +6,6 @@ import nbformat
 from nbconvert.exporters import MarkdownExporter
 from nbconvert.preprocessors import Preprocessor
 
-from generate_api_reference_links import ImportPreprocessor
-
 
 class EscapePreprocessor(Preprocessor):
     def preprocess_cell(self, cell, resources, cell_index):
@@ -107,7 +105,6 @@ exporter = MarkdownExporter(
     preprocessors=[
         EscapePreprocessor,
         ExtractAttachmentsPreprocessor,
-        ImportPreprocessor,
     ],
     template_name="mdoutput",
     extra_template_basedirs=[

docs/_scripts/notebook_hooks.py

@@ -1,13 +1,18 @@
 import logging
+import os
+import re
 from typing import Any, Dict
 
-from mkdocs.structure.pages import Page
 from mkdocs.structure.files import Files, File
+from mkdocs.structure.pages import Page
+
 from notebook_convert import convert_notebook
+from generate_api_reference_links import update_markdown_with_imports
 
 logger = logging.getLogger(__name__)
 logging.basicConfig()
 logger.setLevel(logging.INFO)
+DISABLED = os.getenv("DISABLE_NOTEBOOK_CONVERT") in ("1", "true", "True")
 
 
 class NotebookFile(File):
@@ -16,6 +21,8 @@ class NotebookFile(File):
 
 
 def on_files(files: Files, **kwargs: Dict[str, Any]):
+    if DISABLED:
+        return files
     new_files = Files([])
     for file in files:
         if file.src_path.endswith(".ipynb"):
@@ -31,10 +38,83 @@ def on_files(files: Files, **kwargs: Dict[str, Any]):
     return new_files
 
 
+def _highlight_code_blocks(markdown: str) -> str:
+    """Find code blocks with highlight comments and add hl_lines attribute.
+
+    Args:
+        markdown: The markdown content to process.
+
+    Returns:
+        updated Markdown code with code blocks containing highlight comments
+        updated to use the hl_lines attribute.
+    """
+    # Pattern to find code blocks with highlight comments and without
+    # existing hl_lines for Python and JavaScript
+    # Pattern to find code blocks with highlight comments, handling optional indentation
+    code_block_pattern = re.compile(
+        r"(?P<indent>[ \t]*)```(?P<language>py|python|js|javascript)(?!\s+hl_lines=)\n"
+        r"(?P<code>((?:.*\n)*?))"  # Capture the code inside the block using named group
+        r"(?P=indent)```"  # Match closing backticks with the same indentation
+    )
+
+    def replace_highlight_comments(match: re.Match) -> str:
+        indent = match.group("indent")
+        language = match.group("language")
+        code_block = match.group("code")
+        lines = code_block.split("\n")
+        highlighted_lines = []
+
+        # Skip initial empty lines
+        while lines and not lines[0].strip():
+            lines.pop(0)
+
+        lines_to_keep = []
+
+        comment_syntax = (
+            "# highlight-next-line"
+            if language in ["py", "python"]
+            else "// highlight-next-line"
+        )
+
+        for line in lines:
+            if comment_syntax in line:
+                count = len(lines_to_keep) + 1
+                highlighted_lines.append(str(count))
+            else:
+                lines_to_keep.append(line)
+
+        # Reconstruct the new code block
+        new_code_block = "\n".join(lines_to_keep)
+
+        if highlighted_lines:
+            return (
+                f'{indent}```{language} hl_lines="{" ".join(highlighted_lines)}"\n'
+                # The indent and terminating \n is already included in the code block
+                f'{new_code_block}'
+                f'{indent}```'
+            )
+        else:
+            return (
+                f"{indent}```{language}\n"
+                # The indent and terminating \n is already included in the code block
+                f"{new_code_block}"
+                f"{indent}```"
+            )
+
+    # Replace all code blocks in the markdown
+    markdown = code_block_pattern.sub(replace_highlight_comments, markdown)
+    return markdown
+
+
 def on_page_markdown(markdown: str, page: Page, **kwargs: Dict[str, Any]):
+    if DISABLED:
+        return markdown
     if page.file.src_path.endswith(".ipynb"):
         logger.info("Processing Jupyter notebook: %s", page.file.src_path)
-        body = convert_notebook(page.file.abs_src_path)
-        return body
+        markdown = convert_notebook(page.file.abs_src_path)
 
+    # Append API reference links to code blocks
+    markdown = update_markdown_with_imports(markdown)
+    # Apply highlight comments to code blocks
+    markdown = _highlight_code_blocks(markdown)
     return markdown

docs/_scripts/prepare_notebooks_for_ci.py

@@ -42,8 +42,13 @@ NOTEBOOKS_NO_EXECUTION = [
     "docs/docs/tutorials/storm/storm.ipynb",  # issues only when running with VCR
     "docs/docs/tutorials/lats/lats.ipynb",  # issues only when running with VCR
     "docs/docs/tutorials/rag/langgraph_crag.ipynb",  # flakiness from tavily
-    "docs/docs/tutorials/rag/langgraph_adaptive_rag.ipynb",  # Cannot create a consistent method resolution error from VCR
-    "docs/docs/how-tos/map-reduce.ipynb"  # flakiness from structured output, only when running with VCR
+    "docs/docs/tutorials/rag/langgraph_adaptive_rag.ipynb",  # flakiness only when running in GHA 
+    "docs/docs/tutorials/rag/langgraph_self_rag.ipynb",  # flakiness only when running in GHA
+    "docs/docs/tutorials/rag/langgraph_agentic_rag.ipynb",  # flakiness only when running in GHA
+    "docs/docs/how-tos/map-reduce.ipynb",  # flakiness from structured output, only when running with VCR
+    "docs/docs/tutorials/tot/tot.ipynb",
+    "docs/docs/how-tos/visualization.ipynb",
+    "docs/docs/tutorials/llm-compiler/LLMCompiler.ipynb"
 ]
 
 
@@ -86,6 +91,7 @@ def add_vcr_to_notebook(
 ) -> nbformat.NotebookNode:
     """Inject `with vcr.cassette` into each code cell of the notebook."""
 
+    uses_langsmith = False
     # Inject VCR context manager into each code cell
     for idx, cell in enumerate(notebook.cells):
         if cell.cell_type != "code":
@@ -120,8 +126,22 @@ def add_vcr_to_notebook(
             f"    {line}" for line in lines
         )
 
+        if any("hub.pull" in line or "from langsmith import" in line for line in lines):
+            uses_langsmith = True
+
     # Add import statement
-    vcr_import_lines = [
+    vcr_import_lines = []
+    if uses_langsmith:
+        vcr_import_lines.extend([
+            # patch urllib3 to handle vcr errors, see more here:
+            # https://github.com/langchain-ai/langsmith-sdk/blob/main/python/langsmith/_internal/_patch.py
+            "import sys",
+            f"sys.path.insert(0, '{os.path.join(DOCS_PATH, '_scripts')}')",
+            "import _patch as patch_urllib3",
+            "patch_urllib3.patch_urllib3()",
+        ])
+
+    vcr_import_lines.extend([
         "import nest_asyncio",
         "nest_asyncio.apply()",
         "import vcr",
@@ -151,7 +171,8 @@ def add_vcr_to_notebook(
         "",
         "custom_vcr.register_serializer('advanced_compressed', AdvancedCompressedSerializer())",
         "custom_vcr.serializer = 'advanced_compressed'",
-    ]
+    ])
+
     import_cell = nbformat.v4.new_code_cell(source="\n".join(vcr_import_lines))
     import_cell.pop("id", None)
     notebook.cells.insert(0, import_cell)

docs/cassettes/LLMCompiler_15dd9639-691f-4906-9012-83fd6e9ac126.msgpack.zlib

@@ -1 +0,0 @@
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docs/cassettes/langgraph_self_rag_bd62276f-bf26-40d0-8cff-e07b10e00321.msgpack.zlib

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docs/cassettes/langgraph_self_rag_c6f4c70e-1660-4149-82c0-837f19fc9fb5.msgpack.zlib

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docs/cassettes/multi-agent-network_26a0d4df-ff99-40f0-92a8-0b3f2c591040.msgpack.zlib

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docs/cassettes/pass-config-to-tools_15.msgpack.zlib

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docs/cassettes/pass-config-to-tools_16.msgpack.zlib

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docs/cassettes/pass-config-to-tools_17.msgpack.zlib

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docs/cassettes/pass-config-to-tools_18.msgpack.zlib

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docs/cassettes/plan-and-execute_67ce37b7-e089-479b-bcb8-c3f5d9874613.msgpack.zlib

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docs/cassettes/plan-and-execute_72d233ca-1dbf-4b43-b680-b3bf39e3691f.msgpack.zlib

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docs/cassettes/run-id-langsmith_7.msgpack.zlib

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docs/cassettes/streaming-events-from-within-tools_4c9cdad3-3e9a-444f-9d9d-eae20b8d3486.msgpack.zlib

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docs/cassettes/subgraphs-manage-state_11.msgpack.zlib

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docs/cassettes/subgraphs-manage-state_12.msgpack.zlib

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docs/cassettes/subgraphs-manage-state_13.msgpack.zlib

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docs/cassettes/subgraphs-manage-state_14.msgpack.zlib

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docs/cassettes/subgraphs-manage-state_15.msgpack.zlib

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docs/cassettes/subgraphs-manage-state_16.msgpack.zlib

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docs/cassettes/subgraphs-manage-state_30.msgpack.zlib

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docs/cassettes/subgraphs-manage-state_31.msgpack.zlib

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docs/cassettes/subgraphs-manage-state_33.msgpack.zlib

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docs/cassettes/subgraphs-manage-state_34.msgpack.zlib

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docs/cassettes/subgraphs-manage-state_40.msgpack.zlib

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docs/cassettes/subgraphs-manage-state_41.msgpack.zlib

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docs/cassettes/subgraphs-manage-state_42.msgpack.zlib

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docs/cassettes/subgraphs-manage-state_43.msgpack.zlib

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docs/cassettes/subgraphs-manage-state_48.msgpack.zlib

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docs/cassettes/subgraphs-manage-state_49.msgpack.zlib

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docs/cassettes/update-state-from-tools_9d71af94-572a-4961-88a7-665e792cf96a.msgpack.zlib

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docs/cassettes/update-state-from-tools_de34a58b-1765-4b63-a232-d46790aff884.msgpack.zlib

@@ -0,0 +1 @@
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

docs/docs/cloud/deployment/cloud.md

@@ -5,17 +5,17 @@ LangGraph Cloud is available within <a href="https://www.langchain.com/langsmith
 ## Prerequisites
 
 1. LangGraph Cloud applications are deployed from GitHub repositories. Configure and upload a LangGraph Cloud application to a GitHub repository in order to deploy it to LangGraph Cloud.
-1. [Verify that the LangGraph API runs locally](test_locally.md). If the API does not build and run successfully (i.e. `langgraph up`), deploying to LangGraph Cloud will fail as well.
+1. [Verify that the LangGraph API runs locally](test_locally.md). If the API does not run successfully (i.e. `langgraph dev`), deploying to LangGraph Cloud will fail as well.
 
 ## Create New Deployment
 
 Starting from the <a href="https://smith.langchain.com/" target="_blank">LangSmith UI</a>...
 
-1. In the left-hand navigation panel, select `LangGraph Cloud`. The `LangGraph Cloud` view contains a list of existing LangGraph Cloud deployments.
+1. In the left-hand navigation panel, select `LangGraph Platform`. The `LangGraph Platform` view contains a list of existing LangGraph Cloud deployments.
 1. In the top-right corner, select `+ New Deployment` to create a new deployment.
 1. In the `Create New Deployment` panel, fill out the required fields.
     1. `Deployment details`
-        1. Select `Import from GitHub` and follow the GitHub OAuth workflow to install and authorize LangChain's `hosted-langserve` GitHub app to  access the selected repositories. After installation is complete, return to the `Create New Deployment` panel and select the GitHub repository to deploy from the dropdown menu.
+        1. Select `Import from GitHub` and follow the GitHub OAuth workflow to install and authorize LangChain's `hosted-langserve` GitHub app to access the selected repositories. After installation is complete, return to the `Create New Deployment` panel and select the GitHub repository to deploy from the dropdown menu. **Note**: The GitHub user installing LangChain's `hosted-langserve` GitHub app must be an [owner](https://docs.github.com/en/organizations/managing-peoples-access-to-your-organization-with-roles/roles-in-an-organization#organization-owners) of the organization or account.
         1. Specify a name for the deployment.
         1. Specify the desired `Git Branch`. A deployment is linked to a branch. When a new revision is created, code for the linked branch will be deployed. The branch can be updated later in the [Deployment Settings](#deployment-settings).
         1. Specify the full path to the [LangGraph API config file](../reference/cli.md#configuration-file) including the file name. For example, if the file `langgraph.json` is in the root of the repository, simply specify `langgraph.json`.
@@ -38,7 +38,7 @@ When [creating a new deployment](#create-new-deployment), a new revision is crea
 
 Starting from the <a href="https://smith.langchain.com/" target="_blank">LangSmith UI</a>...
 
-1. In the left-hand navigation panel, select `LangGraph Cloud`. The `LangGraph Cloud` view contains a list of existing LangGraph Cloud deployments.
+1. In the left-hand navigation panel, select `LangGraph Platform`. The `LangGraph Platform` view contains a list of existing LangGraph Cloud deployments.
 1. Select an existing deployment to create a new revision for.
 1. In the `Deployment` view, in the top-right corner, select `+ New Revision`.
 1. In the `New Revision` modal, fill out the required fields.
@@ -52,15 +52,15 @@ Starting from the <a href="https://smith.langchain.com/" target="_blank">LangSmi
         1. Update the value of existing secrets or environment variables.
 1. Select `Submit`. After a few seconds, the `New Revision` modal will close and the new revision will be queued for deployment.
 
-## View Build and Deployment Logs
+## View Build and Server Logs
 
-Build and deployment logs are available for each revision.
+Build and server logs are available for each revision.
 
-Starting from the `LangGraph Cloud` view...
+Starting from the `LangGraph Platform` view...
 
 1. Select the desired revision from the `Revisions` table. A panel slides open from the right-hand side and the `Build` tab is selected by default, which displays build logs for the revision.
-1. In the panel, select the `Deploy` tab to view deployment logs for the revision.
-1. Within the `Deploy` tab, adjust the date/time range picker as needed. By default, the date/time range picker is set to the `Last 15 minutes`.
+1. In the panel, select the `Server` tab to view server logs for the revision. Server logs are only available after a revision has been deployed.
+1. Within the `Server` tab, adjust the date/time range picker as needed. By default, the date/time range picker is set to the `Last 7 days`.
 
 ## Interrupt Revision
 
@@ -69,7 +69,7 @@ Interrupting a revision will stop deployment of the revision.
 !!! warning "Undefined Behavior"
     Interrupted revisions have undefined behavior. This is only useful if you need to deploy a new revision and you already have a revision "stuck" in progress. In the future, this feature may be removed.
 
-Starting from the `LangGraph Cloud` view...
+Starting from the `LangGraph Platform` view...
 
 1. Select the menu icon (three dots) on the right-hand side of the row for the desired revision from the `Revisions` table.
 1. Select `Interrupt` from the menu.
@@ -79,13 +79,13 @@ Starting from the `LangGraph Cloud` view...
 
 Starting from the <a href="https://smith.langchain.com/" target="_blank">LangSmith UI</a>...
 
-1. In the left-hand navigation panel, select `LangGraph Cloud`. The `LangGraph Cloud` view contains a list of existing LangGraph Cloud deployments.
+1. In the left-hand navigation panel, select `LangGraph Platform`. The `LangGraph Platform` view contains a list of existing LangGraph Cloud deployments.
 1. Select the menu icon (three dots) on the right-hand side of the row for the desired deployment and select `Delete`.
 1. A `Confirmation` modal will appear. Select `Delete`.
 
 ## Deployment Settings
 
-Starting from the `LangGraph Cloud` view...
+Starting from the `LangGraph Platform` view...
 
 1. In the top-right corner, select the gear icon (`Deployment Settings`).
 1. Update the `Git Branch` to the desired branch.

docs/docs/cloud/deployment/test_locally.md

@@ -6,17 +6,11 @@ Testing locally ensures that there are no errors or conflicts with Python depend
 
 ## Setup
 
-Install the proper packages:
+Install the LangGraph CLI package:
 
-
-=== "pip" 
-    ```bash
-    pip install -U langgraph-cli
-    ```
-=== "Homebrew (macOS only)"
-    ```bash
-    brew install langgraph-cli
-    ```
+```bash
+pip install -U "langgraph-cli[inmem]"
+```
 
 Ensure you have an API key, which you can create from the [LangSmith UI](https://smith.langchain.com) (Settings > API Keys). This is required to authenticate that you have LangGraph Cloud access. After you have saved the key to a safe place, place the following line in your `.env` file:
 
@@ -29,16 +23,26 @@ LANGSMITH_API_KEY = *********
 Once you have installed the CLI, you can run the following command to start the API server for local testing:
 
 ```shell
-langgraph up
+langgraph dev
 ```
 
 This will start up the LangGraph API server locally. If this runs successfully, you should see something like:
 
-```shell
-Ready!
-- API: http://localhost:8123
-2024-06-26 19:20:41,056:INFO:uvicorn.access 127.0.0.1:44138 - "GET /ok HTTP/1.1" 200
-```
+>    Ready!
+> 
+>    - API: [http://localhost:2024](http://localhost:2024/)
+>     
+>    - Docs: http://localhost:2024/docs
+>     
+>    - LangGraph Studio Web UI: https://smith.langchain.com/studio/?baseUrl=http://127.0.0.1:2024
+
+!!! note "In-Memory Mode"
+
+    The `langgraph dev` command starts LangGraph Server in an in-memory mode. This mode is suitable for development and testing purposes. For production use, you should deploy LangGraph Server with access to a persistent storage backend.
+
+    If you want to test your application with a persistent storage backend, you can use the `langgraph up` command instead of `langgraph dev`. You will
+    need to have `docker` installed on your machine to use this command.
+
 
 ### Interact with the server
 
@@ -53,7 +57,7 @@ You can either initialize by passing authentication or by setting an environment
     ```python
     from langgraph_sdk import get_client
 
-    # only pass the url argument to get_client() if you changed the default port when calling langgraph up
+    # only pass the url argument to get_client() if you changed the default port when calling langgraph dev
     client = get_client(url=<DEPLOYMENT_URL>,api_key=<LANGSMITH_API_KEY>)
     # Using the graph deployed with the name "agent"
     assistant_id = "agent"
@@ -65,7 +69,7 @@ You can either initialize by passing authentication or by setting an environment
     ```js
     import { Client } from "@langchain/langgraph-sdk";
 
-    // only set the apiUrl if you changed the default port when calling langgraph up
+    // only set the apiUrl if you changed the default port when calling langgraph dev
     const client = new Client({ apiUrl: <DEPLOYMENT_URL>, apiKey: <LANGSMITH_API_KEY> });
     // Using the graph deployed with the name "agent"
     const assistantId = "agent";
@@ -91,7 +95,7 @@ If you have a `LANGSMITH_API_KEY` set in your environment, you do not need to ex
     ```python
     from langgraph_sdk import get_client
 
-    # only pass the url argument to get_client() if you changed the default port when calling langgraph up
+    # only pass the url argument to get_client() if you changed the default port when calling langgraph dev
     client = get_client()
     # Using the graph deployed with the name "agent"
     assistant_id = "agent"
@@ -103,7 +107,7 @@ If you have a `LANGSMITH_API_KEY` set in your environment, you do not need to ex
     ```js
     import { Client } from "@langchain/langgraph-sdk";
 
-    // only set the apiUrl if you changed the default port when calling langgraph up
+    // only set the apiUrl if you changed the default port when calling langgraph dev
     const client = new Client();
     // Using the graph deployed with the name "agent"
     const assistantId = "agent";

docs/docs/cloud/how-tos/datasets_studio.md

@@ -0,0 +1,17 @@
+# Adding nodes as dataset examples in Studio
+
+In LangGraph Studio you can create dataset examples from the thread history in the right-hand pane. This can be especially useful when you want to evaluate intermediate steps of the agent.
+
+1. Click on the `Add to Dataset` button to enter the dataset mode.
+1. Select nodes which you want to add to dataset.
+1. Select the target dataset to create the example in.
+
+You can edit the example payload before sending it to the dataset, which is useful if you need to make changes to conform the example to the dataset schema.
+
+Finally, you can customise the target dataset by clicking on the `Settings` button.
+
+See [Evaluating intermediate steps](https://docs.smith.langchain.com/evaluation/how_to_guides/langgraph#evaluating-intermediate-steps) for more details on how to evaluate intermediate steps.
+
+<video controls allowfullscreen="true" poster="../img/studio_datasets.jpg">
+    <source src="https://langgraph-docs-assets.pages.dev/studio_datasets.mp4" type="video/mp4">
+</video>