Merge branch 'wip-v0.4' into cc/0.4/docs

Lots of work that wasn't directly related to core
improvements/messages/testing functionality

.devcontainer/README.md

@@ -15,12 +15,12 @@ You may use the button above, or follow these steps to open this repo in a Codes
 1. Click **Create codespace on master**.
 
 For more info, check out the [GitHub documentation](https://docs.github.com/en/free-pro-team@latest/github/developing-online-with-codespaces/creating-a-codespace#creating-a-codespace).
-  
+
 ## VS Code Dev Containers
 
 [![Open in Dev Containers](https://img.shields.io/static/v1?label=Dev%20Containers&message=Open&color=blue&logo=visualstudiocode)](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/langchain-ai/langchain)
 
-> [!NOTE]  
+> [!NOTE]
 > If you click the link above you will open the main repo (`langchain-ai/langchain`) and *not* your local cloned repo. This is fine if you only want to run and test the library, but if you want to contribute you can use the link below and replace with your username and cloned repo name:
 
 ```txt

.devcontainer/docker-compose.yaml

@@ -4,7 +4,7 @@ services:
     build:
       dockerfile: libs/langchain/dev.Dockerfile
       context: ..
-    
+
     networks:
       - langchain-network
 

.github/CODE_OF_CONDUCT.md

@@ -129,4 +129,4 @@ For answers to common questions about this code of conduct, see the FAQ at
 [v2.1]: https://www.contributor-covenant.org/version/2/1/code_of_conduct.html
 [Mozilla CoC]: https://github.com/mozilla/diversity
 [FAQ]: https://www.contributor-covenant.org/faq
-[translations]: https://www.contributor-covenant.org/translations
+[translations]: https://www.contributor-covenant.org/translations

.github/ISSUE_TEMPLATE/bug-report.yml

@@ -5,7 +5,7 @@ body:
   - type: markdown
     attributes:
       value: |
-        Thank you for taking the time to file a bug report. 
+        Thank you for taking the time to file a bug report.
 
         Use this to report BUGS in LangChain. For usage questions, feature requests and general design questions, please use the [LangChain Forum](https://forum.langchain.com/).
 
@@ -50,7 +50,7 @@ body:
 
         If a maintainer can copy it, run it, and see it right away, there's a much higher chance that you'll be able to get help.
 
-        **Important!** 
+        **Important!**
 
         * Avoid screenshots when possible, as they are hard to read and (more importantly) don't allow others to copy-and-paste your code.
         * Reduce your code to the minimum required to reproduce the issue if possible. This makes it much easier for others to help you.
@@ -58,14 +58,14 @@ body:
         * INCLUDE the language label (e.g. `python`) after the first three backticks to enable syntax highlighting. (e.g., ```python rather than ```).
 
       placeholder: |
-        The following code: 
+        The following code:
 
         ```python
         from langchain_core.runnables import RunnableLambda
 
         def bad_code(inputs) -> int:
           raise NotImplementedError('For demo purpose')
-          
+
           chain = RunnableLambda(bad_code)
           chain.invoke('Hello!')
         ```

.github/ISSUE_TEMPLATE/documentation.yml

@@ -14,7 +14,7 @@ body:
 
         Do **NOT** use this to ask usage questions or reporting issues with your code.
 
-        If you have usage questions or need help solving some problem, 
+        If you have usage questions or need help solving some problem,
         please use the [LangChain Forum](https://forum.langchain.com/).
 
         If you're in the wrong place, here are some helpful links to find a better

.github/ISSUE_TEMPLATE/privileged.yml

@@ -8,7 +8,7 @@ body:
 
         If you are not a LangChain maintainer or were not asked directly by a maintainer to create an issue, then please start the conversation on the [LangChain Forum](https://forum.langchain.com/) instead.
 
-        You are a LangChain maintainer if you maintain any of the packages inside of the LangChain repository 
+        You are a LangChain maintainer if you maintain any of the packages inside of the LangChain repository
         or are a regular contributor to LangChain with previous merged pull requests.
   - type: checkboxes
     id: privileged

.github/actions/people/Dockerfile

@@ -4,4 +4,4 @@ RUN pip install httpx PyGithub "pydantic==2.0.2" pydantic-settings "pyyaml>=5.3.
 
 COPY ./app /app
 
-CMD ["python", "/app/main.py"]
+CMD ["python", "/app/main.py"]

.github/actions/people/action.yml

@@ -4,8 +4,8 @@ description: "Generate the data for the LangChain People page"
 author: "Jacob Lee <jacob@langchain.dev>"
 inputs:
   token:
-    description: 'User token, to read the GitHub API. Can be passed in using {{ secrets.LANGCHAIN_PEOPLE_GITHUB_TOKEN }}'
+    description: "User token, to read the GitHub API. Can be passed in using {{ secrets.LANGCHAIN_PEOPLE_GITHUB_TOKEN }}"
     required: true
 runs:
-  using: 'docker'
-  image: 'Dockerfile'
+  using: "docker"
+  image: "Dockerfile"

.github/scripts/check_diff.py

@@ -3,14 +3,12 @@ import json
 import os
 import sys
 from collections import defaultdict
-from typing import Dict, List, Set
 from pathlib import Path
+from typing import Dict, List, Set
+
 import tomllib
-
-from packaging.requirements import Requirement
-
 from get_min_versions import get_min_version_from_toml
-
+from packaging.requirements import Requirement
 
 LANGCHAIN_DIRS = [
     "libs/core",
@@ -38,7 +36,7 @@ IGNORED_PARTNERS = [
 ]
 
 PY_312_MAX_PACKAGES = [
-    "libs/partners/chroma", # https://github.com/chroma-core/chroma/issues/4382
+    "libs/partners/chroma",  # https://github.com/chroma-core/chroma/issues/4382
 ]
 
 
@@ -85,9 +83,9 @@ def dependents_graph() -> dict:
                 for depline in extended_deps:
                     if depline.startswith("-e "):
                         # editable dependency
-                        assert depline.startswith(
-                            "-e ../partners/"
-                        ), "Extended test deps should only editable install partner packages"
+                        assert depline.startswith("-e ../partners/"), (
+                            "Extended test deps should only editable install partner packages"
+                        )
                         partner = depline.split("partners/")[1]
                         dep = f"langchain-{partner}"
                     else:
@@ -271,7 +269,7 @@ if __name__ == "__main__":
                     dirs_to_run["extended-test"].add(dir_)
         elif file.startswith("libs/standard-tests"):
             # TODO: update to include all packages that rely on standard-tests (all partner packages)
-            # note: won't run on external repo partners
+            # Note: won't run on external repo partners
             dirs_to_run["lint"].add("libs/standard-tests")
             dirs_to_run["test"].add("libs/standard-tests")
             dirs_to_run["lint"].add("libs/cli")
@@ -285,7 +283,7 @@ if __name__ == "__main__":
         elif file.startswith("libs/cli"):
             dirs_to_run["lint"].add("libs/cli")
             dirs_to_run["test"].add("libs/cli")
-            
+
         elif file.startswith("libs/partners"):
             partner_dir = file.split("/")[2]
             if os.path.isdir(f"libs/partners/{partner_dir}") and [
@@ -303,7 +301,10 @@ if __name__ == "__main__":
                 f"Unknown lib: {file}. check_diff.py likely needs "
                 "an update for this new library!"
             )
-        elif file.startswith("docs/") or file in ["pyproject.toml", "uv.lock"]: # docs or root uv files
+        elif file.startswith("docs/") or file in [
+            "pyproject.toml",
+            "uv.lock",
+        ]:  # docs or root uv files
             docs_edited = True
             dirs_to_run["lint"].add(".")
 

.github/scripts/check_prerelease_dependencies.py

@@ -1,4 +1,5 @@
 import sys
+
 import tomllib
 
 if __name__ == "__main__":

.github/scripts/get_min_versions.py

@@ -1,5 +1,5 @@
-from collections import defaultdict
 import sys
+from collections import defaultdict
 from typing import Optional
 
 if sys.version_info >= (3, 11):
@@ -8,17 +8,13 @@ else:
     # for python 3.10 and below, which doesnt have stdlib tomllib
     import tomli as tomllib
 
-from packaging.requirements import Requirement
-from packaging.specifiers import SpecifierSet
-from packaging.version import Version
-
-
-import requests
-from packaging.version import parse
+import re
 from typing import List
 
-import re
-
+import requests
+from packaging.requirements import Requirement
+from packaging.specifiers import SpecifierSet
+from packaging.version import Version, parse
 
 MIN_VERSION_LIBS = [
     "langchain-core",
@@ -72,11 +68,13 @@ def get_minimum_version(package_name: str, spec_string: str) -> Optional[str]:
     spec_string = re.sub(r"\^0\.0\.(\d+)", r"0.0.\1", spec_string)
     # rewrite occurrences of ^0.y.z to >=0.y.z,<0.y+1 (can be anywhere in constraint string)
     for y in range(1, 10):
-        spec_string = re.sub(rf"\^0\.{y}\.(\d+)", rf">=0.{y}.\1,<0.{y+1}", spec_string)
+        spec_string = re.sub(
+            rf"\^0\.{y}\.(\d+)", rf">=0.{y}.\1,<0.{y + 1}", spec_string
+        )
     # rewrite occurrences of ^x.y.z to >=x.y.z,<x+1.0.0 (can be anywhere in constraint string)
     for x in range(1, 10):
         spec_string = re.sub(
-            rf"\^{x}\.(\d+)\.(\d+)", rf">={x}.\1.\2,<{x+1}", spec_string
+            rf"\^{x}\.(\d+)\.(\d+)", rf">={x}.\1.\2,<{x + 1}", spec_string
         )
 
     spec_set = SpecifierSet(spec_string)
@@ -169,12 +167,12 @@ def check_python_version(version_string, constraint_string):
     # rewrite occurrences of ^0.y.z to >=0.y.z,<0.y+1.0 (can be anywhere in constraint string)
     for y in range(1, 10):
         constraint_string = re.sub(
-            rf"\^0\.{y}\.(\d+)", rf">=0.{y}.\1,<0.{y+1}.0", constraint_string
+            rf"\^0\.{y}\.(\d+)", rf">=0.{y}.\1,<0.{y + 1}.0", constraint_string
         )
     # rewrite occurrences of ^x.y.z to >=x.y.z,<x+1.0.0 (can be anywhere in constraint string)
     for x in range(1, 10):
         constraint_string = re.sub(
-            rf"\^{x}\.0\.(\d+)", rf">={x}.0.\1,<{x+1}.0.0", constraint_string
+            rf"\^{x}\.0\.(\d+)", rf">={x}.0.\1,<{x + 1}.0.0", constraint_string
         )
 
     try:

.github/scripts/prep_api_docs_build.py

@@ -3,9 +3,10 @@
 
 import os
 import shutil
-import yaml
 from pathlib import Path
-from typing import Dict, Any
+from typing import Any, Dict
+
+import yaml
 
 
 def load_packages_yaml() -> Dict[str, Any]:
@@ -28,7 +29,6 @@ def get_target_dir(package_name: str) -> Path:
 def clean_target_directories(packages: list) -> None:
     """Remove old directories that will be replaced."""
     for package in packages:
-
         target_dir = get_target_dir(package["name"])
         if target_dir.exists():
             print(f"Removing {target_dir}")
@@ -38,7 +38,6 @@ def clean_target_directories(packages: list) -> None:
 def move_libraries(packages: list) -> None:
     """Move libraries from their source locations to the target directories."""
     for package in packages:
-
         repo_name = package["repo"].split("/")[1]
         source_path = package["path"]
         target_dir = get_target_dir(package["name"])
@@ -68,23 +67,33 @@ def main():
         package_yaml = load_packages_yaml()
 
         # Clean target directories
-        clean_target_directories([
-            p
-            for p in package_yaml["packages"]
-            if (p["repo"].startswith("langchain-ai/") or p.get("include_in_api_ref"))
-            and p["repo"] != "langchain-ai/langchain"
-            and p["name"] != "langchain-ai21"  # Skip AI21 due to dependency conflicts
-        ])
+        clean_target_directories(
+            [
+                p
+                for p in package_yaml["packages"]
+                if (
+                    p["repo"].startswith("langchain-ai/") or p.get("include_in_api_ref")
+                )
+                and p["repo"] != "langchain-ai/langchain"
+                and p["name"]
+                != "langchain-ai21"  # Skip AI21 due to dependency conflicts
+            ]
+        )
 
         # Move libraries to their new locations
-        move_libraries([
-            p
-            for p in package_yaml["packages"]
-            if not p.get("disabled", False)
-            and (p["repo"].startswith("langchain-ai/") or p.get("include_in_api_ref"))
-            and p["repo"] != "langchain-ai/langchain"
-            and p["name"] != "langchain-ai21"  # Skip AI21 due to dependency conflicts
-        ])
+        move_libraries(
+            [
+                p
+                for p in package_yaml["packages"]
+                if not p.get("disabled", False)
+                and (
+                    p["repo"].startswith("langchain-ai/") or p.get("include_in_api_ref")
+                )
+                and p["repo"] != "langchain-ai/langchain"
+                and p["name"]
+                != "langchain-ai21"  # Skip AI21 due to dependency conflicts
+            ]
+        )
 
         # Delete ones without a pyproject.toml
         for partner in Path("langchain/libs/partners").iterdir():

.github/tools/git-restore-mtime

@@ -81,56 +81,93 @@ import time
 __version__ = "2022.12+dev"
 
 # Update symlinks only if the platform supports not following them
-UPDATE_SYMLINKS = bool(os.utime in getattr(os, 'supports_follow_symlinks', []))
+UPDATE_SYMLINKS = bool(os.utime in getattr(os, "supports_follow_symlinks", []))
 
 # Call os.path.normpath() only if not in a POSIX platform (Windows)
-NORMALIZE_PATHS = (os.path.sep != '/')
+NORMALIZE_PATHS = os.path.sep != "/"
 
 # How many files to process in each batch when re-trying merge commits
 STEPMISSING = 100
 
 # (Extra) keywords for the os.utime() call performed by touch()
-UTIME_KWS = {} if not UPDATE_SYMLINKS else {'follow_symlinks': False}
+UTIME_KWS = {} if not UPDATE_SYMLINKS else {"follow_symlinks": False}
 
 
 # Command-line interface ######################################################
 
+
 def parse_args():
-    parser = argparse.ArgumentParser(
-        description=__doc__.split('\n---')[0])
+    parser = argparse.ArgumentParser(description=__doc__.split("\n---")[0])
 
     group = parser.add_mutually_exclusive_group()
-    group.add_argument('--quiet', '-q', dest='loglevel',
-        action="store_const", const=logging.WARNING, default=logging.INFO,
-        help="Suppress informative messages and summary statistics.")
-    group.add_argument('--verbose', '-v', action="count", help="""
+    group.add_argument(
+        "--quiet",
+        "-q",
+        dest="loglevel",
+        action="store_const",
+        const=logging.WARNING,
+        default=logging.INFO,
+        help="Suppress informative messages and summary statistics.",
+    )
+    group.add_argument(
+        "--verbose",
+        "-v",
+        action="count",
+        help="""
         Print additional information for each processed file.
         Specify twice to further increase verbosity.
-        """)
+        """,
+    )
 
-    parser.add_argument('--cwd', '-C', metavar="DIRECTORY", help="""
+    parser.add_argument(
+        "--cwd",
+        "-C",
+        metavar="DIRECTORY",
+        help="""
         Run as if %(prog)s was started in directory %(metavar)s.
         This affects how --work-tree, --git-dir and PATHSPEC arguments are handled.
         See 'man 1 git' or 'git --help' for more information.
-        """)
+        """,
+    )
 
-    parser.add_argument('--git-dir', dest='gitdir', metavar="GITDIR", help="""
+    parser.add_argument(
+        "--git-dir",
+        dest="gitdir",
+        metavar="GITDIR",
+        help="""
         Path to the git repository, by default auto-discovered by searching
         the current directory and its parents for a .git/ subdirectory.
-        """)
+        """,
+    )
 
-    parser.add_argument('--work-tree', dest='workdir', metavar="WORKTREE", help="""
+    parser.add_argument(
+        "--work-tree",
+        dest="workdir",
+        metavar="WORKTREE",
+        help="""
         Path to the work tree root, by default the parent of GITDIR if it's
         automatically discovered, or the current directory if GITDIR is set.
-        """)
+        """,
+    )
 
-    parser.add_argument('--force', '-f', default=False, action="store_true", help="""
+    parser.add_argument(
+        "--force",
+        "-f",
+        default=False,
+        action="store_true",
+        help="""
         Force updating files with uncommitted modifications.
         Untracked files and uncommitted deletions, renames and additions are
         always ignored.
-        """)
+        """,
+    )
 
-    parser.add_argument('--merge', '-m', default=False, action="store_true", help="""
+    parser.add_argument(
+        "--merge",
+        "-m",
+        default=False,
+        action="store_true",
+        help="""
         Include merge commits.
         Leads to more recent times and more files per commit, thus with the same
         time, which may or may not be what you want.
@@ -138,71 +175,130 @@ def parse_args():
         are found sooner, which can improve performance, sometimes substantially.
         But as merge commits are usually huge, processing them may also take longer.
         By default, merge commits are only used for files missing from regular commits.
-        """)
+        """,
+    )
 
-    parser.add_argument('--first-parent', default=False, action="store_true", help="""
+    parser.add_argument(
+        "--first-parent",
+        default=False,
+        action="store_true",
+        help="""
         Consider only the first parent, the "main branch", when evaluating merge commits.
         Only effective when merge commits are processed, either when --merge is
         used or when finding missing files after the first regular log search.
         See --skip-missing.
-        """)
+        """,
+    )
 
-    parser.add_argument('--skip-missing', '-s', dest="missing", default=True,
-        action="store_false", help="""
+    parser.add_argument(
+        "--skip-missing",
+        "-s",
+        dest="missing",
+        default=True,
+        action="store_false",
+        help="""
         Do not try to find missing files.
         If merge commits were not evaluated with --merge and some files were
         not found in regular commits, by default %(prog)s searches for these
         files again in the merge commits.
         This option disables this retry, so files found only in merge commits
         will not have their timestamp updated.
-        """)
+        """,
+    )
 
-    parser.add_argument('--no-directories', '-D', dest='dirs', default=True,
-        action="store_false", help="""
+    parser.add_argument(
+        "--no-directories",
+        "-D",
+        dest="dirs",
+        default=True,
+        action="store_false",
+        help="""
         Do not update directory timestamps.
         By default, use the time of its most recently created, renamed or deleted file.
         Note that just modifying a file will NOT update its directory time.
-        """)
+        """,
+    )
 
-    parser.add_argument('--test', '-t', default=False, action="store_true",
-        help="Test run: do not actually update any file timestamp.")
+    parser.add_argument(
+        "--test",
+        "-t",
+        default=False,
+        action="store_true",
+        help="Test run: do not actually update any file timestamp.",
+    )
 
-    parser.add_argument('--commit-time', '-c', dest='commit_time', default=False,
-        action='store_true', help="Use commit time instead of author time.")
+    parser.add_argument(
+        "--commit-time",
+        "-c",
+        dest="commit_time",
+        default=False,
+        action="store_true",
+        help="Use commit time instead of author time.",
+    )
 
-    parser.add_argument('--oldest-time', '-o', dest='reverse_order', default=False,
-        action='store_true', help="""
+    parser.add_argument(
+        "--oldest-time",
+        "-o",
+        dest="reverse_order",
+        default=False,
+        action="store_true",
+        help="""
         Update times based on the oldest, instead of the most recent commit of a file.
         This reverses the order in which the git log is processed to emulate a
         file "creation" date. Note this will be inaccurate for files deleted and
         re-created at later dates.
-        """)
+        """,
+    )
 
-    parser.add_argument('--skip-older-than', metavar='SECONDS', type=int, help="""
+    parser.add_argument(
+        "--skip-older-than",
+        metavar="SECONDS",
+        type=int,
+        help="""
         Ignore files that are currently older than %(metavar)s.
         Useful in workflows that assume such files already have a correct timestamp,
         as it may improve performance by processing fewer files.
-        """)
+        """,
+    )
 
-    parser.add_argument('--skip-older-than-commit', '-N', default=False,
-        action='store_true', help="""
+    parser.add_argument(
+        "--skip-older-than-commit",
+        "-N",
+        default=False,
+        action="store_true",
+        help="""
         Ignore files older than the timestamp it would be updated to.
         Such files may be considered "original", likely in the author's repository.
-        """)
+        """,
+    )
 
-    parser.add_argument('--unique-times', default=False, action="store_true", help="""
+    parser.add_argument(
+        "--unique-times",
+        default=False,
+        action="store_true",
+        help="""
         Set the microseconds to a unique value per commit.
         Allows telling apart changes that would otherwise have identical timestamps,
         as git's time accuracy is in seconds.
-        """)
+        """,
+    )
 
-    parser.add_argument('pathspec', nargs='*', metavar='PATHSPEC', help="""
+    parser.add_argument(
+        "pathspec",
+        nargs="*",
+        metavar="PATHSPEC",
+        help="""
         Only modify paths matching %(metavar)s, relative to current directory.
         By default, update all but untracked files and submodules.
-        """)
+        """,
+    )
 
-    parser.add_argument('--version', '-V', action='version',
-        version='%(prog)s version {version}'.format(version=get_version()))
+    parser.add_argument(
+        "--version",
+        "-V",
+        action="version",
+        version="%(prog)s version {version}".format(version=get_version()),
+    )
 
     args_ = parser.parse_args()
     if args_.verbose:
@@ -212,17 +308,18 @@ def parse_args():
 
 
 def get_version(version=__version__):
-    if not version.endswith('+dev'):
+    if not version.endswith("+dev"):
         return version
     try:
         cwd = os.path.dirname(os.path.realpath(__file__))
-        return Git(cwd=cwd, errors=False).describe().lstrip('v')
+        return Git(cwd=cwd, errors=False).describe().lstrip("v")
     except Git.Error:
-        return '-'.join((version, "unknown"))
+        return "-".join((version, "unknown"))
 
 
 # Helper functions ############################################################
 
+
 def setup_logging():
     """Add TRACE logging level and corresponding method, return the root logger"""
     logging.TRACE = TRACE = logging.DEBUG // 2
@@ -255,11 +352,13 @@ def normalize(path):
     if path and path[0] == '"':
         # Python 2: path = path[1:-1].decode("string-escape")
         # Python 3: https://stackoverflow.com/a/46650050/624066
-        path = (path[1:-1]                 # Remove enclosing double quotes
-                .encode('latin1')          # Convert to bytes, required by 'unicode-escape'
-                .decode('unicode-escape')  # Perform the actual octal-escaping decode
-                .encode('latin1')          # 1:1 mapping to bytes, UTF-8 encoded
-                .decode('utf8', 'surrogateescape'))  # Decode from UTF-8
+        path = (
+            path[1:-1]  # Remove enclosing double quotes
+            .encode("latin1")  # Convert to bytes, required by 'unicode-escape'
+            .decode("unicode-escape")  # Perform the actual octal-escaping decode
+            .encode("latin1")  # 1:1 mapping to bytes, UTF-8 encoded
+            .decode("utf8", "surrogateescape")
+        )  # Decode from UTF-8
     if NORMALIZE_PATHS:
         # Make sure the slash matches the OS; for Windows we need a backslash
         path = os.path.normpath(path)
@@ -282,12 +381,12 @@ def touch_ns(path, mtime_ns):
 
 def isodate(secs: int):
     # time.localtime() accepts floats, but discards fractional part
-    return time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(secs))
+    return time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(secs))
 
 
 def isodate_ns(ns: int):
     # for integers fromtimestamp() is equivalent and ~16% slower than isodate()
-    return datetime.datetime.fromtimestamp(ns / 1000000000).isoformat(sep=' ')
+    return datetime.datetime.fromtimestamp(ns / 1000000000).isoformat(sep=" ")
 
 
 def get_mtime_ns(secs: int, idx: int):
@@ -305,35 +404,49 @@ def get_mtime_path(path):
 
 # Git class and parse_log(), the heart of the script ##########################
 
+
 class Git:
     def __init__(self, workdir=None, gitdir=None, cwd=None, errors=True):
-        self.gitcmd = ['git']
+        self.gitcmd = ["git"]
         self.errors = errors
         self._proc = None
-        if workdir: self.gitcmd.extend(('--work-tree', workdir))
-        if gitdir:  self.gitcmd.extend(('--git-dir',   gitdir))
-        if cwd:     self.gitcmd.extend(('-C',          cwd))
+        if workdir:
+            self.gitcmd.extend(("--work-tree", workdir))
+        if gitdir:
+            self.gitcmd.extend(("--git-dir", gitdir))
+        if cwd:
+            self.gitcmd.extend(("-C", cwd))
         self.workdir, self.gitdir = self._get_repo_dirs()
 
     def ls_files(self, paths: list = None):
-        return (normalize(_) for _ in self._run('ls-files --full-name', paths))
+        return (normalize(_) for _ in self._run("ls-files --full-name", paths))
 
     def ls_dirty(self, force=False):
-        return (normalize(_[3:].split(' -> ', 1)[-1])
-                for _ in self._run('status --porcelain')
-                if _[:2] != '??' and (not force or (_[0] in ('R', 'A')
-                                                    or _[1] == 'D')))
+        return (
+            normalize(_[3:].split(" -> ", 1)[-1])
+            for _ in self._run("status --porcelain")
+            if _[:2] != "??" and (not force or (_[0] in ("R", "A") or _[1] == "D"))
+        )
 
-    def log(self, merge=False, first_parent=False, commit_time=False,
-            reverse_order=False, paths: list = None):
-        cmd = 'whatchanged --pretty={}'.format('%ct' if commit_time else '%at')
-        if merge:         cmd += ' -m'
-        if first_parent:  cmd += ' --first-parent'
-        if reverse_order: cmd += ' --reverse'
+    def log(
+        self,
+        merge=False,
+        first_parent=False,
+        commit_time=False,
+        reverse_order=False,
+        paths: list = None,
+    ):
+        cmd = "whatchanged --pretty={}".format("%ct" if commit_time else "%at")
+        if merge:
+            cmd += " -m"
+        if first_parent:
+            cmd += " --first-parent"
+        if reverse_order:
+            cmd += " --reverse"
         return self._run(cmd, paths)
 
     def describe(self):
-        return self._run('describe --tags', check=True)[0]
+        return self._run("describe --tags", check=True)[0]
 
     def terminate(self):
         if self._proc is None:
@@ -345,18 +458,22 @@ class Git:
             pass
 
     def _get_repo_dirs(self):
-        return (os.path.normpath(_) for _ in
-            self._run('rev-parse --show-toplevel --absolute-git-dir', check=True))
+        return (
+            os.path.normpath(_)
+            for _ in self._run(
+                "rev-parse --show-toplevel --absolute-git-dir", check=True
+            )
+        )
 
     def _run(self, cmdstr: str, paths: list = None, output=True, check=False):
         cmdlist = self.gitcmd + shlex.split(cmdstr)
         if paths:
-            cmdlist.append('--')
+            cmdlist.append("--")
             cmdlist.extend(paths)
-        popen_args = dict(universal_newlines=True, encoding='utf8')
+        popen_args = dict(universal_newlines=True, encoding="utf8")
         if not self.errors:
-            popen_args['stderr'] = subprocess.DEVNULL
-        log.trace("Executing: %s", ' '.join(cmdlist))
+            popen_args["stderr"] = subprocess.DEVNULL
+        log.trace("Executing: %s", " ".join(cmdlist))
         if not output:
             return subprocess.call(cmdlist, **popen_args)
         if check:
@@ -379,30 +496,26 @@ def parse_log(filelist, dirlist, stats, git, merge=False, filterlist=None):
     mtime = 0
     datestr = isodate(0)
     for line in git.log(
-            merge,
-            args.first_parent,
-            args.commit_time,
-            args.reverse_order,
-            filterlist
+        merge, args.first_parent, args.commit_time, args.reverse_order, filterlist
     ):
-        stats['loglines'] += 1
+        stats["loglines"] += 1
 
         # Blank line between Date and list of files
         if not line:
             continue
 
         # Date line
-        if line[0] != ':':  # Faster than `not line.startswith(':')`
-            stats['commits'] += 1
+        if line[0] != ":":  # Faster than `not line.startswith(':')`
+            stats["commits"] += 1
             mtime = int(line)
             if args.unique_times:
-                mtime = get_mtime_ns(mtime, stats['commits'])
+                mtime = get_mtime_ns(mtime, stats["commits"])
             if args.debug:
                 datestr = isodate(mtime)
             continue
 
         # File line: three tokens if it describes a renaming, otherwise two
-        tokens = line.split('\t')
+        tokens = line.split("\t")
 
         # Possible statuses:
         # M: Modified (content changed)
@@ -411,7 +524,7 @@ def parse_log(filelist, dirlist, stats, git, merge=False, filterlist=None):
         # T: Type changed: to/from regular file, symlinks, submodules
         # R099: Renamed (moved), with % of unchanged content. 100 = pure rename
         # Not possible in log: C=Copied, U=Unmerged, X=Unknown, B=pairing Broken
-        status = tokens[0].split(' ')[-1]
+        status = tokens[0].split(" ")[-1]
         file = tokens[-1]
 
         # Handles non-ASCII chars and OS path separator
@@ -419,56 +532,76 @@ def parse_log(filelist, dirlist, stats, git, merge=False, filterlist=None):
 
         def do_file():
             if args.skip_older_than_commit and get_mtime_path(file) <= mtime:
-                stats['skip'] += 1
+                stats["skip"] += 1
                 return
             if args.debug:
-                log.debug("%d\t%d\t%d\t%s\t%s",
-                          stats['loglines'], stats['commits'], stats['files'],
-                          datestr, file)
+                log.debug(
+                    "%d\t%d\t%d\t%s\t%s",
+                    stats["loglines"],
+                    stats["commits"],
+                    stats["files"],
+                    datestr,
+                    file,
+                )
             try:
                 touch(os.path.join(git.workdir, file), mtime)
-                stats['touches'] += 1
+                stats["touches"] += 1
             except Exception as e:
                 log.error("ERROR: %s: %s", e, file)
-                stats['errors'] += 1
+                stats["errors"] += 1
 
         def do_dir():
             if args.debug:
-                log.debug("%d\t%d\t-\t%s\t%s",
-                          stats['loglines'], stats['commits'],
-                          datestr, "{}/".format(dirname or '.'))
+                log.debug(
+                    "%d\t%d\t-\t%s\t%s",
+                    stats["loglines"],
+                    stats["commits"],
+                    datestr,
+                    "{}/".format(dirname or "."),
+                )
             try:
                 touch(os.path.join(git.workdir, dirname), mtime)
-                stats['dirtouches'] += 1
+                stats["dirtouches"] += 1
             except Exception as e:
                 log.error("ERROR: %s: %s", e, dirname)
-                stats['direrrors'] += 1
+                stats["direrrors"] += 1
 
         if file in filelist:
-            stats['files'] -= 1
+            stats["files"] -= 1
             filelist.remove(file)
             do_file()
 
-        if args.dirs and status in ('A', 'D'):
+        if args.dirs and status in ("A", "D"):
             dirname = os.path.dirname(file)
             if dirname in dirlist:
                 dirlist.remove(dirname)
                 do_dir()
 
         # All files done?
-        if not stats['files']:
+        if not stats["files"]:
             git.terminate()
             return
 
 
 # Main Logic ##################################################################
 
+
 def main():
     start = time.time()  # yes, Wall time. CPU time is not realistic for users.
-    stats = {_: 0 for _ in ('loglines', 'commits', 'touches', 'skip', 'errors',
-                            'dirtouches', 'direrrors')}
+    stats = {
+        _: 0
+        for _ in (
+            "loglines",
+            "commits",
+            "touches",
+            "skip",
+            "errors",
+            "dirtouches",
+            "direrrors",
+        )
+    }
 
-    logging.basicConfig(level=args.loglevel, format='%(message)s')
+    logging.basicConfig(level=args.loglevel, format="%(message)s")
     log.trace("Arguments: %s", args)
 
     # First things first: Where and Who are we?
@@ -499,13 +632,16 @@ def main():
 
             # Symlink (to file, to dir or broken - git handles the same way)
             if not UPDATE_SYMLINKS and os.path.islink(fullpath):
-                log.warning("WARNING: Skipping symlink, no OS support for updates: %s",
-                            path)
+                log.warning(
+                    "WARNING: Skipping symlink, no OS support for updates: %s", path
+                )
                 continue
 
             # skip files which are older than given threshold
-            if (args.skip_older_than
-                    and start - get_mtime_path(fullpath) > args.skip_older_than):
+            if (
+                args.skip_older_than
+                and start - get_mtime_path(fullpath) > args.skip_older_than
+            ):
                 continue
 
             # Always add files relative to worktree root
@@ -519,15 +655,17 @@ def main():
     else:
         dirty = set(git.ls_dirty())
         if dirty:
-            log.warning("WARNING: Modified files in the working directory were ignored."
-                "\nTo include such files, commit your changes or use --force.")
+            log.warning(
+                "WARNING: Modified files in the working directory were ignored."
+                "\nTo include such files, commit your changes or use --force."
+            )
             filelist -= dirty
 
     # Build dir list to be processed
     dirlist = set(os.path.dirname(_) for _ in filelist) if args.dirs else set()
 
-    stats['totalfiles'] = stats['files'] = len(filelist)
-    log.info("{0:,} files to be processed in work dir".format(stats['totalfiles']))
+    stats["totalfiles"] = stats["files"] = len(filelist)
+    log.info("{0:,} files to be processed in work dir".format(stats["totalfiles"]))
 
     if not filelist:
         # Nothing to do. Exit silently and without errors, just like git does
@@ -544,10 +682,18 @@ def main():
         if args.missing and not args.merge:
             filterlist = list(filelist)
             missing = len(filterlist)
-            log.info("{0:,} files not found in log, trying merge commits".format(missing))
+            log.info(
+                "{0:,} files not found in log, trying merge commits".format(missing)
+            )
             for i in range(0, missing, STEPMISSING):
-                parse_log(filelist, dirlist, stats, git,
-                          merge=True, filterlist=filterlist[i:i + STEPMISSING])
+                parse_log(
+                    filelist,
+                    dirlist,
+                    stats,
+                    git,
+                    merge=True,
+                    filterlist=filterlist[i : i + STEPMISSING],
+                )
 
         # Still missing some?
         for file in filelist:
@@ -556,29 +702,33 @@ def main():
     # Final statistics
     # Suggestion: use git-log --before=mtime to brag about skipped log entries
     def log_info(msg, *a, width=13):
-        ifmt = '{:%d,}'    % (width,)  # not using 'n' for consistency with ffmt
-        ffmt = '{:%d,.2f}' % (width,)
+        ifmt = "{:%d,}" % (width,)  # not using 'n' for consistency with ffmt
+        ffmt = "{:%d,.2f}" % (width,)
         # %-formatting lacks a thousand separator, must pre-render with .format()
-        log.info(msg.replace('%d', ifmt).replace('%f', ffmt).format(*a))
+        log.info(msg.replace("%d", ifmt).replace("%f", ffmt).format(*a))
 
     log_info(
-        "Statistics:\n"
-        "%f seconds\n"
-        "%d log lines processed\n"
-        "%d commits evaluated",
-        time.time() - start, stats['loglines'], stats['commits'])
+        "Statistics:\n%f seconds\n%d log lines processed\n%d commits evaluated",
+        time.time() - start,
+        stats["loglines"],
+        stats["commits"],
+    )
 
     if args.dirs:
-        if stats['direrrors']: log_info("%d directory update errors", stats['direrrors'])
-        log_info("%d directories updated", stats['dirtouches'])
+        if stats["direrrors"]:
+            log_info("%d directory update errors", stats["direrrors"])
+        log_info("%d directories updated", stats["dirtouches"])
 
-    if stats['touches'] != stats['totalfiles']:
-                        log_info("%d files",              stats['totalfiles'])
-    if stats['skip']:   log_info("%d files skipped",      stats['skip'])
-    if stats['files']:  log_info("%d files missing",      stats['files'])
-    if stats['errors']: log_info("%d file update errors", stats['errors'])
+    if stats["touches"] != stats["totalfiles"]:
+        log_info("%d files", stats["totalfiles"])
+    if stats["skip"]:
+        log_info("%d files skipped", stats["skip"])
+    if stats["files"]:
+        log_info("%d files missing", stats["files"])
+    if stats["errors"]:
+        log_info("%d file update errors", stats["errors"])
 
-    log_info("%d files updated", stats['touches'])
+    log_info("%d files updated", stats["touches"])
 
     if args.test:
         log.info("TEST RUN - No files modified!")

.github/workflows/_release.yml

@@ -220,7 +220,7 @@ jobs:
         with:
           python-version: ${{ env.PYTHON_VERSION }}
 
-      - uses: actions/download-artifact@v4
+      - uses: actions/download-artifact@v5
         with:
           name: dist
           path: ${{ inputs.working-directory }}/dist/
@@ -379,7 +379,7 @@ jobs:
         with:
           python-version: ${{ env.PYTHON_VERSION }}
 
-      - uses: actions/download-artifact@v4
+      - uses: actions/download-artifact@v5
         if: startsWith(inputs.working-directory, 'libs/core')
         with:
           name: dist
@@ -388,11 +388,12 @@ jobs:
       - name: Test against ${{ matrix.partner }}
         if: startsWith(inputs.working-directory, 'libs/core')
         run: |
-          # Identify latest tag
+          # Identify latest tag, excluding pre-releases
           LATEST_PACKAGE_TAG="$(
             git ls-remote --tags origin "langchain-${{ matrix.partner }}*" \
             | awk '{print $2}' \
             | sed 's|refs/tags/||' \
+            | grep -Ev '==[^=]*(\.?dev[0-9]*|\.?rc[0-9]*)$' \
             | sort -Vr \
             | head -n 1
           )"
@@ -446,7 +447,7 @@ jobs:
         with:
           python-version: ${{ env.PYTHON_VERSION }}
 
-      - uses: actions/download-artifact@v4
+      - uses: actions/download-artifact@v5
         with:
           name: dist
           path: ${{ inputs.working-directory }}/dist/
@@ -485,7 +486,7 @@ jobs:
         with:
           python-version: ${{ env.PYTHON_VERSION }}
 
-      - uses: actions/download-artifact@v4
+      - uses: actions/download-artifact@v5
         with:
           name: dist
           path: ${{ inputs.working-directory }}/dist/

.github/workflows/_test.yml

@@ -79,4 +79,4 @@ jobs:
           # grep will exit non-zero if the target message isn't found,
           # and `set -e` above will cause the step to fail.
           echo "$STATUS" | grep 'nothing to commit, working tree clean'
-          
+

.github/workflows/_test_pydantic.yml

@@ -64,4 +64,4 @@ jobs:
 
           # grep will exit non-zero if the target message isn't found,
           # and `set -e` above will cause the step to fail.
-          echo "$STATUS" | grep 'nothing to commit, working tree clean'
+          echo "$STATUS" | grep 'nothing to commit, working tree clean'

.github/workflows/_test_release.yml

@@ -85,7 +85,7 @@ jobs:
     steps:
       - uses: actions/checkout@v4
 
-      - uses: actions/download-artifact@v4
+      - uses: actions/download-artifact@v5
         with:
           name: test-dist
           path: ${{ inputs.working-directory }}/dist/

.github/workflows/check_diffs.yml

@@ -30,6 +30,7 @@ jobs:
   build:
     name: 'Detect Changes & Set Matrix'
     runs-on: ubuntu-latest
+    if: ${{ !contains(github.event.pull_request.labels.*.name, 'ci-ignore') }}
     steps:
       - name: '📋 Checkout Code'
         uses: actions/checkout@v4

.markdownlint.json

@@ -11,4 +11,4 @@
   "MD046": {
     "style": "fenced"
   }
-}
+}

.vscode/settings.json

@@ -21,7 +21,7 @@
   "[python]": {
     "editor.formatOnSave": true,
     "editor.codeActionsOnSave": {
-      "source.organizeImports": "explicit",
+      "source.organizeImports.ruff": "explicit",
       "source.fixAll": "explicit"
     },
     "editor.defaultFormatter": "charliermarsh.ruff"
@@ -77,4 +77,6 @@
     "editor.tabSize": 2,
     "editor.insertSpaces": true
   },
+  "python.terminal.activateEnvironment": false,
+  "python.defaultInterpreterPath": "./.venv/bin/python"
 }

cookbook/README.md

@@ -63,4 +63,4 @@ Notebook | Description
 [rag-locally-on-intel-cpu.ipynb](https://github.com/langchain-ai/langchain/tree/master/cookbook/rag-locally-on-intel-cpu.ipynb) | Perform Retrieval-Augmented-Generation (RAG) on locally downloaded open-source models using langchain and open source tools and execute it on Intel Xeon CPU. We showed an example of how to apply RAG on Llama 2 model and enable it to answer the queries related to Intel Q1 2024 earnings release.
 [visual_RAG_vdms.ipynb](https://github.com/langchain-ai/langchain/tree/master/cookbook/visual_RAG_vdms.ipynb) | Performs Visual Retrieval-Augmented-Generation (RAG) using videos and scene descriptions generated by open source models.
 [contextual_rag.ipynb](https://github.com/langchain-ai/langchain/tree/master/cookbook/contextual_rag.ipynb) | Performs contextual retrieval-augmented generation (RAG) prepending chunk-specific explanatory context to each chunk before embedding.
-[rag-agents-locally-on-intel-cpu.ipynb](https://github.com/langchain-ai/langchain/tree/master/cookbook/local_rag_agents_intel_cpu.ipynb) | Build a RAG agent locally with open source models that routes questions through one of two paths to find answers. The agent generates answers based on documents retrieved from either the vector database or retrieved from web search. If the vector database lacks relevant information, the agent opts for web search. Open-source models for LLM and embeddings are used locally on an Intel Xeon CPU to execute this pipeline.
+[rag-agents-locally-on-intel-cpu.ipynb](https://github.com/langchain-ai/langchain/tree/master/cookbook/local_rag_agents_intel_cpu.ipynb) | Build a RAG agent locally with open source models that routes questions through one of two paths to find answers. The agent generates answers based on documents retrieved from either the vector database or retrieved from web search. If the vector database lacks relevant information, the agent opts for web search. Open-source models for LLM and embeddings are used locally on an Intel Xeon CPU to execute this pipeline.

docs/api_reference/create_api_rst.py

@@ -97,7 +97,7 @@ def _load_module_members(module_path: str, namespace: str) -> ModuleMembers:
             if type(type_) is typing_extensions._TypedDictMeta:  # type: ignore
                 kind: ClassKind = "TypedDict"
             elif type(type_) is typing._TypedDictMeta:  # type: ignore
-                kind: ClassKind = "TypedDict"
+                kind = "TypedDict"
             elif (
                 issubclass(type_, Runnable)
                 and issubclass(type_, BaseModel)
@@ -189,7 +189,7 @@ def _load_package_modules(
         if isinstance(package_directory, str)
         else package_directory
     )
-    modules_by_namespace = {}
+    modules_by_namespace: Dict[str, ModuleMembers] = {}
 
     # Get the high level package name
     package_name = package_path.name
@@ -217,8 +217,8 @@ def _load_package_modules(
         # Get the full namespace of the module
         namespace = str(relative_module_name).replace(".py", "").replace("/", ".")
         # Keep only the top level namespace
-        # (but make special exception for content_blocks and messages.v1)
-        if namespace == "messages.content_blocks" or namespace == "messages.v1":
+        # (but make special exception for content_blocks and v1.messages)
+        if namespace == "messages.content_blocks" or namespace == "v1.messages":
             top_namespace = namespace  # Keep full namespace for content_blocks
         else:
             top_namespace = namespace.split(".")[0]

docs/docs/concepts/async.mdx

@@ -1,4 +1,4 @@
-# Async programming with langchain
+# Async programming with LangChain
 
 :::info Prerequisites
 * [Runnable interface](/docs/concepts/runnables)
@@ -12,7 +12,7 @@ You are expected to be familiar with asynchronous programming in Python before r
 This guide specifically focuses on what you need to know to work with LangChain in an asynchronous context, assuming that you are already familiar with asynchronous programming.
 :::
 
-## Langchain asynchronous APIs
+## LangChain asynchronous APIs
 
 Many LangChain APIs are designed to be asynchronous, allowing you to build efficient and responsive applications.
 

docs/docs/concepts/tools.mdx

@@ -31,7 +31,7 @@ The key attributes that correspond to the tool's **schema**:
 The key methods to execute the function associated with the **tool**:
 
 - **invoke**: Invokes the tool with the given arguments.
-- **ainvoke**: Invokes the tool with the given arguments, asynchronously. Used for [async programming with Langchain](/docs/concepts/async).
+- **ainvoke**: Invokes the tool with the given arguments, asynchronously. Used for [async programming with LangChain](/docs/concepts/async).
 
 ## Create tools using the `@tool` decorator
 

docs/docs/contributing/how_to/code/setup.mdx

@@ -9,6 +9,14 @@ This project utilizes [uv](https://docs.astral.sh/uv/) v0.5+ as a dependency man
 
 Install `uv`: **[documentation on how to install it](https://docs.astral.sh/uv/getting-started/installation/)**.
 
+### Windows Users
+
+If you're on Windows and don't have `make` installed, you can install it via:
+- **Option 1**: Install via [Chocolatey](https://chocolatey.org/): `choco install make`
+- **Option 2**: Install via [Scoop](https://scoop.sh/): `scoop install make`
+- **Option 3**: Use [Windows Subsystem for Linux (WSL)](https://docs.microsoft.com/en-us/windows/wsl/)
+- **Option 4**: Use the direct `uv` commands shown in the sections below
+
 ## Different packages
 
 This repository contains multiple packages:
@@ -48,7 +56,11 @@ uv sync
 Then verify dependency installation:
 
 ```bash
+# If you have `make` installed:
 make test
+
+# If you don't have `make` (Windows alternative):
+uv run --group test pytest -n auto --disable-socket --allow-unix-socket tests/unit_tests
 ```
 
 ## Testing
@@ -61,7 +73,11 @@ If you add new logic, please add a unit test.
 To run unit tests:
 
 ```bash
+# If you have `make` installed:
 make test
+
+# If you don't have make (Windows alternative):
+uv run --group test pytest -n auto --disable-socket --allow-unix-socket tests/unit_tests
 ```
 
 There are also [integration tests and code-coverage](../testing.mdx) available.
@@ -72,7 +88,12 @@ If you are only developing `langchain_core`, you can simply install the dependen
 
 ```bash
 cd libs/core
+
+# If you have `make` installed:
 make test
+
+# If you don't have `make` (Windows alternative):
+uv run --group test pytest -n auto --disable-socket --allow-unix-socket tests/unit_tests
 ```
 
 ## Formatting and linting
@@ -86,20 +107,37 @@ Formatting for this project is done via [ruff](https://docs.astral.sh/ruff/rules
 To run formatting for docs, cookbook and templates:
 
 ```bash
+# If you have `make` installed:
 make format
+
+# If you don't have make (Windows alternative):
+uv run --all-groups ruff format .
+uv run --all-groups ruff check --fix .
 ```
 
 To run formatting for a library, run the same command from the relevant library directory:
 
 ```bash
 cd libs/{LIBRARY}
+
+# If you have `make` installed:
 make format
+
+# If you don't have make (Windows alternative):
+uv run --all-groups ruff format .
+uv run --all-groups ruff check --fix .
 ```
 
 Additionally, you can run the formatter only on the files that have been modified in your current branch as compared to the master branch using the format_diff command:
 
 ```bash
+# If you have `make` installed:
 make format_diff
+
+# If you don't have `make` (Windows alternative):
+# First, get the list of modified files:
+git diff --relative=libs/langchain --name-only --diff-filter=d master | grep -E '\.py$$|\.ipynb$$' | xargs uv run --all-groups ruff format
+git diff --relative=libs/langchain --name-only --diff-filter=d master | grep -E '\.py$$|\.ipynb$$' | xargs uv run --all-groups ruff check --fix
 ```
 
 This is especially useful when you have made changes to a subset of the project and want to ensure your changes are properly formatted without affecting the rest of the codebase.
@@ -111,20 +149,40 @@ Linting for this project is done via a combination of [ruff](https://docs.astral
 To run linting for docs, cookbook and templates:
 
 ```bash
+# If you have `make` installed:
 make lint
+
+# If you don't have `make` (Windows alternative):
+uv run --all-groups ruff check .
+uv run --all-groups ruff format . --diff
+uv run --all-groups mypy . --cache-dir .mypy_cache
 ```
 
 To run linting for a library, run the same command from the relevant library directory:
 
 ```bash
 cd libs/{LIBRARY}
+
+# If you have `make` installed:
 make lint
+
+# If you don't have `make` (Windows alternative):
+uv run --all-groups ruff check .
+uv run --all-groups ruff format . --diff
+uv run --all-groups mypy . --cache-dir .mypy_cache
 ```
 
 In addition, you can run the linter only on the files that have been modified in your current branch as compared to the master branch using the lint_diff command:
 
 ```bash
+# If you have `make` installed:
 make lint_diff
+
+# If you don't have `make` (Windows alternative):
+# First, get the list of modified files:
+git diff --relative=libs/langchain --name-only --diff-filter=d master | grep -E '\.py$$|\.ipynb$$' | xargs uv run --all-groups ruff check
+git diff --relative=libs/langchain --name-only --diff-filter=d master | grep -E '\.py$$|\.ipynb$$' | xargs uv run --all-groups ruff format --diff
+git diff --relative=libs/langchain --name-only --diff-filter=d master | grep -E '\.py$$|\.ipynb$$' | xargs uv run --all-groups mypy --cache-dir .mypy_cache
 ```
 
 This can be very helpful when you've made changes to only certain parts of the project and want to ensure your changes meet the linting standards without having to check the entire codebase.
@@ -139,13 +197,21 @@ Note that `codespell` finds common typos, so it could have false-positive (corre
 To check spelling for this project:
 
 ```bash
+# If you have `make` installed:
 make spell_check
+
+# If you don't have `make` (Windows alternative):
+uv run --all-groups codespell --toml pyproject.toml
 ```
 
 To fix spelling in place:
 
 ```bash
+# If you have `make` installed:
 make spell_fix
+
+# If you don't have `make` (Windows alternative):
+uv run --all-groups codespell --toml pyproject.toml -w
 ```
 
 If codespell is incorrectly flagging a word, you can skip spellcheck for that word by adding it to the codespell config in the `pyproject.toml` file.

docs/docs/how_to/chat_streaming.ipynb

@@ -24,7 +24,7 @@
     "\n",
     ":::tip\n",
     "\n",
-    "The **default** implementation does **not** provide support for token-by-token streaming, but it ensures that the the model can be swapped in for any other model as it supports the same standard interface.\n",
+    "The **default** implementation does **not** provide support for token-by-token streaming, but it ensures that the model can be swapped in for any other model as it supports the same standard interface.\n",
     "\n",
     ":::\n",
     "\n",

docs/docs/how_to/extraction_long_text.ipynb

@@ -323,7 +323,7 @@
    "source": [
     "## RAG based approach\n",
     "\n",
-    "Another simple idea is to chunk up the text, but instead of extracting information from every chunk, just focus on the the most relevant chunks.\n",
+    "Another simple idea is to chunk up the text, but instead of extracting information from every chunk, just focus on the most relevant chunks.\n",
     "\n",
     ":::caution\n",
     "It can be difficult to identify which chunks are relevant.\n",

docs/docs/how_to/filter_messages.ipynb

@@ -104,7 +104,7 @@
    "source": [
     "## Chaining\n",
     "\n",
-    "`filter_messages` can be used in an imperatively (like above) or declaratively, making it easy to compose with other components in a chain:"
+    "`filter_messages` can be used imperatively (like above) or declaratively, making it easy to compose with other components in a chain:"
    ]
   },
   {

docs/docs/how_to/graph_constructing.ipynb

@@ -122,13 +122,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "import os\n",
     "\n",
-    "from langchain_experimental.graph_transformers import LLMGraphTransformer\n",
+    "# from langchain_experimental.graph_transformers import LLMGraphTransformer\n",
     "from langchain_openai import ChatOpenAI\n",
     "\n",
     "llm = ChatOpenAI(temperature=0, model_name=\"gpt-4-turbo\")\n",

docs/docs/how_to/index.mdx

@@ -34,7 +34,7 @@ These are the core building blocks you can use when building applications.
 [Chat Models](/docs/concepts/chat_models) are newer forms of language models that take messages in and output a message.
 See [supported integrations](/docs/integrations/chat/) for details on getting started with chat models from a specific provider.
 
-- [How to: init any model in one line](/docs/how_to/chat_models_universal_init/)
+- [How to: initialize any model in one line](/docs/how_to/chat_models_universal_init/)
 - [How to: work with local models](/docs/how_to/local_llms)
 - [How to: do function/tool calling](/docs/how_to/tool_calling)
 - [How to: get models to return structured output](/docs/how_to/structured_output)

docs/docs/how_to/indexing.ipynb

@@ -199,7 +199,7 @@
    "outputs": [],
    "source": [
     "def _clear():\n",
-    "    \"\"\"Hacky helper method to clear content. See the `full` mode section to to understand why it works.\"\"\"\n",
+    "    \"\"\"Hacky helper method to clear content. See the `full` mode section to understand why it works.\"\"\"\n",
     "    index([], record_manager, vectorstore, cleanup=\"full\", source_id_key=\"source\")"
    ]
   },

docs/docs/how_to/local_llms.ipynb

@@ -45,8 +45,8 @@
     "A few frameworks for this have emerged to support inference of open-source LLMs on various devices:\n",
     "\n",
     "1. [`llama.cpp`](https://github.com/ggerganov/llama.cpp): C++ implementation of llama inference code with [weight optimization / quantization](https://finbarr.ca/how-is-llama-cpp-possible/)\n",
-    "2. [`gpt4all`](https://docs.gpt4all.io/index.html): Optimized C backend for inference\n",
-    "3. [`Ollama`](https://ollama.ai/): Bundles model weights and environment into an app that runs on device and serves the LLM\n",
+    "2. [`gpt4all`](https://github.com/nomic-ai/gpt4all): Optimized C backend for inference\n",
+    "3. [`ollama`](https://github.com/ollama/ollama): Bundles model weights and environment into an app that runs on device and serves the LLM\n",
     "4. [`llamafile`](https://github.com/Mozilla-Ocho/llamafile): Bundles model weights and everything needed to run the model in a single file, allowing you to run the LLM locally from this file without any additional installation steps\n",
     "\n",
     "In general, these frameworks will do a few things:\n",
@@ -74,12 +74,12 @@
     "\n",
     "## Quickstart\n",
     "\n",
-    "[`Ollama`](https://ollama.ai/) is one way to easily run inference on macOS.\n",
+    "[Ollama](https://ollama.ai/) is one way to easily run inference on macOS.\n",
     " \n",
-    "The instructions [here](https://github.com/jmorganca/ollama?tab=readme-ov-file#ollama) provide details, which we summarize:\n",
+    "The instructions [here](https://github.com/ollama/ollama?tab=readme-ov-file#ollama) provide details, which we summarize:\n",
     " \n",
     "* [Download and run](https://ollama.ai/download) the app\n",
-    "* From command line, fetch a model from this [list of options](https://github.com/jmorganca/ollama): e.g., `ollama pull llama3.1:8b`\n",
+    "* From command line, fetch a model from this [list of options](https://ollama.com/search): e.g., `ollama pull llama3.1:8b`\n",
     "* When the app is running, all models are automatically served on `localhost:11434`\n"
    ]
   },
@@ -111,11 +111,11 @@
     }
    ],
    "source": [
-    "from langchain_ollama import OllamaLLM\n",
+    "from langchain_ollama import ChatOllama\n",
     "\n",
-    "llm = OllamaLLM(model=\"llama3.1:8b\")\n",
+    "llm = ChatOllama(model=\"gpt-oss:20b\")\n",
     "\n",
-    "llm.invoke(\"The first man on the moon was ...\")"
+    "llm.invoke(\"The first man on the moon was ...\").content"
    ]
   },
   {
@@ -149,40 +149,7 @@
    ],
    "source": [
     "for chunk in llm.stream(\"The first man on the moon was ...\"):\n",
-    "    print(chunk, end=\"|\", flush=True)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "e5731060",
-   "metadata": {},
-   "source": [
-    "Ollama also includes a chat model wrapper that handles formatting conversation turns:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "f14a778a",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "AIMessage(content='The answer is a historic one!\\n\\nThe first man to walk on the Moon was Neil Armstrong, an American astronaut and commander of the Apollo 11 mission. On July 20, 1969, Armstrong stepped out of the lunar module Eagle onto the surface of the Moon, famously declaring:\\n\\n\"That\\'s one small step for man, one giant leap for mankind.\"\\n\\nArmstrong was followed by fellow astronaut Edwin \"Buzz\" Aldrin, who also walked on the Moon during the mission. Michael Collins remained in orbit around the Moon in the command module Columbia.\\n\\nNeil Armstrong passed away on August 25, 2012, but his legacy as a pioneering astronaut and engineer continues to inspire people around the world!', response_metadata={'model': 'llama3.1:8b', 'created_at': '2024-08-01T00:38:29.176717Z', 'message': {'role': 'assistant', 'content': ''}, 'done_reason': 'stop', 'done': True, 'total_duration': 10681861417, 'load_duration': 34270292, 'prompt_eval_count': 19, 'prompt_eval_duration': 6209448000, 'eval_count': 141, 'eval_duration': 4432022000}, id='run-7bed57c5-7f54-4092-912c-ae49073dcd48-0', usage_metadata={'input_tokens': 19, 'output_tokens': 141, 'total_tokens': 160})"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "from langchain_ollama import ChatOllama\n",
-    "\n",
-    "chat_model = ChatOllama(model=\"llama3.1:8b\")\n",
-    "\n",
-    "chat_model.invoke(\"Who was the first man on the moon?\")"
+    "    print(chunk.text(), end=\"|\", flush=True)"
    ]
   },
   {
@@ -200,7 +167,7 @@
     "\n",
     "### Running Apple silicon GPU\n",
     "\n",
-    "`Ollama` and [`llamafile`](https://github.com/Mozilla-Ocho/llamafile?tab=readme-ov-file#gpu-support) will automatically utilize the GPU on Apple devices.\n",
+    "`ollama` and [`llamafile`](https://github.com/Mozilla-Ocho/llamafile?tab=readme-ov-file#gpu-support) will automatically utilize the GPU on Apple devices.\n",
     " \n",
     "Other frameworks require the user to set up the environment to utilize the Apple GPU.\n",
     "\n",
@@ -212,15 +179,15 @@
     "\n",
     "In particular, ensure that conda is using the correct virtual environment that you created (`miniforge3`).\n",
     "\n",
-    "E.g., for me:\n",
+    "e.g.,\n",
     "\n",
-    "```\n",
+    "```shell\n",
     "conda activate /Users/rlm/miniforge3/envs/llama\n",
     "```\n",
     "\n",
     "With the above confirmed, then:\n",
     "\n",
-    "```\n",
+    "```shell\n",
     "CMAKE_ARGS=\"-DLLAMA_METAL=on\" FORCE_CMAKE=1 pip install -U llama-cpp-python --no-cache-dir\n",
     "```"
    ]
@@ -234,17 +201,13 @@
     "\n",
     "There are various ways to gain access to quantized model weights.\n",
     "\n",
-    "1. [`HuggingFace`](https://huggingface.co/TheBloke) - Many quantized model are available for download and can be run with framework such as [`llama.cpp`](https://github.com/ggerganov/llama.cpp). You can also download models in [`llamafile` format](https://huggingface.co/models?other=llamafile) from HuggingFace.\n",
-    "2. [`gpt4all`](https://gpt4all.io/index.html) - The model explorer offers a leaderboard of metrics and associated quantized models available for download \n",
-    "3. [`Ollama`](https://github.com/jmorganca/ollama) - Several models can be accessed directly via `pull`\n",
+    "1. [HuggingFace](https://huggingface.co/TheBloke) - Many quantized model are available for download and can be run with framework such as [`llama.cpp`](https://github.com/ggerganov/llama.cpp). You can also download models in [`llamafile` format](https://huggingface.co/models?other=llamafile) from HuggingFace.\n",
+    "2. [gpt4all](https://gpt4all.io/index.html) - The model explorer offers a leaderboard of metrics and associated quantized models available for download \n",
+    "3. [ollama](https://github.com/ollama/ollama) - Several models can be accessed directly via `pull`\n",
     "\n",
     "### Ollama\n",
     "\n",
-    "With [Ollama](https://github.com/jmorganca/ollama), fetch a model via `ollama pull <model family>:<tag>`:\n",
-    "\n",
-    "* E.g., for Llama 2 7b: `ollama pull llama2` will download the most basic version of the model (e.g., smallest # parameters and 4 bit quantization)\n",
-    "* We can also specify a particular version from the [model list](https://github.com/jmorganca/ollama?tab=readme-ov-file#model-library), e.g., `ollama pull llama2:13b`\n",
-    "* See the full set of parameters on the [API reference page](https://python.langchain.com/api_reference/community/llms/langchain_community.llms.ollama.Ollama.html)"
+    "With [Ollama](https://github.com/ollama/ollama), fetch a model via `ollama pull <model family>:<tag>`:"
    ]
   },
   {
@@ -265,7 +228,7 @@
     }
    ],
    "source": [
-    "llm = OllamaLLM(model=\"llama2:13b\")\n",
+    "llm = ChatOllama(model=\"gpt-oss:20b\")\n",
     "llm.invoke(\"The first man on the moon was ... think step by step\")"
    ]
   },
@@ -684,12 +647,6 @@
     "\n",
     "In addition, [here](https://blog.langchain.dev/using-langsmith-to-support-fine-tuning-of-open-source-llms/) is an overview on fine-tuning, which can utilize open-source LLMs."
    ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "14c2c170",
-   "metadata": {},
-   "source": []
   }
  ],
  "metadata": {

docs/docs/how_to/merge_message_runs.ipynb

@@ -88,7 +88,7 @@
    "source": [
     "## Chaining\n",
     "\n",
-    "`merge_message_runs` can be used in an imperatively (like above) or declaratively, making it easy to compose with other components in a chain:"
+    "`merge_message_runs` can be used imperatively (like above) or declaratively, making it easy to compose with other components in a chain:"
    ]
   },
   {

docs/docs/how_to/query_high_cardinality.ipynb

@@ -15,7 +15,7 @@
    "id": "f2195672-0cab-4967-ba8a-c6544635547d",
    "metadata": {},
    "source": [
-    "# How deal with high cardinality categoricals when doing query analysis\n",
+    "# How to deal with high-cardinality categoricals when doing query analysis\n",
     "\n",
     "You may want to do query analysis to create a filter on a categorical column. One of the difficulties here is that you usually need to specify the EXACT categorical value. The issue is you need to make sure the LLM generates that categorical value exactly. This can be done relatively easy with prompting when there are only a few values that are valid. When there are a high number of valid values then it becomes more difficult, as those values may not fit in the LLM context, or (if they do) there may be too many for the LLM to properly attend to.\n",
     "\n",

docs/docs/how_to/semantic-chunker.ipynb

@@ -74,12 +74,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "id": "a88ff70c",
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_experimental.text_splitter import SemanticChunker\n",
+    "# from langchain_experimental.text_splitter import SemanticChunker\n",
     "from langchain_openai.embeddings import OpenAIEmbeddings\n",
     "\n",
     "text_splitter = SemanticChunker(OpenAIEmbeddings())"

docs/docs/how_to/sql_csv.ipynb

@@ -612,56 +612,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": null,
    "id": "35ea904e-795f-411b-bef8-6484dbb6e35c",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "\n",
-      "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
-      "\u001b[32;1m\u001b[1;3m\n",
-      "Invoking: `python_repl_ast` with `{'query': \"df[['Age', 'Fare']].corr().iloc[0,1]\"}`\n",
-      "\n",
-      "\n",
-      "\u001b[0m\u001b[36;1m\u001b[1;3m0.11232863699941621\u001b[0m\u001b[32;1m\u001b[1;3m\n",
-      "Invoking: `python_repl_ast` with `{'query': \"df[['Fare', 'Survived']].corr().iloc[0,1]\"}`\n",
-      "\n",
-      "\n",
-      "\u001b[0m\u001b[36;1m\u001b[1;3m0.2561785496289603\u001b[0m\u001b[32;1m\u001b[1;3mThe correlation between Age and Fare is approximately 0.112, and the correlation between Fare and Survival is approximately 0.256.\n",
-      "\n",
-      "Therefore, the correlation between Fare and Survival (0.256) is greater than the correlation between Age and Fare (0.112).\u001b[0m\n",
-      "\n",
-      "\u001b[1m> Finished chain.\u001b[0m\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "{'input': \"What's the correlation between age and fare? is that greater than the correlation between fare and survival?\",\n",
-       " 'output': 'The correlation between Age and Fare is approximately 0.112, and the correlation between Fare and Survival is approximately 0.256.\\n\\nTherefore, the correlation between Fare and Survival (0.256) is greater than the correlation between Age and Fare (0.112).'}"
-      ]
-     },
-     "execution_count": 18,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "from langchain_experimental.agents import create_pandas_dataframe_agent\n",
-    "\n",
-    "agent = create_pandas_dataframe_agent(\n",
-    "    llm, df, agent_type=\"openai-tools\", verbose=True, allow_dangerous_code=True\n",
-    ")\n",
-    "agent.invoke(\n",
-    "    {\n",
-    "        \"input\": \"What's the correlation between age and fare? is that greater than the correlation between fare and survival?\"\n",
-    "    }\n",
-    ")"
-   ]
+   "outputs": [],
+   "source": "from langchain_experimental.agents import create_pandas_dataframe_agent\n\nagent = create_pandas_dataframe_agent(\n    llm, df, agent_type=\"openai-tools\", verbose=True, allow_dangerous_code=True\n)\nagent.invoke(\n    {\n        \"input\": \"What's the correlation between age and fare? is that greater than the correlation between fare and survival?\"\n    }\n)"
   },
   {
    "cell_type": "markdown",
@@ -786,4 +741,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
+}

docs/docs/how_to/structured_output.ipynb

@@ -614,6 +614,7 @@
     "    HumanMessage(\"Now about caterpillars\", name=\"example_user\"),\n",
     "    AIMessage(\n",
     "        \"\",\n",
+    "        name=\"example_assistant\",\n",
     "        tool_calls=[\n",
     "            {\n",
     "                \"name\": \"joke\",\n",
@@ -909,7 +910,7 @@
     "        ),\n",
     "        (\"human\", \"{query}\"),\n",
     "    ]\n",
-    ").partial(schema=People.schema())\n",
+    ").partial(schema=People.model_json_schema())\n",
     "\n",
     "\n",
     "# Custom parser\n",

docs/docs/integrations/chat/huggingface.ipynb

@@ -52,7 +52,7 @@
     "\n",
     "| Class | Package | Local | Serializable | JS support | Package downloads | Package latest |\n",
     "| :--- | :--- | :---: | :---: |  :---: | :---: | :---: |\n",
-    "| [ChatHuggingFace](https://python.langchain.com/api_reference/huggingface/chat_models/langchain_huggingface.chat_models.huggingface.ChatHuggingFace.html) | [langchain_huggingface](https://python.langchain.com/api_reference/huggingface/index.html) | ✅ | ❌ | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_huggingface?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_huggingface?style=flat-square&label=%20) |\n",
+    "| [ChatHuggingFace](https://python.langchain.com/api_reference/huggingface/chat_models/langchain_huggingface.chat_models.huggingface.ChatHuggingFace.html) | [langchain-huggingface](https://python.langchain.com/api_reference/huggingface/index.html) | ✅ | ❌ | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_huggingface?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_huggingface?style=flat-square&label=%20) |\n",
     "\n",
     "### Model features\n",
     "| [Tool calling](/docs/how_to/tool_calling) | [Structured output](/docs/how_to/structured_output/) | JSON mode | [Image input](/docs/how_to/multimodal_inputs/) | Audio input | Video input | [Token-level streaming](/docs/how_to/chat_streaming/) | Native async | [Token usage](/docs/how_to/chat_token_usage_tracking/) | [Logprobs](/docs/how_to/logprobs/) |\n",
@@ -61,7 +61,7 @@
     "\n",
     "## Setup\n",
     "\n",
-    "To access `langchain_huggingface` models you'll need to create a/an `Hugging Face` account, get an API key, and install the `langchain_huggingface` integration package.\n",
+    "To access `langchain_huggingface` models you'll need to create a `Hugging Face` account, get an API key, and install the `langchain-huggingface` integration package.\n",
     "\n",
     "### Credentials\n",
     "\n",

docs/docs/integrations/chat/mistralai.ipynb

@@ -24,7 +24,7 @@
         "\n",
         "| Class | Package | Local | Serializable | [JS support](https://js.langchain.com/docs/integrations/chat/mistral) | Package downloads | Package latest |\n",
         "| :--- | :--- | :---: | :---: |  :---: | :---: | :---: |\n",
-        "| [ChatMistralAI](https://python.langchain.com/api_reference/mistralai/chat_models/langchain_mistralai.chat_models.ChatMistralAI.html) | [langchain_mistralai](https://python.langchain.com/api_reference/mistralai/index.html) | ❌ | beta | ✅ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_mistralai?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_mistralai?style=flat-square&label=%20) |\n",
+        "| [ChatMistralAI](https://python.langchain.com/api_reference/mistralai/chat_models/langchain_mistralai.chat_models.ChatMistralAI.html) | [langchain-mistralai](https://python.langchain.com/api_reference/mistralai/index.html) | ❌ | beta | ✅ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_mistralai?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_mistralai?style=flat-square&label=%20) |\n",
         "\n",
         "### Model features\n",
         "| [Tool calling](/docs/how_to/tool_calling) | [Structured output](/docs/how_to/structured_output/) | JSON mode | [Image input](/docs/how_to/multimodal_inputs/) | Audio input | Video input | [Token-level streaming](/docs/how_to/chat_streaming/) | Native async | [Token usage](/docs/how_to/chat_token_usage_tracking/) | [Logprobs](/docs/how_to/logprobs/) |\n",
@@ -34,7 +34,7 @@
         "## Setup\n",
         "\n",
         "\n",
-        "To access `ChatMistralAI` models you'll need to create a Mistral account, get an API key, and install the `langchain_mistralai` integration package.\n",
+        "To access `ChatMistralAI` models you'll need to create a Mistral account, get an API key, and install the `langchain-mistralai` integration package.\n",
         "\n",
         "### Credentials\n",
         "\n",
@@ -80,7 +80,7 @@
       "source": [
         "### Installation\n",
         "\n",
-        "The LangChain Mistral integration lives in the `langchain_mistralai` package:"
+        "The LangChain Mistral integration lives in the `langchain-mistralai` package:"
       ]
     },
     {
@@ -90,7 +90,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "%pip install -qU langchain_mistralai"
+        "%pip install -qU langchain-mistralai"
       ]
     },
     {

docs/docs/integrations/chat/nvidia_ai_endpoints.ipynb

@@ -41,7 +41,7 @@
         "\n",
         "| Class | Package | Local | Serializable | JS support | Package downloads | Package latest |\n",
         "| :--- | :--- | :---: | :---: |  :---: | :---: | :---: |\n",
-        "| [ChatNVIDIA](https://python.langchain.com/api_reference/nvidia_ai_endpoints/chat_models/langchain_nvidia_ai_endpoints.chat_models.ChatNVIDIA.html) | [langchain_nvidia_ai_endpoints](https://python.langchain.com/api_reference/nvidia_ai_endpoints/index.html) | ✅ | beta | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_nvidia_ai_endpoints?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_nvidia_ai_endpoints?style=flat-square&label=%20) |\n",
+        "| [ChatNVIDIA](https://python.langchain.com/api_reference/nvidia_ai_endpoints/chat_models/langchain_nvidia_ai_endpoints.chat_models.ChatNVIDIA.html) | [langchain-nvidia-ai-endpoints](https://python.langchain.com/api_reference/nvidia_ai_endpoints/index.html) | ✅ | beta | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_nvidia_ai_endpoints?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_nvidia_ai_endpoints?style=flat-square&label=%20) |\n",
         "\n",
         "### Model features\n",
         "| [Tool calling](/docs/how_to/tool_calling) | [Structured output](/docs/how_to/structured_output/) | JSON mode | [Image input](/docs/how_to/multimodal_inputs/) | Audio input | Video input | [Token-level streaming](/docs/how_to/chat_streaming/) | Native async | [Token usage](/docs/how_to/chat_token_usage_tracking/) | [Logprobs](/docs/how_to/logprobs/) |\n",
@@ -102,7 +102,7 @@
       "source": [
         "### Installation\n",
         "\n",
-        "The LangChain NVIDIA AI Endpoints integration lives in the `langchain_nvidia_ai_endpoints` package:"
+        "The LangChain NVIDIA AI Endpoints integration lives in the `langchain-nvidia-ai-endpoints` package:"
       ]
     },
     {

docs/docs/integrations/chat/ollama.ipynb

@@ -17,25 +17,29 @@
    "source": [
     "# ChatOllama\n",
     "\n",
-    "[Ollama](https://ollama.ai/) allows you to run open-source large language models, such as Llama 2, locally.\n",
+    "[Ollama](https://ollama.com/) allows you to run open-source large language models, such as `gpt-oss`, locally.\n",
     "\n",
-    "Ollama bundles model weights, configuration, and data into a single package, defined by a Modelfile.\n",
+    "`ollama` bundles model weights, configuration, and data into a single package, defined by a Modelfile.\n",
     "\n",
     "It optimizes setup and configuration details, including GPU usage.\n",
     "\n",
-    "For a complete list of supported models and model variants, see the [Ollama model library](https://github.com/jmorganca/ollama#model-library).\n",
+    "For a complete list of supported models and model variants, see the [Ollama model library](https://ollama.com/search).\n",
+    "\n",
+    ":::warning\n",
+    "This page is for the new v1 `ChatOllama` class with standard content block output. If you are looking for the legacy v0 `Ollama` class, see the [v0.3 documentation](https://python.langchain.com/v0.3/docs/integrations/chat/ollama/).\n",
+    ":::\n",
     "\n",
     "## Overview\n",
     "### Integration details\n",
     "\n",
-    "| Class | Package | Local | Serializable | [JS support](https://js.langchain.com/v0.2/docs/integrations/chat/ollama) | Package downloads | Package latest |\n",
+    "| Class | Package | Local | Serializable | [JS support](https://js.langchain.com/docs/integrations/chat/ollama/) | Package downloads | Package latest |\n",
     "| :--- | :--- | :---: | :---: |  :---: | :---: | :---: |\n",
-    "| [ChatOllama](https://python.langchain.com/v0.2/api_reference/ollama/chat_models/langchain_ollama.chat_models.ChatOllama.html) | [langchain-ollama](https://python.langchain.com/v0.2/api_reference/ollama/index.html) | ✅ | ❌ | ✅ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-ollama?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-ollama?style=flat-square&label=%20) |\n",
+    "| [ChatOllama](https://python.langchain.com/api_reference/ollama/chat_models/langchain_ollama.chat_models.ChatOllama.html#chatollama) | [langchain-ollama](https://python.langchain.com/api_reference/ollama/index.html) | ✅ | ❌ | ✅ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-ollama?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-ollama?style=flat-square&label=%20) |\n",
     "\n",
     "### Model features\n",
     "| [Tool calling](/docs/how_to/tool_calling/) | [Structured output](/docs/how_to/structured_output/) | JSON mode | [Image input](/docs/how_to/multimodal_inputs/) | Audio input | Video input | [Token-level streaming](/docs/how_to/chat_streaming/) | Native async | [Token usage](/docs/how_to/chat_token_usage_tracking/) | [Logprobs](/docs/how_to/logprobs/) |\n",
     "| :---: |:----------------------------------------------------:| :---: | :---: |  :---: | :---: | :---: | :---: | :---: | :---: |\n",
-    "| ✅ |                          ✅                           | ✅ | ❌ | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ |\n",
+    "| ✅ |                          ✅                           | ✅ | ✅ | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ |\n",
     "\n",
     "## Setup\n",
     "\n",
@@ -45,17 +49,17 @@
     "    * macOS users can install via Homebrew with `brew install ollama` and start with `brew services start ollama`\n",
     "* Fetch available LLM model via `ollama pull <name-of-model>`\n",
     "    * View a list of available models via the [model library](https://ollama.ai/library)\n",
-    "    * e.g., `ollama pull llama3`\n",
+    "    * e.g., `ollama pull gpt-oss:20b`\n",
     "* This will download the default tagged version of the model. Typically, the default points to the latest, smallest sized-parameter model.\n",
     "\n",
     "> On Mac, the models will be download to `~/.ollama/models`\n",
     ">\n",
     "> On Linux (or WSL), the models will be stored at `/usr/share/ollama/.ollama/models`\n",
     "\n",
-    "* Specify the exact version of the model of interest as such `ollama pull vicuna:13b-v1.5-16k-q4_0` (View the [various tags for the `Vicuna`](https://ollama.ai/library/vicuna/tags) model in this instance)\n",
+    "* Specify the exact version of the model of interest as such `ollama pull gpt-oss:20b`\n",
     "* To view all pulled models, use `ollama list`\n",
     "* To chat directly with a model from the command line, use `ollama run <name-of-model>`\n",
-    "* View the [Ollama documentation](https://github.com/ollama/ollama/tree/main/docs) for more commands. You can run `ollama help` in the terminal to see available commands.\n"
+    "* View the [Ollama documentation](https://github.com/ollama/ollama/blob/main/docs/README.md) for more commands. You can run `ollama help` in the terminal to see available commands.\n"
    ]
   },
   {
@@ -102,7 +106,11 @@
    "id": "b18bd692076f7cf7",
    "metadata": {},
    "source": [
-    "Make sure you're using the latest Ollama version for structured outputs. Update by running:"
+    ":::warning\n",
+    "Make sure you're using the latest Ollama client version!\n",
+    ":::\n",
+    "\n",
+    "Update by running:"
    ]
   },
   {
@@ -127,15 +135,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 2,
    "id": "cb09c344-1836-4e0c-acf8-11d13ac1dbae",
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_ollama import ChatOllama\n",
+    "from langchain_ollama.v1 import ChatOllama\n",
     "\n",
     "llm = ChatOllama(\n",
-    "    model=\"llama3.1\",\n",
+    "    model=\"gpt-oss:20b\",\n",
+    "    validate_model_on_init=True,\n",
     "    temperature=0,\n",
     "    # other params...\n",
     ")"
@@ -158,46 +167,56 @@
    },
    "outputs": [
     {
-     "data": {
-      "text/plain": [
-       "AIMessage(content='The translation of \"I love programming\" in French is:\\n\\n\"J\\'adore le programmation.\"', additional_kwargs={}, response_metadata={'model': 'llama3.1', 'created_at': '2025-06-25T18:43:00.483666Z', 'done': True, 'done_reason': 'stop', 'total_duration': 619971208, 'load_duration': 27793125, 'prompt_eval_count': 35, 'prompt_eval_duration': 36354583, 'eval_count': 22, 'eval_duration': 555182667, 'model_name': 'llama3.1'}, id='run--348bb5ef-9dd9-4271-bc7e-a9ddb54c28c1-0', usage_metadata={'input_tokens': 35, 'output_tokens': 22, 'total_tokens': 57})"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "AIMessage(type='ai', name=None, id='lc_run--5521db11-a5eb-4e46-956c-1455151cdaa3-0', lc_version='v1', content=[{'type': 'text', 'text': 'The translation of \"I love programming\" to French is:\\n\\n\"Je aime le programmation\"\\n\\nHowever, a more common and idiomatic way to express this in French would be:\\n\\n\"J\\'aime programmer\"\\n\\nThis phrase uses the verb \"aimer\" (to love) in the present tense, which is more suitable for expressing a general feeling or preference.'}], usage_metadata={'input_tokens': 34, 'output_tokens': 73, 'total_tokens': 107}, response_metadata={'model_name': 'llama3.2', 'created_at': '2025-08-08T23:07:44.439483Z', 'done': True, 'done_reason': 'stop', 'total_duration': 1410566833, 'load_duration': 28419542, 'prompt_eval_count': 34, 'prompt_eval_duration': 141642125, 'eval_count': 73, 'eval_duration': 1240075000}, parsed=None)\n",
+      "\n",
+      "Content:\n",
+      "The translation of \"I love programming\" to French is:\n",
+      "\n",
+      "\"Je aime le programmation\"\n",
+      "\n",
+      "However, a more common and idiomatic way to express this in French would be:\n",
+      "\n",
+      "\"J'aime programmer\"\n",
+      "\n",
+      "This phrase uses the verb \"aimer\" (to love) in the present tense, which is more suitable for expressing a general feeling or preference.\n"
+     ]
     }
    ],
    "source": [
-    "messages = [\n",
-    "    (\n",
-    "        \"system\",\n",
-    "        \"You are a helpful assistant that translates English to French. Translate the user sentence.\",\n",
-    "    ),\n",
-    "    (\"human\", \"I love programming.\"),\n",
-    "]\n",
-    "ai_msg = llm.invoke(messages)\n",
-    "ai_msg"
+    "ai_msg = llm.invoke(\"Translate 'I love programming' to French.\")\n",
+    "print(f\"{ai_msg}\\n\")\n",
+    "print(f\"Content:\\n{ai_msg.text}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ede35e47",
+   "metadata": {},
+   "source": [
+    "## Streaming"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
-   "id": "d86145b3-bfef-46e8-b227-4dda5c9c2705",
+   "execution_count": 10,
+   "id": "77474829",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "The translation of \"I love programming\" in French is:\n",
-      "\n",
-      "\"J'adore le programmation.\"\n"
+      "Hi| there|!| I|'m| just| a| chat|bot|,| so| I| don|'t| have| feelings|,| but| I|'m| here| and| ready| to| help| you| with| anything| you| need|!| How| can| I| assist| you| today|?| 😊|"
      ]
     }
    ],
    "source": [
-    "print(ai_msg.content)"
+    "for chunk in llm.stream(\"How are you doing?\"):\n",
+    "    if chunk.text:\n",
+    "        print(chunk.text, end=\"|\", flush=True)"
    ]
   },
   {
@@ -219,10 +238,10 @@
     {
      "data": {
       "text/plain": [
-       "AIMessage(content='\"Programmieren ist meine Leidenschaft.\"\\n\\n(I translated \"programming\" to the German word \"Programmieren\", and added \"ist meine Leidenschaft\" which means \"is my passion\")', additional_kwargs={}, response_metadata={'model': 'llama3.1', 'created_at': '2025-06-25T18:43:29.350032Z', 'done': True, 'done_reason': 'stop', 'total_duration': 1194744459, 'load_duration': 26982500, 'prompt_eval_count': 30, 'prompt_eval_duration': 117043458, 'eval_count': 41, 'eval_duration': 1049892167, 'model_name': 'llama3.1'}, id='run--efc6436e-2346-43d9-8118-3c20b3cdf0d0-0', usage_metadata={'input_tokens': 30, 'output_tokens': 41, 'total_tokens': 71})"
+       "'Ich liebe Programmierung.'"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -241,13 +260,15 @@
     ")\n",
     "\n",
     "chain = prompt | llm\n",
-    "chain.invoke(\n",
+    "result = chain.invoke(\n",
     "    {\n",
     "        \"input_language\": \"English\",\n",
     "        \"output_language\": \"German\",\n",
     "        \"input\": \"I love programming.\",\n",
     "    }\n",
-    ")"
+    ")\n",
+    "\n",
+    "result.text"
    ]
   },
   {
@@ -257,10 +278,10 @@
    "source": [
     "## Tool calling\n",
     "\n",
-    "We can use [tool calling](/docs/concepts/tool_calling/) with an LLM [that has been fine-tuned for tool use](https://ollama.com/search?&c=tools) such as `llama3.1`:\n",
+    "We can use [tool calling](/docs/concepts/tool_calling/) with an LLM [that has been fine-tuned for tool use](https://ollama.com/search?&c=tools) such as `gpt-oss`:\n",
     "\n",
     "```\n",
-    "ollama pull llama3.1\n",
+    "ollama pull gpt-oss:20b\n",
     "```\n",
     "\n",
     "Details on creating custom tools are available in [this guide](/docs/how_to/custom_tools/). Below, we demonstrate how to create a tool using the `@tool` decorator on a normal python function."
@@ -276,16 +297,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[{'name': 'validate_user', 'args': {'addresses': ['123 Fake St, Boston, MA', '234 Pretend Boulevard, Houston, TX'], 'user_id': '123'}, 'id': 'aef33a32-a34b-4b37-b054-e0d85584772f', 'type': 'tool_call'}]\n"
+      "[{'type': 'tool_call', 'id': 'f365489e-1dc4-4d60-aaff-e56290ae4f99', 'name': 'validate_user', 'args': {'addresses': ['123 Fake St in Boston MA', '234 Pretend Boulevard in Houston TX'], 'user_id': 123}}]\n"
      ]
     }
    ],
    "source": [
     "from typing import List\n",
     "\n",
-    "from langchain_core.messages import AIMessage\n",
+    "from langchain_core.v1.messages import AIMessage\n",
     "from langchain_core.tools import tool\n",
-    "from langchain_ollama import ChatOllama\n",
+    "from langchain_ollama.v1 import ChatOllama\n",
     "\n",
     "\n",
     "@tool\n",
@@ -300,7 +321,8 @@
     "\n",
     "\n",
     "llm = ChatOllama(\n",
-    "    model=\"llama3.1\",\n",
+    "    model=\"gpt-oss:20b\",\n",
+    "    validate_model_on_init=True,\n",
     "    temperature=0,\n",
     ").bind_tools([validate_user])\n",
     "\n",
@@ -314,6 +336,50 @@
     "    print(result.tool_calls)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "4321b6a8",
+   "metadata": {},
+   "source": [
+    "## Structured output"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "20f8ae70",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Name: Alice, Age: 28, Job: Software Engineer\n"
+     ]
+    }
+   ],
+   "source": [
+    "from langchain_ollama.v1 import ChatOllama\n",
+    "from pydantic import BaseModel, Field\n",
+    "\n",
+    "llm = ChatOllama(model=\"llama3.2\", validate_model_on_init=True, temperature=0)\n",
+    "\n",
+    "\n",
+    "class Person(BaseModel):\n",
+    "    \"\"\"Information about a person.\"\"\"\n",
+    "\n",
+    "    name: str = Field(description=\"The person's full name\")\n",
+    "    age: int = Field(description=\"The person's age in years\")\n",
+    "    occupation: str = Field(description=\"The person's job or profession\")\n",
+    "\n",
+    "\n",
+    "structured_llm = llm.with_structured_output(Person)\n",
+    "response: Person = structured_llm.invoke(\n",
+    "    \"Tell me about a fictional software engineer named Alice who is 28 years old.\"\n",
+    ")\n",
+    "print(f\"Name: {response.name}, Age: {response.age}, Job: {response.occupation}\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "4c5e0197",
@@ -321,11 +387,9 @@
    "source": [
     "## Multi-modal\n",
     "\n",
-    "Ollama has support for multi-modal LLMs, such as [bakllava](https://ollama.com/library/bakllava) and [llava](https://ollama.com/library/llava).\n",
+    "Ollama has limited support for multi-modal LLMs, such as [gemma3](https://ollama.com/library/gemma3).\n",
     "\n",
-    "    ollama pull bakllava\n",
-    "\n",
-    "Be sure to update Ollama so that you have the most recent version to support multi-modal."
+    "### Image input"
    ]
   },
   {
@@ -408,15 +472,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "90%\n"
+      "Based on the image, the dollar-based gross retention rate is **90%**.\n"
      ]
     }
    ],
    "source": [
-    "from langchain_core.messages import HumanMessage\n",
-    "from langchain_ollama import ChatOllama\n",
+    "from langchain_core.v1.messages import HumanMessage\n",
+    "from langchain_ollama.v1 import ChatOllama\n",
     "\n",
-    "llm = ChatOllama(model=\"bakllava\", temperature=0)\n",
+    "llm = ChatOllama(model=\"gemma3:4b\", validate_model_on_init=True, temperature=0)\n",
     "\n",
     "\n",
     "def prompt_func(data):\n",
@@ -424,8 +488,9 @@
     "    image = data[\"image\"]\n",
     "\n",
     "    image_part = {\n",
-    "        \"type\": \"image_url\",\n",
-    "        \"image_url\": f\"data:image/jpeg;base64,{image}\",\n",
+    "        \"type\": \"image\",\n",
+    "        \"base64\": f\"data:image/jpeg;base64,{image}\",\n",
+    "        \"mime_type\": \"image/jpeg\",\n",
     "    }\n",
     "\n",
     "    content_parts = []\n",
@@ -435,7 +500,7 @@
     "    content_parts.append(image_part)\n",
     "    content_parts.append(text_part)\n",
     "\n",
-    "    return [HumanMessage(content=content_parts)]\n",
+    "    return [HumanMessage(content_parts)]\n",
     "\n",
     "\n",
     "from langchain_core.output_parsers import StrOutputParser\n",
@@ -454,11 +519,9 @@
    "id": "fb6a331f-1507-411f-89e5-c4d598154f3c",
    "metadata": {},
    "source": [
-    "## Reasoning models and custom message roles\n",
+    "## Reasoning models\n",
     "\n",
-    "Some models, such as IBM's [Granite 3.2](https://ollama.com/library/granite3.2), support custom message roles to enable thinking processes.\n",
-    "\n",
-    "To access Granite 3.2's thinking features, pass a message with a `\"control\"` role with content set to `\"thinking\"`. Because `\"control\"` is a non-standard message role, we can use a [ChatMessage](https://python.langchain.com/api_reference/core/messages/langchain_core.messages.chat.ChatMessage.html) object to implement it:"
+    "Many models support outputting their reasoning process in addition to the final answer. This is useful for debugging and understanding how the model arrived at its conclusion. This train of thought reasoning is available in models such as `gpt-oss`, `qwen3:8b`, and `deepseek-r1`. To enable reasoning output, set the `reasoning` parameter to `True` either when instantiating the model or during invocation."
    ]
   },
   {
@@ -471,30 +534,25 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Here is my thought process:\n",
-      "The user is asking for the value of 3 raised to the power of 3, which is a basic exponentiation operation.\n",
-      "\n",
-      "Here is my response:\n",
-      "\n",
-      "3^3 (read as \"3 to the power of 3\") equals 27. \n",
-      "\n",
-      "This calculation is performed by multiplying 3 by itself three times: 3*3*3 = 27.\n"
+      "Response including reasoning: [{'type': 'reasoning', 'reasoning': \"Okay, so I need to figure out what 3^3 is. Let me start by recalling what exponents mean. From what I remember, when you have a number raised to a power, like a^b, it means you multiply the number by itself b times. So, for example, 2^3 would be 2 multiplied by itself three times: 2 × 2 × 2. Let me check if that's right. Yeah, I think that's correct. So applying that to 3^3, it should be 3 multiplied by itself three times.\\n\\nWait, let me make sure I'm not confusing the base and the exponent. The base is the number being multiplied, and the exponent is how many times it's multiplied. So in 3^3, the base is 3 and the exponent is 3. That means I need to multiply 3 by itself three times. Let me write that out step by step.\\n\\nFirst, multiply the first two 3s: 3 × 3. What's 3 times 3? That's 9. Okay, so the first multiplication gives me 9. Now, I need to multiply that result by the third 3. So 9 × 3. Let me calculate that. 9 times 3 is... 27. So putting it all together, 3 × 3 × 3 equals 27. \\n\\nWait, let me verify that again. Maybe I should do it in a different way to make sure I didn't make a mistake. Let's break it down. 3^3 is the same as 3 × 3 × 3. Let me compute 3 × 3 first, which is 9, and then multiply that by 3. 9 × 3 is indeed 27. Hmm, that seems right. \\n\\nAlternatively, I can think of exponents as repeated multiplication. So 3^1 is 3, 3^2 is 3 × 3 = 9, and 3^3 is 3 × 3 × 3 = 27. Yeah, that progression makes sense. Each time the exponent increases by 1, you multiply by the base again. So starting from 3^1 = 3, then 3^2 is 3 × 3 = 9, then 3^3 is 9 × 3 = 27. \\n\\nIs there another way to check this? Maybe using exponent rules. For example, if I know that 3^2 is 9, then multiplying by another 3 would give me 3^3. Since 9 × 3 is 27, that confirms it again. \\n\\nAlternatively, maybe I can use logarithms or something else, but that might be overcomplicating. Since exponents are straightforward multiplication, I think my initial calculation is correct. \\n\\nWait, just to be thorough, maybe I can use a calculator to verify. Let me imagine pressing 3, then the exponent key, then 3. If I do that, it should give me 27. Yeah, that's what I remember. So all methods point to 27. \\n\\nI think I've checked it multiple ways: breaking down the multiplication step by step, using the exponent progression, and even considering a calculator verification. All of them lead to the same answer. Therefore, I'm confident that 3^3 equals 27.\\n\"}, {'type': 'text', 'text': 'To determine the value of $3^3$, we start by understanding what an exponent represents. The expression $a^b$ means multiplying the base $a$ by itself $b$ times. \\n\\n### Step-by-Step Calculation:\\n1. **Identify the base and exponent**:  \\n   In $3^3$, the base is **3**, and the exponent is **3**. This means we multiply 3 by itself three times.\\n\\n2. **Perform the multiplication**:  \\n   - First, multiply the first two 3s:  \\n     $3 \\\\times 3 = 9$  \\n   - Next, multiply the result by the third 3:  \\n     $9 \\\\times 3 = 27$\\n\\n3. **Verify the result**:  \\n   - $3^1 = 3$  \\n   - $3^2 = 3 \\\\times 3 = 9$  \\n   - $3^3 = 3 \\\\times 3 \\\\times 3 = 27$  \\n   This progression confirms the calculation.\\n\\n### Final Answer:\\n$$\\n3^3 = \\\\boxed{27}\\n$$'}]\n",
+      "Response without reasoning: [{'type': 'text', 'text': \"Sure! Let's break down what **3³** means and how to calculate it step by step.\\n\\n---\\n\\n### Step 1: Understand the notation\\nThe expression **3³** means **3 multiplied by itself three times**. The small number (3) is called the **exponent**, and it tells us how many times the base number (3) is used as a factor.\\n\\nSo:\\n$$\\n3^3 = 3 \\\\times 3 \\\\times 3\\n$$\\n\\n---\\n\\n### Step 2: Perform the multiplication step by step\\n\\n1. Multiply the first two 3s:\\n   $$\\n   3 \\\\times 3 = 9\\n   $$\\n\\n2. Now multiply the result by the third 3:\\n   $$\\n   9 \\\\times 3 = 27\\n   $$\\n\\n---\\n\\n### Step 3: Final Answer\\n\\n$$\\n3^3 = 27\\n$$\\n\\n---\\n\\n### Summary\\n- **3³** means **3 × 3 × 3**\\n- **3 × 3 = 9**\\n- **9 × 3 = 27**\\n- So, **3³ = 27**\\n\\nLet me know if you'd like to explore exponents further!\"}]\n"
      ]
     }
    ],
    "source": [
-    "from langchain_core.messages import ChatMessage, HumanMessage\n",
-    "from langchain_ollama import ChatOllama\n",
+    "from langchain_ollama.v1 import ChatOllama\n",
     "\n",
-    "llm = ChatOllama(model=\"granite3.2:8b\")\n",
+    "# All outputs from `llm` will include reasoning unless overridden during invocation\n",
+    "llm = ChatOllama(model=\"qwen3:8b\", validate_model_on_init=True, reasoning=True)\n",
     "\n",
-    "messages = [\n",
-    "    ChatMessage(role=\"control\", content=\"thinking\"),\n",
-    "    HumanMessage(\"What is 3^3?\"),\n",
-    "]\n",
+    "response_a = llm.invoke(\"What is 3^3? Explain your reasoning step by step.\")\n",
+    "print(f\"Response including reasoning: {response_a.content}\")\n",
     "\n",
-    "response = llm.invoke(messages)\n",
-    "print(response.content)"
+    "# Test override; note no ReasoningContentBlock in the response\n",
+    "response_b = llm.invoke(\n",
+    "    \"What is 3^3? Explain your reasoning step by step.\", reasoning=False\n",
+    ")\n",
+    "print(f\"Response without reasoning: {response_b.content}\")"
    ]
   },
   {
@@ -502,7 +560,7 @@
    "id": "6271d032-da40-44d4-9b52-58370e164be3",
    "metadata": {},
    "source": [
-    "Note that the model exposes its thought process in addition to its final response."
+    "Note that the model exposes its thought process as a `ReasoningContentBlock` addition to its final response."
    ]
   },
   {

docs/docs/integrations/chat/openai.ipynb

@@ -447,6 +447,163 @@
     ")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "c5d9d19d-8ab1-4d9d-b3a0-56ee4e89c528",
+   "metadata": {},
+   "source": [
+    "### Custom tools\n",
+    "\n",
+    ":::info Requires ``langchain-openai>=0.3.29``\n",
+    "\n",
+    ":::\n",
+    "\n",
+    "[Custom tools](https://platform.openai.com/docs/guides/function-calling#custom-tools) support tools with arbitrary string inputs. They can be particularly useful when you expect your string arguments to be long or complex."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "a47c809b-852f-46bd-8b9e-d9534c17213d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "================================\u001b[1m Human Message \u001b[0m=================================\n",
+      "\n",
+      "Use the tool to calculate 3^3.\n",
+      "==================================\u001b[1m Ai Message \u001b[0m==================================\n",
+      "\n",
+      "[{'id': 'rs_6894ff5747c0819d9b02fc5645b0be9c000169fd9fb68d99', 'summary': [], 'type': 'reasoning'}, {'call_id': 'call_7SYwMSQPbbEqFcKlKOpXeEux', 'input': 'print(3**3)', 'name': 'execute_code', 'type': 'custom_tool_call', 'id': 'ctc_6894ff5b9f54819d8155a63638d34103000169fd9fb68d99', 'status': 'completed'}]\n",
+      "Tool Calls:\n",
+      "  execute_code (call_7SYwMSQPbbEqFcKlKOpXeEux)\n",
+      " Call ID: call_7SYwMSQPbbEqFcKlKOpXeEux\n",
+      "  Args:\n",
+      "    __arg1: print(3**3)\n",
+      "=================================\u001b[1m Tool Message \u001b[0m=================================\n",
+      "Name: execute_code\n",
+      "\n",
+      "[{'type': 'custom_tool_call_output', 'output': '27'}]\n",
+      "==================================\u001b[1m Ai Message \u001b[0m==================================\n",
+      "\n",
+      "[{'type': 'text', 'text': '27', 'annotations': [], 'id': 'msg_6894ff5db3b8819d9159b3a370a25843000169fd9fb68d99'}]\n"
+     ]
+    }
+   ],
+   "source": [
+    "from langchain_openai import ChatOpenAI, custom_tool\n",
+    "from langgraph.prebuilt import create_react_agent\n",
+    "\n",
+    "\n",
+    "@custom_tool\n",
+    "def execute_code(code: str) -> str:\n",
+    "    \"\"\"Execute python code.\"\"\"\n",
+    "    return \"27\"\n",
+    "\n",
+    "\n",
+    "llm = ChatOpenAI(model=\"gpt-5\", output_version=\"responses/v1\")\n",
+    "\n",
+    "agent = create_react_agent(llm, [execute_code])\n",
+    "\n",
+    "input_message = {\"role\": \"user\", \"content\": \"Use the tool to calculate 3^3.\"}\n",
+    "for step in agent.stream(\n",
+    "    {\"messages\": [input_message]},\n",
+    "    stream_mode=\"values\",\n",
+    "):\n",
+    "    step[\"messages\"][-1].pretty_print()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5ef93be6-6d4c-4eea-acfd-248774074082",
+   "metadata": {},
+   "source": [
+    "<details>\n",
+    "<summary>Context-free grammars</summary>\n",
+    "\n",
+    "OpenAI supports the specification of a [context-free grammar](https://platform.openai.com/docs/guides/function-calling#context-free-grammars) for custom tool inputs in `lark` or `regex` format. See [OpenAI docs](https://platform.openai.com/docs/guides/function-calling#context-free-grammars) for details. The `format` parameter can be passed into `@custom_tool` as shown below:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "2ae04586-be33-49c6-8947-7867801d868f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "================================\u001b[1m Human Message \u001b[0m=================================\n",
+      "\n",
+      "Use the tool to calculate 3^3.\n",
+      "==================================\u001b[1m Ai Message \u001b[0m==================================\n",
+      "\n",
+      "[{'id': 'rs_689500828a8481a297ff0f98e328689c0681550c89797f43', 'summary': [], 'type': 'reasoning'}, {'call_id': 'call_jzH01RVhu6EFz7yUrOFXX55s', 'input': '3 * 3 * 3', 'name': 'do_math', 'type': 'custom_tool_call', 'id': 'ctc_6895008d57bc81a2b84d0993517a66b90681550c89797f43', 'status': 'completed'}]\n",
+      "Tool Calls:\n",
+      "  do_math (call_jzH01RVhu6EFz7yUrOFXX55s)\n",
+      " Call ID: call_jzH01RVhu6EFz7yUrOFXX55s\n",
+      "  Args:\n",
+      "    __arg1: 3 * 3 * 3\n",
+      "=================================\u001b[1m Tool Message \u001b[0m=================================\n",
+      "Name: do_math\n",
+      "\n",
+      "[{'type': 'custom_tool_call_output', 'output': '27'}]\n",
+      "==================================\u001b[1m Ai Message \u001b[0m==================================\n",
+      "\n",
+      "[{'type': 'text', 'text': '27', 'annotations': [], 'id': 'msg_6895009776b881a2a25f0be8507d08f20681550c89797f43'}]\n"
+     ]
+    }
+   ],
+   "source": [
+    "from langchain_openai import ChatOpenAI, custom_tool\n",
+    "from langgraph.prebuilt import create_react_agent\n",
+    "\n",
+    "grammar = \"\"\"\n",
+    "start: expr\n",
+    "expr: term (SP ADD SP term)* -> add\n",
+    "| term\n",
+    "term: factor (SP MUL SP factor)* -> mul\n",
+    "| factor\n",
+    "factor: INT\n",
+    "SP: \" \"\n",
+    "ADD: \"+\"\n",
+    "MUL: \"*\"\n",
+    "%import common.INT\n",
+    "\"\"\"\n",
+    "\n",
+    "format_ = {\"type\": \"grammar\", \"syntax\": \"lark\", \"definition\": grammar}\n",
+    "\n",
+    "\n",
+    "# highlight-next-line\n",
+    "@custom_tool(format=format_)\n",
+    "def do_math(input_string: str) -> str:\n",
+    "    \"\"\"Do a mathematical operation.\"\"\"\n",
+    "    return \"27\"\n",
+    "\n",
+    "\n",
+    "llm = ChatOpenAI(model=\"gpt-5\", output_version=\"responses/v1\")\n",
+    "\n",
+    "agent = create_react_agent(llm, [do_math])\n",
+    "\n",
+    "input_message = {\"role\": \"user\", \"content\": \"Use the tool to calculate 3^3.\"}\n",
+    "for step in agent.stream(\n",
+    "    {\"messages\": [input_message]},\n",
+    "    stream_mode=\"values\",\n",
+    "):\n",
+    "    step[\"messages\"][-1].pretty_print()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c63430c9-c7b0-4e92-a491-3f165dddeb8f",
+   "metadata": {},
+   "source": [
+    "</details>"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "84833dd0-17e9-4269-82ed-550639d65751",

docs/docs/integrations/document_loaders/agentql.ipynb

@@ -69,7 +69,7 @@
       },
       "outputs": [],
       "source": [
-        "%pip install -qU langchain_agentql"
+        "%pip install -qU langchain-agentql"
       ]
     },
     {

docs/docs/integrations/document_loaders/amazon_textract.ipynb

@@ -310,7 +310,7 @@
     "from langchain_openai import OpenAI\n",
     "\n",
     "chain = load_qa_chain(llm=OpenAI(), chain_type=\"map_reduce\")\n",
-    "query = [\"Who are the autors?\"]\n",
+    "query = [\"Who are the authors?\"]\n",
     "\n",
     "chain.run(input_documents=documents, question=query)"
    ]

docs/docs/integrations/document_loaders/azure_ai_data.ipynb

@@ -25,7 +25,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%pip install --upgrade --quiet  azureml-fsspec, azure-ai-generative"
+    "%pip install --upgrade --quiet azureml-fsspec azure-ai-generative"
    ]
   },
   {

docs/docs/integrations/document_loaders/bshtml.ipynb

@@ -16,7 +16,7 @@
         "\n",
         "| Class | Package | Local | Serializable | JS support|\n",
         "| :--- | :--- | :---: | :---: |  :---: |\n",
-        "| [BSHTMLLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.html_bs.BSHTMLLoader.html) | [langchain_community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ❌ | \n",
+        "| [BSHTMLLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.html_bs.BSHTMLLoader.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ❌ | \n",
         "### Loader features\n",
         "| Source | Document Lazy Loading | Native Async Support\n",
         "| :---: | :---: | :---: | \n",
@@ -52,7 +52,7 @@
       "source": [
         "### Installation\n",
         "\n",
-        "Install **langchain_community** and **bs4**."
+        "Install **langchain-community** and **bs4**."
       ]
     },
     {
@@ -61,7 +61,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "%pip install -qU langchain_community bs4"
+        "%pip install -qU langchain-community bs4"
       ]
     },
     {

docs/docs/integrations/document_loaders/docling.ipynb

@@ -245,7 +245,7 @@
     }
    ],
    "source": [
-    "%pip install -q --progress-bar off --no-warn-conflicts langchain-core langchain-huggingface langchain_milvus langchain python-dotenv"
+    "%pip install -q --progress-bar off --no-warn-conflicts langchain-core langchain-huggingface langchain-milvus langchain python-dotenv"
    ]
   },
   {

docs/docs/integrations/document_loaders/firecrawl.ipynb

@@ -15,7 +15,7 @@
     "\n",
     "| Class | Package | Local | Serializable | [JS support](https://js.langchain.com/docs/integrations/document_loaders/web_loaders/firecrawl/)|\n",
     "| :--- | :--- | :---: | :---: |  :---: |\n",
-    "| [FireCrawlLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.firecrawl.FireCrawlLoader.html) | [langchain_community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ✅ | \n",
+    "| [FireCrawlLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.firecrawl.FireCrawlLoader.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ✅ | \n",
     "### Loader features\n",
     "| Source | Document Lazy Loading | Native Async Support\n",
     "| :---: | :---: | :---: | \n",

docs/docs/integrations/document_loaders/json.ipynb

@@ -15,7 +15,7 @@
         "\n",
         "| Class | Package | Local | Serializable | [JS support](https://js.langchain.com/docs/integrations/document_loaders/file_loaders/json/)|\n",
         "| :--- | :--- | :---: | :---: |  :---: |\n",
-        "| [JSONLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.json_loader.JSONLoader.html) | [langchain_community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ✅ | \n",
+        "| [JSONLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.json_loader.JSONLoader.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ✅ | \n",
         "### Loader features\n",
         "| Source | Document Lazy Loading | Native Async Support\n",
         "| :---: | :---: | :---: | \n",
@@ -51,7 +51,7 @@
       "source": [
         "### Installation\n",
         "\n",
-        "Install **langchain_community** and **jq**:"
+        "Install **langchain-community** and **jq**:"
       ]
     },
     {
@@ -60,7 +60,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "%pip install -qU langchain_community jq "
+        "%pip install -qU langchain-community jq "
       ]
     },
     {

docs/docs/integrations/document_loaders/mathpix.ipynb

@@ -13,7 +13,7 @@
         "\n",
         "| Class | Package | Local | Serializable | JS support|\n",
         "| :--- | :--- | :---: | :---: |  :---: |\n",
-        "| [MathPixPDFLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.pdf.MathpixPDFLoader.html) | [langchain_community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ❌ | \n",
+        "| [MathPixPDFLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.pdf.MathpixPDFLoader.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ❌ | \n",
         "### Loader features\n",
         "| Source | Document Lazy Loading | Native Async Support\n",
         "| :---: | :---: | :---: | \n",
@@ -60,7 +60,7 @@
       "source": [
         "### Installation\n",
         "\n",
-        "Install **langchain_community**."
+        "Install **langchain-community**."
       ]
     },
     {
@@ -69,7 +69,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "%pip install -qU langchain_community"
+        "%pip install -qU langchain-community"
       ]
     },
     {

docs/docs/integrations/document_loaders/open_city_data.ipynb

@@ -15,7 +15,7 @@
    "source": [
     "[Socrata](https://dev.socrata.com/foundry/data.sfgov.org/vw6y-z8j6) provides an API for city open data. \n",
     "\n",
-    "For a dataset such as [SF crime](https://data.sfgov.org/Public-Safety/Police-Department-Incident-Reports-Historical-2003/tmnf-yvry), to to the `API` tab on top right. \n",
+    "For a dataset such as [SF crime](https://data.sfgov.org/Public-Safety/Police-Department-Incident-Reports-Historical-2003/tmnf-yvry), see the `API` tab on top right. \n",
     "\n",
     "That provides you with the `dataset identifier`.\n",
     "\n",

docs/docs/integrations/document_loaders/pdfminer.ipynb

@@ -15,7 +15,7 @@
     "\n",
     "| Class                                                                                                                                                | Package | Local | Serializable | JS support|\n",
     "|:-----------------------------------------------------------------------------------------------------------------------------------------------------| :--- | :---: | :---: |  :---: |\n",
-    "| [PDFMinerLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.pdf.PDFMinerLoader.html) | [langchain_community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ❌ |\n",
+    "| [PDFMinerLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.pdf.PDFMinerLoader.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ❌ |\n",
     "\n",
     "---------   \n",
     "\n",
@@ -60,7 +60,7 @@
    "source": [
     "### Installation\n",
     "\n",
-    "Install **langchain_community** and **pdfminer**."
+    "Install **langchain-community** and **pdfminer**."
    ]
   },
   {
@@ -82,7 +82,7 @@
     }
    ],
    "source": [
-    "%pip install -qU langchain_community pdfminer.six"
+    "%pip install -qU langchain-community pdfminer.six"
    ]
   },
   {
@@ -938,7 +938,7 @@
     }
    ],
    "source": [
-    "%pip install -qU langchain_openai"
+    "%pip install -qU langchain-openai"
    ]
   },
   {

docs/docs/integrations/document_loaders/pdfplumber.ipynb

@@ -13,7 +13,7 @@
         "\n",
         "| Class | Package | Local | Serializable | JS support|\n",
         "| :--- | :--- | :---: | :---: |  :---: |\n",
-        "| [PDFPlumberLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.pdf.PDFPlumberLoader.html) | [langchain_community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ❌ | \n",
+        "| [PDFPlumberLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.pdf.PDFPlumberLoader.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ❌ | \n",
         "### Loader features\n",
         "| Source | Document Lazy Loading | Native Async Support\n",
         "| :---: | :---: | :---: | \n",
@@ -47,7 +47,7 @@
       "source": [
         "### Installation\n",
         "\n",
-        "Install **langchain_community**."
+        "Install **langchain-community**."
       ]
     },
     {
@@ -56,7 +56,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "%pip install -qU langchain_community"
+        "%pip install -qU langchain-community"
       ]
     },
     {

docs/docs/integrations/document_loaders/powerscale.ipynb

@@ -117,7 +117,7 @@
    "metadata": {},
    "source": [
     "The fields:\n",
-    " - `es_host_url` is the endpoint to to MetadataIQ Elasticsearch database\n",
+    " - `es_host_url` is the endpoint to MetadataIQ Elasticsearch database\n",
     " - `es_index_index` is the name of the index where PowerScale writes it file system metadata\n",
     " - `es_api_key` is the **encoded** version of your elasticsearch API key\n",
     " - `folder_path` is the path on PowerScale to be queried for changes"

docs/docs/integrations/document_loaders/pymupdf.ipynb

@@ -15,7 +15,7 @@
     "\n",
     "| Class | Package | Local | Serializable | JS support|\n",
     "| :--- | :--- | :---: | :---: |  :---: |\n",
-    "| [PyMuPDFLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.pdf.PyMuPDFLoader.html) | [langchain_community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ❌ | \n",
+    "| [PyMuPDFLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.pdf.PyMuPDFLoader.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ❌ | \n",
     "\n",
     "---------   \n",
     "\n",
@@ -60,7 +60,7 @@
    "source": [
     "### Installation\n",
     "\n",
-    "Install **langchain_community** and **pymupdf**."
+    "Install **langchain-community** and **pymupdf**."
    ]
   },
   {
@@ -71,7 +71,7 @@
      "start_time": "2025-01-16T09:48:33.057015Z"
     }
    },
-   "source": "%pip install -qU langchain_community pymupdf",
+   "source": "%pip install -qU langchain-community pymupdf",
    "outputs": [
     {
      "name": "stdout",
@@ -569,7 +569,7 @@
     }
    },
    "source": [
-    "%pip install -qU langchain_openai"
+    "%pip install -qU langchain-openai"
    ],
    "outputs": [
     {

docs/docs/integrations/document_loaders/pymupdf4llm.ipynb

@@ -23,7 +23,7 @@
         "\n",
         "| Class | Package | Local | Serializable | JS support |\n",
         "| :--- | :--- | :---: | :---: |  :---: |\n",
-        "| [PyMuPDF4LLMLoader](https://github.com/lakinduboteju/langchain-pymupdf4llm) | [langchain_pymupdf4llm](https://pypi.org/project/langchain-pymupdf4llm) | ✅ | ❌ | ❌ |\n",
+        "| [PyMuPDF4LLMLoader](https://github.com/lakinduboteju/langchain-pymupdf4llm) | [langchain-pymupdf4llm](https://pypi.org/project/langchain-pymupdf4llm) | ✅ | ❌ | ❌ |\n",
         "\n",
         "### Loader features\n",
         "\n",
@@ -61,7 +61,7 @@
       "source": [
         "### Installation\n",
         "\n",
-        "Install **langchain_community** and **langchain-pymupdf4llm**."
+        "Install **langchain-community** and **langchain-pymupdf4llm**."
       ]
     },
     {
@@ -78,7 +78,7 @@
         }
       ],
       "source": [
-        "%pip install -qU langchain_community langchain-pymupdf4llm"
+        "%pip install -qU langchain-community langchain-pymupdf4llm"
       ]
     },
     {
@@ -554,7 +554,7 @@
         }
       ],
       "source": [
-        "%pip install -qU langchain_openai"
+        "%pip install -qU langchain-openai"
       ]
     },
     {

docs/docs/integrations/document_loaders/pypdfdirectory.ipynb

@@ -14,7 +14,7 @@
         "\n",
         "| Class | Package | Local | Serializable | JS support|\n",
         "| :--- | :--- | :---: | :---: |  :---: |\n",
-        "| [PyPDFDirectoryLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.pdf.PyPDFDirectoryLoader.html) | [langchain_community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ❌ | \n",
+        "| [PyPDFDirectoryLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.pdf.PyPDFDirectoryLoader.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ❌ | \n",
         "### Loader features\n",
         "| Source | Document Lazy Loading | Native Async Support\n",
         "| :---: | :---: | :---: | \n",
@@ -53,7 +53,7 @@
       "source": [
         "### Installation\n",
         "\n",
-        "Install **langchain_community**."
+        "Install **langchain-community**."
       ]
     },
     {
@@ -74,7 +74,7 @@
           ]
         }
       ],
-      "source": "%pip install -qU langchain_community pypdf pillow"
+      "source": "%pip install -qU langchain-community pypdf pillow"
     },
     {
       "cell_type": "markdown",

docs/docs/integrations/document_loaders/pypdfium2.ipynb

@@ -15,7 +15,7 @@
         "\n",
         "| Class | Package | Local | Serializable | JS support|\n",
         "| :--- | :--- | :---: | :---: |  :---: |\n",
-        "| [PyPDFLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.pdf.PyPDFLoader.html) | [langchain_community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ❌ |   \n",
+        "| [PyPDFLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.pdf.PyPDFLoader.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ❌ |   \n",
         "   \n",
         "---------   \n",
         "\n",
@@ -60,7 +60,7 @@
       "source": [
         "### Installation\n",
         "\n",
-        "Install **langchain_community** and **pypdf**."
+        "Install **langchain-community** and **pypdf**."
       ]
     },
     {
@@ -81,7 +81,7 @@
           ]
         }
       ],
-      "source": "%pip install -qU langchain_community pypdfium2"
+      "source": "%pip install -qU langchain-community pypdfium2"
     },
     {
       "cell_type": "markdown",
@@ -802,7 +802,7 @@
         }
       ],
       "source": [
-        "%pip install -qU langchain_openai"
+        "%pip install -qU langchain-openai"
       ]
     },
     {

docs/docs/integrations/document_loaders/pypdfloader.ipynb

@@ -15,7 +15,7 @@
         "\n",
         "| Class | Package | Local | Serializable | JS support|\n",
         "| :--- | :--- | :---: | :---: |  :---: |\n",
-        "| [PyPDFLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.pdf.PyPDFLoader.html) | [langchain_community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ❌ |   \n",
+        "| [PyPDFLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.pdf.PyPDFLoader.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ❌ |   \n",
         "   \n",
         "---------   \n",
         "\n",
@@ -60,7 +60,7 @@
       "source": [
         "### Installation\n",
         "\n",
-        "Install **langchain_community** and **pypdf**."
+        "Install **langchain-community** and **pypdf**."
       ]
     },
     {
@@ -82,7 +82,7 @@
         }
       ],
       "source": [
-        "%pip install -qU langchain_community pypdf"
+        "%pip install -qU langchain-community pypdf"
       ]
     },
     {
@@ -818,7 +818,7 @@
         }
       ],
       "source": [
-        "%pip install -qU langchain_openai"
+        "%pip install -qU langchain-openai"
       ]
     },
     {

docs/docs/integrations/document_loaders/recursive_url.ipynb

@@ -14,7 +14,7 @@
     "\n",
     "| Class | Package | Local | Serializable | [JS support](https://js.langchain.com/docs/integrations/document_loaders/web_loaders/recursive_url_loader/)|\n",
     "| :--- | :--- | :---: | :---: |  :---: |\n",
-    "| [RecursiveUrlLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.recursive_url_loader.RecursiveUrlLoader.html) | [langchain_community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ✅ | \n",
+    "| [RecursiveUrlLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.recursive_url_loader.RecursiveUrlLoader.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ✅ | \n",
     "### Loader features\n",
     "| Source | Document Lazy Loading | Native Async Support\n",
     "| :---: | :---: | :---: | \n",

docs/docs/integrations/document_loaders/reddit.ipynb

@@ -11,7 +11,7 @@
     "\n",
     "This loader fetches the text from the Posts of Subreddits or Reddit users, using the `praw` Python package.\n",
     "\n",
-    "Make a [Reddit Application](https://www.reddit.com/prefs/apps/) and initialize the loader with with your Reddit API credentials."
+    "Make a [Reddit Application](https://www.reddit.com/prefs/apps/) and initialize the loader with your Reddit API credentials."
    ]
   },
   {

docs/docs/integrations/document_loaders/sitemap.ipynb

@@ -15,7 +15,7 @@
         "\n",
         "| Class | Package | Local | Serializable | [JS support](https://js.langchain.com/docs/integrations/document_loaders/web_loaders/sitemap/)|\n",
         "| :--- | :--- | :---: | :---: |  :---: |\n",
-        "| [SiteMapLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.sitemap.SitemapLoader.html#langchain_community.document_loaders.sitemap.SitemapLoader) | [langchain_community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ✅ | \n",
+        "| [SiteMapLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.sitemap.SitemapLoader.html#langchain_community.document_loaders.sitemap.SitemapLoader) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ✅ | \n",
         "### Loader features\n",
         "| Source | Document Lazy Loading | Native Async Support\n",
         "| :---: | :---: | :---: | \n",
@@ -51,7 +51,7 @@
       "source": [
         "### Installation\n",
         "\n",
-        "Install **langchain_community**."
+        "Install **langchain-community**."
       ]
     },
     {

docs/docs/integrations/document_loaders/unstructured_file.ipynb

@@ -16,7 +16,7 @@
     "\n",
     "| Class | Package | Local | Serializable | [JS support](https://js.langchain.com/docs/integrations/document_loaders/file_loaders/unstructured/)|\n",
     "| :--- | :--- | :---: | :---: |  :---: |\n",
-    "| [UnstructuredLoader](https://python.langchain.com/api_reference/unstructured/document_loaders/langchain_unstructured.document_loaders.UnstructuredLoader.html) | [langchain_unstructured](https://python.langchain.com/api_reference/unstructured/index.html) | ✅ | ❌ | ✅ | \n",
+    "| [UnstructuredLoader](https://python.langchain.com/api_reference/unstructured/document_loaders/langchain_unstructured.document_loaders.UnstructuredLoader.html) | [langchain-unstructured](https://python.langchain.com/api_reference/unstructured/index.html) | ✅ | ❌ | ✅ | \n",
     "### Loader features\n",
     "| Source | Document Lazy Loading | Native Async Support\n",
     "| :---: | :---: | :---: | \n",

docs/docs/integrations/document_loaders/vsdx.ipynb

@@ -151,10 +151,10 @@
       "Red arrow magic !\n",
       "Something white\n",
       "Something Red\n",
-      "This a a completly useless diagramm, cool !!\n",
+      "This a completely useless diagram, cool !!\n",
       "\n",
       "But this is for example !\n",
-      "This diagramm is a base of many pages in this file. But it is editable in file \\\"BG WITH CONTENT\\\"\n",
+      "This diagram is a base of many pages in this file. But it is editable in file \\\"BG WITH CONTENT\\\"\n",
       "This is a page with something...\n",
       "\n",
       "WAW I have learned something !\n",
@@ -183,10 +183,10 @@
       "This is a title\n",
       "Something white\n",
       "Something Red\n",
-      "This a a completly useless diagramm, cool !!\n",
+      "This a completely useless diagram, cool !!\n",
       "\n",
       "But this is for example !\n",
-      "This diagramm is a base of many pages in this file. But it is editable in file \\\"BG WITH CONTENT\\\"\n",
+      "This diagram is a base of many pages in this file. But it is editable in file \\\"BG WITH CONTENT\\\"\n",
       "Another RED arrow wow\n",
       "Arrow with point but red\n",
       "Green line\n",
@@ -219,10 +219,10 @@
       "Red arrow magic !\n",
       "Something white\n",
       "Something Red\n",
-      "This a a completly useless diagramm, cool !!\n",
+      "This a completely useless diagram, cool !!\n",
       "\n",
       "But this is for example !\n",
-      "This diagramm is a base of many pages in this file. But it is editable in file \\\"BG WITH CONTENT\\\"\n",
+      "This diagram is a base of many pages in this file. But it is editable in file \\\"BG WITH CONTENT\\\"\n",
       "Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor\n",
       "\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0-\\u00a0incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in\n",
       "\n",
@@ -252,10 +252,10 @@
       "This is a title\n",
       "Something white\n",
       "Something Red\n",
-      "This a a completly useless diagramm, cool !!\n",
+      "This a completely useless diagram, cool !!\n",
       "\n",
       "But this is for example !\n",
-      "This diagramm is a base of many pages in this file. But it is editable in file \\\"BG WITH CONTENT\\\"\n",
+      "This diagram is a base of many pages in this file. But it is editable in file \\\"BG WITH CONTENT\\\"\n",
       "\n",
       "------ Page 7 ------\n",
       "Title page : Useful ↔ Useless page\n",
@@ -276,10 +276,10 @@
       "This is a title\n",
       "Something white\n",
       "Something Red\n",
-      "This a a completly useless diagramm, cool !!\n",
+      "This a completely useless diagram, cool !!\n",
       "\n",
       "But this is for example !\n",
-      "This diagramm is a base of many pages in this file. But it is editable in file \\\"BG WITH CONTENT\\\"\n",
+      "This diagram is a base of many pages in this file. But it is editable in file \\\"BG WITH CONTENT\\\"\n",
       "Title of this document : BLABLABLA\n",
       "\n",
       "------ Page 8 ------\n",
@@ -359,10 +359,10 @@
       "Red arrow magic !\n",
       "Something white\n",
       "Something Red\n",
-      "This a a completly useless diagramm, cool !!\n",
+      "This a completely useless diagram, cool !!\n",
       "\n",
       "But this is for example !\n",
-      "This diagramm is a base of many pages in this file. But it is editable in file \\\"BG WITH CONTENT\\\"\n",
+      "This diagram is a base of many pages in this file. But it is editable in file \\\"BG WITH CONTENT\\\"\n",
       "Useful\\u2194 Useless page\\u00a0\n",
       "\n",
       "Tests of some exotics characters :\\u00a0\\u00e3\\u00e4\\u00e5\\u0101\\u0103 \\u00fc\\u2554\\u00a0\\u00a0\\u00bc \\u00c7 \\u25d8\\u25cb\\u2642\\u266b\\u2640\\u00ee\\u2665\n",
@@ -444,10 +444,10 @@
       "Red arrow magic !\n",
       "Something white\n",
       "Something Red\n",
-      "This a a completly useless diagramm, cool !!\n",
+      "This a completely useless diagram, cool !!\n",
       "\n",
       "But this is for example !\n",
-      "This diagramm is a base of many pages in this file. But it is editable in file \\\"BG WITH CONTENT\\\"\n",
+      "This diagram is a base of many pages in this file. But it is editable in file \\\"BG WITH CONTENT\\\"\n",
       "Only connectors on this page. This is the CoNNeCtor page\n"
      ]
     }

docs/docs/integrations/document_loaders/web_base.ipynb

@@ -20,7 +20,7 @@
     "\n",
     "| Class | Package | Local | Serializable | JS support|\n",
     "| :--- | :--- | :---: | :---: |  :---: |\n",
-    "| [WebBaseLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.web_base.WebBaseLoader.html) | [langchain_community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ❌ | \n",
+    "| [WebBaseLoader](https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.web_base.WebBaseLoader.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ❌ | \n",
     "### Loader features\n",
     "| Source | Document Lazy Loading | Native Async Support\n",
     "| :---: | :---: | :---: | \n",
@@ -44,7 +44,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%pip install -qU langchain_community beautifulsoup4"
+    "%pip install -qU langchain-community beautifulsoup4"
    ]
   },
   {

docs/docs/integrations/graphs/kuzu_db.ipynb

@@ -132,12 +132,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "from langchain_core.documents import Document\n",
-    "from langchain_experimental.graph_transformers import LLMGraphTransformer\n",
+    "\n",
+    "# from langchain_experimental.graph_transformers import LLMGraphTransformer\n",
     "from langchain_openai import ChatOpenAI\n",
     "\n",
     "# Define the LLMGraphTransformer\n",

docs/docs/integrations/graphs/memgraph.ipynb

@@ -548,12 +548,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "from langchain_core.documents import Document\n",
-    "from langchain_experimental.graph_transformers import LLMGraphTransformer"
+    "# from langchain_experimental.graph_transformers import LLMGraphTransformer"
    ]
   },
   {

docs/docs/integrations/llm_caching.ipynb

@@ -261,7 +261,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%pip install -qU upstash_redis"
+    "%pip install -qU upstash-redis"
    ]
   },
   {
@@ -1543,7 +1543,7 @@
     }
    ],
    "source": [
-    "%pip install -qU langchain_astradb\n",
+    "%pip install -qU langchain-astradb\n",
     "\n",
     "import getpass\n",
     "\n",
@@ -2683,7 +2683,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%pip install -qU langchain_couchbase"
+    "%pip install -qU langchain-couchbase"
    ]
   },
   {

docs/docs/integrations/llms/bedrock.ipynb

@@ -34,7 +34,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%pip install --upgrade --quiet langchain_aws"
+    "%pip install --upgrade --quiet langchain-aws"
    ]
   },
   {

docs/docs/integrations/llms/cohere.ipynb

@@ -22,7 +22,7 @@
     "\n",
     "| Class | Package | Local | Serializable | [JS support](https://js.langchain.com/docs/integrations/llms/cohere/) | Package downloads | Package latest |\n",
     "| :--- | :--- | :---: | :---: |  :---: | :---: | :---: |\n",
-    "| [Cohere](https://python.langchain.com/api_reference/community/llms/langchain_community.llms.cohere.Cohere.html) | [langchain_community](https://python.langchain.com/api_reference/community/index.html) | ❌ | beta | ✅ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_community?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_community?style=flat-square&label=%20) |\n"
+    "| [Cohere](https://python.langchain.com/api_reference/community/llms/langchain_community.llms.cohere.Cohere.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ❌ | beta | ✅ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_community?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_community?style=flat-square&label=%20) |\n"
    ]
   },
   {

docs/docs/integrations/llms/fireworks.ipynb

@@ -22,7 +22,7 @@
     "\n",
     "| Class | Package | Local | Serializable | [JS support](https://js.langchain.com/v0.1/docs/integrations/llms/fireworks/) | Package downloads | Package latest |\n",
     "| :--- | :--- | :---: | :---: |  :---: | :---: | :---: |\n",
-    "| [Fireworks](https://python.langchain.com/api_reference/fireworks/llms/langchain_fireworks.llms.Fireworks.html#langchain_fireworks.llms.Fireworks) | [langchain_fireworks](https://python.langchain.com/api_reference/fireworks/index.html) | ❌ | ❌ | ✅ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_fireworks?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_fireworks?style=flat-square&label=%20) |"
+    "| [Fireworks](https://python.langchain.com/api_reference/fireworks/llms/langchain_fireworks.llms.Fireworks.html#langchain_fireworks.llms.Fireworks) | [langchain-fireworks](https://python.langchain.com/api_reference/fireworks/index.html) | ❌ | ❌ | ✅ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_fireworks?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_fireworks?style=flat-square&label=%20) |"
    ]
   },
   {
@@ -59,7 +59,7 @@
    "source": [
     "### Installation\n",
     "\n",
-    "You need to install the `langchain_fireworks` python package for the rest of the notebook to work."
+    "You need to install the `langchain-fireworks` python package for the rest of the notebook to work."
    ]
   },
   {

docs/docs/integrations/llms/nvidia_ai_endpoints.ipynb

@@ -29,7 +29,7 @@
     "\n",
     "| Class | Package | Local | Serializable | JS support | Package downloads | Package latest |\n",
     "| :--- | :--- | :---: | :---: |  :---: | :---: | :---: |\n",
-    "| [NVIDIA](https://python.langchain.com/api_reference/nvidia_ai_endpoints/llms/langchain_nvidia_ai_endpoints.chat_models.ChatNVIDIA.html) | [langchain_nvidia_ai_endpoints](https://python.langchain.com/api_reference/nvidia_ai_endpoints/index.html) | ✅ | beta | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_nvidia_ai_endpoints?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_nvidia_ai_endpoints?style=flat-square&label=%20) |\n",
+    "| [NVIDIA](https://python.langchain.com/api_reference/nvidia_ai_endpoints/llms/langchain_nvidia_ai_endpoints.chat_models.ChatNVIDIA.html) | [langchain-nvidia-ai-endpoints](https://python.langchain.com/api_reference/nvidia_ai_endpoints/index.html) | ✅ | beta | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_nvidia_ai_endpoints?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_nvidia_ai_endpoints?style=flat-square&label=%20) |\n",
     "\n",
     "### Model features\n",
     "| JSON mode | [Image input](/docs/how_to/multimodal_inputs/) | Audio input | Video input | [Token-level streaming](/docs/how_to/chat_streaming/) | Native async | [Token usage](/docs/how_to/chat_token_usage_tracking/) | [Logprobs](/docs/how_to/logprobs/) |\n",
@@ -71,7 +71,7 @@
    "source": [
     "### Installation\n",
     "\n",
-    "The LangChain NVIDIA AI Endpoints integration lives in the `langchain_nvidia_ai_endpoints` package:"
+    "The LangChain NVIDIA AI Endpoints integration lives in the `langchain-nvidia-ai-endpoints` package:"
    ]
   },
   {

docs/docs/integrations/providers/gradientai.mdx

@@ -1,4 +1,4 @@
-# ChatGradient
+# DigitalOcean Gradient
 
 This will help you getting started with DigitalOcean Gradient [chat models](/docs/concepts/chat_models).
 

docs/docs/integrations/providers/ollama.mdx

@@ -1,14 +1,16 @@
 # Ollama
 
 >[Ollama](https://ollama.com/) allows you to run open-source large language models,
-> such as [Llama3.1](https://ai.meta.com/blog/meta-llama-3-1/), locally.
+> such as [gpt-oss](https://ollama.com/library/gpt-oss), locally.
 >
->`Ollama` bundles model weights, configuration, and data into a single package, defined by a Modelfile.
->It optimizes setup and configuration details, including GPU usage.
->For a complete list of supported models and model variants, see the [Ollama model library](https://ollama.ai/library).
+>The `ollama` [package](https://pypi.org/project/ollama/0.5.3/) bundles model weights,
+> configuration, and data into a single package, defined by a Modelfile. It optimizes
+> setup and configuration details, including GPU usage.
+>For a complete list of supported models and model variants, see the
+> [Ollama model library](https://ollama.com/search).
 
-See [this guide](/docs/how_to/local_llms) for more details
-on how to use `Ollama` with LangChain.
+See [this guide](/docs/how_to/local_llms/#ollama) for more details
+on how to use `ollama` with LangChain.
 
 ## Installation and Setup
 ### Ollama installation
@@ -23,10 +25,10 @@ Ollama will start as a background service automatically, if this is disabled, ru
 ollama serve
 ```
 
-After starting ollama, run `ollama pull <name-of-model>` to download a model from the [Ollama model library](https://ollama.ai/library):
+After starting ollama, run `ollama pull <name-of-model>` to download a model from the [Ollama model library](https://ollama.com/library):
 
 ```bash
-ollama pull llama3.1
+ollama pull gpt-oss:20b
 ```
 
 - This will download the default tagged version of the model. Typically, the default points to the latest, smallest sized-parameter model.

docs/docs/integrations/retrievers/wikipedia.ipynb

@@ -67,7 +67,7 @@
       },
       "outputs": [],
       "source": [
-        "%pip install -qU langchain_community wikipedia"
+        "%pip install -qU langchain-community wikipedia"
       ]
     },
     {

docs/docs/integrations/stores/astradb.ipynb

@@ -31,7 +31,7 @@
     "\n",
     "| Class | Package | Local | JS support | Package downloads | Package latest |\n",
     "| :--- | :--- | :---: | :---: |  :---: | :---: |\n",
-    "| [AstraDBByteStore](https://python.langchain.com/api_reference/astradb/storage/langchain_astradb.storage.AstraDBByteStore.html) | [langchain_astradb](https://python.langchain.com/api_reference/astradb/index.html) | ❌ | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_astradb?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_astradb?style=flat-square&label=%20) |\n",
+    "| [AstraDBByteStore](https://python.langchain.com/api_reference/astradb/storage/langchain_astradb.storage.AstraDBByteStore.html) | [langchain-astradb](https://python.langchain.com/api_reference/astradb/index.html) | ❌ | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_astradb?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_astradb?style=flat-square&label=%20) |\n",
     "\n",
     "## Setup\n",
     "\n",
@@ -60,7 +60,7 @@
    "source": [
     "### Installation\n",
     "\n",
-    "The LangChain AstraDB integration lives in the `langchain_astradb` package:"
+    "The LangChain AstraDB integration lives in the `langchain-astradb` package:"
    ]
   },
   {
@@ -69,7 +69,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%pip install -qU langchain_astradb"
+    "%pip install -qU langchain-astradb"
    ]
   },
   {

docs/docs/integrations/stores/cassandra.ipynb

@@ -29,7 +29,7 @@
     "\n",
     "| Class | Package | Local | [JS support](https://js.langchain.com/docs/integrations/stores/cassandra_storage) | Package downloads | Package latest |\n",
     "| :--- | :--- | :---: | :---: |  :---: | :---: |\n",
-    "| [CassandraByteStore](https://python.langchain.com/api_reference/community/storage/langchain_community.storage.cassandra.CassandraByteStore.html) | [langchain_community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ✅ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_community?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_community?style=flat-square&label=%20) |\n",
+    "| [CassandraByteStore](https://python.langchain.com/api_reference/community/storage/langchain_community.storage.cassandra.CassandraByteStore.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ✅ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_community?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_community?style=flat-square&label=%20) |\n",
     "\n",
     "## Setup\n",
     "\n",
@@ -44,7 +44,7 @@
    "source": [
     "### Installation\n",
     "\n",
-    "The LangChain `CassandraByteStore` integration lives in the `langchain_community` package. You'll also need to install the `cassio` package or the `cassandra-driver` package as a peer dependency depending on which initialization method you're using:"
+    "The LangChain `CassandraByteStore` integration lives in the `langchain-community` package. You'll also need to install the `cassio` package or the `cassandra-driver` package as a peer dependency depending on which initialization method you're using:"
    ]
   },
   {
@@ -53,7 +53,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%pip install -qU langchain_community\n",
+    "%pip install -qU langchain-community\n",
     "%pip install -qU cassandra-driver\n",
     "%pip install -qU cassio"
    ]

docs/docs/integrations/stores/elasticsearch.ipynb

@@ -29,7 +29,7 @@
     "\n",
     "| Class | Package | Local | JS support | Package downloads | Package latest |\n",
     "| :--- | :--- | :---: | :---: |  :---: | :---: |\n",
-    "| [ElasticsearchEmbeddingsCache](https://python.langchain.com/api_reference/elasticsearch/cache/langchain_elasticsearch.cache.ElasticsearchEmbeddingsCache.html) | [langchain_elasticsearch](https://python.langchain.com/api_reference/elasticsearch/index.html) | ✅ | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_elasticsearch?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_elasticsearch?style=flat-square&label=%20) |\n",
+    "| [ElasticsearchEmbeddingsCache](https://python.langchain.com/api_reference/elasticsearch/cache/langchain_elasticsearch.cache.ElasticsearchEmbeddingsCache.html) | [langchain-elasticsearch](https://python.langchain.com/api_reference/elasticsearch/index.html) | ✅ | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_elasticsearch?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_elasticsearch?style=flat-square&label=%20) |\n",
     "\n",
     "## Setup\n",
     "\n",
@@ -42,7 +42,7 @@
    "source": [
     "### Installation\n",
     "\n",
-    "The LangChain `ElasticsearchEmbeddingsCache` integration lives in the `__package_name__` package:"
+    "The LangChain `ElasticsearchEmbeddingsCache` integration lives in the `langchain-elasticsearch` package:"
    ]
   },
   {
@@ -51,7 +51,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%pip install -qU langchain_elasticsearch"
+    "%pip install -qU langchain-elasticsearch"
    ]
   },
   {

docs/docs/integrations/stores/in_memory.ipynb

@@ -29,7 +29,7 @@
     "\n",
     "| Class | Package | Local | [JS support](https://js.langchain.com/docs/integrations/stores/in_memory/) | Package downloads | Package latest |\n",
     "| :--- | :--- | :---: | :---: |  :---: | :---: |\n",
-    "| [InMemoryByteStore](https://python.langchain.com/api_reference/core/stores/langchain_core.stores.InMemoryByteStore.html) | [langchain_core](https://python.langchain.com/api_reference/core/index.html) | ✅ | ✅ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_core?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_core?style=flat-square&label=%20) |"
+    "| [InMemoryByteStore](https://python.langchain.com/api_reference/core/stores/langchain_core.stores.InMemoryByteStore.html) | [langchain-core](https://python.langchain.com/api_reference/core/index.html) | ✅ | ✅ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_core?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_core?style=flat-square&label=%20) |"
    ]
   },
   {
@@ -38,7 +38,7 @@
    "source": [
     "### Installation\n",
     "\n",
-    "The LangChain `InMemoryByteStore` integration lives in the `langchain_core` package:"
+    "The LangChain `InMemoryByteStore` integration lives in the `langchain-core` package:"
    ]
   },
   {
@@ -47,7 +47,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%pip install -qU langchain_core"
+    "%pip install -qU langchain-core"
    ]
   },
   {

docs/docs/integrations/stores/redis.ipynb

@@ -29,7 +29,7 @@
     "\n",
     "| Class | Package | Local | [JS support](https://js.langchain.com/docs/integrations/stores/ioredis_storage) | Package downloads | Package latest |\n",
     "| :--- | :--- | :---: | :---: |  :---: | :---: |\n",
-    "| [RedisStore](https://python.langchain.com/api_reference/community/storage/langchain_community.storage.redis.RedisStore.html) | [langchain_community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ✅ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_community?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_community?style=flat-square&label=%20) |\n",
+    "| [RedisStore](https://python.langchain.com/api_reference/community/storage/langchain_community.storage.redis.RedisStore.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ✅ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_community?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_community?style=flat-square&label=%20) |\n",
     "\n",
     "## Setup\n",
     "\n",
@@ -42,7 +42,7 @@
    "source": [
     "### Installation\n",
     "\n",
-    "The LangChain `RedisStore` integration lives in the `langchain_community` package:"
+    "The LangChain `RedisStore` integration lives in the `langchain-community` package:"
    ]
   },
   {
@@ -51,7 +51,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%pip install -qU langchain_community redis"
+    "%pip install -qU langchain-community redis"
    ]
   },
   {

docs/docs/integrations/stores/upstash_redis.ipynb

@@ -31,7 +31,7 @@
     "\n",
     "| Class | Package | Local | [JS support](https://js.langchain.com/docs/integrations/stores/upstash_redis_storage) | Package downloads | Package latest |\n",
     "| :--- | :--- | :---: | :---: |  :---: | :---: |\n",
-    "| [UpstashRedisByteStore](https://python.langchain.com/api_reference/community/storage/langchain_community.storage.upstash_redis.UpstashRedisByteStore.html) | [langchain_community](https://python.langchain.com/api_reference/community/index.html) | ❌ | ✅ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_community?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_community?style=flat-square&label=%20) |\n",
+    "| [UpstashRedisByteStore](https://python.langchain.com/api_reference/community/storage/langchain_community.storage.upstash_redis.UpstashRedisByteStore.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ❌ | ✅ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_community?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_community?style=flat-square&label=%20) |\n",
     "\n",
     "## Setup\n",
     "\n",
@@ -60,7 +60,7 @@
    "source": [
     "### Installation\n",
     "\n",
-    "The LangChain Upstash integration lives in the `langchain_community` package. You'll also need to install the `upstash-redis` package as a peer dependency:"
+    "The LangChain Upstash integration lives in the `langchain-community` package. You'll also need to install the `upstash-redis` package as a peer dependency:"
    ]
   },
   {
@@ -69,7 +69,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%pip install -qU langchain_community upstash-redis"
+    "%pip install -qU langchain-community upstash-redis"
    ]
   },
   {

docs/docs/integrations/text_embedding/nvidia_ai_endpoints.ipynb

@@ -411,7 +411,7 @@
    },
    "outputs": [],
    "source": [
-    "%pip install --upgrade --quiet  langchain faiss-cpu tiktoken langchain_community\n",
+    "%pip install --upgrade --quiet  langchain faiss-cpu tiktoken langchain-community\n",
     "\n",
     "from operator import itemgetter\n",
     "\n",

docs/docs/integrations/tools/agentql.ipynb

@@ -55,7 +55,7 @@
    },
    "outputs": [],
    "source": [
-    "%pip install --quiet -U langchain_agentql"
+    "%pip install --quiet -U langchain-agentql"
    ]
   },
   {

docs/docs/integrations/tools/cassandra_database.ipynb

@@ -85,7 +85,7 @@
     "Install the following Python modules:\n",
     "\n",
     "```bash\n",
-    "pip install ipykernel python-dotenv cassio langchain_openai langchain langchain-community langchainhub\n",
+    "pip install ipykernel python-dotenv cassio langchain-openai langchain langchain-community langchainhub\n",
     "```\n",
     "\n",
     "### .env file\n",

docs/docs/integrations/tools/jira.ipynb

@@ -51,7 +51,7 @@
    },
    "outputs": [],
    "source": [
-    "%pip install -qU langchain-community langchain_openai"
+    "%pip install -qU langchain-community langchain-openai"
    ]
   },
   {

docs/docs/integrations/vectorstores/google_firestore.ipynb

@@ -19,7 +19,7 @@
     "\n",
     "> [Firestore](https://cloud.google.com/firestore) is a serverless document-oriented database that scales to meet any demand. Extend your database application to build AI-powered experiences leveraging Firestore's Langchain integrations.\n",
     "\n",
-    "This notebook goes over how to use [Firestore](https://cloud.google.com/firestore) to to store vectors and query them using the `FirestoreVectorStore` class.\n",
+    "This notebook goes over how to use [Firestore](https://cloud.google.com/firestore) to store vectors and query them using the `FirestoreVectorStore` class.\n",
     "\n",
     "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/googleapis/langchain-google-firestore-python/blob/main/docs/vectorstores.ipynb)"
    ]

docs/docs/integrations/vectorstores/jaguar.ipynb

@@ -29,8 +29,8 @@
     "   Please refer to the instructions in:\n",
     "   [www.jaguardb.com](http://www.jaguardb.com)\n",
     "   For quick setup in docker environment:\n",
-    "   docker pull jaguardb/jaguardb_with_http\n",
-    "   docker run -d -p 8888:8888 -p 8080:8080 --name jaguardb_with_http  jaguardb/jaguardb_with_http\n",
+    "   docker pull jaguardb/jaguardb\n",
+    "   docker run -d -p 8888:8888 -p 8080:8080 --name jaguardb  jaguardb/jaguardb\n",
     "\n",
     "2. You must install the http client package for JaguarDB:\n",
     "   ```\n",

docs/docs/integrations/vectorstores/milvus.ipynb

@@ -36,7 +36,7 @@
     }
    ],
    "source": [
-    "pip install -qU langchain_milvus"
+    "pip install -qU langchain-milvus"
    ]
   },
   {

docs/docs/integrations/vectorstores/pgvector.ipynb

@@ -9,13 +9,13 @@
     "\n",
     "> An implementation of LangChain vectorstore abstraction using `postgres` as the backend and utilizing the `pgvector` extension.\n",
     "\n",
-    "The code lives in an integration package called: [langchain_postgres](https://github.com/langchain-ai/langchain-postgres/).\n",
+    "The code lives in an integration package called: [langchain-postgres](https://github.com/langchain-ai/langchain-postgres/).\n",
     "\n",
     "## Status\n",
     "\n",
-    "This code has been ported over from `langchain_community` into a dedicated package called `langchain-postgres`. The following changes have been made:\n",
+    "This code has been ported over from `langchain-community` into a dedicated package called `langchain-postgres`. The following changes have been made:\n",
     "\n",
-    "* langchain_postgres works only with psycopg3. Please update your connnecion strings from `postgresql+psycopg2://...` to `postgresql+psycopg://langchain:langchain@...` (yes, it's the driver name is `psycopg` not `psycopg3`, but it'll use `psycopg3`.\n",
+    "* `langchain-postgres` works only with psycopg3. Please update your connnecion strings from `postgresql+psycopg2://...` to `postgresql+psycopg://langchain:langchain@...` (yes, it's the driver name is `psycopg` not `psycopg3`, but it'll use `psycopg3`.\n",
     "* The schema of the embedding store and collection have been changed to make add_documents work correctly with user specified ids.\n",
     "* One has to pass an explicit connection object now.\n",
     "\n",
@@ -35,7 +35,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "pip install -qU langchain_postgres"
+    "pip install -qU langchain-postgres"
    ]
   },
   {
@@ -43,7 +43,7 @@
    "id": "0dd87fcc",
    "metadata": {},
    "source": [
-    "You can run the following command to spin up a a postgres container with the `pgvector` extension:"
+    "You can run the following command to spin up a postgres container with the `pgvector` extension:"
    ]
   },
   {
@@ -63,7 +63,7 @@
    "source": [
     "### Credentials\n",
     "\n",
-    "There are no credentials needed to run this notebook, just make sure you downloaded the `langchain_postgres` package and correctly started the postgres container."
+    "There are no credentials needed to run this notebook, just make sure you downloaded the `langchain-postgres` package and correctly started the postgres container."
    ]
   },
   {

docs/docs/integrations/vectorstores/pgvectorstore.ipynb

@@ -10,7 +10,7 @@
     "\n",
     "This notebook goes over how to use the `PGVectorStore` API.\n",
     "\n",
-    "The code lives in an integration package called: [langchain_postgres](https://github.com/langchain-ai/langchain-postgres/)."
+    "The code lives in an integration package called: [langchain-postgres](https://github.com/langchain-ai/langchain-postgres/)."
    ]
   },
   {

docs/docs/integrations/vectorstores/sqlserver.ipynb

@@ -61,7 +61,7 @@
    "source": [
     "## Credentials\n",
     "\n",
-    "There are no credentials needed to run this notebook, just make sure you downloaded the `langchain_sqlserver` package\n",
+    "There are no credentials needed to run this notebook, just make sure you downloaded the `langchain-sqlserver` package\n",
     "If you want to get best in-class automated tracing of your model calls you can also set your [LangSmith](https://docs.smith.langchain.com/) API key by uncommenting below:"
    ]
   },
@@ -591,7 +591,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": null,
    "metadata": {
     "azdata_cell_guid": "d9127900-0942-48f1-bd4d-081c7fa3fcae",
     "language": "python"
@@ -606,7 +606,7 @@
     }
    ],
    "source": [
-    "from langchain.document_loaders import AzureBlobStorageFileLoader\n",
+    "from langchain_community.document_loaders import AzureBlobStorageFileLoader\n",
     "from langchain.text_splitter import RecursiveCharacterTextSplitter\n",
     "from langchain_core.documents import Document\n",
     "\n",

docs/docs/troubleshooting/errors/INVALID_TOOL_RESULTS.ipynb

@@ -193,7 +193,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "You should additionally not pass `ToolMessages` back to to a model if they are not preceded by an `AIMessage` with tool calls. For example, this will fail:"
+    "You should additionally not pass `ToolMessages` back to a model if they are not preceded by an `AIMessage` with tool calls. For example, this will fail:"
    ]
   },
   {

docs/docs/versions/v0_4/how_to_update.mdx

@@ -0,0 +1,107 @@
+---
+sidebar_position: 3
+---
+
+# How to update your code
+
+*Last updated: 08.08.25*
+
+If you maintain custom callbacks or output parsers, type checkers may raise errors if
+they do not accept the new message types as inputs. This guide describes how to
+address those issues.
+
+If you do not maintain custom callbacks or output parsers, there are no breaking
+changes. See our guide on the [new message types](/docs/versions/v0_4/messages) to learn
+about new features introduced in v0.4.
+
+## Custom callbacks
+
+[BaseCallbackHandler](https://python.langchain.com/api_reference/core/callbacks/langchain_core.callbacks.base.BaseCallbackHandler.html)
+now includes an attribute `accepts_new_messages` that defaults to False. When this
+attribute is False, the callback system in langchain-core will automatically convert
+new message types to old, so there should be no runtime errors. You can update callback
+signatures as below to fix type-checking errors:
+
+```python
+from langchain_core.v1.messages import AIMessage, AIMessageChunk, MessageV1
+
+def on_chat_model_start(
+    self,
+    serialized: dict[str, Any],
+    # highlight-next-line
+    messages: Union[list[list[BaseMessage]], list[MessageV1]],
+    *,
+    run_id: UUID,
+    parent_run_id: Optional[UUID] = None,
+    tags: Optional[list[str]] = None,
+    metadata: Optional[dict[str, Any]] = None,
+    **kwargs: Any,
+) -> Any:
+
+def on_llm_new_token(
+    self,
+    token: str,
+    *,
+    chunk: Optional[
+        # highlight-next-line
+        Union[GenerationChunk, ChatGenerationChunk, AIMessageChunk]
+    ] = None,
+    run_id: UUID,
+    parent_run_id: Optional[UUID] = None,
+    **kwargs: Any,
+) -> Any:
+
+def on_llm_end(
+    self,
+    # highlight-next-line
+    response: Union[LLMResult, AIMessage],
+    *,
+    run_id: UUID,
+    parent_run_id: Optional[UUID] = None,
+    **kwargs: Any,
+) -> Any:
+```
+You can also safely type-ignore mypy `override` errors here unless you switch
+`accepts_new_messages` to True.
+
+
+## Custom output parsers
+
+All output parsers in `langchain-core` have been updated to accept the new message
+types.
+
+If you maintain a custom output parser, `langchain-core` exposes a
+`convert_from_v1_message` function so that your parser can easily operate on the new
+message types:
+
+```python
+from langchain_core.messages.utils import convert_from_v1_message
+from langchain_core.v1.messages import AIMessage
+
+def parse_result(
+    self,
+    # highlight-next-line
+    result: Union[list[Generation], AIMessage],
+    *,
+    partial: bool = False,
+) -> Union[list[AgentAction], AgentFinish]:
+    # highlight-start
+    if isinstance(result, AIMessage):
+        result = [ChatGeneration(message=convert_from_v1_message(result))]
+    # highlight-end
+    ...
+
+def _transform(
+    # higlight-next-line
+    self, input: Iterator[Union[str, BaseMessage, AIMessage]]
+) -> Iterator[AddableDict]:
+    for chunk in input:
+        # higlight-start
+        if isinstance(chunk, AIMessage):
+            chunk = convert_from_v1_message(chunk)
+        # higlight-end
+        ...
+```
+This will allow your parser to work as before. You can also update the parser to
+natively handle the new message types to save this conversion step. See our guide on
+the [new message types](/docs/versions/v0_4/messages) for details.

docs/docs/versions/v0_4/index.mdx

@@ -0,0 +1,81 @@
+---
+sidebar_position: 1
+---
+
+# LangChain v0.4
+
+*Last updated: 08.08.25*
+
+## What's changed
+
+LangChain v0.4 allows developers to opt-in to new message types that will become default
+in LangChain v1.0. LangChain v1.0 will be released this fall. These messages provide
+fully typed, provider-agnostic content, introducing standard content blocks for
+reasoning, citations, server-side tool calls, and other LLM features. They also offer
+performance benefits over existing message classes.
+
+New message types have been added to a `v1` namespace in `langchain-core`. Select
+integration packages now also expose a `v1` namespace containing chat models that
+work with the new message types.
+
+Input types for callbacks and output parsers have been widened to accept the new message
+types. If you maintain custom callbacks or output parsers, type checkers may raise
+errors if they do not accept the new message types as inputs. Refer to
+[this guide](/docs/versions/v0_4/how_to_update) for how to address those issues. This
+is the only breaking change.
+
+## What's new
+
+You can access the new chat models through [init_chat_model](/docs/how_to/chat_models_universal_init/) by setting `message_version="v1"`:
+
+```python
+from langchain.chat_models import init_chat_model
+
+llm = init_chat_model("openai:gpt-5", message_version="v1")
+
+input_message = {"role": "user", "content": "Hello, world!"}
+llm.invoke([input_message])
+```
+
+You can also access the `v1` namespaces directly:
+```python
+from langchain_core.v1.messages import HumanMessage
+from langchain_openai.v1 import ChatOpenAI
+
+input_message = HumanMessage("Hello, world!")
+llm.invoke([input_message])
+```
+
+:::info New message details
+
+See our guide on the [new message types](/docs/versions/v0_4/messages) for details.
+
+:::
+
+## How to update your code
+
+If you maintain custom callbacks or output parsers, type checkers may raise errors if
+they do not accept the new message types as inputs. Refer to
+[this guide](/docs/versions/v0_4/how_to_update) for how to address those issues.
+
+If you do not maintain custom callbacks or output parsers, there are no breaking
+changes. See our guide on the [new message types](/docs/versions/v0_4/messages) to learn
+about new features introduced in v0.4.
+
+
+
+### Base packages
+
+| Package                  | Latest | Recommended constraint |
+|--------------------------|--------|------------------------|
+| langchain                | 0.4.0  | >=0.4,<1.0             |
+| langchain-community      | 0.4.0  | >=0.4,<1.0             |
+| langchain-text-splitters | 0.4.0  | >=0.4,<1.0             |
+| langchain-core           | 0.4.0  | >=0.4,<1.0             |
+| langchain-experimental   | 0.4.0  | >=0.4,<1.0             |
+
+
+### Integration packages
+
+...
+

docs/docs/versions/v0_4/messages.mdx

@@ -0,0 +1,429 @@
+---
+sidebar_position: 2
+---
+
+# LangChain v1.0 message types
+
+*Last updated: 08.08.25*
+
+LangChain v0.4 allows developers to opt-in to new message types that will become default
+in LangChain v1.0. LangChain v1.0 will be released this fall.
+
+These messages should be considered a beta feature and are subject to change in
+LangChain v1.0, although we do not anticipate any significant changes.
+
+## Benefits
+
+The new message types offer improvements in performance, type-safety, and consistency
+across OpenAI, Anthropic, Gemini, and other providers.
+
+### Performance
+
+Importantly, the new messages are Python dataclasses, saving some runtime from
+instantiating (layers of) Pydantic BaseModels.
+
+LangChain v0.4 introduces a new `BaseChatModel` class in `langchain_core.v1.chat_models`
+that is faster and leaner than the existing `BaseChatModel` class, offering significant
+reductions in overhead above provider SDKs.
+
+### Type-safety
+
+Message content is typed as
+```python
+import langchain_core.messages.content_blocks as types
+
+content: list[types.ContentBlock]
+```
+
+where we have introduced standard types for text, reasoning, citations, server-side
+tool executions (e.g., web search and code interpreters). These include
+[tool calls](https://python.langchain.com/docs/concepts/tool_calling/) and the
+[multi-modal types](/docs/how_to/multimodal_inputs/) introduced in earlier versions
+of LangChain. There are no breaking changes associated with the existing content types.
+
+**This is the most significant change from the existing message classes**, which permit
+strings, lists of strings, or lists of untyped dicts as content. We have added a
+`.text` getter so that developers can easily recover string content. Consequently, we
+have deprecated `.text()` (as a method) in favor of the new property.
+
+`.tool_calls`, instead of an attribute, is now also a getter with an associated setter,
+so that usage is largely the same. See [usage comparison](#usage-comparison), below,
+for details.
+
+### Consistency
+
+Many chat models can generate a variety of content in a single conversational turn,
+including reasoning, tool calls and responses, images, text with citations, and other
+structured objects. We have standardized these types, resulting in improved
+inter-operability of messages across models.
+
+## Usage comparison
+
+| Task                    | Previous                               | New                                                              |
+|-------------------------|----------------------------------------|------------------------------------------------------------------|
+| Get text content (str)  | `message.content` or `message.text()`  | `message.text`                                                   |
+| Get content blocks      | `message.content`                      | `message.content`                                                |
+| Get `additional_kwargs` | `message.additional_kwargs`            | `[block for block in message.content if block["type"] == "..."]` |
+
+Getting `response_metadata` and `tool_calls` has not changed.
+
+### Changes in content blocks
+
+For providers that generate `list[dict]` content, the dict elements have changed to
+conform to the new content block types. Refer to the
+[API reference](https://python.langchain.com/api_reference/core/messages.html) for
+details. Below we show some examples.
+
+Importantly:
+- Where provider-specific fields map to fields on standard types, LangChain manages
+the translation.
+- Where provider-specific fields do not map to fields on standard types, LangChain
+stores them in an `"extras"` key (see below for examples).
+
+<details>
+  <summary>Citations and web search</summary>
+
+<div className="row">
+  <div className="col col--6" style={{minWidth: 0}}>
+    **Old content**
+```python
+from langchain.chat_models import init_chat_model
+
+llm = init_chat_model("openai:gpt-5-mini", output_version="responses/v1")
+llm_with_tools = llm.bind_tools([{"type": "web_search_preview"}])
+
+response = llm_with_tools.invoke("What was a positive news story from today?")
+response.content
+```
+```
+[
+  {
+    "type": "reasoning",
+    "id": "rs_abc123",
+    "summary": []
+  },
+  {
+    "type": "web_search_call",
+    "id": "ws_abc123",
+    "action": {
+      "query": "positive news today August 8 2025 'good news' 'Aug 8 2025' 'today' ",
+      "type": "search"
+    },
+    "status": "completed"
+  },
+  {
+    "type": "text",
+    "text": "Here are two positive news items from today...",
+    "annotations": [
+      {
+        "type": "url_citation",
+        "end_index": 455,
+        "start_index": 196,
+        "title": "Document title",
+        "url": "<document url>"
+      },
+      {
+        "type": "url_citation",
+        "end_index": 1022,
+        "start_index": 707,
+        "title": "Another Document",
+        "url": "<another document url>"
+      },
+    ],
+    "id": "msg_abc123"
+  }
+]
+```
+</div>
+
+  <div className="col col--6" style={{minWidth: 0}}>
+    **New content**
+```python
+from langchain.chat_models import init_chat_model
+
+llm = init_chat_model("openai:gpt-5-mini", message_version="v1")
+llm_with_tools = llm.bind_tools([{"type": "web_search_preview"}])
+
+response = llm_with_tools.invoke("What was a positive news story from today?")
+response.content
+```
+```
+[
+  {
+    "type": "reasoning",
+    "id": "rs_abc123"
+  },
+  {
+    "type": "web_search_call",
+    "id": "ws_abc123",
+    "query": "positive news August 8 2025 'good news' 'today' ",
+    "extras": {
+      "action": {"type": "search"},
+      "status": "completed",
+    }
+  },
+  {
+    "type": "web_search_result",
+    "id": "ws_abc123"
+  },
+  {
+    "type": "text",
+    "text": "Here are two positive news items from today...",
+    "annotations": [
+      {
+        "type": "citation",
+        "end_index": 455,
+        "start_index": 196,
+        "title": "Document title",
+        "url": "<document url>"
+      },
+      {
+        "type": "citation",
+        "end_index": 1022,
+        "start_index": 707,
+        "title": "Another Document",
+        "url": "<another document url>"
+      }
+    ],
+    "id": "msg_abc123"
+  }
+]
+```
+  </div>
+</div>
+</details>
+
+
+<details>
+  <summary>Reasoning</summary>
+
+<div className="row">
+  <div className="col col--6" style={{minWidth: 0}}>
+    **Old content**
+```python
+from langchain.chat_models import init_chat_model
+
+llm = init_chat_model(
+    "openai:gpt-5",
+    reasoning={"effort": "medium", "summary": "auto"},
+    output_version="responses/v1",
+)
+response = llm.invoke(
+    "What was the third tallest building in the world in the year 2000?"
+)
+response.content
+```
+```
+[
+  {
+    "type": "reasoning",
+    "id": "rs_abc123",
+    "summary": [
+      {
+        "text": "The user is asking about...",
+        "type": "summary_text"
+      },
+      {
+        "text": "We should consider...",
+        "type": "summary_text"
+      }
+    ]
+  },
+  {
+    "type": "text",
+    "text": "In the year 2000 the third-tallest building in the world was...",
+    "id": "msg_abc123"
+  }
+]
+```
+  </div>
+
+  <div className="col col--6" style={{minWidth: 0}}>
+    **New content**
+```python
+from langchain.chat_models import init_chat_model
+
+llm = init_chat_model(
+    "openai:gpt-5",
+    reasoning={"effort": "medium", "summary": "auto"},
+    message_version="v1",
+)
+response = llm.invoke(
+    "What was the third tallest building in the world in the year 2000?"
+)
+response.content
+```
+```
+[
+  {
+    "type": "reasoning",
+    "reasoning": "The user is asking about...",
+    "id": "rs_abc123"
+  },
+  {
+    "type": "reasoning",
+    "reasoning": "We should consider...",
+    "id": "rs_abc123"
+  },
+  {
+    "type": "text",
+    "text": "In the year 2000 the third-tallest building in the world was...",
+    "id": "msg_abc123"
+  }
+]
+```
+  </div>
+</div>
+</details>
+
+
+<details>
+  <summary>Non-standard blocks</summary>
+
+Where content blocks from specific providers do not map to a standard type, they are
+structured into a `"non_standard"` block:
+```python
+{
+    "type": "non_standard",
+    "value": original_block,
+}
+```
+<div className="row">
+  <div className="col col--6" style={{minWidth: 0}}>
+    **Old content**
+```python
+from langchain.chat_models import init_chat_model
+
+llm = init_chat_model("openai:gpt-5-mini", output_version="responses/v1")
+llm_with_tools = llm.bind_tools(
+    [
+        {
+            "type": "file_search",
+            "vector_store_ids": ["vs_67d0baa0544c8191be194a85e19cbf92"],
+        }
+    ]
+)
+
+response = llm_with_tools.invoke("What is deep research by OpenAI?")
+response.content
+```
+```
+[
+  {
+    "type": "reasoning",
+    "id": "rs_abc123",
+    "summary": []
+  },
+  {
+    "type": "file_search_call",
+    "id": "fs_abc123",
+    "queries": [
+      "What is deep research by OpenAI?",
+      "deep research OpenAI definition"
+    ],
+    "status": "completed"
+  },
+  {
+    "type": "reasoning",
+    "id": "rs_def456",
+    "summary": []
+  },
+  {
+    "type": "text",
+    "text": "Deep research is...",
+    "annotations": [
+      {
+        "type": "file_citation",
+        "file_id": "file-abc123",
+        "filename": "sample_file.pdf",
+        "index": 305
+      },
+      {
+        "type": "file_citation",
+        "file_id": "file-abc123",
+        "filename": "sample_file.pdf",
+        "index": 675
+      },
+    ],
+    "id": "msg_abc123"
+  }
+]
+```
+</div>
+
+  <div className="col col--6" style={{minWidth: 0}}>
+    **New content**
+```python
+from langchain.chat_models import init_chat_model
+
+llm = init_chat_model("openai:gpt-5-mini", message_version="v1")
+llm_with_tools = llm.bind_tools(
+    [
+        {
+            "type": "file_search",
+            "vector_store_ids": ["vs_67d0baa0544c8191be194a85e19cbf92"],
+        }
+    ]
+)
+
+response = llm_with_tools.invoke("What is deep research by OpenAI?")
+response.content
+```
+```
+[
+  {
+    "type": "reasoning",
+    "id": "rs_abc123",
+    "summary": []
+  },
+  {
+    "type": "non_standard",
+    "value": {
+      "type": "file_search_call",
+      "id": "fs_abc123",
+      "queries": [
+        "What is deep research by OpenAI?",
+        "deep research OpenAI definition"
+      ],
+      "status": "completed"
+    }
+  },
+  {
+    "type": "reasoning",
+    "id": "rs_def456",
+    "summary": []
+  },
+  {
+    "type": "text",
+    "text": "Deep research is...",
+    "annotations": [
+      {
+        "type": "citation",
+        "title": "sample_file.pdf",
+        "extras": {
+          "file_id": "file-abc123",
+          "index": 305
+        }
+      },
+      {
+        "type": "citation",
+        "title": "sample_file.pdf",
+        "extras": {
+          "file_id": "file-abc123",
+          "index": 675
+        }
+      },
+    ],
+    "id": "msg_abc123"
+  }
+]
+```
+  </div>
+</div>
+</details>
+
+
+## Feature gaps
+
+The new message types do not yet support LangChain's caching layer. Support will be
+added in the coming weeks.

docs/docusaurus.config.js

@@ -224,13 +224,17 @@ const config = {
           },
           {
             type: "dropdown",
-            label: "v0.3",
+            label: "v0.4",
             position: "right",
             items: [
               {
-                label: "v0.3",
+                label: "v0.4",
                 href: "/docs/introduction",
               },
+              {
+                label: "v0.3",
+                href: "https://python.langchain.com/v0.3/docs/introduction/",
+              },
               {
                 label: "v0.2",
                 href: "https://python.langchain.com/v0.2/docs/introduction",

docs/scripts/packages_yml_get_downloads.py

@@ -1,5 +1,6 @@
 from datetime import datetime, timedelta, timezone
 from pathlib import Path
+import re
 
 import requests
 from ruamel.yaml import YAML
@@ -11,10 +12,18 @@ PACKAGE_YML = Path(__file__).parents[2] / "libs" / "packages.yml"
 
 
 def _get_downloads(p: dict) -> int:
-    url = f"https://pypistats.org/api/packages/{p['name']}/recent?period=month"
-    r = requests.get(url)
-    r.raise_for_status()
-    return r.json()["data"]["last_month"]
+    url = f"https://pepy.tech/badge/{p['name']}/month"
+    svg = requests.get(url, timeout=10).text
+    texts = re.findall(r"<text[^>]*>([^<]+)</text>", svg)
+    latest = texts[-1].strip() if texts else "0"
+
+    # parse "1.2k", "3.4M", "12,345" -> int
+    latest = latest.replace(",", "")
+    if latest.endswith(("k", "K")):
+        return int(float(latest[:-1]) * 1_000)
+    if latest.endswith(("m", "M")):
+        return int(float(latest[:-1]) * 1_000_000)
+    return int(float(latest) if "." in latest else int(latest))
 
 
 current_datetime = datetime.now(timezone.utc)

docs/scripts/partner_pkg_table.py

@@ -101,7 +101,12 @@ def package_row(p: dict) -> str:
     link = p["provider_page"]
     title = p["name_title"]
     provider = f"[{title}]({link})" if link else title
-    return f"| {provider} | [{p['name']}]({p['package_url']}) | ![PyPI - Downloads](https://img.shields.io/pypi/dm/{p['name']}?style=flat-square&label=%20&color=blue) | ![PyPI - Version](https://img.shields.io/pypi/v/{p['name']}?style=flat-square&label=%20&color=orange) | {js} |"
+    return (
+        f"| {provider} | [{p['name']}]({p['package_url']}) | "
+        f"![Downloads](https://static.pepy.tech/badge/{p['name']}/month) | "
+        f"![PyPI - Version](https://img.shields.io/pypi/v/{p['name']}?style=flat-square&label=%20&color=orange) | "
+        f"{js} |"
+    )
 
 
 def table() -> str:

docs/sidebars.js

@@ -82,6 +82,14 @@ module.exports = {
       collapsed: false,
       collapsible: false,
       items: [
+        {
+          type: "category",
+          label: "v0.4",
+          items: [{
+            type: 'autogenerated',
+            dirName: 'versions/v0_4',
+          }],
+        },
         {
           type: 'doc',
           id: 'versions/v0_3/index',
@@ -418,7 +426,7 @@ module.exports = {
             },
           ],
         },
-        
+
       ],
       link: {
         type: "generated-index",