core[patch]: Release 0.2.41 (#26687 )

core[patch]: Fixed bedrock chat model load. (#26643 )
Fixes `load` for `ChatBedrock`, in-turn fixes unit test errors for `standard-tests` in `langchain-aws`, when working with v0.2 branch. ``` FAILED tests/unit_tests/test_standard.py::TestBedrockStandard::test_serdes - ValueError: Trying to deserialize something that cannot be deserialized in current version of langchain-core: ('langchain', 'cha... FAILED tests/unit_tests/test_standard.py::TestBedrockAsConverseStandard::test_serdes - ValueError: Trying to deserialize something that cannot be deserialized in current version of langchain-core: ('langchain', 'cha... ```
2026-02-08 18:19:21 +00:00 · 2024-09-19 15:15:23 -07:00 · 2024-09-19 15:00:45 -07:00 · 2024-09-19 17:27:34 +00:00 · 2024-09-17 18:48:20 -07:00 · 2024-09-16 12:58:29 -07:00
35 changed files with 1768 additions and 1530 deletions
--- a/.github/workflows/_release.yml
+++ b/.github/workflows/_release.yml
@@ -85,7 +85,7 @@ jobs:
          path: langchain
          sparse-checkout: | # this only grabs files for relevant dir
            ${{ inputs.working-directory }}
-          ref: master # this scopes to just master branch
+          ref: ${{ github.ref }} # this scopes to just ref'd branch
          fetch-depth: 0 # this fetches entire commit history
      - name: Check Tags
        id: check-tags
--- a/.github/workflows/codespell.yml
+++ b/.github/workflows/codespell.yml
@@ -3,9 +3,8 @@ name: CI / cd . / make spell_check

 on:
  push:
-    branches: [master, v0.1]
+    branches: [master, v0.1, v0.2]
  pull_request:
-    branches: [master, v0.1]

 permissions:
  contents: read
--- a/README.md
+++ b/README.md
@@ -49,7 +49,7 @@ For these applications, LangChain simplifies the entire application lifecycle:
 - **`langchain-community`**: Third party integrations.
  - Some integrations have been further split into **partner packages** that only rely on **`langchain-core`**. Examples include **`langchain_openai`** and **`langchain_anthropic`**.
 - **`langchain`**: Chains, agents, and retrieval strategies that make up an application's cognitive architecture.
- **[`LangGraph`](https://langchain-ai.github.io/langgraph/)**: A library for building robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph. Integrates smoothly with LangChain, but can be used without it.
+- **[`LangGraph`](https://langchain-ai.github.io/langgraph/)**: A library for building robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph. Integrates smoothly with LangChain, but can be used without it. To learn more about LangGraph, check out our first LangChain Academy course, *Introduction to LangGraph*, available [here](https://academy.langchain.com/courses/intro-to-langgraph).

 ### Productionization:

--- a/docs/Makefile
+++ b/docs/Makefile
@@ -82,7 +82,7 @@ vercel-build: install-vercel-deps build generate-references
 	mv $(OUTPUT_NEW_DOCS_DIR) docs
 	rm -rf build
 	mkdir static/api_reference
-	git clone --depth=1 https://github.com/baskaryan/langchain-api-docs-build.git
+	git clone --depth=1 -b v0.2 https://github.com/baskaryan/langchain-api-docs-build.git
 	mv langchain-api-docs-build/api_reference_build/html/* static/api_reference/
 	rm -rf langchain-api-docs-build
 	NODE_OPTIONS="--max-old-space-size=5000" yarn run docusaurus build
--- a/docs/docs/integrations/chat/anthropic_functions.ipynb
+++ b/docs/docs/integrations/chat/anthropic_functions.ipynb
@@ -19,7 +19,7 @@
    "\n",
    "::: {.callout-warning}\n",
    "\n",
-    "The Anthropic API officially supports tool-calling so this workaround is no longer needed. Please use [ChatAnthropic](/docs/integrations/chat/anthropic) with `langchain-anthropic>=0.1.5`.\n",
+    "The Anthropic API officially supports tool-calling so this workaround is no longer needed. Please use [ChatAnthropic](/docs/integrations/chat/anthropic) with `langchain-anthropic>=0.1.15`.\n",
    "\n",
    ":::\n",
    "\n",
--- a/docs/docs/introduction.mdx
+++ b/docs/docs/introduction.mdx
@@ -55,7 +55,7 @@ These are the best ones to get started with:
 - [Build an Agent](/docs/tutorials/agents)
 - [Introduction to LangGraph](https://langchain-ai.github.io/langgraph/tutorials/introduction/)

-Explore the full list of LangChain tutorials [here](/docs/tutorials), and check out other [LangGraph tutorials here](https://langchain-ai.github.io/langgraph/tutorials/).
+Explore the full list of LangChain tutorials [here](/docs/tutorials), and check out other [LangGraph tutorials here](https://langchain-ai.github.io/langgraph/tutorials/). To learn more about LangGraph, check out our first LangChain Academy course, *Introduction to LangGraph*, available [here](https://academy.langchain.com/courses/intro-to-langgraph).


 ## [How-to guides](/docs/how_to)
--- a/docs/docusaurus.config.js
+++ b/docs/docusaurus.config.js
@@ -126,10 +126,8 @@ const config = {
    ({
      announcementBar: {
        content:
-          'Share your thoughts on AI agents. <a target="_blank" href="https://langchain.typeform.com/state-of-agents">Take the 3-min survey</a>.',
-        isCloseable: true,
-        backgroundColor: "rgba(53, 151, 147, 0.1)",
-        textColor: "rgb(53, 151, 147)",
+          'A newer LangChain version is out! Check out the <a href="https://python.langchain.com/docs/introduction">latest version</a>.',
+        isCloseable: false,
      },
      docs: {
        sidebar: {
@@ -222,6 +220,10 @@ const config = {
            label: "v0.2",
            position: "right",
            items: [
+              {
+                label: "Latest",
+                href: "https://python.langchain.com/docs/introduction/"
+              },
              {
                label: "v0.2",
                href: "/docs/introduction"
--- a/docs/ignore-step.sh
+++ b/docs/ignore-step.sh
@@ -4,20 +4,25 @@ echo "VERCEL_ENV: $VERCEL_ENV"
 echo "VERCEL_GIT_COMMIT_REF: $VERCEL_GIT_COMMIT_REF"


-if [ "$VERCEL_ENV" == "production" ] || [ "$VERCEL_GIT_COMMIT_REF" == "master" ] || [ "$VERCEL_GIT_COMMIT_REF" == "v0.1" ]; then 
-    echo "✅ Production build - proceeding with build"
-    exit 1; 
-else 
-    echo "Checking for changes in docs/"
+if [ "$VERCEL_ENV" == "production" ] || \
+    [ "$VERCEL_GIT_COMMIT_REF" == "master" ] || \
+    [ "$VERCEL_GIT_COMMIT_REF" == "v0.1" ] || \
+    [ "$VERCEL_GIT_COMMIT_REF" == "v0.2" ]
+then 
+     echo "✅ Production build - proceeding with build"
+     exit 1
+fi 
+
+
+echo "Checking for changes in docs/"
+echo "---"
+git log -n 50 --pretty=format:"%s" -- . | grep -v '(#'
+if [ $? -eq 0 ]; then
    echo "---"
-    git log -n 50 --pretty=format:"%s" -- . | grep -v '(#'
-    if [ $? -eq 0 ]; then
-        echo "---"
-        echo "✅ Changes detected in docs/ - proceeding with build"
-        exit 1
-    else
-        echo "---"
-        echo "🛑 No changes detected in docs/ - ignoring build"
-        exit 0
-    fi
+    echo "✅ Changes detected in docs/ - proceeding with build"
+    exit 1
+else
+    echo "---"
+    echo "🛑 No changes detected in docs/ - ignoring build"
+    exit 0
 fi
--- a/docs/src/css/custom.css
+++ b/docs/src/css/custom.css
@@ -248,16 +248,26 @@ nav, h1, h2, h3, h4 {
    no-repeat;
 }

-div[class^=announcementBar_] {
-  height:40px !important;
-  font-size: 20px !important;
-}
+div[class^='announcementBar_'] {
+  font-size: 20px;

-[data-theme='dark'] div[class^=announcementBar_] {
-  background-color: #1b1b1b;
-  color: #fff;
-}
+  /*
+  --site-announcement-bar-stripe-color1: hsl(
+    var(--site-primary-hue-saturation) 85%
+  );
+  --site-announcement-bar-stripe-color2: hsl(
+    var(--site-primary-hue-saturation) 95%
+  );
+   */
+  --site-announcement-bar-stripe-color1: rgb(197,186,254);
+  --site-announcement-bar-stripe-color2: rgb(255,246,224);

-[data-theme='dark'] div[class^=announcementBar_] button {
-  color: #fff;
+  background: repeating-linear-gradient(
+    -35deg,
+    var(--site-announcement-bar-stripe-color1),
+    var(--site-announcement-bar-stripe-color1) 20px,
+    var(--site-announcement-bar-stripe-color2) 10px,
+    var(--site-announcement-bar-stripe-color2) 40px
+  );
+  font-weight: bold;
 }
--- a/docs/src/theme/DocVersionBanner/index.js
+++ b/docs/src/theme/DocVersionBanner/index.js
@@ -3,18 +3,10 @@

 import React from 'react';
 import clsx from 'clsx';
-import useDocusaurusContext from '@docusaurus/useDocusaurusContext';
 import Link from '@docusaurus/Link';
 import Translate from '@docusaurus/Translate';
-import {
-  useActivePlugin,
-  useDocVersionSuggestions,
-} from '@docusaurus/plugin-content-docs/client';
 import {ThemeClassNames} from '@docusaurus/theme-common';
-import {
-  useDocsPreferredVersion,
-  useDocsVersion,
-} from '@docusaurus/theme-common/internal';
+import { useLocalPathname } from '@docusaurus/theme-common/internal';
 function UnreleasedVersionLabel({siteTitle, versionMetadata}) {
  return (
    <Translate
@@ -79,123 +71,40 @@ function LatestVersionSuggestionLabel({versionLabel, to, onClick}) {
    </Translate>
  );
 }
-function DocVersionBannerEnabled({className, versionMetadata}) {
-  const {
-    siteConfig: {title: siteTitle},
-  } = useDocusaurusContext();
-  const {pluginId} = useActivePlugin({failfast: true});
-  const getVersionMainDoc = (version) =>
-    version.docs.find((doc) => doc.id === version.mainDocId);
-  const {savePreferredVersionName} = useDocsPreferredVersion(pluginId);
-  const {latestDocSuggestion, latestVersionSuggestion} =
-    useDocVersionSuggestions(pluginId);
-  // Try to link to same doc in latest version (not always possible), falling
-  // back to main doc of latest version
-  const latestVersionSuggestedDoc =
-    latestDocSuggestion ?? getVersionMainDoc(latestVersionSuggestion);
-  return (
-    <div
-      className={clsx(
-        className,
-        ThemeClassNames.docs.docVersionBanner,
-        'alert alert--warning margin-bottom--md',
-      )}
-      role="alert">
-      <div>
-        <BannerLabel siteTitle={siteTitle} versionMetadata={versionMetadata} />
-      </div>
-      <div className="margin-top--md">
-        <LatestVersionSuggestionLabel
-          versionLabel={latestVersionSuggestion.label}
-          to={latestVersionSuggestedDoc.path}
-          onClick={() => savePreferredVersionName(latestVersionSuggestion.name)}
-        />
-      </div>
-    </div>
-  );
-}
-
-function LatestDocVersionBanner({className, versionMetadata}) {
-  const {
-    siteConfig: {title: siteTitle},
-  } = useDocusaurusContext();
-  const {pluginId} = useActivePlugin({failfast: true});
-  const getVersionMainDoc = (version) =>
-    version.docs.find((doc) => doc.id === version.mainDocId);
-  const {savePreferredVersionName} = useDocsPreferredVersion(pluginId);
-  const {latestDocSuggestion, latestVersionSuggestion} =
-    useDocVersionSuggestions(pluginId);
-  // Try to link to same doc in latest version (not always possible), falling
-  // back to main doc of latest version
-  const latestVersionSuggestedDoc =
-    latestDocSuggestion ?? getVersionMainDoc(latestVersionSuggestion);
-  const canaryPath = `/docs/0.2.x/${latestVersionSuggestedDoc.path.slice("/docs/".length)}`;
-  return (
-    <div
-      className={clsx(
-        className,
-        ThemeClassNames.docs.docVersionBanner,
-        'alert alert--info margin-bottom--md',
-      )}
-      role="alert">
-      <div>
-        <Translate
-          id="theme.docs.versions.unmaintainedVersionLabel"
-          description="The label used to encourage the user to view the experimental 0.2.x version"
-          values={{
-            siteTitle,
-            versionLabel: <b>{versionMetadata.label}</b>,
-          }}>
-          {
-            'This is a stable version of documentation for {siteTitle}\'s version {versionLabel}.'
-          }
-        </Translate>
-      </div>
-      <div className="margin-top--md">
-        <Translate
-          id="theme.docs.versions.latestVersionSuggestionLabel"
-          description="The label used to tell the user to check the experimental version"
-          values={{
-            versionLabel: <b>{versionMetadata.label}</b>,
-            latestVersionLink: (
-              <b>
-                <Link to={canaryPath} onClick={() => savePreferredVersionName("0.2.x")}>
-                  <Translate
-                    id="theme.docs.versions.latestVersionLinkLabel"
-                    description="The label used for the latest version suggestion link label">
-                    this experimental version
-                  </Translate>
-                </Link>
-              </b>
-            ),
-          }}>
-          {
-            'You can also check out {latestVersionLink} for an updated experience.'
-          }
-        </Translate>
-      </div>
-    </div>
-  );
-}

 export default function DocVersionBanner({className}) {
-  const versionMetadata = useDocsVersion();
+  const versionMetadata = {
+    badge: false,
+    banner: 'unmaintained',
+    isLast: false,
+    label: 'v0.2',
+    noIndex: false,
+    pluginId: 'default',
+    version: 'Latest',
+  }
+  console.log({versionMetadata});
+  const localPathname = useLocalPathname();
  if (versionMetadata.banner) {
    return (
-      <DocVersionBannerEnabled
-        className={className}
-        versionMetadata={versionMetadata}
-      />
+      <div
+        className={clsx(
+          className,
+          ThemeClassNames.docs.docVersionBanner,
+          'alert alert--warning margin-bottom--md',
+        )}
+        role="alert">
+        <div>
+          <BannerLabel siteTitle={"LangChain"} versionMetadata={versionMetadata} />
+        </div>
+        <div className="margin-top--md">
+          <LatestVersionSuggestionLabel
+            versionLabel={"Latest"}
+            to={`https://python.langchain.com${localPathname}`}
+            onClick={() => {}}
+          />
+        </div>
+      </div>
    );
-  } else if (versionMetadata.isLast) {
-    // Uncomment when we are ready to direct people to new build
-    // return (
-    //   <LatestDocVersionBanner
-    //     className={className}
-    //     versionMetadata={versionMetadata}
-    //   />
-    // );
-    return null;
  }
  return null;
 }
--- a/docs/src/theme/SiteMetadata/index.js
+++ b/docs/src/theme/SiteMetadata/index.js
@@ -0,0 +1,120 @@
+import React from 'react';
+import Head from '@docusaurus/Head';
+import useDocusaurusContext from '@docusaurus/useDocusaurusContext';
+import useBaseUrl from '@docusaurus/useBaseUrl';
+import {PageMetadata, useThemeConfig} from '@docusaurus/theme-common';
+import {
+  DEFAULT_SEARCH_TAG,
+  useAlternatePageUtils,
+  keyboardFocusedClassName,
+} from '@docusaurus/theme-common/internal';
+import {useLocation} from '@docusaurus/router';
+import {applyTrailingSlash} from '@docusaurus/utils-common';
+import SearchMetadata from '@theme/SearchMetadata';
+// TODO move to SiteMetadataDefaults or theme-common ?
+// Useful for i18n/SEO
+// See https://developers.google.com/search/docs/advanced/crawling/localized-versions
+// See https://github.com/facebook/docusaurus/issues/3317
+function AlternateLangHeaders() {
+  const {
+    i18n: {defaultLocale, localeConfigs},
+  } = useDocusaurusContext();
+  const alternatePageUtils = useAlternatePageUtils();
+  // Note: it is fine to use both "x-default" and "en" to target the same url
+  // See https://www.searchviu.com/en/multiple-hreflang-tags-one-url/
+  return (
+    <Head>
+      {Object.entries(localeConfigs).map(([locale, {htmlLang}]) => (
+        <link
+          key={locale}
+          rel="alternate"
+          href={alternatePageUtils.createUrl({
+            locale,
+            fullyQualified: true,
+          })}
+          hrefLang={htmlLang}
+        />
+      ))}
+      <link
+        rel="alternate"
+        href={alternatePageUtils.createUrl({
+          locale: defaultLocale,
+          fullyQualified: true,
+        })}
+        hrefLang="x-default"
+      />
+    </Head>
+  );
+}
+// Default canonical url inferred from current page location pathname
+function useDefaultCanonicalUrl() {
+  const {
+    siteConfig: {url: siteUrl, baseUrl, trailingSlash},
+  } = useDocusaurusContext();
+  // TODO using useLocation().pathname is not a super idea
+  // See https://github.com/facebook/docusaurus/issues/9170
+  const {pathname} = useLocation();
+  const baseUrlPathname = useBaseUrl(pathname);
+  const canonicalPathname = applyTrailingSlash(baseUrlPathname, {
+    trailingSlash,
+    baseUrl,
+  });
+  const canonicalPathnameNoVersion = canonicalPathname.startsWith('/v0.') ? "/"+canonicalPathname.split('/').slice(2).join('/') : canonicalPathname;
+  return siteUrl + canonicalPathnameNoVersion;
+}
+
+// TODO move to SiteMetadataDefaults or theme-common ?
+function CanonicalUrlHeaders({permalink}) {
+  const {
+    siteConfig: {url: siteUrl},
+  } = useDocusaurusContext();
+  const defaultCanonicalUrl = useDefaultCanonicalUrl();
+  const canonicalUrl = permalink
+    ? `${siteUrl}${permalink}`
+    : defaultCanonicalUrl;
+  return (
+    <Head>
+      <meta property="og:url" content={canonicalUrl} />
+      <link rel="canonical" href={canonicalUrl} />
+    </Head>
+  );
+}
+export default function SiteMetadata() {
+  const {
+    i18n: {currentLocale},
+  } = useDocusaurusContext();
+  // TODO maybe move these 2 themeConfig to siteConfig?
+  // These seems useful for other themes as well
+  const {metadata, image: defaultImage} = useThemeConfig();
+  return (
+    <>
+      <Head>
+        <meta name="twitter:card" content="summary_large_image" />
+        {/* The keyboard focus class name need to be applied when SSR so links
+        are outlined when JS is disabled */}
+        <body className={keyboardFocusedClassName} />
+      </Head>
+
+      {defaultImage && <PageMetadata image={defaultImage} />}
+
+      <CanonicalUrlHeaders />
+
+      <AlternateLangHeaders />
+
+      <SearchMetadata tag={DEFAULT_SEARCH_TAG} locale={currentLocale} />
+
+      {/*
+          It's important to have an additional <Head> element here, as it allows
+          react-helmet to override default metadata values set in previous <Head>
+          like "twitter:card". In same Head, the same meta would appear twice
+          instead of overriding.
+        */}
+      <Head>
+        {/* Yes, "metadatum" is the grammatically correct term */}
+        {metadata.map((metadatum, i) => (
+          <meta key={i} {...metadatum} />
+        ))}
+      </Head>
+    </>
+  );
+}
--- a/libs/community/langchain_community/chat_models/openai.py
+++ b/libs/community/langchain_community/chat_models/openai.py
@@ -5,6 +5,7 @@ from __future__ import annotations
 import logging
 import os
 import sys
+import warnings
 from typing import (
    TYPE_CHECKING,
    Any,
@@ -146,6 +147,33 @@ def _convert_delta_to_message_chunk(
        return default_class(content=content)  # type: ignore[call-arg]


+def _update_token_usage(
+    overall_token_usage: Union[int, dict], new_usage: Union[int, dict]
+) -> Union[int, dict]:
+    # Token usage is either ints or dictionaries
+    # `reasoning_tokens` is nested inside `completion_tokens_details`
+    if isinstance(new_usage, int):
+        if not isinstance(overall_token_usage, int):
+            raise ValueError(
+                f"Got different types for token usage: "
+                f"{type(new_usage)} and {type(overall_token_usage)}"
+            )
+        return new_usage + overall_token_usage
+    elif isinstance(new_usage, dict):
+        if not isinstance(overall_token_usage, dict):
+            raise ValueError(
+                f"Got different types for token usage: "
+                f"{type(new_usage)} and {type(overall_token_usage)}"
+            )
+        return {
+            k: _update_token_usage(overall_token_usage.get(k, 0), v)
+            for k, v in new_usage.items()
+        }
+    else:
+        warnings.warn(f"Unexpected type for token usage: {type(new_usage)}")
+        return new_usage
+
+
@deprecated(
    since="0.0.10", removal="1.0", alternative_import="langchain_openai.ChatOpenAI"
 )
@@ -374,7 +402,9 @@ class ChatOpenAI(BaseChatModel):
            if token_usage is not None:
                for k, v in token_usage.items():
                    if k in overall_token_usage:
-                        overall_token_usage[k] += v
+                        overall_token_usage[k] = _update_token_usage(
+                            overall_token_usage[k], v
+                        )
                    else:
                        overall_token_usage[k] = v
            if system_fingerprint is None:
--- a/libs/community/poetry.lock
+++ b/libs/community/poetry.lock
--- a/libs/community/pyproject.toml
+++ b/libs/community/pyproject.toml
@@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api"

 [tool.poetry]
 name = "langchain-community"
-version = "0.2.16"
+version = "0.2.17"
 description = "Community contributed LangChain integrations."
 authors = []
 license = "MIT"
@@ -30,7 +30,7 @@ ignore-words-list = "momento,collison,ned,foor,reworkd,parth,whats,aapply,mysogy

 [tool.poetry.dependencies]
 python = ">=3.8.1,<4.0"
-langchain-core = "^0.2.38"
+langchain-core = "^0.2.39"
 langchain = "^0.2.16"
 SQLAlchemy = ">=1.4,<3"
 requests = "^2"
@@ -88,6 +88,9 @@ pytest-mock = "^3.10.0"
 pytest-socket = "^0.6.0"
 syrupy = "^4.0.2"
 requests-mock = "^1.11.0"
+# TODO: hack to fix 3.9 builds
+cffi = [{version = "<1.17.1", python="<3.10"}, {version = "*", python=">=3.10"}]
+

 [tool.poetry.group.codespell.dependencies]
 codespell = "^2.2.0"
@@ -98,6 +101,9 @@ vcrpy = "^6"

 [tool.poetry.group.lint.dependencies]
 ruff = "^0.5"
+# TODO: hack to fix 3.9 builds
+cffi = [{version = "<1.17.1", python="<3.10"}, {version = "*", python=">=3.10"}]
+

 [tool.poetry.group.dev.dependencies]
 jupyter = "^1.0.0"
--- a/libs/community/tests/unit_tests/test_dependencies.py
+++ b/libs/community/tests/unit_tests/test_dependencies.py
@@ -92,6 +92,7 @@ def test_test_group_dependencies(poetry_conf: Mapping[str, Any]) -> None:
            "responses",
            "syrupy",
            "requests-mock",
+            "cffi",
        ]
    )

--- a/libs/core/langchain_core/load/load.py
+++ b/libs/core/langchain_core/load/load.py
@@ -1,7 +1,7 @@
 import importlib
 import json
 import os
-from typing import Any, Dict, List, Optional
+from typing import Any, Dict, List, Optional, Tuple

 from langchain_core._api import beta
 from langchain_core.load.mapping import (
@@ -18,6 +18,7 @@ DEFAULT_NAMESPACES = [
    "langchain_community",
    "langchain_anthropic",
    "langchain_groq",
+    "langchain_aws",
 ]

 ALL_SERIALIZABLE_MAPPINGS = {
@@ -36,6 +37,9 @@ class Reviver:
        secrets_map: Optional[Dict[str, str]] = None,
        valid_namespaces: Optional[List[str]] = None,
        secrets_from_env: bool = True,
+        additional_import_mappings: Optional[
+            Dict[Tuple[str, ...], Tuple[str, ...]]
+        ] = None,
    ) -> None:
        """Initialize the reviver.

@@ -47,15 +51,27 @@ class Reviver:
                to allow to be deserialized. Defaults to None.
            secrets_from_env: Whether to load secrets from the environment.
                Defaults to True.
+            additional_import_mappings: A dictionary of additional namespace mappings
+                You can use this to override default mappings or add new mappings.
+                Defaults to None.
        """
        self.secrets_from_env = secrets_from_env
        self.secrets_map = secrets_map or dict()
-        # By default only support langchain, but user can pass in additional namespaces
+        # By default, only support langchain, but user can pass in additional namespaces
        self.valid_namespaces = (
            [*DEFAULT_NAMESPACES, *valid_namespaces]
            if valid_namespaces
            else DEFAULT_NAMESPACES
        )
+        self.additional_import_mappings = additional_import_mappings or dict()
+        self.import_mappings = (
+            {
+                **ALL_SERIALIZABLE_MAPPINGS,
+                **self.additional_import_mappings,
+            }
+            if self.additional_import_mappings
+            else ALL_SERIALIZABLE_MAPPINGS
+        )

    def __call__(self, value: Dict[str, Any]) -> Any:
        if (
@@ -96,16 +112,16 @@ class Reviver:
                raise ValueError(f"Invalid namespace: {value}")

            # If namespace is in known namespaces, try to use mapping
+            key = tuple(namespace + [name])
            if namespace[0] in DEFAULT_NAMESPACES:
                # Get the importable path
-                key = tuple(namespace + [name])
-                if key not in ALL_SERIALIZABLE_MAPPINGS:
+                if key not in self.import_mappings:
                    raise ValueError(
                        "Trying to deserialize something that cannot "
                        "be deserialized in current version of langchain-core: "
                        f"{key}"
                    )
-                import_path = ALL_SERIALIZABLE_MAPPINGS[key]
+                import_path = self.import_mappings[key]
                # Split into module and name
                import_dir, import_obj = import_path[:-1], import_path[-1]
                # Import module
@@ -114,7 +130,12 @@ class Reviver:
                cls = getattr(mod, import_obj)
            # Otherwise, load by path
            else:
-                mod = importlib.import_module(".".join(namespace))
+                if key in self.additional_import_mappings:
+                    import_path = self.import_mappings[key]
+                    mod = importlib.import_module(".".join(import_path[:-1]))
+                    name = import_path[-1]
+                else:
+                    mod = importlib.import_module(".".join(namespace))
                cls = getattr(mod, name)

            # The class must be a subclass of Serializable.
@@ -136,6 +157,7 @@ def loads(
    secrets_map: Optional[Dict[str, str]] = None,
    valid_namespaces: Optional[List[str]] = None,
    secrets_from_env: bool = True,
+    additional_import_mappings: Optional[Dict[Tuple[str, ...], Tuple[str, ...]]] = None,
 ) -> Any:
    """Revive a LangChain class from a JSON string.
    Equivalent to `load(json.loads(text))`.
@@ -149,12 +171,18 @@ def loads(
            to allow to be deserialized. Defaults to None.
        secrets_from_env: Whether to load secrets from the environment.
            Defaults to True.
+        additional_import_mappings: A dictionary of additional namespace mappings
+            You can use this to override default mappings or add new mappings.
+            Defaults to None.

    Returns:
        Revived LangChain objects.
    """
    return json.loads(
-        text, object_hook=Reviver(secrets_map, valid_namespaces, secrets_from_env)
+        text,
+        object_hook=Reviver(
+            secrets_map, valid_namespaces, secrets_from_env, additional_import_mappings
+        ),
    )


@@ -165,6 +193,7 @@ def load(
    secrets_map: Optional[Dict[str, str]] = None,
    valid_namespaces: Optional[List[str]] = None,
    secrets_from_env: bool = True,
+    additional_import_mappings: Optional[Dict[Tuple[str, ...], Tuple[str, ...]]] = None,
 ) -> Any:
    """Revive a LangChain class from a JSON object. Use this if you already
    have a parsed JSON object, eg. from `json.load` or `orjson.loads`.
@@ -178,11 +207,16 @@ def load(
            to allow to be deserialized. Defaults to None.
        secrets_from_env: Whether to load secrets from the environment.
            Defaults to True.
+        additional_import_mappings: A dictionary of additional namespace mappings
+            You can use this to override default mappings or add new mappings.
+            Defaults to None.

    Returns:
        Revived LangChain objects.
    """
-    reviver = Reviver(secrets_map, valid_namespaces, secrets_from_env)
+    reviver = Reviver(
+        secrets_map, valid_namespaces, secrets_from_env, additional_import_mappings
+    )

    def _load(obj: Any) -> Any:
        if isinstance(obj, dict):
--- a/libs/core/langchain_core/load/mapping.py
+++ b/libs/core/langchain_core/load/mapping.py
@@ -1017,4 +1017,9 @@ _JS_SERIALIZABLE_MAPPING: Dict[Tuple[str, ...], Tuple[str, ...]] = {
        "image",
        "ImagePromptTemplate",
    ),
+    ("langchain", "chat_models", "bedrock", "ChatBedrock"): (
+        "langchain_aws",
+        "chat_models",
+        "ChatBedrock",
+    ),
 }
--- a/libs/core/langchain_core/tools/base.py
+++ b/libs/core/langchain_core/tools/base.py
@@ -822,7 +822,7 @@ def _is_message_content_block(obj: Any) -> bool:

 def _stringify(content: Any) -> str:
    try:
-        return json.dumps(content)
+        return json.dumps(content, ensure_ascii=False)
    except Exception:
        return str(content)

--- a/libs/core/langchain_core/utils/function_calling.py
+++ b/libs/core/langchain_core/utils/function_calling.py
@@ -280,7 +280,10 @@ def format_tool_to_openai_function(tool: BaseTool) -> FunctionDescription:
    Returns:
        The function description.
    """
-    if tool.tool_call_schema:
+    from langchain_core.tools import simple
+
+    is_simple_oai_tool = isinstance(tool, simple.Tool) and not tool.args_schema
+    if tool.tool_call_schema and not is_simple_oai_tool:
        return convert_pydantic_to_openai_function(
            tool.tool_call_schema, name=tool.name, description=tool.description
        )
@@ -602,9 +605,13 @@ def _recursive_set_additional_properties_false(
    schema: Dict[str, Any],
 ) -> Dict[str, Any]:
    if isinstance(schema, dict):
-        # Check if 'required' is a key at the current level
-        if "required" in schema:
+        # Check if 'required' is a key at the current level or if the schema is empty,
+        # in which case additionalProperties still needs to be specified.
+        if "required" in schema or (
+            "properties" in schema and not schema["properties"]
+        ):
            schema["additionalProperties"] = False
+
        # Recursively check 'properties' and 'items' if they exist
        if "properties" in schema:
            for value in schema["properties"].values():
--- a/libs/core/poetry.lock
+++ b/libs/core/poetry.lock
@@ -16,13 +16,13 @@ typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.9\""}

 [[package]]
 name = "anyio"
-version = "4.4.0"
+version = "4.5.0"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "anyio-4.4.0-py3-none-any.whl", hash = "sha256:c1b2d8f46a8a812513012e1107cb0e68c17159a7a594208005a57dc776e1bdc7"},
-    {file = "anyio-4.4.0.tar.gz", hash = "sha256:5aadc6a1bbb7cdb0bede386cac5e2940f5e2ff3aa20277e991cf028e0585ce94"},
+    {file = "anyio-4.5.0-py3-none-any.whl", hash = "sha256:fdeb095b7cc5a5563175eedd926ec4ae55413bb4be5770c424af0ba46ccb4a78"},
+    {file = "anyio-4.5.0.tar.gz", hash = "sha256:c5a275fe5ca0afd788001f58fca1e69e29ce706d746e317d660e21f70c530ef9"},
 ]

 [package.dependencies]
@@ -32,9 +32,9 @@ sniffio = ">=1.1"
 typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}

 [package.extras]
-doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
-test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
-trio = ["trio (>=0.23)"]
+doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.21.0b1)"]
+trio = ["trio (>=0.26.1)"]

 [[package]]
 name = "appnope"
@@ -243,89 +243,89 @@ css = ["tinycss2 (>=1.1.0,<1.3)"]

 [[package]]
 name = "certifi"
-version = "2024.7.4"
+version = "2024.8.30"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "certifi-2024.7.4-py3-none-any.whl", hash = "sha256:c198e21b1289c2ab85ee4e67bb4b4ef3ead0892059901a8d5b622f24a1101e90"},
-    {file = "certifi-2024.7.4.tar.gz", hash = "sha256:5a1e7645bc0ec61a09e26c36f6106dd4cf40c6db3a1fb6352b0244e7fb057c7b"},
+    {file = "certifi-2024.8.30-py3-none-any.whl", hash = "sha256:922820b53db7a7257ffbda3f597266d435245903d80737e34f8a45ff3e3230d8"},
+    {file = "certifi-2024.8.30.tar.gz", hash = "sha256:bec941d2aa8195e248a60b31ff9f0558284cf01a52591ceda73ea9afffd69fd9"},
 ]

 [[package]]
 name = "cffi"
-version = "1.17.0"
+version = "1.17.1"
 description = "Foreign Function Interface for Python calling C code."
 optional = false
 python-versions = ">=3.8"
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 [package.dependencies]
@@ -953,33 +960,32 @@ referencing = ">=0.31.0"

 [[package]]
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 description = "Jupyter metapackage. Install all the Jupyter components in one go."
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 ipywidgets = "*"
 jupyter-console = "*"
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 nbconvert = "*"
 notebook = "*"
-qtconsole = "*"

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@@ -1230,6 +1236,7 @@ develop = true
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 langchain-core = ">=0.1.40,<0.3"
 pytest = ">=7,<9"
+syrupy = "^4"

 [package.source]
 type = "directory"
@@ -1237,7 +1244,7 @@ url = "../standard-tests"

 [[package]]
 name = "langchain-text-splitters"
-version = "0.2.3"
+version = "0.2.4"
 description = "LangChain text splitting utilities"
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 python-versions = ">=3.8.1,<4.0"
@@ -1245,7 +1252,7 @@ files = []
 develop = true

 [package.dependencies]
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+langchain-core = "^0.2.38"

 [package.source]
 type = "directory"
@@ -1253,13 +1260,13 @@ url = "../text-splitters"

 [[package]]
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 [package.extras]
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-    {file = "zipp-3.20.1-py3-none-any.whl", hash = "sha256:9960cd8967c8f85a56f920d5d507274e74f9ff813a0ab8889a5b5be2daf44064"},
-    {file = "zipp-3.20.1.tar.gz", hash = "sha256:c22b14cc4763c5a5b04134207736c107db42e9d3ef2d9779d465f5f1bcba572b"},
+    {file = "zipp-3.20.2-py3-none-any.whl", hash = "sha256:a817ac80d6cf4b23bf7f2828b7cabf326f15a001bea8b1f9b49631780ba28350"},
+    {file = "zipp-3.20.2.tar.gz", hash = "sha256:bc9eb26f4506fda01b81bcde0ca78103b6e62f991b381fec825435c836edbc29"},
 ]

 [package.extras]
--- a/libs/core/pyproject.toml
+++ b/libs/core/pyproject.toml
@@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api"

 [tool.poetry]
 name = "langchain-core"
-version = "0.2.39"
+version = "0.2.41"
 description = "Building applications with LLMs through composability"
 authors = []
 license = "MIT"
--- a/libs/core/tests/unit_tests/load/test_serializable.py
+++ b/libs/core/tests/unit_tests/load/test_serializable.py
@@ -1,6 +1,6 @@
 from typing import Dict

-from langchain_core.load import Serializable, dumpd
+from langchain_core.load import Serializable, dumpd, load
 from langchain_core.load.serializable import _is_field_useful
 from langchain_core.pydantic_v1 import Field

@@ -107,3 +107,61 @@ def test__is_field_useful() -> None:
    foo = Foo(x=default_x, y=default_y, z=ArrayObj())
    assert not _is_field_useful(foo, "x", foo.x)
    assert not _is_field_useful(foo, "y", foo.y)
+
+
+class Foo(Serializable):
+    bar: int
+    baz: str
+
+    @classmethod
+    def is_lc_serializable(cls) -> bool:
+        return True
+
+
+def test_simple_deserialization() -> None:
+    foo = Foo(bar=1, baz="hello")
+    assert foo.lc_id() == ["tests", "unit_tests", "load", "test_serializable", "Foo"]
+    serialized_foo = dumpd(foo)
+    assert serialized_foo == {
+        "id": ["tests", "unit_tests", "load", "test_serializable", "Foo"],
+        "kwargs": {"bar": 1, "baz": "hello"},
+        "lc": 1,
+        "type": "constructor",
+    }
+    new_foo = load(serialized_foo, valid_namespaces=["tests"])
+    assert new_foo == foo
+
+
+class Foo2(Serializable):
+    bar: int
+    baz: str
+
+    @classmethod
+    def is_lc_serializable(cls) -> bool:
+        return True
+
+
+def test_simple_deserialization_with_additional_imports() -> None:
+    foo = Foo(bar=1, baz="hello")
+    assert foo.lc_id() == ["tests", "unit_tests", "load", "test_serializable", "Foo"]
+    serialized_foo = dumpd(foo)
+    assert serialized_foo == {
+        "id": ["tests", "unit_tests", "load", "test_serializable", "Foo"],
+        "kwargs": {"bar": 1, "baz": "hello"},
+        "lc": 1,
+        "type": "constructor",
+    }
+    new_foo = load(
+        serialized_foo,
+        valid_namespaces=["tests"],
+        additional_import_mappings={
+            ("tests", "unit_tests", "load", "test_serializable", "Foo"): (
+                "tests",
+                "unit_tests",
+                "load",
+                "test_serializable",
+                "Foo2",
+            )
+        },
+    )
+    assert isinstance(new_foo, Foo2)
--- a/libs/core/tests/unit_tests/tracers/test_langchain.py
+++ b/libs/core/tests/unit_tests/tracers/test_langchain.py
@@ -65,7 +65,7 @@ def test_example_id_assignment_threadsafe() -> None:
 def test_tracer_with_run_tree_parent() -> None:
    mock_session = unittest.mock.MagicMock()
    client = Client(session=mock_session, api_key="test")
-    parent = RunTree(name="parent", inputs={"input": "foo"}, client=client)
+    parent = RunTree(name="parent", inputs={"input": "foo"}, _client=client)
    run_id = uuid.uuid4()
    tracer = LangChainTracer(client=client)
    tracer.order_map[parent.id] = (parent.trace_id, parent.dotted_order)
--- a/libs/core/tests/unit_tests/utils/test_function_calling.py
+++ b/libs/core/tests/unit_tests/utils/test_function_calling.py
@@ -37,7 +37,7 @@ except ImportError:
 from langchain_core.messages import AIMessage, HumanMessage, ToolMessage
 from langchain_core.pydantic_v1 import BaseModel, Field
 from langchain_core.runnables import Runnable, RunnableLambda
-from langchain_core.tools import BaseTool, tool
+from langchain_core.tools import BaseTool, StructuredTool, Tool, tool
 from langchain_core.utils.function_calling import (
    _convert_typed_dict_to_openai_function,
    convert_to_openai_function,
@@ -111,6 +111,20 @@ def dummy_tool() -> BaseTool:
    return DummyFunction()


+@pytest.fixture()
+def dummy_structured_tool() -> StructuredTool:
+    class Schema(BaseModel):
+        arg1: int = Field(..., description="foo")
+        arg2: Literal["bar", "baz"] = Field(..., description="one of 'bar', 'baz'")
+
+    return StructuredTool.from_function(
+        lambda x: None,
+        name="dummy_function",
+        description="dummy function",
+        args_schema=Schema,
+    )
+
+
@pytest.fixture()
 def dummy_pydantic() -> Type[BaseModel]:
    class dummy_function(BaseModel):
@@ -233,6 +247,7 @@ class DummyWithClassMethod:
 def test_convert_to_openai_function(
    pydantic: Type[BaseModel],
    function: Callable,
+    dummy_structured_tool: StructuredTool,
    dummy_tool: BaseTool,
    json_schema: Dict,
    Annotated_function: Callable,
@@ -263,6 +278,7 @@ def test_convert_to_openai_function(
    for fn in (
        pydantic,
        function,
+        dummy_structured_tool,
        dummy_tool,
        json_schema,
        expected,
@@ -295,6 +311,27 @@ def test_convert_to_openai_function(
    runnable_expected["parameters"] = parameters
    assert actual == runnable_expected

+    # Test simple Tool
+    def my_function(input_string: str) -> str:
+        pass
+
+    tool = Tool(
+        name="dummy_function",
+        func=my_function,
+        description="test description",
+    )
+    actual = convert_to_openai_function(tool)
+    expected = {
+        "name": "dummy_function",
+        "description": "test description",
+        "parameters": {
+            "properties": {"__arg1": {"title": "__arg1", "type": "string"}},
+            "required": ["__arg1"],
+            "type": "object",
+        },
+    }
+    assert actual == expected
+

@pytest.mark.xfail(reason="Direct pydantic v2 models not yet supported")
 def test_convert_to_openai_function_nested_v2() -> None:
@@ -756,3 +793,22 @@ def test_convert_union_type_py_39() -> None:
    assert result["parameters"]["properties"]["input"] == {
        "anyOf": [{"type": "integer"}, {"type": "number"}]
    }
+
+
+def test_convert_to_openai_function_no_args() -> None:
+    @tool
+    def empty_tool() -> str:
+        """No args"""
+        return "foo"
+
+    actual = convert_to_openai_function(empty_tool, strict=True)
+    assert actual == {
+        "name": "empty_tool",
+        "description": "No args",
+        "parameters": {
+            "properties": {},
+            "additionalProperties": False,
+            "type": "object",
+        },
+        "strict": True,
+    }
--- a/libs/partners/groq/langchain_groq/chat_models.py
+++ b/libs/partners/groq/langchain_groq/chat_models.py
@@ -52,7 +52,6 @@ from langchain_core.messages import (
    ToolMessage,
    ToolMessageChunk,
 )
-from langchain_core.messages.tool import tool_call_chunk as create_tool_call_chunk
 from langchain_core.output_parsers import (
    JsonOutputParser,
    PydanticOutputParser,
@@ -385,9 +384,11 @@ class ChatGroq(BaseChatModel):
            values["temperature"] = 1e-8

        client_params = {
-            "api_key": values["groq_api_key"].get_secret_value()
-            if values["groq_api_key"]
-            else None,
+            "api_key": (
+                values["groq_api_key"].get_secret_value()
+                if values["groq_api_key"]
+                else None
+            ),
            "base_url": values["groq_api_base"],
            "timeout": values["request_timeout"],
            "max_retries": values["max_retries"],
@@ -502,42 +503,6 @@ class ChatGroq(BaseChatModel):
    ) -> Iterator[ChatGenerationChunk]:
        message_dicts, params = self._create_message_dicts(messages, stop)

-        # groq api does not support streaming with tools yet
-        if "tools" in kwargs:
-            response = self.client.create(
-                messages=message_dicts, **{**params, **kwargs}
-            )
-            chat_result = self._create_chat_result(response)
-            generation = chat_result.generations[0]
-            message = cast(AIMessage, generation.message)
-            tool_call_chunks = [
-                create_tool_call_chunk(
-                    name=rtc["function"].get("name"),
-                    args=rtc["function"].get("arguments"),
-                    id=rtc.get("id"),
-                    index=rtc.get("index"),
-                )
-                for rtc in message.additional_kwargs.get("tool_calls", [])
-            ]
-            chunk_ = ChatGenerationChunk(
-                message=AIMessageChunk(
-                    content=message.content,
-                    additional_kwargs=message.additional_kwargs,
-                    tool_call_chunks=tool_call_chunks,
-                    usage_metadata=message.usage_metadata,
-                ),
-                generation_info=generation.generation_info,
-            )
-            if run_manager:
-                geninfo = chunk_.generation_info or {}
-                run_manager.on_llm_new_token(
-                    chunk_.text,
-                    chunk=chunk_,
-                    logprobs=geninfo.get("logprobs"),
-                )
-            yield chunk_
-            return
-
        params = {**params, **kwargs, "stream": True}

        default_chunk_class: Type[BaseMessageChunk] = AIMessageChunk
@@ -574,42 +539,6 @@ class ChatGroq(BaseChatModel):
    ) -> AsyncIterator[ChatGenerationChunk]:
        message_dicts, params = self._create_message_dicts(messages, stop)

-        # groq api does not support streaming with tools yet
-        if "tools" in kwargs:
-            response = await self.async_client.create(
-                messages=message_dicts, **{**params, **kwargs}
-            )
-            chat_result = self._create_chat_result(response)
-            generation = chat_result.generations[0]
-            message = cast(AIMessage, generation.message)
-            tool_call_chunks = [
-                {
-                    "name": rtc["function"].get("name"),
-                    "args": rtc["function"].get("arguments"),
-                    "id": rtc.get("id"),
-                    "index": rtc.get("index"),
-                }
-                for rtc in message.additional_kwargs.get("tool_calls", [])
-            ]
-            chunk_ = ChatGenerationChunk(
-                message=AIMessageChunk(
-                    content=message.content,
-                    additional_kwargs=message.additional_kwargs,
-                    tool_call_chunks=tool_call_chunks,  # type: ignore[arg-type]
-                    usage_metadata=message.usage_metadata,
-                ),
-                generation_info=generation.generation_info,
-            )
-            if run_manager:
-                geninfo = chunk_.generation_info or {}
-                await run_manager.on_llm_new_token(
-                    chunk_.text,
-                    chunk=chunk_,
-                    logprobs=geninfo.get("logprobs"),
-                )
-            yield chunk_
-            return
-
        params = {**params, **kwargs, "stream": True}

        default_chunk_class: Type[BaseMessageChunk] = AIMessageChunk
--- a/libs/partners/groq/poetry.lock
+++ b/libs/partners/groq/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.

 [[package]]
 name = "annotated-types"
@@ -324,7 +324,7 @@ files = [

 [[package]]
 name = "langchain-core"
-version = "0.2.38"
+version = "0.2.39"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = ">=3.8.1,<4.0"
@@ -333,7 +333,7 @@ develop = true

 [package.dependencies]
 jsonpatch = "^1.33"
-langsmith = "^0.1.75"
+langsmith = "^0.1.112"
 packaging = ">=23.2,<25"
 pydantic = [
    {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""},
@@ -368,13 +368,13 @@ url = "../../standard-tests"

 [[package]]
 name = "langsmith"
-version = "0.1.111"
+version = "0.1.118"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langsmith-0.1.111-py3-none-any.whl", hash = "sha256:e5c702764911193c9812fe55136ae01cd0b9ddf5dff0b068ce6fd60eeddbcb40"},
-    {file = "langsmith-0.1.111.tar.gz", hash = "sha256:bab24fd6125685f588d682693c4a3253e163804242829b1ff902e1a3e984a94c"},
+    {file = "langsmith-0.1.118-py3-none-any.whl", hash = "sha256:f017127b3efb037da5e46ff4f8583e8192e7955191737240c327f3eadc144d7c"},
+    {file = "langsmith-0.1.118.tar.gz", hash = "sha256:ff1ca06c92c6081250244ebbce5d0bb347b9d898d2e9b60a13b11f0f0720f09f"},
 ]

 [package.dependencies]
@@ -538,18 +538,18 @@ testing = ["pytest", "pytest-benchmark"]

 [[package]]
 name = "pydantic"
-version = "2.8.2"
+version = "2.9.1"
 description = "Data validation using Python type hints"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "pydantic-2.8.2-py3-none-any.whl", hash = "sha256:73ee9fddd406dc318b885c7a2eab8a6472b68b8fb5ba8150949fc3db939f23c8"},
-    {file = "pydantic-2.8.2.tar.gz", hash = "sha256:6f62c13d067b0755ad1c21a34bdd06c0c12625a22b0fc09c6b149816604f7c2a"},
+    {file = "pydantic-2.9.1-py3-none-any.whl", hash = "sha256:7aff4db5fdf3cf573d4b3c30926a510a10e19a0774d38fc4967f78beb6deb612"},
+    {file = "pydantic-2.9.1.tar.gz", hash = "sha256:1363c7d975c7036df0db2b4a61f2e062fbc0aa5ab5f2772e0ffc7191a4f4bce2"},
 ]

 [package.dependencies]
-annotated-types = ">=0.4.0"
-pydantic-core = "2.20.1"
+annotated-types = ">=0.6.0"
+pydantic-core = "2.23.3"
 typing-extensions = [
    {version = ">=4.6.1", markers = "python_version < \"3.13\""},
    {version = ">=4.12.2", markers = "python_version >= \"3.13\""},
@@ -557,103 +557,104 @@ typing-extensions = [

 [package.extras]
 email = ["email-validator (>=2.0.0)"]
+timezone = ["tzdata"]

 [[package]]
 name = "pydantic-core"
-version = "2.20.1"
+version = "2.23.3"
 description = "Core functionality for Pydantic validation and serialization"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "pydantic_core-2.23.3.tar.gz", hash = "sha256:3cb0f65d8b4121c1b015c60104a685feb929a29d7cf204387c7f2688c7974690"},
 ]

 [package.dependencies]
@@ -905,13 +906,13 @@ files = [

 [[package]]
 name = "urllib3"
-version = "2.2.2"
+version = "2.2.3"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "urllib3-2.2.2-py3-none-any.whl", hash = "sha256:a448b2f64d686155468037e1ace9f2d2199776e17f0a46610480d311f73e3472"},
-    {file = "urllib3-2.2.2.tar.gz", hash = "sha256:dd505485549a7a552833da5e6063639d0d177c04f23bc3864e41e5dc5f612168"},
+    {file = "urllib3-2.2.3-py3-none-any.whl", hash = "sha256:ca899ca043dcb1bafa3e262d73aa25c465bfb49e0bd9dd5d59f1d0acba2f8fac"},
+    {file = "urllib3-2.2.3.tar.gz", hash = "sha256:e7d814a81dad81e6caf2ec9fdedb284ecc9c73076b62654547cc64ccdcae26e9"},
 ]

 [package.extras]
@@ -970,4 +971,4 @@ watchmedo = ["PyYAML (>=3.10)"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8.1,<4.0"
-content-hash = "1acd2a13007daf276263c7036959c1a4c973d4fd8dba924105c8fdc035e02a88"
+content-hash = "700b1e85c503bf36156c6b19ee4f1cdec630738bc5a22096b6a3ff800d6e46a6"
--- a/libs/partners/groq/pyproject.toml
+++ b/libs/partners/groq/pyproject.toml
@@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api"

 [tool.poetry]
 name = "langchain-groq"
-version = "0.1.9"
+version = "0.1.10"
 description = "An integration package connecting Groq and LangChain"
 authors = []
 readme = "README.md"
@@ -20,7 +20,7 @@ disallow_untyped_defs = "True"

 [tool.poetry.dependencies]
 python = ">=3.8.1,<4.0"
-langchain-core = "^0.2.26"
+langchain-core = "^0.2.39"
 groq = ">=0.4.1,<1"

 [tool.ruff.lint]
--- a/libs/partners/groq/tests/unit_tests/snapshots/test_standard.ambr
+++ b/libs/partners/groq/tests/unit_tests/snapshots/test_standard.ambr
@@ -1,42 +1,6 @@
 # serializer version: 1
 # name: TestGroqStandard.test_serdes[serialized]
  dict({
-    'graph': dict({
-      'edges': list([
-        dict({
-          'source': 0,
-          'target': 1,
-        }),
-        dict({
-          'source': 1,
-          'target': 2,
-        }),
-      ]),
-      'nodes': list([
-        dict({
-          'data': 'ChatGroqInput',
-          'id': 0,
-          'type': 'schema',
-        }),
-        dict({
-          'data': dict({
-            'id': list([
-              'langchain_groq',
-              'chat_models',
-              'ChatGroq',
-            ]),
-            'name': 'ChatGroq',
-          }),
-          'id': 1,
-          'type': 'runnable',
-        }),
-        dict({
-          'data': 'ChatGroqOutput',
-          'id': 2,
-          'type': 'schema',
-        }),
-      ]),
-    }),
    'id': list([
      'langchain_groq',
      'chat_models',
--- a/libs/partners/openai/langchain_openai/chat_models/base.py
+++ b/libs/partners/openai/langchain_openai/chat_models/base.py
@@ -65,7 +65,6 @@ from langchain_core.messages import (
 from langchain_core.messages.ai import UsageMetadata
 from langchain_core.messages.tool import tool_call_chunk
 from langchain_core.output_parsers import JsonOutputParser, PydanticOutputParser
-from langchain_core.output_parsers.base import OutputParserLike
 from langchain_core.output_parsers.openai_tools import (
    JsonOutputKeyToolsParser,
    PydanticToolsParser,
@@ -335,6 +334,33 @@ def _convert_chunk_to_generation_chunk(
    return generation_chunk


+def _update_token_usage(
+    overall_token_usage: Union[int, dict], new_usage: Union[int, dict]
+) -> Union[int, dict]:
+    # Token usage is either ints or dictionaries
+    # `reasoning_tokens` is nested inside `completion_tokens_details`
+    if isinstance(new_usage, int):
+        if not isinstance(overall_token_usage, int):
+            raise ValueError(
+                f"Got different types for token usage: "
+                f"{type(new_usage)} and {type(overall_token_usage)}"
+            )
+        return new_usage + overall_token_usage
+    elif isinstance(new_usage, dict):
+        if not isinstance(overall_token_usage, dict):
+            raise ValueError(
+                f"Got different types for token usage: "
+                f"{type(new_usage)} and {type(overall_token_usage)}"
+            )
+        return {
+            k: _update_token_usage(overall_token_usage.get(k, 0), v)
+            for k, v in new_usage.items()
+        }
+    else:
+        warnings.warn(f"Unexpected type for token usage: {type(new_usage)}")
+        return new_usage
+
+
 class _FunctionCall(TypedDict):
    name: str

@@ -561,7 +587,9 @@ class BaseChatOpenAI(BaseChatModel):
            if token_usage is not None:
                for k, v in token_usage.items():
                    if k in overall_token_usage:
-                        overall_token_usage[k] += v
+                        overall_token_usage[k] = _update_token_usage(
+                            overall_token_usage[k], v
+                        )
                    else:
                        overall_token_usage[k] = v
            if system_fingerprint is None:
@@ -1392,7 +1420,7 @@ class BaseChatOpenAI(BaseChatModel):
                strict=strict,
            )
            if is_pydantic_schema:
-                output_parser: OutputParserLike = PydanticToolsParser(
+                output_parser: Runnable = PydanticToolsParser(
                    tools=[schema],  # type: ignore[list-item]
                    first_tool_only=True,  # type: ignore[list-item]
                )
@@ -1416,11 +1444,12 @@ class BaseChatOpenAI(BaseChatModel):
            strict = strict if strict is not None else True
            response_format = _convert_to_openai_response_format(schema, strict=strict)
            llm = self.bind(response_format=response_format)
-            output_parser = (
-                cast(Runnable, _oai_structured_outputs_parser)
-                if is_pydantic_schema
-                else JsonOutputParser()
-            )
+            if is_pydantic_schema:
+                output_parser = _oai_structured_outputs_parser.with_types(
+                    output_type=cast(type, schema)
+                )
+            else:
+                output_parser = JsonOutputParser()
        else:
            raise ValueError(
                f"Unrecognized method argument. Expected one of 'function_calling' or "
--- a/libs/partners/openai/poetry.lock
+++ b/libs/partners/openai/poetry.lock
@@ -38,13 +38,13 @@ trio = ["trio (>=0.23)"]

 [[package]]
 name = "certifi"
-version = "2024.7.4"
+version = "2024.8.30"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "certifi-2024.7.4-py3-none-any.whl", hash = "sha256:c198e21b1289c2ab85ee4e67bb4b4ef3ead0892059901a8d5b622f24a1101e90"},
-    {file = "certifi-2024.7.4.tar.gz", hash = "sha256:5a1e7645bc0ec61a09e26c36f6106dd4cf40c6db3a1fb6352b0244e7fb057c7b"},
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 pytest = ">=7,<9"
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 ]

 [[package]]
@@ -1473,13 +1490,13 @@ files = [

 [[package]]
 name = "urllib3"
-version = "2.2.2"
+version = "2.2.3"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "urllib3-2.2.2-py3-none-any.whl", hash = "sha256:a448b2f64d686155468037e1ace9f2d2199776e17f0a46610480d311f73e3472"},
-    {file = "urllib3-2.2.2.tar.gz", hash = "sha256:dd505485549a7a552833da5e6063639d0d177c04f23bc3864e41e5dc5f612168"},
+    {file = "urllib3-2.2.3-py3-none-any.whl", hash = "sha256:ca899ca043dcb1bafa3e262d73aa25c465bfb49e0bd9dd5d59f1d0acba2f8fac"},
+    {file = "urllib3-2.2.3.tar.gz", hash = "sha256:e7d814a81dad81e6caf2ec9fdedb284ecc9c73076b62654547cc64ccdcae26e9"},
 ]

 [package.extras]
@@ -1538,4 +1555,4 @@ watchmedo = ["PyYAML (>=3.10)"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8.1,<4.0"
-content-hash = "2cc7944c077e0efabce72fc7c8e5e87b145fc122048a1b4c5674ee9d1399bb52"
+content-hash = "f69618f90bef90135927a494c225c7c0d204a5641e4061b15ae9658536f0aa4a"
--- a/libs/partners/openai/pyproject.toml
+++ b/libs/partners/openai/pyproject.toml
@@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api"

 [tool.poetry]
 name = "langchain-openai"
-version = "0.1.23"
+version = "0.1.25"
 description = "An integration package connecting OpenAI and LangChain"
 authors = []
 readme = "README.md"
@@ -23,7 +23,7 @@ ignore_missing_imports = true

 [tool.poetry.dependencies]
 python = ">=3.8.1,<4.0"
-langchain-core = "^0.2.35"
+langchain-core = "^0.2.40"
 openai = "^1.40.0"
 tiktoken = ">=0.7,<1"

--- a/libs/partners/openai/tests/unit_tests/chat_models/snapshots/test_azure_standard.ambr
+++ b/libs/partners/openai/tests/unit_tests/chat_models/snapshots/test_azure_standard.ambr
@@ -1,43 +1,6 @@
 # serializer version: 1
 # name: TestOpenAIStandard.test_serdes[serialized]
  dict({
-    'graph': dict({
-      'edges': list([
-        dict({
-          'source': 0,
-          'target': 1,
-        }),
-        dict({
-          'source': 1,
-          'target': 2,
-        }),
-      ]),
-      'nodes': list([
-        dict({
-          'data': 'AzureChatOpenAIInput',
-          'id': 0,
-          'type': 'schema',
-        }),
-        dict({
-          'data': dict({
-            'id': list([
-              'langchain',
-              'chat_models',
-              'azure_openai',
-              'AzureChatOpenAI',
-            ]),
-            'name': 'AzureChatOpenAI',
-          }),
-          'id': 1,
-          'type': 'runnable',
-        }),
-        dict({
-          'data': 'AzureChatOpenAIOutput',
-          'id': 2,
-          'type': 'schema',
-        }),
-      ]),
-    }),
    'id': list([
      'langchain',
      'chat_models',
--- a/libs/partners/openai/tests/unit_tests/chat_models/snapshots/test_base_standard.ambr
+++ b/libs/partners/openai/tests/unit_tests/chat_models/snapshots/test_base_standard.ambr
@@ -1,43 +1,6 @@
 # serializer version: 1
 # name: TestOpenAIStandard.test_serdes[serialized]
  dict({
-    'graph': dict({
-      'edges': list([
-        dict({
-          'source': 0,
-          'target': 1,
-        }),
-        dict({
-          'source': 1,
-          'target': 2,
-        }),
-      ]),
-      'nodes': list([
-        dict({
-          'data': 'ChatOpenAIInput',
-          'id': 0,
-          'type': 'schema',
-        }),
-        dict({
-          'data': dict({
-            'id': list([
-              'langchain',
-              'chat_models',
-              'openai',
-              'ChatOpenAI',
-            ]),
-            'name': 'ChatOpenAI',
-          }),
-          'id': 1,
-          'type': 'runnable',
-        }),
-        dict({
-          'data': 'ChatOpenAIOutput',
-          'id': 2,
-          'type': 'schema',
-        }),
-      ]),
-    }),
    'id': list([
      'langchain',
      'chat_models',
--- a/libs/partners/openai/tests/unit_tests/chat_models/test_base.py
+++ b/libs/partners/openai/tests/unit_tests/chat_models/test_base.py
@@ -18,6 +18,7 @@ from langchain_core.messages import (
 )
 from langchain_core.messages.ai import UsageMetadata
 from langchain_core.pydantic_v1 import BaseModel
+from pydantic import BaseModel as BaseModelV2

 from langchain_openai import ChatOpenAI
 from langchain_openai.chat_models.base import (
@@ -694,3 +695,31 @@ def test_get_num_tokens_from_messages() -> None:
    expected = 176
    actual = llm.get_num_tokens_from_messages(messages)
    assert expected == actual
+
+
+class Foo(BaseModel):
+    bar: int
+
+
+class FooV2(BaseModelV2):
+    bar: int
+
+
+@pytest.mark.parametrize("schema", [Foo, FooV2])
+def test_schema_from_with_structured_output(schema: Type) -> None:
+    """Test schema from with_structured_output."""
+
+    llm = ChatOpenAI()
+
+    structured_llm = llm.with_structured_output(
+        schema, method="json_schema", strict=True
+    )
+
+    expected = {
+        "properties": {"bar": {"title": "Bar", "type": "integer"}},
+        "required": ["bar"],
+        "title": schema.__name__,
+        "type": "object",
+    }
+    actual = structured_llm.get_output_schema().schema()
+    assert actual == expected
--- a/libs/partners/robocorp/pyproject.toml
+++ b/libs/partners/robocorp/pyproject.toml
@@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api"

 [tool.poetry]
 name = "langchain-robocorp"
-version = "0.0.10"
+version = "0.0.10.post1"
 description = "An integration package connecting Robocorp Action Server and LangChain"
 authors = []
 readme = "README.md"
@@ -15,7 +15,7 @@ license = "MIT"
 disallow_untyped_defs = "True"

 [tool.poetry.urls]
-"Source Code" = "https://github.com/langchain-ai/langchain/tree/master/libs/partners/robocorp"
+"Source Code" = "https://github.com/langchain-ai/langchain/tree/v0.2/libs/partners/robocorp"

 [tool.poetry.dependencies]
 python = ">=3.8.1,<4.0"
Author	SHA1	Message	Date
Bagatur	6cfd1e846a	core[patch]: Release 0.2.41 (#26687 )	2024-09-19 15:15:23 -07:00
Piyush Jain	c5eca37262	core[patch]: Fixed bedrock chat model load. (#26643 ) Fixes `load` for `ChatBedrock`, in-turn fixes unit test errors for `standard-tests` in `langchain-aws`, when working with v0.2 branch. ``` FAILED tests/unit_tests/test_standard.py::TestBedrockStandard::test_serdes - ValueError: Trying to deserialize something that cannot be deserialized in current version of langchain-core: ('langchain', 'cha... FAILED tests/unit_tests/test_standard.py::TestBedrockAsConverseStandard::test_serdes - ValueError: Trying to deserialize something that cannot be deserialized in current version of langchain-core: ('langchain', 'cha... ```	2024-09-19 15:00:45 -07:00
Erick Friis	70c992bd61	community: poetry lock for cffi dep (#26674 )	2024-09-19 17:27:34 +00:00
Erick Friis	51fd70be63	infra: 0.2 release checkout ref for release note (#26604 )	2024-09-17 18:48:20 -07:00
Erick Friis	7d2753fbd6	docs: v0.2 canonical (#26514 )	2024-09-16 12:58:29 -07:00
Erick Friis	cfd11b2c34	docs: v0.2 deprecation warning (#26509 )	2024-09-15 19:33:16 -07:00
Erick Friis	8b7843b343	docs: v0.2 link to latest in dropdown (#26504 )	2024-09-15 18:57:35 +00:00
Bagatur	ffefaa6490	docs: point to v2 api ref (#26485 )	2024-09-14 03:38:54 +00:00
Erick Friis	8ecef68b10	robocorp: release 0.0.10.post1, point to v0.2 branch (#26473 )	2024-09-13 22:57:40 +00:00
Erick Friis	13a6847478	infra: codespell all prs, not by branch [v0.2] (#26475 )	2024-09-13 15:56:07 -07:00
Erick Friis	064b891454	infra: v0.2 docs from v0.2 branch (#26449 )	2024-09-13 14:03:57 -07:00
Bagatur	d9813bdbbc	openai[patch]: Release 0.1.25 (#26439 )	2024-09-13 12:00:01 -07:00
liuhetian	7fc9e99e21	openai[patch]: get output_type when using with_structured_output (#26307 ) - This allows pydantic to correctly resolve annotations necessary when using openai new param `json_schema` Resolves issue: #26250 --------- Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	2024-09-13 11:42:01 -07:00
Bagatur	0f2b32ffa9	core[patch]: Release 0.2.40 (#26435 )	2024-09-13 09:57:09 -07:00
Bagatur	e32adad17a	community[patch]: Release 0.2.17 (#26432 )	2024-09-13 09:56:39 -07:00
langchain-infra	8a02fd9c01	core: add additional import mappings to loads (#26406 ) Support using additional import mapping. This allows users to override old mappings/add new imports to the loads function. - [x ] Add tests and docs: If you're adding a new integration, please include 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. It lives in `docs/docs/integrations` directory. - [ x] Lint and test: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. See contribution guidelines for more: https://python.langchain.com/docs/contributing/	2024-09-13 09:39:58 -07:00
Erick Friis	1d98937e8d	partners/openai: release 0.1.24 (#26417 )	2024-09-12 21:54:13 -07:00
Harrison Chase	28ad244e77	community, openai: support nested dicts (#26414 ) needed for thinking tokens --------- Co-authored-by: Erick Friis <erick@langchain.dev>	2024-09-12 21:47:47 -07:00
Erick Friis	c0dd293f10	partners/groq: release 0.1.10 (#26393 )	2024-09-12 17:41:11 +00:00
Erick Friis	54c85087e2	groq: add back streaming tool calls (#26391 ) api no longer throws an error https://console.groq.com/docs/tool-use#streaming	2024-09-12 10:29:45 -07:00
jessicaou	396c0aee4d	docs: Adding LC Academy links (#26164 ) Thank you for contributing to LangChain! - [ ] PR title: "package: description" - Where "package" is whichever of langchain, community, core, experimental, etc. is being modified. Use "docs: ..." for purely docs changes, "templates: ..." for template changes, "infra: ..." for CI changes. - Example: "community: add foobar LLM" - [ ] PR message: *Delete this entire checklist* and replace with - Description: a description of the change - Issue: the issue # it fixes, if applicable - Dependencies: any dependencies required for this change - Twitter handle: if your PR gets announced, and you'd like a mention, we'll gladly shout you out! - [ ] Add tests and docs: If you're adding a new integration, please include 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. It lives in `docs/docs/integrations` directory. - [ ] Lint and test: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. See contribution guidelines for more: https://python.langchain.com/docs/contributing/ Additional guidelines: - Make sure optional dependencies are imported within a function. - Please do not add dependencies to pyproject.toml files (even optional ones) unless they are required for unit tests. - Most PRs should not touch more than one package. - Changes should be backwards compatible. - If you are adding something to community, do not re-import it in langchain. If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17. --------- Co-authored-by: Jess Ou <jessou@jesss-mbp.local.meter> Co-authored-by: Erick Friis <erick@langchain.dev>	2024-09-11 23:37:17 +00:00
Bagatur	feb351737c	core[patch]: fix empty OpenAI tools when strict=True (#26287 ) Fix #26232 --------- Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>	2024-09-11 16:06:03 -07:00
William FH	d87feb1b04	[Docs] Correct the admonition explaining min langchain-anthropic version in doc (#26359 ) 0.1.15 instead of just 0.1.5	2024-09-11 23:03:42 +00:00
ccurme	398718e1cb	core[patch]: fix regression in convert_to_openai_tool with instances of Tool (#26327 ) ```python from langchain_core.tools import Tool from langchain_core.utils.function_calling import convert_to_openai_tool def my_function(x: int) -> int: return x + 2 tool = Tool( name="tool_name", func=my_function, description="test description", ) convert_to_openai_tool(tool) ``` Current: ``` {'type': 'function', 'function': {'name': 'tool_name', 'description': 'test description', 'parameters': {'type': 'object', 'properties': {'args': {'type': 'array', 'items': {}}, 'config': {'type': 'object', 'properties': {'tags': {'type': 'array', 'items': {'type': 'string'}}, 'metadata': {'type': 'object'}, 'callbacks': {'anyOf': [{'type': 'array', 'items': {}}, {}]}, 'run_name': {'type': 'string'}, 'max_concurrency': {'type': 'integer'}, 'recursion_limit': {'type': 'integer'}, 'configurable': {'type': 'object'}, 'run_id': {'type': 'string', 'format': 'uuid'}}}, 'kwargs': {'type': 'object'}}, 'required': ['config']}}} ``` Here: ``` {'type': 'function', 'function': {'name': 'tool_name', 'description': 'test description', 'parameters': {'properties': {'__arg1': {'title': '__arg1', 'type': 'string'}}, 'required': ['__arg1'], 'type': 'object'}}} ```	2024-09-11 15:51:10 -04:00
이규민	7feae62ad7	core[patch]: Support non ASCII characters in tool output if user doesn't output string (#26319 ) ### simple modify core: add supporting non english character target issue is #26315 same issue on langgraph - https://github.com/langchain-ai/langgraph/issues/1504	2024-09-11 15:21:00 +00:00