update test in community

Generally, this PR is CI performance focused + aims to clean up some
dependencies at the same time.

1. Unpins upper bounds for `numpy` in all `pyproject.toml` files where
`numpy` is specified
2. Requires `numpy >= 2.1.0` for Python 3.13 and `numpy > v1.26.0` for
Python 3.12, plus a `numpy` min version bump for `chroma`
3. Speeds up CI by minutes - linting on Python 3.13, installing `numpy <
2.1.0` was taking [~3
minutes](https://github.com/langchain-ai/langchain/actions/runs/14316342925/job/40123305868?pr=30713),
now the entire env setup takes a few seconds
4. Deleted the `numpy` test dependency from partners where that was not
used, specifically `huggingface`, `voyageai`, `xai`, and `nomic`.

It's a bit unfortunate that `langchain-community` depends on `numpy`, we
might want to try to fix that in the future...

Closes https://github.com/langchain-ai/langchain/issues/26026
Fixes https://github.com/langchain-ai/langchain/issues/30555

.github/CODEOWNERS

@@ -1,2 +1,2 @@
-/.github/   @efriis @baskaryan @ccurme
-/libs/packages.yml   @efriis
+/.github/   @baskaryan @ccurme
+/libs/packages.yml   @ccurme

.github/ISSUE_TEMPLATE/bug-report.yml

@@ -29,14 +29,14 @@ body:
       options:
         - label: I added a very descriptive title to this issue.
           required: true
-        - label: I searched the LangChain documentation with the integrated search.
-          required: true
         - label: I used the GitHub search to find a similar question and didn't find it.
           required: true
         - label: I am sure that this is a bug in LangChain rather than my code.
           required: true
         - label: The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package).
           required: true
+        - label: I posted a self-contained, minimal, reproducible example. A maintainer can copy it and run it AS IS.
+          required: true
   - type: textarea
     id: reproduction
     validations:

.github/PULL_REQUEST_TEMPLATE.md

@@ -26,4 +26,4 @@ Additional guidelines:
 - 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.
+If no one reviews your PR within a few days, please @-mention one of baskaryan, eyurtsev, ccurme, vbarda, hwchase17.

.github/workflows/_integration_test.yml

@@ -6,6 +6,7 @@ on:
       working-directory:
         required: true
         type: string
+        description: "From which folder this pipeline executes"
       python-version:
         required: true
         type: string
@@ -75,6 +76,7 @@ jobs:
           COHERE_API_KEY: ${{ secrets.COHERE_API_KEY }}
           UPSTAGE_API_KEY: ${{ secrets.UPSTAGE_API_KEY }}
           XAI_API_KEY: ${{ secrets.XAI_API_KEY }}
+          PPLX_API_KEY: ${{ secrets.PPLX_API_KEY }}
         run: |
           make integration_tests
 

.github/workflows/_release.yml

@@ -12,6 +12,7 @@ on:
       working-directory:
         required: true
         type: string
+        description: "From which folder this pipeline executes"
         default: 'libs/langchain'
       dangerous-nonmaster-release:
         required: false
@@ -100,15 +101,32 @@ jobs:
           PKG_NAME: ${{ needs.build.outputs.pkg-name }}
           VERSION: ${{ needs.build.outputs.version }}
         run: |
-          PREV_TAG="$PKG_NAME==${VERSION%.*}.$(( ${VERSION##*.} - 1 ))"; [[ "${VERSION##*.}" -eq 0 ]] && PREV_TAG=""
+          # Handle regular versions and pre-release versions differently
+          if [[ "$VERSION" == *"-"* ]]; then
+            # This is a pre-release version (contains a hyphen)
+            # Extract the base version without the pre-release suffix
+            BASE_VERSION=${VERSION%%-*}
+            # Look for the latest release of the same base version
+            REGEX="^$PKG_NAME==$BASE_VERSION\$"
+            PREV_TAG=$(git tag --sort=-creatordate | (grep -P "$REGEX" || true) | head -1)
+            
+            # If no exact base version match, look for the latest release of any kind
+            if [ -z "$PREV_TAG" ]; then
+              REGEX="^$PKG_NAME==\\d+\\.\\d+\\.\\d+\$"
+              PREV_TAG=$(git tag --sort=-creatordate | (grep -P "$REGEX" || true) | head -1)
+            fi
+          else
+            # Regular version handling
+            PREV_TAG="$PKG_NAME==${VERSION%.*}.$(( ${VERSION##*.} - 1 ))"; [[ "${VERSION##*.}" -eq 0 ]] && PREV_TAG=""
 
-          # backup case if releasing e.g. 0.3.0, looks up last release
-          # note if last release (chronologically) was e.g. 0.1.47 it will get 
-          # that instead of the last 0.2 release
-          if [ -z "$PREV_TAG" ]; then
-            REGEX="^$PKG_NAME==\\d+\\.\\d+\\.\\d+\$"
-            echo $REGEX
-            PREV_TAG=$(git tag --sort=-creatordate | (grep -P $REGEX || true) | head -1)
+            # backup case if releasing e.g. 0.3.0, looks up last release
+            # note if last release (chronologically) was e.g. 0.1.47 it will get 
+            # that instead of the last 0.2 release
+            if [ -z "$PREV_TAG" ]; then
+              REGEX="^$PKG_NAME==\\d+\\.\\d+\\.\\d+\$"
+              echo $REGEX
+              PREV_TAG=$(git tag --sort=-creatordate | (grep -P $REGEX || true) | head -1)
+            fi
           fi
 
           # if PREV_TAG is empty, let it be empty
@@ -309,15 +327,93 @@ jobs:
           FIREWORKS_API_KEY: ${{ secrets.FIREWORKS_API_KEY }}
           XAI_API_KEY: ${{ secrets.XAI_API_KEY }}
           DEEPSEEK_API_KEY: ${{ secrets.DEEPSEEK_API_KEY }}
+          PPLX_API_KEY: ${{ secrets.PPLX_API_KEY }}
         run: make integration_tests
         working-directory: ${{ inputs.working-directory }}
 
+  # Test select published packages against new core
+  test-prior-published-packages-against-new-core:
+    needs:
+      - build
+      - release-notes
+      - test-pypi-publish
+      - pre-release-checks
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        partner: [openai, anthropic]
+      fail-fast: false  # Continue testing other partners if one fails
+    env:
+      ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
+      OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+      AZURE_OPENAI_API_VERSION: ${{ secrets.AZURE_OPENAI_API_VERSION }}
+      AZURE_OPENAI_API_BASE: ${{ secrets.AZURE_OPENAI_API_BASE }}
+      AZURE_OPENAI_API_KEY: ${{ secrets.AZURE_OPENAI_API_KEY }}
+      AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_CHAT_DEPLOYMENT_NAME }}
+      AZURE_OPENAI_LEGACY_CHAT_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_LEGACY_CHAT_DEPLOYMENT_NAME }}
+      AZURE_OPENAI_LLM_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_LLM_DEPLOYMENT_NAME }}
+      AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME }}
+    steps:
+      - uses: actions/checkout@v4
+
+      # We implement this conditional as Github Actions does not have good support
+      # for conditionally needing steps. https://github.com/actions/runner/issues/491
+      - name: Check if libs/core
+        run: |
+          if [ "${{ startsWith(inputs.working-directory, 'libs/core') }}" != "true" ]; then
+            echo "Not in libs/core. Exiting successfully."
+            exit 0
+          fi
+
+      - name: Set up Python + uv
+        if: startsWith(inputs.working-directory, 'libs/core')
+        uses: "./.github/actions/uv_setup"
+        with:
+          python-version: ${{ env.PYTHON_VERSION }}
+
+      - uses: actions/download-artifact@v4
+        if: startsWith(inputs.working-directory, 'libs/core')
+        with:
+          name: dist
+          path: ${{ inputs.working-directory }}/dist/
+
+      - name: Test against ${{ matrix.partner }}
+        if: startsWith(inputs.working-directory, 'libs/core')
+        run: |
+          # Identify latest tag
+          LATEST_PACKAGE_TAG="$(
+            git ls-remote --tags origin "langchain-${{ matrix.partner }}*" \
+            | awk '{print $2}' \
+            | sed 's|refs/tags/||' \
+            | sort -Vr \
+            | head -n 1
+          )"
+          echo "Latest package tag: $LATEST_PACKAGE_TAG"
+
+          # Shallow-fetch just that single tag
+          git fetch --depth=1 origin tag "$LATEST_PACKAGE_TAG"
+
+          # Checkout the latest package files
+          rm -rf $GITHUB_WORKSPACE/libs/partners/${{ matrix.partner }}/*
+          cd $GITHUB_WORKSPACE/libs/partners/${{ matrix.partner }}
+          git checkout "$LATEST_PACKAGE_TAG" -- .
+
+          # Print as a sanity check
+          echo "Version number from pyproject.toml: "
+          cat pyproject.toml | grep "version = "
+
+          # Run tests
+          uv sync --group test --group test_integration
+          uv pip install ../../core/dist/*.whl
+          make integration_tests
+
   publish:
     needs:
       - build
       - release-notes
       - test-pypi-publish
       - pre-release-checks
+      - test-prior-published-packages-against-new-core
     runs-on: ubuntu-latest
     permissions:
       # This permission is used for trusted publishing:

.github/workflows/check_diffs.yml

@@ -1,4 +1,3 @@
----
 name: CI
 
 on:

.github/workflows/check_new_docs.yml

@@ -1,4 +1,3 @@
----
 name: Integration docs lint
 
 on:

.github/workflows/codespell.yml

@@ -1,4 +1,3 @@
----
 name: CI / cd . / make spell_check
 
 on:

.github/workflows/people.yml

@@ -6,11 +6,6 @@ on:
   push:
     branches: [jacob/people]
   workflow_dispatch:
-    inputs:
-      debug_enabled:
-        description: 'Run the build with tmate debugging enabled (https://github.com/marketplace/actions/debugging-with-tmate)'
-        required: false
-        default: 'false'
 
 jobs:
   langchain-people:
@@ -26,12 +21,6 @@ jobs:
       # Ref: https://github.com/actions/runner/issues/2033
       - name: Fix git safe.directory in container
         run: mkdir -p /home/runner/work/_temp/_github_home && printf "[safe]\n\tdirectory = /github/workspace" > /home/runner/work/_temp/_github_home/.gitconfig
-      # Allow debugging with tmate
-      - name: Setup tmate session
-        uses: mxschmitt/action-tmate@v3
-        if: ${{ github.event_name == 'workflow_dispatch' && github.event.inputs.debug_enabled == 'true' }}
-        with:
-          limit-access-to-actor: true
       - uses: ./.github/actions/people
         with:
           token: ${{ secrets.LANGCHAIN_PEOPLE_GITHUB_TOKEN }}

.github/workflows/scheduled_test.yml

@@ -145,6 +145,7 @@ jobs:
           GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }}
           GOOGLE_SEARCH_API_KEY: ${{ secrets.GOOGLE_SEARCH_API_KEY }}
           GOOGLE_CSE_ID: ${{ secrets.GOOGLE_CSE_ID }}
+          PPLX_API_KEY: ${{ secrets.PPLX_API_KEY }}
         run: |
           cd langchain/${{ matrix.working-directory }}
           make integration_tests

.readthedocs.yaml

@@ -1,12 +1,7 @@
 # Read the Docs configuration file
 # See https://docs.readthedocs.io/en/stable/config-file/v2.html for details
-
-# Required
 version: 2
 
-formats:
-  - pdf
-
 # Set the version of Python and other tools you might need
 build:
   os: ubuntu-22.04
@@ -15,15 +10,16 @@ build:
   commands:
     - mkdir -p $READTHEDOCS_OUTPUT
     - cp -r api_reference_build/* $READTHEDOCS_OUTPUT
+
 # Build documentation in the docs/ directory with Sphinx
 sphinx:
    configuration: docs/api_reference/conf.py
 
 # If using Sphinx, optionally build your docs in additional formats such as PDF
-# formats:
-#    - pdf
+formats:
+  - pdf
 
 # Optionally declare the Python requirements required to build your docs
 python:
    install:
-   - requirements: docs/api_reference/requirements.txt
+     - requirements: docs/api_reference/requirements.txt

Makefile

@@ -2,7 +2,6 @@
 
 .EXPORT_ALL_VARIABLES:
 UV_FROZEN = true
-UV_NO_SYNC = true
 
 ## help: Show this help info.
 help: Makefile

README.md

@@ -1,6 +1,12 @@
-# 🦜️🔗 LangChain
+<picture>
+  <source media="(prefers-color-scheme: light)" srcset="docs/static/img/logo-dark.svg">
+  <source media="(prefers-color-scheme: dark)" srcset="docs/static/img/logo-light.svg">
+  <img alt="LangChain Logo" src="docs/static/img/logo-dark.svg" width="80%">
+</picture>
 
-⚡ Build context-aware reasoning applications ⚡
+<div>
+<br>
+</div>
 
 [![Release Notes](https://img.shields.io/github/release/langchain-ai/langchain?style=flat-square)](https://github.com/langchain-ai/langchain/releases)
 [![CI](https://github.com/langchain-ai/langchain/actions/workflows/check_diffs.yml/badge.svg)](https://github.com/langchain-ai/langchain/actions/workflows/check_diffs.yml)
@@ -9,134 +15,68 @@
 [![GitHub star chart](https://img.shields.io/github/stars/langchain-ai/langchain?style=flat-square)](https://star-history.com/#langchain-ai/langchain)
 [![Open Issues](https://img.shields.io/github/issues-raw/langchain-ai/langchain?style=flat-square)](https://github.com/langchain-ai/langchain/issues)
 [![Open in Dev Containers](https://img.shields.io/static/v1?label=Dev%20Containers&message=Open&color=blue&logo=visualstudiocode&style=flat-square)](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/langchain-ai/langchain)
-[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/langchain-ai/langchain)
+[<img src="https://github.com/codespaces/badge.svg" title="Open in Github Codespace" width="150" height="20">](https://codespaces.new/langchain-ai/langchain)
 [![Twitter](https://img.shields.io/twitter/url/https/twitter.com/langchainai.svg?style=social&label=Follow%20%40LangChainAI)](https://twitter.com/langchainai)
 
-Looking for the JS/TS library? Check out [LangChain.js](https://github.com/langchain-ai/langchainjs).
+> [!NOTE]
+> Looking for the JS/TS library? Check out [LangChain.js](https://github.com/langchain-ai/langchainjs).
 
-To help you ship LangChain apps to production faster, check out [LangSmith](https://smith.langchain.com).
-[LangSmith](https://smith.langchain.com) is a unified developer platform for building, testing, and monitoring LLM applications.
-Fill out [this form](https://www.langchain.com/contact-sales) to speak with our sales team.
-
-## Quick Install
-
-With pip:
+LangChain is a framework for building LLM-powered applications. It helps you chain
+together interoperable components and third-party integrations to simplify AI
+application development —  all while future-proofing decisions as the underlying
+technology evolves.
 
 ```bash
-pip install langchain
+pip install -U langchain
 ```
 
-With conda:
+To learn more about LangChain, check out
+[the docs](https://python.langchain.com/docs/introduction/). If you’re looking for more
+advanced customization or agent orchestration, check out
+[LangGraph](https://langchain-ai.github.io/langgraph/), our framework for building
+controllable agent workflows.
 
-```bash
-conda install langchain -c conda-forge
-```
+## Why use LangChain?
 
-## 🤔 What is LangChain?
+LangChain helps developers build applications powered by LLMs through a standard
+interface for models, embeddings, vector stores, and more. 
 
-**LangChain** is a framework for developing applications powered by large language models (LLMs).
+Use LangChain for:
+- **Real-time data augmentation**. Easily connect LLMs to diverse data sources and
+external / internal systems, drawing from LangChain’s vast library of integrations with
+model providers, tools, vector stores, retrievers, and more.
+- **Model interoperability**. Swap models in and out as your engineering team
+experiments to find the best choice for your application’s needs. As the industry
+frontier evolves, adapt quickly — LangChain’s abstractions keep you moving without
+losing momentum.
 
-For these applications, LangChain simplifies the entire application lifecycle:
+## LangChain’s ecosystem
+While the LangChain framework can be used standalone, it also integrates seamlessly
+with any LangChain product, giving developers a full suite of tools when building LLM
+applications. 
 
+To improve your LLM application development, pair LangChain with:
 
-- **Open-source libraries**: Build your applications using LangChain's open-source
-[components](https://python.langchain.com/docs/concepts/) and
-[third-party integrations](https://python.langchain.com/docs/integrations/providers/).
-  Use [LangGraph](https://langchain-ai.github.io/langgraph/) to build stateful agents with first-class streaming and human-in-the-loop support.
-- **Productionization**: Inspect, monitor, and evaluate your apps with [LangSmith](https://docs.smith.langchain.com/) so that you can constantly optimize and deploy with confidence.
-- **Deployment**: Turn your LangGraph applications into production-ready APIs and Assistants with [LangGraph Platform](https://langchain-ai.github.io/langgraph/cloud/).
+- [LangSmith](http://www.langchain.com/langsmith) - Helpful for agent evals and
+observability. Debug poor-performing LLM app runs, evaluate agent trajectories, gain
+visibility in production, and improve performance over time.
+- [LangGraph](https://langchain-ai.github.io/langgraph/) - Build agents that can
+reliably handle complex tasks with LangGraph, our low-level agent orchestration
+framework. LangGraph offers customizable architecture, long-term memory, and
+human-in-the-loop workflows — and is trusted in production by companies like LinkedIn,
+Uber, Klarna, and GitLab.
+- [LangGraph Platform](https://langchain-ai.github.io/langgraph/concepts/#langgraph-platform) - Deploy
+and scale agents effortlessly with a purpose-built deployment platform for long
+running, stateful workflows. Discover, reuse, configure, and share agents across
+teams — and iterate quickly with visual prototyping in
+[LangGraph Studio](https://langchain-ai.github.io/langgraph/concepts/langgraph_studio/).
 
-### Open-source libraries
-
-- **`langchain-core`**: Base abstractions.
-- **Integration packages** (e.g. **`langchain-openai`**, **`langchain-anthropic`**, etc.): Important integrations have been split into lightweight packages that are co-maintained by the LangChain team and the integration developers.
-- **`langchain`**: Chains, agents, and retrieval strategies that make up an application's cognitive architecture.
-- **`langchain-community`**: Third-party integrations that are community maintained.
-- **[LangGraph](https://langchain-ai.github.io/langgraph)**: LangGraph powers production-grade agents, trusted by Linkedin, Uber, Klarna, GitLab, and many more. Build 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:
-
-- **[LangSmith](https://docs.smith.langchain.com/)**: A developer platform that lets you debug, test, evaluate, and monitor chains built on any LLM framework and seamlessly integrates with LangChain.
-
-### Deployment:
-
-- **[LangGraph Platform](https://langchain-ai.github.io/langgraph/cloud/)**: Turn your LangGraph applications into production-ready APIs and Assistants.
-
-![Diagram outlining the hierarchical organization of the LangChain framework, displaying the interconnected parts across multiple layers.](docs/static/svg/langchain_stack_112024.svg#gh-light-mode-only "LangChain Architecture Overview")
-![Diagram outlining the hierarchical organization of the LangChain framework, displaying the interconnected parts across multiple layers.](docs/static/svg/langchain_stack_112024_dark.svg#gh-dark-mode-only "LangChain Architecture Overview")
-
-## 🧱 What can you build with LangChain?
-
-**❓ Question answering with RAG**
-
-- [Documentation](https://python.langchain.com/docs/tutorials/rag/)
-- End-to-end Example: [Chat LangChain](https://chat.langchain.com) and [repo](https://github.com/langchain-ai/chat-langchain)
-
-**🧱 Extracting structured output**
-
-- [Documentation](https://python.langchain.com/docs/tutorials/extraction/)
-- End-to-end Example: [LangChain Extract](https://github.com/langchain-ai/langchain-extract/)
-
-**🤖 Chatbots**
-
-- [Documentation](https://python.langchain.com/docs/tutorials/chatbot/)
-- End-to-end Example: [Web LangChain (web researcher chatbot)](https://weblangchain.vercel.app) and [repo](https://github.com/langchain-ai/weblangchain)
-
-And much more! Head to the [Tutorials](https://python.langchain.com/docs/tutorials/) section of the docs for more.
-
-## 🚀 How does LangChain help?
-
-The main value props of the LangChain libraries are:
-
-1. **Components**: composable building blocks, tools and integrations for working with language models. Components are modular and easy-to-use, whether you are using the rest of the LangChain framework or not.
-2. **Easy orchestration with LangGraph**: [LangGraph](https://langchain-ai.github.io/langgraph/),
-built on top of `langchain-core`, has built-in support for [messages](https://python.langchain.com/docs/concepts/messages/), [tools](https://python.langchain.com/docs/concepts/tools/),
-and other LangChain abstractions. This makes it easy to combine components into
-production-ready applications with persistence, streaming, and other key features.
-Check out the LangChain [tutorials page](https://python.langchain.com/docs/tutorials/#orchestration) for examples.
-
-## Components
-
-Components fall into the following **modules**:
-
-**📃 Model I/O**
-
-This includes [prompt management](https://python.langchain.com/docs/concepts/prompt_templates/)
-and a generic interface for [chat models](https://python.langchain.com/docs/concepts/chat_models/), including a consistent interface for [tool-calling](https://python.langchain.com/docs/concepts/tool_calling/) and [structured output](https://python.langchain.com/docs/concepts/structured_outputs/) across model providers.
-
-**📚 Retrieval**
-
-Retrieval Augmented Generation involves [loading data](https://python.langchain.com/docs/concepts/document_loaders/) from a variety of sources, [preparing it](https://python.langchain.com/docs/concepts/text_splitters/), then [searching over (a.k.a. retrieving from)](https://python.langchain.com/docs/concepts/retrievers/) it for use in the generation step.
-
-**🤖 Agents**
-
-Agents allow an LLM autonomy over how a task is accomplished. Agents make decisions about which Actions to take, then take that Action, observe the result, and repeat until the task is complete. [LangGraph](https://langchain-ai.github.io/langgraph/) makes it easy to use
-LangChain components to build both [custom](https://langchain-ai.github.io/langgraph/tutorials/)
-and [built-in](https://langchain-ai.github.io/langgraph/how-tos/create-react-agent/)
-LLM agents.
-
-## 📖 Documentation
-
-Please see [here](https://python.langchain.com) for full documentation, which includes:
-
-- [Introduction](https://python.langchain.com/docs/introduction/): Overview of the framework and the structure of the docs.
-- [Tutorials](https://python.langchain.com/docs/tutorials/): If you're looking to build something specific or are more of a hands-on learner, check out our tutorials. This is the best place to get started.
-- [How-to guides](https://python.langchain.com/docs/how_to/): Answers to “How do I….?” type questions. These guides are goal-oriented and concrete; they're meant to help you complete a specific task.
-- [Conceptual guide](https://python.langchain.com/docs/concepts/): Conceptual explanations of the key parts of the framework.
-- [API Reference](https://python.langchain.com/api_reference/): Thorough documentation of every class and method.
-
-## 🌐 Ecosystem
-
-- [🦜🛠️ LangSmith](https://docs.smith.langchain.com/): Trace and evaluate your language model applications and intelligent agents to help you move from prototype to production.
-- [🦜🕸️ LangGraph](https://langchain-ai.github.io/langgraph/): Create stateful, multi-actor applications with LLMs. Integrates smoothly with LangChain, but can be used without it.
-- [🦜🕸️ LangGraph Platform](https://langchain-ai.github.io/langgraph/concepts/#langgraph-platform): Deploy LLM applications built with LangGraph into production.
-
-## 💁 Contributing
-
-As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.
-
-For detailed information on how to contribute, see [here](https://python.langchain.com/docs/contributing/).
-
-## 🌟 Contributors
-
-[![langchain contributors](https://contrib.rocks/image?repo=langchain-ai/langchain&max=2000)](https://github.com/langchain-ai/langchain/graphs/contributors)
+## Additional resources
+- [Tutorials](https://python.langchain.com/docs/tutorials/): Simple walkthroughs with
+guided examples on getting started with LangChain.
+- [How-to Guides](https://python.langchain.com/docs/how_to/): Quick, actionable code
+snippets for topics such as tool calling, RAG use cases, and more.
+- [Conceptual Guides](https://python.langchain.com/docs/concepts/): Explanations of key
+concepts behind the LangChain framework.
+- [API Reference](https://python.langchain.com/api_reference/): Detailed reference on
+navigating base packages and integrations for LangChain.

cookbook/Gemma_LangChain.ipynb

@@ -60,7 +60,7 @@
     "id": "CI8Elyc5gBQF"
    },
    "source": [
-    "Go to the VertexAI Model Garden on Google Cloud [console](https://pantheon.corp.google.com/vertex-ai/publishers/google/model-garden/335), and deploy the desired version of Gemma to VertexAI. It will take a few minutes, and after the endpoint it ready, you need to copy its number."
+    "Go to the VertexAI Model Garden on Google Cloud [console](https://pantheon.corp.google.com/vertex-ai/publishers/google/model-garden/335), and deploy the desired version of Gemma to VertexAI. It will take a few minutes, and after the endpoint is ready, you need to copy its number."
    ]
   },
   {

cookbook/img-to_img-search_CLIP_ChromaDB.ipynb

@@ -358,7 +358,7 @@
    "id": "6e5cd014-db86-4d6b-8399-25cae3da5570",
    "metadata": {},
    "source": [
-    "## Helper function to plot retrived similar images"
+    "## Helper function to plot retrieved similar images"
    ]
   },
   {

docs/api_reference/_static/css/custom.css

@@ -328,7 +328,7 @@ html[data-theme=dark] .MathJax_SVG * {
 }
 
 .bd-sidebar-primary {
-    width: 22%;  /* Adjust this value to your preference */
+    width: max-content;  /* Adjust this value to your preference */
     line-height: 1.4;
 }
 

docs/api_reference/templates/runnable_non_pydantic.rst

@@ -7,7 +7,7 @@
 
 .. NOTE:: {{objname}} implements the standard :py:class:`Runnable Interface <langchain_core.runnables.base.Runnable>`. 🏃
 
-    The :py:class:`Runnable Interface <langchain_core.runnables.base.Runnable>` has additional methods that are available on runnables, such as :py:meth:`with_types <langchain_core.runnables.base.Runnable.with_types>`, :py:meth:`with_retry <langchain_core.runnables.base.Runnable.with_retry>`, :py:meth:`assign <langchain_core.runnables.base.Runnable.assign>`, :py:meth:`bind <langchain_core.runnables.base.Runnable.bind>`, :py:meth:`get_graph <langchain_core.runnables.base.Runnable.get_graph>`, and more.
+    The :py:class:`Runnable Interface <langchain_core.runnables.base.Runnable>` has additional methods that are available on runnables, such as :py:meth:`with_config <langchain_core.runnables.base.Runnable.with_config>`, :py:meth:`with_types <langchain_core.runnables.base.Runnable.with_types>`, :py:meth:`with_retry <langchain_core.runnables.base.Runnable.with_retry>`, :py:meth:`assign <langchain_core.runnables.base.Runnable.assign>`, :py:meth:`bind <langchain_core.runnables.base.Runnable.bind>`, :py:meth:`get_graph <langchain_core.runnables.base.Runnable.get_graph>`, and more.
 
    {% block attributes %}
    {% if attributes %}

docs/api_reference/templates/runnable_pydantic.rst

@@ -19,6 +19,6 @@
 
     .. NOTE:: {{objname}} implements the standard :py:class:`Runnable Interface <langchain_core.runnables.base.Runnable>`. 🏃
 
-        The :py:class:`Runnable Interface <langchain_core.runnables.base.Runnable>` has additional methods that are available on runnables, such as :py:meth:`with_types <langchain_core.runnables.base.Runnable.with_types>`, :py:meth:`with_retry <langchain_core.runnables.base.Runnable.with_retry>`, :py:meth:`assign <langchain_core.runnables.base.Runnable.assign>`, :py:meth:`bind <langchain_core.runnables.base.Runnable.bind>`, :py:meth:`get_graph <langchain_core.runnables.base.Runnable.get_graph>`, and more.
+        The :py:class:`Runnable Interface <langchain_core.runnables.base.Runnable>` has additional methods that are available on runnables, such as :py:meth:`with_config <langchain_core.runnables.base.Runnable.with_config>`, :py:meth:`with_types <langchain_core.runnables.base.Runnable.with_types>`, :py:meth:`with_retry <langchain_core.runnables.base.Runnable.with_retry>`, :py:meth:`assign <langchain_core.runnables.base.Runnable.assign>`, :py:meth:`bind <langchain_core.runnables.base.Runnable.bind>`, :py:meth:`get_graph <langchain_core.runnables.base.Runnable.get_graph>`, and more.
 
 .. example_links:: {{ objname }}

docs/cassettes/chat_token_usage_tracking_05f22a1d-b021-490f-8840-f628a07459f2.msgpack.zlib

@@ -1 +0,0 @@
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docs/cassettes/chat_token_usage_tracking_07f0c872-6b6c-4fed-a129-9b5a858505be.msgpack.zlib

@@ -1 +1 @@
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docs/cassettes/chat_token_usage_tracking_0b1523d8-127e-4314-82fa-bd97aca37f9a.msgpack.zlib

@@ -1 +1 @@
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docs/cassettes/chat_token_usage_tracking_b39bf807-4125-4db4-bbf7-28a46afff6b4.msgpack.zlib

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docs/cassettes/configure_42647fb7.msgpack.zlib

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docs/cassettes/configure_48b45337.msgpack.zlib

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docs/cassettes/configure_4f83245c.msgpack.zlib

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docs/cassettes/configure_5cf53202.msgpack.zlib

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docs/cassettes/configure_61a67769-4a15-49e2-a945-1f4e7ef19d8c.msgpack.zlib

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docs/cassettes/configure_71248a9f.msgpack.zlib

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docs/cassettes/configure_7ba735f4.msgpack.zlib

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docs/cassettes/configure_927297a1.msgpack.zlib

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docs/cassettes/configure_97538c23.msgpack.zlib

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docs/cassettes/configure_9a9ea077.msgpack.zlib

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docs/cassettes/configure_9f6a7c6c.msgpack.zlib

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docs/cassettes/configure_c09fac15.msgpack.zlib

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docs/cassettes/configure_e4ee9fbc.msgpack.zlib

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docs/cassettes/configure_e75ae678.msgpack.zlib

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docs/cassettes/configure_f33f3cf2.msgpack.zlib

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docs/cassettes/qa_chat_history_how_to_e59541dd-405b-4032-847f-73becf6aefd0.msgpack.zlib

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docs/cassettes/qa_citations_daad793f-f08d-4b56-90e8-3f015a79a88e.msgpack.zlib

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docs/cassettes/qa_sources_def66576-2309-45b5-8699-f0287df8ca9e.msgpack.zlib

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docs/cassettes/qa_streaming_249e71c6-6cc5-40c0-b58f-7ec949c6a28f.msgpack.zlib

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docs/cassettes/rag_46f378c5-858c-488f-8aef-8b59a6280791.msgpack.zlib

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docs/cassettes/response_metadata_161f5898-9976-4a75-943d-03eda1a40a60.msgpack.zlib

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docs/cassettes/response_metadata_1e4ac668-4c6a-48ad-9a6f-7b291477b45d.msgpack.zlib

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