Merge branch 'master' into redirect-new

.devcontainer/devcontainer.json

@@ -26,7 +26,7 @@
   // Use 'forwardPorts' to make a list of ports inside the container available locally.
   // "forwardPorts": [],
   // Run commands after the container is created
-  "postCreateCommand": "cd libs/langchain_v1 && uv sync && echo 'LangChain (Python) dev environment ready!'",
+  "postCreateCommand": "uv sync && echo 'LangChain (Python) dev environment ready!'",
   // Configure tool-specific properties.
   "customizations": {
     "vscode": {
@@ -42,7 +42,7 @@
         "GitHub.copilot-chat"
       ],
       "settings": {
-        "python.defaultInterpreterPath": "libs/langchain_v1/.venv/bin/python",
+        "python.defaultInterpreterPath": ".venv/bin/python",
         "python.formatting.provider": "none",
         "[python]": {
           "editor.formatOnSave": true,

.dockerignore

@@ -1,34 +0,0 @@
-# Git
-.git
-.github
-
-# Python
-__pycache__
-*.pyc
-*.pyo
-.venv
-.mypy_cache
-.pytest_cache
-.ruff_cache
-*.egg-info
-.tox
-
-# IDE
-.idea
-.vscode
-
-# Worktree
-worktree
-
-# Test artifacts
-.coverage
-htmlcov
-coverage.xml
-
-# Build artifacts
-dist
-build
-
-# Misc
-*.log
-.DS_Store

.github/CODEOWNERS

@@ -1,3 +1,3 @@
-/.github/   @ccurme @eyurtsev @mdrxy
+/.github/   @baskaryan @ccurme @eyurtsev
 /libs/core/ @eyurtsev
 /libs/partners/ @ccurme @mdrxy

.github/CODE_OF_CONDUCT.md

@@ -0,0 +1,132 @@
+# Contributor Covenant Code of Conduct
+
+## Our Pledge
+
+We as members, contributors, and leaders pledge to make participation in our
+community a harassment-free experience for everyone, regardless of age, body
+size, visible or invisible disability, ethnicity, sex characteristics, gender
+identity and expression, level of experience, education, socio-economic status,
+nationality, personal appearance, race, caste, color, religion, or sexual
+identity and orientation.
+
+We pledge to act and interact in ways that contribute to an open, welcoming,
+diverse, inclusive, and healthy community.
+
+## Our Standards
+
+Examples of behavior that contributes to a positive environment for our
+community include:
+
+* Demonstrating empathy and kindness toward other people
+* Being respectful of differing opinions, viewpoints, and experiences
+* Giving and gracefully accepting constructive feedback
+* Accepting responsibility and apologizing to those affected by our mistakes,
+  and learning from the experience
+* Focusing on what is best not just for us as individuals, but for the overall
+  community
+
+Examples of unacceptable behavior include:
+
+* The use of sexualized language or imagery, and sexual attention or advances of
+  any kind
+* Trolling, insulting or derogatory comments, and personal or political attacks
+* Public or private harassment
+* Publishing others' private information, such as a physical or email address,
+  without their explicit permission
+* Other conduct which could reasonably be considered inappropriate in a
+  professional setting
+
+## Enforcement Responsibilities
+
+Community leaders are responsible for clarifying and enforcing our standards of
+acceptable behavior and will take appropriate and fair corrective action in
+response to any behavior that they deem inappropriate, threatening, offensive,
+or harmful.
+
+Community leaders have the right and responsibility to remove, edit, or reject
+comments, commits, code, wiki edits, issues, and other contributions that are
+not aligned to this Code of Conduct, and will communicate reasons for moderation
+decisions when appropriate.
+
+## Scope
+
+This Code of Conduct applies within all community spaces, and also applies when
+an individual is officially representing the community in public spaces.
+Examples of representing our community include using an official e-mail address,
+posting via an official social media account, or acting as an appointed
+representative at an online or offline event.
+
+## Enforcement
+
+Instances of abusive, harassing, or otherwise unacceptable behavior may be
+reported to the community leaders responsible for enforcement at
+conduct@langchain.dev.
+All complaints will be reviewed and investigated promptly and fairly.
+
+All community leaders are obligated to respect the privacy and security of the
+reporter of any incident.
+
+## Enforcement Guidelines
+
+Community leaders will follow these Community Impact Guidelines in determining
+the consequences for any action they deem in violation of this Code of Conduct:
+
+### 1. Correction
+
+**Community Impact**: Use of inappropriate language or other behavior deemed
+unprofessional or unwelcome in the community.
+
+**Consequence**: A private, written warning from community leaders, providing
+clarity around the nature of the violation and an explanation of why the
+behavior was inappropriate. A public apology may be requested.
+
+### 2. Warning
+
+**Community Impact**: A violation through a single incident or series of
+actions.
+
+**Consequence**: A warning with consequences for continued behavior. No
+interaction with the people involved, including unsolicited interaction with
+those enforcing the Code of Conduct, for a specified period of time. This
+includes avoiding interactions in community spaces as well as external channels
+like social media. Violating these terms may lead to a temporary or permanent
+ban.
+
+### 3. Temporary Ban
+
+**Community Impact**: A serious violation of community standards, including
+sustained inappropriate behavior.
+
+**Consequence**: A temporary ban from any sort of interaction or public
+communication with the community for a specified period of time. No public or
+private interaction with the people involved, including unsolicited interaction
+with those enforcing the Code of Conduct, is allowed during this period.
+Violating these terms may lead to a permanent ban.
+
+### 4. Permanent Ban
+
+**Community Impact**: Demonstrating a pattern of violation of community
+standards, including sustained inappropriate behavior, harassment of an
+individual, or aggression toward or disparagement of classes of individuals.
+
+**Consequence**: A permanent ban from any sort of public interaction within the
+community.
+
+## Attribution
+
+This Code of Conduct is adapted from the [Contributor Covenant][homepage],
+version 2.1, available at
+[https://www.contributor-covenant.org/version/2/1/code_of_conduct.html][v2.1].
+
+Community Impact Guidelines were inspired by
+[Mozilla's code of conduct enforcement ladder][Mozilla CoC].
+
+For answers to common questions about this code of conduct, see the FAQ at
+[https://www.contributor-covenant.org/faq][FAQ]. Translations are available at
+[https://www.contributor-covenant.org/translations][translations].
+
+[homepage]: https://www.contributor-covenant.org
+[v2.1]: https://www.contributor-covenant.org/version/2/1/code_of_conduct.html
+[Mozilla CoC]: https://github.com/mozilla/diversity
+[FAQ]: https://www.contributor-covenant.org/faq
+[translations]: https://www.contributor-covenant.org/translations

.github/CONTRIBUTING.md

@@ -0,0 +1,6 @@
+# Contributing to LangChain
+
+Hi there! Thank you for even being interested in contributing to LangChain.
+As an open-source project in a rapidly developing field, we are extremely open to contributions, whether they involve new features, improved infrastructure, better documentation, or bug fixes.
+
+To learn how to contribute to LangChain, please follow the [contribution guide here](https://docs.langchain.com/oss/python/contributing).

.github/ISSUE_TEMPLATE/bug-report.yml

@@ -1,5 +1,5 @@
 name: "\U0001F41B Bug Report"
-description: Report a bug in LangChain. To report a security issue, please instead use the security option (below). For questions, please use the LangChain forum (below).
+description: Report a bug in LangChain. To report a security issue, please instead use the security option below. For questions, please use the LangChain forum.
 labels: ["bug"]
 type: bug
 body:
@@ -8,15 +8,16 @@ body:
       value: |
         Thank you for taking the time to file a bug report.
 
-        For usage questions, feature requests and general design questions, please use the [LangChain Forum](https://forum.langchain.com/).
+        Use this to report BUGS in LangChain. For usage questions, feature requests and general design questions, please use the [LangChain Forum](https://forum.langchain.com/).
 
-        Check these before submitting to see if your issue has already been reported, fixed or if there's another way to solve your problem:
+        Relevant links to check before filing a bug report to see if your issue has already been reported, fixed or
+        if there's another way to solve your problem:
 
-        * [Documentation](https://docs.langchain.com/oss/python/langchain/overview),
-        * [API Reference Documentation](https://reference.langchain.com/python/),
+        * [LangChain Forum](https://forum.langchain.com/),
+        * [LangChain documentation with the integrated search](https://docs.langchain.com/oss/python/langchain/overview),
+        * [API Reference](https://reference.langchain.com/python/),
         * [LangChain ChatBot](https://chat.langchain.com/)
         * [GitHub search](https://github.com/langchain-ai/langchain),
-        * [LangChain Forum](https://forum.langchain.com/),
   - type: checkboxes
     id: checks
     attributes:
@@ -35,57 +36,16 @@ body:
           required: true
         - label: This is not related to the langchain-community package.
           required: true
+        - label: I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
+          required: true
         - label: I posted a self-contained, minimal, reproducible example. A maintainer can copy it and run it AS IS.
           required: true
-  - type: checkboxes
-    id: package
-    attributes:
-      label: Package (Required)
-      description: |
-        Which `langchain` package(s) is this bug related to? Select at least one.
-
-        Note that if the package you are reporting for is not listed here, it is not in this repository (e.g. `langchain-google-genai` is in [`langchain-ai/langchain-google`](https://github.com/langchain-ai/langchain-google/)).
-
-        Please report issues for other packages to their respective repositories.
-      options:
-        - label: langchain
-        - label: langchain-openai
-        - label: langchain-anthropic
-        - label: langchain-classic
-        - label: langchain-core
-        - label: langchain-model-profiles
-        - label: langchain-tests
-        - label: langchain-text-splitters
-        - label: langchain-chroma
-        - label: langchain-deepseek
-        - label: langchain-exa
-        - label: langchain-fireworks
-        - label: langchain-groq
-        - label: langchain-huggingface
-        - label: langchain-mistralai
-        - label: langchain-nomic
-        - label: langchain-ollama
-        - label: langchain-perplexity
-        - label: langchain-prompty
-        - label: langchain-qdrant
-        - label: langchain-xai
-        - label: Other / not sure / general
-  - type: textarea
-    id: related
-    validations:
-      required: false
-    attributes:
-      label: Related Issues / PRs
-      description: |
-        If this bug is related to any existing issues or pull requests, please link them here.
-      placeholder: |
-        * e.g. #123, #456
   - type: textarea
     id: reproduction
     validations:
       required: true
     attributes:
-      label: Reproduction Steps / Example Code (Python)
+      label: Example Code
       description: |
         Please add a self-contained, [minimal, reproducible, example](https://stackoverflow.com/help/minimal-reproducible-example) with your use case.
 
@@ -93,12 +53,15 @@ body:
 
         **Important!**
 
-        * Avoid screenshots, as they are hard to read and (more importantly) don't allow others to copy-and-paste your code.
-        * Reduce your code to the minimum required to reproduce the issue if possible.
+        * Avoid screenshots when possible, as they are hard to read and (more importantly) don't allow others to copy-and-paste your code.
+        * Reduce your code to the minimum required to reproduce the issue if possible. This makes it much easier for others to help you.
+        * Use code tags (e.g., ```python ... ```) to correctly [format your code](https://help.github.com/en/github/writing-on-github/creating-and-highlighting-code-blocks#syntax-highlighting).
+        * INCLUDE the language label (e.g. `python`) after the first three backticks to enable syntax highlighting. (e.g., ```python rather than ```).
 
-        (This will be automatically formatted into code, so no need for backticks.)
-      render: python
       placeholder: |
+        The following code:
+
+        ```python
         from langchain_core.runnables import RunnableLambda
 
         def bad_code(inputs) -> int:
@@ -106,14 +69,17 @@ body:
 
           chain = RunnableLambda(bad_code)
           chain.invoke('Hello!')
+        ```
   - type: textarea
+    id: error
+    validations:
+      required: false
     attributes:
       label: Error Message and Stack Trace (if applicable)
       description: |
-        If you are reporting an error, please copy and paste the full error message and
-        stack trace.
-        (This will be automatically formatted into code, so no need for backticks.)
-      render: shell
+        If you are reporting an error, please include the full error message and stack trace.
+      placeholder: |
+        Exception + full stack trace
   - type: textarea
     id: description
     attributes:
@@ -133,7 +99,9 @@ body:
     attributes:
       label: System Info
       description: |
-        Please share your system info with us.
+        Please share your system info with us. Do NOT skip this step and please don't trim
+        the output. Most users don't include enough information here and it makes it harder
+        for us to help you.
 
         Run the following command in your terminal and paste the output here:
 
@@ -145,6 +113,8 @@ body:
         from langchain_core import sys_info
         sys_info.print_sys_info()
         ```
+
+        alternatively, put the entire output of `pip freeze` here.
       placeholder: |
         python -m langchain_core.sys_info
     validations:

.github/ISSUE_TEMPLATE/config.yml

@@ -1,15 +1,9 @@
 blank_issues_enabled: false
 version: 2.1
 contact_links:
+  - name: 📚 Documentation
+    url: https://github.com/langchain-ai/docs/issues/new?template=langchain.yml
+    about: Report an issue related to the LangChain documentation
   - name: 💬 LangChain Forum
     url:  https://forum.langchain.com/
     about: General community discussions and support
-  - name: 📚 LangChain Documentation
-    url: https://docs.langchain.com/oss/python/langchain/overview
-    about: View the official LangChain documentation
-  - name: 📚 API Reference Documentation
-    url: https://reference.langchain.com/python/
-    about: View the official LangChain API reference documentation
-  - name: 📚 Documentation issue
-    url: https://github.com/langchain-ai/docs/issues/new?template=01-langchain.yml
-    about: Report an issue related to the LangChain documentation

.github/ISSUE_TEMPLATE/feature-request.yml

@@ -1,5 +1,5 @@
 name: "✨ Feature Request"
-description: Request a new feature or enhancement for LangChain. For questions, please use the LangChain forum (below).
+description: Request a new feature or enhancement for LangChain. For questions, please use the LangChain forum.
 labels: ["feature request"]
 type: feature
 body:
@@ -13,11 +13,11 @@ body:
         Relevant links to check before filing a feature request to see if your request has already been made or
         if there's another way to achieve what you want:
 
-        * [Documentation](https://docs.langchain.com/oss/python/langchain/overview),
-        * [API Reference Documentation](https://reference.langchain.com/python/),
+        * [LangChain Forum](https://forum.langchain.com/),
+        * [LangChain documentation with the integrated search](https://docs.langchain.com/oss/python/langchain/overview),
+        * [API Reference](https://reference.langchain.com/python/),
         * [LangChain ChatBot](https://chat.langchain.com/)
         * [GitHub search](https://github.com/langchain-ai/langchain),
-        * [LangChain Forum](https://forum.langchain.com/),
   - type: checkboxes
     id: checks
     attributes:
@@ -34,39 +34,6 @@ body:
           required: true
         - label: This is not related to the langchain-community package.
           required: true
-  - type: checkboxes
-    id: package
-    attributes:
-      label: Package (Required)
-      description: |
-        Which `langchain` package(s) is this request related to? Select at least one.
-
-        Note that if the package you are requesting for is not listed here, it is not in this repository (e.g. `langchain-google-genai` is in `langchain-ai/langchain`).
-
-        Please submit feature requests for other packages to their respective repositories.
-      options:
-        - label: langchain
-        - label: langchain-openai
-        - label: langchain-anthropic
-        - label: langchain-classic
-        - label: langchain-core
-        - label: langchain-model-profiles
-        - label: langchain-tests
-        - label: langchain-text-splitters
-        - label: langchain-chroma
-        - label: langchain-deepseek
-        - label: langchain-exa
-        - label: langchain-fireworks
-        - label: langchain-groq
-        - label: langchain-huggingface
-        - label: langchain-mistralai
-        - label: langchain-nomic
-        - label: langchain-ollama
-        - label: langchain-perplexity
-        - label: langchain-prompty
-        - label: langchain-qdrant
-        - label: langchain-xai
-        - label: Other / not sure / general
   - type: textarea
     id: feature-description
     validations:

.github/ISSUE_TEMPLATE/privileged.yml

@@ -18,32 +18,3 @@ body:
     attributes:
       label: Issue Content
       description: Add the content of the issue here.
-  - type: checkboxes
-    id: package
-    attributes:
-      label: Package (Required)
-      description: |
-        Please select package(s) that this issue is related to.
-      options:
-        - label: langchain
-        - label: langchain-openai
-        - label: langchain-anthropic
-        - label: langchain-classic
-        - label: langchain-core
-        - label: langchain-model-profiles
-        - label: langchain-tests
-        - label: langchain-text-splitters
-        - label: langchain-chroma
-        - label: langchain-deepseek
-        - label: langchain-exa
-        - label: langchain-fireworks
-        - label: langchain-groq
-        - label: langchain-huggingface
-        - label: langchain-mistralai
-        - label: langchain-nomic
-        - label: langchain-ollama
-        - label: langchain-perplexity
-        - label: langchain-prompty
-        - label: langchain-qdrant
-        - label: langchain-xai
-        - label: Other / not sure / general

.github/ISSUE_TEMPLATE/task.yml

@@ -25,13 +25,13 @@ body:
       label: Task Description
       description: |
         Provide a clear and detailed description of the task.
-
+        
         What needs to be done? Be specific about the scope and requirements.
       placeholder: |
         This task involves...
-
+        
         The goal is to...
-
+        
         Specific requirements:
         - ...
         - ...
@@ -43,7 +43,7 @@ body:
       label: Acceptance Criteria
       description: |
         Define the criteria that must be met for this task to be considered complete.
-
+        
         What are the specific deliverables or outcomes expected?
       placeholder: |
         This task will be complete when:
@@ -58,15 +58,15 @@ body:
       label: Context and Background
       description: |
         Provide any relevant context, background information, or links to related issues/PRs.
-
+        
         Why is this task needed? What problem does it solve?
       placeholder: |
         Background:
         - ...
-
+        
         Related issues/PRs:
         - #...
-
+        
         Additional context:
         - ...
     validations:
@@ -77,44 +77,15 @@ body:
       label: Dependencies
       description: |
         List any dependencies or blockers for this task.
-
+        
         Are there other tasks, issues, or external factors that need to be completed first?
       placeholder: |
         This task depends on:
         - [ ] Issue #...
         - [ ] PR #...
         - [ ] External dependency: ...
-
+        
         Blocked by:
         - ...
     validations:
       required: false
-  - type: checkboxes
-    id: package
-    attributes:
-      label: Package (Required)
-      description: |
-        Please select package(s) that this task is related to.
-      options:
-        - label: langchain
-        - label: langchain-openai
-        - label: langchain-anthropic
-        - label: langchain-classic
-        - label: langchain-core
-        - label: langchain-model-profiles
-        - label: langchain-tests
-        - label: langchain-text-splitters
-        - label: langchain-chroma
-        - label: langchain-deepseek
-        - label: langchain-exa
-        - label: langchain-fireworks
-        - label: langchain-groq
-        - label: langchain-huggingface
-        - label: langchain-mistralai
-        - label: langchain-nomic
-        - label: langchain-ollama
-        - label: langchain-perplexity
-        - label: langchain-prompty
-        - label: langchain-qdrant
-        - label: langchain-xai
-        - label: Other / not sure / general

.github/PULL_REQUEST_TEMPLATE.md

@@ -1,38 +1,28 @@
 (Replace this entire block of text)
 
-Read the full contributing guidelines: https://docs.langchain.com/oss/python/contributing/overview
-If you paste a large clearly AI generated description here your PR may be IGNORED or CLOSED!
-
-Thank you for contributing to LangChain! Follow these steps to have your pull request considered as ready for review.
-
-1. PR title: Should follow the format: TYPE(SCOPE): DESCRIPTION
+Thank you for contributing to LangChain! Follow these steps to mark your pull request as ready for review. **If any of these steps are not completed, your PR will not be considered for review.**
 
+- [ ] **PR title**: Follows the format: {TYPE}({SCOPE}): {DESCRIPTION}
   - Examples:
-    - fix(anthropic): resolve flag parsing error
     - feat(core): add multi-tenant support
-    - test(openai): update API usage tests
-  - Allowed TYPE and SCOPE values: https://github.com/langchain-ai/langchain/blob/master/.github/workflows/pr_lint.yml#L15-L33
+    - fix(cli): resolve flag parsing error
+    - docs(openai): update API usage examples
+  - Allowed `{TYPE}` values:
+    - feat, fix, docs, style, refactor, perf, test, build, ci, chore, revert, release
+  - Allowed `{SCOPE}` values (optional):
+    - core, cli, langchain, standard-tests, text-splitters, docs, anthropic, chroma, deepseek, exa, fireworks, groq, huggingface, mistralai, nomic, ollama, openai, perplexity, prompty, qdrant, xai, infra
+  - Once you've written the title, please delete this checklist item; do not include it in the PR.
 
-2. PR description:
+- [ ] **PR message**: ***Delete this entire checklist*** and replace with
+  - **Description:** a description of the change. Include a [closing keyword](https://docs.github.com/en/issues/tracking-your-work-with-issues/using-issues/linking-a-pull-request-to-an-issue#linking-a-pull-request-to-an-issue-using-a-keyword) if applicable to a relevant issue.
+  - **Issue:** the issue # it fixes, if applicable (e.g. Fixes #123)
+  - **Dependencies:** any dependencies required for this change
 
-  - Write 1-2 sentences summarizing the change.
-  - If this PR addresses a specific issue, please include "Fixes #ISSUE_NUMBER" in the description to automatically close the issue when the PR is merged.
-  - If there are any breaking changes, please clearly describe them.
-  - If this PR depends on another PR being merged first, please include "Depends on #PR_NUMBER" in the description.
-
-3. Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified.
-
-  - We will not consider a PR unless these three are passing in CI.
-
-4. How did you verify your code works?
+- [ ] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. **We will not consider a PR unless these three are passing in CI.** See [contribution guidelines](https://docs.langchain.com/oss/python/contributing) for more.
 
 Additional guidelines:
 
-  - We ask that if you use generative AI for your contribution, you include a disclaimer.
-  - PRs should not touch more than one package unless absolutely necessary.
-  - Do not update the `uv.lock` files or add dependencies to `pyproject.toml` files (even optional ones) unless you have explicit permission to do so by a maintainer.
-
-## Social handles (optional)
-<!-- If you'd like a shoutout on release, add your socials below -->
-Twitter: @
-LinkedIn: https://linkedin.com/in/
+- Most PRs should not touch more than one package.
+- Please do not add dependencies to `pyproject.toml` files (even optional ones) unless they are **required** for unit tests. Likewise, please do not update the `uv.lock` files unless you are adding a required dependency.
+- Changes should be backwards compatible.
+- Make sure optional dependencies are imported within a function.

.github/actions/poetry_setup/action.yml

@@ -0,0 +1,93 @@
+# An action for setting up poetry install with caching.
+# Using a custom action since the default action does not
+# take poetry install groups into account.
+# Action code from:
+# https://github.com/actions/setup-python/issues/505#issuecomment-1273013236
+name: poetry-install-with-caching
+description: Poetry install with support for caching of dependency groups.
+
+inputs:
+  python-version:
+    description: Python version, supporting MAJOR.MINOR only
+    required: true
+
+  poetry-version:
+    description: Poetry version
+    required: true
+
+  cache-key:
+    description: Cache key to use for manual handling of caching
+    required: true
+
+  working-directory:
+    description: Directory whose poetry.lock file should be cached
+    required: true
+
+runs:
+  using: composite
+  steps:
+    - uses: actions/setup-python@v5
+      name: Setup python ${{ inputs.python-version }}
+      id: setup-python
+      with:
+        python-version: ${{ inputs.python-version }}
+
+    - uses: actions/cache@v4
+      id: cache-bin-poetry
+      name: Cache Poetry binary - Python ${{ inputs.python-version }}
+      env:
+        SEGMENT_DOWNLOAD_TIMEOUT_MIN: "1"
+      with:
+        path: |
+          /opt/pipx/venvs/poetry
+        # This step caches the poetry installation, so make sure it's keyed on the poetry version as well.
+        key: bin-poetry-${{ runner.os }}-${{ runner.arch }}-py-${{ inputs.python-version }}-${{ inputs.poetry-version }}
+
+    - name: Refresh shell hashtable and fixup softlinks
+      if: steps.cache-bin-poetry.outputs.cache-hit == 'true'
+      shell: bash
+      env:
+        POETRY_VERSION: ${{ inputs.poetry-version }}
+        PYTHON_VERSION: ${{ inputs.python-version }}
+      run: |
+        set -eux
+
+        # Refresh the shell hashtable, to ensure correct `which` output.
+        hash -r
+
+        # `actions/cache@v3` doesn't always seem able to correctly unpack softlinks.
+        # Delete and recreate the softlinks pipx expects to have.
+        rm /opt/pipx/venvs/poetry/bin/python
+        cd /opt/pipx/venvs/poetry/bin
+        ln -s "$(which "python$PYTHON_VERSION")" python
+        chmod +x python
+        cd /opt/pipx_bin/
+        ln -s /opt/pipx/venvs/poetry/bin/poetry poetry
+        chmod +x poetry
+
+        # Ensure everything got set up correctly.
+        /opt/pipx/venvs/poetry/bin/python --version
+        /opt/pipx_bin/poetry --version
+
+    - name: Install poetry
+      if: steps.cache-bin-poetry.outputs.cache-hit != 'true'
+      shell: bash
+      env:
+        POETRY_VERSION: ${{ inputs.poetry-version }}
+        PYTHON_VERSION: ${{ inputs.python-version }}
+      # Install poetry using the python version installed by setup-python step.
+      run: pipx install "poetry==$POETRY_VERSION" --python '${{ steps.setup-python.outputs.python-path }}' --verbose
+
+    - name: Restore pip and poetry cached dependencies
+      uses: actions/cache@v4
+      env:
+        SEGMENT_DOWNLOAD_TIMEOUT_MIN: "4"
+        WORKDIR: ${{ inputs.working-directory == '' && '.' || inputs.working-directory }}
+      with:
+        path: |
+          ~/.cache/pip
+          ~/.cache/pypoetry/virtualenvs
+          ~/.cache/pypoetry/cache
+          ~/.cache/pypoetry/artifacts
+          ${{ env.WORKDIR }}/.venv
+        key: py-deps-${{ runner.os }}-${{ runner.arch }}-py-${{ inputs.python-version }}-poetry-${{ inputs.poetry-version }}-${{ inputs.cache-key }}-${{ hashFiles(format('{0}/**/poetry.lock', env.WORKDIR)) }}

.github/actions/uv_setup/action.yml

@@ -27,7 +27,7 @@ runs:
   using: composite
   steps:
     - name: Install uv and set the python version
-      uses: astral-sh/setup-uv@v7
+      uses: astral-sh/setup-uv@v6
       with:
         version: ${{ env.UV_VERSION }}
         python-version: ${{ inputs.python-version }}

.github/copilot-instructions.md

@@ -0,0 +1,330 @@
+# Global Development Guidelines for LangChain Projects
+
+## Core Development Principles
+
+### 1. Maintain Stable Public Interfaces ⚠️ CRITICAL
+
+**Always attempt to preserve function signatures, argument positions, and names for exported/public methods.**
+
+❌ **Bad - Breaking Change:**
+
+```python
+def get_user(id, verbose=False):  # Changed from `user_id`
+    pass
+```
+
+✅ **Good - Stable Interface:**
+
+```python
+def get_user(user_id: str, verbose: bool = False) -> User:
+    """Retrieve user by ID with optional verbose output."""
+    pass
+```
+
+**Before making ANY changes to public APIs:**
+
+- Check if the function/class is exported in `__init__.py`
+- Look for existing usage patterns in tests and examples
+- Use keyword-only arguments for new parameters: `*, new_param: str = "default"`
+- Mark experimental features clearly with docstring admonitions (using MkDocs Material, like `!!! warning`)
+
+🧠 *Ask yourself:* "Would this change break someone's code if they used it last week?"
+
+### 2. Code Quality Standards
+
+**All Python code MUST include type hints and return types.**
+
+❌ **Bad:**
+
+```python
+def p(u, d):
+    return [x for x in u if x not in d]
+```
+
+✅ **Good:**
+
+```python
+def filter_unknown_users(users: list[str], known_users: set[str]) -> list[str]:
+    """Filter out users that are not in the known users set.
+
+    Args:
+        users: List of user identifiers to filter.
+        known_users: Set of known/valid user identifiers.
+
+    Returns:
+        List of users that are not in the known_users set.
+    """
+    return [user for user in users if user not in known_users]
+```
+
+**Style Requirements:**
+
+- Use descriptive, **self-explanatory variable names**. Avoid overly short or cryptic identifiers.
+- Attempt to break up complex functions (>20 lines) into smaller, focused functions where it makes sense
+- Avoid unnecessary abstraction or premature optimization
+- Follow existing patterns in the codebase you're modifying
+
+### 3. Testing Requirements
+
+**Every new feature or bugfix MUST be covered by unit tests.**
+
+**Test Organization:**
+
+- Unit tests: `tests/unit_tests/` (no network calls allowed)
+- Integration tests: `tests/integration_tests/` (network calls permitted)
+- Use `pytest` as the testing framework
+
+**Test Quality Checklist:**
+
+- [ ] Tests fail when your new logic is broken
+- [ ] Happy path is covered
+- [ ] Edge cases and error conditions are tested
+- [ ] Use fixtures/mocks for external dependencies
+- [ ] Tests are deterministic (no flaky tests)
+
+Checklist questions:
+
+- [ ] Does the test suite fail if your new logic is broken?
+- [ ] Are all expected behaviors exercised (happy path, invalid input, etc)?
+- [ ] Do tests use fixtures or mocks where needed?
+
+```python
+def test_filter_unknown_users():
+    """Test filtering unknown users from a list."""
+    users = ["alice", "bob", "charlie"]
+    known_users = {"alice", "bob"}
+
+    result = filter_unknown_users(users, known_users)
+
+    assert result == ["charlie"]
+    assert len(result) == 1
+```
+
+### 4. Security and Risk Assessment
+
+**Security Checklist:**
+
+- No `eval()`, `exec()`, or `pickle` on user-controlled input
+- Proper exception handling (no bare `except:`) and use a `msg` variable for error messages
+- Remove unreachable/commented code before committing
+- Race conditions or resource leaks (file handles, sockets, threads).
+- Ensure proper resource cleanup (file handles, connections)
+
+❌ **Bad:**
+
+```python
+def load_config(path):
+    with open(path) as f:
+        return eval(f.read())  # ⚠️ Never eval config
+```
+
+✅ **Good:**
+
+```python
+import json
+
+def load_config(path: str) -> dict:
+    with open(path) as f:
+        return json.load(f)
+```
+
+### 5. Documentation Standards
+
+**Use Google-style docstrings with Args and Returns sections for all public functions.**
+
+❌ **Insufficient Documentation:**
+
+```python
+def send_email(to, msg):
+    """Send an email to a recipient."""
+```
+
+✅ **Complete Documentation:**
+
+```python
+def send_email(to: str, msg: str, *, priority: str = "normal") -> bool:
+    """
+    Send an email to a recipient with specified priority.
+
+    Args:
+        to: The email address of the recipient.
+        msg: The message body to send.
+        priority: Email priority level.
+
+    Returns:
+        True if email was sent successfully, False otherwise.
+
+    Raises:
+        InvalidEmailError: If the email address format is invalid.
+        SMTPConnectionError: If unable to connect to email server.
+    """
+```
+
+**Documentation Guidelines:**
+
+- Types go in function signatures, NOT in docstrings
+- Focus on "why" rather than "what" in descriptions
+- Document all parameters, return values, and exceptions
+- Keep descriptions concise but clear
+
+📌 *Tip:* Keep descriptions concise but clear. Only document return values if non-obvious.
+
+### 6. Architectural Improvements
+
+**When you encounter code that could be improved, suggest better designs:**
+
+❌ **Poor Design:**
+
+```python
+def process_data(data, db_conn, email_client, logger):
+    # Function doing too many things
+    validated = validate_data(data)
+    result = db_conn.save(validated)
+    email_client.send_notification(result)
+    logger.log(f"Processed {len(data)} items")
+    return result
+```
+
+✅ **Better Design:**
+
+```python
+@dataclass
+class ProcessingResult:
+    """Result of data processing operation."""
+    items_processed: int
+    success: bool
+    errors: List[str] = field(default_factory=list)
+
+class DataProcessor:
+    """Handles data validation, storage, and notification."""
+
+    def __init__(self, db_conn: Database, email_client: EmailClient):
+        self.db = db_conn
+        self.email = email_client
+
+    def process(self, data: List[dict]) -> ProcessingResult:
+        """Process and store data with notifications.
+
+        Args:
+            data: List of data items to process.
+
+        Returns:
+            ProcessingResult with details of the operation.
+        """
+        validated = self._validate_data(data)
+        result = self.db.save(validated)
+        self._notify_completion(result)
+        return result
+```
+
+**Design Improvement Areas:**
+
+If there's a **cleaner**, **more scalable**, or **simpler** design, highlight it and suggest improvements that would:
+
+- Reduce code duplication through shared utilities
+- Make unit testing easier
+- Improve separation of concerns (single responsibility)
+- Make unit testing easier through dependency injection
+- Add clarity without adding complexity
+- Prefer dataclasses for structured data
+
+## Development Tools & Commands
+
+### Package Management
+
+```bash
+# Add package
+uv add package-name
+
+# Sync project dependencies
+uv sync
+uv lock
+```
+
+### Testing
+
+```bash
+# Run unit tests (no network)
+make test
+
+# Don't run integration tests, as API keys must be set
+
+# Run specific test file
+uv run --group test pytest tests/unit_tests/test_specific.py
+```
+
+### Code Quality
+
+```bash
+# Lint code
+make lint
+
+# Format code
+make format
+
+# Type checking
+uv run --group lint mypy .
+```
+
+### Dependency Management Patterns
+
+**Local Development Dependencies:**
+
+```toml
+[tool.uv.sources]
+langchain-core = { path = "../core", editable = true }
+langchain-tests = { path = "../standard-tests", editable = true }
+```
+
+**For tools, use the `@tool` decorator from `langchain_core.tools`:**
+
+```python
+from langchain_core.tools import tool
+
+@tool
+def search_database(query: str) -> str:
+    """Search the database for relevant information.
+
+    Args:
+        query: The search query string.
+    """
+    # Implementation here
+    return results
+```
+
+## Commit Standards
+
+**Use Conventional Commits format for PR titles:**
+
+- `feat(core): add multi-tenant support`
+- `!fix(cli): resolve flag parsing error` (breaking change uses exclamation mark)
+- `docs: update API usage examples`
+- `docs(openai): update API usage examples`
+
+## Framework-Specific Guidelines
+
+- Follow the existing patterns in `langchain_core` for base abstractions
+- Implement proper streaming support where applicable
+- Avoid deprecated components
+
+### Partner Integrations
+
+- Follow the established patterns in existing partner libraries
+- Implement standard interfaces (`BaseChatModel`, `BaseEmbeddings`, etc.)
+- Include comprehensive integration tests
+- Document API key requirements and authentication
+
+---
+
+## Quick Reference Checklist
+
+Before submitting code changes:
+
+- [ ] **Breaking Changes**: Verified no public API changes
+- [ ] **Type Hints**: All functions have complete type annotations
+- [ ] **Tests**: New functionality is fully tested
+- [ ] **Security**: No dangerous patterns (eval, silent failures, etc.)
+- [ ] **Documentation**: Google-style docstrings for public functions
+- [ ] **Code Quality**: `make lint` and `make format` pass
+- [ ] **Architecture**: Suggested improvements where applicable
+- [ ] **Commit Message**: Follows Conventional Commits format

.github/pr-file-labeler.yml

@@ -7,26 +7,27 @@ core:
       - any-glob-to-any-file:
           - "libs/core/**/*"
 
-langchain-classic:
-  - changed-files:
-      - any-glob-to-any-file:
-          - "libs/langchain/**/*"
-
 langchain:
   - changed-files:
       - any-glob-to-any-file:
+          - "libs/langchain/**/*"
           - "libs/langchain_v1/**/*"
 
+v1:
+  - changed-files:
+      - any-glob-to-any-file:
+          - "libs/langchain_v1/**/*"
+
+cli:
+  - changed-files:
+      - any-glob-to-any-file:
+          - "libs/cli/**/*"
+
 standard-tests:
   - changed-files:
       - any-glob-to-any-file:
           - "libs/standard-tests/**/*"
 
-model-profiles:
-  - changed-files:
-      - any-glob-to-any-file:
-          - "libs/model-profiles/**/*"
-
 text-splitters:
   - changed-files:
       - any-glob-to-any-file:
@@ -38,80 +39,16 @@ integration:
       - any-glob-to-any-file:
           - "libs/partners/**/*"
 
-anthropic:
+# Infrastructure and DevOps
+infra:
   - changed-files:
       - any-glob-to-any-file:
-          - "libs/partners/anthropic/**/*"
-
-chroma:
-  - changed-files:
-      - any-glob-to-any-file:
-          - "libs/partners/chroma/**/*"
-
-deepseek:
-  - changed-files:
-      - any-glob-to-any-file:
-          - "libs/partners/deepseek/**/*"
-
-exa:
-  - changed-files:
-      - any-glob-to-any-file:
-          - "libs/partners/exa/**/*"
-
-fireworks:
-  - changed-files:
-      - any-glob-to-any-file:
-          - "libs/partners/fireworks/**/*"
-
-groq:
-  - changed-files:
-      - any-glob-to-any-file:
-          - "libs/partners/groq/**/*"
-
-huggingface:
-  - changed-files:
-      - any-glob-to-any-file:
-          - "libs/partners/huggingface/**/*"
-
-mistralai:
-  - changed-files:
-      - any-glob-to-any-file:
-          - "libs/partners/mistralai/**/*"
-
-nomic:
-  - changed-files:
-      - any-glob-to-any-file:
-          - "libs/partners/nomic/**/*"
-
-ollama:
-  - changed-files:
-      - any-glob-to-any-file:
-          - "libs/partners/ollama/**/*"
-
-openai:
-  - changed-files:
-      - any-glob-to-any-file:
-          - "libs/partners/openai/**/*"
-
-perplexity:
-  - changed-files:
-      - any-glob-to-any-file:
-          - "libs/partners/perplexity/**/*"
-
-prompty:
-  - changed-files:
-      - any-glob-to-any-file:
-          - "libs/partners/prompty/**/*"
-
-qdrant:
-  - changed-files:
-      - any-glob-to-any-file:
-          - "libs/partners/qdrant/**/*"
-
-xai:
-  - changed-files:
-      - any-glob-to-any-file:
-          - "libs/partners/xai/**/*"
+          - ".github/**/*"
+          - "Makefile"
+          - ".pre-commit-config.yaml"
+          - "scripts/**/*"
+          - "docker/**/*"
+          - "Dockerfile*"
 
 github_actions:
   - changed-files:
@@ -126,3 +63,22 @@ dependencies:
           - "uv.lock"
           - "**/requirements*.txt"
           - "**/poetry.lock"
+
+# Documentation
+documentation:
+  - changed-files:
+      - any-glob-to-any-file:
+          - "**/*.md"
+          - "**/*.rst"
+          - "**/README*"
+
+# Security related changes
+security:
+  - changed-files:
+      - any-glob-to-any-file:
+          - "**/*security*"
+          - "**/*auth*"
+          - "**/*credential*"
+          - "**/*secret*"
+          - "**/*token*"
+          - ".github/workflows/security*"

.github/pr-title-labeler.yml

@@ -0,0 +1,41 @@
+# PR title labeler config
+#
+# Labels PRs based on conventional commit patterns in titles
+#
+# Format: type(scope): description or type!: description (breaking)
+
+add-missing-labels: true
+clear-prexisting: false
+include-commits: false
+include-title: true
+label-for-breaking-changes: breaking
+
+label-mapping:
+  documentation: ["docs"]
+  feature: ["feat"]
+  fix: ["fix"]
+  infra: ["build", "ci", "chore"]
+  integration:
+    [
+      "anthropic",
+      "chroma",
+      "deepseek",
+      "exa",
+      "fireworks",
+      "groq",
+      "huggingface",
+      "mistralai",
+      "nomic",
+      "ollama",
+      "openai",
+      "perplexity",
+      "prompty",
+      "qdrant",
+      "xai",
+    ]
+  linting: ["style"]
+  performance: ["perf"]
+  refactor: ["refactor"]
+  release: ["release"]
+  revert: ["revert"]
+  tests: ["test"]

.github/scripts/check_diff.py

@@ -30,7 +30,6 @@ LANGCHAIN_DIRS = [
     "libs/text-splitters",
     "libs/langchain",
     "libs/langchain_v1",
-    "libs/model-profiles",
 ]
 
 # When set to True, we are ignoring core dependents
@@ -56,7 +55,7 @@ def all_package_dirs() -> Set[str]:
     return {
         "/".join(path.split("/")[:-1]).lstrip("./")
         for path in glob.glob("./libs/**/pyproject.toml", recursive=True)
-        if "libs/standard-tests" not in path
+        if "libs/cli" not in path and "libs/standard-tests" not in path
     }
 
 
@@ -131,20 +130,29 @@ def _get_configs_for_single_dir(job: str, dir_: str) -> List[Dict[str, str]]:
         return _get_pydantic_test_configs(dir_)
 
     if job == "codspeed":
-        py_versions = ["3.13"]
+        py_versions = ["3.12"]  # 3.13 is not yet supported
     elif dir_ == "libs/core":
-        py_versions = ["3.10", "3.11", "3.12", "3.13", "3.14"]
+        py_versions = ["3.10", "3.11", "3.12", "3.13"]
     # custom logic for specific directories
-    elif dir_ in {"libs/partners/chroma"}:
+
+    elif dir_ == "libs/langchain" and job == "extended-tests":
         py_versions = ["3.10", "3.13"]
+    elif dir_ == "libs/langchain_v1":
+        py_versions = ["3.10", "3.13"]
+    elif dir_ in {"libs/cli"}:
+        py_versions = ["3.10", "3.13"]
+
+    elif dir_ == ".":
+        # unable to install with 3.13 because tokenizers doesn't support 3.13 yet
+        py_versions = ["3.10", "3.12"]
     else:
-        py_versions = ["3.10", "3.14"]
+        py_versions = ["3.10", "3.13"]
 
     return [{"working-directory": dir_, "python-version": py_v} for py_v in py_versions]
 
 
 def _get_pydantic_test_configs(
-    dir_: str, *, python_version: str = "3.12"
+    dir_: str, *, python_version: str = "3.11"
 ) -> List[Dict[str, str]]:
     with open("./libs/core/uv.lock", "rb") as f:
         core_uv_lock_data = tomllib.load(f)
@@ -286,6 +294,10 @@ if __name__ == "__main__":
             dirs_to_run["test"].add("libs/partners/fireworks")
             dirs_to_run["test"].add("libs/partners/groq")
 
+        elif file.startswith("libs/cli"):
+            dirs_to_run["lint"].add("libs/cli")
+            dirs_to_run["test"].add("libs/cli")
+
         elif file.startswith("libs/partners"):
             partner_dir = file.split("/")[2]
             if os.path.isdir(f"libs/partners/{partner_dir}") and [
@@ -294,9 +306,7 @@ if __name__ == "__main__":
                 if not filename.startswith(".")
             ] != ["README.md"]:
                 dirs_to_run["test"].add(f"libs/partners/{partner_dir}")
-                # Skip codspeed for partners without benchmarks or in IGNORED_PARTNERS
-                if partner_dir not in IGNORED_PARTNERS:
-                    dirs_to_run["codspeed"].add(f"libs/partners/{partner_dir}")
+                dirs_to_run["codspeed"].add(f"libs/partners/{partner_dir}")
             # Skip if the directory was deleted or is just a tombstone readme
         elif file.startswith("libs/"):
             # Check if this is a root-level file in libs/ (e.g., libs/README.md)

.github/scripts/get_min_versions.py

@@ -98,7 +98,7 @@ def _check_python_version_from_requirement(
         return True
     else:
         marker_str = str(requirement.marker)
-        if "python_version" in marker_str or "python_full_version" in marker_str:
+        if "python_version" or "python_full_version" in marker_str:
             python_version_str = "".join(
                 char
                 for char in marker_str

.github/workflows/_compile_integration_test.yml

@@ -35,7 +35,7 @@ jobs:
     timeout-minutes: 20
     name: "Python ${{ inputs.python-version }}"
     steps:
-      - uses: actions/checkout@v6
+      - uses: actions/checkout@v5
 
       - name: "🐍 Set up Python ${{ inputs.python-version }} + UV"
         uses: "./.github/actions/uv_setup"

.github/workflows/_lint.yml

@@ -38,7 +38,7 @@ jobs:
     timeout-minutes: 20
     steps:
       - name: "📋 Checkout Code"
-        uses: actions/checkout@v6
+        uses: actions/checkout@v5
 
       - name: "🐍 Set up Python ${{ inputs.python-version }} + UV"
         uses: "./.github/actions/uv_setup"
@@ -47,12 +47,6 @@ jobs:
           cache-suffix: lint-${{ inputs.working-directory }}
           working-directory: ${{ inputs.working-directory }}
 
-      # - name: "🔒 Verify Lockfile is Up-to-Date"
-      #   working-directory: ${{ inputs.working-directory }}
-      #   run: |
-      #     unset UV_FROZEN
-      #     uv lock --check
-
       - name: "📦 Install Lint & Typing Dependencies"
         working-directory: ${{ inputs.working-directory }}
         run: |

.github/workflows/_release.yml

@@ -19,7 +19,7 @@ on:
         required: true
         type: string
         description: "From which folder this pipeline executes"
-        default: "libs/langchain_v1"
+        default: "libs/langchain"
       release-version:
         required: true
         type: string
@@ -54,7 +54,7 @@ jobs:
       version: ${{ steps.check-version.outputs.version }}
 
     steps:
-      - uses: actions/checkout@v6
+      - uses: actions/checkout@v5
 
       - name: Set up Python + uv
         uses: "./.github/actions/uv_setup"
@@ -77,7 +77,7 @@ jobs:
         working-directory: ${{ inputs.working-directory }}
 
       - name: Upload build
-        uses: actions/upload-artifact@v6
+        uses: actions/upload-artifact@v4
         with:
           name: dist
           path: ${{ inputs.working-directory }}/dist/
@@ -105,7 +105,7 @@ jobs:
     outputs:
       release-body: ${{ steps.generate-release-body.outputs.release-body }}
     steps:
-      - uses: actions/checkout@v6
+      - uses: actions/checkout@v5
         with:
           repository: langchain-ai/langchain
           path: langchain
@@ -149,8 +149,8 @@ jobs:
             fi
           fi
 
-          # if PREV_TAG is empty or came out to 0.0.0, let it be empty
-          if [ -z "$PREV_TAG" ] || [ "$PREV_TAG" = "$PKG_NAME==0.0.0" ]; then
+          # if PREV_TAG is empty, let it be empty
+          if [ -z "$PREV_TAG" ]; then
             echo "No previous tag found - first release"
           else
             # confirm prev-tag actually exists in git repo with git tag
@@ -179,8 +179,8 @@ jobs:
           PREV_TAG: ${{ steps.check-tags.outputs.prev-tag }}
         run: |
           PREAMBLE="Changes since $PREV_TAG"
-          # if PREV_TAG is empty or 0.0.0, then we are releasing the first version
-          if [ -z "$PREV_TAG" ] || [ "$PREV_TAG" = "$PKG_NAME==0.0.0" ]; then
+          # if PREV_TAG is empty, then we are releasing the first version
+          if [ -z "$PREV_TAG" ]; then
             PREAMBLE="Initial release"
             PREV_TAG=$(git rev-list --max-parents=0 HEAD)
           fi
@@ -206,9 +206,9 @@ jobs:
       id-token: write
 
     steps:
-      - uses: actions/checkout@v6
+      - uses: actions/checkout@v5
 
-      - uses: actions/download-artifact@v7
+      - uses: actions/download-artifact@v5
         with:
           name: dist
           path: ${{ inputs.working-directory }}/dist/
@@ -237,7 +237,7 @@ jobs:
       contents: read
     timeout-minutes: 20
     steps:
-      - uses: actions/checkout@v6
+      - uses: actions/checkout@v5
 
       # We explicitly *don't* set up caching here. This ensures our tests are
       # maximally sensitive to catching breakage.
@@ -258,7 +258,7 @@ jobs:
         with:
           python-version: ${{ env.PYTHON_VERSION }}
 
-      - uses: actions/download-artifact@v7
+      - uses: actions/download-artifact@v5
         with:
           name: dist
           path: ${{ inputs.working-directory }}/dist/
@@ -377,7 +377,6 @@ jobs:
           XAI_API_KEY: ${{ secrets.XAI_API_KEY }}
           DEEPSEEK_API_KEY: ${{ secrets.DEEPSEEK_API_KEY }}
           PPLX_API_KEY: ${{ secrets.PPLX_API_KEY }}
-          LANGCHAIN_TESTS_USER_AGENT: ${{ secrets.LANGCHAIN_TESTS_USER_AGENT }}
         run: make integration_tests
         working-directory: ${{ inputs.working-directory }}
 
@@ -396,7 +395,7 @@ jobs:
       contents: read
     strategy:
       matrix:
-        partner: [anthropic]
+        partner: [openai, anthropic]
       fail-fast: false # Continue testing other partners if one fails
     env:
       ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
@@ -410,9 +409,8 @@ jobs:
       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 }}
-      LANGCHAIN_TESTS_USER_AGENT: ${{ secrets.LANGCHAIN_TESTS_USER_AGENT }}
     steps:
-      - uses: actions/checkout@v6
+      - uses: actions/checkout@v5
 
       # We implement this conditional as Github Actions does not have good support
       # for conditionally needing steps. https://github.com/actions/runner/issues/491
@@ -430,7 +428,7 @@ jobs:
         with:
           python-version: ${{ env.PYTHON_VERSION }}
 
-      - uses: actions/download-artifact@v7
+      - uses: actions/download-artifact@v5
         if: startsWith(inputs.working-directory, 'libs/core')
         with:
           name: dist
@@ -444,7 +442,7 @@ jobs:
             git ls-remote --tags origin "langchain-${{ matrix.partner }}*" \
             | awk '{print $2}' \
             | sed 's|refs/tags/||' \
-            | grep -E '[0-9]+\.[0-9]+\.[0-9]+$' \
+            | grep -E '[0-9]+\.[0-9]+\.[0-9]+([a-zA-Z]+[0-9]+)?$' \
             | sort -Vr \
             | head -n 1
           )"
@@ -470,67 +468,6 @@ jobs:
           uv pip install ../../core/dist/*.whl
           make integration_tests
 
-  # Test external packages that depend on langchain-core/langchain against the new release
-  # Only runs for core and langchain_v1 releases to catch breaking changes before publish
-  test-dependents:
-    name: "🐍 Python ${{ matrix.python-version }}: ${{ matrix.package.path }}"
-    needs:
-      - build
-      - release-notes
-      - test-pypi-publish
-      - pre-release-checks
-    runs-on: ubuntu-latest
-    permissions:
-      contents: read
-    # Only run for core or langchain_v1 releases
-    if: startsWith(inputs.working-directory, 'libs/core') || startsWith(inputs.working-directory, 'libs/langchain_v1')
-    strategy:
-      fail-fast: false
-      matrix:
-        python-version: ["3.11", "3.13"]
-        package:
-          - name: deepagents
-            repo: langchain-ai/deepagents
-            path: libs/deepagents
-    # No API keys needed for now - deepagents `make test` only runs unit tests
-
-    steps:
-      - uses: actions/checkout@v6
-        with:
-          path: langchain
-
-      - uses: actions/checkout@v6
-        with:
-          repository: ${{ matrix.package.repo }}
-          path: ${{ matrix.package.name }}
-
-      - name: Set up Python + uv
-        uses: "./langchain/.github/actions/uv_setup"
-        with:
-          python-version: ${{ matrix.python-version }}
-
-      - uses: actions/download-artifact@v7
-        with:
-          name: dist
-          path: dist/
-
-      - name: Install ${{ matrix.package.name }} with local packages
-        # External dependents don't have [tool.uv.sources] pointing to this repo,
-        # so we install the package normally then override with the built wheel.
-        run: |
-          cd ${{ matrix.package.name }}/${{ matrix.package.path }}
-
-          # Install the package with test dependencies
-          uv sync --group test
-
-          # Override with the built wheel from this release
-          uv pip install $GITHUB_WORKSPACE/dist/*.whl
-
-      - name: Run ${{ matrix.package.name }} tests
-        run: |
-          cd ${{ matrix.package.name }}/${{ matrix.package.path }}
-          make test
-
   publish:
     # Publishes the package to PyPI
     needs:
@@ -538,10 +475,7 @@ jobs:
       - release-notes
       - test-pypi-publish
       - pre-release-checks
-      - test-dependents
       - test-prior-published-packages-against-new-core
-    # Run if all needed jobs succeeded or were skipped (test-dependents only runs for core/langchain_v1)
-    if: ${{ !cancelled() && !failure() }}
     runs-on: ubuntu-latest
     permissions:
       # This permission is used for trusted publishing:
@@ -556,14 +490,14 @@ jobs:
         working-directory: ${{ inputs.working-directory }}
 
     steps:
-      - uses: actions/checkout@v6
+      - uses: actions/checkout@v5
 
       - name: Set up Python + uv
         uses: "./.github/actions/uv_setup"
         with:
           python-version: ${{ env.PYTHON_VERSION }}
 
-      - uses: actions/download-artifact@v7
+      - uses: actions/download-artifact@v5
         with:
           name: dist
           path: ${{ inputs.working-directory }}/dist/
@@ -596,14 +530,14 @@ jobs:
         working-directory: ${{ inputs.working-directory }}
 
     steps:
-      - uses: actions/checkout@v6
+      - uses: actions/checkout@v5
 
       - name: Set up Python + uv
         uses: "./.github/actions/uv_setup"
         with:
           python-version: ${{ env.PYTHON_VERSION }}
 
-      - uses: actions/download-artifact@v7
+      - uses: actions/download-artifact@v5
         with:
           name: dist
           path: ${{ inputs.working-directory }}/dist/

.github/workflows/_test.yml

@@ -33,7 +33,7 @@ jobs:
     name: "Python ${{ inputs.python-version }}"
     steps:
       - name: "📋 Checkout Code"
-        uses: actions/checkout@v6
+        uses: actions/checkout@v5
 
       - name: "🐍 Set up Python ${{ inputs.python-version }} + UV"
         uses: "./.github/actions/uv_setup"

.github/workflows/_test_pydantic.yml

@@ -13,7 +13,7 @@ on:
         required: false
         type: string
         description: "Python version to use"
-        default: "3.12"
+        default: "3.11"
       pydantic-version:
         required: true
         type: string
@@ -36,7 +36,7 @@ jobs:
     name: "Pydantic ~=${{ inputs.pydantic-version }}"
     steps:
       - name: "📋 Checkout Code"
-        uses: actions/checkout@v6
+        uses: actions/checkout@v5
 
       - name: "🐍 Set up Python ${{ inputs.python-version }} + UV"
         uses: "./.github/actions/uv_setup"
@@ -51,9 +51,7 @@ jobs:
 
       - name: "🔄 Install Specific Pydantic Version"
         shell: bash
-        env:
-          PYDANTIC_VERSION: ${{ inputs.pydantic-version }}
-        run: VIRTUAL_ENV=.venv uv pip install "pydantic~=$PYDANTIC_VERSION"
+        run: VIRTUAL_ENV=.venv uv pip install pydantic~=${{ inputs.pydantic-version }}
 
       - name: "🧪 Run Core Tests"
         shell: bash

.github/workflows/auto-label-by-package.yml

@@ -1,106 +0,0 @@
-name: Auto Label Issues by Package
-
-on:
-  issues:
-    types: [opened, edited]
-
-jobs:
-  label-by-package:
-    permissions:
-      issues: write
-    runs-on: ubuntu-latest
-
-    steps:
-      - name: Sync package labels
-        uses: actions/github-script@v8
-        with:
-          script: |
-            const body = context.payload.issue.body || "";
-
-            // Extract text under "### Package" (handles " (Required)" suffix and being last section)
-            const match = body.match(/### Package[^\n]*\n([\s\S]*?)(?:\n###|$)/i);
-            if (!match) return;
-
-            const packageSection = match[1].trim();
-
-            // Mapping table for package names to labels
-            const mapping = {
-              "langchain": "langchain",
-              "langchain-openai": "openai",
-              "langchain-anthropic": "anthropic",
-              "langchain-classic": "langchain-classic",
-              "langchain-core": "core",
-              "langchain-model-profiles": "model-profiles",
-              "langchain-tests": "standard-tests",
-              "langchain-text-splitters": "text-splitters",
-              "langchain-chroma": "chroma",
-              "langchain-deepseek": "deepseek",
-              "langchain-exa": "exa",
-              "langchain-fireworks": "fireworks",
-              "langchain-groq": "groq",
-              "langchain-huggingface": "huggingface",
-              "langchain-mistralai": "mistralai",
-              "langchain-nomic": "nomic",
-              "langchain-ollama": "ollama",
-              "langchain-perplexity": "perplexity",
-              "langchain-prompty": "prompty",
-              "langchain-qdrant": "qdrant",
-              "langchain-xai": "xai",
-            };
-
-            // All possible package labels we manage
-            const allPackageLabels = Object.values(mapping);
-            const selectedLabels = [];
-
-            // Check if this is checkbox format (multiple selection)
-            const checkboxMatches = packageSection.match(/- \[x\]\s+([^\n\r]+)/gi);
-            if (checkboxMatches) {
-              // Handle checkbox format
-              for (const match of checkboxMatches) {
-                const packageName = match.replace(/- \[x\]\s+/i, '').trim();
-                const label = mapping[packageName];
-                if (label && !selectedLabels.includes(label)) {
-                  selectedLabels.push(label);
-                }
-              }
-            } else {
-              // Handle dropdown format (single selection)
-              const label = mapping[packageSection];
-              if (label) {
-                selectedLabels.push(label);
-              }
-            }
-
-            // Get current issue labels
-            const issue = await github.rest.issues.get({
-              owner: context.repo.owner,
-              repo: context.repo.repo,
-              issue_number: context.issue.number
-            });
-
-            const currentLabels = issue.data.labels.map(label => label.name);
-            const currentPackageLabels = currentLabels.filter(label => allPackageLabels.includes(label));
-
-            // Determine labels to add and remove
-            const labelsToAdd = selectedLabels.filter(label => !currentPackageLabels.includes(label));
-            const labelsToRemove = currentPackageLabels.filter(label => !selectedLabels.includes(label));
-
-            // Add new labels
-            if (labelsToAdd.length > 0) {
-              await github.rest.issues.addLabels({
-                owner: context.repo.owner,
-                repo: context.repo.repo,
-                issue_number: context.issue.number,
-                labels: labelsToAdd
-              });
-            }
-
-            // Remove old labels
-            for (const label of labelsToRemove) {
-              await github.rest.issues.removeLabel({
-                owner: context.repo.owner,
-                repo: context.repo.repo,
-                issue_number: context.issue.number,
-                name: label
-              });
-            }

.github/workflows/check_agents_sync.yml

@@ -1,42 +0,0 @@
-# Ensures CLAUDE.md and AGENTS.md stay synchronized.
-#
-# These files contain the same development guidelines but are named differently
-# for compatibility with different AI coding assistants (Claude Code uses CLAUDE.md,
-# other tools may use AGENTS.md).
-
-name: "🔄 Check CLAUDE.md / AGENTS.md Sync"
-
-on:
-  push:
-    branches: [master]
-    paths:
-      - "CLAUDE.md"
-      - "AGENTS.md"
-  pull_request:
-    paths:
-      - "CLAUDE.md"
-      - "AGENTS.md"
-
-permissions:
-  contents: read
-
-jobs:
-  check-sync:
-    name: "verify files are identical"
-    runs-on: ubuntu-latest
-    steps:
-      - name: "📋 Checkout Code"
-        uses: actions/checkout@v6
-
-      - name: "🔍 Check CLAUDE.md and AGENTS.md are in sync"
-        run: |
-          if ! diff -q CLAUDE.md AGENTS.md > /dev/null 2>&1; then
-            echo "❌ CLAUDE.md and AGENTS.md are out of sync!"
-            echo ""
-            echo "These files must contain identical content."
-            echo "Differences:"
-            echo ""
-            diff --color=always CLAUDE.md AGENTS.md || true
-            exit 1
-          fi
-          echo "✅ CLAUDE.md and AGENTS.md are in sync"

.github/workflows/check_core_versions.yml

@@ -18,7 +18,7 @@ jobs:
     runs-on: ubuntu-latest
 
     steps:
-      - uses: actions/checkout@v6
+      - uses: actions/checkout@v5
 
       - name: "✅ Verify pyproject.toml & version.py Match"
         run: |

.github/workflows/check_diffs.yml

@@ -47,7 +47,7 @@ jobs:
     if: ${{ !contains(github.event.pull_request.labels.*.name, 'ci-ignore') }}
     steps:
       - name: "📋 Checkout Code"
-        uses: actions/checkout@v6
+        uses: actions/checkout@v5
       - name: "🐍 Setup Python 3.11"
         uses: actions/setup-python@v6
         with:
@@ -141,7 +141,7 @@ jobs:
       run:
         working-directory: ${{ matrix.job-configs.working-directory }}
     steps:
-      - uses: actions/checkout@v6
+      - uses: actions/checkout@v5
 
       - name: "🐍 Set up Python ${{ matrix.job-configs.python-version }} + UV"
         uses: "./.github/actions/uv_setup"
@@ -182,16 +182,17 @@ jobs:
         job-configs: ${{ fromJson(needs.build.outputs.codspeed) }}
       fail-fast: false
     steps:
-      - uses: actions/checkout@v6
+      - uses: actions/checkout@v5
 
+      # We have to use 3.12 as 3.13 is not yet supported
       - name: "📦 Install UV Package Manager"
         uses: astral-sh/setup-uv@v7
         with:
-          python-version: "3.13"
+          python-version: "3.12"
 
       - uses: actions/setup-python@v6
         with:
-          python-version: "3.13"
+          python-version: "3.12"
 
       - name: "📦 Install Test Dependencies"
         run: uv sync --group test

.github/workflows/integration_tests.yml

@@ -1,8 +1,8 @@
 # Routine integration tests against partner libraries with live API credentials.
 #
-# Uses `make integration_tests` within each library being tested.
+# Uses `make integration_tests` for each library in the matrix.
 #
-# Runs daily with the option to trigger manually.
+# Runs daily. Can also be triggered manually for immediate updates.
 
 name: "⏰ Integration Tests"
 run-name: "Run Integration Tests - ${{ inputs.working-directory-force || 'all libs' }} (Python ${{ inputs.python-version-force || '3.10, 3.13' }})"
@@ -24,29 +24,17 @@ permissions:
 
 env:
   UV_FROZEN: "true"
-  DEFAULT_LIBS: >-
-    ["libs/partners/openai",
-    "libs/partners/anthropic",
-    "libs/partners/fireworks",
-    "libs/partners/groq",
-    "libs/partners/mistralai",
-    "libs/partners/xai",
-    "libs/partners/google-vertexai",
-    "libs/partners/google-genai",
-    "libs/partners/aws"]
+  DEFAULT_LIBS: '["libs/partners/openai", "libs/partners/anthropic", "libs/partners/fireworks", "libs/partners/groq", "libs/partners/mistralai", "libs/partners/xai", "libs/partners/google-vertexai", "libs/partners/google-genai", "libs/partners/aws"]'
 
 jobs:
   # Generate dynamic test matrix based on input parameters or defaults
   # Only runs on the main repo (for scheduled runs) or when manually triggered
   compute-matrix:
-    # Defend against forks running scheduled jobs, but allow manual runs from forks
     if: github.repository_owner == 'langchain-ai' || github.event_name != 'schedule'
-
     runs-on: ubuntu-latest
     name: "📋 Compute Test Matrix"
     outputs:
       matrix: ${{ steps.set-matrix.outputs.matrix }}
-      python-version-min-3-11: ${{ steps.set-matrix.outputs.python-version-min-3-11 }}
     steps:
       - name: "🔢 Generate Python & Library Matrix"
         id: set-matrix
@@ -59,16 +47,9 @@ jobs:
           # python-version should default to 3.10 and 3.13, but is overridden to [PYTHON_VERSION_FORCE] if set
           # working-directory should default to DEFAULT_LIBS, but is overridden to [WORKING_DIRECTORY_FORCE] if set
           python_version='["3.10", "3.13"]'
-          python_version_min_3_11='["3.11", "3.13"]'
           working_directory="$DEFAULT_LIBS"
           if [ -n "$PYTHON_VERSION_FORCE" ]; then
             python_version="[\"$PYTHON_VERSION_FORCE\"]"
-            # Bound forced version to >= 3.11 for packages requiring it
-            if [ "$(echo "$PYTHON_VERSION_FORCE >= 3.11" | bc -l)" -eq 1 ]; then
-              python_version_min_3_11="[\"$PYTHON_VERSION_FORCE\"]"
-            else
-              python_version_min_3_11='["3.11"]'
-            fi
           fi
           if [ -n "$WORKING_DIRECTORY_FORCE" ]; then
             working_directory="[\"$WORKING_DIRECTORY_FORCE\"]"
@@ -76,10 +57,8 @@ jobs:
           matrix="{\"python-version\": $python_version, \"working-directory\": $working_directory}"
           echo $matrix
           echo "matrix=$matrix" >> $GITHUB_OUTPUT
-          echo "python-version-min-3-11=$python_version_min_3_11" >> $GITHUB_OUTPUT
-
   # Run integration tests against partner libraries with live API credentials
-  integration-tests:
+  build:
     if: github.repository_owner == 'langchain-ai' || github.event_name != 'schedule'
     name: "🐍 Python ${{ matrix.python-version }}: ${{ matrix.working-directory }}"
     runs-on: ubuntu-latest
@@ -92,30 +71,18 @@ jobs:
         working-directory: ${{ fromJSON(needs.compute-matrix.outputs.matrix).working-directory }}
 
     steps:
-      - uses: actions/checkout@v6
+      - uses: actions/checkout@v5
         with:
           path: langchain
-
-      # These libraries exist outside of the monorepo and need to be checked out separately
-      - uses: actions/checkout@v6
+      - uses: actions/checkout@v5
         with:
           repository: langchain-ai/langchain-google
           path: langchain-google
-      - name: "🔐 Authenticate to Google Cloud"
-        id: "auth"
-        uses: google-github-actions/auth@v3
-        with:
-          credentials_json: "${{ secrets.GOOGLE_CREDENTIALS }}"
-      - uses: actions/checkout@v6
+      - uses: actions/checkout@v5
         with:
           repository: langchain-ai/langchain-aws
           path: langchain-aws
-      - name: "🔐 Configure AWS Credentials"
-        uses: aws-actions/configure-aws-credentials@v5
-        with:
-          aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
-          aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
-          aws-region: ${{ secrets.AWS_REGION }}
+
       - name: "📦 Organize External Libraries"
         run: |
           rm -rf \
@@ -130,27 +97,27 @@ jobs:
         with:
           python-version: ${{ matrix.python-version }}
 
-      - name: "📦 Install Dependencies"
-        # Partner packages use [tool.uv.sources] in their pyproject.toml to resolve
-        # langchain-core/langchain to local editable installs, so `uv sync` automatically
-        # tests against the versions from the current branch (not published releases).
+      - name: "🔐 Authenticate to Google Cloud"
+        id: "auth"
+        uses: google-github-actions/auth@v3
+        with:
+          credentials_json: "${{ secrets.GOOGLE_CREDENTIALS }}"
 
-        # TODO: external google/aws don't have local resolution since they live in
-        # separate repos, so they pull `core`/`langchain_v1` from PyPI. We should update
-        # their dev groups to use git source dependencies pointing to the current
-        # branch's latest commit SHA to fully test against local langchain changes.
+      - name: "🔐 Configure AWS Credentials"
+        uses: aws-actions/configure-aws-credentials@v5
+        with:
+          aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
+          aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
+          aws-region: ${{ secrets.AWS_REGION }}
+
+      - name: "📦 Install Dependencies"
         run: |
           echo "Running scheduled tests, installing dependencies with uv..."
           cd langchain/${{ matrix.working-directory }}
           uv sync --group test --group test_integration
 
       - name: "🚀 Run Integration Tests"
-        # WARNING: All secrets below are available to every matrix job regardless of
-        # which package is being tested. This is intentional for simplicity, but means
-        # any test file could technically access any key. Only use for trusted code.
         env:
-          LANGCHAIN_TESTS_USER_AGENT: ${{ secrets.LANGCHAIN_TESTS_USER_AGENT }}
-
           AI21_API_KEY: ${{ secrets.AI21_API_KEY }}
           ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
           ANTHROPIC_FILES_API_IMAGE_ID: ${{ secrets.ANTHROPIC_FILES_API_IMAGE_ID }}
@@ -211,59 +178,3 @@ jobs:
           # grep will exit non-zero if the target message isn't found,
           # and `set -e` above will cause the step to fail.
           echo "$STATUS" | grep 'nothing to commit, working tree clean'
-
-  # Test dependent packages against local packages to catch breaking changes
-  test-dependents:
-    # Defend against forks running scheduled jobs, but allow manual runs from forks
-    if: github.repository_owner == 'langchain-ai' || github.event_name != 'schedule'
-
-    name: "🐍 Python ${{ matrix.python-version }}: ${{ matrix.package.path }}"
-    runs-on: ubuntu-latest
-    needs: [compute-matrix]
-    timeout-minutes: 30
-    strategy:
-      fail-fast: false
-      matrix:
-        # deepagents requires Python >= 3.11, use bounded version from compute-matrix
-        python-version: ${{ fromJSON(needs.compute-matrix.outputs.python-version-min-3-11) }}
-        package:
-          - name: deepagents
-            repo: langchain-ai/deepagents
-            path: libs/deepagents
-
-    steps:
-      - uses: actions/checkout@v6
-        with:
-          path: langchain
-
-      - uses: actions/checkout@v6
-        with:
-          repository: ${{ matrix.package.repo }}
-          path: ${{ matrix.package.name }}
-
-      - name: "🐍 Set up Python ${{ matrix.python-version }} + UV"
-        uses: "./langchain/.github/actions/uv_setup"
-        with:
-          python-version: ${{ matrix.python-version }}
-
-      - name: "📦 Install ${{ matrix.package.name }} with Local"
-        # Unlike partner packages (which use [tool.uv.sources] for local resolution),
-        # external dependents live in separate repos and need explicit overrides to
-        # test against the langchain versions from the current branch, as their
-        # pyproject.toml files point to released versions.
-        run: |
-          cd ${{ matrix.package.name }}/${{ matrix.package.path }}
-
-          # Install the package with test dependencies
-          uv sync --group test
-
-          # Override langchain packages with local versions
-          uv pip install \
-            -e $GITHUB_WORKSPACE/langchain/libs/core \
-            -e $GITHUB_WORKSPACE/langchain/libs/langchain_v1
-
-      # No API keys needed for now - deepagents `make test` only runs unit tests
-      - name: "🚀 Run ${{ matrix.package.name }} Tests"
-        run: |
-          cd ${{ matrix.package.name }}/${{ matrix.package.path }}
-          make test

.github/workflows/pr_labeler_file.yml

@@ -8,7 +8,7 @@ on:
   # Safe since we're not checking out or running the PR's code
   # Never check out the PR's head in a pull_request_target job
   pull_request_target:
-    types: [opened, synchronize, reopened]
+    types: [opened, synchronize, reopened, edited]
 
 jobs:
   labeler:

.github/workflows/pr_lint.yml

@@ -8,7 +8,7 @@
 #
 # Examples:
 #     feat(core): add multi‐tenant support
-#     fix(langchain): resolve error
+#     fix(cli): resolve flag parsing error
 #     docs: update API usage examples
 #     docs(openai): update API usage examples
 #
@@ -26,19 +26,11 @@
 #   * revert     — reverts a previous commit
 #   * release    — prepare a new release
 #
-# Allowed Scope(s) (optional):
-#   core, langchain, langchain-classic, model-profiles,
-#   standard-tests, text-splitters, docs, anthropic, chroma, deepseek, exa,
-#   fireworks, groq, huggingface, mistralai, nomic, ollama, openai,
-#   perplexity, prompty, qdrant, xai, infra, deps
-#
-# Multiple scopes can be used by separating them with a comma. For example:
-#
-#   feat(core,langchain): add multi‐tenant support to core and langchain
-#
-# Note: PRs touching the langchain package should use the 'langchain' scope. It is not
-#   acceptable to omit the scope for changes to the langchain package, despite it being
-#   the main package & name of the repo.
+# Allowed Scopes (optional):
+#   core, cli, langchain, langchain_v1, langchain_legacy, standard-tests,
+#   text-splitters, docs, anthropic, chroma, deepseek, exa, fireworks, groq,
+#   huggingface, mistralai, nomic, ollama, openai, perplexity, prompty, qdrant,
+#   xai, infra
 #
 # Rules:
 #   1. The 'Type' must start with a lowercase letter.
@@ -85,9 +77,10 @@ jobs:
             release
           scopes: |
             core
+            cli
             langchain
-            langchain-classic
-            model-profiles
+            langchain_v1
+            langchain_legacy
             standard-tests
             text-splitters
             docs
@@ -107,7 +100,6 @@ jobs:
             qdrant
             xai
             infra
-            deps
           requireScope: false
           disallowScopes: |
             release

.github/workflows/tag-external-contributions.yml

@@ -1,148 +0,0 @@
-# Automatically tag issues and pull requests as "external" or "internal"
-# based on whether the author is a member of the langchain-ai
-# GitHub organization.
-#
-# Setup Requirements:
-# 1. Create a GitHub App with permissions:
-#    - Repository: Issues (write), Pull requests (write)
-#    - Organization: Members (read)
-# 2. Install the app on your organization and this repository
-# 3. Add these repository secrets:
-#    - ORG_MEMBERSHIP_APP_ID: Your app's ID
-#    - ORG_MEMBERSHIP_APP_PRIVATE_KEY: Your app's private key
-#
-# The GitHub App token is required to check private organization membership.
-# Without it, the workflow will fail.
-
-name: Tag External Contributions
-
-on:
-  issues:
-    types: [opened]
-  pull_request_target:
-    types: [opened]
-
-jobs:
-  tag-external:
-    runs-on: ubuntu-latest
-    permissions:
-      issues: write
-      pull-requests: write
-
-    steps:
-      - name: Generate GitHub App token
-        id: app-token
-        uses: actions/create-github-app-token@v2
-        with:
-          app-id: ${{ secrets.ORG_MEMBERSHIP_APP_ID }}
-          private-key: ${{ secrets.ORG_MEMBERSHIP_APP_PRIVATE_KEY }}
-
-      - name: Check if contributor is external
-        id: check-membership
-        uses: actions/github-script@v8
-        with:
-          github-token: ${{ steps.app-token.outputs.token }}
-          script: |
-            const { owner, repo } = context.repo;
-            const author = context.payload.sender.login;
-
-            try {
-              // Check if the author is a member of the langchain-ai organization
-              // This requires org:read permissions to see private memberships
-              const membership = await github.rest.orgs.getMembershipForUser({
-                org: 'langchain-ai',
-                username: author
-              });
-
-              // Check if membership is active (not just pending invitation)
-              if (membership.data.state === 'active') {
-                console.log(`User ${author} is an active member of langchain-ai organization`);
-                core.setOutput('is-external', 'false');
-              } else {
-                console.log(`User ${author} has pending membership in langchain-ai organization`);
-                core.setOutput('is-external', 'true');
-              }
-            } catch (error) {
-              if (error.status === 404) {
-                console.log(`User ${author} is not a member of langchain-ai organization`);
-                core.setOutput('is-external', 'true');
-              } else {
-                console.error('Error checking membership:', error);
-                console.log('Status:', error.status);
-                console.log('Message:', error.message);
-                // If we can't determine membership due to API error, assume external for safety
-                core.setOutput('is-external', 'true');
-              }
-            }
-
-      - name: Add external label to issue
-        if: steps.check-membership.outputs.is-external == 'true' && github.event_name == 'issues'
-        uses: actions/github-script@v8
-        with:
-          github-token: ${{ secrets.GITHUB_TOKEN }}
-          script: |
-            const { owner, repo } = context.repo;
-            const issue_number = context.payload.issue.number;
-
-            await github.rest.issues.addLabels({
-              owner,
-              repo,
-              issue_number,
-              labels: ['external']
-            });
-
-            console.log(`Added 'external' label to issue #${issue_number}`);
-
-      - name: Add external label to pull request
-        if: steps.check-membership.outputs.is-external == 'true' && github.event_name == 'pull_request_target'
-        uses: actions/github-script@v8
-        with:
-          github-token: ${{ secrets.GITHUB_TOKEN }}
-          script: |
-            const { owner, repo } = context.repo;
-            const pull_number = context.payload.pull_request.number;
-
-            await github.rest.issues.addLabels({
-              owner,
-              repo,
-              issue_number: pull_number,
-              labels: ['external']
-            });
-
-            console.log(`Added 'external' label to pull request #${pull_number}`);
-
-      - name: Add internal label to issue
-        if: steps.check-membership.outputs.is-external == 'false' && github.event_name == 'issues'
-        uses: actions/github-script@v8
-        with:
-          github-token: ${{ secrets.GITHUB_TOKEN }}
-          script: |
-            const { owner, repo } = context.repo;
-            const issue_number = context.payload.issue.number;
-
-            await github.rest.issues.addLabels({
-              owner,
-              repo,
-              issue_number,
-              labels: ['internal']
-            });
-
-            console.log(`Added 'internal' label to issue #${issue_number}`);
-
-      - name: Add internal label to pull request
-        if: steps.check-membership.outputs.is-external == 'false' && github.event_name == 'pull_request_target'
-        uses: actions/github-script@v8
-        with:
-          github-token: ${{ secrets.GITHUB_TOKEN }}
-          script: |
-            const { owner, repo } = context.repo;
-            const pull_number = context.payload.pull_request.number;
-
-            await github.rest.issues.addLabels({
-              owner,
-              repo,
-              issue_number: pull_number,
-              labels: ['internal']
-            });
-
-            console.log(`Added 'internal' label to pull request #${pull_number}`);

.github/workflows/v03_api_doc_build.yml

@@ -23,12 +23,12 @@ jobs:
     permissions:
       contents: read
     steps:
-      - uses: actions/checkout@v6
+      - uses: actions/checkout@v5
         with:
           ref: v0.3
           path: langchain
 
-      - uses: actions/checkout@v6
+      - uses: actions/checkout@v5
         with:
           repository: langchain-ai/langchain-api-docs-html
           path: langchain-api-docs-html

.github/workflows/v1_changes.md

@@ -0,0 +1,8 @@
+With the deprecation of v0 docs, the following files will need to be migrated/supported
+in the new docs repo:
+
+- run_notebooks.yml: New repo should run Integration tests on code snippets?
+- people.yml: Need to fix and somehow display on the new docs site
+  - Subsequently, `.github/actions/people/`
+- _test_doc_imports.yml
+- check-broken-links.yml

.gitignore

@@ -1,8 +1,6 @@
 .vs/
 .claude/
 .idea/
-#Emacs backup
-*~
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]
@@ -163,6 +161,3 @@ node_modules
 
 prof
 virtualenv/
-scratch/
-
-.langgraph_api/

.mcp.json

@@ -1,8 +0,0 @@
-{
-  "mcpServers": {
-    "docs-langchain": {
-      "type": "http",
-      "url": "https://docs.langchain.com/mcp"
-    }
-  }
-}

.pre-commit-config.yaml

@@ -1,24 +1,4 @@
 repos:
-  - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.3.0
-    hooks:
-      - id: no-commit-to-branch # prevent direct commits to protected branches
-        args: ["--branch", "master"]
-      - id: check-yaml # validate YAML syntax
-        args: ["--unsafe"] # allow custom tags
-      - id: check-toml # validate TOML syntax
-      - id: end-of-file-fixer # ensure files end with a newline
-      - id: trailing-whitespace # remove trailing whitespace from lines
-        exclude: \.ambr$
-
-  # Text normalization hooks for consistent formatting
-  - repo: https://github.com/sirosen/texthooks
-    rev: 0.6.8
-    hooks:
-      - id: fix-smartquotes # replace curly quotes with straight quotes
-      - id: fix-spaces # replace non-standard spaces (e.g., non-breaking) with regular spaces
-
-  # Per-package format and lint hooks for the monorepo
   - repo: local
     hooks:
       - id: core
@@ -117,15 +97,3 @@ repos:
         entry: make -C libs/partners/qdrant format lint
         files: ^libs/partners/qdrant/
         pass_filenames: false
-      - id: core-version
-        name: check core version consistency
-        language: system
-        entry: make -C libs/core check_version
-        files: ^libs/core/(pyproject\.toml|langchain_core/version\.py)$
-        pass_filenames: false
-      - id: langchain-v1-version
-        name: check langchain version consistency
-        language: system
-        entry: make -C libs/langchain_v1 check_version
-        files: ^libs/langchain_v1/(pyproject\.toml|langchain/__init__\.py)$
-        pass_filenames: false

.vscode/extensions.json

@@ -6,6 +6,8 @@
     "ms-toolsai.jupyter",
     "ms-toolsai.jupyter-keymap",
     "ms-toolsai.jupyter-renderers",
+    "ms-toolsai.vscode-jupyter-cell-tags",
+    "ms-toolsai.vscode-jupyter-slideshow",
     "yzhang.markdown-all-in-one",
     "davidanson.vscode-markdownlint",
     "bierner.markdown-mermaid",

AGENTS.md

@@ -1,67 +1,255 @@
-# Global development guidelines for the LangChain monorepo
+# Global Development Guidelines for LangChain Projects
 
-This document provides context to understand the LangChain Python project and assist with development.
+## Core Development Principles
 
-## Project architecture and context
+### 1. Maintain Stable Public Interfaces ⚠️ CRITICAL
 
-### Monorepo structure
+**Always attempt to preserve function signatures, argument positions, and names for exported/public methods.**
 
-This is a Python monorepo with multiple independently versioned packages that use `uv`.
+❌ **Bad - Breaking Change:**
 
-```txt
-langchain/
-├── libs/
-│   ├── core/             # `langchain-core` primitives and base abstractions
-│   ├── langchain/        # `langchain-classic` (legacy, no new features)
-│   ├── langchain_v1/     # Actively maintained `langchain` package
-│   ├── partners/         # Third-party integrations
-│   │   ├── openai/       # OpenAI models and embeddings
-│   │   ├── anthropic/    # Anthropic (Claude) integration
-│   │   ├── ollama/       # Local model support
-│   │   └── ... (other integrations maintained by the LangChain team)
-│   ├── text-splitters/   # Document chunking utilities
-│   ├── standard-tests/   # Shared test suite for integrations
-│   ├── model-profiles/   # Model configuration profiles
-├── .github/              # CI/CD workflows and templates
-├── .vscode/              # VSCode IDE standard settings and recommended extensions
-└── README.md             # Information about LangChain
+```python
+def get_user(id, verbose=False):  # Changed from `user_id`
+    pass
 ```
 
-- **Core layer** (`langchain-core`): Base abstractions, interfaces, and protocols. Users should not need to know about this layer directly.
-- **Implementation layer** (`langchain`): Concrete implementations and high-level public utilities
-- **Integration layer** (`partners/`): Third-party service integrations. Note that this monorepo is not exhaustive of all LangChain integrations; some are maintained in separate repos, such as `langchain-ai/langchain-google` and `langchain-ai/langchain-aws`. Usually these repos are cloned at the same level as this monorepo, so if needed, you can refer to their code directly by navigating to `../langchain-google/` from this monorepo.
-- **Testing layer** (`standard-tests/`): Standardized integration tests for partner integrations
+✅ **Good - Stable Interface:**
 
-### Development tools & commands
+```python
+def get_user(user_id: str, verbose: bool = False) -> User:
+    """Retrieve user by ID with optional verbose output."""
+    pass
+```
 
-- `uv` – Fast Python package installer and resolver (replaces pip/poetry)
-- `make` – Task runner for common development commands. Feel free to look at the `Makefile` for available commands and usage patterns.
-- `ruff` – Fast Python linter and formatter
-- `mypy` – Static type checking
-- `pytest` – Testing framework
+**Before making ANY changes to public APIs:**
 
-This monorepo uses `uv` for dependency management. Local development uses editable installs: `[tool.uv.sources]`
+- Check if the function/class is exported in `__init__.py`
+- Look for existing usage patterns in tests and examples
+- Use keyword-only arguments for new parameters: `*, new_param: str = "default"`
+- Mark experimental features clearly with docstring warnings (using MkDocs Material admonitions, like `!!! warning`)
 
-Each package in `libs/` has its own `pyproject.toml` and `uv.lock`.
+🧠 *Ask yourself:* "Would this change break someone's code if they used it last week?"
 
-Before running your tests, setup all packages by running:
+### 2. Code Quality Standards
+
+**All Python code MUST include type hints and return types.**
+
+❌ **Bad:**
+
+```python
+def p(u, d):
+    return [x for x in u if x not in d]
+```
+
+✅ **Good:**
+
+```python
+def filter_unknown_users(users: list[str], known_users: set[str]) -> list[str]:
+    """Filter out users that are not in the known users set.
+
+    Args:
+        users: List of user identifiers to filter.
+        known_users: Set of known/valid user identifiers.
+
+    Returns:
+        List of users that are not in the known_users set.
+    """
+    return [user for user in users if user not in known_users]
+```
+
+**Style Requirements:**
+
+- Use descriptive, **self-explanatory variable names**. Avoid overly short or cryptic identifiers.
+- Attempt to break up complex functions (>20 lines) into smaller, focused functions where it makes sense
+- Avoid unnecessary abstraction or premature optimization
+- Follow existing patterns in the codebase you're modifying
+
+### 3. Testing Requirements
+
+**Every new feature or bugfix MUST be covered by unit tests.**
+
+**Test Organization:**
+
+- Unit tests: `tests/unit_tests/` (no network calls allowed)
+- Integration tests: `tests/integration_tests/` (network calls permitted)
+- Use `pytest` as the testing framework
+
+**Test Quality Checklist:**
+
+- [ ] Tests fail when your new logic is broken
+- [ ] Happy path is covered
+- [ ] Edge cases and error conditions are tested
+- [ ] Use fixtures/mocks for external dependencies
+- [ ] Tests are deterministic (no flaky tests)
+
+Checklist questions:
+
+- [ ] Does the test suite fail if your new logic is broken?
+- [ ] Are all expected behaviors exercised (happy path, invalid input, etc)?
+- [ ] Do tests use fixtures or mocks where needed?
+
+```python
+def test_filter_unknown_users():
+    """Test filtering unknown users from a list."""
+    users = ["alice", "bob", "charlie"]
+    known_users = {"alice", "bob"}
+
+    result = filter_unknown_users(users, known_users)
+
+    assert result == ["charlie"]
+    assert len(result) == 1
+```
+
+### 4. Security and Risk Assessment
+
+**Security Checklist:**
+
+- No `eval()`, `exec()`, or `pickle` on user-controlled input
+- Proper exception handling (no bare `except:`) and use a `msg` variable for error messages
+- Remove unreachable/commented code before committing
+- Race conditions or resource leaks (file handles, sockets, threads).
+- Ensure proper resource cleanup (file handles, connections)
+
+❌ **Bad:**
+
+```python
+def load_config(path):
+    with open(path) as f:
+        return eval(f.read())  # ⚠️ Never eval config
+```
+
+✅ **Good:**
+
+```python
+import json
+
+def load_config(path: str) -> dict:
+    with open(path) as f:
+        return json.load(f)
+```
+
+### 5. Documentation Standards
+
+**Use Google-style docstrings with Args section for all public functions.**
+
+❌ **Insufficient Documentation:**
+
+```python
+def send_email(to, msg):
+    """Send an email to a recipient."""
+```
+
+✅ **Complete Documentation:**
+
+```python
+def send_email(to: str, msg: str, *, priority: str = "normal") -> bool:
+    """
+    Send an email to a recipient with specified priority.
+
+    Args:
+        to: The email address of the recipient.
+        msg: The message body to send.
+        priority: Email priority level (`'low'`, `'normal'`, `'high'`).
+
+    Returns:
+        `True` if email was sent successfully, `False` otherwise.
+
+    Raises:
+        `InvalidEmailError`: If the email address format is invalid.
+        `SMTPConnectionError`: If unable to connect to email server.
+    """
+```
+
+**Documentation Guidelines:**
+
+- Types go in function signatures, NOT in docstrings
+  - If a default is present, DO NOT repeat it in the docstring unless there is post-processing or it is set conditionally.
+- Focus on "why" rather than "what" in descriptions
+- Document all parameters, return values, and exceptions
+- Keep descriptions concise but clear
+- Ensure American English spelling (e.g., "behavior", not "behaviour")
+
+📌 *Tip:* Keep descriptions concise but clear. Only document return values if non-obvious.
+
+### 6. Architectural Improvements
+
+**When you encounter code that could be improved, suggest better designs:**
+
+❌ **Poor Design:**
+
+```python
+def process_data(data, db_conn, email_client, logger):
+    # Function doing too many things
+    validated = validate_data(data)
+    result = db_conn.save(validated)
+    email_client.send_notification(result)
+    logger.log(f"Processed {len(data)} items")
+    return result
+```
+
+✅ **Better Design:**
+
+```python
+@dataclass
+class ProcessingResult:
+    """Result of data processing operation."""
+    items_processed: int
+    success: bool
+    errors: List[str] = field(default_factory=list)
+
+class DataProcessor:
+    """Handles data validation, storage, and notification."""
+
+    def __init__(self, db_conn: Database, email_client: EmailClient):
+        self.db = db_conn
+        self.email = email_client
+
+    def process(self, data: List[dict]) -> ProcessingResult:
+        """Process and store data with notifications."""
+        validated = self._validate_data(data)
+        result = self.db.save(validated)
+        self._notify_completion(result)
+        return result
+```
+
+**Design Improvement Areas:**
+
+If there's a **cleaner**, **more scalable**, or **simpler** design, highlight it and suggest improvements that would:
+
+- Reduce code duplication through shared utilities
+- Make unit testing easier
+- Improve separation of concerns (single responsibility)
+- Make unit testing easier through dependency injection
+- Add clarity without adding complexity
+- Prefer dataclasses for structured data
+
+## Development Tools & Commands
+
+### Package Management
 
 ```bash
-# For all groups
-uv sync --all-groups
+# Add package
+uv add package-name
 
-# or, to install a specific group only:
-uv sync --group test
+# Sync project dependencies
+uv sync
+uv lock
 ```
 
+### Testing
+
 ```bash
 # Run unit tests (no network)
 make test
 
+# Don't run integration tests, as API keys must be set
+
 # Run specific test file
 uv run --group test pytest tests/unit_tests/test_specific.py
 ```
 
+### Code Quality
+
 ```bash
 # Lint code
 make lint
@@ -73,127 +261,66 @@ make format
 uv run --group lint mypy .
 ```
 
-#### Key config files
+### Dependency Management Patterns
 
-- pyproject.toml: Main workspace configuration with dependency groups
-- uv.lock: Locked dependencies for reproducible builds
-- Makefile: Development tasks
+**Local Development Dependencies:**
 
-#### Commit standards
-
-Suggest PR titles that follow Conventional Commits format. Refer to .github/workflows/pr_lint for allowed types and scopes. Note that all commit/PR titles should be in lowercase with the exception of proper nouns/named entities. All PR titles should include a scope with no exceptions. For example:
-
-```txt
-feat(langchain): add new chat completion feature
-fix(core): resolve type hinting issue in vector store
-chore(anthropic): update infrastructure dependencies
+```toml
+[tool.uv.sources]
+langchain-core = { path = "../core", editable = true }
+langchain-tests = { path = "../standard-tests", editable = true }
 ```
 
-Note how `feat(langchain)` includes a scope even though it is the main package and name of the repo.
+**For tools, use the `@tool` decorator from `langchain_core.tools`:**
 
-#### Pull request guidelines
+```python
+from langchain_core.tools import tool
 
-- Always add a disclaimer to the PR description mentioning how AI agents are involved with the contribution.
-- Describe the "why" of the changes, why the proposed solution is the right one. Limit prose.
-- Highlight areas of the proposed changes that require careful review.
-
-## Core development principles
-
-### Maintain stable public interfaces
-
-CRITICAL: Always attempt to preserve function signatures, argument positions, and names for exported/public methods. Do not make breaking changes.
-You should warn the developer for any function signature changes, regardless of whether they look breaking or not.
-
-**Before making ANY changes to public APIs:**
-
-- Check if the function/class is exported in `__init__.py`
-- Look for existing usage patterns in tests and examples
-- Use keyword-only arguments for new parameters: `*, new_param: str = "default"`
-- Mark experimental features clearly with docstring warnings (using MkDocs Material admonitions, like `!!! warning`)
-
-Ask: "Would this change break someone's code if they used it last week?"
-
-### Code quality standards
-
-All Python code MUST include type hints and return types.
-
-```python title="Example"
-def filter_unknown_users(users: list[str], known_users: set[str]) -> list[str]:
-    """Single line description of the function.
-
-    Any additional context about the function can go here.
+@tool
+def search_database(query: str) -> str:
+    """Search the database for relevant information.
 
     Args:
-        users: List of user identifiers to filter.
-        known_users: Set of known/valid user identifiers.
-
-    Returns:
-        List of users that are not in the `known_users` set.
+        query: The search query string.
     """
+    # Implementation here
+    return results
 ```
 
-- Use descriptive, self-explanatory variable names.
-- Follow existing patterns in the codebase you're modifying
-- Attempt to break up complex functions (>20 lines) into smaller, focused functions where it makes sense
+## Commit Standards
 
-### Testing requirements
+**Use Conventional Commits format for PR titles:**
 
-Every new feature or bugfix MUST be covered by unit tests.
+- `feat(core): add multi-tenant support`
+- `fix(cli): resolve flag parsing error`
+- `docs: update API usage examples`
+- `docs(openai): update API usage examples`
 
-- Unit tests: `tests/unit_tests/` (no network calls allowed)
-- Integration tests: `tests/integration_tests/` (network calls permitted)
-- We use `pytest` as the testing framework; if in doubt, check other existing tests for examples.
-- The testing file structure should mirror the source code structure.
+## Framework-Specific Guidelines
 
-**Checklist:**
+- Follow the existing patterns in `langchain-core` for base abstractions
+- Use `langchain_core.callbacks` for execution tracking
+- Implement proper streaming support where applicable
+- Avoid deprecated components like legacy `LLMChain`
 
-- [ ] Tests fail when your new logic is broken
-- [ ] Happy path is covered
-- [ ] Edge cases and error conditions are tested
-- [ ] Use fixtures/mocks for external dependencies
-- [ ] Tests are deterministic (no flaky tests)
-- [ ] Does the test suite fail if your new logic is broken?
+### Partner Integrations
 
-### Security and risk assessment
+- Follow the established patterns in existing partner libraries
+- Implement standard interfaces (`BaseChatModel`, `BaseEmbeddings`, etc.)
+- Include comprehensive integration tests
+- Document API key requirements and authentication
 
-- No `eval()`, `exec()`, or `pickle` on user-controlled input
-- Proper exception handling (no bare `except:`) and use a `msg` variable for error messages
-- Remove unreachable/commented code before committing
-- Race conditions or resource leaks (file handles, sockets, threads).
-- Ensure proper resource cleanup (file handles, connections)
+---
 
-### Documentation standards
+## Quick Reference Checklist
 
-Use Google-style docstrings with Args section for all public functions.
+Before submitting code changes:
 
-```python title="Example"
-def send_email(to: str, msg: str, *, priority: str = "normal") -> bool:
-    """Send an email to a recipient with specified priority.
-
-    Any additional context about the function can go here.
-
-    Args:
-        to: The email address of the recipient.
-        msg: The message body to send.
-        priority: Email priority level.
-
-    Returns:
-        `True` if email was sent successfully, `False` otherwise.
-
-    Raises:
-        InvalidEmailError: If the email address format is invalid.
-        SMTPConnectionError: If unable to connect to email server.
-    """
-```
-
-- Types go in function signatures, NOT in docstrings
-  - If a default is present, DO NOT repeat it in the docstring unless there is post-processing or it is set conditionally.
-- Focus on "why" rather than "what" in descriptions
-- Document all parameters, return values, and exceptions
-- Keep descriptions concise but clear
-- Ensure American English spelling (e.g., "behavior", not "behaviour")
-
-## Additional resources
-
-- **Documentation:** https://docs.langchain.com/oss/python/langchain/overview and source at https://github.com/langchain-ai/docs or `../docs/`. Prefer the local install and use file search tools for best results. If needed, use the docs MCP server as defined in `.mcp.json` for programmatic access.
-- **Contributing Guide:** [Contributing Guide](https://docs.langchain.com/oss/python/contributing/overview)
+- [ ] **Breaking Changes**: Verified no public API changes
+- [ ] **Type Hints**: All functions have complete type annotations
+- [ ] **Tests**: New functionality is fully tested
+- [ ] **Security**: No dangerous patterns (eval, silent failures, etc.)
+- [ ] **Documentation**: Google-style docstrings for public functions
+- [ ] **Code Quality**: `make lint` and `make format` pass
+- [ ] **Architecture**: Suggested improvements where applicable
+- [ ] **Commit Message**: Follows Conventional Commits format

CLAUDE.md

@@ -1,67 +1,255 @@
-# Global development guidelines for the LangChain monorepo
+# Global Development Guidelines for LangChain Projects
 
-This document provides context to understand the LangChain Python project and assist with development.
+## Core Development Principles
 
-## Project architecture and context
+### 1. Maintain Stable Public Interfaces ⚠️ CRITICAL
 
-### Monorepo structure
+**Always attempt to preserve function signatures, argument positions, and names for exported/public methods.**
 
-This is a Python monorepo with multiple independently versioned packages that use `uv`.
+❌ **Bad - Breaking Change:**
 
-```txt
-langchain/
-├── libs/
-│   ├── core/             # `langchain-core` primitives and base abstractions
-│   ├── langchain/        # `langchain-classic` (legacy, no new features)
-│   ├── langchain_v1/     # Actively maintained `langchain` package
-│   ├── partners/         # Third-party integrations
-│   │   ├── openai/       # OpenAI models and embeddings
-│   │   ├── anthropic/    # Anthropic (Claude) integration
-│   │   ├── ollama/       # Local model support
-│   │   └── ... (other integrations maintained by the LangChain team)
-│   ├── text-splitters/   # Document chunking utilities
-│   ├── standard-tests/   # Shared test suite for integrations
-│   ├── model-profiles/   # Model configuration profiles
-├── .github/              # CI/CD workflows and templates
-├── .vscode/              # VSCode IDE standard settings and recommended extensions
-└── README.md             # Information about LangChain
+```python
+def get_user(id, verbose=False):  # Changed from `user_id`
+    pass
 ```
 
-- **Core layer** (`langchain-core`): Base abstractions, interfaces, and protocols. Users should not need to know about this layer directly.
-- **Implementation layer** (`langchain`): Concrete implementations and high-level public utilities
-- **Integration layer** (`partners/`): Third-party service integrations. Note that this monorepo is not exhaustive of all LangChain integrations; some are maintained in separate repos, such as `langchain-ai/langchain-google` and `langchain-ai/langchain-aws`. Usually these repos are cloned at the same level as this monorepo, so if needed, you can refer to their code directly by navigating to `../langchain-google/` from this monorepo.
-- **Testing layer** (`standard-tests/`): Standardized integration tests for partner integrations
+✅ **Good - Stable Interface:**
 
-### Development tools & commands
+```python
+def get_user(user_id: str, verbose: bool = False) -> User:
+    """Retrieve user by ID with optional verbose output."""
+    pass
+```
 
-- `uv` – Fast Python package installer and resolver (replaces pip/poetry)
-- `make` – Task runner for common development commands. Feel free to look at the `Makefile` for available commands and usage patterns.
-- `ruff` – Fast Python linter and formatter
-- `mypy` – Static type checking
-- `pytest` – Testing framework
+**Before making ANY changes to public APIs:**
 
-This monorepo uses `uv` for dependency management. Local development uses editable installs: `[tool.uv.sources]`
+- Check if the function/class is exported in `__init__.py`
+- Look for existing usage patterns in tests and examples
+- Use keyword-only arguments for new parameters: `*, new_param: str = "default"`
+- Mark experimental features clearly with docstring warnings (using MkDocs Material admonitions, like `!!! warning`)
 
-Each package in `libs/` has its own `pyproject.toml` and `uv.lock`.
+🧠 *Ask yourself:* "Would this change break someone's code if they used it last week?"
 
-Before running your tests, setup all packages by running:
+### 2. Code Quality Standards
+
+**All Python code MUST include type hints and return types.**
+
+❌ **Bad:**
+
+```python
+def p(u, d):
+    return [x for x in u if x not in d]
+```
+
+✅ **Good:**
+
+```python
+def filter_unknown_users(users: list[str], known_users: set[str]) -> list[str]:
+    """Filter out users that are not in the known users set.
+
+    Args:
+        users: List of user identifiers to filter.
+        known_users: Set of known/valid user identifiers.
+
+    Returns:
+        List of users that are not in the known_users set.
+    """
+    return [user for user in users if user not in known_users]
+```
+
+**Style Requirements:**
+
+- Use descriptive, **self-explanatory variable names**. Avoid overly short or cryptic identifiers.
+- Attempt to break up complex functions (>20 lines) into smaller, focused functions where it makes sense
+- Avoid unnecessary abstraction or premature optimization
+- Follow existing patterns in the codebase you're modifying
+
+### 3. Testing Requirements
+
+**Every new feature or bugfix MUST be covered by unit tests.**
+
+**Test Organization:**
+
+- Unit tests: `tests/unit_tests/` (no network calls allowed)
+- Integration tests: `tests/integration_tests/` (network calls permitted)
+- Use `pytest` as the testing framework
+
+**Test Quality Checklist:**
+
+- [ ] Tests fail when your new logic is broken
+- [ ] Happy path is covered
+- [ ] Edge cases and error conditions are tested
+- [ ] Use fixtures/mocks for external dependencies
+- [ ] Tests are deterministic (no flaky tests)
+
+Checklist questions:
+
+- [ ] Does the test suite fail if your new logic is broken?
+- [ ] Are all expected behaviors exercised (happy path, invalid input, etc)?
+- [ ] Do tests use fixtures or mocks where needed?
+
+```python
+def test_filter_unknown_users():
+    """Test filtering unknown users from a list."""
+    users = ["alice", "bob", "charlie"]
+    known_users = {"alice", "bob"}
+
+    result = filter_unknown_users(users, known_users)
+
+    assert result == ["charlie"]
+    assert len(result) == 1
+```
+
+### 4. Security and Risk Assessment
+
+**Security Checklist:**
+
+- No `eval()`, `exec()`, or `pickle` on user-controlled input
+- Proper exception handling (no bare `except:`) and use a `msg` variable for error messages
+- Remove unreachable/commented code before committing
+- Race conditions or resource leaks (file handles, sockets, threads).
+- Ensure proper resource cleanup (file handles, connections)
+
+❌ **Bad:**
+
+```python
+def load_config(path):
+    with open(path) as f:
+        return eval(f.read())  # ⚠️ Never eval config
+```
+
+✅ **Good:**
+
+```python
+import json
+
+def load_config(path: str) -> dict:
+    with open(path) as f:
+        return json.load(f)
+```
+
+### 5. Documentation Standards
+
+**Use Google-style docstrings with Args section for all public functions.**
+
+❌ **Insufficient Documentation:**
+
+```python
+def send_email(to, msg):
+    """Send an email to a recipient."""
+```
+
+✅ **Complete Documentation:**
+
+```python
+def send_email(to: str, msg: str, *, priority: str = "normal") -> bool:
+    """
+    Send an email to a recipient with specified priority.
+
+    Args:
+        to: The email address of the recipient.
+        msg: The message body to send.
+        priority: Email priority level (`'low'`, `'normal'`, `'high'`).
+
+    Returns:
+        `True` if email was sent successfully, `False` otherwise.
+
+    Raises:
+        `InvalidEmailError`: If the email address format is invalid.
+        `SMTPConnectionError`: If unable to connect to email server.
+    """
+```
+
+**Documentation Guidelines:**
+
+- Types go in function signatures, NOT in docstrings
+  - If a default is present, DO NOT repeat it in the docstring unless there is post-processing or it is set conditionally.
+- Focus on "why" rather than "what" in descriptions
+- Document all parameters, return values, and exceptions
+- Keep descriptions concise but clear
+- Ensure American English spelling (e.g., "behavior", not "behaviour")
+
+📌 *Tip:* Keep descriptions concise but clear. Only document return values if non-obvious.
+
+### 6. Architectural Improvements
+
+**When you encounter code that could be improved, suggest better designs:**
+
+❌ **Poor Design:**
+
+```python
+def process_data(data, db_conn, email_client, logger):
+    # Function doing too many things
+    validated = validate_data(data)
+    result = db_conn.save(validated)
+    email_client.send_notification(result)
+    logger.log(f"Processed {len(data)} items")
+    return result
+```
+
+✅ **Better Design:**
+
+```python
+@dataclass
+class ProcessingResult:
+    """Result of data processing operation."""
+    items_processed: int
+    success: bool
+    errors: List[str] = field(default_factory=list)
+
+class DataProcessor:
+    """Handles data validation, storage, and notification."""
+
+    def __init__(self, db_conn: Database, email_client: EmailClient):
+        self.db = db_conn
+        self.email = email_client
+
+    def process(self, data: List[dict]) -> ProcessingResult:
+        """Process and store data with notifications."""
+        validated = self._validate_data(data)
+        result = self.db.save(validated)
+        self._notify_completion(result)
+        return result
+```
+
+**Design Improvement Areas:**
+
+If there's a **cleaner**, **more scalable**, or **simpler** design, highlight it and suggest improvements that would:
+
+- Reduce code duplication through shared utilities
+- Make unit testing easier
+- Improve separation of concerns (single responsibility)
+- Make unit testing easier through dependency injection
+- Add clarity without adding complexity
+- Prefer dataclasses for structured data
+
+## Development Tools & Commands
+
+### Package Management
 
 ```bash
-# For all groups
-uv sync --all-groups
+# Add package
+uv add package-name
 
-# or, to install a specific group only:
-uv sync --group test
+# Sync project dependencies
+uv sync
+uv lock
 ```
 
+### Testing
+
 ```bash
 # Run unit tests (no network)
 make test
 
+# Don't run integration tests, as API keys must be set
+
 # Run specific test file
 uv run --group test pytest tests/unit_tests/test_specific.py
 ```
 
+### Code Quality
+
 ```bash
 # Lint code
 make lint
@@ -73,127 +261,66 @@ make format
 uv run --group lint mypy .
 ```
 
-#### Key config files
+### Dependency Management Patterns
 
-- pyproject.toml: Main workspace configuration with dependency groups
-- uv.lock: Locked dependencies for reproducible builds
-- Makefile: Development tasks
+**Local Development Dependencies:**
 
-#### Commit standards
-
-Suggest PR titles that follow Conventional Commits format. Refer to .github/workflows/pr_lint for allowed types and scopes. Note that all commit/PR titles should be in lowercase with the exception of proper nouns/named entities. All PR titles should include a scope with no exceptions. For example:
-
-```txt
-feat(langchain): add new chat completion feature
-fix(core): resolve type hinting issue in vector store
-chore(anthropic): update infrastructure dependencies
+```toml
+[tool.uv.sources]
+langchain-core = { path = "../core", editable = true }
+langchain-tests = { path = "../standard-tests", editable = true }
 ```
 
-Note how `feat(langchain)` includes a scope even though it is the main package and name of the repo.
+**For tools, use the `@tool` decorator from `langchain_core.tools`:**
 
-#### Pull request guidelines
+```python
+from langchain_core.tools import tool
 
-- Always add a disclaimer to the PR description mentioning how AI agents are involved with the contribution.
-- Describe the "why" of the changes, why the proposed solution is the right one. Limit prose.
-- Highlight areas of the proposed changes that require careful review.
-
-## Core development principles
-
-### Maintain stable public interfaces
-
-CRITICAL: Always attempt to preserve function signatures, argument positions, and names for exported/public methods. Do not make breaking changes.
-You should warn the developer for any function signature changes, regardless of whether they look breaking or not.
-
-**Before making ANY changes to public APIs:**
-
-- Check if the function/class is exported in `__init__.py`
-- Look for existing usage patterns in tests and examples
-- Use keyword-only arguments for new parameters: `*, new_param: str = "default"`
-- Mark experimental features clearly with docstring warnings (using MkDocs Material admonitions, like `!!! warning`)
-
-Ask: "Would this change break someone's code if they used it last week?"
-
-### Code quality standards
-
-All Python code MUST include type hints and return types.
-
-```python title="Example"
-def filter_unknown_users(users: list[str], known_users: set[str]) -> list[str]:
-    """Single line description of the function.
-
-    Any additional context about the function can go here.
+@tool
+def search_database(query: str) -> str:
+    """Search the database for relevant information.
 
     Args:
-        users: List of user identifiers to filter.
-        known_users: Set of known/valid user identifiers.
-
-    Returns:
-        List of users that are not in the `known_users` set.
+        query: The search query string.
     """
+    # Implementation here
+    return results
 ```
 
-- Use descriptive, self-explanatory variable names.
-- Follow existing patterns in the codebase you're modifying
-- Attempt to break up complex functions (>20 lines) into smaller, focused functions where it makes sense
+## Commit Standards
 
-### Testing requirements
+**Use Conventional Commits format for PR titles:**
 
-Every new feature or bugfix MUST be covered by unit tests.
+- `feat(core): add multi-tenant support`
+- `fix(cli): resolve flag parsing error`
+- `docs: update API usage examples`
+- `docs(openai): update API usage examples`
 
-- Unit tests: `tests/unit_tests/` (no network calls allowed)
-- Integration tests: `tests/integration_tests/` (network calls permitted)
-- We use `pytest` as the testing framework; if in doubt, check other existing tests for examples.
-- The testing file structure should mirror the source code structure.
+## Framework-Specific Guidelines
 
-**Checklist:**
+- Follow the existing patterns in `langchain-core` for base abstractions
+- Use `langchain_core.callbacks` for execution tracking
+- Implement proper streaming support where applicable
+- Avoid deprecated components like legacy `LLMChain`
 
-- [ ] Tests fail when your new logic is broken
-- [ ] Happy path is covered
-- [ ] Edge cases and error conditions are tested
-- [ ] Use fixtures/mocks for external dependencies
-- [ ] Tests are deterministic (no flaky tests)
-- [ ] Does the test suite fail if your new logic is broken?
+### Partner Integrations
 
-### Security and risk assessment
+- Follow the established patterns in existing partner libraries
+- Implement standard interfaces (`BaseChatModel`, `BaseEmbeddings`, etc.)
+- Include comprehensive integration tests
+- Document API key requirements and authentication
 
-- No `eval()`, `exec()`, or `pickle` on user-controlled input
-- Proper exception handling (no bare `except:`) and use a `msg` variable for error messages
-- Remove unreachable/commented code before committing
-- Race conditions or resource leaks (file handles, sockets, threads).
-- Ensure proper resource cleanup (file handles, connections)
+---
 
-### Documentation standards
+## Quick Reference Checklist
 
-Use Google-style docstrings with Args section for all public functions.
+Before submitting code changes:
 
-```python title="Example"
-def send_email(to: str, msg: str, *, priority: str = "normal") -> bool:
-    """Send an email to a recipient with specified priority.
-
-    Any additional context about the function can go here.
-
-    Args:
-        to: The email address of the recipient.
-        msg: The message body to send.
-        priority: Email priority level.
-
-    Returns:
-        `True` if email was sent successfully, `False` otherwise.
-
-    Raises:
-        InvalidEmailError: If the email address format is invalid.
-        SMTPConnectionError: If unable to connect to email server.
-    """
-```
-
-- Types go in function signatures, NOT in docstrings
-  - If a default is present, DO NOT repeat it in the docstring unless there is post-processing or it is set conditionally.
-- Focus on "why" rather than "what" in descriptions
-- Document all parameters, return values, and exceptions
-- Keep descriptions concise but clear
-- Ensure American English spelling (e.g., "behavior", not "behaviour")
-
-## Additional resources
-
-- **Documentation:** https://docs.langchain.com/oss/python/langchain/overview and source at https://github.com/langchain-ai/docs or `../docs/`. Prefer the local install and use file search tools for best results. If needed, use the docs MCP server as defined in `.mcp.json` for programmatic access.
-- **Contributing Guide:** [Contributing Guide](https://docs.langchain.com/oss/python/contributing/overview)
+- [ ] **Breaking Changes**: Verified no public API changes
+- [ ] **Type Hints**: All functions have complete type annotations
+- [ ] **Tests**: New functionality is fully tested
+- [ ] **Security**: No dangerous patterns (eval, silent failures, etc.)
+- [ ] **Documentation**: Google-style docstrings for public functions
+- [ ] **Code Quality**: `make lint` and `make format` pass
+- [ ] **Architecture**: Suggested improvements where applicable
+- [ ] **Commit Message**: Follows Conventional Commits format

CONTRIBUTING.md

@@ -1,15 +0,0 @@
-# Contributing to LangChain
-
-Thanks for your interest in contributing to LangChain!
-
-We have moved our contributing guidelines to our documentation site to keep them up-to-date and easy to access.
-
-👉 **[Read the Contributing Guide](https://docs.langchain.com/oss/python/contributing/overview)**
-
-This guide includes instructions on:
-- How to set up your development environment
-- How to run tests and linting
-- How to submit a Pull Request
-- Coding standards and best practices
-
-We look forward to your contributions!

MIGRATE.md

@@ -0,0 +1,8 @@
+# Migrating
+
+Please see the following guides for migrating LangChain code:
+
+* Migrate to [LangChain v0.3](https://python.langchain.com/docs/versions/v0_3/)
+* Migrate to [LangChain v0.2](https://python.langchain.com/docs/versions/v0_2/)
+* Migrating from [LangChain 0.0.x Chains](https://python.langchain.com/docs/versions/migrating_chains/)
+* Upgrade to [LangGraph Memory](https://python.langchain.com/docs/versions/migrating_memory/)

README.md

@@ -1,44 +1,50 @@
-<div align="center">
-  <a href="https://www.langchain.com/">
-    <picture>
-      <source media="(prefers-color-scheme: light)" srcset=".github/images/logo-dark.svg">
-      <source media="(prefers-color-scheme: dark)" srcset=".github/images/logo-light.svg">
-      <img alt="LangChain Logo" src=".github/images/logo-dark.svg" width="80%">
-    </picture>
+<p align="center">
+  <picture>
+    <source media="(prefers-color-scheme: light)" srcset=".github/images/logo-dark.svg">
+    <source media="(prefers-color-scheme: dark)" srcset=".github/images/logo-light.svg">
+    <img alt="LangChain Logo" src=".github/images/logo-dark.svg" width="80%">
+  </picture>
+</p>
+
+<p align="center">
+    The platform for reliable agents.
+</p>
+
+<p align="center">
+  <a href="https://opensource.org/licenses/MIT" target="_blank">
+      <img src="https://img.shields.io/pypi/l/langchain" alt="PyPI - License">
   </a>
-</div>
+  <a href="https://pypistats.org/packages/langchain" target="_blank">
+      <img src="https://img.shields.io/pepy/dt/langchain" alt="PyPI - Downloads">
+  </a>
+  <a href="https://pypi.org/project/langchain/#history" target="_blank">
+      <img src="https://img.shields.io/pypi/v/langchain?label=%20" alt="Version">
+  </a>
+  <a href="https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/langchain-ai/langchain" target="_blank">
+      <img src="https://img.shields.io/static/v1?label=Dev%20Containers&message=Open&color=blue&logo=visualstudiocode" alt="Open in Dev Containers">
+  </a>
+  <a href="https://codespaces.new/langchain-ai/langchain" target="_blank">
+      <img src="https://github.com/codespaces/badge.svg" alt="Open in Github Codespace" title="Open in Github Codespace" width="150" height="20">
+  </a>
+  <a href="https://codspeed.io/langchain-ai/langchain" target="_blank">
+      <img src="https://img.shields.io/endpoint?url=https://codspeed.io/badge.json" alt="CodSpeed Badge">
+  </a>
+  <a href="https://twitter.com/langchainai" target="_blank">
+      <img src="https://img.shields.io/twitter/url/https/twitter.com/langchainai.svg?style=social&label=Follow%20%40LangChainAI" alt="Twitter / X">
+  </a>
+</p>
 
-<div align="center">
-  <h3>The platform for reliable agents.</h3>
-</div>
-
-<div align="center">
-  <a href="https://opensource.org/licenses/MIT" target="_blank"><img src="https://img.shields.io/pypi/l/langchain" alt="PyPI - License"></a>
-  <a href="https://pypistats.org/packages/langchain" target="_blank"><img src="https://img.shields.io/pepy/dt/langchain" alt="PyPI - Downloads"></a>
-  <a href="https://pypi.org/project/langchain/#history" target="_blank"><img src="https://img.shields.io/pypi/v/langchain?label=%20" alt="Version"></a>
-  <a href="https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/langchain-ai/langchain" target="_blank"><img src="https://img.shields.io/static/v1?label=Dev%20Containers&message=Open&color=blue&logo=visualstudiocode" alt="Open in Dev Containers"></a>
-  <a href="https://codespaces.new/langchain-ai/langchain" target="_blank"><img src="https://github.com/codespaces/badge.svg" alt="Open in Github Codespace" title="Open in Github Codespace" width="150" height="20"></a>
-  <a href="https://codspeed.io/langchain-ai/langchain" target="_blank"><img src="https://img.shields.io/endpoint?url=https://codspeed.io/badge.json" alt="CodSpeed Badge"></a>
-  <a href="https://x.com/langchain" target="_blank"><img src="https://img.shields.io/twitter/url/https/twitter.com/langchain.svg?style=social&label=Follow%20%40LangChain" alt="Twitter / X"></a>
-</div>
-
-LangChain is a framework for building agents and 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.
+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
 ```
 
-If you're looking for more advanced customization or agent orchestration, check out [LangGraph](https://docs.langchain.com/oss/python/langgraph/overview), our framework for building controllable agent workflows.
-
 ---
 
-**Documentation**:
+**Documentation**: To learn more about LangChain, check out [the docs](https://docs.langchain.com/oss/python/langchain/overview).
 
-- [docs.langchain.com](https://docs.langchain.com/oss/python/langchain/overview) – Comprehensive documentation, including conceptual overviews and guides
-- [reference.langchain.com/python](https://reference.langchain.com/python) – API reference docs for LangChain packages
-- [Chat LangChain](https://chat.langchain.com/) – Chat with the LangChain documentation and get answers to your questions
-
-**Discussions**: Visit the [LangChain Forum](https://forum.langchain.com) to connect with the community and share all of your technical questions, ideas, and feedback.
+If you're looking for more advanced customization or agent orchestration, check out [LangGraph](https://docs.langchain.com/oss/python/langgraph/overview), our framework for building controllable agent workflows.
 
 > [!NOTE]
 > Looking for the JS/TS library? Check out [LangChain.js](https://github.com/langchain-ai/langchainjs).
@@ -49,28 +55,23 @@ LangChain helps developers build applications powered by LLMs through a standard
 
 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.
-- **Rapid prototyping**. Quickly build and iterate on LLM applications with LangChain's modular, component-based architecture. Test different approaches and workflows without rebuilding from scratch, accelerating your development cycle.
-- **Production-ready features**. Deploy reliable applications with built-in support for monitoring, evaluation, and debugging through integrations like LangSmith. Scale with confidence using battle-tested patterns and best practices.
-- **Vibrant community and ecosystem**. Leverage a rich ecosystem of integrations, templates, and community-contributed components. Benefit from continuous improvements and stay up-to-date with the latest AI developments through an active open-source community.
-- **Flexible abstraction layers**. Work at the level of abstraction that suits your needs - from high-level chains for quick starts to low-level components for fine-grained control. LangChain grows with your application's complexity.
+- **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.
 
-## LangChain ecosystem
+## 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:
 
-- [Deep Agents](https://github.com/langchain-ai/deepagents) *(new!)* – Build agents that can plan, use subagents, and leverage file systems for complex tasks
-- [LangGraph](https://docs.langchain.com/oss/python/langgraph/overview) – 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.
-- [Integrations](https://docs.langchain.com/oss/python/integrations/providers/overview) – List of LangChain integrations, including chat & embedding models, tools & toolkits, and more
-- [LangSmith](https://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.
-- [LangSmith Deployment](https://docs.langchain.com/langsmith/deployments) – 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 [LangSmith Studio](https://docs.langchain.com/langsmith/studio).
+- [LangSmith](https://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://docs.langchain.com/oss/python/langgraph/overview) - 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://docs.langchain.com/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).
 
 ## Additional resources
 
-- [API Reference](https://reference.langchain.com/python) – Detailed reference on navigating base packages and integrations for LangChain.
-- [Contributing Guide](https://docs.langchain.com/oss/python/contributing/overview) – Learn how to contribute to LangChain projects and find good first issues.
-- [Code of Conduct](https://github.com/langchain-ai/langchain/?tab=coc-ov-file) – Our community guidelines and standards for participation.
-- [LangChain Academy](https://academy.langchain.com/) – Comprehensive, free courses on LangChain libraries and products, made by the LangChain team.
+- [Learn](https://docs.langchain.com/oss/python/learn): Use cases, conceptual overviews, and more.
+- [API Reference](https://reference.langchain.com/python): Detailed reference on
+navigating base packages and integrations for LangChain.
+- [LangChain Forum](https://forum.langchain.com): Connect with the community and share all of your technical questions, ideas, and feedback.
+- [Chat LangChain](https://chat.langchain.com): Ask questions & chat with our documentation.

SECURITY.md

@@ -0,0 +1,80 @@
+# Security Policy
+
+LangChain has a large ecosystem of integrations with various external resources like local and remote file systems, APIs and databases. These integrations allow developers to create versatile applications that combine the power of LLMs with the ability to access, interact with and manipulate external resources.
+
+## Best practices
+
+When building such applications, developers should remember to follow good security practices:
+
+* [**Limit Permissions**](https://en.wikipedia.org/wiki/Principle_of_least_privilege): Scope permissions specifically to the application's need. Granting broad or excessive permissions can introduce significant security vulnerabilities. To avoid such vulnerabilities, consider using read-only credentials, disallowing access to sensitive resources, using sandboxing techniques (such as running inside a container), specifying proxy configurations to control external requests, etc., as appropriate for your application.
+* **Anticipate Potential Misuse**: Just as humans can err, so can Large Language Models (LLMs). Always assume that any system access or credentials may be used in any way allowed by the permissions they are assigned. For example, if a pair of database credentials allows deleting data, it's safest to assume that any LLM able to use those credentials may in fact delete data.
+* [**Defense in Depth**](https://en.wikipedia.org/wiki/Defense_in_depth_(computing)): No security technique is perfect. Fine-tuning and good chain design can reduce, but not eliminate, the odds that a Large Language Model (LLM) may make a mistake. It's best to combine multiple layered security approaches rather than relying on any single layer of defense to ensure security. For example: use both read-only permissions and sandboxing to ensure that LLMs are only able to access data that is explicitly meant for them to use.
+
+Risks of not doing so include, but are not limited to:
+
+* Data corruption or loss.
+* Unauthorized access to confidential information.
+* Compromised performance or availability of critical resources.
+
+Example scenarios with mitigation strategies:
+
+* A user may ask an agent with access to the file system to delete files that should not be deleted or read the content of files that contain sensitive information. To mitigate, limit the agent to only use a specific directory and only allow it to read or write files that are safe to read or write. Consider further sandboxing the agent by running it in a container.
+* A user may ask an agent with write access to an external API to write malicious data to the API, or delete data from that API. To mitigate, give the agent read-only API keys, or limit it to only use endpoints that are already resistant to such misuse.
+* A user may ask an agent with access to a database to drop a table or mutate the schema. To mitigate, scope the credentials to only the tables that the agent needs to access and consider issuing READ-ONLY credentials.
+
+If you're building applications that access external resources like file systems, APIs or databases, consider speaking with your company's security team to determine how to best design and secure your applications.
+
+## Reporting OSS Vulnerabilities
+
+LangChain is partnered with [huntr by Protect AI](https://huntr.com/) to provide
+a bounty program for our open source projects.
+
+Please report security vulnerabilities associated with the LangChain
+open source projects at [huntr](https://huntr.com/bounties/disclose/?target=https%3A%2F%2Fgithub.com%2Flangchain-ai%2Flangchain&validSearch=true).
+
+Before reporting a vulnerability, please review:
+
+1) In-Scope Targets and Out-of-Scope Targets below.
+2) The [langchain-ai/langchain](https://docs.langchain.com/oss/python/contributing/code#repository-structure) monorepo structure.
+3) The [Best Practices](#best-practices) above to understand what we consider to be a security vulnerability vs. developer responsibility.
+
+### In-Scope Targets
+
+The following packages and repositories are eligible for bug bounties:
+
+* langchain-core
+* langchain (see exceptions)
+* langchain-community (see exceptions)
+* langgraph
+* langserve
+
+### Out of Scope Targets
+
+All out of scope targets defined by huntr as well as:
+
+* **langchain-experimental**: This repository is for experimental code and is not
+  eligible for bug bounties (see [package warning](https://pypi.org/project/langchain-experimental/)), bug reports to it will be marked as interesting or waste of
+  time and published with no bounty attached.
+* **tools**: Tools in either langchain or langchain-community are not eligible for bug
+  bounties. This includes the following directories
+  * libs/langchain/langchain/tools
+  * libs/community/langchain_community/tools
+  * Please review the [Best Practices](#best-practices)
+    for more details, but generally tools interact with the real world. Developers are
+    expected to understand the security implications of their code and are responsible
+    for the security of their tools.
+* Code documented with security notices. This will be decided on a case-by-case basis, but likely will not be eligible for a bounty as the code is already
+  documented with guidelines for developers that should be followed for making their
+  application secure.
+* Any LangSmith related repositories or APIs (see [Reporting LangSmith Vulnerabilities](#reporting-langsmith-vulnerabilities)).
+
+## Reporting LangSmith Vulnerabilities
+
+Please report security vulnerabilities associated with LangSmith by email to `security@langchain.dev`.
+
+* LangSmith site: [https://smith.langchain.com](https://smith.langchain.com)
+* SDK client: [https://github.com/langchain-ai/langsmith-sdk](https://github.com/langchain-ai/langsmith-sdk)
+
+### Other Security Concerns
+
+For any other security concerns, please contact us at `security@langchain.dev`.

libs/Makefile

@@ -1,20 +0,0 @@
-# Makefile for libs/ directory
-# Contains targets that operate across multiple packages
-
-LANGCHAIN_DIRS = core text-splitters langchain langchain_v1 model-profiles
-
-.PHONY: lock check-lock
-
-# Regenerate lockfiles for all core packages
-lock:
-	@for dir in $(LANGCHAIN_DIRS); do \
-		echo "=== Locking $$dir ==="; \
-		(cd $$dir && uv lock); \
-	done
-
-# Verify all lockfiles are up-to-date
-check-lock:
-	@for dir in $(LANGCHAIN_DIRS); do \
-		echo "=== Checking $$dir ==="; \
-		(cd $$dir && uv lock --check) || exit 1; \
-	done

libs/cli/.gitignore

@@ -0,0 +1,159 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+.integration_test

libs/cli/DOCS.md

@@ -0,0 +1,189 @@
+# `langchain`
+
+**Usage**:
+
+```console
+$ langchain [OPTIONS] COMMAND [ARGS]...
+```
+
+**Options**:
+
+* `--help`: Show this message and exit.
+* `-v, --version`: Print current CLI version.
+
+**Commands**:
+
+* `app`: Manage LangChain apps
+* `serve`: Start the LangServe app, whether it's a...
+* `template`: Develop installable templates.
+
+## `langchain app`
+
+Manage LangChain apps
+
+**Usage**:
+
+```console
+$ langchain app [OPTIONS] COMMAND [ARGS]...
+```
+
+**Options**:
+
+* `--help`: Show this message and exit.
+
+**Commands**:
+
+* `add`: Adds the specified template to the current...
+* `new`: Create a new LangServe application.
+* `remove`: Removes the specified package from the...
+* `serve`: Starts the LangServe app.
+
+### `langchain app add`
+
+Adds the specified template to the current LangServe app.
+
+e.g.:
+langchain app add extraction-openai-functions
+langchain app add git+ssh://git@github.com/efriis/simple-pirate.git
+
+**Usage**:
+
+```console
+$ langchain app add [OPTIONS] [DEPENDENCIES]...
+```
+
+**Arguments**:
+
+* `[DEPENDENCIES]...`: The dependency to add
+
+**Options**:
+
+* `--api-path TEXT`: API paths to add
+* `--project-dir PATH`: The project directory
+* `--repo TEXT`: Install templates from a specific github repo instead
+* `--branch TEXT`: Install templates from a specific branch
+* `--help`: Show this message and exit.
+
+### `langchain app new`
+
+Create a new LangServe application.
+
+**Usage**:
+
+```console
+$ langchain app new [OPTIONS] NAME
+```
+
+**Arguments**:
+
+* `NAME`: The name of the folder to create  [required]
+
+**Options**:
+
+* `--package TEXT`: Packages to seed the project with
+* `--help`: Show this message and exit.
+
+### `langchain app remove`
+
+Removes the specified package from the current LangServe app.
+
+**Usage**:
+
+```console
+$ langchain app remove [OPTIONS] API_PATHS...
+```
+
+**Arguments**:
+
+* `API_PATHS...`: The API paths to remove  [required]
+
+**Options**:
+
+* `--help`: Show this message and exit.
+
+### `langchain app serve`
+
+Starts the LangServe app.
+
+**Usage**:
+
+```console
+$ langchain app serve [OPTIONS]
+```
+
+**Options**:
+
+* `--port INTEGER`: The port to run the server on
+* `--host TEXT`: The host to run the server on
+* `--app TEXT`: The app to run, e.g. `app.server:app`
+* `--help`: Show this message and exit.
+
+## `langchain serve`
+
+Start the LangServe app, whether it's a template or an app.
+
+**Usage**:
+
+```console
+$ langchain serve [OPTIONS]
+```
+
+**Options**:
+
+* `--port INTEGER`: The port to run the server on
+* `--host TEXT`: The host to run the server on
+* `--help`: Show this message and exit.
+
+## `langchain template`
+
+Develop installable templates.
+
+**Usage**:
+
+```console
+$ langchain template [OPTIONS] COMMAND [ARGS]...
+```
+
+**Options**:
+
+* `--help`: Show this message and exit.
+
+**Commands**:
+
+* `new`: Creates a new template package.
+* `serve`: Starts a demo app for this template.
+
+### `langchain template new`
+
+Creates a new template package.
+
+**Usage**:
+
+```console
+$ langchain template new [OPTIONS] NAME
+```
+
+**Arguments**:
+
+* `NAME`: The name of the folder to create  [required]
+
+**Options**:
+
+* `--with-poetry / --no-poetry`: Don't run poetry install  [default: no-poetry]
+* `--help`: Show this message and exit.
+
+### `langchain template serve`
+
+Starts a demo app for this template.
+
+**Usage**:
+
+```console
+$ langchain template serve [OPTIONS]
+```
+
+**Options**:
+
+* `--port INTEGER`: The port to run the server on
+* `--host TEXT`: The host to run the server on
+* `--help`: Show this message and exit.

libs/cli/LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) LangChain, Inc.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

libs/cli/Makefile

@@ -0,0 +1,53 @@
+
+######################
+# LINTING AND FORMATTING
+######################
+
+.EXPORT_ALL_VARIABLES:
+UV_FROZEN = true
+
+# Define a variable for Python and notebook files.
+PYTHON_FILES=.
+MYPY_CACHE=.mypy_cache
+lint format: PYTHON_FILES=.
+lint_diff format_diff: PYTHON_FILES=$(shell git diff --relative=libs/cli --name-only --diff-filter=d master | grep -E '\.py$$|\.ipynb$$')
+lint_package: PYTHON_FILES=langchain_cli
+lint_tests: PYTHON_FILES=tests
+lint_tests: MYPY_CACHE=.mypy_cache_test
+
+lint lint_diff lint_package lint_tests:
+	[ "$(PYTHON_FILES)" = "" ] || uv run --group typing --group lint ruff check $(PYTHON_FILES)
+	[ "$(PYTHON_FILES)" = "" ] || uv run --group typing --group lint ruff format $(PYTHON_FILES) --diff
+	[ "$(PYTHON_FILES)" = "" ] || mkdir -p $(MYPY_CACHE) && uv run --group typing --group lint mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE)
+
+format format_diff:
+	[ "$(PYTHON_FILES)" = "" ] || uv run --group typing --group lint ruff format $(PYTHON_FILES)
+	[ "$(PYTHON_FILES)" = "" ] || uv run --group typing --group lint ruff check --fix $(PYTHON_FILES)
+
+test tests: _test _e2e_test
+
+PYTHON = .venv/bin/python
+
+_test:
+	uv run --group test pytest tests
+
+# custom integration testing for cli integration flow
+# currently ignores vectorstores test because lacks implementation
+_e2e_test:
+	rm -rf .integration_test
+	mkdir .integration_test
+	cd .integration_test && \
+		python3 -m venv .venv && \
+		$(PYTHON) -m pip install --upgrade uv && \
+		$(PYTHON) -m pip install -e .. && \
+		$(PYTHON) -m langchain_cli.cli integration new --name parrot-link --name-class ParrotLink && \
+		$(PYTHON) -m langchain_cli.cli integration new --name parrot-link --name-class ParrotLinkB --src=integration_template/chat_models.py --dst=langchain-parrot-link/langchain_parrot_link/chat_models_b.py && \
+		$(PYTHON) -m langchain_cli.cli integration create-doc --name parrot-link --name-class ParrotLinkB --component-type ChatModel --destination-dir langchain-parrot-link/docs && \
+		cd langchain-parrot-link && \
+			unset UV_FROZEN && \
+			unset VIRTUAL_ENV && \
+			uv sync && \
+			uv add --editable ../../../standard-tests && \
+			make format lint tests && \
+			uv add --editable ../../../core && \
+			make integration_test 

libs/cli/README.md

@@ -0,0 +1,30 @@
+# langchain-cli
+
+[![PyPI - Version](https://img.shields.io/pypi/v/langchain-cli?label=%20)](https://pypi.org/project/langchain-cli/#history)
+[![PyPI - License](https://img.shields.io/pypi/l/langchain-cli)](https://opensource.org/licenses/MIT)
+[![PyPI - Downloads](https://img.shields.io/pepy/dt/langchain-cli)](https://pypistats.org/packages/langchain-cli)
+[![Twitter](https://img.shields.io/twitter/url/https/twitter.com/langchainai.svg?style=social&label=Follow%20%40LangChainAI)](https://twitter.com/langchainai)
+
+## Quick Install
+
+```bash
+pip install langchain-cli
+```
+
+## 🤔 What is this?
+
+This package implements the official CLI for LangChain. Right now, it is most useful for getting started with LangChain Templates!
+
+## 📖 Documentation
+
+[CLI Docs](https://github.com/langchain-ai/langchain/blob/master/libs/cli/DOCS.md)
+
+## 📕 Releases & Versioning
+
+See our [Releases](https://docs.langchain.com/oss/python/release-policy) and [Versioning](https://docs.langchain.com/oss/python/versioning) policies.
+
+## 💁 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 the [Contributing Guide](https://docs.langchain.com/oss/python/contributing/overview).

libs/cli/langchain_cli/__init__.py

@@ -0,0 +1,7 @@
+"""LangChain CLI."""
+
+from langchain_cli._version import __version__
+
+__all__ = [
+    "__version__",
+]

libs/cli/langchain_cli/_version.py

@@ -0,0 +1,10 @@
+from importlib import metadata
+
+try:
+    __version__ = metadata.version(__package__)
+except metadata.PackageNotFoundError:
+    # Case where package metadata is not available.
+    __version__ = ""
+del metadata  # optional, avoids polluting the results of dir(__package__)
+
+__all__ = ["__version__"]

libs/cli/langchain_cli/cli.py

@@ -0,0 +1,88 @@
+"""LangChain CLI."""
+
+from __future__ import annotations
+
+from typing import Annotated
+
+import typer
+
+from langchain_cli._version import __version__
+from langchain_cli.namespaces import app as app_namespace
+from langchain_cli.namespaces import integration as integration_namespace
+from langchain_cli.namespaces import template as template_namespace
+from langchain_cli.namespaces.migrate import main as migrate_namespace
+from langchain_cli.utils.packages import get_langserve_export, get_package_root
+
+app = typer.Typer(no_args_is_help=True, add_completion=False)
+app.add_typer(
+    template_namespace.package_cli,
+    name="template",
+    help=template_namespace.__doc__,
+)
+app.add_typer(app_namespace.app_cli, name="app", help=app_namespace.__doc__)
+app.add_typer(
+    integration_namespace.integration_cli,
+    name="integration",
+    help=integration_namespace.__doc__,
+)
+
+app.command(
+    name="migrate",
+    context_settings={
+        # Let Grit handle the arguments
+        "allow_extra_args": True,
+        "ignore_unknown_options": True,
+    },
+)(
+    migrate_namespace.migrate,
+)
+
+
+def _version_callback(*, show_version: bool) -> None:
+    if show_version:
+        typer.echo(f"langchain-cli {__version__}")
+        raise typer.Exit
+
+
+@app.callback()
+def _main(
+    *,
+    version: bool = typer.Option(
+        False,  # noqa: FBT003
+        "--version",
+        "-v",
+        help="Print the current CLI version.",
+        callback=_version_callback,
+        is_eager=True,
+    ),
+) -> None:
+    pass
+
+
+@app.command()
+def serve(
+    *,
+    port: Annotated[
+        int | None,
+        typer.Option(help="The port to run the server on"),
+    ] = None,
+    host: Annotated[
+        str | None,
+        typer.Option(help="The host to run the server on"),
+    ] = None,
+) -> None:
+    """Start the LangServe app, whether it's a template or an app."""
+    try:
+        project_dir = get_package_root()
+        pyproject = project_dir / "pyproject.toml"
+        get_langserve_export(pyproject)
+    except (KeyError, FileNotFoundError):
+        # not a template
+        app_namespace.serve(port=port, host=host)
+    else:
+        # is a template
+        template_namespace.serve(port=port, host=host)
+
+
+if __name__ == "__main__":
+    app()

libs/cli/langchain_cli/constants.py

@@ -0,0 +1,5 @@
+"""LangChain CLI constants."""
+
+DEFAULT_GIT_REPO = "https://github.com/langchain-ai/langchain.git"
+DEFAULT_GIT_SUBDIRECTORY = "templates"
+DEFAULT_GIT_REF = "master"

libs/cli/langchain_cli/dev_scripts.py

@@ -0,0 +1,70 @@
+"""Development Scripts for template packages."""
+
+from collections.abc import Sequence
+from typing import Literal
+
+from fastapi import FastAPI
+from langserve import add_routes
+
+from langchain_cli.utils.packages import get_langserve_export, get_package_root
+
+
+def create_demo_server(
+    *,
+    config_keys: Sequence[str] = (),
+    playground_type: Literal["default", "chat"] = "default",
+) -> FastAPI:
+    """Create a demo server for the current template.
+
+    Args:
+        config_keys: Optional sequence of config keys to expose in the playground.
+        playground_type: The type of playground to use.
+
+    Returns:
+        The demo server.
+
+    Raises:
+        KeyError: If the `pyproject.toml` file is missing required fields.
+        ImportError: If the module defined in `pyproject.toml` cannot be imported.
+    """
+    app = FastAPI()
+    package_root = get_package_root()
+    pyproject = package_root / "pyproject.toml"
+    try:
+        package = get_langserve_export(pyproject)
+
+        mod = __import__(package["module"], fromlist=[package["attr"]])
+
+        chain = getattr(mod, package["attr"])
+        add_routes(
+            app,
+            chain,
+            config_keys=config_keys,
+            playground_type=playground_type,
+        )
+    except KeyError as e:
+        msg = "Missing fields from pyproject.toml"
+        raise KeyError(msg) from e
+    except ImportError as e:
+        msg = "Could not import module defined in pyproject.toml"
+        raise ImportError(msg) from e
+
+    return app
+
+
+def create_demo_server_configurable() -> FastAPI:
+    """Create a configurable demo server.
+
+    Returns:
+        The configurable demo server.
+    """
+    return create_demo_server(config_keys=["configurable"])
+
+
+def create_demo_server_chat() -> FastAPI:
+    """Create a chat demo server.
+
+    Returns:
+        The chat demo server.
+    """
+    return create_demo_server(playground_type="chat")

libs/cli/langchain_cli/integration_template/.gitignore

@@ -0,0 +1 @@
+__pycache__

libs/cli/langchain_cli/integration_template/LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2024 LangChain, Inc.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

libs/cli/langchain_cli/integration_template/Makefile

@@ -0,0 +1,58 @@
+.PHONY: all format lint test tests integration_tests help extended_tests
+
+# Default target executed when no arguments are given to make.
+all: help
+
+# Define a variable for the test file path.
+TEST_FILE ?= tests/unit_tests/
+integration_test integration_tests: TEST_FILE = tests/integration_tests/
+
+
+# unit tests are run with the --disable-socket flag to prevent network calls
+test tests:
+	uv run pytest --disable-socket --allow-unix-socket $(TEST_FILE)
+
+test_watch:
+	uv run ptw --snapshot-update --now . -- -vv $(TEST_FILE)
+
+# integration tests are run without the --disable-socket flag to allow network calls
+integration_test integration_tests:
+	uv run pytest $(TEST_FILE)
+
+######################
+# LINTING AND FORMATTING
+######################
+
+# Define a variable for Python and notebook files.
+PYTHON_FILES=.
+MYPY_CACHE=.mypy_cache
+lint format: PYTHON_FILES=.
+lint_diff format_diff: PYTHON_FILES=$(shell git diff --relative=libs/partners/__package_name_short__ --name-only --diff-filter=d master | grep -E '\.py$$|\.ipynb$$')
+lint_package: PYTHON_FILES=__module_name__
+lint_tests: PYTHON_FILES=tests
+lint_tests: MYPY_CACHE=.mypy_cache_test
+
+lint lint_diff lint_package lint_tests:
+	[ "$(PYTHON_FILES)" = "" ] || uv run ruff check $(PYTHON_FILES)
+	[ "$(PYTHON_FILES)" = "" ] || uv run ruff format $(PYTHON_FILES) --diff
+	[ "$(PYTHON_FILES)" = "" ] || mkdir -p $(MYPY_CACHE) && uv run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE)
+
+format format_diff:
+	[ "$(PYTHON_FILES)" = "" ] || uv run ruff format $(PYTHON_FILES)
+	[ "$(PYTHON_FILES)" = "" ] || uv run ruff check --fix $(PYTHON_FILES)
+
+check_imports: $(shell find __module_name__ -name '*.py')
+	uv run python ./scripts/check_imports.py $^
+
+######################
+# HELP
+######################
+
+help:
+	@echo '----'
+	@echo 'check_imports				- check imports'
+	@echo 'format                       - run code formatters'
+	@echo 'lint                         - run linters'
+	@echo 'test                         - run unit tests'
+	@echo 'tests                        - run unit tests'
+	@echo 'test TEST_FILE=<test_file>   - run all tests in file'

libs/cli/langchain_cli/integration_template/README.md

@@ -0,0 +1,46 @@
+# __package_name__
+
+This package contains the LangChain integration with __ModuleName__
+
+## Installation
+
+```bash
+pip install -U __package_name__
+```
+
+And you should configure credentials by setting the following environment variables:
+
+* TODO: fill this out
+
+## Chat Models
+
+`Chat__ModuleName__` class exposes chat models from __ModuleName__.
+
+```python
+from __module_name__ import Chat__ModuleName__
+
+model = Chat__ModuleName__()
+model.invoke("Sing a ballad of LangChain.")
+```
+
+## Embeddings
+
+`__ModuleName__Embeddings` class exposes embeddings from __ModuleName__.
+
+```python
+from __module_name__ import __ModuleName__Embeddings
+
+embeddings = __ModuleName__Embeddings()
+embeddings.embed_query("What is the meaning of life?")
+```
+
+## LLMs
+
+`__ModuleName__LLM` class exposes LLMs from __ModuleName__.
+
+```python
+from __module_name__ import __ModuleName__LLM
+
+model = __ModuleName__LLM()
+model.invoke("The meaning of life is")
+```

libs/cli/langchain_cli/integration_template/docs/chat.ipynb

@@ -0,0 +1,264 @@
+{
+  "cells": [
+    {
+      "cell_type": "raw",
+      "id": "afaf8039",
+      "metadata": {},
+      "source": [
+        "---\n",
+        "sidebar_label: __ModuleName__\n",
+        "---"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "e49f1e0d",
+      "metadata": {},
+      "source": [
+        "# Chat__ModuleName__\n",
+        "\n",
+        "- TODO: Make sure API reference link is correct.\n",
+        "\n",
+        "This will help you get started with __ModuleName__ [chat models](/docs/concepts/chat_models). For detailed documentation of all Chat__ModuleName__ features and configurations head to the [API reference](https://python.langchain.com/api_reference/__package_name_short_snake__/chat_models/__module_name__.chat_models.Chat__ModuleName__.html).\n",
+        "\n",
+        "- TODO: Add any other relevant links, like information about models, prices, context windows, etc. See https://python.langchain.com/docs/integrations/chat/openai/ for an example.\n",
+        "\n",
+        "## Overview\n",
+        "### Integration details\n",
+        "\n",
+        "- TODO: Fill in table features.\n",
+        "- TODO: Remove JS support link if not relevant, otherwise ensure link is correct.\n",
+        "- TODO: Make sure API reference links are correct.\n",
+        "\n",
+        "| Class | Package | Local | Serializable | [JS support](https://js.langchain.com/docs/integrations/chat/__package_name_short_snake__) | Package downloads | Package latest |\n",
+        "| :--- | :--- | :---: | :---: |  :---: | :---: | :---: |\n",
+        "| [Chat__ModuleName__](https://python.langchain.com/api_reference/__package_name_short_snake__/chat_models/__module_name__.chat_models.Chat__ModuleName__.html) | [__package_name__](https://python.langchain.com/api_reference/__package_name_short_snake__/) | ✅/❌ | beta/❌ | ✅/❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/__package_name__&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/__package_name__&label=%20) |\n",
+        "\n",
+        "### Model features\n",
+        "| [Tool calling](/docs/how_to/tool_calling) | [Structured output](/docs/how_to/structured_output/) | JSON mode | [Image input](/docs/how_to/multimodal_inputs/) | Audio input | Video input | [Token-level streaming](/docs/how_to/chat_streaming/) | Native async | [Token usage](/docs/how_to/chat_token_usage_tracking/) | [Logprobs](/docs/how_to/logprobs/) |\n",
+        "| :---: | :---: | :---: | :---: |  :---: | :---: | :---: | :---: | :---: | :---: |\n",
+        "| ✅/❌ | ✅/❌ | ✅/❌ | ✅/❌ | ✅/❌ | ✅/❌ | ✅/❌ | ✅/❌ | ✅/❌ | ✅/❌ |\n",
+        "\n",
+        "## Setup\n",
+        "\n",
+        "- TODO: Update with relevant info.\n",
+        "\n",
+        "To access __ModuleName__ models you'll need to create a/an __ModuleName__ account, get an API key, and install the `__package_name__` integration package.\n",
+        "\n",
+        "### Credentials\n",
+        "\n",
+        "- TODO: Update with relevant info.\n",
+        "\n",
+        "Head to (TODO: link) to sign up to __ModuleName__ and generate an API key. Once you've done this set the __MODULE_NAME___API_KEY environment variable:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "433e8d2b-9519-4b49-b2c4-7ab65b046c94",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "import getpass\n",
+        "import os\n",
+        "\n",
+        "if not os.getenv(\"__MODULE_NAME___API_KEY\"):\n",
+        "    os.environ[\"__MODULE_NAME___API_KEY\"] = getpass.getpass(\n",
+        "        \"Enter your __ModuleName__ API key: \"\n",
+        "    )"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "72ee0c4b-9764-423a-9dbf-95129e185210",
+      "metadata": {},
+      "source": [
+        "To enable automated tracing of your model calls, set your [LangSmith](https://docs.smith.langchain.com/) API key:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "a15d341e-3e26-4ca3-830b-5aab30ed66de",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# os.environ[\"LANGSMITH_TRACING\"] = \"true\"\n",
+        "# os.environ[\"LANGSMITH_API_KEY\"] = getpass.getpass(\"Enter your LangSmith API key: \")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "0730d6a1-c893-4840-9817-5e5251676d5d",
+      "metadata": {},
+      "source": [
+        "### Installation\n",
+        "\n",
+        "The LangChain __ModuleName__ integration lives in the `__package_name__` package:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "652d6238-1f87-422a-b135-f5abbb8652fc",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "%pip install -qU __package_name__"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "a38cde65-254d-4219-a441-068766c0d4b5",
+      "metadata": {},
+      "source": [
+        "## Instantiation\n",
+        "\n",
+        "Now we can instantiate our model object and generate chat completions:\n",
+        "\n",
+        "- TODO: Update model instantiation with relevant params."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "cb09c344-1836-4e0c-acf8-11d13ac1dbae",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from __module_name__ import Chat__ModuleName__\n",
+        "\n",
+        "model = Chat__ModuleName__(\n",
+        "    model=\"model-name\",\n",
+        "    temperature=0,\n",
+        "    max_tokens=None,\n",
+        "    timeout=None,\n",
+        "    max_retries=2,\n",
+        "    # other params...\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "2b4f3e15",
+      "metadata": {},
+      "source": [
+        "## Invocation\n",
+        "\n",
+        "- TODO: Run cells so output can be seen."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "62e0dbc3",
+      "metadata": {
+        "tags": []
+      },
+      "outputs": [],
+      "source": [
+        "messages = [\n",
+        "    (\n",
+        "        \"system\",\n",
+        "        \"You are a helpful assistant that translates English to French. Translate the user sentence.\",\n",
+        "    ),\n",
+        "    (\"human\", \"I love programming.\"),\n",
+        "]\n",
+        "ai_msg = model.invoke(messages)\n",
+        "ai_msg"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "d86145b3-bfef-46e8-b227-4dda5c9c2705",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "print(ai_msg.content)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "18e2bfc0-7e78-4528-a73f-499ac150dca8",
+      "metadata": {},
+      "source": [
+        "## Chaining\n",
+        "\n",
+        "We can [chain](/docs/how_to/sequence/) our model with a prompt template like so:\n",
+        "\n",
+        "- TODO: Run cells so output can be seen."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "e197d1d7-a070-4c96-9f8a-a0e86d046e0b",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from langchain_core.prompts import ChatPromptTemplate\n",
+        "\n",
+        "prompt = ChatPromptTemplate(\n",
+        "    [\n",
+        "        (\n",
+        "            \"system\",\n",
+        "            \"You are a helpful assistant that translates {input_language} to {output_language}.\",\n",
+        "        ),\n",
+        "        (\"human\", \"{input}\"),\n",
+        "    ]\n",
+        ")\n",
+        "\n",
+        "chain = prompt | model\n",
+        "chain.invoke(\n",
+        "    {\n",
+        "        \"input_language\": \"English\",\n",
+        "        \"output_language\": \"German\",\n",
+        "        \"input\": \"I love programming.\",\n",
+        "    }\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "d1ee55bc-ffc8-4cfa-801c-993953a08cfd",
+      "metadata": {},
+      "source": [
+        "## TODO: Any functionality specific to this model provider\n",
+        "\n",
+        "E.g. creating/using finetuned models via this provider. Delete if not relevant."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "3a5bb5ca-c3ae-4a58-be67-2cd18574b9a3",
+      "metadata": {},
+      "source": [
+        "## API reference\n",
+        "\n",
+        "For detailed documentation of all Chat__ModuleName__ features and configurations head to the [API reference](https://python.langchain.com/api_reference/__package_name_short_snake__/chat_models/__module_name__.chat_models.Chat__ModuleName__.html)"
+      ]
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3 (ipykernel)",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.11.9"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 5
+}

libs/cli/langchain_cli/integration_template/docs/document_loaders.ipynb

@@ -0,0 +1,219 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "---\n",
+    "sidebar_label: __ModuleName__\n",
+    "---"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# __ModuleName__Loader\n",
+    "\n",
+    "- TODO: Make sure API reference link is correct.\n",
+    "\n",
+    "This notebook provides a quick overview for getting started with __ModuleName__ [document loader](https://python.langchain.com/docs/concepts/document_loaders). For detailed documentation of all __ModuleName__Loader features and configurations head to the [API reference](https://python.langchain.com/v0.2/api_reference/community/document_loaders/langchain_community.document_loaders.__module_name___loader.__ModuleName__Loader.html).\n",
+    "\n",
+    "- TODO: Add any other relevant links, like information about underlying API, etc.\n",
+    "\n",
+    "## Overview\n",
+    "### Integration details\n",
+    "\n",
+    "- TODO: Fill in table features.\n",
+    "- TODO: Remove JS support link if not relevant, otherwise ensure link is correct.\n",
+    "- TODO: Make sure API reference links are correct.\n",
+    "\n",
+    "| Class | Package | Local | Serializable | [JS support](https://js.langchain.com/docs/integrations/document_loaders/web_loaders/__module_name___loader)|\n",
+    "| :--- | :--- | :---: | :---: |  :---: |\n",
+    "| [__ModuleName__Loader](https://python.langchain.com/v0.2/api_reference/community/document_loaders/langchain_community.document_loaders.__module_name__loader.__ModuleName__Loader.html) | [langchain_community](https://api.python.langchain.com/en/latest/community_api_reference.html) | ✅/❌ | beta/❌ | ✅/❌ | \n",
+    "### Loader features\n",
+    "| Source | Document Lazy Loading | Native Async Support\n",
+    "| :---: | :---: | :---: | \n",
+    "| __ModuleName__Loader | ✅/❌ | ✅/❌ | \n",
+    "\n",
+    "## Setup\n",
+    "\n",
+    "- TODO: Update with relevant info.\n",
+    "\n",
+    "To access __ModuleName__ document loader you'll need to install the `__package_name__` integration package, and create a **ModuleName** account and get an API key.\n",
+    "\n",
+    "### Credentials\n",
+    "\n",
+    "- TODO: Update with relevant info.\n",
+    "\n",
+    "Head to (TODO: link) to sign up to __ModuleName__ and generate an API key. Once you've done this set the __MODULE_NAME___API_KEY environment variable:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import getpass\n",
+    "import os\n",
+    "\n",
+    "os.environ[\"__MODULE_NAME___API_KEY\"] = getpass.getpass(\n",
+    "    \"Enter your __ModuleName__ API key: \"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": "To enable automated tracing of your model calls, set your [LangSmith](https://docs.smith.langchain.com/) API key:"
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# os.environ[\"LANGSMITH_API_KEY\"] = getpass.getpass(\"Enter your LangSmith API key: \")\n",
+    "# os.environ[\"LANGSMITH_TRACING\"] = \"true\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Installation\n",
+    "\n",
+    "Install **langchain_community**.\n",
+    "\n",
+    "- TODO: Add any other required packages"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%pip install -qU langchain_community"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Initialization\n",
+    "\n",
+    "Now we can instantiate our model object and load documents:\n",
+    "\n",
+    "- TODO: Update model instantiation with relevant params."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain_community.document_loaders import __ModuleName__Loader\n",
+    "\n",
+    "loader = __ModuleName__Loader(\n",
+    "    # required params = ...\n",
+    "    # optional params = ...\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Load\n",
+    "\n",
+    "- TODO: Run cells to show loading capabilities"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "docs = loader.load()\n",
+    "docs[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "print(docs[0].metadata)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Lazy Load\n",
+    "\n",
+    "- TODO: Run cells to show lazy loading capabilities. Delete if lazy loading is not implemented."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "page = []\n",
+    "for doc in loader.lazy_load():\n",
+    "    page.append(doc)\n",
+    "    if len(page) >= 10:\n",
+    "        # do some paged operation, e.g.\n",
+    "        # index.upsert(page)\n",
+    "\n",
+    "        page = []"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## TODO: Any functionality specific to this document loader\n",
+    "\n",
+    "E.g. using specific configs for different loading behavior. Delete if not relevant."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## API reference\n",
+    "\n",
+    "For detailed documentation of all __ModuleName__Loader features and configurations head to the API reference: https://python.langchain.com/v0.2/api_reference/community/document_loaders/langchain_community.document_loaders.__module_name___loader.__ModuleName__Loader.html"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

libs/cli/langchain_cli/integration_template/docs/llms.ipynb

@@ -0,0 +1,238 @@
+{
+  "cells": [
+    {
+      "cell_type": "raw",
+      "id": "67db2992",
+      "metadata": {},
+      "source": [
+        "---\n",
+        "sidebar_label: __ModuleName__\n",
+        "---"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "9597802c",
+      "metadata": {},
+      "source": [
+        "# __ModuleName__LLM\n",
+        "\n",
+        "- [ ] TODO: Make sure API reference link is correct\n",
+        "\n",
+        "This will help you get started with __ModuleName__ completion models (LLMs) using LangChain. For detailed documentation on `__ModuleName__LLM` features and configuration options, please refer to the [API reference](https://api.python.langchain.com/en/latest/llms/__module_name__.llms.__ModuleName__LLM.html).\n",
+        "\n",
+        "## Overview\n",
+        "### Integration details\n",
+        "\n",
+        "- TODO: Fill in table features.\n",
+        "- TODO: Remove JS support link if not relevant, otherwise ensure link is correct.\n",
+        "- TODO: Make sure API reference links are correct.\n",
+        "\n",
+        "| Class | Package | Local | Serializable | [JS support](https://js.langchain.com/docs/integrations/llms/__package_name_short_snake__) | Package downloads | Package latest |\n",
+        "| :--- | :--- | :---: | :---: |  :---: | :---: | :---: |\n",
+        "| [__ModuleName__LLM](https://api.python.langchain.com/en/latest/llms/__module_name__.llms.__ModuleName__LLM.html) | [__package_name__](https://api.python.langchain.com/en/latest/__package_name_short_snake___api_reference.html) | ✅/❌ | beta/❌ | ✅/❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/__package_name__&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/__package_name__&label=%20) |\n",
+        "\n",
+        "## Setup\n",
+        "\n",
+        "- TODO: Update with relevant info.\n",
+        "\n",
+        "To access __ModuleName__ models you'll need to create a/an __ModuleName__ account, get an API key, and install the `__package_name__` integration package.\n",
+        "\n",
+        "### Credentials\n",
+        "\n",
+        "- TODO: Update with relevant info.\n",
+        "\n",
+        "Head to (TODO: link) to sign up to __ModuleName__ and generate an API key. Once you've done this set the __MODULE_NAME___API_KEY environment variable:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "bc51e756",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "import getpass\n",
+        "import os\n",
+        "\n",
+        "if not os.getenv(\"__MODULE_NAME___API_KEY\"):\n",
+        "    os.environ[\"__MODULE_NAME___API_KEY\"] = getpass.getpass(\n",
+        "        \"Enter your __ModuleName__ API key: \"\n",
+        "    )"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "4b6e1ca6",
+      "metadata": {},
+      "source": [
+        "To enable automated tracing of your model calls, set your [LangSmith](https://docs.smith.langchain.com/) API key:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "196c2b41",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# os.environ[\"LANGSMITH_TRACING\"] = \"true\"\n",
+        "# os.environ[\"LANGSMITH_API_KEY\"] = getpass.getpass(\"Enter your LangSmith API key: \")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "809c6577",
+      "metadata": {},
+      "source": [
+        "### Installation\n",
+        "\n",
+        "The LangChain __ModuleName__ integration lives in the `__package_name__` package:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "59c710c4",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "%pip install -qU __package_name__"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "0a760037",
+      "metadata": {},
+      "source": [
+        "## Instantiation\n",
+        "\n",
+        "Now we can instantiate our model object and generate chat completions:\n",
+        "\n",
+        "- TODO: Update model instantiation with relevant params."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "a0562a13",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from __module_name__ import __ModuleName__LLM\n",
+        "\n",
+        "model = __ModuleName__LLM(\n",
+        "    model=\"model-name\",\n",
+        "    temperature=0,\n",
+        "    max_tokens=None,\n",
+        "    timeout=None,\n",
+        "    max_retries=2,\n",
+        "    # other params...\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "0ee90032",
+      "metadata": {},
+      "source": [
+        "## Invocation\n",
+        "\n",
+        "- [ ] TODO: Run cells so output can be seen."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "035dea0f",
+      "metadata": {
+        "tags": []
+      },
+      "outputs": [],
+      "source": [
+        "input_text = \"__ModuleName__ is an AI company that \"\n",
+        "\n",
+        "completion = model.invoke(input_text)\n",
+        "completion"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "add38532",
+      "metadata": {},
+      "source": [
+        "## Chaining\n",
+        "\n",
+        "We can [chain](/docs/how_to/sequence/) our completion model with a prompt template like so:\n",
+        "\n",
+        "- TODO: Run cells so output can be seen."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "078e9db2",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from langchain_core.prompts import PromptTemplate\n",
+        "\n",
+        "prompt = PromptTemplate(\"How to say {input} in {output_language}:\\n\")\n",
+        "\n",
+        "chain = prompt | model\n",
+        "chain.invoke(\n",
+        "    {\n",
+        "        \"output_language\": \"German\",\n",
+        "        \"input\": \"I love programming.\",\n",
+        "    }\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "e99eef30",
+      "metadata": {},
+      "source": [
+        "## TODO: Any functionality specific to this model provider\n",
+        "\n",
+        "E.g. creating/using finetuned models via this provider. Delete if not relevant"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "e9bdfcef",
+      "metadata": {},
+      "source": [
+        "## API reference\n",
+        "\n",
+        "For detailed documentation of all `__ModuleName__LLM` features and configurations head to the API reference: https://api.python.langchain.com/en/latest/llms/__module_name__.llms.__ModuleName__LLM.html"
+      ]
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3.11.1 64-bit",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.9.7"
+    },
+    "vscode": {
+      "interpreter": {
+        "hash": "e971737741ff4ec9aff7dc6155a1060a59a8a6d52c757dbbe66bf8ee389494b1"
+      }
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 5
+}

libs/cli/langchain_cli/integration_template/docs/provider.ipynb

@@ -0,0 +1,50 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# __ModuleName__\n",
+    "\n",
+    "__ModuleName__ is a platform that offers..."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "id": "y8ku6X96sebl"
+   },
+   "outputs": [],
+   "source": [
+    "from __module_name__ import Chat__ModuleName__\n",
+    "from __module_name__ import __ModuleName__LLM\n",
+    "from __module_name__ import __ModuleName__VectorStore"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}

libs/cli/langchain_cli/integration_template/docs/retrievers.ipynb

@@ -0,0 +1,245 @@
+{
+ "cells": [
+  {
+   "cell_type": "raw",
+   "id": "afaf8039",
+   "metadata": {},
+   "source": [
+    "---\n",
+    "sidebar_label: __ModuleName__\n",
+    "---"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e49f1e0d",
+   "metadata": {},
+   "source": [
+    "# __ModuleName__Retriever\n",
+    "\n",
+    "- TODO: Make sure API reference link is correct.\n",
+    "\n",
+    "This will help you get started with the __ModuleName__ [retriever](/docs/concepts/retrievers). For detailed documentation of all __ModuleName__Retriever features and configurations head to the [API reference](https://api.python.langchain.com/en/latest/retrievers/__module_name__.retrievers.__ModuleName__.__ModuleName__Retriever.html).\n",
+    "\n",
+    "### Integration details\n",
+    "\n",
+    "TODO: Select one of the tables below, as appropriate.\n",
+    "\n",
+    "1: Bring-your-own data (i.e., index and search a custom corpus of documents):\n",
+    "\n",
+    "| Retriever | Self-host | Cloud offering | Package |\n",
+    "| :--- | :--- | :---: | :---: |\n",
+    "[__ModuleName__Retriever](https://api.python.langchain.com/en/latest/retrievers/__package_name__.retrievers.__module_name__.__ModuleName__Retriever.html) | ❌ | ❌ | __package_name__ |\n",
+    "\n",
+    "2: External index (e.g., constructed from Internet data or similar)):\n",
+    "\n",
+    "| Retriever | Source | Package |\n",
+    "| :--- | :--- | :---: |\n",
+    "[__ModuleName__Retriever](https://api.python.langchain.com/en/latest/retrievers/__package_name__.retrievers.__module_name__.__ModuleName__Retriever.html) | Source description | __package_name__ |\n",
+    "\n",
+    "## Setup\n",
+    "\n",
+    "- TODO: Update with relevant info."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "72ee0c4b-9764-423a-9dbf-95129e185210",
+   "metadata": {},
+   "source": [
+    "If you want to get automated tracing from individual queries, you can also set your [LangSmith](https://docs.smith.langchain.com/) API key by uncommenting below:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a15d341e-3e26-4ca3-830b-5aab30ed66de",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# os.environ[\"LANGSMITH_API_KEY\"] = getpass.getpass(\"Enter your LangSmith API key: \")\n",
+    "# os.environ[\"LANGSMITH_TRACING\"] = \"true\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0730d6a1-c893-4840-9817-5e5251676d5d",
+   "metadata": {},
+   "source": [
+    "### Installation\n",
+    "\n",
+    "This retriever lives in the `__package_name__` package:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "652d6238-1f87-422a-b135-f5abbb8652fc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%pip install -qU __package_name__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a38cde65-254d-4219-a441-068766c0d4b5",
+   "metadata": {},
+   "source": [
+    "## Instantiation\n",
+    "\n",
+    "Now we can instantiate our retriever:\n",
+    "\n",
+    "- TODO: Update model instantiation with relevant params."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "70cc8e65-2a02-408a-bbc6-8ef649057d82",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from __module_name__ import __ModuleName__Retriever\n",
+    "\n",
+    "retriever = __ModuleName__Retriever(\n",
+    "    # ...\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5c5f2839-4020-424e-9fc9-07777eede442",
+   "metadata": {},
+   "source": [
+    "## Usage"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "51a60dbe-9f2e-4e04-bb62-23968f17164a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "query = \"...\"\n",
+    "\n",
+    "retriever.invoke(query)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dfe8aad4-8626-4330-98a9-7ea1ca5d2e0e",
+   "metadata": {},
+   "source": [
+    "## Use within a chain\n",
+    "\n",
+    "Like other retrievers, __ModuleName__Retriever can be incorporated into LLM applications via [chains](/docs/how_to/sequence/).\n",
+    "\n",
+    "We will need a LLM or chat model:\n",
+    "\n",
+    "import ChatModelTabs from \"@theme/ChatModelTabs\";\n",
+    "\n",
+    "<ChatModelTabs customVarName=\"llm\" />"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "25b647a3-f8f2-4541-a289-7a241e43f9df",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# | output: false\n",
+    "# | echo: false\n",
+    "\n",
+    "from langchain_openai import ChatOpenAI\n",
+    "\n",
+    "model = ChatOpenAI(model=\"gpt-3.5-turbo-0125\", temperature=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "23e11cc9-abd6-4855-a7eb-799f45ca01ae",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain_core.output_parsers import StrOutputParser\n",
+    "from langchain_core.prompts import ChatPromptTemplate\n",
+    "from langchain_core.runnables import RunnablePassthrough\n",
+    "\n",
+    "prompt = ChatPromptTemplate.from_template(\n",
+    "    \"\"\"Answer the question based only on the context provided.\n",
+    "\n",
+    "Context: {context}\n",
+    "\n",
+    "Question: {question}\"\"\"\n",
+    ")\n",
+    "\n",
+    "\n",
+    "def format_docs(docs):\n",
+    "    return \"\\n\\n\".join(doc.page_content for doc in docs)\n",
+    "\n",
+    "\n",
+    "chain = (\n",
+    "    {\"context\": retriever | format_docs, \"question\": RunnablePassthrough()}\n",
+    "    | prompt\n",
+    "    | model\n",
+    "    | StrOutputParser()\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d47c37dd-5c11-416c-a3b6-bec413cd70e8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "chain.invoke(\"...\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d1ee55bc-ffc8-4cfa-801c-993953a08cfd",
+   "metadata": {},
+   "source": [
+    "## TODO: Any functionality or considerations specific to this retriever\n",
+    "\n",
+    "Fill in or delete if not relevant."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3a5bb5ca-c3ae-4a58-be67-2cd18574b9a3",
+   "metadata": {},
+   "source": [
+    "## API reference\n",
+    "\n",
+    "For detailed documentation of all __ModuleName__Retriever features and configurations head to the [API reference](https://api.python.langchain.com/en/latest/retrievers/__module_name__.retrievers.__ModuleName__.__ModuleName__Retriever.html)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

libs/cli/langchain_cli/integration_template/docs/stores.ipynb

@@ -0,0 +1,204 @@
+{
+  "cells": [
+    {
+      "cell_type": "raw",
+      "metadata": {
+        "vscode": {
+          "languageId": "raw"
+        }
+      },
+      "source": [
+        "---\n",
+        "sidebar_label: __ModuleName__ByteStore\n",
+        "---"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# __ModuleName__ByteStore\n",
+        "\n",
+        "- TODO: Make sure API reference link is correct.\n",
+        "\n",
+        "This will help you get started with __ModuleName__ [key-value stores](/docs/concepts/#key-value-stores). For detailed documentation of all __ModuleName__ByteStore features and configurations head to the [API reference](https://python.langchain.com/v0.2/api_reference/core/stores/langchain_core.stores.__module_name__ByteStore.html).\n",
+        "\n",
+        "- TODO: Add any other relevant links, like information about models, prices, context windows, etc. See https://python.langchain.com/docs/integrations/stores/in_memory/ for an example.\n",
+        "\n",
+        "## Overview\n",
+        "\n",
+        "- TODO: (Optional) A short introduction to the underlying technology/API.\n",
+        "\n",
+        "### Integration details\n",
+        "\n",
+        "- TODO: Fill in table features.\n",
+        "- TODO: Remove JS support link if not relevant, otherwise ensure link is correct.\n",
+        "- TODO: Make sure API reference links are correct.\n",
+        "\n",
+        "| Class | Package | Local | [JS support](https://js.langchain.com/docs/integrations/stores/_package_name_) | Package downloads | Package latest |\n",
+        "| :--- | :--- | :---: | :---: |  :---: | :---: |\n",
+        "| [__ModuleName__ByteStore](https://api.python.langchain.com/en/latest/stores/__module_name__.stores.__ModuleName__ByteStore.html) | [__package_name__](https://api.python.langchain.com/en/latest/__package_name_short_snake___api_reference.html) | ✅/❌ | ✅/❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/__package_name__&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/__package_name__&label=%20) |\n",
+        "\n",
+        "## Setup\n",
+        "\n",
+        "- TODO: Update with relevant info.\n",
+        "\n",
+        "To create a __ModuleName__ byte store, you'll need to create a/an __ModuleName__ account, get an API key, and install the `__package_name__` integration package.\n",
+        "\n",
+        "### Credentials\n",
+        "\n",
+        "- TODO: Update with relevant info, or omit if the service does not require any credentials.\n",
+        "\n",
+        "Head to (TODO: link) to sign up to __ModuleName__ and generate an API key. Once you've done this set the __MODULE_NAME___API_KEY environment variable:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "import getpass\n",
+        "import os\n",
+        "\n",
+        "if not os.getenv(\"__MODULE_NAME___API_KEY\"):\n",
+        "    os.environ[\"__MODULE_NAME___API_KEY\"] = getpass.getpass(\n",
+        "        \"Enter your __ModuleName__ API key: \"\n",
+        "    )"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "### Installation\n",
+        "\n",
+        "The LangChain __ModuleName__ integration lives in the `__package_name__` package:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "%pip install -qU __package_name__"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Instantiation\n",
+        "\n",
+        "Now we can instantiate our byte store:\n",
+        "\n",
+        "- TODO: Update model instantiation with relevant params."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from __module_name__ import __ModuleName__ByteStore\n",
+        "\n",
+        "kv_store = __ModuleName__ByteStore(\n",
+        "    # params...\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Usage\n",
+        "\n",
+        "- TODO: Run cells so output can be seen.\n",
+        "\n",
+        "You can set data under keys like this using the `mset` method:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "kv_store.mset(\n",
+        "    [\n",
+        "        [\"key1\", b\"value1\"],\n",
+        "        [\"key2\", b\"value2\"],\n",
+        "    ]\n",
+        ")\n",
+        "\n",
+        "kv_store.mget(\n",
+        "    [\n",
+        "        \"key1\",\n",
+        "        \"key2\",\n",
+        "    ]\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "And you can delete data using the `mdelete` method:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "kv_store.mdelete(\n",
+        "    [\n",
+        "        \"key1\",\n",
+        "        \"key2\",\n",
+        "    ]\n",
+        ")\n",
+        "\n",
+        "kv_store.mget(\n",
+        "    [\n",
+        "        \"key1\",\n",
+        "        \"key2\",\n",
+        "    ]\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## TODO: Any functionality specific to this key-value store provider\n",
+        "\n",
+        "E.g. extra initialization. Delete if not relevant."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## API reference\n",
+        "\n",
+        "For detailed documentation of all __ModuleName__ByteStore features and configurations, head to the API reference: https://api.python.langchain.com/en/latest/stores/__module_name__.stores.__ModuleName__ByteStore.html"
+      ]
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python",
+      "version": "3.10.5"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 2
+}

libs/cli/langchain_cli/integration_template/docs/text_embedding.ipynb

@@ -0,0 +1,246 @@
+{
+ "cells": [
+  {
+   "cell_type": "raw",
+   "id": "afaf8039",
+   "metadata": {},
+   "source": [
+    "---\n",
+    "sidebar_label: __ModuleName__\n",
+    "---"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9a3d6f34",
+   "metadata": {},
+   "source": [
+    "# __ModuleName__Embeddings\n",
+    "\n",
+    "- [ ] TODO: Make sure API reference link is correct\n",
+    "\n",
+    "This will help you get started with __ModuleName__ embedding models using LangChain. For detailed documentation on `__ModuleName__Embeddings` features and configuration options, please refer to the [API reference](https://python.langchain.com/v0.2/api_reference/__package_name_short__/embeddings/__module_name__.embeddings__ModuleName__Embeddings.html).\n",
+    "\n",
+    "## Overview\n",
+    "### Integration details\n",
+    "\n",
+    "| Provider | Package |\n",
+    "|:--------:|:-------:|\n",
+    "| [__ModuleName__](/docs/integrations/providers/__package_name_short__/) | [__package_name__](https://python.langchain.com/v0.2/api_reference/__module_name__/embeddings/__module_name__.embeddings__ModuleName__Embeddings.html) |\n",
+    "\n",
+    "## Setup\n",
+    "\n",
+    "- [ ] TODO: Update with relevant info.\n",
+    "\n",
+    "To access __ModuleName__ embedding models you'll need to create a/an __ModuleName__ account, get an API key, and install the `__package_name__` integration package.\n",
+    "\n",
+    "### Credentials\n",
+    "\n",
+    "- TODO: Update with relevant info.\n",
+    "\n",
+    "Head to (TODO: link) to sign up to __ModuleName__ and generate an API key. Once you've done this set the __MODULE_NAME___API_KEY environment variable:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "36521c2a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import getpass\n",
+    "import os\n",
+    "\n",
+    "if not os.getenv(\"__MODULE_NAME___API_KEY\"):\n",
+    "    os.environ[\"__MODULE_NAME___API_KEY\"] = getpass.getpass(\n",
+    "        \"Enter your __ModuleName__ API key: \"\n",
+    "    )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c84fb993",
+   "metadata": {},
+   "source": "To enable automated tracing of your model calls, set your [LangSmith](https://docs.smith.langchain.com/) API key:"
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "39a4953b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# os.environ[\"LANGSMITH_TRACING\"] = \"true\"\n",
+    "# os.environ[\"LANGSMITH_API_KEY\"] = getpass.getpass(\"Enter your LangSmith API key: \")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d9664366",
+   "metadata": {},
+   "source": [
+    "### Installation\n",
+    "\n",
+    "The LangChain __ModuleName__ integration lives in the `__package_name__` package:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "64853226",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%pip install -qU __package_name__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "45dd1724",
+   "metadata": {},
+   "source": [
+    "## Instantiation\n",
+    "\n",
+    "Now we can instantiate our model object and generate chat completions:\n",
+    "\n",
+    "- TODO: Update model instantiation with relevant params."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9ea7a09b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from __module_name__ import __ModuleName__Embeddings\n",
+    "\n",
+    "embeddings = __ModuleName__Embeddings(\n",
+    "    model=\"model-name\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "77d271b6",
+   "metadata": {},
+   "source": [
+    "## Indexing and Retrieval\n",
+    "\n",
+    "Embedding models are often used in retrieval-augmented generation (RAG) flows, both as part of indexing data as well as later retrieving it. For more detailed instructions, please see our [RAG tutorials](/docs/tutorials/).\n",
+    "\n",
+    "Below, see how to index and retrieve data using the `embeddings` object we initialized above. In this example, we will index and retrieve a sample document in the `InMemoryVectorStore`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d817716b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create a vector store with a sample text\n",
+    "from langchain_core.vectorstores import InMemoryVectorStore\n",
+    "\n",
+    "text = \"LangChain is the framework for building context-aware reasoning applications\"\n",
+    "\n",
+    "vectorstore = InMemoryVectorStore.from_texts(\n",
+    "    [text],\n",
+    "    embedding=embeddings,\n",
+    ")\n",
+    "\n",
+    "# Use the vectorstore as a retriever\n",
+    "retriever = vectorstore.as_retriever()\n",
+    "\n",
+    "# Retrieve the most similar text\n",
+    "retrieved_documents = retriever.invoke(\"What is LangChain?\")\n",
+    "\n",
+    "# show the retrieved document's content\n",
+    "retrieved_documents[0].page_content"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e02b9855",
+   "metadata": {},
+   "source": [
+    "## Direct Usage\n",
+    "\n",
+    "Under the hood, the vectorstore and retriever implementations are calling `embeddings.embed_documents(...)` and `embeddings.embed_query(...)` to create embeddings for the text(s) used in `from_texts` and retrieval `invoke` operations, respectively.\n",
+    "\n",
+    "You can directly call these methods to get embeddings for your own use cases.\n",
+    "\n",
+    "### Embed single texts\n",
+    "\n",
+    "You can embed single texts or documents with `embed_query`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0d2befcd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "single_vector = embeddings.embed_query(text)\n",
+    "print(str(single_vector)[:100])  # Show the first 100 characters of the vector"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1b5a7d03",
+   "metadata": {},
+   "source": [
+    "### Embed multiple texts\n",
+    "\n",
+    "You can embed multiple texts with `embed_documents`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2f4d6e97",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "text2 = (\n",
+    "    \"LangGraph is a library for building stateful, multi-actor applications with LLMs\"\n",
+    ")\n",
+    "two_vectors = embeddings.embed_documents([text, text2])\n",
+    "for vector in two_vectors:\n",
+    "    print(str(vector)[:100])  # Show the first 100 characters of the vector"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "98785c12",
+   "metadata": {},
+   "source": [
+    "## API Reference\n",
+    "\n",
+    "For detailed documentation on `__ModuleName__Embeddings` features and configuration options, please refer to the [API reference](https://api.python.langchain.com/en/latest/embeddings/__module_name__.embeddings.__ModuleName__Embeddings.html).\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

libs/cli/langchain_cli/integration_template/docs/toolkits.ipynb

@@ -0,0 +1,199 @@
+{
+  "cells": [
+    {
+      "cell_type": "raw",
+      "id": "afaf8039",
+      "metadata": {},
+      "source": [
+        "---\n",
+        "sidebar_label: __ModuleName__\n",
+        "---"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "e49f1e0d",
+      "metadata": {},
+      "source": [
+        "# __ModuleName__Toolkit\n",
+        "\n",
+        "- TODO: Make sure API reference link is correct.\n",
+        "\n",
+        "This will help you get started with the __ModuleName__ [toolkit](/docs/concepts/tools/#toolkits). For detailed documentation of all __ModuleName__Toolkit features and configurations head to the [API reference](https://api.python.langchain.com/en/latest/agent_toolkits/__module_name__.agent_toolkits.__ModuleName__.toolkit.__ModuleName__Toolkit.html).\n",
+        "\n",
+        "## Setup\n",
+        "\n",
+        "- TODO: Update with relevant info."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "72ee0c4b-9764-423a-9dbf-95129e185210",
+      "metadata": {},
+      "source": "To enable automated tracing of individual tools, set your [LangSmith](https://docs.smith.langchain.com/) API key:"
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "a15d341e-3e26-4ca3-830b-5aab30ed66de",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# os.environ[\"LANGSMITH_API_KEY\"] = getpass.getpass(\"Enter your LangSmith API key: \")\n",
+        "# os.environ[\"LANGSMITH_TRACING\"] = \"true\""
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "0730d6a1-c893-4840-9817-5e5251676d5d",
+      "metadata": {},
+      "source": [
+        "### Installation\n",
+        "\n",
+        "This toolkit lives in the `__package_name__` package:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "652d6238-1f87-422a-b135-f5abbb8652fc",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "%pip install -qU __package_name__"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "a38cde65-254d-4219-a441-068766c0d4b5",
+      "metadata": {},
+      "source": [
+        "## Instantiation\n",
+        "\n",
+        "Now we can instantiate our toolkit:\n",
+        "\n",
+        "- TODO: Update model instantiation with relevant params."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "cb09c344-1836-4e0c-acf8-11d13ac1dbae",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from __module_name__ import __ModuleName__Toolkit\n",
+        "\n",
+        "toolkit = __ModuleName__Toolkit(\n",
+        "    # ...\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "5c5f2839-4020-424e-9fc9-07777eede442",
+      "metadata": {},
+      "source": [
+        "## Tools\n",
+        "\n",
+        "View available tools:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "51a60dbe-9f2e-4e04-bb62-23968f17164a",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "toolkit.get_tools()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "d11245ad-3661-4405-8558-1188896347ec",
+      "metadata": {},
+      "source": [
+        "TODO: list API reference pages for individual tools."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "dfe8aad4-8626-4330-98a9-7ea1ca5d2e0e",
+      "metadata": {},
+      "source": [
+        "## Use within an agent"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "310bf18e-6c9a-4072-b86e-47bc1fcca29d",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from langgraph.prebuilt import create_react_agent\n",
+        "\n",
+        "agent_executor = create_react_agent(llm, tools)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "23e11cc9-abd6-4855-a7eb-799f45ca01ae",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "example_query = \"...\"\n",
+        "\n",
+        "events = agent_executor.stream(\n",
+        "    {\"messages\": [(\"user\", example_query)]},\n",
+        "    stream_mode=\"values\",\n",
+        ")\n",
+        "for event in events:\n",
+        "    event[\"messages\"][-1].pretty_print()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "d1ee55bc-ffc8-4cfa-801c-993953a08cfd",
+      "metadata": {},
+      "source": [
+        "## TODO: Any functionality or considerations specific to this toolkit\n",
+        "\n",
+        "Fill in or delete if not relevant."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "3a5bb5ca-c3ae-4a58-be67-2cd18574b9a3",
+      "metadata": {},
+      "source": [
+        "## API reference\n",
+        "\n",
+        "For detailed documentation of all __ModuleName__Toolkit features and configurations head to the [API reference](https://api.python.langchain.com/en/latest/agent_toolkits/__module_name__.agent_toolkits.__ModuleName__.toolkit.__ModuleName__Toolkit.html)."
+      ]
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3 (ipykernel)",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.10.4"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 5
+}

libs/cli/langchain_cli/integration_template/docs/tools.ipynb

@@ -0,0 +1,271 @@
+{
+  "cells": [
+    {
+      "cell_type": "raw",
+      "id": "10238e62-3465-4973-9279-606cbb7ccf16",
+      "metadata": {},
+      "source": [
+        "---\n",
+        "sidebar_label: __ModuleName__\n",
+        "---"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "a6f91f20",
+      "metadata": {},
+      "source": [
+        "# __ModuleName__\n",
+        "\n",
+        "- TODO: Make sure API reference link is correct.\n",
+        "\n",
+        "This notebook provides a quick overview for getting started with __ModuleName__ [tool](/docs/integrations/tools/). For detailed documentation of all __ModuleName__ features and configurations head to the [API reference](https://python.langchain.com/v0.2/api_reference/community/tools/langchain_community.tools.__module_name__.tool.__ModuleName__.html).\n",
+        "\n",
+        "- TODO: Add any other relevant links, like information about underlying API, etc.\n",
+        "\n",
+        "## Overview\n",
+        "\n",
+        "### Integration details\n",
+        "\n",
+        "- TODO: Make sure links and features are correct\n",
+        "\n",
+        "| Class | Package | Serializable | [JS support](https://js.langchain.com/docs/integrations/tools/__module_name__) |  Package latest |\n",
+        "| :--- | :--- | :---: | :---: | :---: |\n",
+        "| [__ModuleName__](https://python.langchain.com/v0.2/api_reference/community/tools/langchain_community.tools.__module_name__.tool.__ModuleName__.html) | [langchain-community](https://api.python.langchain.com/en/latest/community_api_reference.html) | beta/❌ | ✅/❌ |  ![PyPI - Version](https://img.shields.io/pypi/v/langchain-community&label=%20) |\n",
+        "\n",
+        "### Tool features\n",
+        "\n",
+        "- TODO: Add feature table if it makes sense\n",
+        "\n",
+        "\n",
+        "## Setup\n",
+        "\n",
+        "- TODO: Add any additional deps\n",
+        "\n",
+        "The integration lives in the `langchain-community` package."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "f85b4089",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "%pip install --quiet -U langchain-community"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "b15e9266",
+      "metadata": {},
+      "source": [
+        "### Credentials\n",
+        "\n",
+        "- TODO: Add any credentials that are needed"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "id": "e0b178a2-8816-40ca-b57c-ccdd86dde9c9",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "import getpass\n",
+        "import os\n",
+        "\n",
+        "# if not os.environ.get(\"__MODULE_NAME___API_KEY\"):\n",
+        "#     os.environ[\"__MODULE_NAME___API_KEY\"] = getpass.getpass(\"__MODULE_NAME__ API key:\\n\")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "bc5ab717-fd27-4c59-b912-bdd099541478",
+      "metadata": {},
+      "source": [
+        "It's also helpful (but not needed) to set up [LangSmith](https://smith.langchain.com/) for best-in-class observability:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "id": "a6c2f136-6367-4f1f-825d-ae741e1bf281",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# os.environ[\"LANGSMITH_TRACING\"] = \"true\"\n",
+        "# os.environ[\"LANGSMITH_API_KEY\"] = getpass.getpass()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "1c97218f-f366-479d-8bf7-fe9f2f6df73f",
+      "metadata": {},
+      "source": [
+        "## Instantiation\n",
+        "\n",
+        "- TODO: Fill in instantiation params\n",
+        "\n",
+        "Here we show how to instantiate an instance of the __ModuleName__ tool, with "
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 4,
+      "id": "8b3ddfe9-ca79-494c-a7ab-1f56d9407a64",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from langchain_community.tools import __ModuleName__\n",
+        "\n",
+        "\n",
+        "tool = __ModuleName__(...)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "74147a1a",
+      "metadata": {},
+      "source": [
+        "## Invocation\n",
+        "\n",
+        "### [Invoke directly with args](/docs/concepts/tools/#use-the-tool-directly)\n",
+        "\n",
+        "- TODO: Describe what the tool args are, fill them in, run cell"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "65310a8b-eb0c-4d9e-a618-4f4abe2414fc",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "tool.invoke({...})"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "d6e73897",
+      "metadata": {},
+      "source": [
+        "### [Invoke with ToolCall](/docs/concepts/tool_calling/#tool-execution)\n",
+        "\n",
+        "We can also invoke the tool with a model-generated ToolCall, in which case a ToolMessage will be returned:\n",
+        "\n",
+        "- TODO: Fill in tool args and run cell"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "f90e33a7",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# This is usually generated by a model, but we'll create a tool call directly for demo purposes.\n",
+        "model_generated_tool_call = {\n",
+        "    \"args\": {...},  # TODO: FILL IN\n",
+        "    \"id\": \"1\",\n",
+        "    \"name\": tool.name,\n",
+        "    \"type\": \"tool_call\",\n",
+        "}\n",
+        "tool.invoke(model_generated_tool_call)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "659f9fbd-6fcf-445f-aa8c-72d8e60154bd",
+      "metadata": {},
+      "source": [
+        "## Use within an agent\n",
+        "\n",
+        "- TODO: Add user question and run cells\n",
+        "\n",
+        "We can use our tool in an [agent](/docs/concepts/agents/). For this we will need a LLM with [tool-calling](/docs/how_to/tool_calling/) capabilities:\n",
+        "\n",
+        "import ChatModelTabs from \"@theme/ChatModelTabs\";\n",
+        "\n",
+        "<ChatModelTabs customVarName=\"llm\" />\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "af3123ad-7a02-40e5-b58e-7d56e23e5830",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# | output: false\n",
+        "# | echo: false\n",
+        "\n",
+        "# !pip install -qU langchain langchain-openai\n",
+        "from langchain.chat_models import init_chat_model\n",
+        "\n",
+        "model = init_chat_model(model=\"gpt-4o\", model_provider=\"openai\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "bea35fa1",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from langgraph.prebuilt import create_react_agent\n",
+        "\n",
+        "tools = [tool]\n",
+        "agent = create_react_agent(model, tools)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "fdbf35b5-3aaf-4947-9ec6-48c21533fb95",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "example_query = \"...\"\n",
+        "\n",
+        "events = agent.stream(\n",
+        "    {\"messages\": [(\"user\", example_query)]},\n",
+        "    stream_mode=\"values\",\n",
+        ")\n",
+        "for event in events:\n",
+        "    event[\"messages\"][-1].pretty_print()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "4ac8146c",
+      "metadata": {},
+      "source": [
+        "## API reference\n",
+        "\n",
+        "For detailed documentation of all __ModuleName__ features and configurations head to the API reference: https://python.langchain.com/v0.2/api_reference/community/tools/langchain_community.tools.__module_name__.tool.__ModuleName__.html"
+      ]
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "poetry-venv-311",
+      "language": "python",
+      "name": "poetry-venv-311"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.11.9"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 5
+}

libs/cli/langchain_cli/integration_template/docs/vectorstores.ipynb

@@ -0,0 +1,333 @@
+{
+ "cells": [
+  {
+   "cell_type": "raw",
+   "id": "1957f5cb",
+   "metadata": {},
+   "source": [
+    "---\n",
+    "sidebar_label: __ModuleName__\n",
+    "---"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ef1f0986",
+   "metadata": {},
+   "source": [
+    "# __ModuleName__VectorStore\n",
+    "\n",
+    "This notebook covers how to get started with the __ModuleName__ vector store."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "36fdc060",
+   "metadata": {},
+   "source": [
+    "## Setup\n",
+    "\n",
+    "- TODO: Update with relevant info.\n",
+    "- TODO: Update minimum version to be correct.\n",
+    "\n",
+    "To access __ModuleName__ vector stores you'll need to create a/an __ModuleName__ account, get an API key, and install the `__package_name__` integration package."
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "id": "64e28aa6",
+   "metadata": {
+    "vscode": {
+     "languageId": "raw"
+    }
+   },
+   "source": [
+    "%pip install -qU \"__package_name__>=MINIMUM_VERSION\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9695dee7",
+   "metadata": {},
+   "source": [
+    "### Credentials\n",
+    "\n",
+    "- TODO: Update with relevant info.\n",
+    "\n",
+    "Head to (TODO: link) to sign up to __ModuleName__ and generate an API key. Once you've done this set the __MODULE_NAME___API_KEY environment variable:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "894c30e4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import getpass\n",
+    "import os\n",
+    "\n",
+    "if not os.getenv(\"__MODULE_NAME___API_KEY\"):\n",
+    "    os.environ[\"__MODULE_NAME___API_KEY\"] = getpass.getpass(\n",
+    "        \"Enter your __ModuleName__ API key: \"\n",
+    "    )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7f98392b",
+   "metadata": {},
+   "source": "To enable automated tracing of your model calls, set your [LangSmith](https://docs.smith.langchain.com/) API key:"
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e7b6a6e0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# os.environ[\"LANGSMITH_API_KEY\"] = getpass.getpass(\"Enter your LangSmith API key: \")\n",
+    "# os.environ[\"LANGSMITH_TRACING\"] = \"true\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "93df377e",
+   "metadata": {},
+   "source": [
+    "## Initialization\n",
+    "\n",
+    "- TODO: Fill out with relevant init params\n",
+    "\n",
+    "\n",
+    "```{=mdx}\n",
+    "import EmbeddingTabs from \"@theme/EmbeddingTabs\";\n",
+    "\n",
+    "<EmbeddingTabs/>\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "dc37144c-208d-4ab3-9f3a-0407a69fe052",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from __module_name__.vectorstores import __ModuleName__VectorStore\n",
+    "\n",
+    "vector_store = __ModuleName__VectorStore(embeddings=embeddings)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ac6071d4",
+   "metadata": {},
+   "source": [
+    "## Manage vector store\n",
+    "\n",
+    "### Add items to vector store\n",
+    "\n",
+    "- TODO: Edit and then run code cell to generate output"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "17f5efc0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain_core.documents import Document\n",
+    "\n",
+    "document_1 = Document(page_content=\"foo\", metadata={\"source\": \"https://example.com\"})\n",
+    "\n",
+    "document_2 = Document(page_content=\"bar\", metadata={\"source\": \"https://example.com\"})\n",
+    "\n",
+    "document_3 = Document(page_content=\"baz\", metadata={\"source\": \"https://example.com\"})\n",
+    "\n",
+    "documents = [document_1, document_2, document_3]\n",
+    "\n",
+    "vector_store.add_documents(documents=documents, ids=[\"1\", \"2\", \"3\"])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c738c3e0",
+   "metadata": {},
+   "source": [
+    "### Update items in vector store\n",
+    "\n",
+    "- TODO: Edit and then run code cell to generate output"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f0aa8b71",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "updated_document = Document(\n",
+    "    page_content=\"qux\", metadata={\"source\": \"https://another-example.com\"}\n",
+    ")\n",
+    "\n",
+    "vector_store.update_documents(document_id=\"1\", document=updated_document)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dcf1b905",
+   "metadata": {},
+   "source": [
+    "### Delete items from vector store\n",
+    "\n",
+    "- TODO: Edit and then run code cell to generate output"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ef61e188",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "vector_store.delete(ids=[\"3\"])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c3620501",
+   "metadata": {},
+   "source": [
+    "## Query vector store\n",
+    "\n",
+    "Once your vector store has been created and the relevant documents have been added you will most likely wish to query it during the running of your chain or agent.\n",
+    "\n",
+    "### Query directly\n",
+    "\n",
+    "Performing a simple similarity search can be done as follows:\n",
+    "\n",
+    "- TODO: Edit and then run code cell to generate output"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "aa0a16fa",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "results = vector_store.similarity_search(\n",
+    "    query=\"thud\", k=1, filter={\"source\": \"https://another-example.com\"}\n",
+    ")\n",
+    "for doc in results:\n",
+    "    print(f\"* {doc.page_content} [{doc.metadata}]\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3ed9d733",
+   "metadata": {},
+   "source": [
+    "If you want to execute a similarity search and receive the corresponding scores you can run:\n",
+    "\n",
+    "- TODO: Edit and then run code cell to generate output"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5efd2eaa",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "results = vector_store.similarity_search_with_score(\n",
+    "    query=\"thud\", k=1, filter={\"source\": \"https://example.com\"}\n",
+    ")\n",
+    "for doc, score in results:\n",
+    "    print(f\"* [SIM={score:3f}] {doc.page_content} [{doc.metadata}]\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0c235cdc",
+   "metadata": {},
+   "source": [
+    "### Query by turning into retriever\n",
+    "\n",
+    "You can also transform the vector store into a retriever for easier usage in your chains.\n",
+    "\n",
+    "- TODO: Edit and then run code cell to generate output"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f3460093",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "retriever = vector_store.as_retriever(search_type=\"mmr\", search_kwargs={\"k\": 1})\n",
+    "retriever.invoke(\"thud\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "901c75dc",
+   "metadata": {},
+   "source": [
+    "## Usage for retrieval-augmented generation\n",
+    "\n",
+    "For guides on how to use this vector store for retrieval-augmented generation (RAG), see the following sections:\n",
+    "\n",
+    "- [Tutorials](/docs/tutorials/)\n",
+    "- [How-to: Question and answer with RAG](https://python.langchain.com/docs/how_to/#qa-with-rag)\n",
+    "- [Retrieval conceptual docs](https://python.langchain.com/docs/concepts/retrieval/)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "069f1b5f",
+   "metadata": {},
+   "source": [
+    "## TODO: Any functionality specific to this vector store\n",
+    "\n",
+    "E.g. creating a persisten database to save to your disk, etc."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8a27244f",
+   "metadata": {},
+   "source": [
+    "## API reference\n",
+    "\n",
+    "For detailed documentation of all __ModuleName__VectorStore features and configurations head to the API reference: https://api.python.langchain.com/en/latest/vectorstores/__module_name__.vectorstores.__ModuleName__VectorStore.html"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

libs/cli/langchain_cli/integration_template/integration_template/__init__.py

@@ -0,0 +1,27 @@
+from importlib import metadata
+
+from __module_name__.chat_models import Chat__ModuleName__
+from __module_name__.document_loaders import __ModuleName__Loader
+from __module_name__.embeddings import __ModuleName__Embeddings
+from __module_name__.retrievers import __ModuleName__Retriever
+from __module_name__.toolkits import __ModuleName__Toolkit
+from __module_name__.tools import __ModuleName__Tool
+from __module_name__.vectorstores import __ModuleName__VectorStore
+
+try:
+    __version__ = metadata.version(__package__)
+except metadata.PackageNotFoundError:
+    # Case where package metadata is not available.
+    __version__ = ""
+del metadata  # optional, avoids polluting the results of dir(__package__)
+
+__all__ = [
+    "Chat__ModuleName__",
+    "__ModuleName__VectorStore",
+    "__ModuleName__Embeddings",
+    "__ModuleName__Loader",
+    "__ModuleName__Retriever",
+    "__ModuleName__Toolkit",
+    "__ModuleName__Tool",
+    "__version__",
+]

libs/cli/langchain_cli/integration_template/integration_template/chat_models.py

@@ -0,0 +1,423 @@
+"""__ModuleName__ chat models."""
+
+from typing import Any, Dict, Iterator, List
+
+from langchain_core.callbacks import (
+    CallbackManagerForLLMRun,
+)
+from langchain_core.language_models import BaseChatModel
+from langchain_core.messages import (
+    AIMessage,
+    AIMessageChunk,
+    BaseMessage,
+)
+from langchain_core.messages.ai import UsageMetadata
+from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
+from pydantic import Field
+
+
+class Chat__ModuleName__(BaseChatModel):
+    # TODO: Replace all TODOs in docstring. See example docstring:
+    # https://github.com/langchain-ai/langchain/blob/7ff05357bac6eaedf5058a2af88f23a1817d40fe/libs/partners/openai/langchain_openai/chat_models/base.py#L1120
+    """__ModuleName__ chat model integration.
+
+    The default implementation echoes the first `parrot_buffer_length` characters of
+    the input.
+
+    # TODO: Replace with relevant packages, env vars.
+    Setup:
+        Install `__package_name__` and set environment variable
+        `__MODULE_NAME___API_KEY`.
+
+        ```bash
+        pip install -U __package_name__
+        export __MODULE_NAME___API_KEY="your-api-key"
+        ```
+
+    # TODO: Populate with relevant params.
+    Key init args — completion params:
+        model: str
+            Name of __ModuleName__ model to use.
+        temperature: float
+            Sampling temperature.
+        max_tokens: int | None
+            Max number of tokens to generate.
+
+    # TODO: Populate with relevant params.
+    Key init args — client params:
+        timeout: float | None
+            Timeout for requests.
+        max_retries: int
+            Max number of retries.
+        api_key: str | None
+            __ModuleName__ API key. If not passed in will be read from env var
+            __MODULE_NAME___API_KEY.
+
+    See full list of supported init args and their descriptions in the params section.
+
+    # TODO: Replace with relevant init params.
+    Instantiate:
+        ```python
+        from __module_name__ import Chat__ModuleName__
+
+        model = Chat__ModuleName__(
+            model="...",
+            temperature=0,
+            max_tokens=None,
+            timeout=None,
+            max_retries=2,
+            # api_key="...",
+            # other params...
+        )
+        ```
+
+    Invoke:
+        ```python
+        messages = [
+            ("system", "You are a helpful translator. Translate the user sentence to French."),
+            ("human", "I love programming."),
+        ]
+        model.invoke(messages)
+        ```
+
+        ```python
+        # TODO: Example output.
+        ```
+
+    # TODO: Delete if token-level streaming isn't supported.
+    Stream:
+        ```python
+        for chunk in model.stream(messages):
+            print(chunk.text, end="")
+        ```
+
+        ```python
+        # TODO: Example output.
+        ```
+
+        ```python
+        stream = model.stream(messages)
+        full = next(stream)
+        for chunk in stream:
+            full += chunk
+        full
+        ```
+
+        ```python
+        # TODO: Example output.
+        ```
+
+    # TODO: Delete if native async isn't supported.
+    Async:
+        ```python
+        await model.ainvoke(messages)
+
+        # stream:
+        # async for chunk in (await model.astream(messages))
+
+        # batch:
+        # await model.abatch([messages])
+        ```
+
+        ```python
+        # TODO: Example output.
+        ```
+    # TODO: Delete if .bind_tools() isn't supported.
+    Tool calling:
+        ```python
+        from pydantic import BaseModel, Field
+
+        class GetWeather(BaseModel):
+            '''Get the current weather in a given location'''
+
+            location: str = Field(..., description="The city and state, e.g. San Francisco, CA")
+
+        class GetPopulation(BaseModel):
+            '''Get the current population in a given location'''
+
+            location: str = Field(..., description="The city and state, e.g. San Francisco, CA")
+
+        model_with_tools = model.bind_tools([GetWeather, GetPopulation])
+        ai_msg = model_with_tools.invoke("Which city is hotter today and which is bigger: LA or NY?")
+        ai_msg.tool_calls
+        ```
+
+        ```python
+        # TODO: Example output.
+        ```
+
+        See `Chat__ModuleName__.bind_tools()` method for more.
+
+    # TODO: Delete if .with_structured_output() isn't supported.
+    Structured output:
+        ```python
+        from typing import Optional
+
+        from pydantic import BaseModel, Field
+
+        class Joke(BaseModel):
+            '''Joke to tell user.'''
+
+            setup: str = Field(description="The setup of the joke")
+            punchline: str = Field(description="The punchline to the joke")
+            rating: int | None = Field(description="How funny the joke is, from 1 to 10")
+
+        structured_model = model.with_structured_output(Joke)
+        structured_model.invoke("Tell me a joke about cats")
+        ```
+
+        ```python
+        # TODO: Example output.
+        ```
+
+        See `Chat__ModuleName__.with_structured_output()` for more.
+
+    # TODO: Delete if JSON mode response format isn't supported.
+    JSON mode:
+        ```python
+        # TODO: Replace with appropriate bind arg.
+        json_model = model.bind(response_format={"type": "json_object"})
+        ai_msg = json_model.invoke("Return a JSON object with key 'random_ints' and a value of 10 random ints in [0-99]")
+        ai_msg.content
+        ```
+
+        ```python
+        # TODO: Example output.
+        ```
+
+    # TODO: Delete if image inputs aren't supported.
+    Image input:
+        ```python
+        import base64
+        import httpx
+        from langchain_core.messages import HumanMessage
+
+        image_url = "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
+        image_data = base64.b64encode(httpx.get(image_url).content).decode("utf-8")
+        # TODO: Replace with appropriate message content format.
+        message = HumanMessage(
+            content=[
+                {"type": "text", "text": "describe the weather in this image"},
+                {
+                    "type": "image_url",
+                    "image_url": {"url": f"data:image/jpeg;base64,{image_data}"},
+                },
+            ],
+        )
+        ai_msg = model.invoke([message])
+        ai_msg.content
+        ```
+
+        ```python
+        # TODO: Example output.
+        ```
+
+    # TODO: Delete if audio inputs aren't supported.
+    Audio input:
+        ```python
+        # TODO: Example input
+        ```
+
+        ```python
+        # TODO: Example output
+        ```
+
+    # TODO: Delete if video inputs aren't supported.
+    Video input:
+        ```python
+        # TODO: Example input
+        ```
+
+        ```python
+        # TODO: Example output
+        ```
+
+    # TODO: Delete if token usage metadata isn't supported.
+    Token usage:
+        ```python
+        ai_msg = model.invoke(messages)
+        ai_msg.usage_metadata
+        ```
+
+        ```python
+        {'input_tokens': 28, 'output_tokens': 5, 'total_tokens': 33}
+        ```
+
+    # TODO: Delete if logprobs aren't supported.
+    Logprobs:
+        ```python
+        # TODO: Replace with appropriate bind arg.
+        logprobs_model = model.bind(logprobs=True)
+        ai_msg = logprobs_model.invoke(messages)
+        ai_msg.response_metadata["logprobs"]
+        ```
+
+        ```python
+        # TODO: Example output.
+        ```
+    Response metadata
+        ```python
+        ai_msg = model.invoke(messages)
+        ai_msg.response_metadata
+        ```
+
+        ```python
+        # TODO: Example output.
+
+        ```
+    """  # noqa: E501
+
+    model_name: str = Field(alias="model")
+    """The name of the model"""
+    parrot_buffer_length: int
+    """The number of characters from the last message of the prompt to be echoed."""
+    temperature: float | None = None
+    max_tokens: int | None = None
+    timeout: int | None = None
+    stop: list[str] | None = None
+    max_retries: int = 2
+
+    @property
+    def _llm_type(self) -> str:
+        """Return type of chat model."""
+        return "chat-__package_name_short__"
+
+    @property
+    def _identifying_params(self) -> Dict[str, Any]:
+        """Return a dictionary of identifying parameters.
+
+        This information is used by the LangChain callback system, which
+        is used for tracing purposes make it possible to monitor LLMs.
+        """
+        return {
+            # The model name allows users to specify custom token counting
+            # rules in LLM monitoring applications (e.g., in LangSmith users
+            # can provide per token pricing for their model and monitor
+            # costs for the given LLM.)
+            "model_name": self.model_name,
+        }
+
+    def _generate(
+        self,
+        messages: List[BaseMessage],
+        stop: list[str] | None = None,
+        run_manager: CallbackManagerForLLMRun | None = None,
+        **kwargs: Any,
+    ) -> ChatResult:
+        """Override the _generate method to implement the chat model logic.
+
+        This can be a call to an API, a call to a local model, or any other
+        implementation that generates a response to the input prompt.
+
+        Args:
+            messages: the prompt composed of a list of messages.
+            stop: a list of strings on which the model should stop generating.
+                If generation stops due to a stop token, the stop token itself
+                SHOULD BE INCLUDED as part of the output. This is not enforced
+                across models right now, but it's a good practice to follow since
+                it makes it much easier to parse the output of the model
+                downstream and understand why generation stopped.
+            run_manager: A run manager with callbacks for the LLM.
+        """
+        # Replace this with actual logic to generate a response from a list
+        # of messages.
+        last_message = messages[-1]
+        tokens = last_message.content[: self.parrot_buffer_length]
+        ct_input_tokens = sum(len(message.content) for message in messages)
+        ct_output_tokens = len(tokens)
+        message = AIMessage(
+            content=tokens,
+            additional_kwargs={},  # Used to add additional payload to the message
+            response_metadata={  # Use for response metadata
+                "time_in_seconds": 3,
+                "model_name": self.model_name,
+            },
+            usage_metadata={
+                "input_tokens": ct_input_tokens,
+                "output_tokens": ct_output_tokens,
+                "total_tokens": ct_input_tokens + ct_output_tokens,
+            },
+        )
+        ##
+
+        generation = ChatGeneration(message=message)
+        return ChatResult(generations=[generation])
+
+    def _stream(
+        self,
+        messages: List[BaseMessage],
+        stop: list[str] | None = None,
+        run_manager: CallbackManagerForLLMRun | None = None,
+        **kwargs: Any,
+    ) -> Iterator[ChatGenerationChunk]:
+        """Stream the output of the model.
+
+        This method should be implemented if the model can generate output
+        in a streaming fashion. If the model does not support streaming,
+        do not implement it. In that case streaming requests will be automatically
+        handled by the _generate method.
+
+        Args:
+            messages: the prompt composed of a list of messages.
+            stop: a list of strings on which the model should stop generating.
+                If generation stops due to a stop token, the stop token itself
+                SHOULD BE INCLUDED as part of the output. This is not enforced
+                across models right now, but it's a good practice to follow since
+                it makes it much easier to parse the output of the model
+                downstream and understand why generation stopped.
+            run_manager: A run manager with callbacks for the LLM.
+        """
+        last_message = messages[-1]
+        tokens = str(last_message.content[: self.parrot_buffer_length])
+        ct_input_tokens = sum(len(message.content) for message in messages)
+
+        for token in tokens:
+            usage_metadata = UsageMetadata(
+                {
+                    "input_tokens": ct_input_tokens,
+                    "output_tokens": 1,
+                    "total_tokens": ct_input_tokens + 1,
+                }
+            )
+            ct_input_tokens = 0
+            chunk = ChatGenerationChunk(
+                message=AIMessageChunk(content=token, usage_metadata=usage_metadata)
+            )
+
+            if run_manager:
+                # This is optional in newer versions of LangChain
+                # The on_llm_new_token will be called automatically
+                run_manager.on_llm_new_token(token, chunk=chunk)
+
+            yield chunk
+
+        # Let's add some other information (e.g., response metadata)
+        chunk = ChatGenerationChunk(
+            message=AIMessageChunk(
+                content="",
+                response_metadata={"time_in_sec": 3, "model_name": self.model_name},
+            )
+        )
+        if run_manager:
+            # This is optional in newer versions of LangChain
+            # The on_llm_new_token will be called automatically
+            run_manager.on_llm_new_token(token, chunk=chunk)
+        yield chunk
+
+    # TODO: Implement if Chat__ModuleName__ supports async streaming. Otherwise delete.
+    # async def _astream(
+    #     self,
+    #     messages: List[BaseMessage],
+    #     stop: list[str] | None = None,
+    #     run_manager: AsyncCallbackManagerForLLMRun | None = None,
+    #     **kwargs: Any,
+    # ) -> AsyncIterator[ChatGenerationChunk]:
+
+    # TODO: Implement if Chat__ModuleName__ supports async generation. Otherwise delete.
+    # async def _agenerate(
+    #     self,
+    #     messages: List[BaseMessage],
+    #     stop: list[str] | None = None,
+    #     run_manager: AsyncCallbackManagerForLLMRun | None = None,
+    #     **kwargs: Any,
+    # ) -> ChatResult:

libs/cli/langchain_cli/integration_template/integration_template/document_loaders.py

@@ -0,0 +1,74 @@
+"""__ModuleName__ document loader."""
+
+from typing import Iterator
+
+from langchain_core.document_loaders.base import BaseLoader
+from langchain_core.documents import Document
+
+
+class __ModuleName__Loader(BaseLoader):
+    # TODO: Replace all TODOs in docstring. See example docstring:
+    # https://github.com/langchain-ai/langchain/blob/869523ad728e6b76d77f170cce13925b4ebc3c1e/libs/community/langchain_community/document_loaders/recursive_url_loader.py#L54
+    """
+    __ModuleName__ document loader integration
+
+    # TODO: Replace with relevant packages, env vars.
+    Setup:
+        Install `__package_name__` and set environment variable
+        `__MODULE_NAME___API_KEY`.
+
+        ```bash
+        pip install -U __package_name__
+        export __MODULE_NAME___API_KEY="your-api-key"
+        ```
+
+    # TODO: Replace with relevant init params.
+    Instantiate:
+        ```python
+        from langchain_community.document_loaders import __ModuleName__Loader
+
+        loader = __ModuleName__Loader(
+            # required params = ...
+            # other params = ...
+        )
+        ```
+
+    Lazy load:
+        ```python
+        docs = []
+        docs_lazy = loader.lazy_load()
+
+        # async variant:
+        # docs_lazy = await loader.alazy_load()
+
+        for doc in docs_lazy:
+            docs.append(doc)
+        print(docs[0].page_content[:100])
+        print(docs[0].metadata)
+        ```
+
+        ```python
+        TODO: Example output
+        ```
+
+    # TODO: Delete if async load is not implemented
+    Async load:
+        ```python
+        docs = await loader.aload()
+        print(docs[0].page_content[:100])
+        print(docs[0].metadata)
+        ```
+
+        ```python
+        TODO: Example output
+
+        ```
+    """
+
+    # TODO: This method must be implemented to load documents.
+    # Do not implement load(), a default implementation is already available.
+    def lazy_load(self) -> Iterator[Document]:
+        raise NotImplementedError()
+
+    # TODO: Implement if you would like to change default BaseLoader implementation
+    # async def alazy_load(self) -> AsyncIterator[Document]:

libs/cli/langchain_cli/integration_template/integration_template/embeddings.py

@@ -0,0 +1,96 @@
+from typing import List
+
+from langchain_core.embeddings import Embeddings
+
+
+class __ModuleName__Embeddings(Embeddings):
+    """__ModuleName__ embedding model integration.
+
+    # TODO: Replace with relevant packages, env vars.
+    Setup:
+        Install `__package_name__` and set environment variable
+        `__MODULE_NAME___API_KEY`.
+
+        ```bash
+        pip install -U __package_name__
+        export __MODULE_NAME___API_KEY="your-api-key"
+        ```
+
+    # TODO: Populate with relevant params.
+    Key init args — completion params:
+        model: str
+            Name of __ModuleName__ model to use.
+
+    See full list of supported init args and their descriptions in the params section.
+
+    # TODO: Replace with relevant init params.
+    Instantiate:
+        ```python
+        from __module_name__ import __ModuleName__Embeddings
+
+        embed = __ModuleName__Embeddings(
+            model="...",
+            # api_key="...",
+            # other params...
+        )
+        ```
+
+    Embed single text:
+        ```python
+        input_text = "The meaning of life is 42"
+        embed.embed_query(input_text)
+        ```
+
+        ```python
+        # TODO: Example output.
+        ```
+
+    # TODO: Delete if token-level streaming isn't supported.
+    Embed multiple text:
+        ```python
+        input_texts = ["Document 1...", "Document 2..."]
+        embed.embed_documents(input_texts)
+        ```
+
+        ```python
+        # TODO: Example output.
+        ```
+
+    # TODO: Delete if native async isn't supported.
+    Async:
+        ```python
+        await embed.aembed_query(input_text)
+
+        # multiple:
+        # await embed.aembed_documents(input_texts)
+        ```
+
+        ```python
+        # TODO: Example output.
+
+        ```
+    """
+
+    def __init__(self, model: str):
+        self.model = model
+
+    def embed_documents(self, texts: List[str]) -> List[List[float]]:
+        """Embed search docs."""
+        return [[0.5, 0.6, 0.7] for _ in texts]
+
+    def embed_query(self, text: str) -> List[float]:
+        """Embed query text."""
+        return self.embed_documents([text])[0]
+
+    # optional: add custom async implementations here
+    # you can also delete these, and the base class will
+    # use the default implementation, which calls the sync
+    # version in an async executor:
+
+    # async def aembed_documents(self, texts: List[str]) -> List[List[float]]:
+    #     """Asynchronous Embed search docs."""
+    #     ...
+
+    # async def aembed_query(self, text: str) -> List[float]:
+    #     """Asynchronous Embed query text."""
+    #     ...

libs/cli/langchain_cli/integration_template/integration_template/retrievers.py

@@ -0,0 +1,107 @@
+"""__ModuleName__ retrievers."""
+
+from typing import Any, List
+
+from langchain_core.callbacks import CallbackManagerForRetrieverRun
+from langchain_core.documents import Document
+from langchain_core.retrievers import BaseRetriever
+
+
+class __ModuleName__Retriever(BaseRetriever):
+    # TODO: Replace all TODOs in docstring. See example docstring:
+    # https://github.com/langchain-ai/langchain/blob/master/libs/community/langchain_community/retrievers/tavily_search_api.py#L17
+    """__ModuleName__ retriever.
+
+    # TODO: Replace with relevant packages, env vars, etc.
+    Setup:
+        Install `__package_name__` and set environment variable
+        `__MODULE_NAME___API_KEY`.
+
+        ```bash
+        pip install -U __package_name__
+        export __MODULE_NAME___API_KEY="your-api-key"
+        ```
+
+    # TODO: Populate with relevant params.
+    Key init args:
+        arg 1: type
+            description
+        arg 2: type
+            description
+
+    # TODO: Replace with relevant init params.
+    Instantiate:
+        ```python
+        from __package_name__ import __ModuleName__Retriever
+
+        retriever = __ModuleName__Retriever(
+            # ...
+        )
+        ```
+
+    Usage:
+        ```python
+        query = "..."
+
+        retriever.invoke(query)
+        ```
+
+        ```txt
+        # TODO: Example output.
+        ```
+
+    Use within a chain:
+        ```python
+        from langchain_core.output_parsers import StrOutputParser
+        from langchain_core.prompts import ChatPromptTemplate
+        from langchain_core.runnables import RunnablePassthrough
+        from langchain_openai import ChatOpenAI
+
+        prompt = ChatPromptTemplate.from_template(
+            \"\"\"Answer the question based only on the context provided.
+
+        Context: {context}
+
+        Question: {question}\"\"\"
+        )
+
+        model = ChatOpenAI(model="gpt-3.5-turbo-0125")
+
+        def format_docs(docs):
+            return "\\n\\n".join(doc.page_content for doc in docs)
+
+        chain = (
+            {"context": retriever | format_docs, "question": RunnablePassthrough()}
+            | prompt
+            | model
+            | StrOutputParser()
+        )
+
+        chain.invoke("...")
+        ```
+
+        ```
+        # TODO: Example output.
+        ```
+
+    """
+
+    k: int = 3
+
+    # TODO: This method must be implemented to retrieve documents.
+    def _get_relevant_documents(
+        self, query: str, *, run_manager: CallbackManagerForRetrieverRun, **kwargs: Any
+    ) -> List[Document]:
+        k = kwargs.get("k", self.k)
+        return [
+            Document(page_content=f"Result {i} for query: {query}") for i in range(k)
+        ]
+
+    # optional: add custom async implementations here
+    # async def _aget_relevant_documents(
+    #     self,
+    #     query: str,
+    #     *,
+    #     run_manager: AsyncCallbackManagerForRetrieverRun,
+    #     **kwargs: Any,
+    # ) -> List[Document]: ...

libs/cli/langchain_cli/integration_template/integration_template/toolkits.py

@@ -0,0 +1,73 @@
+"""__ModuleName__ toolkits."""
+
+from typing import List
+
+from langchain_core.tools import BaseTool, BaseToolkit
+
+
+class __ModuleName__Toolkit(BaseToolkit):
+    # TODO: Replace all TODOs in docstring. See example docstring:
+    # https://github.com/langchain-ai/langchain/blob/c123cb2b304f52ab65db4714eeec46af69a861ec/libs/community/langchain_community/agent_toolkits/sql/toolkit.py#L19
+    """__ModuleName__ toolkit.
+
+    # TODO: Replace with relevant packages, env vars, etc.
+    Setup:
+        Install `__package_name__` and set environment variable
+        `__MODULE_NAME___API_KEY`.
+
+        ```bash
+        pip install -U __package_name__
+        export __MODULE_NAME___API_KEY="your-api-key"
+        ```
+
+    # TODO: Populate with relevant params.
+    Key init args:
+        arg 1: type
+            description
+        arg 2: type
+            description
+
+    # TODO: Replace with relevant init params.
+    Instantiate:
+        ```python
+        from __package_name__ import __ModuleName__Toolkit
+
+        toolkit = __ModuleName__Toolkit(
+            # ...
+        )
+        ```
+
+    Tools:
+        ```python
+        toolkit.get_tools()
+        ```
+
+        ```txt
+        # TODO: Example output.
+        ```
+
+    Use within an agent:
+        ```python
+        from langgraph.prebuilt import create_react_agent
+
+        agent_executor = create_react_agent(llm, tools)
+
+        example_query = "..."
+
+        events = agent_executor.stream(
+            {"messages": [("user", example_query)]},
+            stream_mode="values",
+        )
+        for event in events:
+            event["messages"][-1].pretty_print()
+        ```
+
+        ```txt
+        # TODO: Example output.
+        ```
+
+    """
+
+    # TODO: This method must be implemented to list tools.
+    def get_tools(self) -> List[BaseTool]:
+        raise NotImplementedError()

libs/cli/langchain_cli/integration_template/integration_template/tools.py

@@ -0,0 +1,95 @@
+"""__ModuleName__ tools."""
+
+from typing import Type
+
+from langchain_core.callbacks import (
+    CallbackManagerForToolRun,
+)
+from langchain_core.tools import BaseTool
+from pydantic import BaseModel, Field
+
+
+class __ModuleName__ToolInput(BaseModel):
+    """Input schema for __ModuleName__ tool.
+
+    This docstring is **not** part of what is sent to the model when performing tool
+    calling. The Field default values and descriptions **are** part of what is sent to
+    the model when performing tool calling.
+    """
+
+    # TODO: Add input args and descriptions.
+    a: int = Field(..., description="first number to add")
+    b: int = Field(..., description="second number to add")
+
+
+class __ModuleName__Tool(BaseTool):  # type: ignore[override]
+    """__ModuleName__ tool.
+
+    Setup:
+        # TODO: Replace with relevant packages, env vars.
+        Install `__package_name__` and set environment variable
+        `__MODULE_NAME___API_KEY`.
+
+        ```bash
+        pip install -U __package_name__
+        export __MODULE_NAME___API_KEY="your-api-key"
+        ```
+
+    Instantiation:
+        ```python
+        tool = __ModuleName__Tool(
+            # TODO: init params
+        )
+        ```
+
+    Invocation with args:
+        ```python
+        # TODO: invoke args
+        tool.invoke({...})
+        ```
+
+        ```python
+        # TODO: output of invocation
+        ```
+
+    Invocation with ToolCall:
+
+        ```python
+        # TODO: invoke args
+        tool.invoke({"args": {...}, "id": "1", "name": tool.name, "type": "tool_call"})
+        ```
+
+        ```python
+        # TODO: output of invocation
+
+        ```
+    """  # noqa: E501
+
+    # TODO: Set tool name and description
+    name: str = "TODO: Tool name"
+    """The name that is passed to the model when performing tool calling."""
+    description: str = "TODO: Tool description."
+    """The description that is passed to the model when performing tool calling."""
+    args_schema: Type[BaseModel] = __ModuleName__ToolInput
+    """The schema that is passed to the model when performing tool calling."""
+
+    # TODO: Add any other init params for the tool.
+    # param1: str | None
+    # """param1 determines foobar"""
+
+    # TODO: Replaced (a, b) with real tool arguments.
+    def _run(
+        self, a: int, b: int, *, run_manager: CallbackManagerForToolRun | None = None
+    ) -> str:
+        return str(a + b + 80)
+
+    # TODO: Implement if tool has native async functionality, otherwise delete.
+
+    # async def _arun(
+    #     self,
+    #     a: int,
+    #     b: int,
+    #     *,
+    #     run_manager: AsyncCallbackManagerForToolRun | None = None,
+    # ) -> str:
+    #     ...

libs/cli/langchain_cli/integration_template/integration_template/vectorstores.py

@@ -0,0 +1,438 @@
+"""__ModuleName__ vector stores."""
+
+from __future__ import annotations
+
+import uuid
+from typing import (
+    Any,
+    Callable,
+    Iterator,
+    List,
+    Sequence,
+    Tuple,
+    Type,
+    TypeVar,
+)
+
+from langchain_core.documents import Document
+from langchain_core.embeddings import Embeddings
+from langchain_core.vectorstores import VectorStore
+from langchain_core.vectorstores.utils import _cosine_similarity as cosine_similarity
+
+VST = TypeVar("VST", bound=VectorStore)
+
+
+class __ModuleName__VectorStore(VectorStore):
+    # TODO: Replace all TODOs in docstring.
+    """__ModuleName__ vector store integration.
+
+    # TODO: Replace with relevant packages, env vars.
+    Setup:
+        Install `__package_name__` and set environment variable `__MODULE_NAME___API_KEY`.
+
+        ```bash
+        pip install -U __package_name__
+        export __MODULE_NAME___API_KEY="your-api-key"
+        ```
+
+    # TODO: Populate with relevant params.
+    Key init args — indexing params:
+        collection_name: str
+            Name of the collection.
+        embedding_function: Embeddings
+            Embedding function to use.
+
+    # TODO: Populate with relevant params.
+    Key init args — client params:
+        client: Client | None
+            Client to use.
+        connection_args: dict | None
+            Connection arguments.
+
+    # TODO: Replace with relevant init params.
+    Instantiate:
+        ```python
+        from __module_name__.vectorstores import __ModuleName__VectorStore
+        from langchain_openai import OpenAIEmbeddings
+
+        vector_store = __ModuleName__VectorStore(
+            collection_name="foo",
+            embedding_function=OpenAIEmbeddings(),
+            connection_args={"uri": "./foo.db"},
+            # other params...
+        )
+        ```
+
+    # TODO: Populate with relevant variables.
+    Add Documents:
+        ```python
+        from langchain_core.documents import Document
+
+        document_1 = Document(page_content="foo", metadata={"baz": "bar"})
+        document_2 = Document(page_content="thud", metadata={"bar": "baz"})
+        document_3 = Document(page_content="i will be deleted :(")
+
+        documents = [document_1, document_2, document_3]
+        ids = ["1", "2", "3"]
+        vector_store.add_documents(documents=documents, ids=ids)
+        ```
+
+    # TODO: Populate with relevant variables.
+    Delete Documents:
+        ```python
+        vector_store.delete(ids=["3"])
+        ```
+
+    # TODO: Fill out with relevant variables and example output.
+    Search:
+        ```python
+        results = vector_store.similarity_search(query="thud",k=1)
+        for doc in results:
+            print(f"* {doc.page_content} [{doc.metadata}]")
+        ```
+
+        ```python
+        # TODO: Example output
+        ```
+
+    # TODO: Fill out with relevant variables and example output.
+    Search with filter:
+        ```python
+        results = vector_store.similarity_search(query="thud",k=1,filter={"bar": "baz"})
+        for doc in results:
+            print(f"* {doc.page_content} [{doc.metadata}]")
+        ```
+
+        ```python
+        # TODO: Example output
+        ```
+
+    # TODO: Fill out with relevant variables and example output.
+    Search with score:
+        ```python
+        results = vector_store.similarity_search_with_score(query="qux",k=1)
+        for doc, score in results:
+            print(f"* [SIM={score:3f}] {doc.page_content} [{doc.metadata}]")
+        ```
+
+        ```python
+        # TODO: Example output
+        ```
+
+    # TODO: Fill out with relevant variables and example output.
+    Async:
+        ```python
+        # add documents
+        # await vector_store.aadd_documents(documents=documents, ids=ids)
+
+        # delete documents
+        # await vector_store.adelete(ids=["3"])
+
+        # search
+        # results = vector_store.asimilarity_search(query="thud",k=1)
+
+        # search with score
+        results = await vector_store.asimilarity_search_with_score(query="qux",k=1)
+        for doc,score in results:
+            print(f"* [SIM={score:3f}] {doc.page_content} [{doc.metadata}]")
+        ```
+
+        ```python
+        # TODO: Example output
+        ```
+
+    # TODO: Fill out with relevant variables and example output.
+    Use as Retriever:
+        ```python
+        retriever = vector_store.as_retriever(
+            search_type="mmr",
+            search_kwargs={"k": 1, "fetch_k": 2, "lambda_mult": 0.5},
+        )
+        retriever.invoke("thud")
+        ```
+
+        ```python
+        # TODO: Example output
+
+        ```
+    """  # noqa: E501
+
+    def __init__(self, embedding: Embeddings) -> None:
+        """Initialize with the given embedding function.
+
+        Args:
+            embedding: embedding function to use.
+        """
+        self._database: dict[str, dict[str, Any]] = {}
+        self.embedding = embedding
+
+    @classmethod
+    def from_texts(
+        cls: Type[__ModuleName__VectorStore],
+        texts: List[str],
+        embedding: Embeddings,
+        metadatas: list[dict] | None = None,
+        **kwargs: Any,
+    ) -> __ModuleName__VectorStore:
+        store = cls(
+            embedding=embedding,
+        )
+        store.add_texts(texts=texts, metadatas=metadatas, **kwargs)
+        return store
+
+    # optional: add custom async implementations
+    # @classmethod
+    # async def afrom_texts(
+    #     cls: Type[VST],
+    #     texts: List[str],
+    #     embedding: Embeddings,
+    #     metadatas: list[dict] | None = None,
+    #     **kwargs: Any,
+    # ) -> VST:
+    #     return await asyncio.get_running_loop().run_in_executor(
+    #         None, partial(cls.from_texts, **kwargs), texts, embedding, metadatas
+    #     )
+
+    @property
+    def embeddings(self) -> Embeddings:
+        return self.embedding
+
+    def add_documents(
+        self,
+        documents: List[Document],
+        ids: list[str] | None = None,
+        **kwargs: Any,
+    ) -> List[str]:
+        """Add documents to the store."""
+        texts = [doc.page_content for doc in documents]
+        vectors = self.embedding.embed_documents(texts)
+
+        if ids and len(ids) != len(texts):
+            msg = (
+                f"ids must be the same length as texts. "
+                f"Got {len(ids)} ids and {len(texts)} texts."
+            )
+            raise ValueError(msg)
+
+        id_iterator: Iterator[str | None] = (
+            iter(ids) if ids else iter(doc.id for doc in documents)
+        )
+
+        ids_ = []
+
+        for doc, vector in zip(documents, vectors):
+            doc_id = next(id_iterator)
+            doc_id_ = doc_id if doc_id else str(uuid.uuid4())
+            ids_.append(doc_id_)
+            self._database[doc_id_] = {
+                "id": doc_id_,
+                "vector": vector,
+                "text": doc.page_content,
+                "metadata": doc.metadata,
+            }
+
+        return ids_
+
+    # optional: add custom async implementations
+    # async def aadd_documents(
+    #     self,
+    #     documents: List[Document],
+    #     ids: list[str] | None = None,
+    #     **kwargs: Any,
+    # ) -> List[str]:
+    #     raise NotImplementedError
+
+    def delete(self, ids: list[str] | None = None, **kwargs: Any) -> None:
+        if ids:
+            for _id in ids:
+                self._database.pop(_id, None)
+
+    # optional: add custom async implementations
+    # async def adelete(
+    #     self, ids: list[str] | None = None, **kwargs: Any
+    # ) -> None:
+    #     raise NotImplementedError
+
+    def get_by_ids(self, ids: Sequence[str], /) -> list[Document]:
+        """Get documents by their ids.
+
+        Args:
+            ids: The ids of the documents to get.
+
+        Returns:
+            A list of Document objects.
+        """
+        documents = []
+
+        for doc_id in ids:
+            doc = self._database.get(doc_id)
+            if doc:
+                documents.append(
+                    Document(
+                        id=doc["id"],
+                        page_content=doc["text"],
+                        metadata=doc["metadata"],
+                    )
+                )
+        return documents
+
+    # optional: add custom async implementations
+    # async def aget_by_ids(self, ids: Sequence[str], /) -> list[Document]:
+    #     raise NotImplementedError
+
+    # NOTE: the below helper method implements similarity search for in-memory
+    # storage. It is optional and not a part of the vector store interface.
+    def _similarity_search_with_score_by_vector(
+        self,
+        embedding: List[float],
+        k: int = 4,
+        filter: Callable[[Document], bool] | None = None,
+        **kwargs: Any,
+    ) -> List[tuple[Document, float, List[float]]]:
+        # get all docs with fixed order in list
+        docs = list(self._database.values())
+
+        if filter is not None:
+            docs = [
+                doc
+                for doc in docs
+                if filter(Document(page_content=doc["text"], metadata=doc["metadata"]))
+            ]
+
+        if not docs:
+            return []
+
+        similarity = cosine_similarity([embedding], [doc["vector"] for doc in docs])[0]
+
+        # get the indices ordered by similarity score
+        top_k_idx = similarity.argsort()[::-1][:k]
+
+        return [
+            (
+                # Document
+                Document(
+                    id=doc_dict["id"],
+                    page_content=doc_dict["text"],
+                    metadata=doc_dict["metadata"],
+                ),
+                # Score
+                float(similarity[idx].item()),
+                # Embedding vector
+                doc_dict["vector"],
+            )
+            for idx in top_k_idx
+            # Assign using walrus operator to avoid multiple lookups
+            if (doc_dict := docs[idx])
+        ]
+
+    def similarity_search(
+        self, query: str, k: int = 4, **kwargs: Any
+    ) -> List[Document]:
+        embedding = self.embedding.embed_query(query)
+        return [
+            doc
+            for doc, _, _ in self._similarity_search_with_score_by_vector(
+                embedding=embedding, k=k, **kwargs
+            )
+        ]
+
+    # optional: add custom async implementations
+    # async def asimilarity_search(
+    #     self, query: str, k: int = 4, **kwargs: Any
+    # ) -> List[Document]:
+    #     # This is a temporary workaround to make the similarity search
+    #     # asynchronous. The proper solution is to make the similarity search
+    #     # asynchronous in the vector store implementations.
+    #     func = partial(self.similarity_search, query, k=k, **kwargs)
+    #     return await asyncio.get_event_loop().run_in_executor(None, func)
+
+    def similarity_search_with_score(
+        self, query: str, k: int = 4, **kwargs: Any
+    ) -> List[Tuple[Document, float]]:
+        embedding = self.embedding.embed_query(query)
+        return [
+            (doc, similarity)
+            for doc, similarity, _ in self._similarity_search_with_score_by_vector(
+                embedding=embedding, k=k, **kwargs
+            )
+        ]
+
+    # optional: add custom async implementations
+    # async def asimilarity_search_with_score(
+    #     self, *args: Any, **kwargs: Any
+    # ) -> List[Tuple[Document, float]]:
+    #     # This is a temporary workaround to make the similarity search
+    #     # asynchronous. The proper solution is to make the similarity search
+    #     # asynchronous in the vector store implementations.
+    #     func = partial(self.similarity_search_with_score, *args, **kwargs)
+    #     return await asyncio.get_event_loop().run_in_executor(None, func)
+
+    ### ADDITIONAL OPTIONAL SEARCH METHODS BELOW ###
+
+    # def similarity_search_by_vector(
+    #     self, embedding: List[float], k: int = 4, **kwargs: Any
+    # ) -> List[Document]:
+    #     raise NotImplementedError
+
+    # optional: add custom async implementations
+    # async def asimilarity_search_by_vector(
+    #     self, embedding: List[float], k: int = 4, **kwargs: Any
+    # ) -> List[Document]:
+    #     # This is a temporary workaround to make the similarity search
+    #     # asynchronous. The proper solution is to make the similarity search
+    #     # asynchronous in the vector store implementations.
+    #     func = partial(self.similarity_search_by_vector, embedding, k=k, **kwargs)
+    #     return await asyncio.get_event_loop().run_in_executor(None, func)
+
+    # def max_marginal_relevance_search(
+    #     self,
+    #     query: str,
+    #     k: int = 4,
+    #     fetch_k: int = 20,
+    #     lambda_mult: float = 0.5,
+    #     **kwargs: Any,
+    # ) -> List[Document]:
+    #     raise NotImplementedError
+
+    # optional: add custom async implementations
+    # async def amax_marginal_relevance_search(
+    #     self,
+    #     query: str,
+    #     k: int = 4,
+    #     fetch_k: int = 20,
+    #     lambda_mult: float = 0.5,
+    #     **kwargs: Any,
+    # ) -> List[Document]:
+    #     # This is a temporary workaround to make the similarity search
+    #     # asynchronous. The proper solution is to make the similarity search
+    #     # asynchronous in the vector store implementations.
+    #     func = partial(
+    #         self.max_marginal_relevance_search,
+    #         query,
+    #         k=k,
+    #         fetch_k=fetch_k,
+    #         lambda_mult=lambda_mult,
+    #         **kwargs,
+    #     )
+    #     return await asyncio.get_event_loop().run_in_executor(None, func)
+
+    # def max_marginal_relevance_search_by_vector(
+    #     self,
+    #     embedding: List[float],
+    #     k: int = 4,
+    #     fetch_k: int = 20,
+    #     lambda_mult: float = 0.5,
+    #     **kwargs: Any,
+    # ) -> List[Document]:
+    #     raise NotImplementedError
+
+    # optional: add custom async implementations
+    # async def amax_marginal_relevance_search_by_vector(
+    #     self,
+    #     embedding: List[float],
+    #     k: int = 4,
+    #     fetch_k: int = 20,
+    #     lambda_mult: float = 0.5,
+    #     **kwargs: Any,
+    # ) -> List[Document]:
+    #     raise NotImplementedError

libs/cli/langchain_cli/integration_template/pyproject.toml

@@ -0,0 +1,50 @@
+[build-system]
+requires = ["pdm-backend"]
+build-backend = "pdm.backend"
+
+[project]
+name = "__package_name__"
+version = "0.1.0"
+description = "An integration package connecting __ModuleName__ and LangChain"
+authors = []
+readme = "README.md"
+license = "MIT"
+requires-python = ">=3.10.0,<4.0.0"
+dependencies = [
+    "langchain-core>=0.3.15",
+]
+
+[project.urls]
+"Source Code" = "https://github.com/langchain-ai/langchain/tree/master/libs/partners/__package_name_short__"
+"Release Notes" = "https://github.com/langchain-ai/langchain/releases?q=tag%3A%22__package_name_short__%3D%3D0%22&expanded=true"
+"Repository" = "https://github.com/langchain-ai/langchain"
+
+[tool.mypy]
+disallow_untyped_defs = "True"
+
+[tool.uv]
+dev-dependencies = [
+    "pytest>=7.4.3",
+    "pytest-asyncio>=0.23.2",
+    "pytest-socket>=0.7.0",
+    "pytest-watcher>=0.3.4",
+    "langchain-tests>=0.3.5",
+    "ruff>=0.5",
+    "mypy>=1.10",
+]
+
+[tool.ruff.lint]
+select = ["E", "F", "I", "T201"]
+
+[tool.ruff.lint.per-file-ignores]
+"docs/**" = [ "ALL",]
+
+[tool.coverage.run]
+omit = ["tests/*"]
+
+[tool.pytest.ini_options]
+addopts = "--strict-markers --strict-config --durations=5"
+markers = [
+    "compile: mark placeholder test used to compile integration tests without running them",
+]
+asyncio_mode = "auto"

libs/cli/langchain_cli/integration_template/scripts/check_imports.py

@@ -0,0 +1,17 @@
+import sys
+import traceback
+from importlib.machinery import SourceFileLoader
+
+if __name__ == "__main__":
+    files = sys.argv[1:]
+    has_failure = False
+    for file in files:
+        try:
+            SourceFileLoader("x", file).load_module()
+        except Exception:
+            has_failure = True
+            print(file)  # noqa: T201
+            traceback.print_exc()
+            print()  # noqa: T201
+
+    sys.exit(1 if has_failure else 0)

libs/cli/langchain_cli/integration_template/scripts/lint_imports.sh

@@ -0,0 +1,18 @@
+#!/bin/bash
+
+set -eu
+
+# Initialize a variable to keep track of errors
+errors=0
+
+# make sure not importing from langchain, langchain_experimental, or langchain_community
+git --no-pager grep '^from langchain\.' . && errors=$((errors+1))
+git --no-pager grep '^from langchain_experimental\.' . && errors=$((errors+1))
+git --no-pager grep '^from langchain_community\.' . && errors=$((errors+1))
+
+# Decide on an exit status based on the errors
+if [ "$errors" -gt 0 ]; then
+    exit 1
+else
+    exit 0
+fi

libs/cli/langchain_cli/integration_template/tests/integration_tests/test_chat_models.py

@@ -0,0 +1,21 @@
+"""Test Chat__ModuleName__ chat model."""
+
+from typing import Type
+
+from __module_name__.chat_models import Chat__ModuleName__
+from langchain_tests.integration_tests import ChatModelIntegrationTests
+
+
+class TestChatParrotLinkIntegration(ChatModelIntegrationTests):
+    @property
+    def chat_model_class(self) -> Type[Chat__ModuleName__]:
+        return Chat__ModuleName__
+
+    @property
+    def chat_model_params(self) -> dict:
+        # These should be parameters used to initialize your integration for testing
+        return {
+            "model": "bird-brain-001",
+            "temperature": 0,
+            "parrot_buffer_length": 50,
+        }

libs/cli/langchain_cli/integration_template/tests/integration_tests/test_compile.py

@@ -1,8 +1,7 @@
-"""Test compilation of integration tests."""
-
 import pytest
 
 
 @pytest.mark.compile
 def test_placeholder() -> None:
     """Used for compiling integration tests without running any real tests."""
+    pass

libs/cli/langchain_cli/integration_template/tests/integration_tests/test_embeddings.py

@@ -0,0 +1,16 @@
+"""Test __ModuleName__ embeddings."""
+
+from typing import Type
+
+from __module_name__.embeddings import __ModuleName__Embeddings
+from langchain_tests.integration_tests import EmbeddingsIntegrationTests
+
+
+class TestParrotLinkEmbeddingsIntegration(EmbeddingsIntegrationTests):
+    @property
+    def embeddings_class(self) -> Type[__ModuleName__Embeddings]:
+        return __ModuleName__Embeddings
+
+    @property
+    def embedding_model_params(self) -> dict:
+        return {"model": "nest-embed-001"}

libs/cli/langchain_cli/integration_template/tests/integration_tests/test_retrievers.py

@@ -0,0 +1,22 @@
+from typing import Type
+
+from __module_name__.retrievers import __ModuleName__Retriever
+from langchain_tests.integration_tests import (
+    RetrieversIntegrationTests,
+)
+
+
+class Test__ModuleName__Retriever(RetrieversIntegrationTests):
+    @property
+    def retriever_constructor(self) -> Type[__ModuleName__Retriever]:
+        """Get an empty vectorstore for unit tests."""
+        return __ModuleName__Retriever
+
+    @property
+    def retriever_constructor_params(self) -> dict:
+        return {"k": 2}
+
+    @property
+    def retriever_query_example(self) -> str:
+        """Returns a str representing the "query" of an example retriever call."""
+        return "example query"

libs/cli/langchain_cli/integration_template/tests/integration_tests/test_tools.py

@@ -0,0 +1,27 @@
+from typing import Type
+
+from __module_name__.tools import __ModuleName__Tool
+from langchain_tests.integration_tests import ToolsIntegrationTests
+
+
+class TestParrotMultiplyToolIntegration(ToolsIntegrationTests):
+    @property
+    def tool_constructor(self) -> Type[__ModuleName__Tool]:
+        return __ModuleName__Tool
+
+    @property
+    def tool_constructor_params(self) -> dict:
+        # if your tool constructor instead required initialization arguments like
+        # `def __init__(self, some_arg: int):`, you would return those here
+        # as a dictionary, e.g.: `return {'some_arg': 42}`
+        return {}
+
+    @property
+    def tool_invoke_params_example(self) -> dict:
+        """
+        Returns a dictionary representing the "args" of an example tool call.
+
+        This should NOT be a ToolCall dict - i.e. it should not have
+        `{"name", "id", "args"}` keys.
+        """
+        return {"a": 2, "b": 3}

libs/cli/langchain_cli/integration_template/tests/integration_tests/test_vectorstores.py

@@ -0,0 +1,20 @@
+from typing import Generator
+
+import pytest
+from __module_name__.vectorstores import __ModuleName__VectorStore
+from langchain_core.vectorstores import VectorStore
+from langchain_tests.integration_tests import VectorStoreIntegrationTests
+
+
+class Test__ModuleName__VectorStore(VectorStoreIntegrationTests):
+    @pytest.fixture()
+    def vectorstore(self) -> Generator[VectorStore, None, None]:  # type: ignore
+        """Get an empty vectorstore for unit tests."""
+        store = __ModuleName__VectorStore(self.get_embeddings())
+        # note: store should be EMPTY at this point
+        # if you need to delete data, you may do so here
+        try:
+            yield store
+        finally:
+            # cleanup operations, or deleting data
+            pass

libs/cli/langchain_cli/integration_template/tests/unit_tests/test_chat_models.py

@@ -0,0 +1,21 @@
+"""Test chat model integration."""
+
+from typing import Type
+
+from __module_name__.chat_models import Chat__ModuleName__
+from langchain_tests.unit_tests import ChatModelUnitTests
+
+
+class TestChat__ModuleName__Unit(ChatModelUnitTests):
+    @property
+    def chat_model_class(self) -> Type[Chat__ModuleName__]:
+        return Chat__ModuleName__
+
+    @property
+    def chat_model_params(self) -> dict:
+        # These should be parameters used to initialize your integration for testing
+        return {
+            "model": "bird-brain-001",
+            "temperature": 0,
+            "parrot_buffer_length": 50,
+        }

libs/cli/langchain_cli/integration_template/tests/unit_tests/test_embeddings.py

@@ -0,0 +1,16 @@
+"""Test embedding model integration."""
+
+from typing import Type
+
+from __module_name__.embeddings import __ModuleName__Embeddings
+from langchain_tests.unit_tests import EmbeddingsUnitTests
+
+
+class TestParrotLinkEmbeddingsUnit(EmbeddingsUnitTests):
+    @property
+    def embeddings_class(self) -> Type[__ModuleName__Embeddings]:
+        return __ModuleName__Embeddings
+
+    @property
+    def embedding_model_params(self) -> dict:
+        return {"model": "nest-embed-001"}

libs/cli/langchain_cli/integration_template/tests/unit_tests/test_tools.py

@@ -0,0 +1,27 @@
+from typing import Type
+
+from __module_name__.tools import __ModuleName__Tool
+from langchain_tests.unit_tests import ToolsUnitTests
+
+
+class TestParrotMultiplyToolUnit(ToolsUnitTests):
+    @property
+    def tool_constructor(self) -> Type[__ModuleName__Tool]:
+        return __ModuleName__Tool
+
+    @property
+    def tool_constructor_params(self) -> dict:
+        # If your tool constructor instead required initialization arguments like
+        # `def __init__(self, some_arg: int):`, you would return those here
+        # as a dictionary, e.g.: `return {'some_arg': 42}`
+        return {}
+
+    @property
+    def tool_invoke_params_example(self) -> dict:
+        """
+        Returns a dictionary representing the "args" of an example tool call.
+
+        This should NOT be a ToolCall dict - i.e. it should not have
+        `{"name", "id", "args"}` keys.
+        """
+        return {"a": 2, "b": 3}

libs/cli/langchain_cli/namespaces/__init__.py

@@ -0,0 +1 @@
+"""Namespaces."""

libs/cli/langchain_cli/namespaces/app.py

@@ -0,0 +1,371 @@
+"""Manage LangChain apps."""
+
+import shutil
+import subprocess
+import sys
+import warnings
+from pathlib import Path
+from typing import Annotated
+
+import typer
+import uvicorn
+
+from langchain_cli.utils.events import create_events
+from langchain_cli.utils.git import (
+    DependencySource,
+    copy_repo,
+    parse_dependencies,
+    update_repo,
+)
+from langchain_cli.utils.packages import (
+    LangServeExport,
+    get_langserve_export,
+    get_package_root,
+)
+from langchain_cli.utils.pyproject import (
+    add_dependencies_to_pyproject_toml,
+    remove_dependencies_from_pyproject_toml,
+)
+
+REPO_DIR = Path(typer.get_app_dir("langchain")) / "git_repos"
+
+app_cli = typer.Typer(no_args_is_help=True, add_completion=False)
+
+
+@app_cli.command()
+def new(
+    name: Annotated[
+        str | None,
+        typer.Argument(
+            help="The name of the folder to create",
+        ),
+    ] = None,
+    *,
+    package: Annotated[
+        list[str] | None,
+        typer.Option(help="Packages to seed the project with"),
+    ] = None,
+    pip: Annotated[
+        bool | None,
+        typer.Option(
+            "--pip/--no-pip",
+            help="Pip install the template(s) as editable dependencies",
+        ),
+    ] = None,
+    noninteractive: Annotated[
+        bool,
+        typer.Option(
+            "--non-interactive/--interactive",
+            help="Don't prompt for any input",
+        ),
+    ] = False,
+) -> None:
+    """Create a new LangServe application."""
+    has_packages = package is not None and len(package) > 0
+
+    if noninteractive:
+        if name is None:
+            msg = "name is required when --non-interactive is set"
+            raise typer.BadParameter(msg)
+        name_str = name
+        pip_bool = bool(pip)  # None should be false
+    else:
+        name_str = name or typer.prompt("What folder would you like to create?")
+        if not has_packages:
+            package = []
+            package_prompt = "What package would you like to add? (leave blank to skip)"
+            while True:
+                package_str = typer.prompt(
+                    package_prompt,
+                    default="",
+                    show_default=False,
+                )
+                if not package_str:
+                    break
+                package.append(package_str)
+                package_prompt = (
+                    f"{len(package)} added. Any more packages (leave blank to end)?"
+                )
+
+            has_packages = len(package) > 0
+
+        pip_bool = False
+        if pip is None and has_packages:
+            pip_bool = typer.confirm(
+                "Would you like to install these templates into your environment "
+                "with pip?",
+                default=False,
+            )
+    # copy over template from ../project_template
+    project_template_dir = Path(__file__).parents[1] / "project_template"
+    destination_dir = Path.cwd() / name_str if name_str != "." else Path.cwd()
+    app_name = name_str if name_str != "." else Path.cwd().name
+    shutil.copytree(project_template_dir, destination_dir, dirs_exist_ok=name == ".")
+
+    readme = destination_dir / "README.md"
+    readme_contents = readme.read_text()
+    readme.write_text(readme_contents.replace("__app_name__", app_name))
+
+    pyproject = destination_dir / "pyproject.toml"
+    pyproject_contents = pyproject.read_text()
+    pyproject.write_text(pyproject_contents.replace("__app_name__", app_name))
+
+    # add packages if specified
+    if has_packages:
+        add(package, project_dir=destination_dir, pip=pip_bool)
+
+    typer.echo(f'\n\nSuccess! Created a new LangChain app under "./{app_name}"!\n\n')
+    typer.echo("Next, enter your new app directory by running:\n")
+    typer.echo(f"    cd ./{app_name}\n")
+    typer.echo("Then add templates with commands like:\n")
+    typer.echo("    langchain app add extraction-openai-functions")
+    typer.echo(
+        "    langchain app add git+ssh://git@github.com/efriis/simple-pirate.git\n\n",
+    )
+
+
+@app_cli.command()
+def add(
+    dependencies: Annotated[
+        list[str] | None,
+        typer.Argument(help="The dependency to add"),
+    ] = None,
+    *,
+    api_path: Annotated[
+        list[str] | None,
+        typer.Option(help="API paths to add"),
+    ] = None,
+    project_dir: Annotated[
+        Path | None,
+        typer.Option(help="The project directory"),
+    ] = None,
+    repo: Annotated[
+        list[str] | None,
+        typer.Option(help="Install templates from a specific github repo instead"),
+    ] = None,
+    branch: Annotated[
+        list[str] | None,
+        typer.Option(help="Install templates from a specific branch"),
+    ] = None,
+    pip: Annotated[
+        bool,
+        typer.Option(
+            "--pip/--no-pip",
+            help="Pip install the template(s) as editable dependencies",
+            prompt="Would you like to `pip install -e` the template(s)?",
+        ),
+    ],
+) -> None:
+    """Add the specified template to the current LangServe app.
+
+    e.g.:
+    `langchain app add extraction-openai-functions`
+    `langchain app add git+ssh://git@github.com/efriis/simple-pirate.git`
+    """
+    if branch is None:
+        branch = []
+    if repo is None:
+        repo = []
+    if api_path is None:
+        api_path = []
+    if not branch and not repo:
+        warnings.warn(
+            "Adding templates from the default branch and repo is deprecated."
+            " At a minimum, you will have to add `--branch v0.2` for this to work",
+            stacklevel=2,
+        )
+
+    parsed_deps = parse_dependencies(dependencies, repo, branch, api_path)
+
+    project_root = get_package_root(project_dir)
+
+    package_dir = project_root / "packages"
+
+    create_events(
+        [{"event": "serve add", "properties": {"parsed_dep": d}} for d in parsed_deps],
+    )
+
+    # group by repo/ref
+    grouped: dict[tuple[str, str | None], list[DependencySource]] = {}
+    for dep in parsed_deps:
+        key_tup = (dep["git"], dep["ref"])
+        lst = grouped.get(key_tup, [])
+        lst.append(dep)
+        grouped[key_tup] = lst
+
+    installed_destination_paths: list[Path] = []
+    installed_destination_names: list[str] = []
+    installed_exports: list[LangServeExport] = []
+
+    for (git, ref), group_deps in grouped.items():
+        if len(group_deps) == 1:
+            typer.echo(f"Adding {git}@{ref}...")
+        else:
+            typer.echo(f"Adding {len(group_deps)} templates from {git}@{ref}")
+        source_repo_path = update_repo(git, ref, REPO_DIR)
+
+        for dep in group_deps:
+            source_path = (
+                source_repo_path / dep["subdirectory"]
+                if dep["subdirectory"]
+                else source_repo_path
+            )
+            pyproject_path = source_path / "pyproject.toml"
+            if not pyproject_path.exists():
+                typer.echo(f"Could not find {pyproject_path}")
+                continue
+            langserve_export = get_langserve_export(pyproject_path)
+
+            # default path to package_name
+            inner_api_path = dep["api_path"] or langserve_export["package_name"]
+
+            destination_path = package_dir / inner_api_path
+            if destination_path.exists():
+                typer.echo(
+                    f"Folder {inner_api_path} already exists. Skipping...",
+                )
+                continue
+            copy_repo(source_path, destination_path)
+            typer.echo(f" - Downloaded {dep['subdirectory']} to {inner_api_path}")
+            installed_destination_paths.append(destination_path)
+            installed_destination_names.append(inner_api_path)
+            installed_exports.append(langserve_export)
+
+    if len(installed_destination_paths) == 0:
+        typer.echo("No packages installed. Exiting.")
+        return
+
+    try:
+        add_dependencies_to_pyproject_toml(
+            project_root / "pyproject.toml",
+            zip(installed_destination_names, installed_destination_paths, strict=False),
+        )
+    except Exception:
+        # Can fail if user modified/removed pyproject.toml
+        typer.echo("Failed to add dependencies to pyproject.toml, continuing...")
+
+    try:
+        cwd = Path.cwd()
+        installed_destination_strs = [
+            str(p.relative_to(cwd)) for p in installed_destination_paths
+        ]
+    except ValueError:
+        # Can fail if the cwd is not a parent of the package
+        typer.echo("Failed to print install command, continuing...")
+    else:
+        if pip:
+            cmd = ["pip", "install", "-e", *installed_destination_strs]
+            cmd_str = " \\\n  ".join(installed_destination_strs)
+            typer.echo(f"Running: pip install -e \\\n  {cmd_str}")
+            subprocess.run(cmd, cwd=cwd, check=True)  # noqa: S603
+
+    chain_names = []
+    for e in installed_exports:
+        original_candidate = f"{e['package_name'].replace('-', '_')}_chain"
+        candidate = original_candidate
+        i = 2
+        while candidate in chain_names:
+            candidate = original_candidate + "_" + str(i)
+            i += 1
+        chain_names.append(candidate)
+
+    api_paths = [
+        str(Path("/") / path.relative_to(package_dir))
+        for path in installed_destination_paths
+    ]
+
+    imports = [
+        f"from {e['module']} import {e['attr']} as {name}"
+        for e, name in zip(installed_exports, chain_names, strict=False)
+    ]
+    routes = [
+        f'add_routes(app, {name}, path="{path}")'
+        for name, path in zip(chain_names, api_paths, strict=False)
+    ]
+
+    t = (
+        "this template"
+        if len(chain_names) == 1
+        else f"these {len(chain_names)} templates"
+    )
+    lines = [
+        "",
+        f"To use {t}, add the following to your app:\n\n```",
+        "",
+        *imports,
+        "",
+        *routes,
+        "```",
+    ]
+    typer.echo("\n".join(lines))
+
+
+@app_cli.command()
+def remove(
+    api_paths: Annotated[list[str], typer.Argument(help="The API paths to remove")],
+    *,
+    project_dir: Annotated[
+        Path | None,
+        typer.Option(help="The project directory"),
+    ] = None,
+) -> None:
+    """Remove the specified package from the current LangServe app."""
+    project_root = get_package_root(project_dir)
+
+    project_pyproject = project_root / "pyproject.toml"
+
+    package_root = project_root / "packages"
+
+    remove_deps: list[str] = []
+
+    for api_path in api_paths:
+        package_dir = package_root / api_path
+        if not package_dir.exists():
+            typer.echo(f"Package {api_path} does not exist. Skipping...")
+            continue
+        try:
+            pyproject = package_dir / "pyproject.toml"
+            langserve_export = get_langserve_export(pyproject)
+            typer.echo(f"Removing {langserve_export['package_name']}...")
+
+            shutil.rmtree(package_dir)
+            remove_deps.append(api_path)
+        except OSError as exc:
+            typer.echo(f"Failed to remove {api_path}: {exc}")
+
+    try:
+        remove_dependencies_from_pyproject_toml(project_pyproject, remove_deps)
+    except Exception:
+        # Can fail if user modified/removed pyproject.toml
+        typer.echo("Failed to remove dependencies from pyproject.toml.")
+
+
+@app_cli.command()
+def serve(
+    *,
+    port: Annotated[
+        int | None,
+        typer.Option(help="The port to run the server on"),
+    ] = None,
+    host: Annotated[
+        str | None,
+        typer.Option(help="The host to run the server on"),
+    ] = None,
+    app: Annotated[
+        str | None,
+        typer.Option(help="The app to run, e.g. `app.server:app`"),
+    ] = None,
+) -> None:
+    """Start the LangServe app."""
+    # add current dir as first entry of path
+    sys.path.append(str(Path.cwd()))
+
+    app_str = app if app is not None else "app.server:app"
+    host_str = host if host is not None else "127.0.0.1"
+
+    uvicorn.run(
+        app_str,
+        host=host_str,
+        port=port if port is not None else 8000,
+        reload=True,
+    )

libs/cli/langchain_cli/namespaces/integration.py

@@ -0,0 +1,260 @@
+"""Develop integration packages for LangChain."""
+
+import os
+import re
+import shutil
+import subprocess
+from pathlib import Path
+from typing import Annotated, cast
+
+import typer
+from typing_extensions import TypedDict
+
+from langchain_cli.utils.find_replace import replace_file, replace_glob
+
+integration_cli = typer.Typer(no_args_is_help=True, add_completion=False)
+
+
+class Replacements(TypedDict):
+    """Replacements."""
+
+    __package_name__: str
+    __module_name__: str
+    __ModuleName__: str
+    __MODULE_NAME__: str
+    __package_name_short__: str
+    __package_name_short_snake__: str
+
+
+def _process_name(name: str, *, community: bool = False) -> Replacements:
+    preprocessed = name.replace("_", "-").lower()
+
+    preprocessed = preprocessed.removeprefix("langchain-")
+
+    if not re.match(r"^[a-z][a-z0-9-]*$", preprocessed):
+        msg = (
+            "Name should only contain lowercase letters (a-z), numbers, and hyphens"
+            ", and start with a letter."
+        )
+        raise ValueError(msg)
+    if preprocessed.endswith("-"):
+        msg = "Name should not end with `-`."
+        raise ValueError(msg)
+    if preprocessed.find("--") != -1:
+        msg = "Name should not contain consecutive hyphens."
+        raise ValueError(msg)
+    replacements: Replacements = {
+        "__package_name__": f"langchain-{preprocessed}",
+        "__module_name__": "langchain_" + preprocessed.replace("-", "_"),
+        "__ModuleName__": preprocessed.title().replace("-", ""),
+        "__MODULE_NAME__": preprocessed.upper().replace("-", ""),
+        "__package_name_short__": preprocessed,
+        "__package_name_short_snake__": preprocessed.replace("-", "_"),
+    }
+    if community:
+        replacements["__module_name__"] = preprocessed.replace("-", "_")
+    return replacements
+
+
+@integration_cli.command()
+def new(
+    name: Annotated[
+        str,
+        typer.Option(
+            help="The name of the integration to create (e.g. `my-integration`)",
+            prompt="The name of the integration to create (e.g. `my-integration`)",
+        ),
+    ],
+    name_class: Annotated[
+        str | None,
+        typer.Option(
+            help="The name of the integration in PascalCase. e.g. `MyIntegration`."
+            " This is used to name classes like `MyIntegrationVectorStore`",
+        ),
+    ] = None,
+    src: Annotated[
+        list[str] | None,
+        typer.Option(
+            help="The name of the single template file to copy."
+            " e.g. `--src integration_template/chat_models.py "
+            "--dst my_integration/chat_models.py`. Can be used multiple times.",
+        ),
+    ] = None,
+    dst: Annotated[
+        list[str] | None,
+        typer.Option(
+            help="The relative path to the integration package to place the new file in"
+            ". e.g. `my-integration/my_integration.py`",
+        ),
+    ] = None,
+) -> None:
+    """Create a new integration package."""
+    try:
+        replacements = _process_name(name)
+    except ValueError as e:
+        typer.echo(e)
+        raise typer.Exit(code=1) from None
+
+    if name_class:
+        if not re.match(r"^[A-Z][a-zA-Z0-9]*$", name_class):
+            typer.echo(
+                "Name should only contain letters (a-z, A-Z), numbers, and underscores"
+                ", and start with a capital letter.",
+            )
+            raise typer.Exit(code=1)
+        replacements["__ModuleName__"] = name_class
+    else:
+        replacements["__ModuleName__"] = typer.prompt(
+            "Name of integration in PascalCase",
+            default=replacements["__ModuleName__"],
+        )
+
+    project_template_dir = Path(__file__).parents[1] / "integration_template"
+    destination_dir = Path.cwd() / replacements["__package_name__"]
+    if not src and not dst:
+        if destination_dir.exists():
+            typer.echo(f"Folder {destination_dir} exists.")
+            raise typer.Exit(code=1)
+
+        # Copy over template from ../integration_template
+        shutil.copytree(project_template_dir, destination_dir, dirs_exist_ok=False)
+
+        # Folder movement
+        package_dir = destination_dir / replacements["__module_name__"]
+        shutil.move(destination_dir / "integration_template", package_dir)
+
+        # Replacements in files
+        replace_glob(destination_dir, "**/*", cast("dict[str, str]", replacements))
+
+        # Dependency install
+        try:
+            # Use --no-progress to avoid tty issues in CI/test environments
+            env = os.environ.copy()
+            env.pop("UV_FROZEN", None)
+            env.pop("VIRTUAL_ENV", None)
+            subprocess.run(
+                ["uv", "sync", "--dev", "--no-progress"],  # noqa: S607
+                cwd=destination_dir,
+                check=True,
+                env=env,
+            )
+        except FileNotFoundError:
+            typer.echo(
+                "uv is not installed. Skipping dependency installation; run "
+                "`uv sync --dev` manually if needed.",
+            )
+        except subprocess.CalledProcessError:
+            typer.echo(
+                "Failed to install dependencies. You may need to run "
+                "`uv sync --dev` manually in the package directory.",
+            )
+    else:
+        # Confirm src and dst are the same length
+        if not src:
+            typer.echo("Cannot provide --dst without --src.")
+            raise typer.Exit(code=1)
+        src_paths = [project_template_dir / p for p in src]
+        if dst and len(src) != len(dst):
+            typer.echo("Number of --src and --dst arguments must match.")
+            raise typer.Exit(code=1)
+        if not dst:
+            # Assume we're in a package dir, copy to equivalent path
+            dst_paths = [destination_dir / p for p in src]
+        else:
+            dst_paths = [Path.cwd() / p for p in dst]
+            dst_paths = [
+                p / f"{replacements['__package_name_short_snake__']}.ipynb"
+                if not p.suffix
+                else p
+                for p in dst_paths
+            ]
+
+        # Confirm no duplicate dst_paths
+        if len(dst_paths) != len(set(dst_paths)):
+            typer.echo(
+                "Duplicate destination paths provided or computed - please "
+                "specify them explicitly with --dst.",
+            )
+            raise typer.Exit(code=1)
+
+        # Confirm no files exist at dst_paths
+        for dst_path in dst_paths:
+            if dst_path.exists():
+                typer.echo(f"File {dst_path} exists.")
+                raise typer.Exit(code=1)
+
+        for src_path, dst_path in zip(src_paths, dst_paths, strict=False):
+            shutil.copy(src_path, dst_path)
+            replace_file(dst_path, cast("dict[str, str]", replacements))
+
+
+TEMPLATE_MAP: dict[str, str] = {
+    "ChatModel": "chat.ipynb",
+    "DocumentLoader": "document_loaders.ipynb",
+    "Tool": "tools.ipynb",
+    "VectorStore": "vectorstores.ipynb",
+    "Embeddings": "text_embedding.ipynb",
+    "ByteStore": "kv_store.ipynb",
+    "LLM": "llms.ipynb",
+    "Provider": "provider.ipynb",
+    "Toolkit": "toolkits.ipynb",
+    "Retriever": "retrievers.ipynb",
+}
+
+_component_types_str = ", ".join(f"`{k}`" for k in TEMPLATE_MAP)
+
+
+@integration_cli.command()
+def create_doc(
+    name: Annotated[
+        str,
+        typer.Option(
+            help=(
+                "The kebab-case name of the integration (e.g. `openai`, "
+                "`google-vertexai`). Do not include a 'langchain-' prefix."
+            ),
+            prompt=(
+                "The kebab-case name of the integration (e.g. `openai`, "
+                "`google-vertexai`). Do not include a 'langchain-' prefix."
+            ),
+        ),
+    ],
+    name_class: Annotated[
+        str | None,
+        typer.Option(
+            help=(
+                "The PascalCase name of the integration (e.g. `OpenAI`, "
+                "`VertexAI`). Do not include a 'Chat', 'VectorStore', etc. "
+                "prefix/suffix."
+            ),
+        ),
+    ] = None,
+    component_type: Annotated[
+        str,
+        typer.Option(
+            help=(
+                f"The type of component. Currently supported: {_component_types_str}."
+            ),
+        ),
+    ] = "ChatModel",
+    destination_dir: Annotated[
+        str,
+        typer.Option(
+            help="The relative path to the docs directory to place the new file in.",
+            prompt="The relative path to the docs directory to place the new file in.",
+        ),
+    ] = "docs/docs/integrations/chat/",
+) -> None:
+    """Create a new integration doc."""
+    if component_type not in TEMPLATE_MAP:
+        typer.echo(
+            f"Unrecognized {component_type=}. Expected one of {_component_types_str}.",
+        )
+        raise typer.Exit(code=1)
+
+    new(
+        name=name,
+        name_class=name_class,
+        src=[f"docs/{TEMPLATE_MAP[component_type]}"],
+        dst=[destination_dir],
+    )

libs/cli/langchain_cli/namespaces/migrate/.grit/.gitignore

@@ -0,0 +1,2 @@
+.gritmodules*
+*.log

libs/cli/langchain_cli/namespaces/migrate/.grit/grit.yaml

@@ -0,0 +1,3 @@
+version: 0.0.1
+patterns:
+  - name: github.com/getgrit/stdlib#*

libs/cli/langchain_cli/namespaces/migrate/.grit/patterns/_test_replace_imports.md

@@ -0,0 +1,56 @@
+# Testing the replace_imports migration
+
+This runs the v0.2 migration with a desired set of rules.
+
+```grit
+language python
+
+langchain_all_migrations()
+```
+
+## Single import
+
+Before:
+
+```python
+from langchain.chat_models import ChatOpenAI
+```
+
+After:
+
+```python
+from langchain_community.chat_models import ChatOpenAI
+```
+
+## Community to partner
+
+```python
+from langchain_community.chat_models import ChatOpenAI
+```
+
+```python
+from langchain_openai import ChatOpenAI
+```
+
+## Noop
+
+This file should not match at all.
+
+```python
+from foo import ChatOpenAI
+```
+
+## Mixed imports
+
+```python
+from langchain_community.chat_models import ChatOpenAI, ChatAnthropic, foo
+```
+
+```python
+from langchain_community.chat_models import foo
+
+from langchain_openai import ChatOpenAI
+
+from langchain_anthropic import ChatAnthropic
+
+```

libs/cli/langchain_cli/namespaces/migrate/.grit/patterns/anthropic.grit

@@ -0,0 +1,15 @@
+
+language python
+
+// This migration is generated automatically - do not manually edit this file
+pattern langchain_migrate_anthropic() {
+  find_replace_imports(list=[
+    [`langchain_community.chat_models.anthropic`, `ChatAnthropic`, `langchain_anthropic`, `ChatAnthropic`],
+    [`langchain_community.llms.anthropic`, `Anthropic`, `langchain_anthropic`, `Anthropic`],
+    [`langchain_community.chat_models`, `ChatAnthropic`, `langchain_anthropic`, `ChatAnthropic`],
+    [`langchain_community.llms`, `Anthropic`, `langchain_anthropic`, `Anthropic`]
+  ])
+}
+
+// Add this for invoking directly
+langchain_migrate_anthropic()

libs/cli/langchain_cli/namespaces/migrate/.grit/patterns/astradb.grit

@@ -0,0 +1,67 @@
+
+language python
+
+// This migration is generated automatically - do not manually edit this file
+pattern langchain_migrate_astradb() {
+  find_replace_imports(list=[
+
+            [
+                `langchain_community.vectorstores.astradb`,
+                `AstraDB`,
+                `langchain_astradb`,
+                `AstraDBVectorStore`
+            ]
+            ,
+
+            [
+                `langchain_community.storage.astradb`,
+                `AstraDBByteStore`,
+                `langchain_astradb`,
+                `AstraDBByteStore`
+            ]
+            ,
+
+            [
+                `langchain_community.storage.astradb`,
+                `AstraDBStore`,
+                `langchain_astradb`,
+                `AstraDBStore`
+            ]
+            ,
+
+            [
+                `langchain_community.cache`,
+                `AstraDBCache`,
+                `langchain_astradb`,
+                `AstraDBCache`
+            ]
+            ,
+
+            [
+                `langchain_community.cache`,
+                `AstraDBSemanticCache`,
+                `langchain_astradb`,
+                `AstraDBSemanticCache`
+            ]
+            ,
+
+            [
+                `langchain_community.chat_message_histories.astradb`,
+                `AstraDBChatMessageHistory`,
+                `langchain_astradb`,
+                `AstraDBChatMessageHistory`
+            ]
+            ,
+
+            [
+                `langchain_community.document_loaders.astradb`,
+                `AstraDBLoader`,
+                `langchain_astradb`,
+                `AstraDBLoader`
+            ]
+            
+  ])
+}
+
+// Add this for invoking directly
+langchain_migrate_astradb()