release(groq): 1.1.2 (#34977)

following #34944

.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": "uv sync && echo 'LangChain (Python) dev environment ready!'",
+  "postCreateCommand": "cd libs/langchain_v1 && uv sync && echo 'LangChain (Python) dev environment ready!'",
   // Configure tool-specific properties.
   "customizations": {
     "vscode": {
@@ -42,7 +42,7 @@
         "GitHub.copilot-chat"
       ],
       "settings": {
-        "python.defaultInterpreterPath": ".venv/bin/python",
+        "python.defaultInterpreterPath": "libs/langchain_v1/.venv/bin/python",
         "python.formatting.provider": "none",
         "[python]": {
           "editor.formatOnSave": true,

.dockerignore

@@ -0,0 +1,34 @@
+# 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/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.
+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).
 labels: ["bug"]
 type: bug
 body:
@@ -53,7 +53,6 @@ body:
         - label: langchain-anthropic
         - label: langchain-classic
         - label: langchain-core
-        - label: langchain-cli
         - label: langchain-model-profiles
         - label: langchain-tests
         - label: langchain-text-splitters
@@ -71,12 +70,22 @@ body:
         - 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: Example Code (Python)
+      label: Reproduction Steps / Example Code (Python)
       description: |
         Please add a self-contained, [minimal, reproducible, example](https://stackoverflow.com/help/minimal-reproducible-example) with your use case.
 

.github/ISSUE_TEMPLATE/config.yml

@@ -1,9 +1,6 @@
 blank_issues_enabled: false
 version: 2.1
 contact_links:
-  - 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
   - name: 💬 LangChain Forum
     url:  https://forum.langchain.com/
     about: General community discussions and support
@@ -13,3 +10,6 @@ contact_links:
   - 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.
+description: Request a new feature or enhancement for LangChain. For questions, please use the LangChain forum (below).
 labels: ["feature request"]
 type: feature
 body:
@@ -50,7 +50,6 @@ body:
         - label: langchain-anthropic
         - label: langchain-classic
         - label: langchain-core
-        - label: langchain-cli
         - label: langchain-model-profiles
         - label: langchain-tests
         - label: langchain-text-splitters

.github/ISSUE_TEMPLATE/privileged.yml

@@ -30,7 +30,6 @@ body:
         - label: langchain-anthropic
         - label: langchain-classic
         - label: langchain-core
-        - label: langchain-cli
         - label: langchain-model-profiles
         - label: langchain-tests
         - label: langchain-text-splitters

.github/ISSUE_TEMPLATE/task.yml

@@ -101,7 +101,6 @@ body:
         - label: langchain-anthropic
         - label: langchain-classic
         - label: langchain-core
-        - label: langchain-cli
         - label: langchain-model-profiles
         - label: langchain-tests
         - label: langchain-text-splitters

.github/PULL_REQUEST_TEMPLATE.md

@@ -17,7 +17,7 @@ Thank you for contributing to LangChain! Follow these steps to have your pull re
   - 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" inthe description.
+  - 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.
 
@@ -27,4 +27,4 @@ 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 unless or add dependencies to `pyproject.toml` files (even optional ones) unless you have explicit permission to do so by a maintainer.
+  - 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.

.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@v6
+      uses: astral-sh/setup-uv@v7
       with:
         version: ${{ env.UV_VERSION }}
         python-version: ${{ inputs.python-version }}

.github/pr-file-labeler.yml

@@ -17,11 +17,6 @@ langchain:
       - 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:
@@ -118,17 +113,6 @@ xai:
       - any-glob-to-any-file:
           - "libs/partners/xai/**/*"
 
-# Infrastructure and DevOps
-infra:
-  - changed-files:
-      - any-glob-to-any-file:
-          - ".github/**/*"
-          - "Makefile"
-          - ".pre-commit-config.yaml"
-          - "scripts/**/*"
-          - "docker/**/*"
-          - "Dockerfile*"
-
 github_actions:
   - changed-files:
       - any-glob-to-any-file:
@@ -142,11 +126,3 @@ dependencies:
           - "uv.lock"
           - "**/requirements*.txt"
           - "**/poetry.lock"
-
-# Documentation
-documentation:
-  - changed-files:
-      - any-glob-to-any-file:
-          - "**/*.md"
-          - "**/README*"
-

.github/scripts/check_diff.py

@@ -56,7 +56,7 @@ def all_package_dirs() -> Set[str]:
     return {
         "/".join(path.split("/")[:-1]).lstrip("./")
         for path in glob.glob("./libs/**/pyproject.toml", recursive=True)
-        if "libs/cli" not in path and "libs/standard-tests" not in path
+        if "libs/standard-tests" not in path
     }
 
 
@@ -286,10 +286,6 @@ 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 [

.github/workflows/_release.yml

@@ -396,7 +396,7 @@ jobs:
       contents: read
     strategy:
       matrix:
-        partner: [openai, anthropic]
+        partner: [anthropic]
       fail-fast: false # Continue testing other partners if one fails
     env:
       ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
@@ -470,6 +470,67 @@ 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:
@@ -477,7 +538,10 @@ 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:

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

@@ -17,8 +17,8 @@ jobs:
           script: |
             const body = context.payload.issue.body || "";
 
-            // Extract text under "### Package"
-            const match = body.match(/### Package\s+([\s\S]*?)\n###/i);
+            // 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();
@@ -30,7 +30,6 @@ jobs:
               "langchain-anthropic": "anthropic",
               "langchain-classic": "langchain-classic",
               "langchain-core": "core",
-              "langchain-cli": "cli",
               "langchain-model-profiles": "model-profiles",
               "langchain-tests": "standard-tests",
               "langchain-text-splitters": "text-splitters",

.github/workflows/check_agents_sync.yml

@@ -0,0 +1,42 @@
+# 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/integration_tests.yml

@@ -1,8 +1,8 @@
 # Routine integration tests against partner libraries with live API credentials.
 #
-# Uses `make integration_tests` for each library in the matrix.
+# Uses `make integration_tests` within each library being tested.
 #
-# Runs daily. Can also be triggered manually for immediate updates.
+# Runs daily with the option to trigger manually.
 
 name: "⏰ Integration Tests"
 run-name: "Run Integration Tests - ${{ inputs.working-directory-force || 'all libs' }} (Python ${{ inputs.python-version-force || '3.10, 3.13' }})"
@@ -24,17 +24,29 @@ 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: ${{ steps.set-matrix.outputs.python-version-min-3-11 }}
     steps:
       - name: "🔢 Generate Python & Library Matrix"
         id: set-matrix
@@ -47,9 +59,16 @@ jobs:
           # python-version should default to 3.10 and 3.13, but is overridden to [PYTHON_VERSION_FORCE] if set
           # working-directory should default to DEFAULT_LIBS, but is overridden to [WORKING_DIRECTORY_FORCE] if set
           python_version='["3.10", "3.13"]'
+          python_version_min_3_11='["3.11", "3.13"]'
           working_directory="$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\"]"
@@ -57,8 +76,10 @@ 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
-  build:
+  integration-tests:
     if: github.repository_owner == 'langchain-ai' || github.event_name != 'schedule'
     name: "🐍 Python ${{ matrix.python-version }}: ${{ matrix.working-directory }}"
     runs-on: ubuntu-latest
@@ -74,15 +95,27 @@ jobs:
       - uses: actions/checkout@v6
         with:
           path: langchain
+
+      # These libraries exist outside of the monorepo and need to be checked out separately
       - uses: actions/checkout@v6
         with:
           repository: langchain-ai/langchain-google
           path: langchain-google
+      - name: "🔐 Authenticate to Google Cloud"
+        id: "auth"
+        uses: google-github-actions/auth@v3
+        with:
+          credentials_json: "${{ secrets.GOOGLE_CREDENTIALS }}"
       - uses: actions/checkout@v6
         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 \
@@ -97,27 +130,27 @@ jobs:
         with:
           python-version: ${{ matrix.python-version }}
 
-      - name: "🔐 Authenticate to Google Cloud"
-        id: "auth"
-        uses: google-github-actions/auth@v3
-        with:
-          credentials_json: "${{ secrets.GOOGLE_CREDENTIALS }}"
-
-      - 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: ${{ secrets.AWS_REGION }}
-
       - name: "📦 Install Dependencies"
+        # Partner packages use [tool.uv.sources] in their pyproject.toml to resolve
+        # langchain-core/langchain to local editable installs, so `uv sync` automatically
+        # tests against the versions from the current branch (not published releases).
+
+        # TODO: external google/aws don't have local resolution since they live in
+        # separate repos, so they pull `core`/`langchain_v1` from PyPI. We should update
+        # their dev groups to use git source dependencies pointing to the current
+        # branch's latest commit SHA to fully test against local langchain changes.
         run: |
           echo "Running scheduled tests, installing dependencies with uv..."
           cd langchain/${{ 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 }}
@@ -155,7 +188,6 @@ jobs:
           WATSONX_APIKEY: ${{ secrets.WATSONX_APIKEY }}
           WATSONX_PROJECT_ID: ${{ secrets.WATSONX_PROJECT_ID }}
           XAI_API_KEY: ${{ secrets.XAI_API_KEY }}
-          LANGCHAIN_TESTS_USER_AGENT: ${{ secrets.LANGCHAIN_TESTS_USER_AGENT }}
         run: |
           cd langchain/${{ matrix.working-directory }}
           make integration_tests
@@ -179,3 +211,59 @@ 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, edited]
+    types: [opened, synchronize, reopened]
 
 jobs:
   labeler:

.github/workflows/pr_lint.yml

@@ -8,7 +8,7 @@
 #
 # Examples:
 #     feat(core): add multi‐tenant support
-#     fix(cli): resolve flag parsing error
+#     fix(langchain): resolve error
 #     docs: update API usage examples
 #     docs(openai): update API usage examples
 #
@@ -27,12 +27,18 @@
 #   * release    — prepare a new release
 #
 # Allowed Scope(s) (optional):
-#   core, cli, langchain, langchain_v1, langchain-classic, model-profiles,
+#   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.
+# 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.
 #
 # Rules:
 #   1. The 'Type' must start with a lowercase letter.
@@ -79,7 +85,6 @@ jobs:
             release
           scopes: |
             core
-            cli
             langchain
             langchain-classic
             model-profiles

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

@@ -0,0 +1,148 @@
+# 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}`);

.pre-commit-config.yaml

@@ -1,4 +1,24 @@
 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
@@ -97,3 +117,15 @@ 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

AGENTS.md

@@ -22,7 +22,6 @@ langchain/
 │   ├── text-splitters/   # Document chunking utilities
 │   ├── standard-tests/   # Shared test suite for integrations
 │   ├── model-profiles/   # Model configuration profiles
-│   └── cli/              # Command-line interface tools
 ├── .github/              # CI/CD workflows and templates
 ├── .vscode/              # VSCode IDE standard settings and recommended extensions
 └── README.md             # Information about LangChain
@@ -33,7 +32,7 @@ langchain/
 - **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
 
-### Development tools & commands**
+### Development tools & commands
 
 - `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.
@@ -45,6 +44,16 @@ This monorepo uses `uv` for dependency management. Local development uses editab
 
 Each package in `libs/` has its own `pyproject.toml` and `uv.lock`.
 
+Before running your tests, setup all packages by running:
+
+```bash
+# For all groups
+uv sync --all-groups
+
+# or, to install a specific group only:
+uv sync --group test
+```
+
 ```bash
 # Run unit tests (no network)
 make test
@@ -72,7 +81,15 @@ uv run --group lint mypy .
 
 #### Commit standards
 
-Suggest PR titles that follow Conventional Commits format. Refer to .github/workflows/pr_lint for allowed types and scopes.
+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
+```
+
+Note how `feat(langchain)` includes a scope even though it is the main package and name of the repo.
 
 #### Pull request guidelines
 
@@ -85,6 +102,7 @@ Suggest PR titles that follow Conventional Commits format. Refer to .github/work
 ### 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:**
 
@@ -110,7 +128,7 @@ def filter_unknown_users(users: list[str], known_users: set[str]) -> list[str]:
         known_users: Set of known/valid user identifiers.
 
     Returns:
-        List of users that are not in the known_users set.
+        List of users that are not in the `known_users` set.
     """
 ```
 
@@ -178,4 +196,4 @@ def send_email(to: str, msg: str, *, priority: str = "normal") -> bool:
 ## 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:** [`.github/CONTRIBUTING.md`](https://docs.langchain.com/oss/python/contributing/overview)
+- **Contributing Guide:** [Contributing Guide](https://docs.langchain.com/oss/python/contributing/overview)

CLAUDE.md

@@ -22,7 +22,6 @@ langchain/
 │   ├── text-splitters/   # Document chunking utilities
 │   ├── standard-tests/   # Shared test suite for integrations
 │   ├── model-profiles/   # Model configuration profiles
-│   └── cli/              # Command-line interface tools
 ├── .github/              # CI/CD workflows and templates
 ├── .vscode/              # VSCode IDE standard settings and recommended extensions
 └── README.md             # Information about LangChain
@@ -33,7 +32,7 @@ langchain/
 - **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
 
-### Development tools & commands**
+### Development tools & commands
 
 - `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.
@@ -45,6 +44,16 @@ This monorepo uses `uv` for dependency management. Local development uses editab
 
 Each package in `libs/` has its own `pyproject.toml` and `uv.lock`.
 
+Before running your tests, setup all packages by running:
+
+```bash
+# For all groups
+uv sync --all-groups
+
+# or, to install a specific group only:
+uv sync --group test
+```
+
 ```bash
 # Run unit tests (no network)
 make test
@@ -72,7 +81,15 @@ uv run --group lint mypy .
 
 #### Commit standards
 
-Suggest PR titles that follow Conventional Commits format. Refer to .github/workflows/pr_lint for allowed types and scopes.
+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
+```
+
+Note how `feat(langchain)` includes a scope even though it is the main package and name of the repo.
 
 #### Pull request guidelines
 
@@ -85,6 +102,7 @@ Suggest PR titles that follow Conventional Commits format. Refer to .github/work
 ### 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:**
 
@@ -110,7 +128,7 @@ def filter_unknown_users(users: list[str], known_users: set[str]) -> list[str]:
         known_users: Set of known/valid user identifiers.
 
     Returns:
-        List of users that are not in the known_users set.
+        List of users that are not in the `known_users` set.
     """
 ```
 
@@ -178,4 +196,4 @@ def send_email(to: str, msg: str, *, priority: str = "normal") -> bool:
 ## 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:** [`.github/CONTRIBUTING.md`](https://docs.langchain.com/oss/python/contributing/overview)
+- **Contributing Guide:** [Contributing Guide](https://docs.langchain.com/oss/python/contributing/overview)

CONTRIBUTING.md

@@ -0,0 +1,15 @@
+# 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!

README.md

@@ -19,7 +19,7 @@
   <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>
+  <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.
@@ -36,6 +36,7 @@ If you're looking for more advanced customization or agent orchestration, check
 
 - [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.
 
@@ -61,14 +62,15 @@ While the LangChain framework can be used standalone, it also integrates seamles
 
 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).
-- [Deep Agents](https://github.com/langchain-ai/deepagents) *(new!)* – Build agents that can plan, use subagents, and leverage file systems for complex tasks
 
 ## 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/blob/master/.github/CODE_OF_CONDUCT.md) – Our community guidelines and standards for participation.
+- [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.

libs/cli/.gitignore

@@ -1,159 +0,0 @@
-# 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

@@ -1,189 +0,0 @@
-# `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

@@ -1,21 +0,0 @@
-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

@@ -1,53 +0,0 @@
-
-######################
-# 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

@@ -1,30 +0,0 @@
-# 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

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

libs/cli/langchain_cli/_version.py

@@ -1,10 +0,0 @@
-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

@@ -1,88 +0,0 @@
-"""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

@@ -1,5 +0,0 @@
-"""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

@@ -1,70 +0,0 @@
-"""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

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

libs/cli/langchain_cli/integration_template/LICENSE

@@ -1,21 +0,0 @@
-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

@@ -1,58 +0,0 @@
-.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

@@ -1,46 +0,0 @@
-# __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

@@ -1,264 +0,0 @@
-{
-  "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

@@ -1,219 +0,0 @@
-{
- "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

@@ -1,238 +0,0 @@
-{
-  "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

@@ -1,50 +0,0 @@
-{
- "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

@@ -1,245 +0,0 @@
-{
- "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

@@ -1,204 +0,0 @@
-{
-  "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

@@ -1,246 +0,0 @@
-{
- "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

@@ -1,199 +0,0 @@
-{
-  "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

@@ -1,271 +0,0 @@
-{
-  "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

@@ -1,333 +0,0 @@
-{
- "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 persistent 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

@@ -1,27 +0,0 @@
-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

@@ -1,423 +0,0 @@
-"""__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:
-            Name of __ModuleName__ model to use.
-        temperature:
-            Sampling temperature.
-        max_tokens:
-            Max number of tokens to generate.
-
-    # TODO: Populate with relevant params.
-    Key init args — client params:
-        timeout:
-            Timeout for requests.
-        max_retries:
-            Max number of retries.
-        api_key:
-            __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

@@ -1,74 +0,0 @@
-"""__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

@@ -1,96 +0,0 @@
-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

@@ -1,107 +0,0 @@
-"""__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

@@ -1,73 +0,0 @@
-"""__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

@@ -1,95 +0,0 @@
-"""__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

@@ -1,438 +0,0 @@
-"""__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:
-            Name of the collection.
-        embedding_function:
-            Embedding function to use.
-
-    # TODO: Populate with relevant params.
-    Key init args — client params:
-        client:
-            Client to use.
-        connection_args:
-            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

@@ -1,50 +0,0 @@
-[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

@@ -1,17 +0,0 @@
-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

@@ -1,18 +0,0 @@
-#!/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

@@ -1,21 +0,0 @@
-"""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

@@ -1,7 +0,0 @@
-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

@@ -1,16 +0,0 @@
-"""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

@@ -1,22 +0,0 @@
-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

@@ -1,27 +0,0 @@
-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

@@ -1,20 +0,0 @@
-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

@@ -1,21 +0,0 @@
-"""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

@@ -1,16 +0,0 @@
-"""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

@@ -1,27 +0,0 @@
-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

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

libs/cli/langchain_cli/namespaces/app.py

@@ -1,371 +0,0 @@
-"""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

@@ -1,260 +0,0 @@
-"""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

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

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

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

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

@@ -1,56 +0,0 @@
-# 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

@@ -1,15 +0,0 @@
-
-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

@@ -1,67 +0,0 @@
-
-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()

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

@@ -1,38 +0,0 @@
-
-language python
-
-// This migration is generated automatically - do not manually edit this file
-pattern langchain_migrate_community_to_core() {
-  find_replace_imports(list=[
-    [`langchain_community.callbacks.tracers`, `ConsoleCallbackHandler`, `langchain_core.tracers`, `ConsoleCallbackHandler`],
-    [`langchain_community.callbacks.tracers`, `FunctionCallbackHandler`, `langchain_core.tracers.stdout`, `FunctionCallbackHandler`],
-    [`langchain_community.callbacks.tracers`, `LangChainTracer`, `langchain_core.tracers`, `LangChainTracer`],
-    [`langchain_community.callbacks.tracers`, `LangChainTracerV1`, `langchain_core.tracers.langchain_v1`, `LangChainTracerV1`],
-    [`langchain_community.docstore.document`, `Document`, `langchain_core.documents`, `Document`],
-    [`langchain_community.document_loaders`, `Blob`, `langchain_core.document_loaders`, `Blob`],
-    [`langchain_community.document_loaders`, `BlobLoader`, `langchain_core.document_loaders`, `BlobLoader`],
-    [`langchain_community.document_loaders.base`, `BaseBlobParser`, `langchain_core.document_loaders`, `BaseBlobParser`],
-    [`langchain_community.document_loaders.base`, `BaseLoader`, `langchain_core.document_loaders`, `BaseLoader`],
-    [`langchain_community.document_loaders.blob_loaders`, `Blob`, `langchain_core.document_loaders`, `Blob`],
-    [`langchain_community.document_loaders.blob_loaders`, `BlobLoader`, `langchain_core.document_loaders`, `BlobLoader`],
-    [`langchain_community.document_loaders.blob_loaders.schema`, `Blob`, `langchain_core.document_loaders`, `Blob`],
-    [`langchain_community.document_loaders.blob_loaders.schema`, `BlobLoader`, `langchain_core.document_loaders`, `BlobLoader`],
-    [`langchain_community.tools`, `BaseTool`, `langchain_core.tools`, `BaseTool`],
-    [`langchain_community.tools`, `StructuredTool`, `langchain_core.tools`, `StructuredTool`],
-    [`langchain_community.tools`, `Tool`, `langchain_core.tools`, `Tool`],
-    [`langchain_community.tools`, `format_tool_to_openai_function`, `langchain_core.utils.function_calling`, `format_tool_to_openai_function`],
-    [`langchain_community.tools`, `tool`, `langchain_core.tools`, `tool`],
-    [`langchain_community.tools.convert_to_openai`, `format_tool_to_openai_function`, `langchain_core.utils.function_calling`, `format_tool_to_openai_function`],
-    [`langchain_community.tools.convert_to_openai`, `format_tool_to_openai_tool`, `langchain_core.utils.function_calling`, `format_tool_to_openai_tool`],
-    [`langchain_community.tools.render`, `format_tool_to_openai_function`, `langchain_core.utils.function_calling`, `format_tool_to_openai_function`],
-    [`langchain_community.tools.render`, `format_tool_to_openai_tool`, `langchain_core.utils.function_calling`, `format_tool_to_openai_tool`],
-    [`langchain_community.utils.openai_functions`, `FunctionDescription`, `langchain_core.utils.function_calling`, `FunctionDescription`],
-    [`langchain_community.utils.openai_functions`, `ToolDescription`, `langchain_core.utils.function_calling`, `ToolDescription`],
-    [`langchain_community.utils.openai_functions`, `convert_pydantic_to_openai_function`, `langchain_core.utils.function_calling`, `convert_pydantic_to_openai_function`],
-    [`langchain_community.utils.openai_functions`, `convert_pydantic_to_openai_tool`, `langchain_core.utils.function_calling`, `convert_pydantic_to_openai_tool`],
-    [`langchain_community.vectorstores`, `VectorStore`, `langchain_core.vectorstores`, `VectorStore`]
-  ])
-}
-
-// Add this for invoking directly
-langchain_migrate_community_to_core()

libs/cli/langchain_cli/namespaces/migrate/.grit/patterns/community_to_core.json

@@ -1,101 +0,0 @@
-[
-  [
-    "langchain_community.callbacks.tracers.ConsoleCallbackHandler",
-    "langchain_core.tracers.ConsoleCallbackHandler"
-  ],
-  [
-    "langchain_community.callbacks.tracers.FunctionCallbackHandler",
-    "langchain_core.tracers.stdout.FunctionCallbackHandler"
-  ],
-  [
-    "langchain_community.callbacks.tracers.LangChainTracer",
-    "langchain_core.tracers.LangChainTracer"
-  ],
-  [
-    "langchain_community.callbacks.tracers.LangChainTracerV1",
-    "langchain_core.tracers.langchain_v1.LangChainTracerV1"
-  ],
-  [
-    "langchain_community.docstore.document.Document",
-    "langchain_core.documents.Document"
-  ],
-  [
-    "langchain_community.document_loaders.Blob",
-    "langchain_core.document_loaders.Blob"
-  ],
-  [
-    "langchain_community.document_loaders.BlobLoader",
-    "langchain_core.document_loaders.BlobLoader"
-  ],
-  [
-    "langchain_community.document_loaders.base.BaseBlobParser",
-    "langchain_core.document_loaders.BaseBlobParser"
-  ],
-  [
-    "langchain_community.document_loaders.base.BaseLoader",
-    "langchain_core.document_loaders.BaseLoader"
-  ],
-  [
-    "langchain_community.document_loaders.blob_loaders.Blob",
-    "langchain_core.document_loaders.Blob"
-  ],
-  [
-    "langchain_community.document_loaders.blob_loaders.BlobLoader",
-    "langchain_core.document_loaders.BlobLoader"
-  ],
-  [
-    "langchain_community.document_loaders.blob_loaders.schema.Blob",
-    "langchain_core.document_loaders.Blob"
-  ],
-  [
-    "langchain_community.document_loaders.blob_loaders.schema.BlobLoader",
-    "langchain_core.document_loaders.BlobLoader"
-  ],
-  ["langchain_community.tools.BaseTool", "langchain_core.tools.BaseTool"],
-  [
-    "langchain_community.tools.StructuredTool",
-    "langchain_core.tools.StructuredTool"
-  ],
-  ["langchain_community.tools.Tool", "langchain_core.tools.Tool"],
-  [
-    "langchain_community.tools.format_tool_to_openai_function",
-    "langchain_core.utils.function_calling.format_tool_to_openai_function"
-  ],
-  ["langchain_community.tools.tool", "langchain_core.tools.tool"],
-  [
-    "langchain_community.tools.convert_to_openai.format_tool_to_openai_function",
-    "langchain_core.utils.function_calling.format_tool_to_openai_function"
-  ],
-  [
-    "langchain_community.tools.convert_to_openai.format_tool_to_openai_tool",
-    "langchain_core.utils.function_calling.format_tool_to_openai_tool"
-  ],
-  [
-    "langchain_community.tools.render.format_tool_to_openai_function",
-    "langchain_core.utils.function_calling.format_tool_to_openai_function"
-  ],
-  [
-    "langchain_community.tools.render.format_tool_to_openai_tool",
-    "langchain_core.utils.function_calling.format_tool_to_openai_tool"
-  ],
-  [
-    "langchain_community.utils.openai_functions.FunctionDescription",
-    "langchain_core.utils.function_calling.FunctionDescription"
-  ],
-  [
-    "langchain_community.utils.openai_functions.ToolDescription",
-    "langchain_core.utils.function_calling.ToolDescription"
-  ],
-  [
-    "langchain_community.utils.openai_functions.convert_pydantic_to_openai_function",
-    "langchain_core.utils.function_calling.convert_pydantic_to_openai_function"
-  ],
-  [
-    "langchain_community.utils.openai_functions.convert_pydantic_to_openai_tool",
-    "langchain_core.utils.function_calling.convert_pydantic_to_openai_tool"
-  ],
-  [
-    "langchain_community.vectorstores.VectorStore",
-    "langchain_core.vectorstores.VectorStore"
-  ]
-]

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

@@ -1,18 +0,0 @@
-language python
-
-pattern langchain_all_migrations() {
-  any {
-    langchain_migrate_community_to_core(),
-    langchain_migrate_fireworks(),
-    langchain_migrate_ibm(),
-    langchain_migrate_langchain_to_core(),
-    langchain_migrate_langchain_to_langchain_community(),
-    langchain_migrate_langchain_to_textsplitters(),
-    langchain_migrate_openai(),
-    langchain_migrate_pinecone(),
-    langchain_migrate_anthropic(),
-    replace_pydantic_v1_shim()
-  }
-}
-
-langchain_all_migrations()

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

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

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

@@ -1,13 +0,0 @@
-
-language python
-
-// This migration is generated automatically - do not manually edit this file
-pattern langchain_migrate_ibm() {
-  find_replace_imports(list=[
-    [`langchain_community.llms.watsonxllm`, `WatsonxLLM`, `langchain_ibm`, `WatsonxLLM`],
-    [`langchain_community.llms`, `WatsonxLLM`, `langchain_ibm`, `WatsonxLLM`]
-  ])
-}
-
-// Add this for invoking directly
-langchain_migrate_ibm()

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

@@ -1,542 +0,0 @@
-
-language python
-
-// This migration is generated automatically - do not manually edit this file
-pattern langchain_migrate_langchain_to_core() {
-  find_replace_imports(list=[
-    [`langchain._api`, `deprecated`, `langchain_core._api`, `deprecated`],
-    [`langchain._api`, `LangChainDeprecationWarning`, `langchain_core._api`, `LangChainDeprecationWarning`],
-    [`langchain._api`, `suppress_langchain_deprecation_warning`, `langchain_core._api`, `suppress_langchain_deprecation_warning`],
-    [`langchain._api`, `surface_langchain_deprecation_warnings`, `langchain_core._api`, `surface_langchain_deprecation_warnings`],
-    [`langchain._api`, `warn_deprecated`, `langchain_core._api`, `warn_deprecated`],
-    [`langchain._api.deprecation`, `LangChainDeprecationWarning`, `langchain_core._api`, `LangChainDeprecationWarning`],
-    [`langchain._api.deprecation`, `LangChainPendingDeprecationWarning`, `langchain_core._api.deprecation`, `LangChainPendingDeprecationWarning`],
-    [`langchain._api.deprecation`, `deprecated`, `langchain_core._api`, `deprecated`],
-    [`langchain._api.deprecation`, `suppress_langchain_deprecation_warning`, `langchain_core._api`, `suppress_langchain_deprecation_warning`],
-    [`langchain._api.deprecation`, `warn_deprecated`, `langchain_core._api`, `warn_deprecated`],
-    [`langchain._api.deprecation`, `surface_langchain_deprecation_warnings`, `langchain_core._api`, `surface_langchain_deprecation_warnings`],
-    [`langchain._api.path`, `get_relative_path`, `langchain_core._api`, `get_relative_path`],
-    [`langchain._api.path`, `as_import_path`, `langchain_core._api`, `as_import_path`],
-    [`langchain.agents`, `Tool`, `langchain_core.tools`, `Tool`],
-    [`langchain.agents`, `tool`, `langchain_core.tools`, `tool`],
-    [`langchain.agents.tools`, `BaseTool`, `langchain_core.tools`, `BaseTool`],
-    [`langchain.agents.tools`, `tool`, `langchain_core.tools`, `tool`],
-    [`langchain.agents.tools`, `Tool`, `langchain_core.tools`, `Tool`],
-    [`langchain.base_language`, `BaseLanguageModel`, `langchain_core.language_models`, `BaseLanguageModel`],
-    [`langchain.callbacks`, `StdOutCallbackHandler`, `langchain_core.callbacks`, `StdOutCallbackHandler`],
-    [`langchain.callbacks`, `StreamingStdOutCallbackHandler`, `langchain_core.callbacks`, `StreamingStdOutCallbackHandler`],
-    [`langchain.callbacks`, `LangChainTracer`, `langchain_core.tracers`, `LangChainTracer`],
-    [`langchain.callbacks`, `tracing_enabled`, `langchain_core.tracers.context`, `tracing_enabled`],
-    [`langchain.callbacks`, `tracing_v2_enabled`, `langchain_core.tracers.context`, `tracing_v2_enabled`],
-    [`langchain.callbacks`, `collect_runs`, `langchain_core.tracers.context`, `collect_runs`],
-    [`langchain.callbacks.base`, `RetrieverManagerMixin`, `langchain_core.callbacks`, `RetrieverManagerMixin`],
-    [`langchain.callbacks.base`, `LLMManagerMixin`, `langchain_core.callbacks`, `LLMManagerMixin`],
-    [`langchain.callbacks.base`, `ChainManagerMixin`, `langchain_core.callbacks`, `ChainManagerMixin`],
-    [`langchain.callbacks.base`, `ToolManagerMixin`, `langchain_core.callbacks`, `ToolManagerMixin`],
-    [`langchain.callbacks.base`, `CallbackManagerMixin`, `langchain_core.callbacks`, `CallbackManagerMixin`],
-    [`langchain.callbacks.base`, `RunManagerMixin`, `langchain_core.callbacks`, `RunManagerMixin`],
-    [`langchain.callbacks.base`, `BaseCallbackHandler`, `langchain_core.callbacks`, `BaseCallbackHandler`],
-    [`langchain.callbacks.base`, `AsyncCallbackHandler`, `langchain_core.callbacks`, `AsyncCallbackHandler`],
-    [`langchain.callbacks.base`, `BaseCallbackManager`, `langchain_core.callbacks`, `BaseCallbackManager`],
-    [`langchain.callbacks.manager`, `BaseRunManager`, `langchain_core.callbacks`, `BaseRunManager`],
-    [`langchain.callbacks.manager`, `RunManager`, `langchain_core.callbacks`, `RunManager`],
-    [`langchain.callbacks.manager`, `ParentRunManager`, `langchain_core.callbacks`, `ParentRunManager`],
-    [`langchain.callbacks.manager`, `AsyncRunManager`, `langchain_core.callbacks`, `AsyncRunManager`],
-    [`langchain.callbacks.manager`, `AsyncParentRunManager`, `langchain_core.callbacks`, `AsyncParentRunManager`],
-    [`langchain.callbacks.manager`, `CallbackManagerForLLMRun`, `langchain_core.callbacks`, `CallbackManagerForLLMRun`],
-    [`langchain.callbacks.manager`, `AsyncCallbackManagerForLLMRun`, `langchain_core.callbacks`, `AsyncCallbackManagerForLLMRun`],
-    [`langchain.callbacks.manager`, `CallbackManagerForChainRun`, `langchain_core.callbacks`, `CallbackManagerForChainRun`],
-    [`langchain.callbacks.manager`, `AsyncCallbackManagerForChainRun`, `langchain_core.callbacks`, `AsyncCallbackManagerForChainRun`],
-    [`langchain.callbacks.manager`, `CallbackManagerForToolRun`, `langchain_core.callbacks`, `CallbackManagerForToolRun`],
-    [`langchain.callbacks.manager`, `AsyncCallbackManagerForToolRun`, `langchain_core.callbacks`, `AsyncCallbackManagerForToolRun`],
-    [`langchain.callbacks.manager`, `CallbackManagerForRetrieverRun`, `langchain_core.callbacks`, `CallbackManagerForRetrieverRun`],
-    [`langchain.callbacks.manager`, `AsyncCallbackManagerForRetrieverRun`, `langchain_core.callbacks`, `AsyncCallbackManagerForRetrieverRun`],
-    [`langchain.callbacks.manager`, `CallbackManager`, `langchain_core.callbacks`, `CallbackManager`],
-    [`langchain.callbacks.manager`, `CallbackManagerForChainGroup`, `langchain_core.callbacks`, `CallbackManagerForChainGroup`],
-    [`langchain.callbacks.manager`, `AsyncCallbackManager`, `langchain_core.callbacks`, `AsyncCallbackManager`],
-    [`langchain.callbacks.manager`, `AsyncCallbackManagerForChainGroup`, `langchain_core.callbacks`, `AsyncCallbackManagerForChainGroup`],
-    [`langchain.callbacks.manager`, `tracing_enabled`, `langchain_core.tracers.context`, `tracing_enabled`],
-    [`langchain.callbacks.manager`, `tracing_v2_enabled`, `langchain_core.tracers.context`, `tracing_v2_enabled`],
-    [`langchain.callbacks.manager`, `collect_runs`, `langchain_core.tracers.context`, `collect_runs`],
-    [`langchain.callbacks.manager`, `atrace_as_chain_group`, `langchain_core.callbacks.manager`, `atrace_as_chain_group`],
-    [`langchain.callbacks.manager`, `trace_as_chain_group`, `langchain_core.callbacks.manager`, `trace_as_chain_group`],
-    [`langchain.callbacks.manager`, `handle_event`, `langchain_core.callbacks.manager`, `handle_event`],
-    [`langchain.callbacks.manager`, `ahandle_event`, `langchain_core.callbacks.manager`, `ahandle_event`],
-    [`langchain.callbacks.manager`, `env_var_is_set`, `langchain_core.utils.env`, `env_var_is_set`],
-    [`langchain.callbacks.stdout`, `StdOutCallbackHandler`, `langchain_core.callbacks`, `StdOutCallbackHandler`],
-    [`langchain.callbacks.streaming_stdout`, `StreamingStdOutCallbackHandler`, `langchain_core.callbacks`, `StreamingStdOutCallbackHandler`],
-    [`langchain.callbacks.tracers`, `ConsoleCallbackHandler`, `langchain_core.tracers`, `ConsoleCallbackHandler`],
-    [`langchain.callbacks.tracers`, `FunctionCallbackHandler`, `langchain_core.tracers.stdout`, `FunctionCallbackHandler`],
-    [`langchain.callbacks.tracers`, `LangChainTracer`, `langchain_core.tracers`, `LangChainTracer`],
-    [`langchain.callbacks.tracers`, `LangChainTracerV1`, `langchain_core.tracers.langchain_v1`, `LangChainTracerV1`],
-    [`langchain.callbacks.tracers.base`, `BaseTracer`, `langchain_core.tracers`, `BaseTracer`],
-    [`langchain.callbacks.tracers.base`, `TracerException`, `langchain_core.exceptions`, `TracerException`],
-    [`langchain.callbacks.tracers.evaluation`, `wait_for_all_evaluators`, `langchain_core.tracers.evaluation`, `wait_for_all_evaluators`],
-    [`langchain.callbacks.tracers.evaluation`, `EvaluatorCallbackHandler`, `langchain_core.tracers`, `EvaluatorCallbackHandler`],
-    [`langchain.callbacks.tracers.langchain`, `LangChainTracer`, `langchain_core.tracers`, `LangChainTracer`],
-    [`langchain.callbacks.tracers.langchain`, `wait_for_all_tracers`, `langchain_core.tracers.langchain`, `wait_for_all_tracers`],
-    [`langchain.callbacks.tracers.langchain_v1`, `LangChainTracerV1`, `langchain_core.tracers.langchain_v1`, `LangChainTracerV1`],
-    [`langchain.callbacks.tracers.log_stream`, `LogEntry`, `langchain_core.tracers.log_stream`, `LogEntry`],
-    [`langchain.callbacks.tracers.log_stream`, `RunState`, `langchain_core.tracers.log_stream`, `RunState`],
-    [`langchain.callbacks.tracers.log_stream`, `RunLog`, `langchain_core.tracers`, `RunLog`],
-    [`langchain.callbacks.tracers.log_stream`, `RunLogPatch`, `langchain_core.tracers`, `RunLogPatch`],
-    [`langchain.callbacks.tracers.log_stream`, `LogStreamCallbackHandler`, `langchain_core.tracers`, `LogStreamCallbackHandler`],
-    [`langchain.callbacks.tracers.root_listeners`, `RootListenersTracer`, `langchain_core.tracers.root_listeners`, `RootListenersTracer`],
-    [`langchain.callbacks.tracers.run_collector`, `RunCollectorCallbackHandler`, `langchain_core.tracers.run_collector`, `RunCollectorCallbackHandler`],
-    [`langchain.callbacks.tracers.schemas`, `BaseRun`, `langchain_core.tracers.schemas`, `BaseRun`],
-    [`langchain.callbacks.tracers.schemas`, `ChainRun`, `langchain_core.tracers.schemas`, `ChainRun`],
-    [`langchain.callbacks.tracers.schemas`, `LLMRun`, `langchain_core.tracers.schemas`, `LLMRun`],
-    [`langchain.callbacks.tracers.schemas`, `Run`, `langchain_core.tracers`, `Run`],
-    [`langchain.callbacks.tracers.schemas`, `RunTypeEnum`, `langchain_core.tracers.schemas`, `RunTypeEnum`],
-    [`langchain.callbacks.tracers.schemas`, `ToolRun`, `langchain_core.tracers.schemas`, `ToolRun`],
-    [`langchain.callbacks.tracers.schemas`, `TracerSession`, `langchain_core.tracers.schemas`, `TracerSession`],
-    [`langchain.callbacks.tracers.schemas`, `TracerSessionBase`, `langchain_core.tracers.schemas`, `TracerSessionBase`],
-    [`langchain.callbacks.tracers.schemas`, `TracerSessionV1`, `langchain_core.tracers.schemas`, `TracerSessionV1`],
-    [`langchain.callbacks.tracers.schemas`, `TracerSessionV1Base`, `langchain_core.tracers.schemas`, `TracerSessionV1Base`],
-    [`langchain.callbacks.tracers.schemas`, `TracerSessionV1Create`, `langchain_core.tracers.schemas`, `TracerSessionV1Create`],
-    [`langchain.callbacks.tracers.stdout`, `FunctionCallbackHandler`, `langchain_core.tracers.stdout`, `FunctionCallbackHandler`],
-    [`langchain.callbacks.tracers.stdout`, `ConsoleCallbackHandler`, `langchain_core.tracers`, `ConsoleCallbackHandler`],
-    [`langchain.chains.openai_functions`, `convert_to_openai_function`, `langchain_core.utils.function_calling`, `convert_to_openai_function`],
-    [`langchain.chains.openai_functions.base`, `convert_to_openai_function`, `langchain_core.utils.function_calling`, `convert_to_openai_function`],
-    [`langchain.chat_models.base`, `BaseChatModel`, `langchain_core.language_models`, `BaseChatModel`],
-    [`langchain.chat_models.base`, `SimpleChatModel`, `langchain_core.language_models`, `SimpleChatModel`],
-    [`langchain.chat_models.base`, `generate_from_stream`, `langchain_core.language_models.chat_models`, `generate_from_stream`],
-    [`langchain.chat_models.base`, `agenerate_from_stream`, `langchain_core.language_models.chat_models`, `agenerate_from_stream`],
-    [`langchain.docstore.document`, `Document`, `langchain_core.documents`, `Document`],
-    [`langchain.document_loaders`, `Blob`, `langchain_core.document_loaders`, `Blob`],
-    [`langchain.document_loaders`, `BlobLoader`, `langchain_core.document_loaders`, `BlobLoader`],
-    [`langchain.document_loaders.base`, `BaseLoader`, `langchain_core.document_loaders`, `BaseLoader`],
-    [`langchain.document_loaders.base`, `BaseBlobParser`, `langchain_core.document_loaders`, `BaseBlobParser`],
-    [`langchain.document_loaders.blob_loaders`, `BlobLoader`, `langchain_core.document_loaders`, `BlobLoader`],
-    [`langchain.document_loaders.blob_loaders`, `Blob`, `langchain_core.document_loaders`, `Blob`],
-    [`langchain.document_loaders.blob_loaders.schema`, `Blob`, `langchain_core.document_loaders`, `Blob`],
-    [`langchain.document_loaders.blob_loaders.schema`, `BlobLoader`, `langchain_core.document_loaders`, `BlobLoader`],
-    [`langchain.embeddings.base`, `Embeddings`, `langchain_core.embeddings`, `Embeddings`],
-    [`langchain.formatting`, `StrictFormatter`, `langchain_core.utils`, `StrictFormatter`],
-    [`langchain.input`, `get_bolded_text`, `langchain_core.utils`, `get_bolded_text`],
-    [`langchain.input`, `get_color_mapping`, `langchain_core.utils`, `get_color_mapping`],
-    [`langchain.input`, `get_colored_text`, `langchain_core.utils`, `get_colored_text`],
-    [`langchain.input`, `print_text`, `langchain_core.utils`, `print_text`],
-    [`langchain.llms.base`, `BaseLanguageModel`, `langchain_core.language_models`, `BaseLanguageModel`],
-    [`langchain.llms.base`, `BaseLLM`, `langchain_core.language_models`, `BaseLLM`],
-    [`langchain.llms.base`, `LLM`, `langchain_core.language_models`, `LLM`],
-    [`langchain.load`, `dumpd`, `langchain_core.load`, `dumpd`],
-    [`langchain.load`, `dumps`, `langchain_core.load`, `dumps`],
-    [`langchain.load`, `load`, `langchain_core.load`, `load`],
-    [`langchain.load`, `loads`, `langchain_core.load`, `loads`],
-    [`langchain.load.dump`, `default`, `langchain_core.load.dump`, `default`],
-    [`langchain.load.dump`, `dumps`, `langchain_core.load`, `dumps`],
-    [`langchain.load.dump`, `dumpd`, `langchain_core.load`, `dumpd`],
-    [`langchain.load.load`, `Reviver`, `langchain_core.load.load`, `Reviver`],
-    [`langchain.load.load`, `loads`, `langchain_core.load`, `loads`],
-    [`langchain.load.load`, `load`, `langchain_core.load`, `load`],
-    [`langchain.load.serializable`, `BaseSerialized`, `langchain_core.load.serializable`, `BaseSerialized`],
-    [`langchain.load.serializable`, `SerializedConstructor`, `langchain_core.load.serializable`, `SerializedConstructor`],
-    [`langchain.load.serializable`, `SerializedSecret`, `langchain_core.load.serializable`, `SerializedSecret`],
-    [`langchain.load.serializable`, `SerializedNotImplemented`, `langchain_core.load.serializable`, `SerializedNotImplemented`],
-    [`langchain.load.serializable`, `try_neq_default`, `langchain_core.load.serializable`, `try_neq_default`],
-    [`langchain.load.serializable`, `Serializable`, `langchain_core.load`, `Serializable`],
-    [`langchain.load.serializable`, `to_json_not_implemented`, `langchain_core.load.serializable`, `to_json_not_implemented`],
-    [`langchain.output_parsers`, `CommaSeparatedListOutputParser`, `langchain_core.output_parsers`, `CommaSeparatedListOutputParser`],
-    [`langchain.output_parsers`, `ListOutputParser`, `langchain_core.output_parsers`, `ListOutputParser`],
-    [`langchain.output_parsers`, `MarkdownListOutputParser`, `langchain_core.output_parsers`, `MarkdownListOutputParser`],
-    [`langchain.output_parsers`, `NumberedListOutputParser`, `langchain_core.output_parsers`, `NumberedListOutputParser`],
-    [`langchain.output_parsers`, `PydanticOutputParser`, `langchain_core.output_parsers`, `PydanticOutputParser`],
-    [`langchain.output_parsers`, `XMLOutputParser`, `langchain_core.output_parsers`, `XMLOutputParser`],
-    [`langchain.output_parsers`, `JsonOutputToolsParser`, `langchain_core.output_parsers.openai_tools`, `JsonOutputToolsParser`],
-    [`langchain.output_parsers`, `PydanticToolsParser`, `langchain_core.output_parsers.openai_tools`, `PydanticToolsParser`],
-    [`langchain.output_parsers`, `JsonOutputKeyToolsParser`, `langchain_core.output_parsers.openai_tools`, `JsonOutputKeyToolsParser`],
-    [`langchain.output_parsers.json`, `SimpleJsonOutputParser`, `langchain_core.output_parsers`, `JsonOutputParser`],
-    [`langchain.output_parsers.json`, `parse_partial_json`, `langchain_core.utils.json`, `parse_partial_json`],
-    [`langchain.output_parsers.json`, `parse_json_markdown`, `langchain_core.utils.json`, `parse_json_markdown`],
-    [`langchain.output_parsers.json`, `parse_and_check_json_markdown`, `langchain_core.utils.json`, `parse_and_check_json_markdown`],
-    [`langchain.output_parsers.list`, `ListOutputParser`, `langchain_core.output_parsers`, `ListOutputParser`],
-    [`langchain.output_parsers.list`, `CommaSeparatedListOutputParser`, `langchain_core.output_parsers`, `CommaSeparatedListOutputParser`],
-    [`langchain.output_parsers.list`, `NumberedListOutputParser`, `langchain_core.output_parsers`, `NumberedListOutputParser`],
-    [`langchain.output_parsers.list`, `MarkdownListOutputParser`, `langchain_core.output_parsers`, `MarkdownListOutputParser`],
-    [`langchain.output_parsers.openai_functions`, `PydanticOutputFunctionsParser`, `langchain_core.output_parsers.openai_functions`, `PydanticOutputFunctionsParser`],
-    [`langchain.output_parsers.openai_functions`, `PydanticAttrOutputFunctionsParser`, `langchain_core.output_parsers.openai_functions`, `PydanticAttrOutputFunctionsParser`],
-    [`langchain.output_parsers.openai_functions`, `JsonOutputFunctionsParser`, `langchain_core.output_parsers.openai_functions`, `JsonOutputFunctionsParser`],
-    [`langchain.output_parsers.openai_functions`, `JsonKeyOutputFunctionsParser`, `langchain_core.output_parsers.openai_functions`, `JsonKeyOutputFunctionsParser`],
-    [`langchain.output_parsers.openai_tools`, `PydanticToolsParser`, `langchain_core.output_parsers.openai_tools`, `PydanticToolsParser`],
-    [`langchain.output_parsers.openai_tools`, `JsonOutputToolsParser`, `langchain_core.output_parsers.openai_tools`, `JsonOutputToolsParser`],
-    [`langchain.output_parsers.openai_tools`, `JsonOutputKeyToolsParser`, `langchain_core.output_parsers.openai_tools`, `JsonOutputKeyToolsParser`],
-    [`langchain.output_parsers.pydantic`, `PydanticOutputParser`, `langchain_core.output_parsers`, `PydanticOutputParser`],
-    [`langchain.output_parsers.xml`, `XMLOutputParser`, `langchain_core.output_parsers`, `XMLOutputParser`],
-    [`langchain.prompts`, `AIMessagePromptTemplate`, `langchain_core.prompts`, `AIMessagePromptTemplate`],
-    [`langchain.prompts`, `BaseChatPromptTemplate`, `langchain_core.prompts`, `BaseChatPromptTemplate`],
-    [`langchain.prompts`, `BasePromptTemplate`, `langchain_core.prompts`, `BasePromptTemplate`],
-    [`langchain.prompts`, `ChatMessagePromptTemplate`, `langchain_core.prompts`, `ChatMessagePromptTemplate`],
-    [`langchain.prompts`, `ChatPromptTemplate`, `langchain_core.prompts`, `ChatPromptTemplate`],
-    [`langchain.prompts`, `FewShotPromptTemplate`, `langchain_core.prompts`, `FewShotPromptTemplate`],
-    [`langchain.prompts`, `FewShotPromptWithTemplates`, `langchain_core.prompts`, `FewShotPromptWithTemplates`],
-    [`langchain.prompts`, `HumanMessagePromptTemplate`, `langchain_core.prompts`, `HumanMessagePromptTemplate`],
-    [`langchain.prompts`, `LengthBasedExampleSelector`, `langchain_core.example_selectors`, `LengthBasedExampleSelector`],
-    [`langchain.prompts`, `MaxMarginalRelevanceExampleSelector`, `langchain_core.example_selectors`, `MaxMarginalRelevanceExampleSelector`],
-    [`langchain.prompts`, `MessagesPlaceholder`, `langchain_core.prompts`, `MessagesPlaceholder`],
-    [`langchain.prompts`, `PipelinePromptTemplate`, `langchain_core.prompts`, `PipelinePromptTemplate`],
-    [`langchain.prompts`, `PromptTemplate`, `langchain_core.prompts`, `PromptTemplate`],
-    [`langchain.prompts`, `SemanticSimilarityExampleSelector`, `langchain_core.example_selectors`, `SemanticSimilarityExampleSelector`],
-    [`langchain.prompts`, `StringPromptTemplate`, `langchain_core.prompts`, `StringPromptTemplate`],
-    [`langchain.prompts`, `SystemMessagePromptTemplate`, `langchain_core.prompts`, `SystemMessagePromptTemplate`],
-    [`langchain.prompts`, `load_prompt`, `langchain_core.prompts`, `load_prompt`],
-    [`langchain.prompts`, `FewShotChatMessagePromptTemplate`, `langchain_core.prompts`, `FewShotChatMessagePromptTemplate`],
-    [`langchain.prompts`, `Prompt`, `langchain_core.prompts`, `PromptTemplate`],
-    [`langchain.prompts.base`, `jinja2_formatter`, `langchain_core.prompts`, `jinja2_formatter`],
-    [`langchain.prompts.base`, `validate_jinja2`, `langchain_core.prompts`, `validate_jinja2`],
-    [`langchain.prompts.base`, `check_valid_template`, `langchain_core.prompts`, `check_valid_template`],
-    [`langchain.prompts.base`, `get_template_variables`, `langchain_core.prompts`, `get_template_variables`],
-    [`langchain.prompts.base`, `StringPromptTemplate`, `langchain_core.prompts`, `StringPromptTemplate`],
-    [`langchain.prompts.base`, `BasePromptTemplate`, `langchain_core.prompts`, `BasePromptTemplate`],
-    [`langchain.prompts.base`, `StringPromptValue`, `langchain_core.prompt_values`, `StringPromptValue`],
-    [`langchain.prompts.base`, `_get_jinja2_variables_from_template`, `langchain_core.prompts.string`, `_get_jinja2_variables_from_template`],
-    [`langchain.prompts.chat`, `BaseMessagePromptTemplate`, `langchain_core.prompts.chat`, `BaseMessagePromptTemplate`],
-    [`langchain.prompts.chat`, `MessagesPlaceholder`, `langchain_core.prompts`, `MessagesPlaceholder`],
-    [`langchain.prompts.chat`, `BaseStringMessagePromptTemplate`, `langchain_core.prompts.chat`, `BaseStringMessagePromptTemplate`],
-    [`langchain.prompts.chat`, `ChatMessagePromptTemplate`, `langchain_core.prompts`, `ChatMessagePromptTemplate`],
-    [`langchain.prompts.chat`, `HumanMessagePromptTemplate`, `langchain_core.prompts`, `HumanMessagePromptTemplate`],
-    [`langchain.prompts.chat`, `AIMessagePromptTemplate`, `langchain_core.prompts`, `AIMessagePromptTemplate`],
-    [`langchain.prompts.chat`, `SystemMessagePromptTemplate`, `langchain_core.prompts`, `SystemMessagePromptTemplate`],
-    [`langchain.prompts.chat`, `BaseChatPromptTemplate`, `langchain_core.prompts`, `BaseChatPromptTemplate`],
-    [`langchain.prompts.chat`, `ChatPromptTemplate`, `langchain_core.prompts`, `ChatPromptTemplate`],
-    [`langchain.prompts.chat`, `ChatPromptValue`, `langchain_core.prompt_values`, `ChatPromptValue`],
-    [`langchain.prompts.chat`, `ChatPromptValueConcrete`, `langchain_core.prompt_values`, `ChatPromptValueConcrete`],
-    [`langchain.prompts.chat`, `_convert_to_message`, `langchain_core.prompts.chat`, `_convert_to_message`],
-    [`langchain.prompts.chat`, `_create_template_from_message_type`, `langchain_core.prompts.chat`, `_create_template_from_message_type`],
-    [`langchain.prompts.example_selector`, `LengthBasedExampleSelector`, `langchain_core.example_selectors`, `LengthBasedExampleSelector`],
-    [`langchain.prompts.example_selector`, `MaxMarginalRelevanceExampleSelector`, `langchain_core.example_selectors`, `MaxMarginalRelevanceExampleSelector`],
-    [`langchain.prompts.example_selector`, `SemanticSimilarityExampleSelector`, `langchain_core.example_selectors`, `SemanticSimilarityExampleSelector`],
-    [`langchain.prompts.example_selector.base`, `BaseExampleSelector`, `langchain_core.example_selectors`, `BaseExampleSelector`],
-    [`langchain.prompts.example_selector.length_based`, `LengthBasedExampleSelector`, `langchain_core.example_selectors`, `LengthBasedExampleSelector`],
-    [`langchain.prompts.example_selector.semantic_similarity`, `sorted_values`, `langchain_core.example_selectors`, `sorted_values`],
-    [`langchain.prompts.example_selector.semantic_similarity`, `SemanticSimilarityExampleSelector`, `langchain_core.example_selectors`, `SemanticSimilarityExampleSelector`],
-    [`langchain.prompts.example_selector.semantic_similarity`, `MaxMarginalRelevanceExampleSelector`, `langchain_core.example_selectors`, `MaxMarginalRelevanceExampleSelector`],
-    [`langchain.prompts.few_shot`, `FewShotPromptTemplate`, `langchain_core.prompts`, `FewShotPromptTemplate`],
-    [`langchain.prompts.few_shot`, `FewShotChatMessagePromptTemplate`, `langchain_core.prompts`, `FewShotChatMessagePromptTemplate`],
-    [`langchain.prompts.few_shot`, `_FewShotPromptTemplateMixin`, `langchain_core.prompts.few_shot`, `_FewShotPromptTemplateMixin`],
-    [`langchain.prompts.few_shot_with_templates`, `FewShotPromptWithTemplates`, `langchain_core.prompts`, `FewShotPromptWithTemplates`],
-    [`langchain.prompts.loading`, `load_prompt_from_config`, `langchain_core.prompts.loading`, `load_prompt_from_config`],
-    [`langchain.prompts.loading`, `load_prompt`, `langchain_core.prompts`, `load_prompt`],
-    [`langchain.prompts.loading`, `try_load_from_hub`, `langchain_core.utils`, `try_load_from_hub`],
-    [`langchain.prompts.loading`, `_load_examples`, `langchain_core.prompts.loading`, `_load_examples`],
-    [`langchain.prompts.loading`, `_load_few_shot_prompt`, `langchain_core.prompts.loading`, `_load_few_shot_prompt`],
-    [`langchain.prompts.loading`, `_load_output_parser`, `langchain_core.prompts.loading`, `_load_output_parser`],
-    [`langchain.prompts.loading`, `_load_prompt`, `langchain_core.prompts.loading`, `_load_prompt`],
-    [`langchain.prompts.loading`, `_load_prompt_from_file`, `langchain_core.prompts.loading`, `_load_prompt_from_file`],
-    [`langchain.prompts.loading`, `_load_template`, `langchain_core.prompts.loading`, `_load_template`],
-    [`langchain.prompts.pipeline`, `PipelinePromptTemplate`, `langchain_core.prompts`, `PipelinePromptTemplate`],
-    [`langchain.prompts.pipeline`, `_get_inputs`, `langchain_core.prompts.pipeline`, `_get_inputs`],
-    [`langchain.prompts.prompt`, `PromptTemplate`, `langchain_core.prompts`, `PromptTemplate`],
-    [`langchain.prompts.prompt`, `Prompt`, `langchain_core.prompts`, `PromptTemplate`],
-    [`langchain.schema`, `BaseCache`, `langchain_core.caches`, `BaseCache`],
-    [`langchain.schema`, `BaseMemory`, `langchain_core.memory`, `BaseMemory`],
-    [`langchain.schema`, `BaseStore`, `langchain_core.stores`, `BaseStore`],
-    [`langchain.schema`, `AgentFinish`, `langchain_core.agents`, `AgentFinish`],
-    [`langchain.schema`, `AgentAction`, `langchain_core.agents`, `AgentAction`],
-    [`langchain.schema`, `Document`, `langchain_core.documents`, `Document`],
-    [`langchain.schema`, `BaseChatMessageHistory`, `langchain_core.chat_history`, `BaseChatMessageHistory`],
-    [`langchain.schema`, `BaseDocumentTransformer`, `langchain_core.documents`, `BaseDocumentTransformer`],
-    [`langchain.schema`, `BaseMessage`, `langchain_core.messages`, `BaseMessage`],
-    [`langchain.schema`, `ChatMessage`, `langchain_core.messages`, `ChatMessage`],
-    [`langchain.schema`, `FunctionMessage`, `langchain_core.messages`, `FunctionMessage`],
-    [`langchain.schema`, `HumanMessage`, `langchain_core.messages`, `HumanMessage`],
-    [`langchain.schema`, `AIMessage`, `langchain_core.messages`, `AIMessage`],
-    [`langchain.schema`, `SystemMessage`, `langchain_core.messages`, `SystemMessage`],
-    [`langchain.schema`, `messages_from_dict`, `langchain_core.messages`, `messages_from_dict`],
-    [`langchain.schema`, `messages_to_dict`, `langchain_core.messages`, `messages_to_dict`],
-    [`langchain.schema`, `message_to_dict`, `langchain_core.messages`, `message_to_dict`],
-    [`langchain.schema`, `_message_to_dict`, `langchain_core.messages`, `message_to_dict`],
-    [`langchain.schema`, `_message_from_dict`, `langchain_core.messages`, `_message_from_dict`],
-    [`langchain.schema`, `get_buffer_string`, `langchain_core.messages`, `get_buffer_string`],
-    [`langchain.schema`, `RunInfo`, `langchain_core.outputs`, `RunInfo`],
-    [`langchain.schema`, `LLMResult`, `langchain_core.outputs`, `LLMResult`],
-    [`langchain.schema`, `ChatResult`, `langchain_core.outputs`, `ChatResult`],
-    [`langchain.schema`, `ChatGeneration`, `langchain_core.outputs`, `ChatGeneration`],
-    [`langchain.schema`, `Generation`, `langchain_core.outputs`, `Generation`],
-    [`langchain.schema`, `PromptValue`, `langchain_core.prompt_values`, `PromptValue`],
-    [`langchain.schema`, `LangChainException`, `langchain_core.exceptions`, `LangChainException`],
-    [`langchain.schema`, `BaseRetriever`, `langchain_core.retrievers`, `BaseRetriever`],
-    [`langchain.schema`, `Memory`, `langchain_core.memory`, `BaseMemory`],
-    [`langchain.schema`, `OutputParserException`, `langchain_core.exceptions`, `OutputParserException`],
-    [`langchain.schema`, `StrOutputParser`, `langchain_core.output_parsers`, `StrOutputParser`],
-    [`langchain.schema`, `BaseOutputParser`, `langchain_core.output_parsers`, `BaseOutputParser`],
-    [`langchain.schema`, `BaseLLMOutputParser`, `langchain_core.output_parsers`, `BaseLLMOutputParser`],
-    [`langchain.schema`, `BasePromptTemplate`, `langchain_core.prompts`, `BasePromptTemplate`],
-    [`langchain.schema`, `format_document`, `langchain_core.prompts`, `format_document`],
-    [`langchain.schema.agent`, `AgentAction`, `langchain_core.agents`, `AgentAction`],
-    [`langchain.schema.agent`, `AgentActionMessageLog`, `langchain_core.agents`, `AgentActionMessageLog`],
-    [`langchain.schema.agent`, `AgentFinish`, `langchain_core.agents`, `AgentFinish`],
-    [`langchain.schema.cache`, `BaseCache`, `langchain_core.caches`, `BaseCache`],
-    [`langchain.schema.callbacks.base`, `RetrieverManagerMixin`, `langchain_core.callbacks`, `RetrieverManagerMixin`],
-    [`langchain.schema.callbacks.base`, `LLMManagerMixin`, `langchain_core.callbacks`, `LLMManagerMixin`],
-    [`langchain.schema.callbacks.base`, `ChainManagerMixin`, `langchain_core.callbacks`, `ChainManagerMixin`],
-    [`langchain.schema.callbacks.base`, `ToolManagerMixin`, `langchain_core.callbacks`, `ToolManagerMixin`],
-    [`langchain.schema.callbacks.base`, `CallbackManagerMixin`, `langchain_core.callbacks`, `CallbackManagerMixin`],
-    [`langchain.schema.callbacks.base`, `RunManagerMixin`, `langchain_core.callbacks`, `RunManagerMixin`],
-    [`langchain.schema.callbacks.base`, `BaseCallbackHandler`, `langchain_core.callbacks`, `BaseCallbackHandler`],
-    [`langchain.schema.callbacks.base`, `AsyncCallbackHandler`, `langchain_core.callbacks`, `AsyncCallbackHandler`],
-    [`langchain.schema.callbacks.base`, `BaseCallbackManager`, `langchain_core.callbacks`, `BaseCallbackManager`],
-    [`langchain.schema.callbacks.manager`, `tracing_enabled`, `langchain_core.tracers.context`, `tracing_enabled`],
-    [`langchain.schema.callbacks.manager`, `tracing_v2_enabled`, `langchain_core.tracers.context`, `tracing_v2_enabled`],
-    [`langchain.schema.callbacks.manager`, `collect_runs`, `langchain_core.tracers.context`, `collect_runs`],
-    [`langchain.schema.callbacks.manager`, `trace_as_chain_group`, `langchain_core.callbacks.manager`, `trace_as_chain_group`],
-    [`langchain.schema.callbacks.manager`, `handle_event`, `langchain_core.callbacks.manager`, `handle_event`],
-    [`langchain.schema.callbacks.manager`, `BaseRunManager`, `langchain_core.callbacks`, `BaseRunManager`],
-    [`langchain.schema.callbacks.manager`, `RunManager`, `langchain_core.callbacks`, `RunManager`],
-    [`langchain.schema.callbacks.manager`, `ParentRunManager`, `langchain_core.callbacks`, `ParentRunManager`],
-    [`langchain.schema.callbacks.manager`, `AsyncRunManager`, `langchain_core.callbacks`, `AsyncRunManager`],
-    [`langchain.schema.callbacks.manager`, `AsyncParentRunManager`, `langchain_core.callbacks`, `AsyncParentRunManager`],
-    [`langchain.schema.callbacks.manager`, `CallbackManagerForLLMRun`, `langchain_core.callbacks`, `CallbackManagerForLLMRun`],
-    [`langchain.schema.callbacks.manager`, `AsyncCallbackManagerForLLMRun`, `langchain_core.callbacks`, `AsyncCallbackManagerForLLMRun`],
-    [`langchain.schema.callbacks.manager`, `CallbackManagerForChainRun`, `langchain_core.callbacks`, `CallbackManagerForChainRun`],
-    [`langchain.schema.callbacks.manager`, `AsyncCallbackManagerForChainRun`, `langchain_core.callbacks`, `AsyncCallbackManagerForChainRun`],
-    [`langchain.schema.callbacks.manager`, `CallbackManagerForToolRun`, `langchain_core.callbacks`, `CallbackManagerForToolRun`],
-    [`langchain.schema.callbacks.manager`, `AsyncCallbackManagerForToolRun`, `langchain_core.callbacks`, `AsyncCallbackManagerForToolRun`],
-    [`langchain.schema.callbacks.manager`, `CallbackManagerForRetrieverRun`, `langchain_core.callbacks`, `CallbackManagerForRetrieverRun`],
-    [`langchain.schema.callbacks.manager`, `AsyncCallbackManagerForRetrieverRun`, `langchain_core.callbacks`, `AsyncCallbackManagerForRetrieverRun`],
-    [`langchain.schema.callbacks.manager`, `CallbackManager`, `langchain_core.callbacks`, `CallbackManager`],
-    [`langchain.schema.callbacks.manager`, `CallbackManagerForChainGroup`, `langchain_core.callbacks`, `CallbackManagerForChainGroup`],
-    [`langchain.schema.callbacks.manager`, `AsyncCallbackManager`, `langchain_core.callbacks`, `AsyncCallbackManager`],
-    [`langchain.schema.callbacks.manager`, `AsyncCallbackManagerForChainGroup`, `langchain_core.callbacks`, `AsyncCallbackManagerForChainGroup`],
-    [`langchain.schema.callbacks.manager`, `register_configure_hook`, `langchain_core.tracers.context`, `register_configure_hook`],
-    [`langchain.schema.callbacks.manager`, `env_var_is_set`, `langchain_core.utils.env`, `env_var_is_set`],
-    [`langchain.schema.callbacks.stdout`, `StdOutCallbackHandler`, `langchain_core.callbacks`, `StdOutCallbackHandler`],
-    [`langchain.schema.callbacks.streaming_stdout`, `StreamingStdOutCallbackHandler`, `langchain_core.callbacks`, `StreamingStdOutCallbackHandler`],
-    [`langchain.schema.callbacks.tracers.base`, `TracerException`, `langchain_core.exceptions`, `TracerException`],
-    [`langchain.schema.callbacks.tracers.base`, `BaseTracer`, `langchain_core.tracers`, `BaseTracer`],
-    [`langchain.schema.callbacks.tracers.evaluation`, `wait_for_all_evaluators`, `langchain_core.tracers.evaluation`, `wait_for_all_evaluators`],
-    [`langchain.schema.callbacks.tracers.evaluation`, `EvaluatorCallbackHandler`, `langchain_core.tracers`, `EvaluatorCallbackHandler`],
-    [`langchain.schema.callbacks.tracers.langchain`, `log_error_once`, `langchain_core.tracers.langchain`, `log_error_once`],
-    [`langchain.schema.callbacks.tracers.langchain`, `wait_for_all_tracers`, `langchain_core.tracers.langchain`, `wait_for_all_tracers`],
-    [`langchain.schema.callbacks.tracers.langchain`, `get_client`, `langchain_core.tracers.langchain`, `get_client`],
-    [`langchain.schema.callbacks.tracers.langchain`, `LangChainTracer`, `langchain_core.tracers`, `LangChainTracer`],
-    [`langchain.schema.callbacks.tracers.langchain_v1`, `get_headers`, `langchain_core.tracers.langchain_v1`, `get_headers`],
-    [`langchain.schema.callbacks.tracers.langchain_v1`, `LangChainTracerV1`, `langchain_core.tracers.langchain_v1`, `LangChainTracerV1`],
-    [`langchain.schema.callbacks.tracers.log_stream`, `LogEntry`, `langchain_core.tracers.log_stream`, `LogEntry`],
-    [`langchain.schema.callbacks.tracers.log_stream`, `RunState`, `langchain_core.tracers.log_stream`, `RunState`],
-    [`langchain.schema.callbacks.tracers.log_stream`, `RunLogPatch`, `langchain_core.tracers`, `RunLogPatch`],
-    [`langchain.schema.callbacks.tracers.log_stream`, `RunLog`, `langchain_core.tracers`, `RunLog`],
-    [`langchain.schema.callbacks.tracers.log_stream`, `LogStreamCallbackHandler`, `langchain_core.tracers`, `LogStreamCallbackHandler`],
-    [`langchain.schema.callbacks.tracers.root_listeners`, `RootListenersTracer`, `langchain_core.tracers.root_listeners`, `RootListenersTracer`],
-    [`langchain.schema.callbacks.tracers.run_collector`, `RunCollectorCallbackHandler`, `langchain_core.tracers.run_collector`, `RunCollectorCallbackHandler`],
-    [`langchain.schema.callbacks.tracers.schemas`, `RunTypeEnum`, `langchain_core.tracers.schemas`, `RunTypeEnum`],
-    [`langchain.schema.callbacks.tracers.schemas`, `TracerSessionV1Base`, `langchain_core.tracers.schemas`, `TracerSessionV1Base`],
-    [`langchain.schema.callbacks.tracers.schemas`, `TracerSessionV1Create`, `langchain_core.tracers.schemas`, `TracerSessionV1Create`],
-    [`langchain.schema.callbacks.tracers.schemas`, `TracerSessionV1`, `langchain_core.tracers.schemas`, `TracerSessionV1`],
-    [`langchain.schema.callbacks.tracers.schemas`, `TracerSessionBase`, `langchain_core.tracers.schemas`, `TracerSessionBase`],
-    [`langchain.schema.callbacks.tracers.schemas`, `TracerSession`, `langchain_core.tracers.schemas`, `TracerSession`],
-    [`langchain.schema.callbacks.tracers.schemas`, `BaseRun`, `langchain_core.tracers.schemas`, `BaseRun`],
-    [`langchain.schema.callbacks.tracers.schemas`, `LLMRun`, `langchain_core.tracers.schemas`, `LLMRun`],
-    [`langchain.schema.callbacks.tracers.schemas`, `ChainRun`, `langchain_core.tracers.schemas`, `ChainRun`],
-    [`langchain.schema.callbacks.tracers.schemas`, `ToolRun`, `langchain_core.tracers.schemas`, `ToolRun`],
-    [`langchain.schema.callbacks.tracers.schemas`, `Run`, `langchain_core.tracers`, `Run`],
-    [`langchain.schema.callbacks.tracers.stdout`, `try_json_stringify`, `langchain_core.tracers.stdout`, `try_json_stringify`],
-    [`langchain.schema.callbacks.tracers.stdout`, `elapsed`, `langchain_core.tracers.stdout`, `elapsed`],
-    [`langchain.schema.callbacks.tracers.stdout`, `FunctionCallbackHandler`, `langchain_core.tracers.stdout`, `FunctionCallbackHandler`],
-    [`langchain.schema.callbacks.tracers.stdout`, `ConsoleCallbackHandler`, `langchain_core.tracers`, `ConsoleCallbackHandler`],
-    [`langchain.schema.chat`, `ChatSession`, `langchain_core.chat_sessions`, `ChatSession`],
-    [`langchain.schema.chat_history`, `BaseChatMessageHistory`, `langchain_core.chat_history`, `BaseChatMessageHistory`],
-    [`langchain.schema.document`, `Document`, `langchain_core.documents`, `Document`],
-    [`langchain.schema.document`, `BaseDocumentTransformer`, `langchain_core.documents`, `BaseDocumentTransformer`],
-    [`langchain.schema.embeddings`, `Embeddings`, `langchain_core.embeddings`, `Embeddings`],
-    [`langchain.schema.exceptions`, `LangChainException`, `langchain_core.exceptions`, `LangChainException`],
-    [`langchain.schema.language_model`, `BaseLanguageModel`, `langchain_core.language_models`, `BaseLanguageModel`],
-    [`langchain.schema.language_model`, `_get_token_ids_default_method`, `langchain_core.language_models.base`, `_get_token_ids_default_method`],
-    [`langchain.schema.memory`, `BaseMemory`, `langchain_core.memory`, `BaseMemory`],
-    [`langchain.schema.messages`, `get_buffer_string`, `langchain_core.messages`, `get_buffer_string`],
-    [`langchain.schema.messages`, `BaseMessage`, `langchain_core.messages`, `BaseMessage`],
-    [`langchain.schema.messages`, `merge_content`, `langchain_core.messages`, `merge_content`],
-    [`langchain.schema.messages`, `BaseMessageChunk`, `langchain_core.messages`, `BaseMessageChunk`],
-    [`langchain.schema.messages`, `HumanMessage`, `langchain_core.messages`, `HumanMessage`],
-    [`langchain.schema.messages`, `HumanMessageChunk`, `langchain_core.messages`, `HumanMessageChunk`],
-    [`langchain.schema.messages`, `AIMessage`, `langchain_core.messages`, `AIMessage`],
-    [`langchain.schema.messages`, `AIMessageChunk`, `langchain_core.messages`, `AIMessageChunk`],
-    [`langchain.schema.messages`, `SystemMessage`, `langchain_core.messages`, `SystemMessage`],
-    [`langchain.schema.messages`, `SystemMessageChunk`, `langchain_core.messages`, `SystemMessageChunk`],
-    [`langchain.schema.messages`, `FunctionMessage`, `langchain_core.messages`, `FunctionMessage`],
-    [`langchain.schema.messages`, `FunctionMessageChunk`, `langchain_core.messages`, `FunctionMessageChunk`],
-    [`langchain.schema.messages`, `ToolMessage`, `langchain_core.messages`, `ToolMessage`],
-    [`langchain.schema.messages`, `ToolMessageChunk`, `langchain_core.messages`, `ToolMessageChunk`],
-    [`langchain.schema.messages`, `ChatMessage`, `langchain_core.messages`, `ChatMessage`],
-    [`langchain.schema.messages`, `ChatMessageChunk`, `langchain_core.messages`, `ChatMessageChunk`],
-    [`langchain.schema.messages`, `messages_to_dict`, `langchain_core.messages`, `messages_to_dict`],
-    [`langchain.schema.messages`, `messages_from_dict`, `langchain_core.messages`, `messages_from_dict`],
-    [`langchain.schema.messages`, `_message_to_dict`, `langchain_core.messages`, `message_to_dict`],
-    [`langchain.schema.messages`, `_message_from_dict`, `langchain_core.messages`, `_message_from_dict`],
-    [`langchain.schema.messages`, `message_to_dict`, `langchain_core.messages`, `message_to_dict`],
-    [`langchain.schema.output`, `Generation`, `langchain_core.outputs`, `Generation`],
-    [`langchain.schema.output`, `GenerationChunk`, `langchain_core.outputs`, `GenerationChunk`],
-    [`langchain.schema.output`, `ChatGeneration`, `langchain_core.outputs`, `ChatGeneration`],
-    [`langchain.schema.output`, `ChatGenerationChunk`, `langchain_core.outputs`, `ChatGenerationChunk`],
-    [`langchain.schema.output`, `RunInfo`, `langchain_core.outputs`, `RunInfo`],
-    [`langchain.schema.output`, `ChatResult`, `langchain_core.outputs`, `ChatResult`],
-    [`langchain.schema.output`, `LLMResult`, `langchain_core.outputs`, `LLMResult`],
-    [`langchain.schema.output_parser`, `BaseLLMOutputParser`, `langchain_core.output_parsers`, `BaseLLMOutputParser`],
-    [`langchain.schema.output_parser`, `BaseGenerationOutputParser`, `langchain_core.output_parsers`, `BaseGenerationOutputParser`],
-    [`langchain.schema.output_parser`, `BaseOutputParser`, `langchain_core.output_parsers`, `BaseOutputParser`],
-    [`langchain.schema.output_parser`, `BaseTransformOutputParser`, `langchain_core.output_parsers`, `BaseTransformOutputParser`],
-    [`langchain.schema.output_parser`, `BaseCumulativeTransformOutputParser`, `langchain_core.output_parsers`, `BaseCumulativeTransformOutputParser`],
-    [`langchain.schema.output_parser`, `NoOpOutputParser`, `langchain_core.output_parsers`, `StrOutputParser`],
-    [`langchain.schema.output_parser`, `StrOutputParser`, `langchain_core.output_parsers`, `StrOutputParser`],
-    [`langchain.schema.output_parser`, `OutputParserException`, `langchain_core.exceptions`, `OutputParserException`],
-    [`langchain.schema.prompt`, `PromptValue`, `langchain_core.prompt_values`, `PromptValue`],
-    [`langchain.schema.prompt_template`, `BasePromptTemplate`, `langchain_core.prompts`, `BasePromptTemplate`],
-    [`langchain.schema.prompt_template`, `format_document`, `langchain_core.prompts`, `format_document`],
-    [`langchain.schema.retriever`, `BaseRetriever`, `langchain_core.retrievers`, `BaseRetriever`],
-    [`langchain.schema.runnable`, `ConfigurableField`, `langchain_core.runnables`, `ConfigurableField`],
-    [`langchain.schema.runnable`, `ConfigurableFieldSingleOption`, `langchain_core.runnables`, `ConfigurableFieldSingleOption`],
-    [`langchain.schema.runnable`, `ConfigurableFieldMultiOption`, `langchain_core.runnables`, `ConfigurableFieldMultiOption`],
-    [`langchain.schema.runnable`, `patch_config`, `langchain_core.runnables`, `patch_config`],
-    [`langchain.schema.runnable`, `RouterInput`, `langchain_core.runnables`, `RouterInput`],
-    [`langchain.schema.runnable`, `RouterRunnable`, `langchain_core.runnables`, `RouterRunnable`],
-    [`langchain.schema.runnable`, `Runnable`, `langchain_core.runnables`, `Runnable`],
-    [`langchain.schema.runnable`, `RunnableSerializable`, `langchain_core.runnables`, `RunnableSerializable`],
-    [`langchain.schema.runnable`, `RunnableBinding`, `langchain_core.runnables`, `RunnableBinding`],
-    [`langchain.schema.runnable`, `RunnableBranch`, `langchain_core.runnables`, `RunnableBranch`],
-    [`langchain.schema.runnable`, `RunnableConfig`, `langchain_core.runnables`, `RunnableConfig`],
-    [`langchain.schema.runnable`, `RunnableGenerator`, `langchain_core.runnables`, `RunnableGenerator`],
-    [`langchain.schema.runnable`, `RunnableLambda`, `langchain_core.runnables`, `RunnableLambda`],
-    [`langchain.schema.runnable`, `RunnableMap`, `langchain_core.runnables`, `RunnableMap`],
-    [`langchain.schema.runnable`, `RunnableParallel`, `langchain_core.runnables`, `RunnableParallel`],
-    [`langchain.schema.runnable`, `RunnablePassthrough`, `langchain_core.runnables`, `RunnablePassthrough`],
-    [`langchain.schema.runnable`, `RunnableSequence`, `langchain_core.runnables`, `RunnableSequence`],
-    [`langchain.schema.runnable`, `RunnableWithFallbacks`, `langchain_core.runnables`, `RunnableWithFallbacks`],
-    [`langchain.schema.runnable.base`, `Runnable`, `langchain_core.runnables`, `Runnable`],
-    [`langchain.schema.runnable.base`, `RunnableSerializable`, `langchain_core.runnables`, `RunnableSerializable`],
-    [`langchain.schema.runnable.base`, `RunnableSequence`, `langchain_core.runnables`, `RunnableSequence`],
-    [`langchain.schema.runnable.base`, `RunnableParallel`, `langchain_core.runnables`, `RunnableParallel`],
-    [`langchain.schema.runnable.base`, `RunnableGenerator`, `langchain_core.runnables`, `RunnableGenerator`],
-    [`langchain.schema.runnable.base`, `RunnableLambda`, `langchain_core.runnables`, `RunnableLambda`],
-    [`langchain.schema.runnable.base`, `RunnableEachBase`, `langchain_core.runnables.base`, `RunnableEachBase`],
-    [`langchain.schema.runnable.base`, `RunnableEach`, `langchain_core.runnables.base`, `RunnableEach`],
-    [`langchain.schema.runnable.base`, `RunnableBindingBase`, `langchain_core.runnables.base`, `RunnableBindingBase`],
-    [`langchain.schema.runnable.base`, `RunnableBinding`, `langchain_core.runnables`, `RunnableBinding`],
-    [`langchain.schema.runnable.base`, `RunnableMap`, `langchain_core.runnables`, `RunnableMap`],
-    [`langchain.schema.runnable.base`, `coerce_to_runnable`, `langchain_core.runnables.base`, `coerce_to_runnable`],
-    [`langchain.schema.runnable.branch`, `RunnableBranch`, `langchain_core.runnables`, `RunnableBranch`],
-    [`langchain.schema.runnable.config`, `EmptyDict`, `langchain_core.runnables.config`, `EmptyDict`],
-    [`langchain.schema.runnable.config`, `RunnableConfig`, `langchain_core.runnables`, `RunnableConfig`],
-    [`langchain.schema.runnable.config`, `ensure_config`, `langchain_core.runnables`, `ensure_config`],
-    [`langchain.schema.runnable.config`, `get_config_list`, `langchain_core.runnables`, `get_config_list`],
-    [`langchain.schema.runnable.config`, `patch_config`, `langchain_core.runnables`, `patch_config`],
-    [`langchain.schema.runnable.config`, `merge_configs`, `langchain_core.runnables.config`, `merge_configs`],
-    [`langchain.schema.runnable.config`, `acall_func_with_variable_args`, `langchain_core.runnables.config`, `acall_func_with_variable_args`],
-    [`langchain.schema.runnable.config`, `call_func_with_variable_args`, `langchain_core.runnables.config`, `call_func_with_variable_args`],
-    [`langchain.schema.runnable.config`, `get_callback_manager_for_config`, `langchain_core.runnables.config`, `get_callback_manager_for_config`],
-    [`langchain.schema.runnable.config`, `get_async_callback_manager_for_config`, `langchain_core.runnables.config`, `get_async_callback_manager_for_config`],
-    [`langchain.schema.runnable.config`, `get_executor_for_config`, `langchain_core.runnables.config`, `get_executor_for_config`],
-    [`langchain.schema.runnable.configurable`, `DynamicRunnable`, `langchain_core.runnables.configurable`, `DynamicRunnable`],
-    [`langchain.schema.runnable.configurable`, `RunnableConfigurableFields`, `langchain_core.runnables.configurable`, `RunnableConfigurableFields`],
-    [`langchain.schema.runnable.configurable`, `StrEnum`, `langchain_core.runnables.configurable`, `StrEnum`],
-    [`langchain.schema.runnable.configurable`, `RunnableConfigurableAlternatives`, `langchain_core.runnables.configurable`, `RunnableConfigurableAlternatives`],
-    [`langchain.schema.runnable.configurable`, `make_options_spec`, `langchain_core.runnables.configurable`, `make_options_spec`],
-    [`langchain.schema.runnable.fallbacks`, `RunnableWithFallbacks`, `langchain_core.runnables`, `RunnableWithFallbacks`],
-    [`langchain.schema.runnable.history`, `RunnableWithMessageHistory`, `langchain_core.runnables.history`, `RunnableWithMessageHistory`],
-    [`langchain.schema.runnable.passthrough`, `aidentity`, `langchain_core.runnables.passthrough`, `aidentity`],
-    [`langchain.schema.runnable.passthrough`, `identity`, `langchain_core.runnables.passthrough`, `identity`],
-    [`langchain.schema.runnable.passthrough`, `RunnablePassthrough`, `langchain_core.runnables`, `RunnablePassthrough`],
-    [`langchain.schema.runnable.passthrough`, `RunnableAssign`, `langchain_core.runnables`, `RunnableAssign`],
-    [`langchain.schema.runnable.retry`, `RunnableRetry`, `langchain_core.runnables.retry`, `RunnableRetry`],
-    [`langchain.schema.runnable.router`, `RouterInput`, `langchain_core.runnables`, `RouterInput`],
-    [`langchain.schema.runnable.router`, `RouterRunnable`, `langchain_core.runnables`, `RouterRunnable`],
-    [`langchain.schema.runnable.utils`, `accepts_run_manager`, `langchain_core.runnables.utils`, `accepts_run_manager`],
-    [`langchain.schema.runnable.utils`, `accepts_config`, `langchain_core.runnables.utils`, `accepts_config`],
-    [`langchain.schema.runnable.utils`, `IsLocalDict`, `langchain_core.runnables.utils`, `IsLocalDict`],
-    [`langchain.schema.runnable.utils`, `IsFunctionArgDict`, `langchain_core.runnables.utils`, `IsFunctionArgDict`],
-    [`langchain.schema.runnable.utils`, `GetLambdaSource`, `langchain_core.runnables.utils`, `GetLambdaSource`],
-    [`langchain.schema.runnable.utils`, `get_function_first_arg_dict_keys`, `langchain_core.runnables.utils`, `get_function_first_arg_dict_keys`],
-    [`langchain.schema.runnable.utils`, `get_lambda_source`, `langchain_core.runnables.utils`, `get_lambda_source`],
-    [`langchain.schema.runnable.utils`, `indent_lines_after_first`, `langchain_core.runnables.utils`, `indent_lines_after_first`],
-    [`langchain.schema.runnable.utils`, `AddableDict`, `langchain_core.runnables`, `AddableDict`],
-    [`langchain.schema.runnable.utils`, `SupportsAdd`, `langchain_core.runnables.utils`, `SupportsAdd`],
-    [`langchain.schema.runnable.utils`, `add`, `langchain_core.runnables`, `add`],
-    [`langchain.schema.runnable.utils`, `ConfigurableField`, `langchain_core.runnables`, `ConfigurableField`],
-    [`langchain.schema.runnable.utils`, `ConfigurableFieldSingleOption`, `langchain_core.runnables`, `ConfigurableFieldSingleOption`],
-    [`langchain.schema.runnable.utils`, `ConfigurableFieldMultiOption`, `langchain_core.runnables`, `ConfigurableFieldMultiOption`],
-    [`langchain.schema.runnable.utils`, `ConfigurableFieldSpec`, `langchain_core.runnables`, `ConfigurableFieldSpec`],
-    [`langchain.schema.runnable.utils`, `get_unique_config_specs`, `langchain_core.runnables.utils`, `get_unique_config_specs`],
-    [`langchain.schema.runnable.utils`, `aadd`, `langchain_core.runnables`, `aadd`],
-    [`langchain.schema.runnable.utils`, `gated_coro`, `langchain_core.runnables.utils`, `gated_coro`],
-    [`langchain.schema.runnable.utils`, `gather_with_concurrency`, `langchain_core.runnables.utils`, `gather_with_concurrency`],
-    [`langchain.schema.storage`, `BaseStore`, `langchain_core.stores`, `BaseStore`],
-    [`langchain.schema.vectorstore`, `VectorStore`, `langchain_core.vectorstores`, `VectorStore`],
-    [`langchain.schema.vectorstore`, `VectorStoreRetriever`, `langchain_core.vectorstores`, `VectorStoreRetriever`],
-    [`langchain.tools`, `BaseTool`, `langchain_core.tools`, `BaseTool`],
-    [`langchain.tools`, `StructuredTool`, `langchain_core.tools`, `StructuredTool`],
-    [`langchain.tools`, `Tool`, `langchain_core.tools`, `Tool`],
-    [`langchain.tools`, `format_tool_to_openai_function`, `langchain_core.utils.function_calling`, `format_tool_to_openai_function`],
-    [`langchain.tools`, `tool`, `langchain_core.tools`, `tool`],
-    [`langchain.tools.base`, `SchemaAnnotationError`, `langchain_core.tools`, `SchemaAnnotationError`],
-    [`langchain.tools.base`, `create_schema_from_function`, `langchain_core.tools`, `create_schema_from_function`],
-    [`langchain.tools.base`, `ToolException`, `langchain_core.tools`, `ToolException`],
-    [`langchain.tools.base`, `BaseTool`, `langchain_core.tools`, `BaseTool`],
-    [`langchain.tools.base`, `Tool`, `langchain_core.tools`, `Tool`],
-    [`langchain.tools.base`, `StructuredTool`, `langchain_core.tools`, `StructuredTool`],
-    [`langchain.tools.base`, `tool`, `langchain_core.tools`, `tool`],
-    [`langchain.tools.convert_to_openai`, `format_tool_to_openai_function`, `langchain_core.utils.function_calling`, `format_tool_to_openai_function`],
-    [`langchain.tools.render`, `format_tool_to_openai_tool`, `langchain_core.utils.function_calling`, `format_tool_to_openai_tool`],
-    [`langchain.tools.render`, `format_tool_to_openai_function`, `langchain_core.utils.function_calling`, `format_tool_to_openai_function`],
-    [`langchain.utilities.loading`, `try_load_from_hub`, `langchain_core.utils`, `try_load_from_hub`],
-    [`langchain.utils`, `StrictFormatter`, `langchain_core.utils`, `StrictFormatter`],
-    [`langchain.utils`, `check_package_version`, `langchain_core.utils`, `check_package_version`],
-    [`langchain.utils`, `comma_list`, `langchain_core.utils`, `comma_list`],
-    [`langchain.utils`, `convert_to_secret_str`, `langchain_core.utils`, `convert_to_secret_str`],
-    [`langchain.utils`, `get_bolded_text`, `langchain_core.utils`, `get_bolded_text`],
-    [`langchain.utils`, `get_color_mapping`, `langchain_core.utils`, `get_color_mapping`],
-    [`langchain.utils`, `get_colored_text`, `langchain_core.utils`, `get_colored_text`],
-    [`langchain.utils`, `get_from_dict_or_env`, `langchain_core.utils`, `get_from_dict_or_env`],
-    [`langchain.utils`, `get_from_env`, `langchain_core.utils`, `get_from_env`],
-    [`langchain.utils`, `get_pydantic_field_names`, `langchain_core.utils`, `get_pydantic_field_names`],
-    [`langchain.utils`, `guard_import`, `langchain_core.utils`, `guard_import`],
-    [`langchain.utils`, `mock_now`, `langchain_core.utils`, `mock_now`],
-    [`langchain.utils`, `print_text`, `langchain_core.utils`, `print_text`],
-    [`langchain.utils`, `raise_for_status_with_text`, `langchain_core.utils`, `raise_for_status_with_text`],
-    [`langchain.utils`, `stringify_dict`, `langchain_core.utils`, `stringify_dict`],
-    [`langchain.utils`, `stringify_value`, `langchain_core.utils`, `stringify_value`],
-    [`langchain.utils`, `xor_args`, `langchain_core.utils`, `xor_args`],
-    [`langchain.utils.aiter`, `py_anext`, `langchain_core.utils.aiter`, `py_anext`],
-    [`langchain.utils.aiter`, `NoLock`, `langchain_core.utils.aiter`, `NoLock`],
-    [`langchain.utils.aiter`, `Tee`, `langchain_core.utils.aiter`, `Tee`],
-    [`langchain.utils.env`, `get_from_dict_or_env`, `langchain_core.utils`, `get_from_dict_or_env`],
-    [`langchain.utils.env`, `get_from_env`, `langchain_core.utils`, `get_from_env`],
-    [`langchain.utils.formatting`, `StrictFormatter`, `langchain_core.utils`, `StrictFormatter`],
-    [`langchain.utils.html`, `find_all_links`, `langchain_core.utils.html`, `find_all_links`],
-    [`langchain.utils.html`, `extract_sub_links`, `langchain_core.utils.html`, `extract_sub_links`],
-    [`langchain.utils.input`, `get_color_mapping`, `langchain_core.utils`, `get_color_mapping`],
-    [`langchain.utils.input`, `get_colored_text`, `langchain_core.utils`, `get_colored_text`],
-    [`langchain.utils.input`, `get_bolded_text`, `langchain_core.utils`, `get_bolded_text`],
-    [`langchain.utils.input`, `print_text`, `langchain_core.utils`, `print_text`],
-    [`langchain.utils.iter`, `NoLock`, `langchain_core.utils.iter`, `NoLock`],
-    [`langchain.utils.iter`, `tee_peer`, `langchain_core.utils.iter`, `tee_peer`],
-    [`langchain.utils.iter`, `Tee`, `langchain_core.utils.iter`, `Tee`],
-    [`langchain.utils.iter`, `batch_iterate`, `langchain_core.utils.iter`, `batch_iterate`],
-    [`langchain.utils.json_schema`, `_retrieve_ref`, `langchain_core.utils.json_schema`, `_retrieve_ref`],
-    [`langchain.utils.json_schema`, `_dereference_refs_helper`, `langchain_core.utils.json_schema`, `_dereference_refs_helper`],
-    [`langchain.utils.json_schema`, `_infer_skip_keys`, `langchain_core.utils.json_schema`, `_infer_skip_keys`],
-    [`langchain.utils.json_schema`, `dereference_refs`, `langchain_core.utils.json_schema`, `dereference_refs`],
-    [`langchain.utils.loading`, `try_load_from_hub`, `langchain_core.utils`, `try_load_from_hub`],
-    [`langchain.utils.openai_functions`, `FunctionDescription`, `langchain_core.utils.function_calling`, `FunctionDescription`],
-    [`langchain.utils.openai_functions`, `ToolDescription`, `langchain_core.utils.function_calling`, `ToolDescription`],
-    [`langchain.utils.openai_functions`, `convert_pydantic_to_openai_function`, `langchain_core.utils.function_calling`, `convert_pydantic_to_openai_function`],
-    [`langchain.utils.openai_functions`, `convert_pydantic_to_openai_tool`, `langchain_core.utils.function_calling`, `convert_pydantic_to_openai_tool`],
-    [`langchain.utils.pydantic`, `get_pydantic_major_version`, `langchain_core.utils.pydantic`, `get_pydantic_major_version`],
-    [`langchain.utils.strings`, `stringify_value`, `langchain_core.utils`, `stringify_value`],
-    [`langchain.utils.strings`, `stringify_dict`, `langchain_core.utils`, `stringify_dict`],
-    [`langchain.utils.strings`, `comma_list`, `langchain_core.utils`, `comma_list`],
-    [`langchain.utils.utils`, `xor_args`, `langchain_core.utils`, `xor_args`],
-    [`langchain.utils.utils`, `raise_for_status_with_text`, `langchain_core.utils`, `raise_for_status_with_text`],
-    [`langchain.utils.utils`, `mock_now`, `langchain_core.utils`, `mock_now`],
-    [`langchain.utils.utils`, `guard_import`, `langchain_core.utils`, `guard_import`],
-    [`langchain.utils.utils`, `check_package_version`, `langchain_core.utils`, `check_package_version`],
-    [`langchain.utils.utils`, `get_pydantic_field_names`, `langchain_core.utils`, `get_pydantic_field_names`],
-    [`langchain.utils.utils`, `build_extra_kwargs`, `langchain_core.utils`, `build_extra_kwargs`],
-    [`langchain.utils.utils`, `convert_to_secret_str`, `langchain_core.utils`, `convert_to_secret_str`],
-    [`langchain.vectorstores`, `VectorStore`, `langchain_core.vectorstores`, `VectorStore`],
-    [`langchain.vectorstores.base`, `VectorStore`, `langchain_core.vectorstores`, `VectorStore`],
-    [`langchain.vectorstores.base`, `VectorStoreRetriever`, `langchain_core.vectorstores`, `VectorStoreRetriever`],
-    [`langchain.vectorstores.singlestoredb`, `SingleStoreDBRetriever`, `langchain_core.vectorstores`, `VectorStoreRetriever`]
-  ])
-}
-
-// Add this for invoking directly
-langchain_migrate_langchain_to_core()

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

@@ -1,31 +0,0 @@
-
-language python
-
-// This migration is generated automatically - do not manually edit this file
-pattern langchain_migrate_langchain_to_textsplitters() {
-  find_replace_imports(list=[
-    [`langchain.text_splitter`, `TokenTextSplitter`, `langchain_text_splitters`, `TokenTextSplitter`],
-    [`langchain.text_splitter`, `TextSplitter`, `langchain_text_splitters`, `TextSplitter`],
-    [`langchain.text_splitter`, `Tokenizer`, `langchain_text_splitters`, `Tokenizer`],
-    [`langchain.text_splitter`, `Language`, `langchain_text_splitters`, `Language`],
-    [`langchain.text_splitter`, `RecursiveCharacterTextSplitter`, `langchain_text_splitters`, `RecursiveCharacterTextSplitter`],
-    [`langchain.text_splitter`, `RecursiveJsonSplitter`, `langchain_text_splitters`, `RecursiveJsonSplitter`],
-    [`langchain.text_splitter`, `LatexTextSplitter`, `langchain_text_splitters`, `LatexTextSplitter`],
-    [`langchain.text_splitter`, `PythonCodeTextSplitter`, `langchain_text_splitters`, `PythonCodeTextSplitter`],
-    [`langchain.text_splitter`, `KonlpyTextSplitter`, `langchain_text_splitters`, `KonlpyTextSplitter`],
-    [`langchain.text_splitter`, `SpacyTextSplitter`, `langchain_text_splitters`, `SpacyTextSplitter`],
-    [`langchain.text_splitter`, `NLTKTextSplitter`, `langchain_text_splitters`, `NLTKTextSplitter`],
-    [`langchain.text_splitter`, `split_text_on_tokens`, `langchain_text_splitters`, `split_text_on_tokens`],
-    [`langchain.text_splitter`, `SentenceTransformersTokenTextSplitter`, `langchain_text_splitters`, `SentenceTransformersTokenTextSplitter`],
-    [`langchain.text_splitter`, `ElementType`, `langchain_text_splitters`, `ElementType`],
-    [`langchain.text_splitter`, `HeaderType`, `langchain_text_splitters`, `HeaderType`],
-    [`langchain.text_splitter`, `LineType`, `langchain_text_splitters`, `LineType`],
-    [`langchain.text_splitter`, `HTMLHeaderTextSplitter`, `langchain_text_splitters`, `HTMLHeaderTextSplitter`],
-    [`langchain.text_splitter`, `MarkdownHeaderTextSplitter`, `langchain_text_splitters`, `MarkdownHeaderTextSplitter`],
-    [`langchain.text_splitter`, `MarkdownTextSplitter`, `langchain_text_splitters`, `MarkdownTextSplitter`],
-    [`langchain.text_splitter`, `CharacterTextSplitter`, `langchain_text_splitters`, `CharacterTextSplitter`]
-  ])
-}
-
-// Add this for invoking directly
-langchain_migrate_langchain_to_textsplitters()

libs/cli/langchain_cli/namespaces/migrate/.grit/patterns/langchain_to_textsplitters.json

@@ -1,70 +0,0 @@
-[
-  [
-    "langchain.text_splitter.TokenTextSplitter",
-    "langchain_text_splitters.TokenTextSplitter"
-  ],
-  [
-    "langchain.text_splitter.TextSplitter",
-    "langchain_text_splitters.TextSplitter"
-  ],
-  ["langchain.text_splitter.Tokenizer", "langchain_text_splitters.Tokenizer"],
-  ["langchain.text_splitter.Language", "langchain_text_splitters.Language"],
-  [
-    "langchain.text_splitter.RecursiveCharacterTextSplitter",
-    "langchain_text_splitters.RecursiveCharacterTextSplitter"
-  ],
-  [
-    "langchain.text_splitter.RecursiveJsonSplitter",
-    "langchain_text_splitters.RecursiveJsonSplitter"
-  ],
-  [
-    "langchain.text_splitter.LatexTextSplitter",
-    "langchain_text_splitters.LatexTextSplitter"
-  ],
-  [
-    "langchain.text_splitter.PythonCodeTextSplitter",
-    "langchain_text_splitters.PythonCodeTextSplitter"
-  ],
-  [
-    "langchain.text_splitter.KonlpyTextSplitter",
-    "langchain_text_splitters.KonlpyTextSplitter"
-  ],
-  [
-    "langchain.text_splitter.SpacyTextSplitter",
-    "langchain_text_splitters.SpacyTextSplitter"
-  ],
-  [
-    "langchain.text_splitter.NLTKTextSplitter",
-    "langchain_text_splitters.NLTKTextSplitter"
-  ],
-  [
-    "langchain.text_splitter.split_text_on_tokens",
-    "langchain_text_splitters.split_text_on_tokens"
-  ],
-  [
-    "langchain.text_splitter.SentenceTransformersTokenTextSplitter",
-    "langchain_text_splitters.SentenceTransformersTokenTextSplitter"
-  ],
-  [
-    "langchain.text_splitter.ElementType",
-    "langchain_text_splitters.ElementType"
-  ],
-  ["langchain.text_splitter.HeaderType", "langchain_text_splitters.HeaderType"],
-  ["langchain.text_splitter.LineType", "langchain_text_splitters.LineType"],
-  [
-    "langchain.text_splitter.HTMLHeaderTextSplitter",
-    "langchain_text_splitters.HTMLHeaderTextSplitter"
-  ],
-  [
-    "langchain.text_splitter.MarkdownHeaderTextSplitter",
-    "langchain_text_splitters.MarkdownHeaderTextSplitter"
-  ],
-  [
-    "langchain.text_splitter.MarkdownTextSplitter",
-    "langchain_text_splitters.MarkdownTextSplitter"
-  ],
-  [
-    "langchain.text_splitter.CharacterTextSplitter",
-    "langchain_text_splitters.CharacterTextSplitter"
-  ]
-]

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

@@ -1,23 +0,0 @@
-
-language python
-
-// This migration is generated automatically - do not manually edit this file
-pattern langchain_migrate_openai() {
-  find_replace_imports(list=[
-    [`langchain_community.embeddings.openai`, `OpenAIEmbeddings`, `langchain_openai`, `OpenAIEmbeddings`],
-    [`langchain_community.embeddings.azure_openai`, `AzureOpenAIEmbeddings`, `langchain_openai`, `AzureOpenAIEmbeddings`],
-    [`langchain_community.chat_models.openai`, `ChatOpenAI`, `langchain_openai`, `ChatOpenAI`],
-    [`langchain_community.chat_models.azure_openai`, `AzureChatOpenAI`, `langchain_openai`, `AzureChatOpenAI`],
-    [`langchain_community.llms.openai`, `OpenAI`, `langchain_openai`, `OpenAI`],
-    [`langchain_community.llms.openai`, `AzureOpenAI`, `langchain_openai`, `AzureOpenAI`],
-    [`langchain_community.embeddings`, `AzureOpenAIEmbeddings`, `langchain_openai`, `AzureOpenAIEmbeddings`],
-    [`langchain_community.embeddings`, `OpenAIEmbeddings`, `langchain_openai`, `OpenAIEmbeddings`],
-    [`langchain_community.chat_models`, `AzureChatOpenAI`, `langchain_openai`, `AzureChatOpenAI`],
-    [`langchain_community.chat_models`, `ChatOpenAI`, `langchain_openai`, `ChatOpenAI`],
-    [`langchain_community.llms`, `AzureOpenAI`, `langchain_openai`, `AzureOpenAI`],
-    [`langchain_community.llms`, `OpenAI`, `langchain_openai`, `OpenAI`]
-  ])
-}
-
-// Add this for invoking directly
-langchain_migrate_openai()

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

@@ -1,13 +0,0 @@
-
-language python
-
-// This migration is generated automatically - do not manually edit this file
-pattern langchain_migrate_pinecone() {
-  find_replace_imports(list=[
-    [`langchain_community.vectorstores.pinecone`, `Pinecone`, `langchain_pinecone`, `Pinecone`],
-    [`langchain_community.vectorstores`, `Pinecone`, `langchain_pinecone`, `Pinecone`]
-  ])
-}
-
-// Add this for invoking directly
-langchain_migrate_pinecone()

libs/cli/langchain_cli/namespaces/migrate/.grit/patterns/replace_pydantic_v1_shim.grit

@@ -1,36 +0,0 @@
-language python
-
-// This migration is generated automatically - do not manually edit this file
-pattern replace_pydantic_v1_shim() {
-    `from $IMPORT import $...` where {
-        or {
-            and {
-                $IMPORT <: or {
-                    "langchain_core.pydantic_v1",
-                    "langchain.pydantic_v1",
-                    "langserve.pydantic_v1",
-                },
-                $IMPORT => `pydantic`
-            },
-            and {
-                $IMPORT <: or {
-                    "langchain_core.pydantic_v1.data_classes",
-                    "langchain.pydantic_v1.data_classes",
-                    "langserve.pydantic_v1.data_classes",
-                },
-                $IMPORT => `pydantic.data_classes`
-            },
-            and {
-                $IMPORT <: or {
-                    "langchain_core.pydantic_v1.main",
-                    "langchain.pydantic_v1.main",
-                    "langserve.pydantic_v1.main",
-                },
-                $IMPORT => `pydantic.main`
-            },
-        }
-    }
-}
-
-// Add this for invoking directly
- replace_pydantic_v1_shim()

libs/cli/langchain_cli/namespaces/migrate/__init__.py

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

libs/cli/langchain_cli/namespaces/migrate/generate/__init__.py

@@ -1 +0,0 @@
-"""Generate migrations."""

libs/cli/langchain_cli/namespaces/migrate/generate/generic.py

@@ -1,182 +0,0 @@
-"""Generate migrations from langchain to langchain-community or core packages."""
-
-import importlib
-import inspect
-import pkgutil
-from types import ModuleType
-
-
-def generate_raw_migrations(
-    from_package: str,
-    to_package: str,
-    filter_by_all: bool = False,  # noqa: FBT001, FBT002
-) -> list[tuple[str, str]]:
-    """Scan the `langchain` package and generate migrations for all modules.
-
-    Args:
-        from_package: The package to migrate from.
-        to_package: The package to migrate to.
-        filter_by_all: Whether to only consider items in `__all__`.
-
-    Returns:
-        A list of tuples containing the original import path and the new import path.
-    """
-    package = importlib.import_module(from_package)
-
-    items = []
-    for _importer, modname, _ispkg in pkgutil.walk_packages(
-        package.__path__,
-        package.__name__ + ".",
-    ):
-        try:
-            module = importlib.import_module(modname)
-        except ModuleNotFoundError:
-            continue
-
-        # Check if the module is an __init__ file and evaluate __all__
-        try:
-            has_all = hasattr(module, "__all__")
-        except ImportError:
-            has_all = False
-
-        if has_all:
-            all_objects = module.__all__
-            for name in all_objects:
-                # Attempt to fetch each object declared in __all__
-                try:
-                    obj = getattr(module, name, None)
-                except ImportError:
-                    continue
-                if (
-                    obj
-                    and (inspect.isclass(obj) or inspect.isfunction(obj))
-                    and obj.__module__.startswith(to_package)
-                ):
-                    items.append(
-                        (f"{modname}.{name}", f"{obj.__module__}.{obj.__name__}"),
-                    )
-
-        if not filter_by_all:
-            # Iterate over all members of the module
-            for name, obj in inspect.getmembers(module):
-                # Check if it's a class or function
-                # Check if the module name of the obj starts with
-                # 'langchain_community'
-                if inspect.isclass(obj) or (
-                    inspect.isfunction(obj) and obj.__module__.startswith(to_package)
-                ):
-                    items.append(
-                        (f"{modname}.{name}", f"{obj.__module__}.{obj.__name__}"),
-                    )
-
-    return items
-
-
-def generate_top_level_imports(pkg: str) -> list[tuple[str, str]]:
-    """Look at all the top level modules in langchain_community.
-
-    Attempt to import everything from each `__init__` file. For example,
-
-    langchain_community/
-        chat_models/
-            __init__.py # <-- import everything from here
-        llm/
-            __init__.py # <-- import everything from here
-
-    It'll collect all the imports, import the classes / functions it can find
-    there. It'll return a list of 2-tuples
-
-    Each tuple will contain the fully qualified path of the class / function to where
-    its logic is defined.
-    (e.g., `langchain_community.chat_models.xyz_implementation.ver2.XYZ`)
-    and the second tuple will contain the path
-    to importing it from the top level namespaces
-    (e.g., `langchain_community.chat_models.XYZ`)
-
-    Args:
-        pkg: The package to scan.
-
-    Returns:
-        A list of tuples containing the fully qualified path and the top-level
-        import path.
-    """
-    package = importlib.import_module(pkg)
-
-    items = []
-
-    # Function to handle importing from modules
-    def handle_module(module: ModuleType, module_name: str) -> None:
-        if hasattr(module, "__all__"):
-            all_objects = module.__all__
-            for name in all_objects:
-                # Attempt to fetch each object declared in __all__
-                obj = getattr(module, name, None)
-                if obj and (inspect.isclass(obj) or inspect.isfunction(obj)):
-                    # Capture the fully qualified name of the object
-                    original_module = obj.__module__
-                    original_name = obj.__name__
-                    # Form the new import path from the top-level namespace
-                    top_level_import = f"{module_name}.{name}"
-                    # Append the tuple with original and top-level paths
-                    items.append(
-                        (f"{original_module}.{original_name}", top_level_import),
-                    )
-
-    # Handle the package itself (root level)
-    handle_module(package, pkg)
-
-    # Only iterate through top-level modules/packages
-    for _finder, modname, ispkg in pkgutil.iter_modules(
-        package.__path__,
-        package.__name__ + ".",
-    ):
-        if ispkg:
-            try:
-                module = importlib.import_module(modname)
-                handle_module(module, modname)
-            except ModuleNotFoundError:
-                continue
-
-    return items
-
-
-def generate_simplified_migrations(
-    from_package: str,
-    to_package: str,
-    filter_by_all: bool = True,  # noqa: FBT001, FBT002
-) -> list[tuple[str, str]]:
-    """Get all the raw migrations, then simplify them if possible.
-
-    Args:
-        from_package: The package to migrate from.
-        to_package: The package to migrate to.
-        filter_by_all: Whether to only consider items in `__all__`.
-
-    Returns:
-        A list of tuples containing the original import path and the simplified
-        import path.
-    """
-    raw_migrations = generate_raw_migrations(
-        from_package,
-        to_package,
-        filter_by_all=filter_by_all,
-    )
-    top_level_simplifications = generate_top_level_imports(to_package)
-    top_level_dict = dict(top_level_simplifications)
-    simple_migrations = []
-    for migration in raw_migrations:
-        original, new = migration
-        replacement = top_level_dict.get(new, new)
-        simple_migrations.append((original, replacement))
-
-    # Now let's deduplicate the list based on the original path (which is
-    # the 1st element of the tuple)
-    deduped_migrations = []
-    seen = set()
-    for migration in simple_migrations:
-        original = migration[0]
-        if original not in seen:
-            deduped_migrations.append(migration)
-            seen.add(original)
-
-    return deduped_migrations

libs/cli/langchain_cli/namespaces/migrate/generate/grit.py

@@ -1,53 +0,0 @@
-"""Migration as Grit file."""
-
-
-def split_package(package: str) -> tuple[str, str]:
-    """Split a package name into the containing package and the final name.
-
-    Args:
-        package: The full package name.
-
-    Returns:
-        A tuple of `(containing_package, final_name)`.
-    """
-    parts = package.split(".")
-    return ".".join(parts[:-1]), parts[-1]
-
-
-def dump_migrations_as_grit(name: str, migration_pairs: list[tuple[str, str]]) -> str:
-    """Dump the migration pairs as a Grit file.
-
-    Args:
-        name: The name of the migration.
-        migration_pairs: A list of tuples `(from_module, to_module)`.
-
-    Returns:
-        The Grit file as a string.
-    """
-    remapped = ",\n".join(
-        [
-            f"""
-            [
-                `{split_package(from_module)[0]}`,
-                `{split_package(from_module)[1]}`,
-                `{split_package(to_module)[0]}`,
-                `{split_package(to_module)[1]}`
-            ]
-            """
-            for from_module, to_module in migration_pairs
-        ],
-    )
-    pattern_name = f"langchain_migrate_{name}"
-    return f"""
-language python
-
-// This migration is generated automatically - do not manually edit this file
-pattern {pattern_name}() {{
-  find_replace_imports(list=[
-{remapped}
-  ])
-}}
-
-// Add this for invoking directly
-{pattern_name}()
-"""

libs/cli/langchain_cli/namespaces/migrate/generate/partner.py

@@ -1,53 +0,0 @@
-"""Generate migrations for partner packages."""
-
-import importlib
-
-from langchain_core.documents import BaseDocumentCompressor, BaseDocumentTransformer
-from langchain_core.embeddings import Embeddings
-from langchain_core.language_models import BaseLanguageModel
-from langchain_core.retrievers import BaseRetriever
-from langchain_core.vectorstores import VectorStore
-
-from langchain_cli.namespaces.migrate.generate.utils import (
-    COMMUNITY_PKG,
-    find_subclasses_in_module,
-    list_classes_by_package,
-    list_init_imports_by_package,
-)
-
-# PUBLIC API
-
-
-def get_migrations_for_partner_package(pkg_name: str) -> list[tuple[str, str]]:
-    """Generate migrations from community package to partner package.
-
-    This code works
-
-    Args:
-        pkg_name: The name of the partner package.
-
-    Returns:
-        List of 2-tuples containing old and new import paths.
-    """
-    package = importlib.import_module(pkg_name)
-    classes_ = find_subclasses_in_module(
-        package,
-        [
-            BaseLanguageModel,
-            Embeddings,
-            BaseRetriever,
-            VectorStore,
-            BaseDocumentTransformer,
-            BaseDocumentCompressor,
-        ],
-    )
-    community_classes = list_classes_by_package(str(COMMUNITY_PKG))
-    imports_for_pkg = list_init_imports_by_package(str(COMMUNITY_PKG))
-
-    old_paths = community_classes + imports_for_pkg
-
-    return [
-        (f"{module}.{item}", f"{pkg_name}.{item}")
-        for module, item in old_paths
-        if item in classes_
-    ]

libs/cli/langchain_cli/namespaces/migrate/generate/utils.py

@@ -1,222 +0,0 @@
-"""Generate migrations utilities."""
-
-import ast
-import inspect
-import os
-import pathlib
-from pathlib import Path
-from types import ModuleType
-
-from typing_extensions import override
-
-HERE = Path(__file__).parent
-# Should bring us to [root]/src
-PKGS_ROOT = HERE.parent.parent.parent.parent.parent
-
-LANGCHAIN_PKG = PKGS_ROOT / "langchain"
-COMMUNITY_PKG = PKGS_ROOT / "community"
-PARTNER_PKGS = PKGS_ROOT / "partners"
-
-
-class ImportExtractor(ast.NodeVisitor):
-    """Import extractor."""
-
-    def __init__(self, *, from_package: str | None = None) -> None:
-        """Extract all imports from the given code, optionally filtering by package."""
-        self.imports: list[tuple[str, str]] = []
-        self.package = from_package
-
-    @override
-    def visit_ImportFrom(self, node: ast.ImportFrom) -> None:
-        if node.module and (
-            self.package is None or str(node.module).startswith(self.package)
-        ):
-            for alias in node.names:
-                self.imports.append((node.module, alias.name))
-        self.generic_visit(node)
-
-
-def _get_class_names(code: str) -> list[str]:
-    """Extract class names from a code string."""
-    # Parse the content of the file into an AST
-    tree = ast.parse(code)
-
-    # Initialize a list to hold all class names
-    class_names = []
-
-    # Define a node visitor class to collect class names
-    class ClassVisitor(ast.NodeVisitor):
-        @override
-        def visit_ClassDef(self, node: ast.ClassDef) -> None:
-            class_names.append(node.name)
-            self.generic_visit(node)
-
-    # Create an instance of the visitor and visit the AST
-    visitor = ClassVisitor()
-    visitor.visit(tree)
-    return class_names
-
-
-def is_subclass(class_obj: type, classes_: list[type]) -> bool:
-    """Check if the given class object is a subclass of any class in list classes.
-
-    Args:
-        class_obj: The class to check.
-        classes_: A list of classes to check against.
-
-    Returns:
-        True if `class_obj` is a subclass of any class in `classes_`, `False` otherwise.
-    """
-    return any(
-        issubclass(class_obj, kls)
-        for kls in classes_
-        if inspect.isclass(class_obj) and inspect.isclass(kls)
-    )
-
-
-def find_subclasses_in_module(module: ModuleType, classes_: list[type]) -> list[str]:
-    """Find all classes in the module that inherit from one of the classes.
-
-    Args:
-        module: The module to inspect.
-        classes_: A list of classes to check against.
-
-    Returns:
-        A list of class names that are subclasses of any class in `classes_`.
-    """
-    subclasses = []
-    # Iterate over all attributes of the module that are classes
-    for _name, obj in inspect.getmembers(module, inspect.isclass):
-        if is_subclass(obj, classes_):
-            subclasses.append(obj.__name__)
-    return subclasses
-
-
-def _get_all_classnames_from_file(file: Path, pkg: str) -> list[tuple[str, str]]:
-    """Extract all class names from a file."""
-    code = Path(file).read_text(encoding="utf-8")
-    module_name = _get_current_module(file, pkg)
-    class_names = _get_class_names(code)
-
-    return [(module_name, class_name) for class_name in class_names]
-
-
-def identify_all_imports_in_file(
-    file: str,
-    *,
-    from_package: str | None = None,
-) -> list[tuple[str, str]]:
-    """Identify all the imports in the given file.
-
-    Args:
-        file: The file to analyze.
-        from_package: If provided, only return imports from this package.
-
-    Returns:
-        A list of tuples `(module, name)` representing the imports found in the file.
-    """
-    code = Path(file).read_text(encoding="utf-8")
-    return find_imports_from_package(code, from_package=from_package)
-
-
-def identify_pkg_source(pkg_root: str) -> pathlib.Path:
-    """Identify the source of the package.
-
-    Args:
-        pkg_root: the root of the package. This contains source + tests, and other
-            things like pyproject.toml, lock files etc
-
-    Returns:
-        Returns the path to the source code for the package.
-
-    Raises:
-        ValueError: If there is not exactly one directory starting with `'langchain_'`
-            in the package root.
-    """
-    dirs = [d for d in Path(pkg_root).iterdir() if d.is_dir()]
-    matching_dirs = [d for d in dirs if d.name.startswith("langchain_")]
-    if len(matching_dirs) != 1:
-        msg = "There should be only one langchain package."
-        raise ValueError(msg)
-    return matching_dirs[0]
-
-
-def list_classes_by_package(pkg_root: str) -> list[tuple[str, str]]:
-    """List all classes in a package.
-
-    Args:
-        pkg_root: the root of the package.
-
-    Returns:
-        A list of tuples `(module, class_name)` representing all classes found in the
-        package, excluding test files.
-    """
-    module_classes = []
-    pkg_source = identify_pkg_source(pkg_root)
-    files = list(pkg_source.rglob("*.py"))
-
-    for file in files:
-        rel_path = os.path.relpath(file, pkg_root)
-        if rel_path.startswith("tests"):
-            continue
-        module_classes.extend(_get_all_classnames_from_file(file, pkg_root))
-    return module_classes
-
-
-def list_init_imports_by_package(pkg_root: str) -> list[tuple[str, str]]:
-    """List all the things that are being imported in a package by module.
-
-    Args:
-        pkg_root: the root of the package.
-
-    Returns:
-        A list of tuples `(module, name)` representing the imports found in
-        `__init__.py` files.
-    """
-    imports = []
-    pkg_source = identify_pkg_source(pkg_root)
-    # Scan all the files in the package
-    files = list(Path(pkg_source).rglob("*.py"))
-
-    for file in files:
-        if file.name != "__init__.py":
-            continue
-        import_in_file = identify_all_imports_in_file(str(file))
-        module_name = _get_current_module(file, pkg_root)
-        imports.extend([(module_name, item) for _, item in import_in_file])
-    return imports
-
-
-def find_imports_from_package(
-    code: str,
-    *,
-    from_package: str | None = None,
-) -> list[tuple[str, str]]:
-    """Find imports in code.
-
-    Args:
-        code: The code to analyze.
-        from_package: If provided, only return imports from this package.
-
-    Returns:
-        A list of tuples `(module, name)` representing the imports found.
-    """
-    # Parse the code into an AST
-    tree = ast.parse(code)
-    # Create an instance of the visitor
-    extractor = ImportExtractor(from_package=from_package)
-    # Use the visitor to update the imports list
-    extractor.visit(tree)
-    return extractor.imports
-
-
-def _get_current_module(path: Path, pkg_root: str) -> str:
-    """Convert a path to a module name."""
-    relative_path = path.relative_to(pkg_root).with_suffix("")
-    posix_path = relative_path.as_posix()
-    norm_path = os.path.normpath(str(posix_path))
-    fully_qualified_module = norm_path.replace("/", ".")
-    # Strip __init__ if present
-    if fully_qualified_module.endswith(".__init__"):
-        return fully_qualified_module[:-9]
-    return fully_qualified_module

libs/cli/langchain_cli/namespaces/migrate/main.py

@@ -1,74 +0,0 @@
-"""Migrate LangChain to the most recent version."""
-
-from pathlib import Path
-
-import rich
-import typer
-from gritql import run  # type: ignore[import-untyped]
-from typer import Option
-
-
-def get_gritdir_path() -> Path:
-    """Get the path to the grit directory."""
-    script_dir = Path(__file__).parent
-    return script_dir / ".grit"
-
-
-def migrate(
-    ctx: typer.Context,
-    # Using diff instead of dry-run for backwards compatibility with the old CLI
-    diff: bool = Option(  # noqa: FBT001
-        False,  # noqa: FBT003
-        "--diff",
-        help="Show the changes that would be made without applying them.",
-    ),
-    interactive: bool = Option(  # noqa: FBT001
-        False,  # noqa: FBT003
-        "--interactive",
-        help="Prompt for confirmation before making each change",
-    ),
-) -> None:
-    """Migrate langchain to the most recent version.
-
-    Any undocumented arguments will be passed to the Grit CLI.
-    """
-    rich.print(
-        "✈️ This script will help you migrate to a LangChain 0.3. "
-        "This migration script will attempt to replace old imports in the code "
-        "with new ones. "
-        "If you need to migrate to LangChain 0.2, please downgrade to version 0.0.29 "
-        "of the langchain-cli.\n\n"
-        "🔄 You will need to run the migration script TWICE to migrate (e.g., "
-        "to update llms import from langchain, the script will first move them to "
-        "corresponding imports from the community package, and on the second "
-        "run will migrate from the community package to the partner package "
-        "when possible). \n\n"
-        "🔍 You can pre-view the changes by running with the --diff flag. \n\n"
-        "🚫 You can disable specific import changes by using the --disable "
-        "flag. \n\n"
-        "📄 Update your pyproject.toml or requirements.txt file to "
-        "reflect any imports from new packages. For example, if you see new "
-        "imports from langchain_openai, langchain_anthropic or "
-        "langchain_text_splitters you "
-        "should add them to your dependencies! \n\n"
-        '⚠️ This script is a "best-effort", and is likely to make some '
-        "mistakes.\n\n"
-        "🛡️ Backup your code prior to running the migration script -- it will "
-        "modify your files!\n\n",
-    )
-    rich.print("-" * 10)
-    rich.print()
-
-    args = list(ctx.args)
-    if interactive:
-        args.append("--interactive")
-    if diff:
-        args.append("--dry-run")
-
-    final_code = run.apply_pattern(
-        "langchain_all_migrations()",
-        args,
-        grit_dir=str(get_gritdir_path()),
-    )
-
-    raise typer.Exit(code=final_code)

libs/cli/langchain_cli/namespaces/template.py

@@ -1,147 +0,0 @@
-"""Develop installable templates."""
-
-import re
-import shutil
-import subprocess
-from pathlib import Path
-from typing import Annotated
-
-import typer
-import uvicorn
-
-from langchain_cli.utils.github import list_packages
-from langchain_cli.utils.packages import get_langserve_export, get_package_root
-
-package_cli = typer.Typer(no_args_is_help=True, add_completion=False)
-
-
-@package_cli.command()
-def new(
-    name: Annotated[str, typer.Argument(help="The name of the folder to create")],
-    with_poetry: Annotated[  # noqa: FBT002
-        bool,
-        typer.Option("--with-poetry/--no-poetry", help="Don't run poetry install"),
-    ] = False,
-) -> None:
-    """Create a new template package."""
-    computed_name = name if name != "." else Path.cwd().name
-    destination_dir = Path.cwd() / name if name != "." else Path.cwd()
-
-    # copy over template from ../package_template
-    project_template_dir = Path(__file__).parents[1] / "package_template"
-    shutil.copytree(project_template_dir, destination_dir, dirs_exist_ok=name == ".")
-
-    package_name_split = computed_name.split("/")
-    package_name = (
-        package_name_split[-2]
-        if len(package_name_split) > 1 and not package_name_split[-1]
-        else package_name_split[-1]
-    )
-    module_name = re.sub(
-        r"[^a-zA-Z0-9_]",
-        "_",
-        package_name,
-    )
-
-    # generate app route code
-    chain_name = f"{module_name}_chain"
-    app_route_code = (
-        f"from {module_name} import chain as {chain_name}\n\n"
-        f'add_routes(app, {chain_name}, path="/{package_name}")'
-    )
-
-    # replace template strings
-    pyproject = destination_dir / "pyproject.toml"
-    pyproject_contents = pyproject.read_text()
-    pyproject.write_text(
-        pyproject_contents.replace("__package_name__", package_name).replace(
-            "__module_name__",
-            module_name,
-        ),
-    )
-
-    # move module folder
-    package_dir = destination_dir / module_name
-    shutil.move(destination_dir / "package_template", package_dir)
-
-    # update init
-    init = package_dir / "__init__.py"
-    init_contents = init.read_text()
-    init.write_text(init_contents.replace("__module_name__", module_name))
-
-    # replace readme
-    readme = destination_dir / "README.md"
-    readme_contents = readme.read_text()
-    readme.write_text(
-        readme_contents.replace("__package_name__", package_name).replace(
-            "__app_route_code__",
-            app_route_code,
-        ),
-    )
-
-    # poetry install
-    if with_poetry:
-        subprocess.run(["poetry", "install"], cwd=destination_dir, check=True)  # noqa: S607
-
-
-@package_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,
-    configurable: Annotated[
-        bool | None,
-        typer.Option(
-            "--configurable/--no-configurable",
-            help="Whether to include a configurable route",
-        ),
-    ] = None,  # defaults to `not chat_playground`
-    chat_playground: Annotated[
-        bool,
-        typer.Option(
-            "--chat-playground/--no-chat-playground",
-            help="Whether to include a chat playground route",
-        ),
-    ] = False,
-) -> None:
-    """Start a demo app for this template."""
-    # load pyproject.toml
-    project_dir = get_package_root()
-    pyproject = project_dir / "pyproject.toml"
-
-    # get langserve export - throws KeyError if invalid
-    get_langserve_export(pyproject)
-
-    host_str = host if host is not None else "127.0.0.1"
-
-    script = (
-        "langchain_cli.dev_scripts:create_demo_server_chat"
-        if chat_playground
-        else (
-            "langchain_cli.dev_scripts:create_demo_server_configurable"
-            if configurable
-            else "langchain_cli.dev_scripts:create_demo_server"
-        )
-    )
-
-    uvicorn.run(
-        script,
-        factory=True,
-        reload=True,
-        port=port if port is not None else 8000,
-        host=host_str,
-    )
-
-
-@package_cli.command()
-def list(contains: Annotated[str | None, typer.Argument()] = None) -> None:  # noqa: A001
-    """List all or search for available templates."""
-    packages = list_packages(contains=contains)
-    for package in packages:
-        typer.echo(package)

libs/cli/langchain_cli/package_template/.gitignore

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