check passing message names

Thank you for contributing to LangChain!

- [x] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core, etc. is
being modified. Use "docs: ..." for purely docs changes, "infra: ..."
for CI changes.
  - Example: "community: add foobar LLM"


- [ ] **PR message**: ***Delete this entire checklist*** and replace
with
    - **Description:** a description of the change
    - **Issue:** the issue # it fixes, if applicable
    - **Dependencies:** any dependencies required for this change
- **Twitter handle:** if your PR gets announced, and you'd like a
mention, we'll gladly shout you out!


- [ ] **Add tests and docs**: If you're adding a new integration, please
include
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in
`docs/docs/integrations` directory.


- [ ] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/

Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.

If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.

.github/actions/uv_setup/action.yml

@@ -0,0 +1,21 @@
+# TODO: https://docs.astral.sh/uv/guides/integration/github/#caching
+
+name: uv-install
+description: Set up Python and uv
+
+inputs:
+  python-version:
+    description: Python version, supporting MAJOR.MINOR only
+    required: true
+
+env:
+  UV_VERSION: "0.5.25"
+
+runs:
+  using: composite
+  steps:
+    - name: Install uv and set the python version
+      uses: astral-sh/setup-uv@v5
+      with:
+        version: ${{ env.UV_VERSION }}
+        python-version: ${{ inputs.python-version }}

.github/scripts/check_diff.py

@@ -7,6 +7,8 @@ from typing import Dict, List, Set
 from pathlib import Path
 import tomllib
 
+from packaging.requirements import Requirement
+
 from get_min_versions import get_min_version_from_toml
 
 
@@ -37,6 +39,8 @@ IGNORED_PARTNERS = [
 
 PY_312_MAX_PACKAGES = [
     "libs/partners/huggingface",  # https://github.com/pytorch/pytorch/issues/130249
+    "libs/partners/pinecone",
+    "libs/partners/voyageai",
 ]
 
 
@@ -61,15 +65,17 @@ def dependents_graph() -> dict:
 
         # load regular and test deps from pyproject.toml
         with open(path, "rb") as f:
-            pyproject = tomllib.load(f)["tool"]["poetry"]
+            pyproject = tomllib.load(f)
 
         pkg_dir = "libs" + "/".join(path.split("libs")[1].split("/")[:-1])
         for dep in [
-            *pyproject["dependencies"].keys(),
-            *pyproject["group"]["test"]["dependencies"].keys(),
+            *pyproject["project"]["dependencies"],
+            *pyproject["dependency-groups"]["test"],
         ]:
+            requirement = Requirement(dep)
+            package_name = requirement.name
             if "langchain" in dep:
-                dependents[dep].add(pkg_dir)
+                dependents[package_name].add(pkg_dir)
                 continue
 
         # load extended deps from extended_testing_deps.txt
@@ -120,8 +126,7 @@ def _get_configs_for_single_dir(job: str, dir_: str) -> List[Dict[str, str]]:
         py_versions = ["3.9", "3.10", "3.11", "3.12", "3.13"]
     # custom logic for specific directories
     elif dir_ == "libs/partners/milvus":
-        # milvus poetry doesn't allow 3.12 because they
-        # declare deps in funny way
+        # milvus doesn't allow 3.12 because they declare deps in funny way
         py_versions = ["3.9", "3.11"]
 
     elif dir_ in PY_312_MAX_PACKAGES:
@@ -148,17 +153,17 @@ def _get_configs_for_single_dir(job: str, dir_: str) -> List[Dict[str, str]]:
 def _get_pydantic_test_configs(
     dir_: str, *, python_version: str = "3.11"
 ) -> List[Dict[str, str]]:
-    with open("./libs/core/poetry.lock", "rb") as f:
-        core_poetry_lock_data = tomllib.load(f)
-    for package in core_poetry_lock_data["package"]:
+    with open("./libs/core/uv.lock", "rb") as f:
+        core_uv_lock_data = tomllib.load(f)
+    for package in core_uv_lock_data["package"]:
         if package["name"] == "pydantic":
             core_max_pydantic_minor = package["version"].split(".")[1]
             break
 
-    with open(f"./{dir_}/poetry.lock", "rb") as f:
-        dir_poetry_lock_data = tomllib.load(f)
+    with open(f"./{dir_}/uv.lock", "rb") as f:
+        dir_uv_lock_data = tomllib.load(f)
 
-    for package in dir_poetry_lock_data["package"]:
+    for package in dir_uv_lock_data["package"]:
         if package["name"] == "pydantic":
             dir_max_pydantic_minor = package["version"].split(".")[1]
             break
@@ -304,7 +309,7 @@ if __name__ == "__main__":
                 f"Unknown lib: {file}. check_diff.py likely needs "
                 "an update for this new library!"
             )
-        elif file.startswith("docs/") or file in ["pyproject.toml", "poetry.lock"]: # docs or root poetry files
+        elif file.startswith("docs/") or file in ["pyproject.toml", "uv.lock"]: # docs or root uv files
             docs_edited = True
             dirs_to_run["lint"].add(".")
 

.github/scripts/check_prerelease_dependencies.py

@@ -10,26 +10,25 @@ if __name__ == "__main__":
         toml_data = tomllib.load(file)
 
     # see if we're releasing an rc
-    version = toml_data["tool"]["poetry"]["version"]
+    version = toml_data["project"]["version"]
     releasing_rc = "rc" in version or "dev" in version
 
     # if not, iterate through dependencies and make sure none allow prereleases
     if not releasing_rc:
-        dependencies = toml_data["tool"]["poetry"]["dependencies"]
-        for lib in dependencies:
-            dep_version = dependencies[lib]
+        dependencies = toml_data["project"]["dependencies"]
+        for dep_version in dependencies:
             dep_version_string = (
                 dep_version["version"] if isinstance(dep_version, dict) else dep_version
             )
 
             if "rc" in dep_version_string:
                 raise ValueError(
-                    f"Dependency {lib} has a prerelease version. Please remove this."
+                    f"Dependency {dep_version} has a prerelease version. Please remove this."
                 )
 
             if isinstance(dep_version, dict) and dep_version.get(
                 "allow-prereleases", False
             ):
                 raise ValueError(
-                    f"Dependency {lib} has allow-prereleases set to true. Please remove this."
+                    f"Dependency {dep_version} has allow-prereleases set to true. Please remove this."
                 )

.github/scripts/get_min_versions.py

@@ -1,3 +1,4 @@
+from collections import defaultdict
 import sys
 from typing import Optional
 
@@ -7,6 +8,7 @@ else:
     # for python 3.10 and below, which doesnt have stdlib tomllib
     import tomli as tomllib
 
+from packaging.requirements import Requirement
 from packaging.specifiers import SpecifierSet
 from packaging.version import Version
 
@@ -94,6 +96,23 @@ def get_minimum_version(package_name: str, spec_string: str) -> Optional[str]:
     return str(min(valid_versions)) if valid_versions else None
 
 
+def _check_python_version_from_requirement(
+    requirement: Requirement, python_version: str
+) -> bool:
+    if not requirement.marker:
+        return True
+    else:
+        marker_str = str(requirement.marker)
+        if "python_version" or "python_full_version" in marker_str:
+            python_version_str = "".join(
+                char
+                for char in marker_str
+                if char.isdigit() or char in (".", "<", ">", "=", ",")
+            )
+            return check_python_version(python_version, python_version_str)
+        return True
+
+
 def get_min_version_from_toml(
     toml_path: str,
     versions_for: str,
@@ -105,8 +124,10 @@ def get_min_version_from_toml(
     with open(toml_path, "rb") as file:
         toml_data = tomllib.load(file)
 
-    # Get the dependencies from tool.poetry.dependencies
-    dependencies = toml_data["tool"]["poetry"]["dependencies"]
+    dependencies = defaultdict(list)
+    for dep in toml_data["project"]["dependencies"]:
+        requirement = Requirement(dep)
+        dependencies[requirement.name].append(requirement)
 
     # Initialize a dictionary to store the minimum versions
     min_versions = {}
@@ -121,17 +142,11 @@ def get_min_version_from_toml(
         if lib in dependencies:
             if include and lib not in include:
                 continue
-            # Get the version string
-            version_string = dependencies[lib]
-
-            if isinstance(version_string, dict):
-                version_string = version_string["version"]
-            if isinstance(version_string, list):
-                version_string = [
-                    vs
-                    for vs in version_string
-                    if check_python_version(python_version, vs["python"])
-                ][0]["version"]
+            requirements = dependencies[lib]
+            for requirement in requirements:
+                if _check_python_version_from_requirement(requirement, python_version):
+                    version_string = str(requirement.specifier)
+                    break
 
             # Use parse_version to get the minimum supported version from version_string
             min_version = get_minimum_version(lib, version_string)

.github/workflows/_compile_integration_test.yml

@@ -13,7 +13,7 @@ on:
         description: "Python version to use"
 
 env:
-  POETRY_VERSION: "1.8.4"
+  UV_FROZEN: "true"
 
 jobs:
   build:
@@ -22,25 +22,22 @@ jobs:
         working-directory: ${{ inputs.working-directory }}
     runs-on: ubuntu-latest
     timeout-minutes: 20
-    name: "poetry run pytest -m compile tests/integration_tests #${{ inputs.python-version }}"
+    name: "uv run pytest -m compile tests/integration_tests #${{ inputs.python-version }}"
     steps:
       - uses: actions/checkout@v4
 
-      - name: Set up Python ${{ inputs.python-version }} + Poetry ${{ env.POETRY_VERSION }}
-        uses: "./.github/actions/poetry_setup"
+      - name: Set up Python ${{ inputs.python-version }} + uv
+        uses: "./.github/actions/uv_setup"
         with:
           python-version: ${{ inputs.python-version }}
-          poetry-version: ${{ env.POETRY_VERSION }}
-          working-directory: ${{ inputs.working-directory }}
-          cache-key: compile-integration
 
       - name: Install integration dependencies
         shell: bash
-        run: poetry install --with=test_integration,test
+        run: uv sync --group test --group test_integration
 
       - name: Check integration tests compile
         shell: bash
-        run: poetry run pytest -m compile tests/integration_tests
+        run: uv run pytest -m compile tests/integration_tests
 
       - name: Ensure the tests did not create any additional files
         shell: bash

.github/workflows/_integration_test.yml

@@ -12,7 +12,7 @@ on:
         description: "Python version to use"
 
 env:
-  POETRY_VERSION: "1.8.4"
+  UV_FROZEN: "true"
 
 jobs:
   build:
@@ -24,22 +24,19 @@ jobs:
     steps:
       - uses: actions/checkout@v4
 
-      - name: Set up Python ${{ inputs.python-version }} + Poetry ${{ env.POETRY_VERSION }}
-        uses: "./.github/actions/poetry_setup"
+      - name: Set up Python ${{ inputs.python-version }} + uv
+        uses: "./.github/actions/uv_setup"
         with:
           python-version: ${{ inputs.python-version }}
-          poetry-version: ${{ env.POETRY_VERSION }}
-          working-directory: ${{ inputs.working-directory }}
-          cache-key: core
 
       - name: Install dependencies
         shell: bash
-        run: poetry install --with test,test_integration
+        run: uv sync --group test --group test_integration
 
       - name: Install deps outside pyproject
         if: ${{ startsWith(inputs.working-directory, 'libs/community/') }}
         shell: bash
-        run: poetry run pip install "boto3<2" "google-cloud-aiplatform<2"
+        run: VIRTUAL_ENV=.venv uv pip install "boto3<2" "google-cloud-aiplatform<2"
 
       - name: Run integration tests
         shell: bash

.github/workflows/_lint.yml

@@ -13,12 +13,13 @@ on:
         description: "Python version to use"
 
 env:
-  POETRY_VERSION: "1.8.4"
   WORKDIR: ${{ inputs.working-directory == '' && '.' || inputs.working-directory }}
 
   # This env var allows us to get inline annotations when ruff has complaints.
   RUFF_OUTPUT_FORMAT: github
 
+  UV_FROZEN: "true"
+
 jobs:
   build:
     name: "make lint #${{ inputs.python-version }}"
@@ -27,25 +28,10 @@ jobs:
     steps:
       - uses: actions/checkout@v4
 
-      - name: Set up Python ${{ inputs.python-version }} + Poetry ${{ env.POETRY_VERSION }}
-        uses: "./.github/actions/poetry_setup"
+      - name: Set up Python ${{ inputs.python-version }} + uv
+        uses: "./.github/actions/uv_setup"
         with:
           python-version: ${{ inputs.python-version }}
-          poetry-version: ${{ env.POETRY_VERSION }}
-          working-directory: ${{ inputs.working-directory }}
-          cache-key: lint-with-extras
-
-      - name: Check Poetry File
-        shell: bash
-        working-directory: ${{ inputs.working-directory }}
-        run: |
-          poetry check
-
-      - name: Check lock file
-        shell: bash
-        working-directory: ${{ inputs.working-directory }}
-        run: |
-          poetry lock --check
 
       - name: Install dependencies
         # Also installs dev/lint/test/typing dependencies, to ensure we have
@@ -58,17 +44,7 @@ jobs:
         # It doesn't matter how you change it, any change will cause a cache-bust.
         working-directory: ${{ inputs.working-directory }}
         run: |
-          poetry install --with lint,typing
-
-      - name: Get .mypy_cache to speed up mypy
-        uses: actions/cache@v4
-        env:
-          SEGMENT_DOWNLOAD_TIMEOUT_MIN: "2"
-        with:
-          path: |
-            ${{ env.WORKDIR }}/.mypy_cache
-          key: mypy-lint-${{ runner.os }}-${{ runner.arch }}-py${{ inputs.python-version }}-${{ inputs.working-directory }}-${{ hashFiles(format('{0}/poetry.lock', inputs.working-directory)) }}
-
+          uv sync --group lint --group typing
 
       - name: Analysing the code with our lint
         working-directory: ${{ inputs.working-directory }}
@@ -87,21 +63,12 @@ jobs:
         if: ${{ ! startsWith(inputs.working-directory, 'libs/partners/') }}
         working-directory: ${{ inputs.working-directory }}
         run: |
-          poetry install --with test
+          uv sync --group test
       - name: Install unit+integration test dependencies
         if: ${{ startsWith(inputs.working-directory, 'libs/partners/') }}
         working-directory: ${{ inputs.working-directory }}
         run: |
-          poetry install --with test,test_integration
-
-      - name: Get .mypy_cache_test to speed up mypy
-        uses: actions/cache@v4
-        env:
-          SEGMENT_DOWNLOAD_TIMEOUT_MIN: "2"
-        with:
-          path: |
-            ${{ env.WORKDIR }}/.mypy_cache_test
-          key: mypy-test-${{ runner.os }}-${{ runner.arch }}-py${{ inputs.python-version }}-${{ inputs.working-directory }}-${{ hashFiles(format('{0}/poetry.lock', inputs.working-directory)) }}
+          uv sync --group test --group test_integration
 
       - name: Analysing the code with our lint
         working-directory: ${{ inputs.working-directory }}

.github/workflows/_release.yml

@@ -21,7 +21,7 @@ on:
 
 env:
   PYTHON_VERSION: "3.11"
-  POETRY_VERSION: "1.8.4"
+  UV_FROZEN: "true"
 
 jobs:
   build:
@@ -36,13 +36,10 @@ jobs:
     steps:
       - uses: actions/checkout@v4
 
-      - name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
-        uses: "./.github/actions/poetry_setup"
+      - name: Set up Python + uv
+        uses: "./.github/actions/uv_setup"
         with:
           python-version: ${{ env.PYTHON_VERSION }}
-          poetry-version: ${{ env.POETRY_VERSION }}
-          working-directory: ${{ inputs.working-directory }}
-          cache-key: release
 
       # We want to keep this build stage *separate* from the release stage,
       # so that there's no sharing of permissions between them.
@@ -56,7 +53,7 @@ jobs:
       # > from the publish job.
       # https://github.com/pypa/gh-action-pypi-publish#non-goals
       - name: Build project for distribution
-        run: poetry build
+        run: uv build
         working-directory: ${{ inputs.working-directory }}
 
       - name: Upload build
@@ -67,11 +64,18 @@ jobs:
 
       - name: Check Version
         id: check-version
-        shell: bash
+        shell: python
         working-directory: ${{ inputs.working-directory }}
         run: |
-          echo pkg-name="$(poetry version | cut -d ' ' -f 1)" >> $GITHUB_OUTPUT
-          echo version="$(poetry version --short)" >> $GITHUB_OUTPUT
+          import os
+          import tomllib
+          with open("pyproject.toml", "rb") as f:
+              data = tomllib.load(f)
+          pkg_name = data["project"]["name"]
+          version = data["project"]["version"]
+          with open(os.environ["GITHUB_OUTPUT"], "a") as f:
+              f.write(f"pkg-name={pkg_name}\n")
+              f.write(f"version={version}\n")
   release-notes:
     needs:
       - build
@@ -184,13 +188,11 @@ jobs:
       # - The package is published, and it breaks on the missing dependency when
       #   used in the real world.
 
-      - name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
-        uses: "./.github/actions/poetry_setup"
+      - name: Set up Python + uv
+        uses: "./.github/actions/uv_setup"
         id: setup-python
         with:
           python-version: ${{ env.PYTHON_VERSION }}
-          poetry-version: ${{ env.POETRY_VERSION }}
-          working-directory: ${{ inputs.working-directory }}
 
       - uses: actions/download-artifact@v4
         with:
@@ -213,17 +215,18 @@ jobs:
         # - attempt install again after 5 seconds if it fails because there is
         #   sometimes a delay in availability on test pypi
         run: |
-          poetry run pip install dist/*.whl
+          uv venv
+          VIRTUAL_ENV=.venv uv pip install dist/*.whl
 
           # Replace all dashes in the package name with underscores,
           # since that's how Python imports packages with dashes in the name.
           # also remove _official suffix
           IMPORT_NAME="$(echo "$PKG_NAME" | sed s/-/_/g | sed s/_official//g)"
 
-          poetry run python -c "import $IMPORT_NAME; print(dir($IMPORT_NAME))"
+          uv run python -c "import $IMPORT_NAME; print(dir($IMPORT_NAME))"
 
       - name: Import test dependencies
-        run: poetry install --with test --no-root
+        run: uv sync --group test
         working-directory: ${{ inputs.working-directory }}
 
       # Overwrite the local version of the package with the built version
@@ -234,7 +237,7 @@ jobs:
           PKG_NAME: ${{ needs.build.outputs.pkg-name }}
           VERSION: ${{ needs.build.outputs.version }}
         run: |
-          poetry run pip install dist/*.whl
+          VIRTUAL_ENV=.venv uv pip install dist/*.whl
 
       - name: Run unit tests
         run: make tests
@@ -243,15 +246,15 @@ jobs:
       - name: Check for prerelease versions
         working-directory: ${{ inputs.working-directory }}
         run: |
-          poetry run python $GITHUB_WORKSPACE/.github/scripts/check_prerelease_dependencies.py pyproject.toml
+          uv run python $GITHUB_WORKSPACE/.github/scripts/check_prerelease_dependencies.py pyproject.toml
 
       - name: Get minimum versions
         working-directory: ${{ inputs.working-directory }}
         id: min-version
         run: |
-          poetry run pip install packaging requests
-          python_version="$(poetry run python --version | awk '{print $2}')"
-          min_versions="$(poetry run python $GITHUB_WORKSPACE/.github/scripts/get_min_versions.py pyproject.toml release $python_version)"
+          VIRTUAL_ENV=.venv uv pip install packaging requests
+          python_version="$(uv run python --version | awk '{print $2}')"
+          min_versions="$(uv run python $GITHUB_WORKSPACE/.github/scripts/get_min_versions.py pyproject.toml release $python_version)"
           echo "min-versions=$min_versions" >> "$GITHUB_OUTPUT"
           echo "min-versions=$min_versions"
 
@@ -260,12 +263,12 @@ jobs:
         env:
           MIN_VERSIONS: ${{ steps.min-version.outputs.min-versions }}
         run: |
-          poetry run pip install --force-reinstall $MIN_VERSIONS --editable .
+          VIRTUAL_ENV=.venv uv pip install --force-reinstall $MIN_VERSIONS --editable .
           make tests
         working-directory: ${{ inputs.working-directory }}
 
       - name: Import integration test dependencies
-        run: poetry install --with test,test_integration
+        run: uv sync --group test --group test_integration
         working-directory: ${{ inputs.working-directory }}
 
       - name: Run integration tests
@@ -306,6 +309,7 @@ jobs:
           UPSTAGE_API_KEY: ${{ secrets.UPSTAGE_API_KEY }}
           FIREWORKS_API_KEY: ${{ secrets.FIREWORKS_API_KEY }}
           XAI_API_KEY: ${{ secrets.XAI_API_KEY }}
+          DEEPSEEK_API_KEY: ${{ secrets.DEEPSEEK_API_KEY }}
         run: make integration_tests
         working-directory: ${{ inputs.working-directory }}
 
@@ -331,13 +335,10 @@ jobs:
     steps:
       - uses: actions/checkout@v4
 
-      - name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
-        uses: "./.github/actions/poetry_setup"
+      - name: Set up Python + uv
+        uses: "./.github/actions/uv_setup"
         with:
           python-version: ${{ env.PYTHON_VERSION }}
-          poetry-version: ${{ env.POETRY_VERSION }}
-          working-directory: ${{ inputs.working-directory }}
-          cache-key: release
 
       - uses: actions/download-artifact@v4
         with:
@@ -373,13 +374,10 @@ jobs:
     steps:
       - uses: actions/checkout@v4
 
-      - name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
-        uses: "./.github/actions/poetry_setup"
+      - name: Set up Python + uv
+        uses: "./.github/actions/uv_setup"
         with:
           python-version: ${{ env.PYTHON_VERSION }}
-          poetry-version: ${{ env.POETRY_VERSION }}
-          working-directory: ${{ inputs.working-directory }}
-          cache-key: release
 
       - uses: actions/download-artifact@v4
         with:

.github/workflows/_test.yml

@@ -13,7 +13,7 @@ on:
         description: "Python version to use"
 
 env:
-  POETRY_VERSION: "1.8.4"
+  UV_FROZEN: "true"
 
 jobs:
   build:
@@ -26,17 +26,14 @@ jobs:
     steps:
       - uses: actions/checkout@v4
 
-      - name: Set up Python ${{ inputs.python-version }} + Poetry ${{ env.POETRY_VERSION }}
-        uses: "./.github/actions/poetry_setup"
+      - name: Set up Python ${{ inputs.python-version }} + uv
+        uses: "./.github/actions/uv_setup"
         id: setup-python
         with:
           python-version: ${{ inputs.python-version }}
-          poetry-version: ${{ env.POETRY_VERSION }}
-          working-directory: ${{ inputs.working-directory }}
-          cache-key: core
       - name: Install dependencies
         shell: bash
-        run: poetry install --with test
+        run: uv sync --group test --dev
 
       - name: Run core tests
         shell: bash
@@ -48,9 +45,9 @@ jobs:
         id: min-version
         shell: bash
         run: |
-          poetry run pip install packaging tomli requests
-          python_version="$(poetry run python --version | awk '{print $2}')"
-          min_versions="$(poetry run python $GITHUB_WORKSPACE/.github/scripts/get_min_versions.py pyproject.toml pull_request $python_version)"
+          VIRTUAL_ENV=.venv uv pip install packaging tomli requests
+          python_version="$(uv run python --version | awk '{print $2}')"
+          min_versions="$(uv run python $GITHUB_WORKSPACE/.github/scripts/get_min_versions.py pyproject.toml pull_request $python_version)"
           echo "min-versions=$min_versions" >> "$GITHUB_OUTPUT"
           echo "min-versions=$min_versions"
 
@@ -59,8 +56,7 @@ jobs:
         env:
           MIN_VERSIONS: ${{ steps.min-version.outputs.min-versions }}
         run: |
-          poetry run pip install uv
-          poetry run uv pip install $MIN_VERSIONS
+          VIRTUAL_ENV=.venv uv pip install $MIN_VERSIONS
           make tests
         working-directory: ${{ inputs.working-directory }}
 

.github/workflows/_test_doc_imports.yml

@@ -9,7 +9,7 @@ on:
         description: "Python version to use"
 
 env:
-  POETRY_VERSION: "1.8.4"
+  UV_FROZEN: "true"
 
 jobs:
   build:
@@ -19,25 +19,23 @@ jobs:
     steps:
       - uses: actions/checkout@v4
 
-      - name: Set up Python ${{ inputs.python-version }} + Poetry ${{ env.POETRY_VERSION }}
-        uses: "./.github/actions/poetry_setup"
+      - name: Set up Python ${{ inputs.python-version }} + uv
+        uses: "./.github/actions/uv_setup"
         with:
           python-version: ${{ inputs.python-version }}
-          poetry-version: ${{ env.POETRY_VERSION }}
-          cache-key: core
 
       - name: Install dependencies
         shell: bash
-        run: poetry install --with test
+        run: uv sync --group test
 
       - name: Install langchain editable
         run: |
-          poetry run pip install langchain-experimental -e libs/core libs/langchain libs/community
+          VIRTUAL_ENV=.venv uv pip install langchain-experimental -e libs/core libs/langchain libs/community
 
       - name: Check doc imports
         shell: bash
         run: |
-          poetry run python docs/scripts/check_imports.py
+          uv run python docs/scripts/check_imports.py
 
       - name: Ensure the test did not create any additional files
         shell: bash

.github/workflows/_test_pydantic.yml

@@ -18,7 +18,7 @@ on:
         description: "Pydantic version to test."
 
 env:
-  POETRY_VERSION: "1.8.4"
+  UV_FROZEN: "true"
 
 jobs:
   build:
@@ -31,21 +31,18 @@ jobs:
     steps:
       - uses: actions/checkout@v4
 
-      - name: Set up Python ${{ inputs.python-version }} + Poetry ${{ env.POETRY_VERSION }}
-        uses: "./.github/actions/poetry_setup"
+      - name: Set up Python ${{ inputs.python-version }} + uv
+        uses: "./.github/actions/uv_setup"
         with:
           python-version: ${{ inputs.python-version }}
-          poetry-version: ${{ env.POETRY_VERSION }}
-          working-directory: ${{ inputs.working-directory }}
-          cache-key: core
 
       - name: Install dependencies
         shell: bash
-        run: poetry install --with test
+        run: uv sync --group test
 
       - name: Overwrite pydantic version
         shell: bash
-        run: poetry run pip install pydantic~=${{ inputs.pydantic-version }}
+        run: VIRTUAL_ENV=.venv uv pip install pydantic~=${{ inputs.pydantic-version }}
 
       - name: Run core tests
         shell: bash

.github/workflows/_test_release.yml

@@ -14,8 +14,8 @@ on:
         description: "Release from a non-master branch (danger!)"
 
 env:
-  POETRY_VERSION: "1.8.4"
-  PYTHON_VERSION: "3.10"
+  PYTHON_VERSION: "3.11"
+  UV_FROZEN: "true"
 
 jobs:
   build:
@@ -29,13 +29,10 @@ jobs:
     steps:
       - uses: actions/checkout@v4
 
-      - name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
-        uses: "./.github/actions/poetry_setup"
+      - name: Set up Python + uv
+        uses: "./.github/actions/uv_setup"
         with:
           python-version: ${{ env.PYTHON_VERSION }}
-          poetry-version: ${{ env.POETRY_VERSION }}
-          working-directory: ${{ inputs.working-directory }}
-          cache-key: release
 
       # We want to keep this build stage *separate* from the release stage,
       # so that there's no sharing of permissions between them.
@@ -49,7 +46,7 @@ jobs:
       # > from the publish job.
       # https://github.com/pypa/gh-action-pypi-publish#non-goals
       - name: Build project for distribution
-        run: poetry build
+        run: uv build
         working-directory: ${{ inputs.working-directory }}
 
       - name: Upload build
@@ -60,11 +57,18 @@ jobs:
 
       - name: Check Version
         id: check-version
-        shell: bash
+        shell: python
         working-directory: ${{ inputs.working-directory }}
         run: |
-          echo pkg-name="$(poetry version | cut -d ' ' -f 1)" >> $GITHUB_OUTPUT
-          echo version="$(poetry version --short)" >> $GITHUB_OUTPUT
+          import os
+          import tomllib
+          with open("pyproject.toml", "rb") as f:
+              data = tomllib.load(f)
+          pkg_name = data["project"]["name"]
+          version = data["project"]["version"]
+          with open(os.environ["GITHUB_OUTPUT"], "a") as f:
+              f.write(f"pkg-name={pkg_name}\n")
+              f.write(f"version={version}\n")
 
   publish:
     needs:

.github/workflows/api_doc_build.yml

@@ -5,7 +5,6 @@ on:
   schedule:
     - cron:  '0 13 * * *'
 env:
-  POETRY_VERSION: "1.8.4"
   PYTHON_VERSION: "3.11"
 
 jobs:
@@ -46,20 +45,18 @@ jobs:
             fi
           done
 
-      - name: Set up Python ${{ env.PYTHON_VERSION }} + Poetry ${{ env.POETRY_VERSION }}
-        uses: "./langchain/.github/actions/poetry_setup"
+      - name: Setup python ${{ env.PYTHON_VERSION }}
+        uses: actions/setup-python@v5
+        id: setup-python
         with:
           python-version: ${{ env.PYTHON_VERSION }}
-          poetry-version: ${{ env.POETRY_VERSION }}
-          cache-key: api-docs
-          working-directory: langchain
 
       - name: Install initial py deps
         working-directory: langchain
         run: |
           python -m pip install -U uv
           python -m uv pip install --upgrade --no-cache-dir pip setuptools pyyaml
-          
+
       - name: Move libs with script
         run: python langchain/.github/scripts/prep_api_docs_build.py
         env:

.github/workflows/check_diffs.yml

@@ -18,7 +18,7 @@ concurrency:
   cancel-in-progress: true
 
 env:
-  POETRY_VERSION: "1.8.4"
+  UV_FROZEN: "true"
 
 jobs:
   build:
@@ -127,24 +127,19 @@ jobs:
     steps:
       - uses: actions/checkout@v4
 
-      - name: Set up Python ${{ matrix.job-configs.python-version }} + Poetry ${{ env.POETRY_VERSION }}
-        uses: "./.github/actions/poetry_setup"
+      - name: Set up Python ${{ matrix.job-configs.python-version }} + uv
+        uses: "./.github/actions/uv_setup"
         with:
           python-version: ${{ matrix.job-configs.python-version }}
-          poetry-version: ${{ env.POETRY_VERSION }}
-          working-directory: ${{ matrix.job-configs.working-directory }}
-          cache-key: extended
 
-      - name: Install dependencies
+      - name: Install dependencies and run extended tests
         shell: bash
         run: |
-          echo "Running extended tests, installing dependencies with poetry..."
-          poetry install --with test
-          poetry run pip install uv
-          poetry run uv pip install -r extended_testing_deps.txt
-
-      - name: Run extended tests
-        run: make extended_tests
+          echo "Running extended tests, installing dependencies with uv..."
+          uv venv
+          uv sync --group test
+          VIRTUAL_ENV=.venv uv pip install -r extended_testing_deps.txt
+          VIRTUAL_ENV=.venv make extended_tests
 
       - name: Ensure the tests did not create any additional files
         shell: bash

.github/workflows/run_notebooks.yml

@@ -15,7 +15,7 @@ on:
     - cron: '0 13 * * *'
 
 env:
-  POETRY_VERSION: "1.8.4"
+  UV_FROZEN: "true"
 
 jobs:
   build:
@@ -25,13 +25,10 @@ jobs:
     steps:
       - uses: actions/checkout@v4
 
-      - name: Set up Python + Poetry ${{ env.POETRY_VERSION }}
-        uses: "./.github/actions/poetry_setup"
+      - name: Set up Python + uv
+        uses: "./.github/actions/uv_setup"
         with:
           python-version: ${{ github.event.inputs.python_version || '3.11' }}
-          poetry-version: ${{ env.POETRY_VERSION }}
-          working-directory: ${{ inputs.working-directory }}
-          cache-key: run-notebooks
 
       - name: 'Authenticate to Google Cloud'
         id: 'auth'
@@ -48,17 +45,17 @@ jobs:
 
       - name: Install dependencies
         run: |
-          poetry install --with dev,test
+          uv sync --group dev --group test
 
       - name: Pre-download files
         run: |
-          poetry run python docs/scripts/cache_data.py
+          uv run python docs/scripts/cache_data.py
           curl -s https://raw.githubusercontent.com/lerocha/chinook-database/master/ChinookDatabase/DataSources/Chinook_Sqlite.sql | sqlite3 docs/docs/how_to/Chinook.db
           cp docs/docs/how_to/Chinook.db docs/docs/tutorials/Chinook.db
 
       - name: Prepare notebooks
         run: |
-          poetry run python docs/scripts/prepare_notebooks_for_ci.py --comment-install-cells --working-directory ${{ github.event.inputs.working-directory || 'all' }}
+          uv run python docs/scripts/prepare_notebooks_for_ci.py --comment-install-cells --working-directory ${{ github.event.inputs.working-directory || 'all' }}
 
       - name: Run notebooks
         env:

.github/workflows/scheduled_test.yml

@@ -14,7 +14,9 @@ on:
 
 env:
   POETRY_VERSION: "1.8.4"
+  UV_FROZEN: "true"
   DEFAULT_LIBS: '["libs/partners/openai", "libs/partners/anthropic", "libs/partners/fireworks", "libs/partners/groq", "libs/partners/mistralai", "libs/partners/google-vertexai", "libs/partners/google-genai", "libs/partners/aws"]'
+  POETRY_LIBS: ("libs/partners/google-vertexai" "libs/partners/google-genai" "libs/partners/aws")
 
 jobs:
   compute-matrix:
@@ -79,7 +81,8 @@ jobs:
           mv langchain-google/libs/vertexai langchain/libs/partners/google-vertexai
           mv langchain-aws/libs/aws langchain/libs/partners/aws
 
-      - name: Set up Python ${{ matrix.python-version }}
+      - name: Set up Python ${{ matrix.python-version }} with poetry
+        if: contains(env.POETRY_LIBS, matrix.working-directory)
         uses: "./langchain/.github/actions/poetry_setup"
         with:
           python-version: ${{ matrix.python-version }}
@@ -87,6 +90,12 @@ jobs:
           working-directory: langchain/${{ matrix.working-directory }}
           cache-key: scheduled
 
+      - name: Set up Python ${{ matrix.python-version }} + uv
+        if: "!contains(env.POETRY_LIBS, matrix.working-directory)"
+        uses: "./langchain/.github/actions/uv_setup"
+        with:
+          python-version: ${{ matrix.python-version }}
+
       - name: 'Authenticate to Google Cloud'
         id: 'auth'
         uses: google-github-actions/auth@v2
@@ -100,12 +109,20 @@ jobs:
           aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
           aws-region: ${{ secrets.AWS_REGION }}
 
-      - name: Install dependencies
+      - name: Install dependencies (poetry)
+        if: contains(env.POETRY_LIBS, matrix.working-directory)
         run: |
           echo "Running scheduled tests, installing dependencies with poetry..."
           cd langchain/${{ matrix.working-directory }}
           poetry install --with=test_integration,test
 
+      - name: Install dependencies (uv)
+        if: "!contains(env.POETRY_LIBS, matrix.working-directory)"
+        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
         env:
           OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
@@ -117,6 +134,7 @@ jobs:
           AZURE_OPENAI_LEGACY_CHAT_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_LEGACY_CHAT_DEPLOYMENT_NAME }}
           AZURE_OPENAI_LLM_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_LLM_DEPLOYMENT_NAME }}
           AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME }}
+          DEEPSEEK_API_KEY: ${{ secrets.DEEPSEEK_API_KEY }}
           FIREWORKS_API_KEY: ${{ secrets.FIREWORKS_API_KEY }}
           GROQ_API_KEY: ${{ secrets.GROQ_API_KEY }}
           HUGGINGFACEHUB_API_TOKEN: ${{ secrets.HUGGINGFACEHUB_API_TOKEN }}

Makefile

@@ -1,5 +1,8 @@
 .PHONY: all clean help docs_build docs_clean docs_linkcheck api_docs_build api_docs_clean api_docs_linkcheck spell_check spell_fix lint lint_package lint_tests format format_diff
 
+.EXPORT_ALL_VARIABLES:
+UV_FROZEN = true
+
 ## help: Show this help info.
 help: Makefile
 	@printf "\n\033[1mUsage: make <TARGETS> ...\033[0m\n\n\033[1mTargets:\033[0m\n\n"
@@ -25,20 +28,20 @@ docs_clean:
 
 ## docs_linkcheck: Run linkchecker on the documentation.
 docs_linkcheck:
-	poetry run linkchecker _dist/docs/ --ignore-url node_modules
+	uv run --no-group test linkchecker _dist/docs/ --ignore-url node_modules
 
 ## api_docs_build: Build the API Reference documentation.
 api_docs_build:
-	poetry run python docs/api_reference/create_api_rst.py
-	cd docs/api_reference && poetry run make html
-	poetry run python docs/api_reference/scripts/custom_formatter.py docs/api_reference/_build/html/
+	uv run --no-group test python docs/api_reference/create_api_rst.py
+	cd docs/api_reference && uv run --no-group test make html
+	uv run --no-group test python docs/api_reference/scripts/custom_formatter.py docs/api_reference/_build/html/
 
 API_PKG ?= text-splitters
 
 api_docs_quick_preview:
-	poetry run python docs/api_reference/create_api_rst.py $(API_PKG)
-	cd docs/api_reference && poetry run make html
-	poetry run python docs/api_reference/scripts/custom_formatter.py docs/api_reference/_build/html/
+	uv run --no-group test python docs/api_reference/create_api_rst.py $(API_PKG)
+	cd docs/api_reference && uv run make html
+	uv run --no-group test python docs/api_reference/scripts/custom_formatter.py docs/api_reference/_build/html/
 	open docs/api_reference/_build/html/reference.html
 
 ## api_docs_clean: Clean the API Reference documentation build artifacts.
@@ -50,15 +53,15 @@ api_docs_clean:
 
 ## api_docs_linkcheck: Run linkchecker on the API Reference documentation.
 api_docs_linkcheck:
-	poetry run linkchecker docs/api_reference/_build/html/index.html
+	uv run --no-group test linkchecker docs/api_reference/_build/html/index.html
 
 ## spell_check: Run codespell on the project.
 spell_check:
-	poetry run codespell --toml pyproject.toml
+	uv run --no-group test codespell --toml pyproject.toml
 
 ## spell_fix: Run codespell on the project and fix the errors.
 spell_fix:
-	poetry run codespell --toml pyproject.toml -w
+	uv run --no-group test codespell --toml pyproject.toml -w
 
 ######################
 # LINTING AND FORMATTING
@@ -66,9 +69,9 @@ spell_fix:
 
 ## lint: Run linting on the project.
 lint lint_package lint_tests:
-	poetry run ruff check docs cookbook
-	poetry run ruff format docs cookbook cookbook --diff
-	poetry run ruff check --select I docs cookbook
+	uv run --group lint ruff check docs cookbook
+	uv run --group lint ruff format docs cookbook cookbook --diff
+	uv run --group lint ruff check --select I docs cookbook
 	git --no-pager grep 'from langchain import' docs cookbook | grep -vE 'from langchain import (hub)' && echo "Error: no importing langchain from root in docs, except for hub" && exit 1 || exit 0
 	
 	git --no-pager grep 'api.python.langchain.com' -- docs/docs ':!docs/docs/additional_resources/arxiv_references.mdx' ':!docs/docs/integrations/document_loaders/sitemap.ipynb' || exit 0 && \
@@ -77,5 +80,5 @@ lint lint_package lint_tests:
 
 ## format: Format the project files.
 format format_diff:
-	poetry run ruff format docs cookbook
-	poetry run ruff check --select I --fix docs cookbook
+	uv run --group lint ruff format docs cookbook
+	uv run --group lint ruff check --select I --fix docs cookbook

README.md

@@ -52,7 +52,7 @@ For these applications, LangChain simplifies the entire application lifecycle:
 - **Integration packages** (e.g. **`langchain-openai`**, **`langchain-anthropic`**, etc.): Important integrations have been split into lightweight packages that are co-maintained by the LangChain team and the integration developers.
 - **`langchain`**: Chains, agents, and retrieval strategies that make up an application's cognitive architecture.
 - **`langchain-community`**: Third-party integrations that are community maintained.
-- **[LangGraph](https://langchain-ai.github.io/langgraph)**: Build robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph. Integrates smoothly with LangChain, but can be used without it. To learn more about LangGraph, check out our first LangChain Academy course, *Introduction to LangGraph*, available [here](https://academy.langchain.com/courses/intro-to-langgraph).
+- **[LangGraph](https://langchain-ai.github.io/langgraph)**: LangGraph powers production-grade agents, trusted by Linkedin, Uber, Klarna, GitLab, and many more. Build robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph. Integrates smoothly with LangChain, but can be used without it. To learn more about LangGraph, check out our first LangChain Academy course, *Introduction to LangGraph*, available [here](https://academy.langchain.com/courses/intro-to-langgraph).
 
 ### Productionization:
 

docs/api_reference/create_api_rst.py

@@ -528,7 +528,12 @@ def _get_package_version(package_dir: Path) -> str:
             "Aborting the build."
         )
         exit(1)
-    return pyproject["tool"]["poetry"]["version"]
+    try:
+        # uses uv
+        return pyproject["project"]["version"]
+    except KeyError:
+        # uses poetry
+        return pyproject["tool"]["poetry"]["version"]
 
 
 def _out_file_path(package_name: str) -> Path:

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

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

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

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docs/cassettes/chat_token_usage_tracking_c00c9158-7bb4-4279-88e6-ea70f46e6ac2.msgpack.zlib

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

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docs/cassettes/sql_qa_11.msgpack.zlib

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docs/cassettes/sql_qa_39.msgpack.zlib

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docs/cassettes/tools_builtin_1365784c-e666-41c8-a1bb-e50f822b5936.msgpack.zlib

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docs/cassettes/tools_builtin_b4eaed85-c5a6-4ba9-b401-40258b0131c2.msgpack.zlib

@@ -1 +1 @@
-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

docs/docs/concepts/vectorstores.mdx

@@ -39,7 +39,7 @@ The interface consists of basic methods for writing, deleting and searching for
 The key methods are:
 
 - `add_documents`: Add a list of texts to the vector store.
-- `delete_documents`: Delete a list of documents from the vector store.
+- `delete`: Delete a list of documents from the vector store.
 - `similarity_search`: Search for similar documents to a given query.
 
 
@@ -89,10 +89,10 @@ vector_store.add_documents(documents=documents, ids=["doc1", "doc2"])
 
 ## Delete
 
-To delete documents, use the `delete_documents` method which takes a list of document IDs to delete.
+To delete documents, use the `delete` method which takes a list of document IDs to delete.
 
 ```python
-vector_store.delete_documents(ids=["doc1"])
+vector_store.delete(ids=["doc1"])
 ```
 
 ## Search

docs/docs/concepts/why_langchain.mdx

@@ -31,7 +31,7 @@ This provides a standard way to interact with chat models, supporting important
 
 ### Example: chat models 
 
-Many [model providers](/docs/concepts/chat_models/) support [tool calling](/docs/concepts/tool_calling/), a critical features for many applications (e.g., [agents](https://langchain-ai.github.io/langgraph/concepts/agentic_concepts/)), that allows a developer to request model responses that match a particular schema.
+Many [model providers](/docs/concepts/chat_models/) support [tool calling](/docs/concepts/tool_calling/), a critical feature for many applications (e.g., [agents](https://langchain-ai.github.io/langgraph/concepts/agentic_concepts/)), that allows a developer to request model responses that match a particular schema.
 The APIs for each provider differ. 
 LangChain's [chat model](/docs/concepts/chat_models/) interface provides a common way to bind [tools](/docs/concepts/tools) to a model in order to support [tool calling](/docs/concepts/tool_calling/):
 

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

@@ -3,16 +3,11 @@
 This guide walks through how to run the repository locally and check in your first code.
 For a [development container](https://containers.dev/), see the [.devcontainer folder](https://github.com/langchain-ai/langchain/tree/master/.devcontainer).
 
-## Dependency Management: Poetry and other env/dependency managers
+## Dependency Management: `uv` and other env/dependency managers
 
-This project utilizes [Poetry](https://python-poetry.org/) v1.7.1+ as a dependency manager.
+This project utilizes [uv](https://docs.astral.sh/uv/) v0.5+ as a dependency manager.
 
-❗Note: *Before installing Poetry*, if you use `Conda`, create and activate a new Conda env (e.g. `conda create -n langchain python=3.9`)
-
-Install Poetry: **[documentation on how to install it](https://python-poetry.org/docs/#installation)**.
-
-❗Note: If you use `Conda` or `Pyenv` as your environment/package manager, after installing Poetry,
-tell Poetry to use the virtualenv python environment (`poetry config virtualenvs.prefer-active-python true`)
+Install `uv`: **[documentation on how to install it](https://docs.astral.sh/uv/getting-started/installation/)**.
 
 ## Different packages
 
@@ -37,7 +32,7 @@ cd libs/community
 Install langchain-community development requirements (for running langchain, running examples, linting, formatting, tests, and coverage):
 
 ```bash
-poetry install --with lint,typing,test,test_integration
+uv sync
 ```
 
 Then verify dependency installation:
@@ -46,12 +41,6 @@ Then verify dependency installation:
 make test
 ```
 
-If during installation you receive a `WheelFileValidationError` for `debugpy`, please make sure you are running
-Poetry v1.6.1+. This bug was present in older versions of Poetry (e.g. 1.4.1) and has been resolved in newer releases.
-If you are still seeing this bug on v1.6.1+, you may also try disabling "modern installation"
-(`poetry config installer.modern-installation false`) and re-installing requirements.
-See [this `debugpy` issue](https://github.com/microsoft/debugpy/issues/1246) for more details.
-
 ## Testing
 
 **Note:** In `langchain`, `langchain-community`, and `langchain-experimental`, some test dependencies are optional. See the following section about optional dependencies.
@@ -79,7 +68,6 @@ If you are only developing `langchain_core` or `langchain_community`, you can si
 
 ```bash
 cd libs/core
-poetry install --with test
 make test
 ```
 
@@ -87,7 +75,6 @@ Or:
 
 ```bash
 cd libs/community
-poetry install --with test
 make test
 ```
 
@@ -179,7 +166,7 @@ ignore-words-list = 'momento,collison,ned,foor,reworkd,parth,whats,aapply,mysogy
 
 `langchain-core` and partner packages **do not use** optional dependencies in this way.
 
-You'll notice that `pyproject.toml` and `poetry.lock` are **not** touched when you add optional dependencies below.
+You'll notice that `pyproject.toml` and `uv.lock` are **not** touched when you add optional dependencies below.
 
 If you're adding a new dependency to Langchain, assume that it will be an optional dependency, and
 that most users won't have it installed.
@@ -196,18 +183,10 @@ test makes use of lightweight fixtures to test the logic of the code.
 
 ## Adding a Jupyter Notebook
 
-If you are adding a Jupyter Notebook example, you'll want to install the optional `dev` dependencies.
-
-To install dev dependencies:
+If you are adding a Jupyter Notebook example, you'll want to run with `test` dependencies:
 
 ```bash
-poetry install --with dev
+uv run --group test jupyter notebook
 ```
 
-Launch a notebook:
-
-```bash
-poetry run jupyter notebook
-```
-
-When you run `poetry install`, the `langchain` package is installed as editable in the virtualenv, so your new logic can be imported into the notebook.
+When you run `uv sync`, the `langchain` package is installed as editable in the virtualenv, so your new logic can be imported into the notebook.

docs/docs/contributing/how_to/integrations/publish.mdx

@@ -118,8 +118,8 @@ langchain-cli integration create-doc \
 These commands will create the following 3 files, which you should fill out with information about your package:
 
 - `docs/docs/integrations/providers/parrot_link.ipynb`
-- `docs/docs/integrations/chat/parrot_-_link.ipynb`
-- `docs/docs/integrations/vectorstores/parrot_-_link.ipynb`
+- `docs/docs/integrations/chat/parrot_link.ipynb`
+- `docs/docs/integrations/vectorstores/parrot_link.ipynb`
 
 ### Manually create your documentation pages (if you prefer)
 

docs/docs/how_to/local_llms.ipynb

@@ -477,7 +477,7 @@
     "2) Make the file executable\n",
     "3) Run the file\n",
     "\n",
-    "llamafiles bundle model weights and a [specially-compiled](https://github.com/Mozilla-Ocho/llamafile?tab=readme-ov-file#technical-details) version of [`llama.cpp`](https://github.com/ggerganov/llama.cpp) into a single file that can run on most computers any additional dependencies. They also come with an embedded inference server that provides an [API](https://github.com/Mozilla-Ocho/llamafile/blob/main/llama.cpp/server/README.md#api-endpoints) for interacting with your model. \n",
+    "llamafiles bundle model weights and a [specially-compiled](https://github.com/Mozilla-Ocho/llamafile?tab=readme-ov-file#technical-details) version of [`llama.cpp`](https://github.com/ggerganov/llama.cpp) into a single file that can run on most computers without any additional dependencies. They also come with an embedded inference server that provides an [API](https://github.com/Mozilla-Ocho/llamafile/blob/main/llama.cpp/server/README.md#api-endpoints) for interacting with your model. \n",
     "\n",
     "Here's a simple bash script that shows all 3 setup steps:\n",
     "\n",

docs/docs/integrations/chat/databricks.ipynb

@@ -509,7 +509,7 @@
    "source": [
     "## API reference\n",
     "\n",
-    "For detailed documentation of all ChatDatabricks features and configurations head to the API reference: https://python.langchain.com/api_reference/databricks/chat_models/langchain_databricks.chat_models.ChatDatabricks.html"
+    "For detailed documentation of all ChatDatabricks features and configurations head to the API reference: https://api-docs.databricks.com/python/databricks-ai-bridge/latest/databricks_langchain.html#databricks_langchain.ChatDatabricks"
    ]
   }
  ],

docs/docs/integrations/chat/deepseek.ipynb

@@ -31,7 +31,7 @@
     "\n",
     "| Class | Package | Local | Serializable | [JS support](https://js.langchain.com/docs/integrations/chat/deepseek) | Package downloads | Package latest |\n",
     "| :--- | :--- | :---: | :---: |  :---: | :---: | :---: |\n",
-    "| [ChatDeepSeek](https://python.langchain.com/api_reference/deepseek/chat_models/langchain_deepseek.chat_models.ChatDeepSeek.html) | [langchain-deepseek-official](https://python.langchain.com/api_reference/deepseek/) | ❌ | beta | ✅ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-deepseek-official?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-deepseek-official?style=flat-square&label=%20) |\n",
+    "| [ChatDeepSeek](https://python.langchain.com/api_reference/deepseek/chat_models/langchain_deepseek.chat_models.ChatDeepSeek.html) | [langchain-deepseek](https://python.langchain.com/api_reference/deepseek/) | ❌ | beta | ✅ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-deepseek?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-deepseek?style=flat-square&label=%20) |\n",
     "\n",
     "### Model features\n",
     "| [Tool calling](/docs/how_to/tool_calling) | [Structured output](/docs/how_to/structured_output/) | JSON mode | [Image input](/docs/how_to/multimodal_inputs/) | Audio input | Video input | [Token-level streaming](/docs/how_to/chat_streaming/) | Native async | [Token usage](/docs/how_to/chat_token_usage_tracking/) | [Logprobs](/docs/how_to/logprobs/) |\n",
@@ -40,7 +40,7 @@
     "\n",
     "## Setup\n",
     "\n",
-    "To access DeepSeek models you'll need to create a/an DeepSeek account, get an API key, and install the `langchain-deepseek-official` integration package.\n",
+    "To access DeepSeek models you'll need to create a/an DeepSeek account, get an API key, and install the `langchain-deepseek` integration package.\n",
     "\n",
     "### Credentials\n",
     "\n",
@@ -87,7 +87,7 @@
    "source": [
     "### Installation\n",
     "\n",
-    "The LangChain DeepSeek integration lives in the `langchain-deepseek-official` package:"
+    "The LangChain DeepSeek integration lives in the `langchain-deepseek` package:"
    ]
   },
   {
@@ -97,7 +97,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%pip install -qU langchain-deepseek-official"
+    "%pip install -qU langchain-deepseek"
    ]
   },
   {

docs/docs/integrations/chat/goodfire.ipynb

@@ -0,0 +1,354 @@
+{
+ "cells": [
+  {
+   "cell_type": "raw",
+   "id": "afaf8039",
+   "metadata": {},
+   "source": [
+    "---\n",
+    "sidebar_label: Goodfire\n",
+    "---"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e49f1e0d",
+   "metadata": {},
+   "source": [
+    "# ChatGoodfire\n",
+    "\n",
+    "This will help you getting started with Goodfire [chat models](/docs/concepts/chat_models). For detailed documentation of all ChatGoodfire features and configurations head to the [PyPI project page](https://pypi.org/project/langchain-goodfire/), or go directly to the [Goodfire SDK docs](https://docs.goodfire.ai/sdk-reference/example). All of the Goodfire-specific functionality (e.g. SAE features, variants, etc.) is available via the main `goodfire` package. This integration is a wrapper around the Goodfire SDK.\n",
+    "\n",
+    "## Overview\n",
+    "### Integration details\n",
+    "\n",
+    "| Class | Package | Local | Serializable | JS support | Package downloads | Package latest |\n",
+    "| :--- | :--- | :---: | :---: |  :---: | :---: | :---: |\n",
+    "| [ChatGoodfire](https://python.langchain.com/api_reference/goodfire/chat_models/langchain_goodfire.chat_models.ChatGoodfire.html) | [langchain-goodfire](https://python.langchain.com/api_reference/goodfire/) | ❌ | ❌ | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-goodfire?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-goodfire?style=flat-square&label=%20) |\n",
+    "\n",
+    "### Model features\n",
+    "| [Tool calling](/docs/how_to/tool_calling) | [Structured output](/docs/how_to/structured_output/) | JSON mode | [Image input](/docs/how_to/multimodal_inputs/) | Audio input | Video input | [Token-level streaming](/docs/how_to/chat_streaming/) | Native async | [Token usage](/docs/how_to/chat_token_usage_tracking/) | [Logprobs](/docs/how_to/logprobs/) |\n",
+    "| :---: | :---: | :---: | :---: |  :---: | :---: | :---: | :---: | :---: | :---: |\n",
+    "| ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ✅ | ✅ | ✅ | ❌ | \n",
+    "\n",
+    "## Setup\n",
+    "\n",
+    "To access Goodfire models you'll need to create a/an Goodfire account, get an API key, and install the `langchain-goodfire` integration package.\n",
+    "\n",
+    "### Credentials\n",
+    "\n",
+    "Head to [Goodfire Settings](https://platform.goodfire.ai/organization/settings/api-keys) to sign up to Goodfire and generate an API key. Once you've done this set the GOODFIRE_API_KEY environment variable."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "433e8d2b-9519-4b49-b2c4-7ab65b046c94",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import getpass\n",
+    "import os\n",
+    "\n",
+    "if not os.getenv(\"GOODFIRE_API_KEY\"):\n",
+    "    os.environ[\"GOODFIRE_API_KEY\"] = getpass.getpass(\"Enter your Goodfire API key: \")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "72ee0c4b-9764-423a-9dbf-95129e185210",
+   "metadata": {},
+   "source": [
+    "If you want to get automated tracing of your model calls 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_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 Goodfire integration lives in the `langchain-goodfire` package:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "652d6238-1f87-422a-b135-f5abbb8652fc",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "%pip install -qU langchain-goodfire"
+   ]
+  },
+  {
+   "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:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "cb09c344-1836-4e0c-acf8-11d13ac1dbae",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "None of PyTorch, TensorFlow >= 2.0, or Flax have been found. Models won't be available and only tokenizers, configuration and file/data utilities can be used.\n"
+     ]
+    }
+   ],
+   "source": [
+    "import goodfire\n",
+    "from langchain_goodfire import ChatGoodfire\n",
+    "\n",
+    "base_variant = goodfire.Variant(\"meta-llama/Llama-3.3-70B-Instruct\")\n",
+    "\n",
+    "llm = ChatGoodfire(\n",
+    "    model=base_variant,\n",
+    "    temperature=0,\n",
+    "    max_completion_tokens=1000,\n",
+    "    seed=42,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2b4f3e15",
+   "metadata": {},
+   "source": [
+    "## Invocation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "62e0dbc3",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "AIMessage(content=\"J'adore la programmation.\", additional_kwargs={}, response_metadata={}, id='run-8d43cf35-bce8-4827-8935-c64f8fb78cd0-0', usage_metadata={'input_tokens': 51, 'output_tokens': 39, 'total_tokens': 90})"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "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 = await llm.ainvoke(messages)\n",
+    "ai_msg"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "d86145b3-bfef-46e8-b227-4dda5c9c2705",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "J'adore la programmation.\n"
+     ]
+    }
+   ],
+   "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:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "e197d1d7-a070-4c96-9f8a-a0e86d046e0b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "AIMessage(content='Ich liebe das Programmieren. How can I help you with programming today?', additional_kwargs={}, response_metadata={}, id='run-03d1a585-8234-46f1-a8df-bf9143fe3309-0', usage_metadata={'input_tokens': 46, 'output_tokens': 46, 'total_tokens': 92})"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "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 | llm\n",
+    "await chain.ainvoke(\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": [
+    "## Goodfire-specific functionality\n",
+    "\n",
+    "To use Goodfire-specific functionality such as SAE features and variants, you can use the `goodfire` package directly."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "3aef9e0a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "FeatureGroup([\n",
+       "   0: \"The assistant should adopt the persona of a pirate\",\n",
+       "   1: \"The assistant should roleplay as a pirate\",\n",
+       "   2: \"The assistant should engage with pirate-themed content or roleplay as a pirate\",\n",
+       "   3: \"The assistant should roleplay as a character\",\n",
+       "   4: \"The assistant should roleplay as a specific character\",\n",
+       "   5: \"The assistant should roleplay as a game character or NPC\",\n",
+       "   6: \"The assistant should roleplay as a human character\",\n",
+       "   7: \"Requests for the assistant to roleplay or pretend to be something else\",\n",
+       "   8: \"Requests for the assistant to roleplay or pretend to be something\",\n",
+       "   9: \"The assistant is being assigned a role or persona to roleplay\"\n",
+       "])"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "client = goodfire.Client(api_key=os.environ[\"GOODFIRE_API_KEY\"])\n",
+    "\n",
+    "pirate_features = client.features.search(\n",
+    "    \"assistant should roleplay as a pirate\", base_variant\n",
+    ")\n",
+    "pirate_features"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "52f03a00",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "AIMessage(content='Why did the scarecrow win an award? Because he was outstanding in his field! Arrr! Hope that made ye laugh, matey!', additional_kwargs={}, response_metadata={}, id='run-7d8bd30f-7f80-41cb-bdb6-25c29c22a7ce-0', usage_metadata={'input_tokens': 35, 'output_tokens': 60, 'total_tokens': 95})"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pirate_variant = goodfire.Variant(\"meta-llama/Llama-3.3-70B-Instruct\")\n",
+    "\n",
+    "pirate_variant.set(pirate_features[0], 0.4)\n",
+    "pirate_variant.set(pirate_features[1], 0.3)\n",
+    "\n",
+    "await llm.ainvoke(\"Tell me a joke\", model=pirate_variant)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3a5bb5ca-c3ae-4a58-be67-2cd18574b9a3",
+   "metadata": {},
+   "source": [
+    "## API reference\n",
+    "\n",
+    "For detailed documentation of all ChatGoodfire features and configurations head to the [API reference](https://python.langchain.com/api_reference/goodfire/chat_models/langchain_goodfire.chat_models.ChatGoodfire.html)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "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": "3.12.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

docs/docs/integrations/document_loaders/pypdfdirectory.ipynb

@@ -36,13 +36,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-01-21T08:00:08.878423Z",
+     "start_time": "2025-01-21T08:00:08.876042Z"
+    }
+   },
    "source": [
     "# os.environ[\"LANGSMITH_API_KEY\"] = getpass.getpass(\"Enter your LangSmith API key: \")\n",
     "# os.environ[\"LANGSMITH_TRACING\"] = \"true\""
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 1
   },
   {
    "cell_type": "markdown",
@@ -54,17 +59,28 @@
    ]
   },
   {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-01-21T08:00:12.003718Z",
+     "start_time": "2025-01-21T08:00:10.291617Z"
+    }
+   },
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "%pip install -qU langchain_community"
-   ]
+   "source": "%pip install -qU langchain_community pypdf pillow",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "execution_count": 2
   },
   {
-   "cell_type": "markdown",
    "metadata": {},
+   "cell_type": "markdown",
    "source": [
     "## Initialization\n",
     "\n",
@@ -72,10 +88,13 @@
    ]
   },
   {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-01-21T08:00:18.512061Z",
+     "start_time": "2025-01-21T08:00:17.313969Z"
+    }
+   },
    "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
    "source": [
     "from langchain_community.document_loaders import PyPDFDirectoryLoader\n",
     "\n",
@@ -83,7 +102,9 @@
     "    \"../../docs/integrations/document_loaders/example_data/layout-parser-paper.pdf\"\n",
     ")\n",
     "loader = PyPDFDirectoryLoader(\"example_data/\")"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 3
   },
   {
    "cell_type": "markdown",
@@ -94,41 +115,51 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-01-21T08:00:23.549752Z",
+     "start_time": "2025-01-21T08:00:23.129010Z"
+    }
+   },
+   "source": [
+    "docs = loader.load()\n",
+    "docs[0]"
+   ],
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "Document(metadata={'source': 'example_data/layout-parser-paper.pdf', 'page': 0}, page_content='LayoutParser : A Unified Toolkit for Deep\\nLearning Based Document Image Analysis\\nZejiang Shen1( \\x00), Ruochen Zhang2, Melissa Dell3, Benjamin Charles Germain\\nLee4, Jacob Carlson3, and Weining Li5\\n1Allen Institute for AI\\nshannons@allenai.org\\n2Brown University\\nruochen zhang@brown.edu\\n3Harvard University\\n{melissadell,jacob carlson }@fas.harvard.edu\\n4University of Washington\\nbcgl@cs.washington.edu\\n5University of Waterloo\\nw422li@uwaterloo.ca\\nAbstract. Recent advances in document image analysis (DIA) have been\\nprimarily driven by the application of neural networks. Ideally, research\\noutcomes could be easily deployed in production and extended for further\\ninvestigation. However, various factors like loosely organized codebases\\nand sophisticated model configurations complicate the easy reuse of im-\\nportant innovations by a wide audience. Though there have been on-going\\nefforts to improve reusability and simplify deep learning (DL) model\\ndevelopment in disciplines like natural language processing and computer\\nvision, none of them are optimized for challenges in the domain of DIA.\\nThis represents a major gap in the existing toolkit, as DIA is central to\\nacademic research across a wide range of disciplines in the social sciences\\nand humanities. This paper introduces LayoutParser , an open-source\\nlibrary for streamlining the usage of DL in DIA research and applica-\\ntions. The core LayoutParser library comes with a set of simple and\\nintuitive interfaces for applying and customizing DL models for layout de-\\ntection, character recognition, and many other document processing tasks.\\nTo promote extensibility, LayoutParser also incorporates a community\\nplatform for sharing both pre-trained models and full document digiti-\\nzation pipelines. We demonstrate that LayoutParser is helpful for both\\nlightweight and large-scale digitization pipelines in real-word use cases.\\nThe library is publicly available at https://layout-parser.github.io .\\nKeywords: Document Image Analysis ·Deep Learning ·Layout Analysis\\n·Character Recognition ·Open Source library ·Toolkit.\\n1 Introduction\\nDeep Learning(DL)-based approaches are the state-of-the-art for a wide range of\\ndocument image analysis (DIA) tasks including document image classification [ 11,arXiv:2103.15348v2  [cs.CV]  21 Jun 2021')"
+       "Document(metadata={'producer': 'pdfTeX-1.40.21', 'creator': 'LaTeX with hyperref', 'creationdate': '2021-06-22T01:27:10+00:00', 'author': '', 'keywords': '', 'moddate': '2021-06-22T01:27:10+00:00', 'ptex.fullbanner': 'This is pdfTeX, Version 3.14159265-2.6-1.40.21 (TeX Live 2020) kpathsea version 6.3.2', 'subject': '', 'title': '', 'trapped': '/False', 'source': 'example_data/layout-parser-paper.pdf', 'total_pages': 16, 'page': 0, 'page_label': '1'}, page_content='LayoutParser: A Unified Toolkit for Deep\\nLearning Based Document Image Analysis\\nZejiang Shen1 (\\x00 ), Ruochen Zhang2, Melissa Dell3, Benjamin Charles Germain\\nLee4, Jacob Carlson3, and Weining Li5\\n1 Allen Institute for AI\\nshannons@allenai.org\\n2 Brown University\\nruochen zhang@brown.edu\\n3 Harvard University\\n{melissadell,jacob carlson}@fas.harvard.edu\\n4 University of Washington\\nbcgl@cs.washington.edu\\n5 University of Waterloo\\nw422li@uwaterloo.ca\\nAbstract. Recent advances in document image analysis (DIA) have been\\nprimarily driven by the application of neural networks. Ideally, research\\noutcomes could be easily deployed in production and extended for further\\ninvestigation. However, various factors like loosely organized codebases\\nand sophisticated model configurations complicate the easy reuse of im-\\nportant innovations by a wide audience. Though there have been on-going\\nefforts to improve reusability and simplify deep learning (DL) model\\ndevelopment in disciplines like natural language processing and computer\\nvision, none of them are optimized for challenges in the domain of DIA.\\nThis represents a major gap in the existing toolkit, as DIA is central to\\nacademic research across a wide range of disciplines in the social sciences\\nand humanities. This paper introduces LayoutParser, an open-source\\nlibrary for streamlining the usage of DL in DIA research and applica-\\ntions. The core LayoutParser library comes with a set of simple and\\nintuitive interfaces for applying and customizing DL models for layout de-\\ntection, character recognition, and many other document processing tasks.\\nTo promote extensibility, LayoutParser also incorporates a community\\nplatform for sharing both pre-trained models and full document digiti-\\nzation pipelines. We demonstrate that LayoutParser is helpful for both\\nlightweight and large-scale digitization pipelines in real-word use cases.\\nThe library is publicly available at https://layout-parser.github.io.\\nKeywords: Document Image Analysis · Deep Learning · Layout Analysis\\n· Character Recognition · Open Source library · Toolkit.\\n1 Introduction\\nDeep Learning(DL)-based approaches are the state-of-the-art for a wide range of\\ndocument image analysis (DIA) tasks including document image classification [11,\\narXiv:2103.15348v2  [cs.CV]  21 Jun 2021')"
       ]
      },
-     "execution_count": 2,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
-   "source": [
-    "docs = loader.load()\n",
-    "docs[0]"
-   ]
+   "execution_count": 4
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-01-21T08:00:26.612346Z",
+     "start_time": "2025-01-21T08:00:26.609051Z"
+    }
+   },
+   "source": [
+    "print(docs[0].metadata)"
+   ],
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "{'source': 'example_data/layout-parser-paper.pdf', 'page': 0}\n"
+      "{'producer': 'pdfTeX-1.40.21', 'creator': 'LaTeX with hyperref', 'creationdate': '2021-06-22T01:27:10+00:00', 'author': '', 'keywords': '', 'moddate': '2021-06-22T01:27:10+00:00', 'ptex.fullbanner': 'This is pdfTeX, Version 3.14159265-2.6-1.40.21 (TeX Live 2020) kpathsea version 6.3.2', 'subject': '', 'title': '', 'trapped': '/False', 'source': 'example_data/layout-parser-paper.pdf', 'total_pages': 16, 'page': 0, 'page_label': '1'}\n"
      ]
     }
    ],
-   "source": [
-    "print(docs[0].metadata)"
-   ]
+   "execution_count": 5
   },
   {
    "cell_type": "markdown",
@@ -139,9 +170,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-01-21T08:00:30.251598Z",
+     "start_time": "2025-01-21T08:00:29.972141Z"
+    }
+   },
    "source": [
     "page = []\n",
     "for doc in loader.lazy_load():\n",
@@ -151,7 +185,9 @@
     "        # index.upsert(page)\n",
     "\n",
     "        page = []"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 6
   },
   {
    "cell_type": "markdown",
@@ -161,6 +197,13 @@
     "\n",
     "For detailed documentation of all PyPDFDirectoryLoader features and configurations head to the API reference: https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.pdf.PyPDFDirectoryLoader.html"
    ]
+  },
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": ""
   }
  ],
  "metadata": {

docs/docs/integrations/document_loaders/readthedocs_documentation.ipynb

@@ -55,7 +55,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "loader = ReadTheDocsLoader(\"rtdocs\", features=\"html.parser\")"
+    "loader = ReadTheDocsLoader(\"rtdocs\")"
    ]
   },
   {

docs/docs/integrations/llms/oci_generative_ai.ipynb

@@ -135,6 +135,7 @@
     "    compartment_id=\"MY_OCID\",\n",
     "    auth_type=\"SECURITY_TOKEN\",\n",
     "    auth_profile=\"MY_PROFILE\",  # replace with your profile name\n",
+    "    auth_file_location=\"MY_CONFIG_FILE_LOCATION\",  # replace with file location where profile name configs present\n",
     ")"
    ]
   },
@@ -159,6 +160,7 @@
     "    service_endpoint=\"https://inference.generativeai.us-chicago-1.oci.oraclecloud.com\",\n",
     "    compartment_id=\"DEDICATED_COMPARTMENT_OCID\",\n",
     "    auth_profile=\"MY_PROFILE\",  # replace with your profile name,\n",
+    "    auth_file_location=\"MY_CONFIG_FILE_LOCATION\",  # replace with file location where profile name configs present\n",
     "    provider=\"MODEL_PROVIDER\",  # e.g., \"cohere\" or \"meta\"\n",
     "    context_size=\"MODEL_CONTEXT_SIZE\",  # e.g., 128000\n",
     ")"

docs/docs/integrations/providers/goodfire.mdx

@@ -0,0 +1,14 @@
+# Goodfire
+
+[Goodfire](https://www.goodfire.ai/) is a research lab focused on AI safety and
+interpretability.
+
+## Installation and Setup
+
+```bash
+pip install langchain-goodfire
+```
+
+## Chat models
+
+See detail on available chat models [here](/docs/integrations/chat/goodfire).

docs/docs/integrations/providers/jenkins.mdx

@@ -0,0 +1,17 @@
+# Jenkins
+
+[Jenkins](https://www.jenkins.io/) is an open-source automation platform that enables
+software teams to streamline their development workflows. It's widely adopted in the
+DevOps community as a tool for automating the building, testing, and deployment of
+applications through CI/CD pipelines.
+
+
+## Installation and Setup
+
+```bash
+pip install langchain-jenkins
+```
+
+## Tools
+
+See detail on available tools [here](/docs/integrations/tools/jenkins).

docs/docs/integrations/providers/nimble.ipynb

@@ -0,0 +1,107 @@
+{
+ "cells": [
+  {
+   "cell_type": "raw",
+   "id": "afaf8039",
+   "metadata": {
+    "id": "afaf8039"
+   },
+   "source": [
+    "---\n",
+    "sidebar_label: Nimble\n",
+    "---"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "72ee0c4b-9764-423a-9dbf-95129e185210",
+   "metadata": {
+    "id": "72ee0c4b-9764-423a-9dbf-95129e185210"
+   },
+   "source": [
+    "# Nimble\n",
+    "\n",
+    "  [Nimble](https://www.linkedin.com/company/nimbledata) is the first business external data platform, making data decision-making easier than ever, with our award-winning AI-powered data structuring technology Nimble connects business users with the public web knowledge.\n",
+    "We empower businesses with mission-critical real-time external data to unlock advanced business intelligence, price comparison, and other public data for sales and marketing. We translate data into immediate business value.\n",
+    "\n",
+    "If you'd like to learn more about Nimble, visit us at [nimbleway.com](https://www.nimbleway.com/).\n",
+    "\n",
+    "\n",
+    "## Currently we expose the following components\n",
+    "\n",
+    "*   **Retriever** - Allow us to query the internet and get parsed textual results utilizing several search engines.\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "source": [
+    "## Usage"
+   ],
+   "metadata": {
+    "id": "AuMFgVFrKbNH"
+   },
+   "id": "AuMFgVFrKbNH"
+  },
+  {
+   "cell_type": "markdown",
+   "source": [
+    "In order to use our provider you have to provide an API key like so"
+   ],
+   "metadata": {
+    "id": "sFlPjZX9KdK6"
+   },
+   "id": "sFlPjZX9KdK6"
+  },
+  {
+   "cell_type": "code",
+   "source": [
+    "import getpass\n",
+    "import os\n",
+    "\n",
+    "os.environ[\"NIMBLE_API_KEY\"] = getpass.getpass()"
+   ],
+   "metadata": {
+    "id": "eAqSHZ-Z8R3F"
+   },
+   "id": "eAqSHZ-Z8R3F",
+   "execution_count": null,
+   "outputs": []
+  },
+  {
+   "cell_type": "markdown",
+   "source": [
+    "For more information about the Authentication process, see [Nimble APIs Authentication Documentation](https://docs.nimbleway.com/nimble-sdk/web-api/nimble-web-api-quick-start-guide/nimble-apis-authentication)."
+   ],
+   "metadata": {
+    "id": "WfwnI_RS8PO5"
+   },
+   "id": "WfwnI_RS8PO5"
+  }
+ ],
+ "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"
+  },
+  "colab": {
+   "provenance": []
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

docs/docs/integrations/providers/payman-tool.mdx

@@ -1,4 +1,3 @@
-
 # PaymanAI
 
 PaymanAI provides functionality to send and receive payments (fiat and crypto) on behalf of an AI Agent. To get started:
@@ -24,16 +23,16 @@ These can be wrapped as **LangChain Tools** for an LLM-based agent to call them
 
 | Class | Package | Serializable | JS support | Package latest |
 | :--- | :--- | :---: | :---: | :--- |
-| PaymanAI | `langchain_community` | ❌ | ❌ | [PyPI Version] |
+| PaymanAI | `langchain-payman-tool` | ❌ | ❌ | [PyPI Version] |
 
 If you're simply calling the PaymanAI SDK, you can do it directly or via the **Tool** interface in LangChain.
 
 ## Setup
 
-1. **Install** the `langchain-community` (or equivalent) package:
+1. **Install** the PaymanAI tool package:
 
 ```bash
-pip install --quiet -U langchain-community
+pip install langchain-payman-tool
 ```
 
 2. **Install** the PaymanAI SDK:
@@ -54,7 +53,7 @@ Your `PAYMAN_API_SECRET` should be the secret key from app.paymanai.com. The `PA
 Here is an example of instantiating a PaymanAI tool. If you have multiple Payman methods, you can create multiple tools.
 
 ```python
-from langchain_community.tools.langchain_payman_tool.tool import PaymanAI
+from langchain_payman_tool.tool import PaymanAI
 
 # Instantiate the PaymanAI tool (example)
 tool = PaymanAI(
@@ -104,7 +103,7 @@ You can bind a PaymanAI tool to a LangChain agent or chain that supports tool-ca
 1. **Sign up** at app.paymanai.com to get your **API Key**.
 2. **Install** dependencies:
    ```bash
-   pip install paymanai langchain-community
+   pip install paymanai langchain-payman-tool
    ```
 3. **Export** environment variables:
    ```bash
@@ -112,4 +111,4 @@ You can bind a PaymanAI tool to a LangChain agent or chain that supports tool-ca
    export PAYMAN_ENVIRONMENT="sandbox"
    ```
 4. **Instantiate** a PaymanAI tool, passing your desired name/description.
-5. **Call** the tool with `.invoke(...)` or integrate it into a chain or agent.
+5. **Call** the tool with `.invoke(...)` or integrate it into a chain or agent.

docs/docs/integrations/text_embedding/oci_generative_ai.ipynb

@@ -103,6 +103,7 @@
     "    compartment_id=\"MY_OCID\",\n",
     "    auth_type=\"SECURITY_TOKEN\",\n",
     "    auth_profile=\"MY_PROFILE\",  # replace with your profile name\n",
+    "    auth_file_location=\"MY_CONFIG_FILE_LOCATION\",  # replace with file location where profile name configs present\n",
     ")\n",
     "\n",
     "\n",

docs/docs/integrations/tools/jenkins.ipynb

@@ -0,0 +1,225 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Jenkins\n",
+    "\n",
+    "Tools for interacting with [Jenkins](https://www.jenkins.io/).\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Overview\n",
+    "\n",
+    "The `langchain-jenkins` package allows you to execute and control CI/CD pipelines with\n",
+    "Jenkins."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Setup\n",
+    "\n",
+    "Install `langchain-jenkins`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "vscode": {
+     "languageId": "shellscript"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "%pip install --upgrade --quiet langchain-jenkins"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Credentials\n",
+    "\n",
+    "You'll need to setup or obtain authorization to access Jenkins server."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "vscode": {
+     "languageId": "shellscript"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import getpass\n",
+    "import os\n",
+    "\n",
+    "\n",
+    "def _set_env(var: str):\n",
+    "    if not os.environ.get(var):\n",
+    "        os.environ[var] = getpass.getpass(f\"{var}: \")\n",
+    "\n",
+    "\n",
+    "_set_env(\"PASSWORD\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Instantiation\n",
+    "To disable the SSL Verify, set `os.environ[\"PYTHONHTTPSVERIFY\"] = \"0\"`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain_jenkins import JenkinsAPIWrapper, JenkinsJobRun\n",
+    "\n",
+    "tools = [\n",
+    "    JenkinsJobRun(\n",
+    "        api_wrapper=JenkinsAPIWrapper(\n",
+    "            jenkins_server=\"https://example.com\",\n",
+    "            username=\"admin\",\n",
+    "            password=os.environ[\"PASSWORD\"],\n",
+    "        )\n",
+    "    )\n",
+    "]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Invocation\n",
+    "You can now call invoke and pass arguments."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "1. Create the Jenkins job"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "jenkins_job_content = \"\"\n",
+    "src_file = \"job1.xml\"\n",
+    "with open(src_file) as fread:\n",
+    "    jenkins_job_content = fread.read()\n",
+    "tools[0].invoke({\"job\": \"job01\", \"config_xml\": jenkins_job_content, \"action\": \"create\"})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "2. Run the Jenkins Job"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tools[0].invoke({\"job\": \"job01\", \"parameters\": {}, \"action\": \"run\"})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "3. Get job info"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "resp = tools[0].invoke({\"job\": \"job01\", \"number\": 1, \"action\": \"status\"})\n",
+    "if not resp[\"inProgress\"]:\n",
+    "    print(resp[\"result\"])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "4. Delete the jenkins job"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tools[0].invoke({\"job\": \"job01\", \"action\": \"delete\"})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Chaining\n",
+    "\n",
+    "TODO.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## API reference\n",
+    "\n",
+    "For detailed documentation [API reference](https://python.langchain.com/docs/integrations/tools/jenkins/)"
+   ]
+  }
+ ],
+ "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": "3.9.1"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "3929050b09828356c9f5ebaf862d05c053d8228eddbc70f990c168e54dd824ba"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

docs/docs/integrations/vectorstores/databricks_vector_search.ipynb

@@ -506,7 +506,7 @@
    "source": [
     "## API reference\n",
     "\n",
-    "For detailed documentation of all DatabricksVectorSearch features and configurations head to the API reference: https://python.langchain.com/api_reference/databricks/vectorstores/langchain_databricks.vectorstores.DatabricksVectorSearch.html"
+    "For detailed documentation of all DatabricksVectorSearch features and configurations head to the API reference: https://api-docs.databricks.com/python/databricks-ai-bridge/latest/databricks_langchain.html#databricks_langchain.DatabricksVectorSearch"
    ]
   }
  ],

docs/docs/introduction.mdx

@@ -104,7 +104,7 @@ Head to the reference section for full documentation of all classes and methods
 Trace and evaluate your language model applications and intelligent agents to help you move from prototype to production.
 
 ### [🦜🕸️ LangGraph](https://langchain-ai.github.io/langgraph)
-Build stateful, multi-actor applications with LLMs. Integrates smoothly with LangChain, but can be used without it.
+Build stateful, multi-actor applications with LLMs. Integrates smoothly with LangChain, but can be used without it. LangGraph powers production-grade agents, trusted by Linkedin, Uber, Klarna, GitLab, and many more.
 
 ## Additional resources
 

docs/docusaurus.config.js

@@ -137,6 +137,11 @@ const config = {
         disableSwitch: false,
         respectPrefersColorScheme: true,
       },
+      announcementBar: {
+        content:
+          '<strong>Join us at <a href="https://interrupt.langchain.com/" target="_blank" rel="noopener noreferrer"> Interrupt: The Agent AI Conference by LangChain</a> on May 13 & 14 in San Francisco!</strong>',
+          backgroundColor: '#d0c9fe'
+      },
       prism: {
         theme: {
           ...baseLightCodeBlockTheme,

docs/scripts/execute_notebooks.sh

@@ -1,7 +1,7 @@
 #!/bin/bash
 
 # Read the list of notebooks to skip from the JSON file
-SKIP_NOTEBOOKS=$(python -c "import json; print('\n'.join(json.load(open('docs/notebooks_no_execution.json'))))")
+SKIP_NOTEBOOKS=$(uv run python -c "import json; print('\n'.join(json.load(open('docs/notebooks_no_execution.json'))))")
 
 # Get the working directory or specific notebook file from the input parameter
 WORKING_DIRECTORY=$1
@@ -13,7 +13,7 @@ execute_notebook() {
     total="$3"
     echo "Starting execution of $file ($index/$total)"
     start_time=$(date +%s)
-    if ! output=$(time poetry run jupyter nbconvert --to notebook --execute --ExecutePreprocessor.kernel_name=python3 $file 2>&1); then
+    if ! output=$(time uv run --group dev --group test jupyter nbconvert --to notebook --execute --ExecutePreprocessor.kernel_name=python3 $file 2>&1); then
         end_time=$(date +%s)
         execution_time=$((end_time - start_time))
         echo "Error in $file. Execution time: $execution_time seconds"

docs/scripts/update_cassettes.sh

@@ -12,7 +12,7 @@
 # modifications should be discarded after the cassettes are generated.
 #
 # Usage:
-# In monorepo env, `poetry install --with dev,test`
+# In monorepo env, `uv sync --group dev --group test`
 # `./docs/scripts/update_cassettes.sh path/to/notebook`
 # e.g., `./docs/scripts/update_cassettes.sh docs/docs/how_to/tool_choice.ipynb`
 #
@@ -41,11 +41,11 @@ delete_cassettes "$WORKING_DIRECTORY"
 
 # Pre-download tiktoken files
 echo "Pre-downloading nltk and tiktoken files..."
-poetry run python docs/scripts/cache_data.py
+uv run python docs/scripts/cache_data.py
 
 # Prepare notebooks
 echo "Preparing notebooks for CI..."
-poetry run python docs/scripts/prepare_notebooks_for_ci.py --comment-install-cells --working-directory "$WORKING_DIRECTORY"
+uv run python docs/scripts/prepare_notebooks_for_ci.py --comment-install-cells --working-directory "$WORKING_DIRECTORY"
 
 # Run notebooks
 echo "Running notebooks..."

docs/src/theme/ChatModelTabs.js

@@ -121,7 +121,7 @@ export const CustomDropdown = ({ selectedOption, options, onSelect, modelType })
  * @param {ChatModelTabsProps} props - Component props.
  */
 export default function ChatModelTabs(props) {
-  const [selectedModel, setSelectedModel] = useState("OpenAI");
+  const [selectedModel, setSelectedModel] = useState("Groq");
   const {
     openaiParams,
     anthropicParams,
@@ -174,13 +174,20 @@ export default function ChatModelTabs(props) {
   const llmVarName = customVarName ?? "model";
 
   const tabItems = [
+    {
+      value: "Groq",
+      label: "Groq",
+      text: `from langchain_groq import ChatGroq\n\n${llmVarName} = ChatGroq(${groqParamsOrDefault})`,
+      apiKeyName: "GROQ_API_KEY",
+      packageName: "langchain-groq",
+      shouldHide: hideGroq,
+    },
     {
       value: "OpenAI",
       label: "OpenAI",
       text: `from langchain_openai import ChatOpenAI\n\n${llmVarName} = ChatOpenAI(${openAIParamsOrDefault})`,
       apiKeyName: "OPENAI_API_KEY",
       packageName: "langchain-openai",
-      default: true,
       shouldHide: hideOpenai,
     },
     {
@@ -189,7 +196,6 @@ export default function ChatModelTabs(props) {
       text: `from langchain_anthropic import ChatAnthropic\n\n${llmVarName} = ChatAnthropic(${anthropicParamsOrDefault})`,
       apiKeyName: "ANTHROPIC_API_KEY",
       packageName: "langchain-anthropic",
-      default: false,
       shouldHide: hideAnthropic,
     },
     {
@@ -198,7 +204,6 @@ export default function ChatModelTabs(props) {
       text: `from langchain_openai import AzureChatOpenAI\n\n${llmVarName} = AzureChatOpenAI(${azureParamsOrDefault})`,
       apiKeyName: "AZURE_OPENAI_API_KEY",
       packageName: "langchain-openai",
-      default: false,
       shouldHide: hideAzure,
     },
     {
@@ -207,7 +212,6 @@ export default function ChatModelTabs(props) {
       text: `from langchain_google_vertexai import ChatVertexAI\n\n${llmVarName} = ChatVertexAI(${googleParamsOrDefault})`,
       apiKeyText: "# Ensure your VertexAI credentials are configured",
       packageName: "langchain-google-vertexai",
-      default: false,
       shouldHide: hideGoogle,
     },
     {
@@ -216,7 +220,6 @@ export default function ChatModelTabs(props) {
       text: `from langchain_aws import ChatBedrock\n\n${llmVarName} = ChatBedrock(${awsBedrockParamsOrDefault})`,
       apiKeyText: "# Ensure your AWS credentials are configured",
       packageName: "langchain-aws",
-      default: false,
       shouldHide: hideAWS,
     },
     {
@@ -225,7 +228,6 @@ export default function ChatModelTabs(props) {
       text: `from langchain_cohere import ChatCohere\n\n${llmVarName} = ChatCohere(${cohereParamsOrDefault})`,
       apiKeyName: "COHERE_API_KEY",
       packageName: "langchain-cohere",
-      default: false,
       shouldHide: hideCohere,
     },
     {
@@ -234,7 +236,6 @@ export default function ChatModelTabs(props) {
       text: `from langchain_nvidia_ai_endpoints import ChatNVIDIA\n\n${llmVarName} = ChatNVIDIA(${nvidiaParamsOrDefault})`,
       apiKeyName: "NVIDIA_API_KEY",
       packageName: "langchain-nvidia-ai-endpoints",
-      default: false,
       shouldHide: hideNvidia,
     },
     {
@@ -243,25 +244,14 @@ export default function ChatModelTabs(props) {
       text: `from langchain_fireworks import ChatFireworks\n\n${llmVarName} = ChatFireworks(${fireworksParamsOrDefault})`,
       apiKeyName: "FIREWORKS_API_KEY",
       packageName: "langchain-fireworks",
-      default: false,
       shouldHide: hideFireworks,
     },
-    {
-      value: "Groq",
-      label: "Groq",
-      text: `from langchain_groq import ChatGroq\n\n${llmVarName} = ChatGroq(${groqParamsOrDefault})`,
-      apiKeyName: "GROQ_API_KEY",
-      packageName: "langchain-groq",
-      default: false,
-      shouldHide: hideGroq,
-    },
     {
       value: "MistralAI",
       label: "Mistral AI",
       text: `from langchain_mistralai import ChatMistralAI\n\n${llmVarName} = ChatMistralAI(${mistralParamsOrDefault})`,
       apiKeyName: "MISTRAL_API_KEY",
       packageName: "langchain-mistralai",
-      default: false,
       shouldHide: hideMistral,
     },
     {
@@ -270,7 +260,6 @@ export default function ChatModelTabs(props) {
       text: `from langchain_openai import ChatOpenAI\n\n${llmVarName} = ChatOpenAI(${togetherParamsOrDefault})`,
       apiKeyName: "TOGETHER_API_KEY",
       packageName: "langchain-openai",
-      default: false,
       shouldHide: hideTogether,
     },
     {
@@ -279,7 +268,6 @@ export default function ChatModelTabs(props) {
       text: `from databricks_langchain import ChatDatabricks\n\nos.environ["DATABRICKS_HOST"] = "https://example.staging.cloud.databricks.com/serving-endpoints"\n\n${llmVarName} = ChatDatabricks(${databricksParamsOrDefault})`,
       apiKeyName: "DATABRICKS_TOKEN",
       packageName: "databricks-langchain",
-      default: false,
       shouldHide: hideDatabricks,
     },
   ];

docs/src/theme/FeatureTables.js

@@ -27,7 +27,6 @@ const FEATURE_TABLES = {
                 "multimodal": true,
                 "local": false,
                 "apiLink": "https://python.langchain.com/api_reference/anthropic/chat_models/langchain_anthropic.chat_models.ChatAnthropic.html"
-                
             },
             {
                 "name": "ChatMistralAI",
@@ -200,21 +199,21 @@ const FEATURE_TABLES = {
                 "link": "upstage",
                 "structured_output": true,
                 "tool_calling": true,
-                "json_mode": false, 
+                "json_mode": false,
                 "multimodal": false,
                 "local": false,
                 "apiLink": "https://python.langchain.com/api_reference/upstage/chat_models/langchain_upstage.chat_models.ChatUpstage.html"
             },
             {
                 "name": "ChatDatabricks",
-                "package": "langchain-databricks",
+                "package": "databricks-langchain",
                 "link": "databricks",
                 "structured_output": true,
                 "tool_calling": true,
-                "json_mode": false, 
+                "json_mode": false,
                 "multimodal": false,
                 "local": false,
-                "apiLink": "https://python.langchain.com/api_reference/upstage/chat_models/langchain_databricks.chat_models.ChatDatabricks.html"
+                "apiLink": "https://api-docs.databricks.com/python/databricks-ai-bridge/latest/databricks_langchain.html#databricks_langchain.ChatDatabricks"
             },
             {
                 "name": "ChatWatsonx",
@@ -222,7 +221,7 @@ const FEATURE_TABLES = {
                 "link": "ibm_watsonx",
                 "structured_output": true,
                 "tool_calling": true,
-                "json_mode": true, 
+                "json_mode": true,
                 "multimodal": false,
                 "local": false,
                 "apiLink": "https://python.langchain.com/api_reference/ibm/chat_models/langchain_ibm.chat_models.ChatWatsonx.html"
@@ -389,8 +388,8 @@ const FEATURE_TABLES = {
             {
                 name: "Databricks",
                 link: "databricks",
-                package: "langchain-databricks",
-                apiLink: "https://python.langchain.com/api_reference/nomic/embeddings/langchain_databricks.embeddings.DatabricksEmbeddings.html"
+                package: "databricks-langchain",
+                apiLink: "https://api-docs.databricks.com/python/databricks-ai-bridge/latest/databricks_langchain.html#databricks_langchain.DatabricksEmbeddings"
             },
             {
                 name: "VoyageAI",
@@ -620,7 +619,6 @@ const FEATURE_TABLES = {
                 partnerPackage: false,
                 loaderName: "SharePointLoader",
                 apiLink: "https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.sharepoint.SharePointLoader.html"
-                
             },
             {
                 name: "Tencent COS Directory",
@@ -754,7 +752,6 @@ const FEATURE_TABLES = {
                 link: "twitter",
                 loaderName: "TwitterTweetLoader",
                 apiLink: "https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.twitter.TwitterTweetLoader.html"
-                
             },
             {
                 name: "Reddit",
@@ -1185,7 +1182,7 @@ const FEATURE_TABLES = {
                 multiTenancy: false,
                 local: false,
                 idsInAddDocuments: false,
-            }, 
+            },
         ],
     }
 };

docs/vercel.json

@@ -137,6 +137,10 @@
     {
       "source": "/api_reference/mongodb/:path(.*/?)*",
       "destination": "https://langchain-mongodb.readthedocs.io/en/latest/langchain_mongodb/api_docs.html"
+    },
+    {
+      "source": "/api_reference/tests/:path(.*/?)*",
+      "destination": "/api_reference/standard_tests/:path"
     }
   ]
 }

libs/cli/Makefile

@@ -3,6 +3,9 @@
 # LINTING AND FORMATTING
 ######################
 
+.EXPORT_ALL_VARIABLES:
+UV_FROZEN = true
+
 # Define a variable for Python and notebook files.
 PYTHON_FILES=.
 MYPY_CACHE=.mypy_cache
@@ -13,20 +16,20 @@ lint_tests: PYTHON_FILES=tests
 lint_tests: MYPY_CACHE=.mypy_cache_test
 
 lint lint_diff lint_package lint_tests:
-	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff check $(PYTHON_FILES)
-	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) --diff
-	[ "$(PYTHON_FILES)" = "" ] || mkdir -p $(MYPY_CACHE) && poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE)
+	[ "$(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)" = "" ] || poetry run ruff format $(PYTHON_FILES)
-	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff check --select I --fix $(PYTHON_FILES)
+	[ "$(PYTHON_FILES)" = "" ] || uv run --group typing --group lint ruff format $(PYTHON_FILES)
+	[ "$(PYTHON_FILES)" = "" ] || uv run --group typing --group lint ruff check --select I --fix $(PYTHON_FILES)
 
 test tests: _test _e2e_test
 
 PYTHON = .venv/bin/python
 
 _test:
-	poetry run pytest tests
+	uv run --group test pytest tests
 
 # custom integration testing for cli integration flow
 # currently ignores vectorstores test because lacks implementation
@@ -35,7 +38,7 @@ _e2e_test:
 	mkdir .integration_test
 	cd .integration_test && \
 		python3 -m venv .venv && \
-		$(PYTHON) -m pip install --upgrade poetry && \
+		pip install --upgrade poetry && \
 		$(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 && \

libs/cli/pyproject.toml

@@ -1,48 +1,52 @@
-[tool.poetry]
+[build-system]
+requires = ["pdm-backend"]
+build-backend = "pdm.backend"
+
+[project]
+authors = [
+    {name = "Erick Friis", email = "erick@langchain.dev"},
+]
+license = {text = "MIT"}
+requires-python = "<4.0,>=3.9"
+dependencies = [
+    "typer[all]<1.0.0,>=0.9.0",
+    "gitpython<4,>=3",
+    "langserve[all]>=0.0.51",
+    "uvicorn<1.0,>=0.23",
+    "tomlkit>=0.12",
+    "gritql<1.0.0,>=0.2.0",
+]
 name = "langchain-cli"
 version = "0.0.35"
 description = "CLI for interacting with LangChain"
-authors = ["Erick Friis <erick@langchain.dev>"]
 readme = "README.md"
-repository = "https://github.com/langchain-ai/langchain"
-license = "MIT"
 
-[tool.poetry.urls]
+[project.urls]
 "Source Code" = "https://github.com/langchain-ai/langchain/tree/master/libs/cli"
 "Release Notes" = "https://github.com/langchain-ai/langchain/releases?q=tag%3A%22langchain-cli%3D%3D0%22&expanded=true"
+repository = "https://github.com/langchain-ai/langchain"
 
-[tool.poetry.dependencies]
-python = ">=3.9,<4.0"
-typer = { extras = ["all"], version = "^0.9.0" }
-gitpython = "^3"
-langserve = { extras = ["all"], version = ">=0.0.51" }
-uvicorn = ">=0.23,<1.0"
-tomlkit = ">=0.12"
-gritql = "^0.2.0"
-
-[tool.poetry.scripts]
+[project.scripts]
 langchain = "langchain_cli.cli:app"
 langchain-cli = "langchain_cli.cli:app"
 
-[tool.poetry.group.dev.dependencies]
-pytest = "^7.4.2"
-pytest-watch = "^4.2.0"
+[dependency-groups]
+dev = [
+    "pytest<8.0.0,>=7.4.2",
+    "pytest-watch<5.0.0,>=4.2.0",
+]
+lint = [
+    "ruff<1.0,>=0.5",
+    "mypy<2.0.0,>=1.13.0",
+]
+test = [
+    "langchain @ file:///${PROJECT_ROOT}/../langchain",
+]
+typing = [
+    "langchain @ file:///${PROJECT_ROOT}/../langchain",
+]
+test_integration = []
 
-[tool.poetry.group.lint.dependencies]
-ruff = "^0.5"
-mypy = "^1.13.0"
-
-[tool.poetry.group.test.dependencies]
-langchain = {path = "../langchain", develop = true}
-
-[tool.poetry.group.typing.dependencies]
-langchain = {path = "../langchain", develop = true}
-
-[tool.poetry.group.test_integration.dependencies]
-
-[tool.poetry.extras]
-# For langserve
-serve = []
 
 [tool.ruff.lint]
 select = [
@@ -57,7 +61,3 @@ exclude = [
   "langchain_cli/integration_template",
   "langchain_cli/package_template",
 ]
-
-[build-system]
-requires = ["poetry-core"]
-build-backend = "poetry.core.masonry.api"

libs/community/Makefile

@@ -7,28 +7,31 @@ all: help
 TEST_FILE ?= tests/unit_tests/
 integration_tests: TEST_FILE = tests/integration_tests/
 
+.EXPORT_ALL_VARIABLES:
+UV_FROZEN = true
+
 # Run unit tests and generate a coverage report.
 coverage:
-	poetry run pytest --cov \
+	uv run --group test pytest --cov \
 		--cov-config=.coveragerc \
 		--cov-report xml \
 		--cov-report term-missing:skip-covered \
 		$(TEST_FILE)
 
 test tests:
-	poetry run pytest -n auto --disable-socket --allow-unix-socket $(TEST_FILE)
+	uv run --group test pytest -n auto --disable-socket --allow-unix-socket $(TEST_FILE)
 
 integration_tests:
-	poetry run pytest $(TEST_FILE)
+	uv run --group test --group test_integration pytest $(TEST_FILE)
 
 test_watch:
-	poetry run ptw --disable-socket --allow-unix-socket --snapshot-update --now . -- -vv tests/unit_tests
+	uv run --group test ptw --disable-socket --allow-unix-socket --snapshot-update --now . -- -vv tests/unit_tests
 
 check_imports: $(shell find langchain_community -name '*.py')
-	poetry run python ./scripts/check_imports.py $^
+	uv run --group test python ./scripts/check_imports.py $^
 
 extended_tests:
-	poetry run pytest --disable-socket --allow-unix-socket --only-extended tests/unit_tests
+	uv run --no-sync --group test pytest --disable-socket --allow-unix-socket --only-extended tests/unit_tests
 
 
 ######################
@@ -48,19 +51,19 @@ lint lint_diff lint_package lint_tests:
 	./scripts/check_pydantic.sh .
 	./scripts/lint_imports.sh .
 	./scripts/check_pickle.sh .
-	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff check $(PYTHON_FILES)
-	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) --diff
-	[ "$(PYTHON_FILES)" = "" ] || mkdir -p $(MYPY_CACHE) && poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE)
+	[ "$(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)" = "" ] || poetry run ruff format $(PYTHON_FILES)
-	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff check --select I --fix $(PYTHON_FILES)
+	[ "$(PYTHON_FILES)" = "" ] || uv run --group typing --group lint ruff format $(PYTHON_FILES)
+	[ "$(PYTHON_FILES)" = "" ] || uv run --group typing --group lint ruff check --select I --fix $(PYTHON_FILES)
 
 spell_check:
-	poetry run codespell --toml pyproject.toml
+	uv run --group typing --group lint codespell --toml pyproject.toml
 
 spell_fix:
-	poetry run codespell --toml pyproject.toml -w
+	uv run --group typing --group lint codespell --toml pyproject.toml -w
 
 ######################
 # HELP

libs/community/extended_testing_deps.txt

@@ -59,7 +59,7 @@ openapi-pydantic>=0.3.2,<0.4
 oracle-ads>=2.9.1,<3
 oracledb>=2.2.0,<3
 pandas>=2.0.1,<3
-pdfminer-six>=20221105,<20240706
+pdfminer-six==20231228
 pdfplumber>=0.11
 pgvector>=0.1.6,<0.2
 playwright>=1.48.0,<2
@@ -104,3 +104,5 @@ mlflow[genai]>=2.14.0
 databricks-sdk>=0.30.0
 websocket>=0.2.1,<1
 writer-sdk>=1.2.0
+yandexcloud==0.144.0
+unstructured[pdf]>=0.15

libs/community/langchain_community/callbacks/openai_info.py

@@ -10,6 +10,22 @@ from langchain_core.messages import AIMessage
 from langchain_core.outputs import ChatGeneration, LLMResult
 
 MODEL_COST_PER_1K_TOKENS = {
+    # OpenAI o1 input
+    "o1": 0.015,
+    "o1-2024-12-17": 0.015,
+    "o1-cached": 0.0075,
+    "o1-2024-12-17-cached": 0.0075,
+    # OpenAI o1 output
+    "o1-completion": 0.06,
+    "o1-2024-12-17-completion": 0.06,
+    # OpenAI o3-mini input
+    "o3-mini": 0.0011,
+    "o3-mini-2025-01-31": 0.0011,
+    "o3-mini-cached": 0.00055,
+    "o3-mini-2025-01-31-cached": 0.00055,
+    # OpenAI o3-mini output
+    "o3-mini-completion": 0.0044,
+    "o3-mini-2025-01-31-completion": 0.0044,
     # OpenAI o1-preview input
     "o1-preview": 0.015,
     "o1-preview-cached": 0.0075,

libs/community/langchain_community/chat_models/databricks.py

@@ -11,7 +11,7 @@ logger = logging.getLogger(__name__)
 @deprecated(
     since="0.3.3",
     removal="1.0",
-    alternative_import="langchain_databricks.ChatDatabricks",
+    alternative_import="databricks_langchain.ChatDatabricks",
 )
 class ChatDatabricks(ChatMlflow):
     """`Databricks` chat models API.

libs/community/langchain_community/chat_models/oci_generative_ai.py

@@ -539,6 +539,8 @@ class ChatOCIGenAI(BaseChatModel, OCIGenAIBase):
             The authentication type to use, e.g., API_KEY (default), SECURITY_TOKEN, INSTANCE_PRINCIPAL, RESOURCE_PRINCIPAL.
         auth_profile: Optional[str]
             The name of the profile in ~/.oci/config, if not specified , DEFAULT will be used.
+        auth_file_location: Optional[str]
+            Path to the config file, If not specified, ~/.oci/config will be used.
         provider: str
             Provider name of the model. Default to None, will try to be derived from the model_id otherwise, requires user input.
     See full list of supported init args and their descriptions in the params section.