docs: Adds the langchain-neo4j package to the API docs (#28386)

This PR adds the `langchain-neo4j` package to the `libs/packages.yml` so
the API docs can be built.

.github/scripts/check_diff.py

@@ -32,18 +32,8 @@ IGNORED_PARTNERS = [
     "huggingface",
 ]
 
-# Cap python version at 3.12 for some packages with dependencies that are not yet
-# compatible with python 3.13 (mostly hf tokenizers).
 PY_312_MAX_PACKAGES = [
-    f"libs/partners/{integration}"
-    for integration in [
-        "chroma",
-        "couchbase",
-        "huggingface",
-        "mistralai",
-        "nomic",
-        "qdrant",
-    ]
+    "libs/partners/huggingface",  # https://github.com/pytorch/pytorch/issues/130249
 ]
 
 
@@ -134,10 +124,11 @@ def _get_configs_for_single_dir(job: str, dir_: str) -> List[Dict[str, str]]:
     elif dir_ in PY_312_MAX_PACKAGES:
         py_versions = ["3.9", "3.12"]
 
-    elif dir_ in ["libs/community", "libs/langchain"] and job == "extended-tests":
-        # community extended test resolution in 3.12 is slow
-        # even in uv
-        py_versions = ["3.9", "3.11"]
+    elif dir_ == "libs/langchain" and job == "extended-tests":
+        py_versions = ["3.9", "3.13"]
+
+    elif dir_ == "libs/community" and job == "extended-tests":
+        py_versions = ["3.9", "3.12"]
 
     elif dir_ == "libs/community" and job == "compile-integration-tests":
         # community integration deps are slow in 3.12

.github/scripts/get_min_versions.py

@@ -23,6 +23,7 @@ MIN_VERSION_LIBS = [
     "langchain-community",
     "langchain",
     "langchain-text-splitters",
+    "numpy",
     "SQLAlchemy",
 ]
 

.github/scripts/prep_api_docs_build.py

@@ -23,24 +23,19 @@ def get_target_dir(package_name: str) -> Path:
     return base_path / "partners" / package_name_short
 
 
-def clean_target_directories(packages: Dict[str, Any]) -> None:
+def clean_target_directories(packages: list) -> None:
     """Remove old directories that will be replaced."""
-    for package in packages["packages"]:
-        if package["repo"] != "langchain-ai/langchain":
-            target_dir = get_target_dir(package["name"])
-            if target_dir.exists():
-                print(f"Removing {target_dir}")
-                shutil.rmtree(target_dir)
+    for package in packages:
+
+        target_dir = get_target_dir(package["name"])
+        if target_dir.exists():
+            print(f"Removing {target_dir}")
+            shutil.rmtree(target_dir)
 
 
-def move_libraries(packages: Dict[str, Any]) -> None:
+def move_libraries(packages: list) -> None:
     """Move libraries from their source locations to the target directories."""
-    for package in packages["packages"]:
-        # Skip if it's the main langchain repo or disabled
-        if package["repo"] == "langchain-ai/langchain" or package.get(
-            "disabled", False
-        ):
-            continue
+    for package in packages:
 
         repo_name = package["repo"].split("/")[1]
         source_path = package["path"]
@@ -68,7 +63,14 @@ def main():
     """Main function to orchestrate the library sync process."""
     try:
         # Load packages configuration
-        packages = load_packages_yaml()
+        package_yaml = load_packages_yaml()
+        packages = [
+            p
+            for p in package_yaml["packages"]
+            if not p.get("disabled", False)
+            and p["repo"].startswith("langchain-ai/")
+            and p["repo"] != "langchain-ai/langchain"
+        ]
 
         # Clean target directories
         clean_target_directories(packages)

.github/workflows/_release_docker.yml

@@ -1,62 +0,0 @@
-name: release_docker
-
-on:
-  workflow_call:
-    inputs:
-      dockerfile:
-        required: true
-        type: string
-        description: "Path to the Dockerfile to build"
-      image:
-        required: true
-        type: string
-        description: "Name of the image to build"
-
-env:
-  TEST_TAG: ${{ inputs.image }}:test
-  LATEST_TAG: ${{ inputs.image }}:latest
-
-jobs:
-  docker:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout
-        uses: actions/checkout@v4
-      - name: Get git tag
-        uses: actions-ecosystem/action-get-latest-tag@v1
-        id: get-latest-tag
-      - name: Set docker tag
-        env:
-          VERSION: ${{ steps.get-latest-tag.outputs.tag }}
-        run: |
-          echo "VERSION_TAG=${{ inputs.image }}:${VERSION#v}" >> $GITHUB_ENV
-      - name: Set up QEMU
-        uses: docker/setup-qemu-action@v3
-      - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v3
-      - name: Login to Docker Hub
-        uses: docker/login-action@v3
-        with:
-          username: ${{ secrets.DOCKERHUB_USERNAME }}
-          password: ${{ secrets.DOCKERHUB_TOKEN }}
-      - name: Build for Test
-        uses: docker/build-push-action@v5
-        with:
-          context: .
-          file: ${{ inputs.dockerfile }}
-          load: true
-          tags: ${{ env.TEST_TAG }}
-      - name: Test
-        run: |
-          docker run --rm ${{ env.TEST_TAG }} python -c "import langchain"
-      - name: Build and Push to Docker Hub
-        uses: docker/build-push-action@v5
-        with:
-          context: .
-          file: ${{ inputs.dockerfile }}
-          # We can only build for the intersection of platforms supported by
-          # QEMU and base python image, for now build only for
-          # linux/amd64 and linux/arm64
-          platforms: linux/amd64,linux/arm64
-          tags: ${{ env.LATEST_TAG }},${{ env.VERSION_TAG }}
-          push: true

.github/workflows/api_doc_build.yml

@@ -37,9 +37,9 @@ jobs:
           # Get unique repositories
           REPOS=$(echo "$REPOS_UNSORTED" | sort -u)
           
-          # Checkout each unique repository
+          # Checkout each unique repository that is in langchain-ai org
           for repo in $REPOS; do
-            if [ "$repo" != "langchain-ai/langchain" ]; then
+            if [[ "$repo" != "langchain-ai/langchain" && "$repo" == langchain-ai/* ]]; then
               REPO_NAME=$(echo $repo | cut -d'/' -f2)
               echo "Checking out $repo to $REPO_NAME"
               git clone --depth 1 https://github.com/$repo.git $REPO_NAME
@@ -73,7 +73,7 @@ jobs:
         working-directory: langchain
         run: |
           python -m uv pip install $(ls ./libs/partners | xargs -I {} echo "./libs/partners/{}")
-          python -m uv pip install libs/core libs/langchain libs/text-splitters libs/community libs/experimental
+          python -m uv pip install libs/core libs/langchain libs/text-splitters libs/community libs/experimental libs/standard-tests
           python -m uv pip install -r docs/api_reference/requirements.txt
 
       - name: Set Git config

.github/workflows/langchain_release_docker.yml

@@ -1,14 +0,0 @@
----
-name: docker/langchain/langchain Release
-
-on:
-  workflow_dispatch: # Allows to trigger the workflow manually in GitHub UI
-  workflow_call: # Allows triggering from another workflow
-
-jobs:
-  release:
-    uses: ./.github/workflows/_release_docker.yml
-    with:
-      dockerfile: docker/Dockerfile.base
-      image: langchain/langchain
-    secrets: inherit

README.md

@@ -129,7 +129,7 @@ Please see [here](https://python.langchain.com) for full documentation, which in
 
 - [🦜🛠️ LangSmith](https://docs.smith.langchain.com/): Trace and evaluate your language model applications and intelligent agents to help you move from prototype to production.
 - [🦜🕸️ LangGraph](https://langchain-ai.github.io/langgraph/): Create stateful, multi-actor applications with LLMs. Integrates smoothly with LangChain, but can be used without it.
-- [🦜🏓 LangServe](https://python.langchain.com/docs/langserve): Deploy LangChain runnables and chains as REST APIs.
+- [🦜🕸️ LangGraph Platform](https://langchain-ai.github.io/langgraph/concepts/#langgraph-platform): Deploy LLM applications built with LangGraph into production.
 
 ## 💁 Contributing
 

cookbook/README.md

@@ -63,4 +63,5 @@ Notebook | Description
 [oracleai_demo.ipynb](https://github.com/langchain-ai/langchain/tree/master/cookbook/oracleai_demo.ipynb) | This guide outlines how to utilize Oracle AI Vector Search alongside Langchain for an end-to-end RAG pipeline, providing step-by-step examples. The process includes loading documents from various sources using OracleDocLoader, summarizing them either within or outside the database with OracleSummary, and generating embeddings similarly through OracleEmbeddings. It also covers chunking documents according to specific requirements using Advanced Oracle Capabilities from OracleTextSplitter, and finally, storing and indexing these documents in a Vector Store for querying with OracleVS.
 [rag-locally-on-intel-cpu.ipynb](https://github.com/langchain-ai/langchain/tree/master/cookbook/rag-locally-on-intel-cpu.ipynb) | Perform Retrieval-Augmented-Generation (RAG) on locally downloaded open-source models using langchain and open source tools and execute it on Intel Xeon CPU. We showed an example of how to apply RAG on Llama 2 model and enable it to answer the queries related to Intel Q1 2024 earnings release.
 [visual_RAG_vdms.ipynb](https://github.com/langchain-ai/langchain/tree/master/cookbook/visual_RAG_vdms.ipynb) | Performs Visual Retrieval-Augmented-Generation (RAG) using videos and scene descriptions generated by open source models.
-[contextual_rag.ipynb](https://github.com/langchain-ai/langchain/tree/master/cookbook/contextual_rag.ipynb) | Performs contextual retrieval-augmented generation (RAG) prepending chunk-specific explanatory context to each chunk before embedding.
+[contextual_rag.ipynb](https://github.com/langchain-ai/langchain/tree/master/cookbook/contextual_rag.ipynb) | Performs contextual retrieval-augmented generation (RAG) prepending chunk-specific explanatory context to each chunk before embedding.
+[rag-agents-locally-on-intel-cpu.ipynb](https://github.com/langchain-ai/langchain/tree/master/cookbook/local_rag_agents_intel_cpu.ipynb) | Build a RAG agent locally with open source models that routes questions through one of two paths to find answers. The agent generates answers based on documents retrieved from either the vector database or retrieved from web search. If the vector database lacks relevant information, the agent opts for web search. Open-source models for LLM and embeddings are used locally on an Intel Xeon CPU to execute this pipeline.

docker/Dockerfile.base

@@ -1,3 +0,0 @@
-FROM python:3.11
-
-RUN pip install langchain

docker/Makefile

@@ -1,12 +0,0 @@
-# Makefile
-
-build_graphdb:
-	docker build --tag graphdb ./graphdb
-
-start_graphdb:
-	docker-compose up -d graphdb
-
-down:
-	docker-compose down -v --remove-orphans
-
-.PHONY: build_graphdb start_graphdb down

docker/docker-compose.yml

@@ -1,84 +0,0 @@
-# docker-compose to make it easier to spin up integration tests.
-# Services should use NON standard ports to avoid collision with
-# any existing services that might be used for development.
-# ATTENTION: When adding a service below use a non-standard port
-# increment by one from the preceding port.
-# For credentials always use `langchain` and `langchain` for the
-# username and password.
-version: "3"
-name: langchain-tests
-
-services:
-  redis:
-    image: redis/redis-stack-server:latest
-    # We use non standard ports since
-    # these instances are used for testing
-    # and users may already have existing
-    # redis instances set up locally
-    # for other projects
-    ports:
-      - "6020:6379"
-    volumes:
-      - ./redis-volume:/data
-  graphdb:
-    image: graphdb
-    ports:
-      - "6021:7200"
-  mongo:
-    image: mongo:latest
-    container_name: mongo_container
-    ports:
-      - "6022:27017"
-    environment:
-      MONGO_INITDB_ROOT_USERNAME: langchain
-      MONGO_INITDB_ROOT_PASSWORD: langchain
-  postgres:
-    image: postgres:16
-    environment:
-      POSTGRES_DB: langchain
-      POSTGRES_USER: langchain
-      POSTGRES_PASSWORD: langchain
-    ports:
-      - "6023:5432"
-    command: |
-      postgres -c log_statement=all
-    healthcheck:
-      test:
-        [
-          "CMD-SHELL",
-          "psql postgresql://langchain:langchain@localhost/langchain --command 'SELECT 1;' || exit 1",
-        ]
-      interval: 5s
-      retries: 60
-    volumes:
-      - postgres_data:/var/lib/postgresql/data
-  pgvector:
-    # postgres with the pgvector extension
-    image: ankane/pgvector
-    environment:
-      POSTGRES_DB: langchain
-      POSTGRES_USER: langchain
-      POSTGRES_PASSWORD: langchain
-    ports:
-      - "6024:5432"
-    command: |
-      postgres -c log_statement=all
-    healthcheck:
-      test:
-        [
-          "CMD-SHELL",
-          "psql postgresql://langchain:langchain@localhost/langchain --command 'SELECT 1;' || exit 1",
-        ]
-      interval: 5s
-      retries: 60
-    volumes:
-      - postgres_data_pgvector:/var/lib/postgresql/data
-  vdms:
-    image: intellabs/vdms:latest
-    container_name: vdms_container
-    ports:
-      - "6025:55555"
-
-volumes:
-  postgres_data:
-  postgres_data_pgvector:

docker/graphdb/Dockerfile

@@ -1,5 +0,0 @@
-FROM ontotext/graphdb:10.5.1
-RUN mkdir -p /opt/graphdb/dist/data/repositories/langchain
-COPY config.ttl /opt/graphdb/dist/data/repositories/langchain/
-COPY graphdb_create.sh /run.sh
-ENTRYPOINT bash /run.sh

docker/graphdb/config.ttl

@@ -1,46 +0,0 @@
-@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#>.
-@prefix rep: <http://www.openrdf.org/config/repository#>.
-@prefix sr: <http://www.openrdf.org/config/repository/sail#>.
-@prefix sail: <http://www.openrdf.org/config/sail#>.
-@prefix graphdb: <http://www.ontotext.com/config/graphdb#>.
-
-[] a rep:Repository ;
-    rep:repositoryID "langchain" ;
-    rdfs:label "" ;
-    rep:repositoryImpl [
-        rep:repositoryType "graphdb:SailRepository" ;
-        sr:sailImpl [
-            sail:sailType "graphdb:Sail" ;
-
-            graphdb:read-only "false" ;
-
-            # Inference and Validation
-            graphdb:ruleset "empty" ;
-            graphdb:disable-sameAs "true" ;
-            graphdb:check-for-inconsistencies "false" ;
-
-            # Indexing
-            graphdb:entity-id-size "32" ;
-            graphdb:enable-context-index "false" ;
-            graphdb:enablePredicateList "true" ;
-            graphdb:enable-fts-index "false" ;
-            graphdb:fts-indexes ("default" "iri") ;
-            graphdb:fts-string-literals-index "default" ;
-            graphdb:fts-iris-index "none" ;
-
-            # Queries and Updates
-            graphdb:query-timeout "0" ;
-            graphdb:throw-QueryEvaluationException-on-timeout "false" ;
-            graphdb:query-limit-results "0" ;
-
-            # Settable in the file but otherwise hidden in the UI and in the RDF4J console
-            graphdb:base-URL "http://example.org/owlim#" ;
-            graphdb:defaultNS "" ;
-            graphdb:imports "" ;
-            graphdb:repository-type "file-repository" ;
-            graphdb:storage-folder "storage" ;
-            graphdb:entity-index-size "10000000" ;
-            graphdb:in-memory-literal-properties "true" ;
-            graphdb:enable-literal-index "true" ;
-        ]
-    ].

docker/graphdb/graphdb_create.sh

@@ -1,28 +0,0 @@
-#! /bin/bash
-REPOSITORY_ID="langchain"
-GRAPHDB_URI="http://localhost:7200/"
-
-echo -e "\nUsing GraphDB: ${GRAPHDB_URI}"
-
-function startGraphDB {
- echo -e "\nStarting GraphDB..."
- exec /opt/graphdb/dist/bin/graphdb
-}
-
-function waitGraphDBStart {
-  echo -e "\nWaiting GraphDB to start..."
-  for _ in $(seq 1 5); do
-    CHECK_RES=$(curl --silent --write-out '%{http_code}' --output /dev/null ${GRAPHDB_URI}/rest/repositories)
-    if [ "${CHECK_RES}" = '200' ]; then
-        echo -e "\nUp and running"
-        break
-    fi
-    sleep 30s
-    echo "CHECK_RES: ${CHECK_RES}"
-  done
-}
-
-
-startGraphDB &
-waitGraphDBStart
-wait

docs/Makefile

@@ -38,7 +38,7 @@ install-py-deps:
 
 generate-files:
 	mkdir -p $(INTERMEDIATE_DIR)
-	cp -r $(SOURCE_DIR)/* $(INTERMEDIATE_DIR)
+	cp -rp $(SOURCE_DIR)/* $(INTERMEDIATE_DIR)
 
 	$(PYTHON) scripts/tool_feat_table.py $(INTERMEDIATE_DIR)
 

docs/api_reference/create_api_rst.py

@@ -479,11 +479,11 @@ def _package_namespace(package_name: str) -> str:
     Returns:
         modified package_name: Can be either "langchain" or "langchain_{package_name}"
     """
-    return (
-        package_name
-        if package_name == "langchain"
-        else f"langchain_{package_name.replace('-', '_')}"
-    )
+    if package_name == "langchain":
+        return "langchain"
+    if package_name == "standard-tests":
+        return "langchain_tests"
+    return f"langchain_{package_name.replace('-', '_')}"
 
 
 def _package_dir(package_name: str = "langchain") -> Path:
@@ -495,6 +495,7 @@ def _package_dir(package_name: str = "langchain") -> Path:
         "core",
         "cli",
         "text-splitters",
+        "standard-tests",
     ):
         return ROOT_DIR / "libs" / package_name / _package_namespace(package_name)
     else:
@@ -649,7 +650,7 @@ def main(dirs: Optional[list] = None) -> None:
         dirs = [
             dir_
             for dir_ in os.listdir(ROOT_DIR / "libs")
-            if dir_ not in ("cli", "partners", "standard-tests", "packages.yml")
+            if dir_ not in ("cli", "partners", "packages.yml")
         ]
         dirs += [
             dir_

docs/cassettes/extraction_0bb138d7-116e-4542-aa5f-bebf0c301ec6.msgpack.zlib

@@ -0,0 +1 @@
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

docs/cassettes/extraction_13165ac8-a1dc-44ce-a6ed-f52b577473e4.msgpack.zlib

@@ -1 +0,0 @@
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docs/cassettes/extraction_dd42a935-022f-4860-b9e0-84268f55b22a.msgpack.zlib

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docs/cassettes/llm_chain_0abb0863-bee7-448d-b013-79d8db01e330.msgpack.zlib

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docs/cassettes/llm_chain_1b2481f0.msgpack.zlib

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docs/cassettes/llm_chain_3e45595a.msgpack.zlib

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docs/cassettes/llm_chain_3e82f933.msgpack.zlib

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docs/cassettes/llm_chain_6bacb837.msgpack.zlib

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