Merge commit '28a8ecec8365e1759da27968939e785afd74b081' into usemotio…

…n_toolkit

* commit '28a8ecec8365e1759da27968939e785afd74b081': (235 commits)
  community[patch]: more deprecations (langchain-ai#15782)
  core[patch]: release 0.1.9 (langchain-ai#15794)
  docs: collapse structured use case (langchain-ai#15791)
  mistralai[patch]: warn on stop token, fix on_llm_new_token (langchain-ai#15787)
  mistralai[patch]: persist async client (langchain-ai#15786)
  templates: Add neo4j semantic layer template (langchain-ai#15652)
  community[patch]: fix qianfan chat stream calling caused exception (langchain-ai#13800)
  core[patch]: add alternative_import to deprecated (langchain-ai#15781)
  robocorp[patch]: fix readme, release 0.0.1.post1 (langchain-ai#15777)
  templates: robocorp action server template (langchain-ai#15776)
  openai[patch]: unit test load (langchain-ai#15624)
  openai[patch], docs: readme (langchain-ai#15773)
  community[patch]: update oai deprecation message (langchain-ai#15681)
  robocorp[minor]: Add robocorp action server toolkit (langchain-ai#15766)
  docs: integration package pip installs (langchain-ai#15762)
  docs: fix recognition (langchain-ai#15769)
  community[patch]: release 0.0.11 (langchain-ai#15760)
  experimental[patch]: loosen core max version (langchain-ai#15763)
  docs: remove unnecessary description (langchain-ai#15752)
  CI: Fix template for questions (langchain-ai#15756)
  ...

# Conflicts:
#	libs/community/poetry.lock
#	libs/community/pyproject.toml

.github/ISSUE_TEMPLATE/config.yml

@@ -1,6 +1,9 @@
 blank_issues_enabled: true
 version: 2.1
 contact_links:
+  - name: 🤔 Question or Problem
+    about: Ask a question or ask about a problem in GitHub Discussions.
+    url: https://github.com/langchain-ai/langchain/discussions
   - name: Discord
     url: https://discord.gg/6adMQxSpJS
     about: General community discussions

.github/actions/poetry_setup/action.yml

@@ -26,7 +26,7 @@ inputs:
 runs:
   using: composite
   steps:
-    - uses: actions/setup-python@v4
+    - uses: actions/setup-python@v5
       name: Setup python ${{ inputs.python-version }}
       with:
         python-version: ${{ inputs.python-version }}

.github/scripts/check_diff.py

@@ -13,6 +13,10 @@
     files = sys.argv[1:]
     dirs_to_run = set()
 
+    if len(files) == 300:
+        # max diff length is 300 files - there are likely files missing
+        raise ValueError("Max diff reached. Please manually run CI on changed libs.")
+
     for file in files:
         if any(
             file.startswith(dir_)
@@ -48,4 +52,5 @@
             dirs_to_run.update(LANGCHAIN_DIRS)
         else:
             pass
-    print(json.dumps(list(dirs_to_run)))
+    json_output = json.dumps(list(dirs_to_run))
+    print(f"dirs-to-run={json_output}")

.github/workflows/_integration_test.yml

@@ -37,13 +37,20 @@ jobs:
         shell: bash
         run: poetry install --with test,test_integration
 
+      - name: 'Authenticate to Google Cloud'
+        id: 'auth'
+        uses: google-github-actions/auth@v2
+        with:
+          credentials_json: '${{ secrets.GOOGLE_CREDENTIALS }}'
+
       - name: Run integration tests
         shell: bash
         env:
           GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }}
           ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
           MISTRAL_API_KEY: ${{ secrets.MISTRAL_API_KEY }}
           TOGETHER_API_KEY: ${{ secrets.TOGETHER_API_KEY }}
+          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
         run: |
           make integration_tests
 

.github/workflows/_release.yml

@@ -1,5 +1,5 @@
 name: release
-
+run-name: Release ${{ inputs.working-directory }} by @${{ github.actor }}
 on:
   workflow_call:
     inputs:
@@ -149,16 +149,29 @@ jobs:
         run: make tests
         working-directory: ${{ inputs.working-directory }}
 
+      - name: 'Authenticate to Google Cloud'
+        id: 'auth'
+        uses: google-github-actions/auth@v2
+        with:
+          credentials_json: '${{ secrets.GOOGLE_CREDENTIALS }}'
+
       - name: Run integration tests
         if: ${{ startsWith(inputs.working-directory, 'libs/partners/') }}
         env:
           GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }}
           ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
           MISTRAL_API_KEY: ${{ secrets.MISTRAL_API_KEY }}
           TOGETHER_API_KEY: ${{ secrets.TOGETHER_API_KEY }}
+          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
         run: make integration_tests
         working-directory: ${{ inputs.working-directory }}
 
+      - name: Run unit tests with minimum dependency versions
+        if: ${{ (inputs.working-directory == 'libs/langchain') || (inputs.working-directory == 'libs/community') || (inputs.working-directory == 'libs/experimental') }}
+        run: |
+          poetry run pip install -r _test_minimum_requirements.txt
+          make tests
+        working-directory: ${{ inputs.working-directory }}
 
   publish:
     needs:

.github/workflows/check_diffs.yml

@@ -5,11 +5,6 @@ on:
   push:
     branches: [master]
   pull_request:
-    paths:
-      - ".github/actions/**"
-      - ".github/tools/**"
-      - ".github/workflows/**"
-      - "libs/**"
 
 # If another push to the same PR or branch happens while this workflow is still running,
 # cancel the earlier run in favor of the next run.
@@ -26,13 +21,14 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
-      - uses: actions/setup-python@v4
+      - uses: actions/setup-python@v5
         with:
           python-version: '3.10'
       - id: files
         uses: Ana06/[email protected]
       - id: set-matrix
-        run: echo "dirs-to-run=$(python .github/scripts/check_diff.py ${{ steps.files.outputs.all }})" >> $GITHUB_OUTPUT
+        run: |
+          python .github/scripts/check_diff.py ${{ steps.files.outputs.all }} >> $GITHUB_OUTPUT
     outputs:
       dirs-to-run: ${{ steps.set-matrix.outputs.dirs-to-run }}
   ci:

.github/workflows/scheduled_test.yml

@@ -36,7 +36,7 @@ jobs:
 
       - name: 'Authenticate to Google Cloud'
         id: 'auth'
-        uses: 'google-github-actions/auth@v1'
+        uses: google-github-actions/auth@v2
         with:
           credentials_json: '${{ secrets.GOOGLE_CREDENTIALS }}'
 

.readthedocs.yaml

@@ -10,7 +10,7 @@ build:
   tools:
     python: "3.11"
   commands:
-      - python -mvirtualenv $READTHEDOCS_VIRTUALENV_PATH
+      - python -m virtualenv $READTHEDOCS_VIRTUALENV_PATH
       - python -m pip install --upgrade --no-cache-dir pip setuptools
       - python -m pip install --upgrade --no-cache-dir sphinx readthedocs-sphinx-ext
       - python -m pip install ./libs/partners/*

cookbook/LLaMA2_sql_chat.ipynb

@@ -61,13 +61,13 @@
    ],
    "source": [
     "# Local\n",
-    "from langchain.chat_models import ChatOllama\n",
+    "from langchain_community.chat_models import ChatOllama\n",
     "\n",
     "llama2_chat = ChatOllama(model=\"llama2:13b-chat\")\n",
     "llama2_code = ChatOllama(model=\"codellama:7b-instruct\")\n",
     "\n",
     "# API\n",
-    "from langchain.llms import Replicate\n",
+    "from langchain_community.llms import Replicate\n",
     "\n",
     "# REPLICATE_API_TOKEN = getpass()\n",
     "# os.environ[\"REPLICATE_API_TOKEN\"] = REPLICATE_API_TOKEN\n",
@@ -107,7 +107,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.utilities import SQLDatabase\n",
+    "from langchain_community.utilities import SQLDatabase\n",
     "\n",
     "db = SQLDatabase.from_uri(\"sqlite:///nba_roster.db\", sample_rows_in_table_info=0)\n",
     "\n",
@@ -125,7 +125,7 @@
    "id": "654b3577-baa2-4e12-a393-f40e5db49ac7",
    "metadata": {},
    "source": [
-    "## Query a SQL DB \n",
+    "## Query a SQL Database \n",
     "\n",
     "Follow the runnables workflow [here](https://python.langchain.com/docs/expression_language/cookbook/sql_db)."
    ]
@@ -149,8 +149,9 @@
    ],
    "source": [
     "# Prompt\n",
-    "from langchain.prompts import ChatPromptTemplate\n",
+    "from langchain_core.prompts import ChatPromptTemplate\n",
     "\n",
+    "# Update the template based on the type of SQL Database like MySQL, Microsoft SQL Server and so on\n",
     "template = \"\"\"Based on the table schema below, write a SQL query that would answer the user's question:\n",
     "{schema}\n",
     "\n",
@@ -277,7 +278,7 @@
    "source": [
     "# Prompt\n",
     "from langchain.memory import ConversationBufferMemory\n",
-    "from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
+    "from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
     "\n",
     "template = \"\"\"Given an input question, convert it to a SQL query. No pre-amble. Based on the table schema below, write a SQL query that would answer the user's question:\n",
     "{schema}\n",

cookbook/Multi_modal_RAG.ipynb

@@ -101,7 +101,7 @@
     "If you want to use the provided folder, then simply opt for a [pdf loader](https://python.langchain.com/docs/modules/data_connection/document_loaders/pdf) for the document:\n",
     "\n",
     "```\n",
-    "from langchain.document_loaders import PyPDFLoader\n",
+    "from langchain_community.document_loaders import PyPDFLoader\n",
     "loader = PyPDFLoader(path + fname)\n",
     "docs = loader.load()\n",
     "tables = [] # Ignore w/ basic pdf loader\n",
@@ -198,9 +198,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.chat_models import ChatOpenAI\n",
-    "from langchain.prompts import ChatPromptTemplate\n",
     "from langchain_core.output_parsers import StrOutputParser\n",
+    "from langchain_core.prompts import ChatPromptTemplate\n",
+    "from langchain_openai import ChatOpenAI\n",
     "\n",
     "\n",
     "# Generate summaries of text elements\n",
@@ -341,7 +341,7 @@
     "Add raw docs and doc summaries to [Multi Vector Retriever](https://python.langchain.com/docs/modules/data_connection/retrievers/multi_vector#summary): \n",
     "\n",
     "* Store the raw texts, tables, and images in the `docstore`.\n",
-    "* Store the texts, table summaries, and image summaries in the `vectorstore` for semantic retrieval."
+    "* Store the texts, table summaries, and image summaries in the `vectorstore` for efficient semantic retrieval."
    ]
   },
   {
@@ -353,11 +353,11 @@
    "source": [
     "import uuid\n",
     "\n",
-    "from langchain.embeddings import OpenAIEmbeddings\n",
     "from langchain.retrievers.multi_vector import MultiVectorRetriever\n",
     "from langchain.storage import InMemoryStore\n",
-    "from langchain.vectorstores import Chroma\n",
+    "from langchain_community.vectorstores import Chroma\n",
     "from langchain_core.documents import Document\n",
+    "from langchain_openai import OpenAIEmbeddings\n",
     "\n",
     "\n",
     "def create_multi_vector_retriever(\n",

cookbook/Multi_modal_RAG_google.ipynb

@@ -93,7 +93,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.document_loaders import PyPDFLoader\n",
+    "from langchain_community.document_loaders import PyPDFLoader\n",
     "\n",
     "loader = PyPDFLoader(\"./cj/cj.pdf\")\n",
     "docs = loader.load()\n",
@@ -158,11 +158,11 @@
     }
    ],
    "source": [
-    "from langchain.chat_models import ChatVertexAI\n",
-    "from langchain.llms import VertexAI\n",
     "from langchain.prompts import PromptTemplate\n",
-    "from langchain.schema.output_parser import StrOutputParser\n",
+    "from langchain_community.chat_models import ChatVertexAI\n",
+    "from langchain_community.llms import VertexAI\n",
     "from langchain_core.messages import AIMessage\n",
+    "from langchain_core.output_parsers import StrOutputParser\n",
     "from langchain_core.runnables import RunnableLambda\n",
     "\n",
     "\n",
@@ -243,7 +243,7 @@
     "import base64\n",
     "import os\n",
     "\n",
-    "from langchain.schema.messages import HumanMessage\n",
+    "from langchain_core.messages import HumanMessage\n",
     "\n",
     "\n",
     "def encode_image(image_path):\n",
@@ -342,11 +342,11 @@
    "source": [
     "import uuid\n",
     "\n",
-    "from langchain.embeddings import VertexAIEmbeddings\n",
     "from langchain.retrievers.multi_vector import MultiVectorRetriever\n",
-    "from langchain.schema.document import Document\n",
     "from langchain.storage import InMemoryStore\n",
-    "from langchain.vectorstores import Chroma\n",
+    "from langchain_community.embeddings import VertexAIEmbeddings\n",
+    "from langchain_community.vectorstores import Chroma\n",
+    "from langchain_core.documents import Document\n",
     "\n",
     "\n",
     "def create_multi_vector_retriever(\n",
@@ -440,7 +440,7 @@
     "import re\n",
     "\n",
     "from IPython.display import HTML, display\n",
-    "from langchain.schema.runnable import RunnableLambda, RunnablePassthrough\n",
+    "from langchain_core.runnables import RunnableLambda, RunnablePassthrough\n",
     "from PIL import Image\n",
     "\n",
     "\n",

cookbook/Semi_Structured_RAG.ipynb

@@ -235,9 +235,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.chat_models import ChatOpenAI\n",
-    "from langchain.prompts import ChatPromptTemplate\n",
-    "from langchain_core.output_parsers import StrOutputParser"
+    "from langchain_core.output_parsers import StrOutputParser\n",
+    "from langchain_core.prompts import ChatPromptTemplate\n",
+    "from langchain_openai import ChatOpenAI"
    ]
   },
   {
@@ -318,11 +318,11 @@
    "source": [
     "import uuid\n",
     "\n",
-    "from langchain.embeddings import OpenAIEmbeddings\n",
     "from langchain.retrievers.multi_vector import MultiVectorRetriever\n",
     "from langchain.storage import InMemoryStore\n",
-    "from langchain.vectorstores import Chroma\n",
+    "from langchain_community.vectorstores import Chroma\n",
     "from langchain_core.documents import Document\n",
+    "from langchain_openai import OpenAIEmbeddings\n",
     "\n",
     "# The vectorstore to use to index the child chunks\n",
     "vectorstore = Chroma(collection_name=\"summaries\", embedding_function=OpenAIEmbeddings())\n",

cookbook/Semi_structured_and_multi_modal_RAG.ipynb

@@ -211,9 +211,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.chat_models import ChatOpenAI\n",
-    "from langchain.prompts import ChatPromptTemplate\n",
-    "from langchain_core.output_parsers import StrOutputParser"
+    "from langchain_core.output_parsers import StrOutputParser\n",
+    "from langchain_core.prompts import ChatPromptTemplate\n",
+    "from langchain_openai import ChatOpenAI"
    ]
   },
   {
@@ -373,11 +373,11 @@
    "source": [
     "import uuid\n",
     "\n",
-    "from langchain.embeddings import OpenAIEmbeddings\n",
     "from langchain.retrievers.multi_vector import MultiVectorRetriever\n",
     "from langchain.storage import InMemoryStore\n",
-    "from langchain.vectorstores import Chroma\n",
+    "from langchain_community.vectorstores import Chroma\n",
     "from langchain_core.documents import Document\n",
+    "from langchain_openai import OpenAIEmbeddings\n",
     "\n",
     "# The vectorstore to use to index the child chunks\n",
     "vectorstore = Chroma(collection_name=\"summaries\", embedding_function=OpenAIEmbeddings())\n",

cookbook/Semi_structured_multi_modal_RAG_LLaMA2.ipynb

@@ -209,9 +209,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.chat_models import ChatOllama\n",
-    "from langchain.prompts import ChatPromptTemplate\n",
-    "from langchain_core.output_parsers import StrOutputParser"
+    "from langchain_community.chat_models import ChatOllama\n",
+    "from langchain_core.output_parsers import StrOutputParser\n",
+    "from langchain_core.prompts import ChatPromptTemplate"
    ]
   },
   {
@@ -376,10 +376,10 @@
    "source": [
     "import uuid\n",
     "\n",
-    "from langchain.embeddings import GPT4AllEmbeddings\n",
     "from langchain.retrievers.multi_vector import MultiVectorRetriever\n",
     "from langchain.storage import InMemoryStore\n",
-    "from langchain.vectorstores import Chroma\n",
+    "from langchain_community.embeddings import GPT4AllEmbeddings\n",
+    "from langchain_community.vectorstores import Chroma\n",
     "from langchain_core.documents import Document\n",
     "\n",
     "# The vectorstore to use to index the child chunks\n",