stuff

.github/ISSUE_TEMPLATE/bug-report.yml

@@ -5,84 +5,60 @@ body:
   - type: markdown
     attributes:
       value: >
-        Thank you for taking the time to file a bug report. 
-        
-        Relevant links to check before filing a bug report to see if your issue has already been reported, fixed or
-        if there's another way to solve your problem:
-        
-        [LangChain documentation with the integrated search](https://python.langchain.com/docs/get_started/introduction),
-        [API Reference](https://api.python.langchain.com/en/stable/),
-        [GitHub search](https://github.com/langchain-ai/langchain),
-        [LangChain Github Discussions](https://github.com/langchain-ai/langchain/discussions),
-        [LangChain Github Issues](https://github.com/langchain-ai/langchain/issues?q=is%3Aissue)
-  - type: checkboxes
-    id: checks
-    attributes:
-      label: Checked other resources
-      description: Please confirm and check all the following options.
-      options:
-        - label: I added a very descriptive title to this issue.
-          required: true
-        - label: I searched the LangChain documentation with the integrated search.
-          required: true
-        - label: I used the GitHub search to find a similar question and didn't find it.
-          required: true
-  - type: textarea
-    id: reproduction
-    validations:
-      required: true
-    attributes:
-      label: Example Code
-      description: |
-        Please add a self-contained, [minimal, reproducible, example](https://stackoverflow.com/help/minimal-reproducible-example) with your use case.
-        
-        If a maintainer can copy it, run it, and see it right away, there's a much higher chance that you'll be able to get help.
-        
-        If you're including an error message, please include the full stack trace not just the last error.
-        
-        **Important!** Use code tags to correctly format your code. See https://help.github.com/en/github/writing-on-github/creating-and-highlighting-code-blocks#syntax-highlighting
-        Avoid screenshots when possible, as they are hard to read and (more importantly) don't allow others to copy-and-paste your code.
+        Thank you for taking the time to file a bug report. Before creating a new
+        issue, please make sure to take a few moments to check the issue tracker
+        for existing issues about the bug.
 
-      placeholder: |
-        The following code: 
-        
-        ```python
-        from langchain_core.runnables import RunnableLambda
-
-        def bad_code(inputs) -> int:
-          raise NotImplementedError('For demo purpose')
-          
-          chain = RunnableLambda(bad_code)
-          chain.invoke('Hello!')
-        ```
-        
-        Include both the error and the full stack trace if reporting an exception!
-
-  - type: textarea
-    id: description
-    attributes:
-      label: Description
-      description: |
-        What is the problem, question, or error?
-
-        Write a short description telling what you are doing, what you expect to happen, and what is currently happening.
-      placeholder: |
-        * I'm trying to use the `langchain` library to do X.
-        * I expect to see Y.
-        * Instead, it does Z.
-    validations:
-      required: true
   - type: textarea
     id: system-info
     attributes:
       label: System Info
       description: Please share your system info with us.
-      placeholder: |
-        "pip freeze | grep langchain"
-        platform
-        python version
+      placeholder: LangChain version, platform, python version, ...
     validations:
       required: true
+
+  - type: textarea
+    id: who-can-help
+    attributes:
+      label: Who can help?
+      description: |
+        Your issue will be replied to more quickly if you can figure out the right person to tag with @
+        If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
+
+        The core maintainers strive to read all issues, but tagging them will help them prioritize.
+
+        Please tag fewer than 3 people.
+
+        @hwchase17 - project lead
+
+        Tracing / Callbacks
+        - @agola11
+
+        Async
+        - @agola11
+
+        DataLoader Abstractions
+        - @eyurtsev
+
+        LLM/Chat Wrappers
+        - @hwchase17
+        - @agola11
+
+        Tools / Toolkits
+        - ...
+
+      placeholder: "@Username ..."
+
+  - type: checkboxes
+    id: information-scripts-examples
+    attributes:
+      label: Information
+      description: "The problem arises when using:"
+      options:
+        - label: "The official example notebooks/scripts"
+        - label: "My own modified scripts"
+
   - type: checkboxes
     id: related-components
     attributes:
@@ -101,3 +77,30 @@ body:
         - label: "Chains"
         - label: "Callbacks/Tracing"
         - label: "Async"
+
+  - type: textarea
+    id: reproduction
+    validations:
+      required: true
+    attributes:
+      label: Reproduction
+      description: |
+        Please provide a [code sample](https://stackoverflow.com/help/minimal-reproducible-example) that reproduces the problem you ran into. It can be a Colab link or just a code snippet.
+        If you have code snippets, error messages, stack traces please provide them here as well.
+        Important! Use code tags to correctly format your code. See https://help.github.com/en/github/writing-on-github/creating-and-highlighting-code-blocks#syntax-highlighting
+        Avoid screenshots when possible, as they are hard to read and (more importantly) don't allow others to copy-and-paste your code.
+
+      placeholder: |
+        Steps to reproduce the behavior:
+
+          1.
+          2.
+          3.
+
+  - type: textarea
+    id: expected-behavior
+    validations:
+      required: true
+    attributes:
+      label: Expected behavior
+      description: "A clear and concise description of what you would expect to happen."

.github/ISSUE_TEMPLATE/config.yml

@@ -1,9 +1,6 @@
 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/ISSUE_TEMPLATE/other.yml

@@ -0,0 +1,18 @@
+name: Other Issue
+description: Raise an issue that wouldn't be covered by the other templates.
+title: "Issue: <Please write a comprehensive title after the 'Issue: ' prefix>"
+labels: [04 - Other]
+
+body:
+  - type: textarea
+    attributes:
+      label: "Issue you'd like to raise."
+      description: >
+        Please describe the issue you'd like to raise as clearly as possible.
+        Make sure to include any relevant links or references.
+
+  - type: textarea
+    attributes:
+      label: "Suggestion:"
+      description: >
+        Please outline a suggestion to improve the issue here.

.github/actions/poetry_setup/action.yml

@@ -26,9 +26,8 @@ inputs:
 runs:
   using: composite
   steps:
-    - uses: actions/setup-python@v5
+    - uses: actions/setup-python@v4
       name: Setup python ${{ inputs.python-version }}
-      id: setup-python
       with:
         python-version: ${{ inputs.python-version }}
 
@@ -75,8 +74,7 @@ runs:
       env:
         POETRY_VERSION: ${{ inputs.poetry-version }}
         PYTHON_VERSION: ${{ inputs.python-version }}
-      # Install poetry using the python version installed by setup-python step.
-      run: pipx install "poetry==$POETRY_VERSION" --python '${{ steps.setup-python.outputs.python-path }}' --verbose
+      run: pipx install "poetry==$POETRY_VERSION" --python "python$PYTHON_VERSION" --verbose
 
     - name: Restore pip and poetry cached dependencies
       uses: actions/cache@v3

.github/scripts/check_diff.py

@@ -13,10 +13,6 @@ if __name__ == "__main__":
     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_)
@@ -52,5 +48,4 @@ if __name__ == "__main__":
             dirs_to_run.update(LANGCHAIN_DIRS)
         else:
             pass
-    json_output = json.dumps(list(dirs_to_run))
-    print(f"dirs-to-run={json_output}")
+    print(json.dumps(list(dirs_to_run)))

.github/workflows/_integration_test.yml

@@ -37,12 +37,6 @@ 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:
@@ -50,7 +44,6 @@ jobs:
           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:
@@ -149,12 +149,6 @@ 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:
@@ -162,16 +156,9 @@ jobs:
           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

@@ -5,6 +5,11 @@ 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.
@@ -21,14 +26,13 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
-      - uses: actions/setup-python@v5
+      - uses: actions/setup-python@v4
         with:
           python-version: '3.10'
       - id: files
         uses: Ana06/get-changed-files@v2.2.0
       - id: set-matrix
-        run: |
-          python .github/scripts/check_diff.py ${{ steps.files.outputs.all }} >> $GITHUB_OUTPUT
+        run: echo "dirs-to-run=$(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@v2
+        uses: 'google-github-actions/auth@v1'
         with:
           credentials_json: '${{ secrets.GOOGLE_CREDENTIALS }}'
 

.readthedocs.yaml

@@ -10,7 +10,7 @@ build:
   tools:
     python: "3.11"
   commands:
-      - python -m virtualenv $READTHEDOCS_VIRTUALENV_PATH
+      - python -mvirtualenv $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_community.chat_models import ChatOllama\n",
+    "from langchain.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_community.llms import Replicate\n",
+    "from langchain.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_community.utilities import SQLDatabase\n",
+    "from langchain.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 Database \n",
+    "## Query a SQL DB \n",
     "\n",
     "Follow the runnables workflow [here](https://python.langchain.com/docs/expression_language/cookbook/sql_db)."
    ]
@@ -149,9 +149,8 @@
    ],
    "source": [
     "# Prompt\n",
-    "from langchain_core.prompts import ChatPromptTemplate\n",
+    "from langchain.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",
@@ -278,7 +277,7 @@
    "source": [
     "# Prompt\n",
     "from langchain.memory import ConversationBufferMemory\n",
-    "from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
+    "from langchain.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_community.document_loaders import PyPDFLoader\n",
+    "from langchain.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 efficient semantic retrieval."
+    "* Store the texts, table summaries, and image summaries in the `vectorstore` for 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_community.vectorstores import Chroma\n",
+    "from langchain.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_community.document_loaders import PyPDFLoader\n",
+    "from langchain.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_community.chat_models import ChatVertexAI\n",
-    "from langchain_community.llms import VertexAI\n",
+    "from langchain.schema.output_parser import StrOutputParser\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_core.messages import HumanMessage\n",
+    "from langchain.schema.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_community.embeddings import VertexAIEmbeddings\n",
-    "from langchain_community.vectorstores import Chroma\n",
-    "from langchain_core.documents import Document\n",
+    "from langchain.vectorstores import Chroma\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_core.runnables import RunnableLambda, RunnablePassthrough\n",
+    "from langchain.schema.runnable 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_core.output_parsers import StrOutputParser\n",
-    "from langchain_core.prompts import ChatPromptTemplate\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
+    "from langchain_core.output_parsers import StrOutputParser"
    ]
   },
   {
@@ -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_community.vectorstores import Chroma\n",
+    "from langchain.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_core.output_parsers import StrOutputParser\n",
-    "from langchain_core.prompts import ChatPromptTemplate\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
+    "from langchain_core.output_parsers import StrOutputParser"
    ]
   },
   {
@@ -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_community.vectorstores import Chroma\n",
+    "from langchain.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_community.chat_models import ChatOllama\n",
-    "from langchain_core.output_parsers import StrOutputParser\n",
-    "from langchain_core.prompts import ChatPromptTemplate"
+    "from langchain.chat_models import ChatOllama\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
+    "from langchain_core.output_parsers import StrOutputParser"
    ]
   },
   {
@@ -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_community.embeddings import GPT4AllEmbeddings\n",
-    "from langchain_community.vectorstores import Chroma\n",
+    "from langchain.vectorstores import Chroma\n",
     "from langchain_core.documents import Document\n",
     "\n",
     "# The vectorstore to use to index the child chunks\n",

cookbook/advanced_rag_eval.ipynb

@@ -62,7 +62,7 @@
     "path = \"/Users/rlm/Desktop/cpi/\"\n",
     "\n",
     "# Load\n",
-    "from langchain_community.document_loaders import PyPDFLoader\n",
+    "from langchain.document_loaders import PyPDFLoader\n",
     "\n",
     "loader = PyPDFLoader(path + \"cpi.pdf\")\n",
     "pdf_pages = loader.load()\n",
@@ -132,8 +132,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_community.vectorstores import Chroma\n",
-    "from langchain_openai import OpenAIEmbeddings\n",
+    "from langchain.embeddings import OpenAIEmbeddings\n",
+    "from langchain.vectorstores import Chroma\n",
     "\n",
     "baseline = Chroma.from_texts(\n",
     "    texts=all_splits_pypdf_texts,\n",
@@ -160,9 +160,9 @@
    "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",
     "# Prompt\n",
     "prompt_text = \"\"\"You are an assistant tasked with summarizing tables and text for retrieval. \\\n",

cookbook/analyze_document.ipynb

@@ -29,7 +29,7 @@
    "outputs": [],
    "source": [
     "from langchain.chains import AnalyzeDocumentChain\n",
-    "from langchain_openai import ChatOpenAI\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "\n",
     "llm = ChatOpenAI(model=\"gpt-3.5-turbo\", temperature=0)"
    ]

cookbook/autogpt/autogpt.ipynb

@@ -28,9 +28,9 @@
    "outputs": [],
    "source": [
     "from langchain.agents import Tool\n",
-    "from langchain_community.tools.file_management.read import ReadFileTool\n",
-    "from langchain_community.tools.file_management.write import WriteFileTool\n",
-    "from langchain_community.utilities import SerpAPIWrapper\n",
+    "from langchain.tools.file_management.read import ReadFileTool\n",
+    "from langchain.tools.file_management.write import WriteFileTool\n",
+    "from langchain.utilities import SerpAPIWrapper\n",
     "\n",
     "search = SerpAPIWrapper()\n",
     "tools = [\n",
@@ -62,8 +62,8 @@
    "outputs": [],
    "source": [
     "from langchain.docstore import InMemoryDocstore\n",
-    "from langchain_community.vectorstores import FAISS\n",
-    "from langchain_openai import OpenAIEmbeddings"
+    "from langchain.embeddings import OpenAIEmbeddings\n",
+    "from langchain.vectorstores import FAISS"
    ]
   },
   {
@@ -100,8 +100,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_experimental.autonomous_agents import AutoGPT\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain_experimental.autonomous_agents import AutoGPT"
    ]
   },
   {
@@ -167,7 +167,7 @@
    },
    "outputs": [],
    "source": [
-    "from langchain_community.chat_message_histories import FileChatMessageHistory\n",
+    "from langchain.memory.chat_message_histories import FileChatMessageHistory\n",
     "\n",
     "agent = AutoGPT.from_llm_and_tools(\n",
     "    ai_name=\"Tom\",\n",

cookbook/autogpt/marathon_times.ipynb

@@ -39,10 +39,10 @@
     "\n",
     "import nest_asyncio\n",
     "import pandas as pd\n",
+    "from langchain.agents.agent_toolkits.pandas.base import create_pandas_dataframe_agent\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.docstore.document import Document\n",
-    "from langchain_community.agent_toolkits.pandas.base import create_pandas_dataframe_agent\n",
     "from langchain_experimental.autonomous_agents import AutoGPT\n",
-    "from langchain_openai import ChatOpenAI\n",
     "\n",
     "# Needed synce jupyter runs an async eventloop\n",
     "nest_asyncio.apply()"
@@ -93,8 +93,8 @@
     "from typing import Optional\n",
     "\n",
     "from langchain.agents import tool\n",
-    "from langchain_community.tools.file_management.read import ReadFileTool\n",
-    "from langchain_community.tools.file_management.write import WriteFileTool\n",
+    "from langchain.tools.file_management.read import ReadFileTool\n",
+    "from langchain.tools.file_management.write import WriteFileTool\n",
     "\n",
     "ROOT_DIR = \"./data/\"\n",
     "\n",
@@ -311,8 +311,8 @@
     "# Memory\n",
     "import faiss\n",
     "from langchain.docstore import InMemoryDocstore\n",
-    "from langchain_community.vectorstores import FAISS\n",
-    "from langchain_openai import OpenAIEmbeddings\n",
+    "from langchain.embeddings import OpenAIEmbeddings\n",
+    "from langchain.vectorstores import FAISS\n",
     "\n",
     "embeddings_model = OpenAIEmbeddings()\n",
     "embedding_size = 1536\n",

cookbook/baby_agi.ipynb

@@ -31,8 +31,9 @@
    "source": [
     "from typing import Optional\n",
     "\n",
-    "from langchain_experimental.autonomous_agents import BabyAGI\n",
-    "from langchain_openai import OpenAI, OpenAIEmbeddings"
+    "from langchain.embeddings import OpenAIEmbeddings\n",
+    "from langchain.llms import OpenAI\n",
+    "from langchain_experimental.autonomous_agents import BabyAGI"
    ]
   },
   {
@@ -53,7 +54,7 @@
    "outputs": [],
    "source": [
     "from langchain.docstore import InMemoryDocstore\n",
-    "from langchain_community.vectorstores import FAISS"
+    "from langchain.vectorstores import FAISS"
    ]
   },
   {

cookbook/baby_agi_with_agent.ipynb

@@ -28,9 +28,10 @@
     "from typing import Optional\n",
     "\n",
     "from langchain.chains import LLMChain\n",
+    "from langchain.embeddings import OpenAIEmbeddings\n",
+    "from langchain.llms import OpenAI\n",
     "from langchain.prompts import PromptTemplate\n",
-    "from langchain_experimental.autonomous_agents import BabyAGI\n",
-    "from langchain_openai import OpenAI, OpenAIEmbeddings"
+    "from langchain_experimental.autonomous_agents import BabyAGI"
    ]
   },
   {
@@ -62,7 +63,7 @@
     "%pip install faiss-cpu > /dev/null\n",
     "%pip install google-search-results > /dev/null\n",
     "from langchain.docstore import InMemoryDocstore\n",
-    "from langchain_community.vectorstores import FAISS"
+    "from langchain.vectorstores import FAISS"
    ]
   },
   {
@@ -107,8 +108,8 @@
    "source": [
     "from langchain.agents import AgentExecutor, Tool, ZeroShotAgent\n",
     "from langchain.chains import LLMChain\n",
-    "from langchain_community.utilities import SerpAPIWrapper\n",
-    "from langchain_openai import OpenAI\n",
+    "from langchain.llms import OpenAI\n",
+    "from langchain.utilities import SerpAPIWrapper\n",
     "\n",
     "todo_prompt = PromptTemplate.from_template(\n",
     "    \"You are a planner who is an expert at coming up with a todo list for a given objective. Come up with a todo list for this objective: {objective}\"\n",

cookbook/camel_role_playing.ipynb

@@ -36,6 +36,7 @@
    "source": [
     "from typing import List\n",
     "\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.prompts.chat import (\n",
     "    HumanMessagePromptTemplate,\n",
     "    SystemMessagePromptTemplate,\n",
@@ -45,8 +46,7 @@
     "    BaseMessage,\n",
     "    HumanMessage,\n",
     "    SystemMessage,\n",
-    ")\n",
-    "from langchain_openai import ChatOpenAI"
+    ")"
    ]
   },
   {

cookbook/causal_program_aided_language_model.ipynb

@@ -47,9 +47,9 @@
    "outputs": [],
    "source": [
     "from IPython.display import SVG\n",
+    "from langchain.llms import OpenAI\n",
     "from langchain_experimental.cpal.base import CPALChain\n",
     "from langchain_experimental.pal_chain import PALChain\n",
-    "from langchain_openai import OpenAI\n",
     "\n",
     "llm = OpenAI(temperature=0, max_tokens=512)\n",
     "cpal_chain = CPALChain.from_univariate_prompt(llm=llm, verbose=True)\n",

cookbook/code-analysis-deeplake.ipynb

@@ -23,9 +23,9 @@
    "metadata": {},
    "source": [
     "1. Prepare data:\n",
-    "   1. Upload all python project files using the `langchain_community.document_loaders.TextLoader`. We will call these files the **documents**.\n",
+    "   1. Upload all python project files using the `langchain.document_loaders.TextLoader`. We will call these files the **documents**.\n",
     "   2. Split all documents to chunks using the `langchain.text_splitter.CharacterTextSplitter`.\n",
-    "   3. Embed chunks and upload them into the DeepLake using `langchain.embeddings.openai.OpenAIEmbeddings` and `langchain_community.vectorstores.DeepLake`\n",
+    "   3. Embed chunks and upload them into the DeepLake using `langchain.embeddings.openai.OpenAIEmbeddings` and `langchain.vectorstores.DeepLake`\n",
     "2. Question-Answering:\n",
     "   1. Build a chain from `langchain.chat_models.ChatOpenAI` and `langchain.chains.ConversationalRetrievalChain`\n",
     "   2. Prepare questions.\n",
@@ -166,7 +166,7 @@
     }
    ],
    "source": [
-    "from langchain_community.document_loaders import TextLoader\n",
+    "from langchain.document_loaders import TextLoader\n",
     "\n",
     "root_dir = \"../../../../../../libs\"\n",
     "\n",
@@ -657,7 +657,7 @@
     }
    ],
    "source": [
-    "from langchain_openai import OpenAIEmbeddings\n",
+    "from langchain.embeddings.openai import OpenAIEmbeddings\n",
     "\n",
     "embeddings = OpenAIEmbeddings()\n",
     "embeddings"
@@ -706,7 +706,7 @@
     {
      "data": {
       "text/plain": [
-       "<langchain_community.vectorstores.deeplake.DeepLake at 0x7fe1b67d7a30>"
+       "<langchain.vectorstores.deeplake.DeepLake at 0x7fe1b67d7a30>"
       ]
      },
      "execution_count": 15,
@@ -715,7 +715,7 @@
     }
    ],
    "source": [
-    "from langchain_community.vectorstores import DeepLake\n",
+    "from langchain.vectorstores import DeepLake\n",
     "\n",
     "username = \"<USERNAME_OR_ORG>\"\n",
     "\n",
@@ -740,7 +740,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# from langchain_community.vectorstores import DeepLake\n",
+    "# from langchain.vectorstores import DeepLake\n",
     "\n",
     "# db = DeepLake.from_documents(\n",
     "#     texts, embeddings, dataset_path=f\"hub://{<org_id>}/langchain-code\", runtime={\"tensor_db\": True}\n",
@@ -834,7 +834,7 @@
    "outputs": [],
    "source": [
     "from langchain.chains import ConversationalRetrievalChain\n",
-    "from langchain_openai import ChatOpenAI\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "\n",
     "model = ChatOpenAI(\n",
     "    model_name=\"gpt-3.5-turbo-0613\"\n",

cookbook/custom_agent_with_plugin_retrieval.ipynb

@@ -40,12 +40,12 @@
     "    AgentOutputParser,\n",
     "    LLMSingleActionAgent,\n",
     ")\n",
+    "from langchain.agents.agent_toolkits import NLAToolkit\n",
     "from langchain.chains import LLMChain\n",
+    "from langchain.llms import OpenAI\n",
     "from langchain.prompts import StringPromptTemplate\n",
     "from langchain.schema import AgentAction, AgentFinish\n",
-    "from langchain_community.agent_toolkits import NLAToolkit\n",
-    "from langchain_community.tools.plugin import AIPlugin\n",
-    "from langchain_openai import OpenAI"
+    "from langchain.tools.plugin import AIPlugin"
    ]
   },
   {
@@ -114,9 +114,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langchain.embeddings import OpenAIEmbeddings\n",
     "from langchain.schema import Document\n",
-    "from langchain_community.vectorstores import FAISS\n",
-    "from langchain_openai import OpenAIEmbeddings"
+    "from langchain.vectorstores import FAISS"
    ]
   },
   {

cookbook/custom_agent_with_plugin_retrieval_using_plugnplai.ipynb

@@ -65,12 +65,12 @@
     "    AgentOutputParser,\n",
     "    LLMSingleActionAgent,\n",
     ")\n",
+    "from langchain.agents.agent_toolkits import NLAToolkit\n",
     "from langchain.chains import LLMChain\n",
+    "from langchain.llms import OpenAI\n",
     "from langchain.prompts import StringPromptTemplate\n",
     "from langchain.schema import AgentAction, AgentFinish\n",
-    "from langchain_community.agent_toolkits import NLAToolkit\n",
-    "from langchain_community.tools.plugin import AIPlugin\n",
-    "from langchain_openai import OpenAI"
+    "from langchain.tools.plugin import AIPlugin"
    ]
   },
   {
@@ -138,9 +138,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langchain.embeddings import OpenAIEmbeddings\n",
     "from langchain.schema import Document\n",
-    "from langchain_community.vectorstores import FAISS\n",
-    "from langchain_openai import OpenAIEmbeddings"
+    "from langchain.vectorstores import FAISS"
    ]
   },
   {

cookbook/databricks_sql_db.ipynb

@@ -80,7 +80,7 @@
    "outputs": [],
    "source": [
     "# Connecting to Databricks with SQLDatabase wrapper\n",
-    "from langchain_community.utilities import SQLDatabase\n",
+    "from langchain.utilities import SQLDatabase\n",
     "\n",
     "db = SQLDatabase.from_databricks(catalog=\"samples\", schema=\"nyctaxi\")"
    ]
@@ -93,7 +93,7 @@
    "outputs": [],
    "source": [
     "# Creating a OpenAI Chat LLM wrapper\n",
-    "from langchain_openai import ChatOpenAI\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "\n",
     "llm = ChatOpenAI(temperature=0, model_name=\"gpt-4\")"
    ]
@@ -115,7 +115,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_community.utilities import SQLDatabaseChain\n",
+    "from langchain.utilities import SQLDatabaseChain\n",
     "\n",
     "db_chain = SQLDatabaseChain.from_llm(llm, db, verbose=True)"
    ]
@@ -177,7 +177,7 @@
    "outputs": [],
    "source": [
     "from langchain.agents import create_sql_agent\n",
-    "from langchain_community.agent_toolkits import SQLDatabaseToolkit\n",
+    "from langchain.agents.agent_toolkits import SQLDatabaseToolkit\n",
     "\n",
     "toolkit = SQLDatabaseToolkit(db=db, llm=llm)\n",
     "agent = create_sql_agent(llm=llm, toolkit=toolkit, verbose=True)"

cookbook/deeplake_semantic_search_over_chat.ipynb

@@ -52,12 +52,13 @@
     "import os\n",
     "\n",
     "from langchain.chains import RetrievalQA\n",
+    "from langchain.embeddings.openai import OpenAIEmbeddings\n",
+    "from langchain.llms import OpenAI\n",
     "from langchain.text_splitter import (\n",
     "    CharacterTextSplitter,\n",
     "    RecursiveCharacterTextSplitter,\n",
     ")\n",
-    "from langchain_community.vectorstores import DeepLake\n",
-    "from langchain_openai import OpenAI, OpenAIEmbeddings\n",
+    "from langchain.vectorstores import DeepLake\n",
     "\n",
     "os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"OpenAI API Key:\")\n",
     "activeloop_token = getpass.getpass(\"Activeloop Token:\")\n",

cookbook/docugami_xml_kg_rag.ipynb

@@ -470,13 +470,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.prompts import (\n",
     "    ChatPromptTemplate,\n",
     "    HumanMessagePromptTemplate,\n",
     "    SystemMessagePromptTemplate,\n",
     ")\n",
-    "from langchain_core.output_parsers import StrOutputParser\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain_core.output_parsers import StrOutputParser"
    ]
   },
   {
@@ -545,11 +545,11 @@
    "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_community.vectorstores.chroma import Chroma\n",
+    "from langchain.vectorstores.chroma import Chroma\n",
     "from langchain_core.documents import Document\n",
-    "from langchain_openai import OpenAIEmbeddings\n",
     "\n",
     "\n",
     "def build_retriever(text_elements, tables, table_summaries):\n",

cookbook/elasticsearch_db_qa.ipynb

@@ -39,7 +39,7 @@
    "source": [
     "from elasticsearch import Elasticsearch\n",
     "from langchain.chains.elasticsearch_database import ElasticsearchDatabaseChain\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain.chat_models import ChatOpenAI"
    ]
   },
   {

cookbook/extraction_openai_tools.ipynb

@@ -22,8 +22,8 @@
     "from typing import List, Optional\n",
     "\n",
     "from langchain.chains.openai_tools import create_extraction_chain_pydantic\n",
-    "from langchain_core.pydantic_v1 import BaseModel\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain_core.pydantic_v1 import BaseModel"
    ]
   },
   {
@@ -153,7 +153,7 @@
     "from langchain.utils.openai_functions import convert_pydantic_to_openai_tool\n",
     "from langchain_core.runnables import Runnable\n",
     "from langchain_core.pydantic_v1 import BaseModel\n",
-    "from langchain_core.prompts import ChatPromptTemplate\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
     "from langchain_core.messages import SystemMessage\n",
     "from langchain_core.language_models import BaseLanguageModel\n",
     "\n",

cookbook/fake_llm.ipynb

@@ -20,7 +20,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_community.llms.fake import FakeListLLM"
+    "from langchain.llms.fake import FakeListLLM"
    ]
   },
   {

cookbook/forward_looking_retrieval_augmented_generation.ipynb

@@ -73,9 +73,10 @@
     "    AsyncCallbackManagerForRetrieverRun,\n",
     "    CallbackManagerForRetrieverRun,\n",
     ")\n",
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.llms import OpenAI\n",
     "from langchain.schema import BaseRetriever, Document\n",
-    "from langchain_community.utilities import GoogleSerperAPIWrapper\n",
-    "from langchain_openai import ChatOpenAI, OpenAI"
+    "from langchain.utilities import GoogleSerperAPIWrapper"
    ]
   },
   {

cookbook/generative_agents_interactive_simulacra_of_human_behavior.ipynb

@@ -47,10 +47,11 @@
     "from datetime import datetime, timedelta\n",
     "from typing import List\n",
     "\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.docstore import InMemoryDocstore\n",
+    "from langchain.embeddings import OpenAIEmbeddings\n",
     "from langchain.retrievers import TimeWeightedVectorStoreRetriever\n",
-    "from langchain_community.vectorstores import FAISS\n",
-    "from langchain_openai import ChatOpenAI, OpenAIEmbeddings\n",
+    "from langchain.vectorstores import FAISS\n",
     "from termcolor import colored"
    ]
   },

cookbook/hugginggpt.ipynb

@@ -75,8 +75,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langchain.llms import OpenAI\n",
     "from langchain_experimental.autonomous_agents import HuggingGPT\n",
-    "from langchain_openai import OpenAI\n",
     "\n",
     "# %env OPENAI_API_BASE=http://localhost:8000/v1"
    ]

cookbook/human_input_chat_model.ipynb

@@ -20,7 +20,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_community.chat_models.human import HumanInputChatModel"
+    "from langchain.chat_models.human import HumanInputChatModel"
    ]
   },
   {

cookbook/human_input_llm.ipynb

@@ -19,7 +19,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_community.llms.human import HumanInputLLM"
+    "from langchain.llms.human import HumanInputLLM"
    ]
   },
   {

cookbook/hypothetical_document_embeddings.ipynb

@@ -21,8 +21,9 @@
    "outputs": [],
    "source": [
     "from langchain.chains import HypotheticalDocumentEmbedder, LLMChain\n",
-    "from langchain.prompts import PromptTemplate\n",
-    "from langchain_openai import OpenAI, OpenAIEmbeddings"
+    "from langchain.embeddings import OpenAIEmbeddings\n",
+    "from langchain.llms import OpenAI\n",
+    "from langchain.prompts import PromptTemplate"
    ]
   },
   {
@@ -171,7 +172,7 @@
    "outputs": [],
    "source": [
     "from langchain.text_splitter import CharacterTextSplitter\n",
-    "from langchain_community.vectorstores import Chroma\n",
+    "from langchain.vectorstores import Chroma\n",
     "\n",
     "with open(\"../../state_of_the_union.txt\") as f:\n",
     "    state_of_the_union = f.read()\n",

cookbook/learned_prompt_optimization.ipynb

@@ -49,7 +49,7 @@
    "source": [
     "# pick and configure the LLM of your choice\n",
     "\n",
-    "from langchain_openai import OpenAI\n",
+    "from langchain.llms import OpenAI\n",
     "\n",
     "llm = OpenAI(model=\"gpt-3.5-turbo-instruct\")"
    ]

cookbook/llm_bash.ipynb

@@ -43,8 +43,8 @@
     }
    ],
    "source": [
+    "from langchain.llms import OpenAI\n",
     "from langchain_experimental.llm_bash.base import LLMBashChain\n",
-    "from langchain_openai import OpenAI\n",
     "\n",
     "llm = OpenAI(temperature=0)\n",
     "\n",

cookbook/llm_checker.ipynb

@@ -42,7 +42,7 @@
    ],
    "source": [
     "from langchain.chains import LLMCheckerChain\n",
-    "from langchain_openai import OpenAI\n",
+    "from langchain.llms import OpenAI\n",
     "\n",
     "llm = OpenAI(temperature=0.7)\n",
     "\n",

cookbook/llm_math.ipynb

@@ -46,7 +46,7 @@
    ],
    "source": [
     "from langchain.chains import LLMMathChain\n",
-    "from langchain_openai import OpenAI\n",
+    "from langchain.llms import OpenAI\n",
     "\n",
     "llm = OpenAI(temperature=0)\n",
     "llm_math = LLMMathChain.from_llm(llm, verbose=True)\n",

cookbook/llm_summarization_checker.ipynb

@@ -331,7 +331,7 @@
    ],
    "source": [
     "from langchain.chains import LLMSummarizationCheckerChain\n",
-    "from langchain_openai import OpenAI\n",
+    "from langchain.llms import OpenAI\n",
     "\n",
     "llm = OpenAI(temperature=0)\n",
     "checker_chain = LLMSummarizationCheckerChain.from_llm(llm, verbose=True, max_checks=2)\n",
@@ -822,7 +822,7 @@
    ],
    "source": [
     "from langchain.chains import LLMSummarizationCheckerChain\n",
-    "from langchain_openai import OpenAI\n",
+    "from langchain.llms import OpenAI\n",
     "\n",
     "llm = OpenAI(temperature=0)\n",
     "checker_chain = LLMSummarizationCheckerChain.from_llm(llm, verbose=True, max_checks=3)\n",
@@ -1096,7 +1096,7 @@
    ],
    "source": [
     "from langchain.chains import LLMSummarizationCheckerChain\n",
-    "from langchain_openai import OpenAI\n",
+    "from langchain.llms import OpenAI\n",
     "\n",
     "llm = OpenAI(temperature=0)\n",
     "checker_chain = LLMSummarizationCheckerChain.from_llm(llm, max_checks=3, verbose=True)\n",

cookbook/llm_symbolic_math.ipynb

@@ -14,8 +14,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langchain.llms import OpenAI\n",
     "from langchain_experimental.llm_symbolic_math.base import LLMSymbolicMathChain\n",
-    "from langchain_openai import OpenAI\n",
     "\n",
     "llm = OpenAI(temperature=0)\n",
     "llm_symbolic_math = LLMSymbolicMathChain.from_llm(llm)"

cookbook/meta_prompt.ipynb

@@ -57,9 +57,9 @@
    "outputs": [],
    "source": [
     "from langchain.chains import LLMChain\n",
+    "from langchain.llms import OpenAI\n",
     "from langchain.memory import ConversationBufferWindowMemory\n",
-    "from langchain.prompts import PromptTemplate\n",
-    "from langchain_openai import OpenAI"
+    "from langchain.prompts import PromptTemplate"
    ]
   },
   {

cookbook/multi_modal_QA.ipynb

@@ -91,8 +91,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_core.messages import HumanMessage, SystemMessage\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain_core.messages import HumanMessage, SystemMessage"
    ]
   },
   {

cookbook/multi_modal_RAG_chroma.ipynb

@@ -187,7 +187,7 @@
     "\n",
     "import chromadb\n",
     "import numpy as np\n",
-    "from langchain_community.vectorstores import Chroma\n",
+    "from langchain.vectorstores import Chroma\n",
     "from langchain_experimental.open_clip import OpenCLIPEmbeddings\n",
     "from PIL import Image as _PILImage\n",
     "\n",
@@ -315,10 +315,10 @@
    "source": [
     "from operator import itemgetter\n",
     "\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain_core.messages import HumanMessage, SystemMessage\n",
     "from langchain_core.output_parsers import StrOutputParser\n",
     "from langchain_core.runnables import RunnableLambda, RunnablePassthrough\n",
-    "from langchain_openai import ChatOpenAI\n",
     "\n",
     "\n",
     "def prompt_func(data_dict):\n",

cookbook/multi_modal_output_agent.ipynb

@@ -43,8 +43,8 @@
    "outputs": [],
    "source": [
     "from langchain.agents import AgentType, initialize_agent\n",
-    "from langchain.tools import SteamshipImageGenerationTool\n",
-    "from langchain_openai import OpenAI"
+    "from langchain.llms import OpenAI\n",
+    "from langchain.tools import SteamshipImageGenerationTool"
    ]
   },
   {

cookbook/multi_player_dnd.ipynb

@@ -28,11 +28,11 @@
    "source": [
     "from typing import Callable, List\n",
     "\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.schema import (\n",
     "    HumanMessage,\n",
     "    SystemMessage,\n",
-    ")\n",
-    "from langchain_openai import ChatOpenAI"
+    ")"
    ]
   },
   {

cookbook/multiagent_authoritarian.ipynb

@@ -33,6 +33,7 @@
     "from typing import Callable, List\n",
     "\n",
     "import tenacity\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.output_parsers import RegexParser\n",
     "from langchain.prompts import (\n",
     "    PromptTemplate,\n",
@@ -40,8 +41,7 @@
     "from langchain.schema import (\n",
     "    HumanMessage,\n",
     "    SystemMessage,\n",
-    ")\n",
-    "from langchain_openai import ChatOpenAI"
+    ")"
    ]
   },
   {

cookbook/multiagent_bidding.ipynb

@@ -27,13 +27,13 @@
     "from typing import Callable, List\n",
     "\n",
     "import tenacity\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.output_parsers import RegexParser\n",
     "from langchain.prompts import PromptTemplate\n",
     "from langchain.schema import (\n",
     "    HumanMessage,\n",
     "    SystemMessage,\n",
-    ")\n",
-    "from langchain_openai import ChatOpenAI"
+    ")"
    ]
   },
   {

cookbook/myscale_vector_sql.ipynb

@@ -31,10 +31,10 @@
     "from os import environ\n",
     "\n",
     "from langchain.chains import LLMChain\n",
+    "from langchain.llms import OpenAI\n",
     "from langchain.prompts import PromptTemplate\n",
-    "from langchain_community.utilities import SQLDatabase\n",
+    "from langchain.utilities import SQLDatabase\n",
     "from langchain_experimental.sql.vector_sql import VectorSQLDatabaseChain\n",
-    "from langchain_openai import OpenAI\n",
     "from sqlalchemy import MetaData, create_engine\n",
     "\n",
     "MYSCALE_HOST = \"msc-4a9e710a.us-east-1.aws.staging.myscale.cloud\"\n",
@@ -57,7 +57,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_community.embeddings import HuggingFaceInstructEmbeddings\n",
+    "from langchain.embeddings import HuggingFaceInstructEmbeddings\n",
     "from langchain_experimental.sql.vector_sql import VectorSQLOutputParser\n",
     "\n",
     "output_parser = VectorSQLOutputParser.from_embeddings(\n",
@@ -75,10 +75,10 @@
    "outputs": [],
    "source": [
     "from langchain.callbacks import StdOutCallbackHandler\n",
-    "from langchain_community.utilities.sql_database import SQLDatabase\n",
+    "from langchain.llms import OpenAI\n",
+    "from langchain.utilities.sql_database import SQLDatabase\n",
     "from langchain_experimental.sql.prompt import MYSCALE_PROMPT\n",
     "from langchain_experimental.sql.vector_sql import VectorSQLDatabaseChain\n",
-    "from langchain_openai import OpenAI\n",
     "\n",
     "chain = VectorSQLDatabaseChain(\n",
     "    llm_chain=LLMChain(\n",
@@ -117,6 +117,7 @@
    "outputs": [],
    "source": [
     "from langchain.chains.qa_with_sources.retrieval import RetrievalQAWithSourcesChain\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain_experimental.retrievers.vector_sql_database import (\n",
     "    VectorSQLDatabaseChainRetriever,\n",
     ")\n",
@@ -125,7 +126,6 @@
     "    VectorSQLDatabaseChain,\n",
     "    VectorSQLRetrieveAllOutputParser,\n",
     ")\n",
-    "from langchain_openai import ChatOpenAI\n",
     "\n",
     "output_parser_retrieve_all = VectorSQLRetrieveAllOutputParser.from_embeddings(\n",
     "    output_parser.model\n",

cookbook/openai_functions_retrieval_qa.ipynb

@@ -20,10 +20,10 @@
    "outputs": [],
    "source": [
     "from langchain.chains import RetrievalQA\n",
+    "from langchain.document_loaders import TextLoader\n",
+    "from langchain.embeddings.openai import OpenAIEmbeddings\n",
     "from langchain.text_splitter import CharacterTextSplitter\n",
-    "from langchain_community.document_loaders import TextLoader\n",
-    "from langchain_community.vectorstores import Chroma\n",
-    "from langchain_openai import OpenAIEmbeddings"
+    "from langchain.vectorstores import Chroma"
    ]
   },
   {
@@ -52,8 +52,8 @@
    "source": [
     "from langchain.chains import create_qa_with_sources_chain\n",
     "from langchain.chains.combine_documents.stuff import StuffDocumentsChain\n",
-    "from langchain.prompts import PromptTemplate\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.prompts import PromptTemplate"
    ]
   },
   {

cookbook/openai_v1_cookbook.ipynb

@@ -28,8 +28,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_core.messages import HumanMessage, SystemMessage\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain_core.messages import HumanMessage, SystemMessage"
    ]
   },
   {
@@ -414,7 +414,7 @@
     "BREAKING CHANGES:\n",
     "- To use Azure embeddings with OpenAI V1, you'll need to use the new `AzureOpenAIEmbeddings` instead of the existing `OpenAIEmbeddings`. `OpenAIEmbeddings` continue to work when using Azure with `openai<1`.\n",
     "```python\n",
-    "from langchain_openai import AzureOpenAIEmbeddings\n",
+    "from langchain.embeddings import AzureOpenAIEmbeddings\n",
     "```\n",
     "\n",
     "\n",
@@ -456,8 +456,8 @@
     "from typing import Literal\n",
     "\n",
     "from langchain.output_parsers.openai_tools import PydanticToolsParser\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
     "from langchain.utils.openai_functions import convert_pydantic_to_openai_tool\n",
-    "from langchain_core.prompts import ChatPromptTemplate\n",
     "from langchain_core.pydantic_v1 import BaseModel, Field\n",
     "\n",
     "\n",

cookbook/petting_zoo.ipynb

@@ -47,12 +47,12 @@
     "import inspect\n",
     "\n",
     "import tenacity\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.output_parsers import RegexParser\n",
     "from langchain.schema import (\n",
     "    HumanMessage,\n",
     "    SystemMessage,\n",
-    ")\n",
-    "from langchain_openai import ChatOpenAI"
+    ")"
    ]
   },
   {

cookbook/plan_and_execute_agent.ipynb

@@ -30,14 +30,15 @@
    "outputs": [],
    "source": [
     "from langchain.chains import LLMMathChain\n",
-    "from langchain_community.utilities import DuckDuckGoSearchAPIWrapper\n",
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.llms import OpenAI\n",
+    "from langchain.utilities import DuckDuckGoSearchAPIWrapper\n",
     "from langchain_core.tools import Tool\n",
     "from langchain_experimental.plan_and_execute import (\n",
     "    PlanAndExecute,\n",
     "    load_agent_executor,\n",
     "    load_chat_planner,\n",
-    ")\n",
-    "from langchain_openai import ChatOpenAI, OpenAI"
+    ")"
    ]
   },
   {

cookbook/press_releases.ipynb

@@ -81,8 +81,8 @@
    "outputs": [],
    "source": [
     "from langchain.chains import ConversationalRetrievalChain\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.retrievers import KayAiRetriever\n",
-    "from langchain_openai import ChatOpenAI\n",
     "\n",
     "model = ChatOpenAI(model_name=\"gpt-3.5-turbo\")\n",
     "retriever = KayAiRetriever.create(\n",

cookbook/program_aided_language_model.ipynb

@@ -17,8 +17,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_experimental.pal_chain import PALChain\n",
-    "from langchain_openai import OpenAI"
+    "from langchain.llms import OpenAI\n",
+    "from langchain_experimental.pal_chain import PALChain"
    ]
   },
   {

cookbook/qa_citations.ipynb

@@ -27,7 +27,7 @@
    ],
    "source": [
     "from langchain.chains import create_citation_fuzzy_match_chain\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain.chat_models import ChatOpenAI"
    ]
   },
   {

cookbook/qianfan_baidu_elasticesearch_RAG.ipynb

@@ -59,13 +59,11 @@
     "from baidubce.auth.bce_credentials import BceCredentials\n",
     "from baidubce.bce_client_configuration import BceClientConfiguration\n",
     "from langchain.chains.retrieval_qa import RetrievalQA\n",
+    "from langchain.document_loaders.baiducloud_bos_directory import BaiduBOSDirectoryLoader\n",
+    "from langchain.embeddings.huggingface import HuggingFaceEmbeddings\n",
+    "from langchain.llms.baidu_qianfan_endpoint import QianfanLLMEndpoint\n",
     "from langchain.text_splitter import RecursiveCharacterTextSplitter\n",
-    "from langchain_community.document_loaders.baiducloud_bos_directory import (\n",
-    "    BaiduBOSDirectoryLoader,\n",
-    ")\n",
-    "from langchain_community.embeddings.huggingface import HuggingFaceEmbeddings\n",
-    "from langchain_community.llms.baidu_qianfan_endpoint import QianfanLLMEndpoint\n",
-    "from langchain_community.vectorstores import BESVectorStore"
+    "from langchain.vectorstores import BESVectorStore"
    ]
   },
   {

cookbook/rag_fusion.ipynb

@@ -30,8 +30,8 @@
    "outputs": [],
    "source": [
     "import pinecone\n",
-    "from langchain_community.vectorstores import Pinecone\n",
-    "from langchain_openai import OpenAIEmbeddings\n",
+    "from langchain.embeddings import OpenAIEmbeddings\n",
+    "from langchain.vectorstores import Pinecone\n",
     "\n",
     "pinecone.init(api_key=\"...\", environment=\"...\")"
    ]
@@ -86,8 +86,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_core.output_parsers import StrOutputParser\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain_core.output_parsers import StrOutputParser"
    ]
   },
   {

cookbook/retrieval_in_sql.ipynb

@@ -42,8 +42,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.sql_database import SQLDatabase\n",
-    "from langchain_openai import ChatOpenAI\n",
     "\n",
     "CONNECTION_STRING = \"postgresql+psycopg2://postgres:test@localhost:5432/vectordb\"  # Replace with your own\n",
     "db = SQLDatabase.from_uri(CONNECTION_STRING)"
@@ -88,7 +88,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_openai import OpenAIEmbeddings\n",
+    "from langchain.embeddings import OpenAIEmbeddings\n",
     "\n",
     "embeddings_model = OpenAIEmbeddings()"
    ]
@@ -219,7 +219,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_core.prompts import ChatPromptTemplate\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
     "\n",
     "template = \"\"\"You are a Postgres expert. Given an input question, first create a syntactically correct Postgres query to run, then look at the results of the query and return the answer to the input question.\n",
     "Unless the user specifies in the question a specific number of examples to obtain, query for at most 5 results using the LIMIT clause as per Postgres. You can order the results to return the most informative data in the database.\n",
@@ -267,9 +267,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain_core.output_parsers import StrOutputParser\n",
     "from langchain_core.runnables import RunnablePassthrough\n",
-    "from langchain_openai import ChatOpenAI\n",
     "\n",
     "db = SQLDatabase.from_uri(\n",
     "    CONNECTION_STRING\n",

cookbook/rewrite.ipynb

@@ -31,11 +31,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_community.utilities import DuckDuckGoSearchAPIWrapper\n",
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
+    "from langchain.utilities import DuckDuckGoSearchAPIWrapper\n",
     "from langchain_core.output_parsers import StrOutputParser\n",
-    "from langchain_core.prompts import ChatPromptTemplate\n",
-    "from langchain_core.runnables import RunnablePassthrough\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain_core.runnables import RunnablePassthrough"
    ]
   },
   {

cookbook/sales_agent_with_context.ipynb

@@ -49,13 +49,14 @@
     "from langchain.agents.conversational.prompt import FORMAT_INSTRUCTIONS\n",
     "from langchain.chains import LLMChain, RetrievalQA\n",
     "from langchain.chains.base import Chain\n",
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.embeddings.openai import OpenAIEmbeddings\n",
+    "from langchain.llms import BaseLLM, OpenAI\n",
     "from langchain.prompts import PromptTemplate\n",
     "from langchain.prompts.base import StringPromptTemplate\n",
     "from langchain.schema import AgentAction, AgentFinish\n",
     "from langchain.text_splitter import CharacterTextSplitter\n",
-    "from langchain_community.llms import BaseLLM\n",
-    "from langchain_community.vectorstores import Chroma\n",
-    "from langchain_openai import ChatOpenAI, OpenAI, OpenAIEmbeddings\n",
+    "from langchain.vectorstores import Chroma\n",
     "from pydantic import BaseModel, Field"
    ]
   },

cookbook/selecting_llms_based_on_context_length.ipynb

@@ -17,10 +17,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.prompts import PromptTemplate\n",
     "from langchain_core.output_parsers import StrOutputParser\n",
-    "from langchain_core.prompt_values import PromptValue\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain_core.prompt_values import PromptValue"
    ]
   },
   {

cookbook/self_query_hotel_search.ipynb

@@ -255,7 +255,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_openai import ChatOpenAI\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "\n",
     "model = ChatOpenAI(model=\"gpt-4\")\n",
     "res = model.predict(\n",
@@ -1083,8 +1083,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_community.vectorstores import ElasticsearchStore\n",
-    "from langchain_openai import OpenAIEmbeddings\n",
+    "from langchain.embeddings import OpenAIEmbeddings\n",
+    "from langchain.vectorstores import ElasticsearchStore\n",
     "\n",
     "embeddings = OpenAIEmbeddings()"
    ]

cookbook/smart_llm.ipynb

@@ -51,9 +51,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.prompts import PromptTemplate\n",
-    "from langchain_experimental.smart_llm import SmartLLMChain\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain_experimental.smart_llm import SmartLLMChain"
    ]
   },
   {

cookbook/sql_db_qa.mdx

@@ -9,8 +9,8 @@ To set it up, follow the instructions on https://database.guide/2-sample-databas
 
 
 ```python
-from langchain_openai import OpenAI
-from langchain_community.utilities import SQLDatabase
+from langchain.llms import OpenAI
+from langchain.utilities import SQLDatabase
 from langchain_experimental.sql import SQLDatabaseChain
 ```
 
@@ -200,8 +200,8 @@ result["intermediate_steps"]
 How to add memory to a SQLDatabaseChain:
 
 ```python
-from langchain_openai import OpenAI
-from langchain_community.utilities import SQLDatabase
+from langchain.llms import OpenAI
+from langchain.utilities import SQLDatabase
 from langchain_experimental.sql import SQLDatabaseChain
 ```
 
@@ -647,7 +647,7 @@ Sometimes you may not have the luxury of using OpenAI or other service-hosted la
 import logging
 import torch
 from transformers import AutoTokenizer, GPT2TokenizerFast, pipeline, AutoModelForSeq2SeqLM, AutoModelForCausalLM
-from langchain_community.llms import HuggingFacePipeline
+from langchain.llms import HuggingFacePipeline
 
 # Note: This model requires a large GPU, e.g. an 80GB A100. See documentation for other ways to run private non-OpenAI models.
 model_id = "google/flan-ul2"
@@ -679,7 +679,7 @@ local_llm = HuggingFacePipeline(pipeline=pipe)
 
 
 ```python
-from langchain_community.utilities import SQLDatabase
+from langchain.utilities import SQLDatabase
 from langchain_experimental.sql import SQLDatabaseChain
 
 db = SQLDatabase.from_uri("sqlite:///../../../../notebooks/Chinook.db", include_tables=['Customer'])
@@ -994,9 +994,9 @@ Now that you have some examples (with manually corrected output SQL), you can do
 ```python
 from langchain.prompts import FewShotPromptTemplate, PromptTemplate
 from langchain.chains.sql_database.prompt import _sqlite_prompt, PROMPT_SUFFIX
-from langchain_community.embeddings.huggingface import HuggingFaceEmbeddings
+from langchain.embeddings.huggingface import HuggingFaceEmbeddings
 from langchain.prompts.example_selector.semantic_similarity import SemanticSimilarityExampleSelector
-from langchain_community.vectorstores import Chroma
+from langchain.vectorstores import Chroma
 
 example_prompt = PromptTemplate(
     input_variables=["table_info", "input", "sql_cmd", "sql_result", "answer"],

cookbook/stepback-qa.ipynb

@@ -23,10 +23,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.prompts import ChatPromptTemplate, FewShotChatMessagePromptTemplate\n",
     "from langchain_core.output_parsers import StrOutputParser\n",
-    "from langchain_core.prompts import ChatPromptTemplate, FewShotChatMessagePromptTemplate\n",
-    "from langchain_core.runnables import RunnableLambda\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain_core.runnables import RunnableLambda"
    ]
   },
   {
@@ -129,7 +129,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_community.utilities import DuckDuckGoSearchAPIWrapper\n",
+    "from langchain.utilities import DuckDuckGoSearchAPIWrapper\n",
     "\n",
     "search = DuckDuckGoSearchAPIWrapper(max_results=4)\n",
     "\n",

cookbook/together_ai.ipynb

@@ -1,156 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "0fc0309d-4d49-4bb5-bec0-bd92c6fddb28",
-   "metadata": {},
-   "source": [
-    "## Together AI + RAG\n",
-    " \n",
-    "[Together AI](https://python.langchain.com/docs/integrations/llms/together) has a broad set of OSS LLMs via inference API.\n",
-    "\n",
-    "See [here](https://api.together.xyz/playground). We use `\"mistralai/Mixtral-8x7B-Instruct-v0.1` for RAG on the Mixtral paper.\n",
-    "\n",
-    "Download the paper:\n",
-    "https://arxiv.org/pdf/2401.04088.pdf"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d12fb75a-f707-48d5-82a5-efe2d041813c",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "! pip install --quiet pypdf chromadb tiktoken openai langchain-together"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "9ab49327-0532-4480-804c-d066c302a322",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Load\n",
-    "from langchain_community.document_loaders import PyPDFLoader\n",
-    "\n",
-    "loader = PyPDFLoader(\"~/Desktop/mixtral.pdf\")\n",
-    "data = loader.load()\n",
-    "\n",
-    "# Split\n",
-    "from langchain.text_splitter import RecursiveCharacterTextSplitter\n",
-    "\n",
-    "text_splitter = RecursiveCharacterTextSplitter(chunk_size=2000, chunk_overlap=0)\n",
-    "all_splits = text_splitter.split_documents(data)\n",
-    "\n",
-    "# Add to vectorDB\n",
-    "from langchain_community.embeddings import OpenAIEmbeddings\n",
-    "from langchain_community.vectorstores import Chroma\n",
-    "\n",
-    "\"\"\"\n",
-    "from langchain_together.embeddings import TogetherEmbeddings\n",
-    "embeddings = TogetherEmbeddings(model=\"togethercomputer/m2-bert-80M-8k-retrieval\")\n",
-    "\"\"\"\n",
-    "vectorstore = Chroma.from_documents(\n",
-    "    documents=all_splits,\n",
-    "    collection_name=\"rag-chroma\",\n",
-    "    embedding=OpenAIEmbeddings(),\n",
-    ")\n",
-    "\n",
-    "retriever = vectorstore.as_retriever()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "4efaddd9-3dbb-455c-ba54-0ad7f2d2ce0f",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from langchain_core.output_parsers import StrOutputParser\n",
-    "from langchain_core.prompts import ChatPromptTemplate\n",
-    "from langchain_core.pydantic_v1 import BaseModel\n",
-    "from langchain_core.runnables import RunnableParallel, RunnablePassthrough\n",
-    "\n",
-    "# RAG prompt\n",
-    "template = \"\"\"Answer the question based only on the following context:\n",
-    "{context}\n",
-    "\n",
-    "Question: {question}\n",
-    "\"\"\"\n",
-    "prompt = ChatPromptTemplate.from_template(template)\n",
-    "\n",
-    "# LLM\n",
-    "from langchain_community.llms import Together\n",
-    "\n",
-    "llm = Together(\n",
-    "    model=\"mistralai/Mixtral-8x7B-Instruct-v0.1\",\n",
-    "    temperature=0.0,\n",
-    "    max_tokens=2000,\n",
-    "    top_k=1,\n",
-    ")\n",
-    "\n",
-    "# RAG chain\n",
-    "chain = (\n",
-    "    RunnableParallel({\"context\": retriever, \"question\": RunnablePassthrough()})\n",
-    "    | prompt\n",
-    "    | llm\n",
-    "    | StrOutputParser()\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "88b1ee51-1b0f-4ebf-bb32-e50e843f0eeb",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'\\nAnswer: The architectural details of Mixtral are as follows:\\n- Dimension (dim): 4096\\n- Number of layers (n\\\\_layers): 32\\n- Dimension of each head (head\\\\_dim): 128\\n- Hidden dimension (hidden\\\\_dim): 14336\\n- Number of heads (n\\\\_heads): 32\\n- Number of kv heads (n\\\\_kv\\\\_heads): 8\\n- Context length (context\\\\_len): 32768\\n- Vocabulary size (vocab\\\\_size): 32000\\n- Number of experts (num\\\\_experts): 8\\n- Number of top k experts (top\\\\_k\\\\_experts): 2\\n\\nMixtral is based on a transformer architecture and uses the same modifications as described in [18], with the notable exceptions that Mixtral supports a fully dense context length of 32k tokens, and the feedforward block picks from a set of 8 distinct groups of parameters. At every layer, for every token, a router network chooses two of these groups (the “experts”) to process the token and combine their output additively. This technique increases the number of parameters of a model while controlling cost and latency, as the model only uses a fraction of the total set of parameters per token. Mixtral is pretrained with multilingual data using a context size of 32k tokens. It either matches or exceeds the performance of Llama 2 70B and GPT-3.5, over several benchmarks. In particular, Mixtral vastly outperforms Llama 2 70B on mathematics, code generation, and multilingual benchmarks.'"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "chain.invoke(\"What are the Architectural details of Mixtral?\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "755cf871-26b7-4e30-8b91-9ffd698470f4",
-   "metadata": {},
-   "source": [
-    "Trace: \n",
-    "\n",
-    "https://smith.langchain.com/public/935fd642-06a6-4b42-98e3-6074f93115cd/r"
-   ]
-  }
- ],
- "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": "3.9.16"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}

cookbook/tree_of_thought.ipynb

@@ -24,7 +24,7 @@
     }
    ],
    "source": [
-    "from langchain_openai import OpenAI\n",
+    "from langchain.llms import OpenAI\n",
     "\n",
     "llm = OpenAI(temperature=1, max_tokens=512, model=\"gpt-3.5-turbo-instruct\")"
    ]

cookbook/twitter-the-algorithm-analysis-deeplake.ipynb

@@ -37,8 +37,8 @@
     "import getpass\n",
     "import os\n",
     "\n",
-    "from langchain_community.vectorstores import DeepLake\n",
-    "from langchain_openai import OpenAIEmbeddings\n",
+    "from langchain.embeddings.openai import OpenAIEmbeddings\n",
+    "from langchain.vectorstores import DeepLake\n",
     "\n",
     "os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"OpenAI API Key:\")\n",
     "activeloop_token = getpass.getpass(\"Activeloop Token:\")\n",
@@ -110,7 +110,7 @@
    "source": [
     "import os\n",
     "\n",
-    "from langchain_community.document_loaders import TextLoader\n",
+    "from langchain.document_loaders import TextLoader\n",
     "\n",
     "root_dir = \"./the-algorithm\"\n",
     "docs = []\n",
@@ -3809,7 +3809,7 @@
    "outputs": [],
    "source": [
     "from langchain.chains import ConversationalRetrievalChain\n",
-    "from langchain_openai import ChatOpenAI\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "\n",
     "model = ChatOpenAI(model_name=\"gpt-3.5-turbo-0613\")  # switch to 'gpt-4'\n",
     "qa = ConversationalRetrievalChain.from_llm(model, retriever=retriever)"

cookbook/two_agent_debate_tools.ipynb

@@ -24,13 +24,13 @@
    "source": [
     "from typing import Callable, List\n",
     "\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.memory import ConversationBufferMemory\n",
     "from langchain.schema import (\n",
     "    AIMessage,\n",
     "    HumanMessage,\n",
     "    SystemMessage,\n",
-    ")\n",
-    "from langchain_openai import ChatOpenAI"
+    ")"
    ]
   },
   {

cookbook/two_player_dnd.ipynb

@@ -24,11 +24,11 @@
    "source": [
     "from typing import Callable, List\n",
     "\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.schema import (\n",
     "    HumanMessage,\n",
     "    SystemMessage,\n",
-    ")\n",
-    "from langchain_openai import ChatOpenAI"
+    ")"
    ]
   },
   {

cookbook/wikibase_agent.ipynb

@@ -599,7 +599,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_openai import ChatOpenAI\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "\n",
     "llm = ChatOpenAI(model_name=\"gpt-4\", temperature=0)"
    ]

docs/.local_build.sh

@@ -20,4 +20,4 @@ wget https://raw.githubusercontent.com/langchain-ai/langserve/main/README.md -O
 
 yarn
 
-poetry run quarto preview docs
+quarto preview docs

docs/docs/_templates/integration.mdx

@@ -32,7 +32,7 @@ There isn't any special setup for it.
 See a [usage example](/docs/integrations/llms/INCLUDE_REAL_NAME).
 
 ```python
-from langchain_community.llms import integration_class_REPLACE_ME
+from langchain.llms import integration_class_REPLACE_ME
 ```
 
 ## Text Embedding Models
@@ -40,7 +40,7 @@ from langchain_community.llms import integration_class_REPLACE_ME
 See a [usage example](/docs/integrations/text_embedding/INCLUDE_REAL_NAME)
 
 ```python
-from langchain_community.embeddings import integration_class_REPLACE_ME
+from langchain.embeddings import integration_class_REPLACE_ME
 ```
 
 ## Chat models
@@ -48,7 +48,7 @@ from langchain_community.embeddings import integration_class_REPLACE_ME
 See a [usage example](/docs/integrations/chat/INCLUDE_REAL_NAME)
 
 ```python
-from langchain_community.chat_models import integration_class_REPLACE_ME
+from langchain.chat_models import integration_class_REPLACE_ME
 ```
 
 ## Document Loader
@@ -56,5 +56,5 @@ from langchain_community.chat_models import integration_class_REPLACE_ME
 See a [usage example](/docs/integrations/document_loaders/INCLUDE_REAL_NAME).
 
 ```python
-from langchain_community.document_loaders import integration_class_REPLACE_ME
+from langchain.document_loaders import integration_class_REPLACE_ME
 ```

docs/docs/changelog/core.mdx

@@ -1,27 +0,0 @@
-# langchain-core
-
-## 0.1.7 (Jan 5, 2024)
-
-#### Deleted
-
-No deletions.
-
-#### Deprecated
-
-- `BaseChatModel` methods `__call__`, `call_as_llm`, `predict`, `predict_messages`. Will be removed in 0.2.0. Use `BaseChatModel.invoke` instead.
-- `BaseChatModel` methods `apredict`, `apredict_messages`. Will be removed in 0.2.0. Use `BaseChatModel.ainvoke` instead.
-- `BaseLLM` methods `__call__, `predict`, `predict_messages`. Will be removed in 0.2.0. Use `BaseLLM.invoke` instead.
-- `BaseLLM` methods `apredict`, `apredict_messages`. Will be removed in 0.2.0. Use `BaseLLM.ainvoke` instead.
-
-#### Fixed
-
-- Restrict recursive URL scraping: [#15559](https://github.com/langchain-ai/langchain/pull/15559)
-
-#### Added
-
-No additions.
-
-#### Beta
-
-- Marked `langchain_core.load.load` and `langchain_core.load.loads` as beta.
-- Marked `langchain_core.beta.runnables.context.ContextGet` and `langchain_core.beta.runnables.context.ContextSet` as beta.

docs/docs/changelog/langchain.mdx

@@ -1,36 +0,0 @@
-# langchain
-
-## 0.1.0 (Jan 5, 2024)
-
-#### Deleted
-
-No deletions.
-
-#### Deprecated
-
-Deprecated classes and methods will be removed in 0.2.0
-
-| Deprecated                | Alternative                       | Reason                                         |
-|---------------------------------|-----------------------------------|------------------------------------------------|
-| ChatVectorDBChain               | ConversationalRetrievalChain      | More general to all retrievers                 |
-| create_ernie_fn_chain           | create_ernie_fn_runnable          | Use LCEL under the hood                        |
-| created_structured_output_chain | create_structured_output_runnable | Use LCEL under the hood                        |
-| NatBotChain                     |                                   | Not used                                       |
-| create_openai_fn_chain          | create_openai_fn_runnable         | Use LCEL under the hood                        |
-| create_structured_output_chain  | create_structured_output_runnable | Use LCEL under the hood                        |
-| load_query_constructor_chain    | load_query_constructor_runnable   | Use LCEL under the hood                        |
-| VectorDBQA                      | RetrievalQA                       | More general to all retrievers                 |
-| Sequential Chain                | LCEL                              | Obviated by LCEL                               |
-| SimpleSequentialChain           | LCEL                              | Obviated by LCEL                               |
-| TransformChain                  | LCEL/RunnableLambda               | Obviated by LCEL                               |
-| create_tagging_chain            | create_structured_output_runnable | Use LCEL under the hood                        |
-| ChatAgent                       | create_react_agent                | Use LCEL builder over a class                  |
-| ConversationalAgent             | create_react_agent                | Use LCEL builder over a class                  |
-| ConversationalChatAgent         | create_json_chat_agent            | Use LCEL builder over a class                  |
-| initialize_agent                | Individual create agent methods   | Individual create agent methods are more clear |
-| ZeroShotAgent                   | create_react_agent                | Use LCEL builder over a class                  |
-| OpenAIFunctionsAgent            | create_openai_functions_agent     | Use LCEL builder over a class                  |
-| OpenAIMultiFunctionsAgent       | create_openai_tools_agent         | Use LCEL builder over a class                  |
-| SelfAskWithSearchAgent          | create_self_ask_with_search       | Use LCEL builder over a class                  |
-| StructuredChatAgent             | create_structured_chat_agent      | Use LCEL builder over a class                  |
-| XMLAgent                        | create_xml_agent                  | Use LCEL builder over a class                  |

docs/docs/community.md

@@ -0,0 +1,53 @@
+# Community navigator
+
+Hi! Thanks for being here. We’re lucky to have a community of so many passionate developers building with LangChain–we have so much to teach and learn from each other. Community members contribute code, host meetups, write blog posts, amplify each other’s work, become each other's customers and collaborators, and so much more.
+
+Whether you’re new to LangChain, looking to go deeper, or just want to get more exposure to the world of building with LLMs, this page can point you in the right direction. 
+
+- **🦜 Contribute to LangChain**
+
+- **🌍 Meetups, Events, and Hackathons**
+
+- **📣 Help Us Amplify Your Work**
+
+- **💬 Stay in the loop**
+
+
+# 🦜 Contribute to LangChain
+
+LangChain is the product of over 5,000+ contributions by 1,500+ contributors, and there is ******still****** so much to do together. Here are some ways to get involved:
+
+- **[Open a pull request](https://github.com/langchain-ai/langchain/issues):** We’d appreciate all forms of contributions–new features, infrastructure improvements, better documentation, bug fixes, etc. If you have an improvement or an idea, we’d love to work on it with you.
+- **[Read our contributor guidelines:](./contributing/)** We ask contributors to follow a ["fork and pull request"](https://docs.github.com/en/get-started/quickstart/contributing-to-projects) workflow, run a few local checks for formatting, linting, and testing before submitting, and follow certain documentation and testing conventions.
+    - **First time contributor?** [Try one of these PRs with the “good first issue” tag](https://github.com/langchain-ai/langchain/contribute).
+- **Become an expert:** Our experts help the community by answering product questions in Discord. If that’s a role you’d like to play, we’d be so grateful! (And we have some special experts-only goodies/perks we can tell you more about). Send us an email to introduce yourself at hello@langchain.dev and we’ll take it from there!
+- **Integrate with LangChain:** If your product integrates with LangChain–or aspires to–we want to help make sure the experience is as smooth as possible for you and end users. Send us an email at hello@langchain.dev and tell us what you’re working on.
+    - **Become an Integration Maintainer:** Partner with our team to ensure your integration stays up-to-date and talk directly with users (and answer their inquiries) in our Discord. Introduce yourself at hello@langchain.dev if you’d like to explore this role.
+
+
+# 🌍 Meetups, Events, and Hackathons
+
+One of our favorite things about working in AI is how much enthusiasm there is for building together. We want to help make that as easy and impactful for you as possible! 
+- **Find a meetup, hackathon, or webinar:** You can find the one for you on our [global events calendar](https://mirror-feeling-d80.notion.site/0bc81da76a184297b86ca8fc782ee9a3?v=0d80342540df465396546976a50cfb3f).  
+    - **Submit an event to our calendar:** Email us at events@langchain.dev with a link to your event page! We can also help you spread the word with our local communities.
+- **Host a meetup:** If you want to bring a group of builders together, we want to help! We can publicize your event on our event calendar/Twitter, share it with our local communities in Discord, send swag, or potentially hook you up with a sponsor. Email us at events@langchain.dev to tell us about your event!
+- **Become a meetup sponsor:** We often hear from groups of builders that want to get together, but are blocked or limited on some dimension (space to host, budget for snacks, prizes to distribute, etc.). If you’d like to help, send us an email to events@langchain.dev we can share more about how it works!
+- **Speak at an event:** Meetup hosts are always looking for great speakers, presenters, and panelists. If you’d like to do that at an event, send us an email to hello@langchain.dev with more information about yourself, what you want to talk about, and what city you’re based in and we’ll try to match you with an upcoming event!
+- **Tell us about your LLM community:** If you host or participate in a community that would welcome support from LangChain and/or our team, send us an email at hello@langchain.dev and let us know how we can help.
+
+# 📣 Help Us Amplify Your Work
+
+If you’re working on something you’re proud of, and think the LangChain community would benefit from knowing about it, we want to help you show it off.
+
+- **Post about your work and mention us:** We love hanging out on Twitter to see what people in the space are talking about and working on. If you tag [@langchainai](https://twitter.com/LangChainAI), we’ll almost certainly see it and can show you some love.
+- **Publish something on our blog:** If you’re writing about your experience building with LangChain, we’d love to post (or crosspost) it on our blog! E-mail hello@langchain.dev with a draft of your post! Or even an idea for something you want to write about.
+- **Get your product onto our [integrations hub](https://integrations.langchain.com/):** Many developers take advantage of our seamless integrations with other products, and come to our integrations hub to find out who those are. If you want to get your product up there, tell us about it (and how it works with LangChain) at hello@langchain.dev.
+
+# ☀️ Stay in the loop
+
+Here’s where our team hangs out, talks shop, spotlights cool work, and shares what we’re up to. We’d love to see you there too.
+
+- **[Twitter](https://twitter.com/LangChainAI):** We post about what we’re working on and what cool things we’re seeing in the space. If you tag @langchainai in your post, we’ll almost certainly see it, and can show you some love!
+- **[Discord](https://discord.gg/6adMQxSpJS):** connect with over 30,000 developers who are building with LangChain.
+- **[GitHub](https://github.com/langchain-ai/langchain):** Open pull requests, contribute to a discussion, and/or contribute
+- **[Subscribe to our bi-weekly Release Notes](https://6w1pwbss0py.typeform.com/to/KjZB1auB):** a twice/month email roundup of the coolest things going on in our orbit

docs/docs/contributing/faq.mdx

@@ -1,26 +0,0 @@
----
-sidebar_position: 6
-sidebar_label: FAQ
----
-# Frequently Asked Questions
-
-## Pull Requests (PRs)
-
-### How do I allow maintainers to edit my PR?
-
-When you submit a pull request, there may be additional changes
-necessary before merging it. Oftentimes, it is more efficient for the
-maintainers to make these changes themselves before merging, rather than asking you
-to do so in code review.
-
-By default, most pull requests will have a 
-`✅ Maintainers are allowed to edit this pull request.`
-badge in the right-hand sidebar.
-
-If you do not see this badge, you may have this setting off for the fork you are
-pull-requesting from. See [this Github docs page](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/allowing-changes-to-a-pull-request-branch-created-from-a-fork)
-for more information.
-
-Notably, Github doesn't allow this setting to be enabled for forks in **organizations** ([issue](https://github.com/orgs/community/discussions/5634)).
-If you are working in an organization, we recommend submitting your PR from a personal
-fork in order to enable this setting.

docs/docs/contributing/index.mdx

@@ -12,9 +12,9 @@ As an open-source project in a rapidly developing field, we are extremely open t
 
 There are many ways to contribute to LangChain. Here are some common ways people contribute:
 
-- [**Documentation**](./documentation.mdx): Help improve our docs, including this one!
-- [**Code**](./code.mdx): Help us write code, fix bugs, or improve our infrastructure.
-- [**Integrations**](integrations.mdx): Help us integrate with your favorite vendors and tools.
+- [**Documentation**](./documentation): Help improve our docs, including this one!
+- [**Code**](./code): Help us write code, fix bugs, or improve our infrastructure.
+- [**Integrations**](./integrations): Help us integrate with your favorite vendors and tools.
 
 ### 🚩GitHub Issues
 
@@ -40,8 +40,3 @@ smooth for future contributors.
 In a similar vein, we do enforce certain linting, formatting, and documentation standards in the codebase.
 If you are finding these difficult (or even just annoying) to work with, feel free to contact a maintainer for help -
 we do not want these to get in the way of getting good code into the codebase.
-
-# 🌟 Recognition
-
-If your contribution has made its way into a release, we will want to give you credit on Twitter (only if you want though)!
-If you have a Twitter account you would like us to mention, please let us know in the PR or through another means.

docs/docs/contributing/integrations.mdx

@@ -53,9 +53,9 @@ And we would write tests in:
 - Integration tests: `libs/community/tests/integration_tests/chat_models/test_parrot_link.py`
 
 And add documentation to:
-
 - `docs/docs/integrations/chat/parrot_link.ipynb`
 
+- `docs/docs/
 ## Partner Packages
 
 Partner packages are in `libs/partners/*` and are installed by users with `pip install langchain-{partner}`, and exported members can be imported with code like 

docs/docs/contributing/packages.mdx

@@ -0,0 +1,56 @@
+---
+sidebar_label: Package Versioning
+sidebar_position: 4
+---
+
+# 📕 Package Versioning
+
+As of now, LangChain has an ad hoc release process: releases are cut with high frequency by
+a maintainer and published to [PyPI](https://pypi.org/). 
+The different packages are versioned slightly differently.
+
+## `langchain-core`
+
+`langchain-core` is currently on version `0.1.x`. 
+
+As `langchain-core` contains the base abstractions and runtime for the whole LangChain ecosystem, we will communicate any breaking changes with advance notice and version bumps. The exception for this is anything in `langchain_core.beta`. The reason for `langchain_core.beta` is that given the rate of change of the field, being able to move quickly is still a priority, and this module is our attempt to do so.
+
+Minor version increases will occur for:
+
+- Breaking changes for any public interfaces NOT in `langchain_core.beta`
+
+Patch version increases will occur for:
+
+- Bug fixes
+- New features
+- Any changes to private interfaces
+- Any changes to `langchain_core.beta`
+
+## `langchain`
+
+`langchain` is currently on version `0.0.x`
+
+All changes will be accompanied by a patch version increase. Any changes to public interfaces are nearly always done in a backwards compatible way and will be communicated ahead of time when they are not backwards compatible.
+
+We are targeting January 2024 for a release of `langchain` v0.1, at which point `langchain` will adopt the same versioning policy as `langchain-core`.
+
+## `langchain-community`
+
+`langchain-community` is currently on version `0.0.x`
+
+All changes will be accompanied by a patch version increase.
+
+## `langchain-experimental`
+
+`langchain-experimental` is currently on version `0.0.x`
+
+All changes will be accompanied by a patch version increase.
+
+## Partner Packages
+
+Partner packages are versioned independently.
+
+# 🌟 Recognition
+
+If your contribution has made its way into a release, we will want to give you credit on Twitter (only if you want though)!
+If you have a Twitter account you would like us to mention, please let us know in the PR or through another means.

docs/docs/expression_language/cookbook/agent.ipynb

@@ -12,20 +12,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 1,
    "id": "af4381de",
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain import hub\n",
-    "from langchain.agents import AgentExecutor, tool\n",
-    "from langchain.agents.output_parsers import XMLAgentOutputParser\n",
-    "from langchain_community.chat_models import ChatAnthropic"
+    "from langchain.agents import AgentExecutor, XMLAgent, tool\n",
+    "from langchain.chat_models import ChatAnthropic"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "id": "24cc8134",
    "metadata": {},
    "outputs": [],
@@ -35,7 +33,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "id": "67c0b0e4",
    "metadata": {},
    "outputs": [],
@@ -48,7 +46,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "id": "7203b101",
    "metadata": {},
    "outputs": [],
@@ -58,18 +56,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "id": "b68e756d",
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Get the prompt to use - you can modify this!\n",
-    "prompt = hub.pull(\"hwchase17/xml-agent-convo\")"
+    "# Get prompt to use\n",
+    "prompt = XMLAgent.get_default_prompt()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "id": "61ab3e9a",
    "metadata": {},
    "outputs": [],
@@ -109,27 +107,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 7,
    "id": "e92f1d6f",
    "metadata": {},
    "outputs": [],
    "source": [
     "agent = (\n",
     "    {\n",
-    "        \"input\": lambda x: x[\"input\"],\n",
-    "        \"agent_scratchpad\": lambda x: convert_intermediate_steps(\n",
+    "        \"question\": lambda x: x[\"question\"],\n",
+    "        \"intermediate_steps\": lambda x: convert_intermediate_steps(\n",
     "            x[\"intermediate_steps\"]\n",
     "        ),\n",
     "    }\n",
     "    | prompt.partial(tools=convert_tools(tool_list))\n",
     "    | model.bind(stop=[\"</tool_input>\", \"</final_answer>\"])\n",
-    "    | XMLAgentOutputParser()\n",
+    "    | XMLAgent.get_default_output_parser()\n",
     ")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 8,
    "id": "6ce6ec7a",
    "metadata": {},
    "outputs": [],
@@ -139,7 +137,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 9,
    "id": "fb5cb2e3",
    "metadata": {},
    "outputs": [
@@ -150,8 +148,10 @@
       "\n",
       "\n",
       "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
-      "\u001b[32;1m\u001b[1;3m <tool>search</tool><tool_input>weather in New York\u001b[0m\u001b[36;1m\u001b[1;3m32 degrees\u001b[0m\u001b[32;1m\u001b[1;3m <tool>search</tool>\n",
-      "<tool_input>weather in New York\u001b[0m\u001b[36;1m\u001b[1;3m32 degrees\u001b[0m\u001b[32;1m\u001b[1;3m <final_answer>The weather in New York is 32 degrees\u001b[0m\n",
+      "\u001b[32;1m\u001b[1;3m <tool>search</tool>\n",
+      "<tool_input>weather in new york\u001b[0m\u001b[36;1m\u001b[1;3m32 degrees\u001b[0m\u001b[32;1m\u001b[1;3m\n",
+      "\n",
+      "<final_answer>The weather in New York is 32 degrees\u001b[0m\n",
       "\n",
       "\u001b[1m> Finished chain.\u001b[0m\n"
      ]
@@ -159,17 +159,17 @@
     {
      "data": {
       "text/plain": [
-       "{'input': 'whats the weather in New york?',\n",
+       "{'question': 'whats the weather in New york?',\n",
        " 'output': 'The weather in New York is 32 degrees'}"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "agent_executor.invoke({\"input\": \"whats the weather in New york?\"})"
+    "agent_executor.invoke({\"question\": \"whats the weather in New york?\"})"
    ]
   },
   {

docs/docs/expression_language/cookbook/code_writing.ipynb

@@ -10,16 +10,6 @@
     "Example of how to use LCEL to write Python code."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "0653c7c7",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "%pip install --upgrade --quiet  langchain-core langchain-experimental langchain-openai"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -27,12 +17,12 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_core.output_parsers import StrOutputParser\n",
-    "from langchain_core.prompts import (\n",
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.prompts import (\n",
     "    ChatPromptTemplate,\n",
     ")\n",
-    "from langchain_experimental.utilities import PythonREPL\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain_core.output_parsers import StrOutputParser\n",
+    "from langchain_experimental.utilities import PythonREPL"
    ]
   },
   {

docs/docs/expression_language/cookbook/embedding_router.ipynb

@@ -12,16 +12,6 @@
     "One especially useful technique is to use embeddings to route a query to the most relevant prompt. Here's a very simple example."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b793a0aa",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "%pip install --upgrade --quiet  langchain-core langchain langchain-openai"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -29,11 +19,12 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.embeddings import OpenAIEmbeddings\n",
+    "from langchain.prompts import PromptTemplate\n",
     "from langchain.utils.math import cosine_similarity\n",
     "from langchain_core.output_parsers import StrOutputParser\n",
-    "from langchain_core.prompts import PromptTemplate\n",
     "from langchain_core.runnables import RunnableLambda, RunnablePassthrough\n",
-    "from langchain_openai import ChatOpenAI, OpenAIEmbeddings\n",
     "\n",
     "physics_template = \"\"\"You are a very smart physics professor. \\\n",
     "You are great at answering questions about physics in a concise and easy to understand manner. \\\n",

docs/docs/expression_language/cookbook/memory.ipynb

@@ -10,16 +10,6 @@
     "This shows how to add memory to an arbitrary chain. Right now, you can use the memory classes but need to hook it up manually"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "18753dee",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "%pip install --upgrade --quiet  langchain langchain-openai"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -29,10 +19,10 @@
    "source": [
     "from operator import itemgetter\n",
     "\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.memory import ConversationBufferMemory\n",
-    "from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
+    "from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
     "from langchain_core.runnables import RunnableLambda, RunnablePassthrough\n",
-    "from langchain_openai import ChatOpenAI\n",
     "\n",
     "model = ChatOpenAI()\n",
     "prompt = ChatPromptTemplate.from_messages(\n",

docs/docs/expression_language/cookbook/moderation.ipynb

@@ -10,16 +10,6 @@
     "This shows how to add in moderation (or other safeguards) around your LLM application."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6acf3505",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "%pip install --upgrade --quiet  langchain langchain-openai"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 20,
@@ -28,8 +18,8 @@
    "outputs": [],
    "source": [
     "from langchain.chains import OpenAIModerationChain\n",
-    "from langchain_core.prompts import ChatPromptTemplate\n",
-    "from langchain_openai import OpenAI"
+    "from langchain.llms import OpenAI\n",
+    "from langchain.prompts import ChatPromptTemplate"
    ]
   },
   {

docs/docs/expression_language/cookbook/multiple_chains.ipynb

@@ -19,14 +19,6 @@
     "Runnables can easily be used to string together multiple Chains"
    ]
   },
-  {
-   "cell_type": "raw",
-   "id": "0f316b5c",
-   "metadata": {},
-   "source": [
-    "%pip install --upgrade --quiet  langchain langchain-openai"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 4,
@@ -47,9 +39,9 @@
    "source": [
     "from operator import itemgetter\n",
     "\n",
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
     "from langchain.schema import StrOutputParser\n",
-    "from langchain_core.prompts import ChatPromptTemplate\n",
-    "from langchain_openai import ChatOpenAI\n",
     "\n",
     "prompt1 = ChatPromptTemplate.from_template(\"what is the city {person} is from?\")\n",
     "prompt2 = ChatPromptTemplate.from_template(\n",

docs/docs/expression_language/cookbook/prompt_llm_parser.ipynb

@@ -35,14 +35,6 @@
     "Note, you can mix and match PromptTemplate/ChatPromptTemplates and LLMs/ChatModels as you like here."
    ]
   },
-  {
-   "cell_type": "raw",
-   "id": "ef79a54b",
-   "metadata": {},
-   "source": [
-    "%pip install --upgrade --quiet  langchain langchain-openai"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -50,8 +42,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_core.prompts import ChatPromptTemplate\n",
-    "from langchain_openai import ChatOpenAI\n",
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
     "\n",
     "prompt = ChatPromptTemplate.from_template(\"tell me a joke about {foo}\")\n",
     "model = ChatOpenAI()\n",

docs/docs/expression_language/cookbook/prompt_size.ipynb

@@ -12,16 +12,6 @@
     "With LCEL, it's easy to add custom functionality for managing the size of prompts within your chain or agent. Let's look at simple agent example that can search Wikipedia for information."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1846587d",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "%pip install --upgrade --quiet  langchain langchain-openai wikipedia"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -29,17 +19,19 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "# !pip install langchain wikipedia\n",
+    "\n",
     "from operator import itemgetter\n",
     "\n",
     "from langchain.agents import AgentExecutor, load_tools\n",
     "from langchain.agents.format_scratchpad import format_to_openai_function_messages\n",
     "from langchain.agents.output_parsers import OpenAIFunctionsAgentOutputParser\n",
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
     "from langchain.prompts.chat import ChatPromptValue\n",
     "from langchain.tools import WikipediaQueryRun\n",
-    "from langchain_community.tools.convert_to_openai import format_tool_to_openai_function\n",
-    "from langchain_community.utilities import WikipediaAPIWrapper\n",
-    "from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain.tools.render import format_tool_to_openai_function\n",
+    "from langchain.utilities import WikipediaAPIWrapper"
    ]
   },
   {

docs/docs/expression_language/cookbook/retrieval.ipynb

@@ -26,7 +26,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%pip install --upgrade --quiet  langchain langchain-openai faiss-cpu tiktoken"
+    "!pip install langchain openai faiss-cpu tiktoken"
    ]
   },
   {
@@ -38,11 +38,12 @@
    "source": [
     "from operator import itemgetter\n",
     "\n",
-    "from langchain_community.vectorstores import FAISS\n",
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.embeddings import OpenAIEmbeddings\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
+    "from langchain.vectorstores import FAISS\n",
     "from langchain_core.output_parsers import StrOutputParser\n",
-    "from langchain_core.prompts import ChatPromptTemplate\n",
-    "from langchain_core.runnables import RunnableLambda, RunnablePassthrough\n",
-    "from langchain_openai import ChatOpenAI, OpenAIEmbeddings"
+    "from langchain_core.runnables import RunnableLambda, RunnablePassthrough"
    ]
   },
   {

docs/docs/expression_language/cookbook/sql_db.ipynb

@@ -19,14 +19,6 @@
     "We can replicate our SQLDatabaseChain with Runnables."
    ]
   },
-  {
-   "cell_type": "raw",
-   "id": "b3121aa8",
-   "metadata": {},
-   "source": [
-    "%pip install --upgrade --quiet  langchain langchain-openai"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -34,7 +26,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_core.prompts import ChatPromptTemplate\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
     "\n",
     "template = \"\"\"Based on the table schema below, write a SQL query that would answer the user's question:\n",
     "{schema}\n",
@@ -51,7 +43,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_community.utilities import SQLDatabase"
+    "from langchain.utilities import SQLDatabase"
    ]
   },
   {
@@ -101,9 +93,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain_core.output_parsers import StrOutputParser\n",
     "from langchain_core.runnables import RunnablePassthrough\n",
-    "from langchain_openai import ChatOpenAI\n",
     "\n",
     "model = ChatOpenAI()\n",
     "\n",

docs/docs/expression_language/cookbook/tools.ipynb

@@ -17,7 +17,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%pip install --upgrade --quiet  langchain langchain-openai duckduckgo-search"
+    "!pip install duckduckgo-search"
    ]
   },
   {
@@ -27,10 +27,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
     "from langchain.tools import DuckDuckGoSearchRun\n",
-    "from langchain_core.output_parsers import StrOutputParser\n",
-    "from langchain_core.prompts import ChatPromptTemplate\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain_core.output_parsers import StrOutputParser"
    ]
   },
   {

docs/docs/expression_language/get_started.ipynb

@@ -30,38 +30,30 @@
     "The most basic and common use case is chaining a prompt template and a model together. To see how this works, let's create a chain that takes a topic and generates a joke:"
    ]
   },
-  {
-   "cell_type": "raw",
-   "id": "278b0027",
-   "metadata": {},
-   "source": [
-    "%pip install --upgrade --quiet  langchain-core langchain-community langchain-openai"
-   ]
-  },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 7,
    "id": "466b65b3",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "\"Why don't ice creams ever get invited to parties?\\n\\nBecause they always drip when things heat up!\""
+       "\"Why did the ice cream go to therapy?\\n\\nBecause it had too many toppings and couldn't find its cone-fidence!\""
       ]
      },
-     "execution_count": 1,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "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",
     "prompt = ChatPromptTemplate.from_template(\"tell me a short joke about {topic}\")\n",
-    "model = ChatOpenAI(model=\"gpt-4\")\n",
+    "model = ChatOpenAI()\n",
     "output_parser = StrOutputParser()\n",
     "\n",
     "chain = prompt | model | output_parser\n",
@@ -97,7 +89,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 8,
    "id": "b8656990",
    "metadata": {},
    "outputs": [
@@ -107,7 +99,7 @@
        "ChatPromptValue(messages=[HumanMessage(content='tell me a short joke about ice cream')])"
       ]
      },
-     "execution_count": 2,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -119,7 +111,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 9,
    "id": "e6034488",
    "metadata": {},
    "outputs": [
@@ -129,7 +121,7 @@
        "[HumanMessage(content='tell me a short joke about ice cream')]"
       ]
      },
-     "execution_count": 3,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -140,7 +132,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 10,
    "id": "60565463",
    "metadata": {},
    "outputs": [
@@ -150,7 +142,7 @@
        "'Human: tell me a short joke about ice cream'"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -171,17 +163,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 11,
    "id": "33cf5f72",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "AIMessage(content=\"Why don't ice creams ever get invited to parties?\\n\\nBecause they always bring a melt down!\")"
+       "AIMessage(content=\"Why did the ice cream go to therapy? \\n\\nBecause it had too many toppings and couldn't find its cone-fidence!\")"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -201,23 +193,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 12,
    "id": "8feb05da",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'\\n\\nRobot: Why did the ice cream truck break down? Because it had a meltdown!'"
+       "'\\n\\nRobot: Why did the ice cream go to therapy? Because it had a rocky road.'"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "from langchain_openai.llms import OpenAI\n",
+    "from langchain.llms import OpenAI\n",
     "\n",
     "llm = OpenAI(model=\"gpt-3.5-turbo-instruct\")\n",
     "llm.invoke(prompt_value)"
@@ -332,12 +324,12 @@
     "# Requires:\n",
     "# pip install langchain docarray tiktoken\n",
     "\n",
-    "from langchain_community.vectorstores import DocArrayInMemorySearch\n",
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.embeddings import OpenAIEmbeddings\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
+    "from langchain.vectorstores import DocArrayInMemorySearch\n",
     "from langchain_core.output_parsers import StrOutputParser\n",
-    "from langchain_core.prompts import ChatPromptTemplate\n",
     "from langchain_core.runnables import RunnableParallel, RunnablePassthrough\n",
-    "from langchain_openai.chat_models import ChatOpenAI\n",
-    "from langchain_openai.embeddings import OpenAIEmbeddings\n",
     "\n",
     "vectorstore = DocArrayInMemorySearch.from_texts(\n",
     "    [\"harrison worked at kensho\", \"bears like to eat honey\"],\n",
@@ -494,7 +486,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.4"
+   "version": "3.9.1"
   }
  },
  "nbformat": 4,

docs/docs/expression_language/how_to/binding.ipynb

@@ -12,16 +12,6 @@
     "Suppose we have a simple prompt + model sequence:"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c5dad8b5",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "%pip install --upgrade --quiet  langchain langchain-openai"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -29,10 +19,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
     "from langchain.schema import StrOutputParser\n",
-    "from langchain_core.prompts import ChatPromptTemplate\n",
-    "from langchain_core.runnables import RunnablePassthrough\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain_core.runnables import RunnablePassthrough"
    ]
   },
   {

docs/docs/expression_language/how_to/configure.ipynb

@@ -34,16 +34,6 @@
     "With LLMs we can configure things like temperature"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "40ed76a2",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "%pip install --upgrade --quiet  langchain langchain-openai"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 35,
@@ -51,9 +41,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.prompts import PromptTemplate\n",
     "from langchain_core.runnables import ConfigurableField\n",
-    "from langchain_openai import ChatOpenAI\n",
     "\n",
     "model = ChatOpenAI(temperature=0).configurable_fields(\n",
     "    temperature=ConfigurableField(\n",
@@ -273,10 +263,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langchain.chat_models import ChatAnthropic, ChatOpenAI\n",
     "from langchain.prompts import PromptTemplate\n",
-    "from langchain_community.chat_models import ChatAnthropic\n",
-    "from langchain_core.runnables import ConfigurableField\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain_core.runnables import ConfigurableField"
    ]
   },
   {

docs/docs/expression_language/how_to/decorator.ipynb

@@ -1,136 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "b45110ef",
-   "metadata": {},
-   "source": [
-    "# Create a runnable with the `@chain` decorator\n",
-    "\n",
-    "You can also turn an arbitrary function into a chain by adding a `@chain` decorator. This is functionaly equivalent to wrapping in a [`RunnableLambda`](./functions).\n",
-    "\n",
-    "This will have the benefit of improved observability by tracing your chain correctly. Any calls to runnables inside this function will be traced as nested childen.\n",
-    "\n",
-    "It will also allow you to use this as any other runnable, compose it in chain, etc.\n",
-    "\n",
-    "Let's take a look at this in action!"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "23b2b564",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "%pip install --upgrade --quiet  langchain langchain-openai"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "id": "d9370420",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from langchain_core.output_parsers import StrOutputParser\n",
-    "from langchain_core.prompts import ChatPromptTemplate\n",
-    "from langchain_core.runnables import chain\n",
-    "from langchain_openai import ChatOpenAI"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "id": "b7f74f7e",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "prompt1 = ChatPromptTemplate.from_template(\"Tell me a joke about {topic}\")\n",
-    "prompt2 = ChatPromptTemplate.from_template(\"What is the subject of this joke: {joke}\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "id": "2b0365c4",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "@chain\n",
-    "def custom_chain(text):\n",
-    "    prompt_val1 = prompt1.invoke({\"topic\": text})\n",
-    "    output1 = ChatOpenAI().invoke(prompt_val1)\n",
-    "    parsed_output1 = StrOutputParser().invoke(output1)\n",
-    "    chain2 = prompt2 | ChatOpenAI() | StrOutputParser()\n",
-    "    return chain2.invoke({\"joke\": parsed_output1})"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "904d6872",
-   "metadata": {},
-   "source": [
-    "`custom_chain` is now a runnable, meaning you will need to use `invoke`"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "id": "6448bdd3",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'The subject of this joke is bears.'"
-      ]
-     },
-     "execution_count": 21,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "custom_chain.invoke(\"bears\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "aa767ea9",
-   "metadata": {},
-   "source": [
-    "If you check out your LangSmith traces, you should see a `custom_chain` trace in there, with the calls to OpenAI nested underneath"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f1245bdc",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "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": "3.10.1"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}