docs: update apify integration

docs/docs/integrations/document_loaders/apify_dataset.ipynb

@@ -2,7 +2,9 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "id": "xwiDq5fOuoRn"
+   },
    "source": [
     "# Apify Dataset\n",
     "\n",
@@ -20,33 +22,63 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "id": "qRW2-mokuoRp",
     "tags": []
    },
    "outputs": [],
    "source": [
-    "%pip install --upgrade --quiet  apify-client"
+    "%pip install --upgrade --quiet langchain langchain-apify langchain-openai"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "id": "8jRVq16LuoRq"
+   },
    "source": [
     "First, import `ApifyDatasetLoader` into your source code:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
+   "execution_count": 2,
+   "metadata": {
+    "id": "umXQHqIJuoRq"
+   },
    "outputs": [],
    "source": [
-    "from langchain_community.document_loaders import ApifyDatasetLoader\n",
+    "from langchain_apify import ApifyDatasetLoader\n",
     "from langchain_core.documents import Document"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "id": "NjGwKy59vz1X"
+   },
+   "source": [
+    "Find your [Apify API token](https://console.apify.com/account/integrations) and [OpenAI API key](https://platform.openai.com/account/api-keys) and initialize these into environment variable:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "id": "AvzNtyCxwDdr"
+   },
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "\n",
+    "os.environ[\"APIFY_API_TOKEN\"] = \"your-apify-api-token\"\n",
+    "os.environ[\"OPENAI_API_KEY\"] = \"your-openai-api-key\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "d1O-KL48uoRr"
+   },
    "source": [
     "Then provide a function that maps Apify dataset record fields to LangChain `Document` format.\n",
     "\n",
@@ -64,8 +96,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
+   "execution_count": 8,
+   "metadata": {
+    "id": "m1SpA7XZuoRr"
+   },
    "outputs": [],
    "source": [
     "loader = ApifyDatasetLoader(\n",
@@ -78,16 +112,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
+   "execution_count": 9,
+   "metadata": {
+    "id": "0hWX7ABsuoRs"
+   },
    "outputs": [],
    "source": [
     "data = loader.load()"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "id": "EJCVFVKNuoRs"
+   },
    "source": [
     "## An example with question answering\n",
     "\n",
@@ -96,21 +134,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
+   "execution_count": 14,
+   "metadata": {
+    "id": "sNisJKzZuoRt"
+   },
    "outputs": [],
    "source": [
     "from langchain.indexes import VectorstoreIndexCreator\n",
-    "from langchain_community.utilities import ApifyWrapper\n",
+    "from langchain_apify import ApifyWrapper\n",
     "from langchain_core.documents import Document\n",
-    "from langchain_openai import OpenAI\n",
+    "from langchain_core.vectorstores import InMemoryVectorStore\n",
+    "from langchain_openai import ChatOpenAI\n",
     "from langchain_openai.embeddings import OpenAIEmbeddings"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
+   "execution_count": 15,
+   "metadata": {
+    "id": "qcfmnbdDuoRu"
+   },
    "outputs": [],
    "source": [
     "loader = ApifyDatasetLoader(\n",
@@ -123,27 +166,47 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
+   "execution_count": 16,
+   "metadata": {
+    "id": "8b0xzKJxuoRv"
+   },
    "outputs": [],
    "source": [
-    "index = VectorstoreIndexCreator(embedding=OpenAIEmbeddings()).from_loaders([loader])"
+    "index = VectorstoreIndexCreator(\n",
+    "    vectorstore_cls=InMemoryVectorStore, embedding=OpenAIEmbeddings()\n",
+    ").from_loaders([loader])"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
+   "execution_count": 17,
+   "metadata": {
+    "id": "7zPXGsVFwUGA"
+   },
+   "outputs": [],
+   "source": [
+    "llm = ChatOpenAI(model=\"gpt-4o-mini\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "id": "ecWrdM4guoRv"
+   },
    "outputs": [],
    "source": [
     "query = \"What is Apify?\"\n",
-    "result = index.query_with_sources(query, llm=OpenAI())"
+    "result = index.query_with_sources(query, llm=llm)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
+   "execution_count": null,
+   "metadata": {
+    "id": "QH8r44e9uoRv",
+    "outputId": "361fe050-f75d-4d5a-c327-5e7bd190fba5"
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -162,6 +225,9 @@
   }
  ],
  "metadata": {
+  "colab": {
+   "provenance": []
+  },
   "kernelspec": {
    "display_name": "Python 3 (ipykernel)",
    "language": "python",
@@ -181,5 +247,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 4
-}
+ "nbformat_minor": 0
+}

docs/docs/integrations/providers/apify.mdx

@@ -14,28 +14,45 @@ blogs, or knowledge bases.
 
 ## Installation and Setup
 
-- Install the Apify API client for Python with `pip install apify-client`
+- Install the LangChain Apify package for Python with:
+```bash
+pip install langchain-apify
+```
 - Get your [Apify API token](https://console.apify.com/account/integrations) and either set it as
-  an environment variable (`APIFY_API_TOKEN`) or pass it to the `ApifyWrapper` as `apify_api_token` in the constructor.
+  an environment variable (`APIFY_API_TOKEN`) or pass it as `apify_api_token` in the constructor.
+
+## Tool
+
+You can use the `ApifyActorsTool` to use Apify Actors with agents.
 
+```python
+from langchain_apify import ApifyActorsTool
+```
 
-## Utility
+See [this notebook](/docs/integrations/tools/apify_actors) for example usage.
+
+For more information on how to use this tool, visit [the Apify integration documentation](https://docs.apify.com/platform/integrations/langgraph).
+
+## Wrapper
 
 You can use the `ApifyWrapper` to run Actors on the Apify platform.
 
 ```python
-from langchain_community.utilities import ApifyWrapper
+from langchain_apify import ApifyWrapper
 ```
 
-For more information on this wrapper, see [the API reference](https://python.langchain.com/api_reference/community/utilities/langchain_community.utilities.apify.ApifyWrapper.html).
+For more information on how to use this wrapper, see [the Apify integration documentation](https://docs.apify.com/platform/integrations/langchain).
 
 
 ## Document loader
 
 You can also use our `ApifyDatasetLoader` to get data from Apify dataset.
 
 ```python
-from langchain_community.document_loaders import ApifyDatasetLoader
+from langchain_apify import ApifyDatasetLoader
 ```
 
 For a more detailed walkthrough of this loader, see [this notebook](/docs/integrations/document_loaders/apify_dataset).
+
+
+Source code for this integration can be found in the [LangChain Apify repository](https://github.com/apify/langchain-apify).