langchain/docs/modules/indexes/vectorstores/examples/azuresearch.ipynb

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  {
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   "metadata": {},
   "source": [
    "# Azure Cognitive Search"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Install Azure Cognitive Search SDK"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install --index-url=https://pkgs.dev.azure.com/azure-sdk/public/_packaging/azure-sdk-for-python/pypi/simple/ azure-search-documents==11.4.0a20230509004\n",
    "!pip install azure-identity"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import required libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os, json\n",
    "import openai\n",
    "from dotenv import load_dotenv\n",
    "from langchain.embeddings.openai import OpenAIEmbeddings\n",
    "from langchain.schema import BaseRetriever\n",
    "from langchain.vectorstores.azuresearch import AzureSearch"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Configure OpenAI settings\n",
    "Configure the OpenAI settings to use Azure OpenAI or OpenAI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load environment variables from a .env file using load_dotenv():\n",
    "load_dotenv()\n",
    "\n",
    "openai.api_type = \"azure\"\n",
    "openai.api_base = \"YOUR_OPENAI_ENDPOINT\"\n",
    "openai.api_version = \"2023-05-15\"\n",
    "openai.api_key = \"YOUR_OPENAI_API_KEY\"\n",
    "model: str = \"text-embedding-ada-002\""
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Configure vector store settings\n",
    " \n",
    "Set up the vector store settings using environment variables:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "vector_store_address: str = 'YOUR_AZURE_SEARCH_ENDPOINT'\n",
    "vector_store_password: str = 'YOUR_AZURE_SEARCH_ADMIN_KEY'\n",
    "index_name: str = \"langchain-vector-demo\""
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create embeddings and vector store instances\n",
    " \n",
    "Create instances of the OpenAIEmbeddings and AzureSearch classes:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "embeddings: OpenAIEmbeddings = OpenAIEmbeddings(model=model, chunk_size=1)  \n",
    "vector_store: AzureSearch = AzureSearch(azure_search_endpoint=vector_store_address,  \n",
    "                                        azure_search_key=vector_store_password,  \n",
    "                                        index_name=index_name,  \n",
    "                                        embedding_function=embeddings.embed_query)  \n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Insert text and embeddings into vector store\n",
    " \n",
    "Add texts and metadata from the JSON data to the vector store:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.document_loaders import TextLoader\n",
    "from langchain.text_splitter import CharacterTextSplitter\n",
    "loader = TextLoader('../../../state_of_the_union.txt', encoding='utf-8')\n",
    "\n",
    "documents = loader.load()\n",
    "text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)\n",
    "docs = text_splitter.split_documents(documents)\n",
    "\n",
    "vector_store.add_documents(documents=docs)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Perform a vector similarity search\n",
    " \n",
    "Execute a pure vector similarity search using the similarity_search() method:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tonight. I call on the Senate to: Pass the Freedom to Vote Act. Pass the John Lewis Voting Rights Act. And while you’re at it, pass the Disclose Act so Americans can know who is funding our elections. \n",
      "\n",
      "Tonight, I’d like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer—an Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer, thank you for your service. \n",
      "\n",
      "One of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court. \n",
      "\n",
      "And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence.\n"
     ]
    }
   ],
   "source": [
    "# Perform a similarity search\n",
    "docs = vector_store.similarity_search(query=\"What did the president say about Ketanji Brown Jackson\", k=3, search_type='similarity')\n",
    "print(docs[0].page_content)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Perform a Hybrid Search\n",
    "\n",
    "Execute hybrid search using the hybrid_search() method:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tonight. I call on the Senate to: Pass the Freedom to Vote Act. Pass the John Lewis Voting Rights Act. And while you’re at it, pass the Disclose Act so Americans can know who is funding our elections. \n",
      "\n",
      "Tonight, I’d like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer—an Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer, thank you for your service. \n",
      "\n",
      "One of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court. \n",
      "\n",
      "And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence.\n"
     ]
    }
   ],
   "source": [
    "# Perform a hybrid search \n",
    "docs = vector_store.similarity_search(query=\"What did the president say about Ketanji Brown Jackson\", k=3)\n",
    "print(docs[0].page_content)"
   ]
  }
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