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

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  {
   "cell_type": "markdown",
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   "metadata": {},
   "source": [
    "# Zilliz\n",
    "\n",
    ">[Zilliz Cloud](https://zilliz.com/doc/quick_start) is a fully managed service on cloud for `LF AI Milvus®`,\n",
    "\n",
    "This notebook shows how to use functionality related to the Zilliz Cloud managed vector database.\n",
    "\n",
    "To run, you should have a `Zilliz Cloud` instance up and running. Here are the [installation instructions](https://zilliz.com/cloud)"
   ]
  },
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   "id": "c0c50102-e6ac-4475-a930-49c94ed0bd99",
   "metadata": {
    "tags": []
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   "source": [
    "!pip install pymilvus"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b25e246-ffe7-4822-a6bf-85d1a120df00",
   "metadata": {},
   "source": [
    "We want to use `OpenAIEmbeddings` so we have to get the OpenAI API Key."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d6691489-1ebc-40fa-bc09-b0916903a24d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import getpass\n",
    "\n",
    "os.environ['OPENAI_API_KEY'] = getpass.getpass('OpenAI API Key:')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "19a71422",
   "metadata": {},
   "outputs": [],
   "source": [
    "# replace \n",
    "ZILLIZ_CLOUD_URI = \"\" # example: \"https://in01-17f69c292d4a5sa.aws-us-west-2.vectordb.zillizcloud.com:19536\"\n",
    "ZILLIZ_CLOUD_USERNAME = \"\"  # example: \"username\"\n",
    "ZILLIZ_CLOUD_PASSWORD = \"\"  # example: \"*********\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "aac9563e",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.embeddings.openai import OpenAIEmbeddings\n",
    "from langchain.text_splitter import CharacterTextSplitter\n",
    "from langchain.vectorstores import Milvus\n",
    "from langchain.document_loaders import TextLoader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a3c3999a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.document_loaders import TextLoader\n",
    "loader = TextLoader('../../../state_of_the_union.txt')\n",
    "documents = loader.load()\n",
    "text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)\n",
    "docs = text_splitter.split_documents(documents)\n",
    "\n",
    "embeddings = OpenAIEmbeddings()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dcf88bdf",
   "metadata": {},
   "outputs": [],
   "source": [
    "vector_db = Milvus.from_documents(\n",
    "    docs,\n",
    "    embeddings,\n",
    "    connection_args={\n",
    "        \"uri\": ZILLIZ_CLOUD_URI,\n",
    "        \"username\": ZILLIZ_CLOUD_USERNAME,\n",
    "        \"password\": ZILLIZ_CLOUD_PASSWORD,\n",
    "        \"secure\": True\n",
    "    }\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a8c513ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "docs = vector_db.similarity_search(query)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fc516993",
   "metadata": {},
   "outputs": [],
   "source": [
    "docs[0]"
   ]
  }
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