{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"https://colab.research.google.com/github/run-llama/llama_index/blob/main/docs/examples/embeddings/modelscope.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ModelScope Embeddings"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this notebook, we show how to use the ModelScope Embeddings in LlamaIndex. Check out the [ModelScope site](https://www.modelscope.cn/).\n",
    "\n",
    "If you're opening this Notebook on colab, you will need to install LlamaIndex 🦙 and the modelscope."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install llama-index-embeddings-modelscope"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Basic Usage\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "from llama_index.embeddings.modelscope.base import ModelScopeEmbedding\n",
    "\n",
    "model = ModelScopeEmbedding(\n",
    "    model_name=\"iic/nlp_gte_sentence-embedding_chinese-base\",\n",
    "    model_revision=\"master\",\n",
    ")\n",
    "\n",
    "rsp = model.get_query_embedding(\"Hello, who are you?\")\n",
    "print(rsp)\n",
    "\n",
    "rsp = model.get_text_embedding(\"Hello, who are you?\")\n",
    "print(rsp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Generate Batch Embedding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from llama_index.embeddings.modelscope.base import ModelScopeEmbedding\n",
    "\n",
    "model = ModelScopeEmbedding(\n",
    "    model_name=\"iic/nlp_gte_sentence-embedding_chinese-base\",\n",
    "    model_revision=\"master\",\n",
    ")\n",
    "\n",
    "rsp = model.get_text_embedding_batch(\n",
    "    [\"Hello, who are you?\", \"I am a student.\"]\n",
    ")\n",
    "print(rsp)"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "name": "gemini.ipynb",
   "toc_visible": true
  },
  "kernelspec": {
   "display_name": "Python 3",
   "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"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}