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   "source": [
    "## Construct Jina Document\n",
    "\n",
    "`Document` is [Jina's primitive data type](https://hanxiao.io/2020/11/22/Primitive-Data-Types-in-Neural-Search-System/#primitive-types). It can contain text, image, array, embedding, URI, and accompanied by rich meta information. It can be recurred both vertically and horizontally to have nested documents and matched documents. To construct a Document, one can use:\n",
    "\n",
    "For a text document:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "#Start by installing Jina in colab \n",
    "!pip install jina"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "from jina import Document\n",
    "doc1 = Document(content='hello world')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
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   "source": [
    "For a `ndarray` document:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "import numpy\n",
    "doc2 = Document(content=numpy.random.random([10, 10]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "To make `doc2` as a sub-document of `doc1`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "doc1.chunks.append(doc2)  # doc2 is now a sub-document of doc1"
   ]
  }
 ],
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