{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "70e9b619",
   "metadata": {},
   "source": [
    "# MarkdownHeaderTextSplitter\n",
    "\n",
    "The objective is to split a markdown file by a specified set of headers.\n",
    " \n",
    "**Given this example:**\n",
    "\n",
    "# Foo\n",
    "\n",
    "## Bar\n",
    "\n",
    "Hi this is Jim  \n",
    "Hi this is Joe\n",
    "\n",
    "## Baz\n",
    "\n",
    "Hi this is Molly\n",
    " \n",
    "**Written as:**\n",
    "\n",
    "```\n",
    "md = '# Foo\\n\\n ## Bar\\n\\nHi this is Jim  \\nHi this is Joe\\n\\n ## Baz\\n\\n Hi this is Molly' \n",
    "```\n",
    "\n",
    "**If we want to split on specified headers:**\n",
    "```\n",
    "[(\"#\", \"Header 1\"),(\"##\", \"Header 2\")]\n",
    "```\n",
    "\n",
    "**Then we expect:** \n",
    "```\n",
    "{'content': 'Hi this is Jim  \\nHi this is Joe', 'metadata': {'Header 1': 'Foo', 'Header 2': 'Bar'}}\n",
    "{'content': 'Hi this is Molly', 'metadata': {'Header 1': 'Foo', 'Header 2': 'Baz'}}\n",
    "```\n",
    "\n",
    "**Options:**\n",
    " \n",
    "This also includes `return_each_line` in case a user want to perform other types of aggregation. \n",
    "\n",
    "If `return_each_line=True`, each line and associated header metadata are returned. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "19c044f0",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.text_splitter import MarkdownHeaderTextSplitter"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec8d8053",
   "metadata": {},
   "source": [
    "`Test case 1`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5cd0a66c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'content': 'Hi this is Jim', 'metadata': {'Header 1': 'Foo', 'Header 2': 'Bar'}}\n",
      "{'content': 'Hi this is Joe', 'metadata': {'Header 1': 'Foo', 'Header 2': 'Bar'}}\n",
      "{'content': 'Hi this is Molly', 'metadata': {'Header 1': 'Foo', 'Header 2': 'Baz'}}\n"
     ]
    }
   ],
   "source": [
    "# Doc\n",
    "markdown_document = '# Foo\\n\\n    ## Bar\\n\\nHi this is Jim\\n\\nHi this is Joe\\n\\n ## Baz\\n\\n Hi this is Molly' \n",
    "    \n",
    "# Test case 1\n",
    "headers_to_split_on = [\n",
    "    (\"#\", \"Header 1\"),\n",
    "    (\"##\", \"Header 2\"),\n",
    "]\n",
    "\n",
    "markdown_splitter = MarkdownHeaderTextSplitter(headers_to_split_on=headers_to_split_on,return_each_line=True)\n",
    "\n",
    "chunked_docs = markdown_splitter.split_text(markdown_document)\n",
    "for chunk in chunked_docs:\n",
    "    print(chunk)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "67d25a1c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'content': 'Hi this is Jim  \\nHi this is Joe', 'metadata': {'Header 1': 'Foo', 'Header 2': 'Bar'}}\n",
      "{'content': 'Hi this is Molly', 'metadata': {'Header 1': 'Foo', 'Header 2': 'Baz'}}\n"
     ]
    }
   ],
   "source": [
    "markdown_splitter = MarkdownHeaderTextSplitter(headers_to_split_on=headers_to_split_on,return_each_line=False)\n",
    "chunked_docs = markdown_splitter.split_text(markdown_document)\n",
    "for chunk in chunked_docs:\n",
    "    print(chunk)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1f74dfa",
   "metadata": {},
   "source": [
    "`Test case 2`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2183c96a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'content': 'Text under H3.', 'metadata': {'Header 1': 'H1', 'Header 2': 'H2', 'Header 3': 'H3'}}\n",
      "{'content': 'Text under H2_2.', 'metadata': {'Header 1': 'H1_2', 'Header 2': 'H2_2'}}\n"
     ]
    }
   ],
   "source": [
    "headers_to_split_on = [\n",
    "    (\"#\", \"Header 1\"),\n",
    "    (\"##\", \"Header 2\"),\n",
    "    (\"###\", \"Header 3\"),\n",
    "]\n",
    "markdown_document = '# H1\\n\\n## H2\\n\\n### H3\\n\\nText under H3.\\n\\n# H1_2\\n\\n## H2_2\\n\\nText under H2_2.'\n",
    "markdown_splitter = MarkdownHeaderTextSplitter(headers_to_split_on=headers_to_split_on,return_each_line=False)\n",
    "chunked_docs = markdown_splitter.split_text(markdown_document)\n",
    "for chunk in chunked_docs:\n",
    "    print(chunk)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "add24254",
   "metadata": {},
   "source": [
    "`Test case 3`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c3f4690f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'content': 'Hi this is Jim  \\nHi this is Joe', 'metadata': {'Header 1': 'Foo', 'Header 2': 'Bar'}}\n",
      "{'content': 'Hi this is Lance', 'metadata': {'Header 1': 'Foo', 'Header 2': 'Bar', 'Header 3': 'Boo'}}\n",
      "{'content': 'Hi this is Molly', 'metadata': {'Header 1': 'Foo', 'Header 2': 'Baz'}}\n"
     ]
    }
   ],
   "source": [
    "markdown_document = '# Foo\\n\\n    ## Bar\\n\\nHi this is Jim\\n\\nHi this is Joe\\n\\n ### Boo \\n\\n Hi this is Lance \\n\\n ## Baz\\n\\n Hi this is Molly' \n",
    "    \n",
    "headers_to_split_on = [\n",
    "    (\"#\", \"Header 1\"),\n",
    "    (\"##\", \"Header 2\"),\n",
    "    (\"###\", \"Header 3\"),\n",
    "]\n",
    "markdown_splitter = MarkdownHeaderTextSplitter(headers_to_split_on=headers_to_split_on,return_each_line=False)\n",
    "chunked_docs = markdown_splitter.split_text(markdown_document)\n",
    "for chunk in chunked_docs:\n",
    "    print(chunk)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "20907fb7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'content': 'Hi this is Jim', 'metadata': {'Header 1': 'Foo', 'Header 2': 'Bar'}}\n",
      "{'content': 'Hi this is Joe', 'metadata': {'Header 1': 'Foo', 'Header 2': 'Bar'}}\n",
      "{'content': 'Hi this is Lance', 'metadata': {'Header 1': 'Foo', 'Header 2': 'Bar', 'Header 3': 'Boo'}}\n",
      "{'content': 'Hi this is Molly', 'metadata': {'Header 1': 'Foo', 'Header 2': 'Baz'}}\n"
     ]
    }
   ],
   "source": [
    "markdown_splitter = MarkdownHeaderTextSplitter(headers_to_split_on=headers_to_split_on,return_each_line=True)\n",
    "chunked_docs = markdown_splitter.split_text(markdown_document)\n",
    "for chunk in chunked_docs:\n",
    "    print(chunk)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c448431",
   "metadata": {},
   "source": [
    "`Test case 4`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "9858ea51",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'content': 'Hi this is Jim  \\nHi this is Joe', 'metadata': {'Header 1': 'Foo', 'Header 2': 'Bar'}}\n",
      "{'content': 'Hi this is Lance', 'metadata': {'Header 1': 'Foo', 'Header 2': 'Bar', 'Header 3': 'Boo'}}\n",
      "{'content': 'Hi this is John', 'metadata': {'Header 1': 'Foo', 'Header 2': 'Bar', 'Header 3': 'Boo', 'Header 4': 'Bim'}}\n",
      "{'content': 'Hi this is Molly', 'metadata': {'Header 1': 'Foo', 'Header 2': 'Baz'}}\n"
     ]
    }
   ],
   "source": [
    "markdown_document = '# Foo\\n\\n    ## Bar\\n\\nHi this is Jim\\n\\nHi this is Joe\\n\\n ### Boo \\n\\n Hi this is Lance \\n\\n #### Bim \\n\\n Hi this is John \\n\\n ## Baz\\n\\n Hi this is Molly'\n",
    "    \n",
    "headers_to_split_on = [\n",
    "    (\"#\", \"Header 1\"),\n",
    "    (\"##\", \"Header 2\"),\n",
    "    (\"###\", \"Header 3\"),\n",
    "    (\"####\", \"Header 4\"),\n",
    "]\n",
    " \n",
    "markdown_splitter = MarkdownHeaderTextSplitter(headers_to_split_on=headers_to_split_on,return_each_line=False)\n",
    "chunked_docs = markdown_splitter.split_text(markdown_document)\n",
    "for chunk in chunked_docs:\n",
    "    print(chunk)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bba6eb9e",
   "metadata": {},
   "source": [
    "`Test case 5`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8af8f9a2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'content': 'Markdown[9] is a lightweight markup language for creating formatted text using a plain-text editor. John Gruber created Markdown in 2004 as a markup language that is appealing to human readers in its source code form.[9]  \\nMarkdown is widely used in blogging, instant messaging, online forums, collaborative software, documentation pages, and readme files.', 'metadata': {'Header 1': 'Intro', 'Header 2': 'History'}}\n",
      "{'content': 'As Markdown popularity grew rapidly, many Markdown implementations appeared, driven mostly by the need for  \\nadditional features such as tables, footnotes, definition lists,[note 1] and Markdown inside HTML blocks.', 'metadata': {'Header 1': 'Intro', 'Header 2': 'Rise and divergence'}}\n",
      "{'content': 'From 2012, a group of people, including Jeff Atwood and John MacFarlane, launched what Atwood characterised as a standardisation effort.', 'metadata': {'Header 1': 'Intro', 'Header 2': 'Rise and divergence', 'Header 4': 'Standardization'}}\n",
      "{'content': 'Implementations of Markdown are available for over a dozen programming languages.', 'metadata': {'Header 1': 'Intro', 'Header 2': 'Implementations'}}\n"
     ]
    }
   ],
   "source": [
    "markdown_document = '# Intro \\n\\n    ## History \\n\\n Markdown[9] is a lightweight markup language for creating formatted text using a plain-text editor. John Gruber created Markdown in 2004 as a markup language that is appealing to human readers in its source code form.[9] \\n\\n Markdown is widely used in blogging, instant messaging, online forums, collaborative software, documentation pages, and readme files. \\n\\n ## Rise and divergence \\n\\n As Markdown popularity grew rapidly, many Markdown implementations appeared, driven mostly by the need for \\n\\n additional features such as tables, footnotes, definition lists,[note 1] and Markdown inside HTML blocks. \\n\\n #### Standardization \\n\\n From 2012, a group of people, including Jeff Atwood and John MacFarlane, launched what Atwood characterised as a standardisation effort. \\n\\n ## Implementations \\n\\n Implementations of Markdown are available for over a dozen programming languages.'\n",
    "    \n",
    "headers_to_split_on = [\n",
    "    (\"#\", \"Header 1\"),\n",
    "    (\"##\", \"Header 2\"),\n",
    "    (\"###\", \"Header 3\"),\n",
    "    (\"####\", \"Header 4\"),\n",
    "]\n",
    " \n",
    "markdown_splitter = MarkdownHeaderTextSplitter(headers_to_split_on=headers_to_split_on,return_each_line=False)\n",
    "chunked_docs = markdown_splitter.split_text(markdown_document)\n",
    "for chunk in chunked_docs:\n",
    "    print(chunk)"
   ]
  }
 ],
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