langchain/docs/modules/indexes/text_splitters/examples/markdown.ipynb

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   "source": [
    "# Markdown Text Splitter\n",
    "\n",
    "MarkdownTextSplitter splits text along Markdown headings, code blocks, or horizontal rules. It's implemented as a simple subclass of RecursiveCharacterSplitter with Markdown-specific separators. See the source code to see the Markdown syntax expected by default.\n",
    "\n",
    "1. How the text is split: by list of markdown specific characters\n",
    "2. How the chunk size is measured: by length function passed in (defaults to number of characters)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "96d64839",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.text_splitter import MarkdownTextSplitter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "cfb0da17",
   "metadata": {},
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   "source": [
    "markdown_text = \"\"\"\n",
    "# 🦜️🔗 LangChain\n",
    "\n",
    "⚡ Building applications with LLMs through composability ⚡\n",
    "\n",
    "## Quick Install\n",
    "\n",
    "```bash\n",
    "# Hopefully this code block isn't split\n",
    "pip install langchain\n",
    "```\n",
    "\n",
    "As an open source project in a rapidly developing field, we are extremely open to contributions.\n",
    "\"\"\"\n",
    "markdown_splitter = MarkdownTextSplitter(chunk_size=100, chunk_overlap=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d59a4fe8",
   "metadata": {},
   "outputs": [],
   "source": [
    "docs = markdown_splitter.create_documents([markdown_text])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "cbb2e100",
   "metadata": {},
   "outputs": [
    {
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       " Document(page_content=\"Quick Install\\n\\n```bash\\n# Hopefully this code block isn't split\\npip install langchain\", lookup_str='', metadata={}, lookup_index=0),\n",
       " Document(page_content='As an open source project in a rapidly developing field, we are extremely open to contributions.', lookup_str='', metadata={}, lookup_index=0)]"
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    "docs"
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