forked from Archives/langchain
Harrison/html splitter (#5468)
Co-authored-by: David Revillas <26328973+r3v1@users.noreply.github.com>searx_updates
Harrison Chase
12 months ago
committed by
GitHub
parent
1671c2afb2
commit
f72bb966f8
@ -0,0 +1,172 @@
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{
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"id": "80f6cd99",
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"metadata": {},
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"source": [
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"# HTML\n",
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"\n",
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">[HTML](https://en.wikipedia.org/wiki/HMTL) s the standard markup language for documents designed to be displayed in a web browser.\n",
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"\n",
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"`HtmlTextSplitter` splits text along Markdown headings, code blocks, or horizontal rules. It's implemented as a simple subclass of `RecursiveCharacterSplitter` with HTML-specific separators. See the source code to see the HTML syntax expected by default.\n",
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"\n",
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"1. How the text is split: by list of `HTML` specific separators\n",
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"2. How the chunk size is measured: by number of characters"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "96d64839",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"from langchain.text_splitter import HtmlTextSplitter"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"id": "cfb0da17",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"html_text = \"\"\"\n",
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"<!DOCTYPE html>\n",
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"<html>\n",
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" <head>\n",
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" <title>🦜️🔗 LangChain</title>\n",
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" <style>\n",
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" body {\n",
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" font-family: Arial, sans-serif;\n",
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" }\n",
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" h1 {\n",
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" color: darkblue;\n",
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" }\n",
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" </style>\n",
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" </head>\n",
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" <body>\n",
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" <div>\n",
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" <h1>🦜️🔗 LangChain</h1>\n",
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" <p>⚡ Building applications with LLMs through composability ⚡</p>\n",
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" </div>\n",
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" <div>\n",
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" As an open source project in a rapidly developing field, we are extremely open to contributions.\n",
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" </div>\n",
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" </body>\n",
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"</html>\n",
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"\"\"\"\n",
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"\n",
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"html_splitter = HtmlTextSplitter(chunk_size=175, chunk_overlap=20)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"id": "d59a4fe8",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"docs = html_splitter.create_documents([html_text])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"id": "cbb2e100",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[Document(page_content='<!DOCTYPE html>\\n<html>', metadata={}),\n",
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" Document(page_content='<title>🦜️🔗 LangChain</title>', metadata={}),\n",
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" Document(page_content='body {\\n font-family: Arial, sans-serif;\\n }\\n h1 {\\n color: darkblue;\\n }\\n </style>\\n </head>', metadata={}),\n",
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" Document(page_content='/style>\\n </head>', metadata={}),\n",
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" Document(page_content='<div>\\n <h1>🦜️🔗 LangChain</h1>\\n <p>⚡ Building applications with LLMs through composability ⚡</p>\\n </div>', metadata={}),\n",
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" Document(page_content='As an open source project in a rapidly developing field, we are extremely open to contributions.\\n </div>\\n </body>\\n</html>', metadata={})]"
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]
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},
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"execution_count": 14,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"docs"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"id": "91b56e7e-b285-4ca4-a786-149544e0e3c6",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"['<!DOCTYPE html>\\n<html>',\n",
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" '<title>🦜️🔗 LangChain</title>',\n",
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" 'body {\\n font-family: Arial, sans-serif;\\n }\\n h1 {\\n color: darkblue;\\n }\\n </style>\\n </head>',\n",
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" '/style>\\n </head>',\n",
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" '<div>\\n <h1>🦜️🔗 LangChain</h1>\\n <p>⚡ Building applications with LLMs through composability ⚡</p>\\n </div>',\n",
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" 'As an open source project in a rapidly developing field, we are extremely open to contributions.\\n </div>\\n </body>\\n</html>']"
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]
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},
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"execution_count": 15,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"html_splitter.split_text(html_text)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "9bee7858-9175-4d99-bd30-68f2dece8601",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.10"
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},
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"vscode": {
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"interpreter": {
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"hash": "aee8b7b246df8f9039afb4144a1f6fd8d2ca17a180786b69acc140d282b71a49"
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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