mirror of
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103 lines
2.0 KiB
Plaintext
103 lines
2.0 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "53049ff5",
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"metadata": {},
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"source": [
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"# TiktokenText Splitter\n",
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"\n",
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"1. How the text is split: by `tiktoken` tokens\n",
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"2. How the chunk size is measured: by `tiktoken` tokens"
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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": 3,
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"id": "8c73186a",
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"metadata": {},
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"outputs": [],
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"source": [
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"# This is a long document we can split up.\n",
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"with open('../../../state_of_the_union.txt') as f:\n",
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" state_of_the_union = f.read()"
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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": 4,
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"id": "a1a118b1",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain.text_splitter import TokenTextSplitter"
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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": 5,
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"id": "ef37c5d3",
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"metadata": {},
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"outputs": [],
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"source": [
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"text_splitter = TokenTextSplitter(chunk_size=10, chunk_overlap=0)"
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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": 6,
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"id": "5750228a",
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"metadata": {
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"scrolled": false
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Madam Speaker, Madam Vice President, our\n"
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]
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}
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],
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"source": [
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"texts = text_splitter.split_text(state_of_the_union)\n",
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"print(texts[0])"
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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": "9a87dc30",
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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": "3.9.1"
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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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