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chore: import upstream snapshot with attribution
2026-07-13 12:37:31 +08:00

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{
"cells": [
{
"cell_type": "code",
"execution_count": 3,
"id": "cf52b7c7",
"metadata": {},
"outputs": [],
"source": [
"# Copyright (c) 2026 Microsoft Corporation.\n",
"# Licensed under the MIT License."
]
},
{
"cell_type": "markdown",
"id": "37a05202",
"metadata": {},
"source": [
"## Using the factory via helper util example\n",
"\n",
"\n",
"The create_chunker factory function provides a configuration-driven approach to instantiate chunkers by accepting a ChunkingConfig object that specifies the chunking strategy and parameters. This allows for more flexible and maintainable code by separating chunker configuration from direct instantiation."
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "027e9c45",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[TextChunk(original='This is a', text='This is a', index=0, start_char=0, end_char=8, token_count=3), TextChunk(original=' test. Another', text=' test. Another', index=1, start_char=9, end_char=22, token_count=3), TextChunk(original=' sentence. And', text=' sentence. And', index=2, start_char=23, end_char=36, token_count=3), TextChunk(original=' another one.', text=' another one.', index=3, start_char=37, end_char=49, token_count=3)]\n"
]
}
],
"source": [
"import tiktoken\n",
"from graphrag_chunking.chunker_factory import create_chunker\n",
"from graphrag_chunking.chunking_config import ChunkingConfig\n",
"\n",
"tokenizer = tiktoken.get_encoding(\"o200k_base\")\n",
"config = ChunkingConfig(\n",
" strategy=\"tokens\", # type: ignore\n",
" size=3,\n",
" overlap=0,\n",
")\n",
"chunker = create_chunker(config, tokenizer.encode, tokenizer.decode)\n",
"\n",
"print(chunker.chunk(\"This is a test. Another sentence. And another one.\"))"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.9"
}
},
"nbformat": 4,
"nbformat_minor": 5
}