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langchain/docs/modules/document_loaders/examples/example_data/notebook.ipynb

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{
"cells": [
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"# Notebook\n",
"\n",
"This notebook covers how to load data from an .ipynb notebook into a format suitable by LangChain."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from langchain.document_loaders import NotebookLoader"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"loader = NotebookLoader(\"example_data/notebook.ipynb\")"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"`NotebookLoader.load()` loads the `.ipynb` notebook file into a `Document` object.\n",
"\n",
"**Parameters**:\n",
"\n",
"* `include_outputs` (bool): whether to include cell outputs in the resulting document (default is False).\n",
"* `max_output_length` (int): the maximum number of characters to include from each cell output (default is 10).\n",
"* `remove_newline` (bool): whether to remove newline characters from the cell sources and outputs (default is False).\n",
"* `traceback` (bool): whether to include full traceback (default is False)."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"loader.load(include_outputs=True, max_output_length=20, remove_newline=True)"
]
}
],
"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": "3.11.1"
},
"orig_nbformat": 4,
"vscode": {
"interpreter": {
"hash": "981b6680a42bdb5eb22187741e1607b3aae2cf73db800d1af1f268d1de6a1f70"
}
}
},
"nbformat": 4,
"nbformat_minor": 2
}