mirror of
https://github.com/hwchase17/langchain
synced 2024-11-10 01:10:59 +00:00
105 lines
3.6 KiB
Plaintext
105 lines
3.6 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Jupyter Notebook\n",
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"\n",
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">[Jupyter Notebook](https://en.wikipedia.org/wiki/Project_Jupyter#Applications) (formerly `IPython Notebook`) is a web-based interactive computational environment for creating notebook documents.\n",
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"\n",
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"This notebook covers how to load data from a `Jupyter notebook (.html)` into a format suitable by LangChain."
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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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"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.document_loaders import NotebookLoader"
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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": 2,
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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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"loader = NotebookLoader(\n",
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" \"example_data/notebook.html\",\n",
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" include_outputs=True,\n",
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" max_output_length=20,\n",
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" remove_newline=True,\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"`NotebookLoader.load()` loads the `.html` notebook file into a `Document` object.\n",
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"\n",
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"**Parameters**:\n",
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"\n",
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"* `include_outputs` (bool): whether to include cell outputs in the resulting document (default is False).\n",
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"* `max_output_length` (int): the maximum number of characters to include from each cell output (default is 10).\n",
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"* `remove_newline` (bool): whether to remove newline characters from the cell sources and outputs (default is False).\n",
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"* `traceback` (bool): whether to include full traceback (default is False)."
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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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"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='\\'markdown\\' cell: \\'[\\'# Notebook\\', \\'\\', \\'This notebook covers how to load data from an .html notebook into a format suitable by LangChain.\\']\\'\\n\\n \\'code\\' cell: \\'[\\'from langchain.document_loaders import NotebookLoader\\']\\'\\n\\n \\'code\\' cell: \\'[\\'loader = NotebookLoader(\"example_data/notebook.html\")\\']\\'\\n\\n \\'markdown\\' cell: \\'[\\'`NotebookLoader.load()` loads the `.html` notebook file into a `Document` object.\\', \\'\\', \\'**Parameters**:\\', \\'\\', \\'* `include_outputs` (bool): whether to include cell outputs in the resulting document (default is False).\\', \\'* `max_output_length` (int): the maximum number of characters to include from each cell output (default is 10).\\', \\'* `remove_newline` (bool): whether to remove newline characters from the cell sources and outputs (default is False).\\', \\'* `traceback` (bool): whether to include full traceback (default is False).\\']\\'\\n\\n \\'code\\' cell: \\'[\\'loader.load(include_outputs=True, max_output_length=20, remove_newline=True)\\']\\'\\n\\n', metadata={'source': 'example_data/notebook.html'})]"
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]
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},
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"execution_count": 3,
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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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"loader.load()"
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]
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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": "3.10.6"
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},
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"vscode": {
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"interpreter": {
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"hash": "981b6680a42bdb5eb22187741e1607b3aae2cf73db800d1af1f268d1de6a1f70"
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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