mirror of
https://github.com/hwchase17/langchain
synced 2024-10-31 15:20:26 +00:00
59204a5033
- made notebooks consistent: titles, service/format descriptions. - corrected short names to full names, for example, `Word` -> `Microsoft Word` - added missed descriptions - renamed notebook files to make ToC correctly sorted
209 lines
4.2 KiB
Plaintext
209 lines
4.2 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "39af9ecd",
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"metadata": {},
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"source": [
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"# Microsoft Word\n",
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"\n",
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">[Microsoft Word](https://www.microsoft.com/en-us/microsoft-365/word) is a word processor developed by Microsoft.\n",
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"\n",
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"This covers how to load `Word` documents into a document format that we can use downstream."
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]
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},
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{
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"cell_type": "markdown",
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"id": "9438686b",
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"metadata": {},
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"source": [
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"## Using Docx2txt\n",
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"\n",
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"Load .docx using `Docx2txt` into a document."
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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": "7b80ea89",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain.document_loaders import Docx2txtLoader"
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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": "99a12031",
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"metadata": {},
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"outputs": [],
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"source": [
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"loader = Docx2txtLoader(\"example_data/fake.docx\")"
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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": "b92f68b0",
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"metadata": {},
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"outputs": [],
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"source": [
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"data = loader.load()"
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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": 7,
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"id": "d83dd755",
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"metadata": {},
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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='Lorem ipsum dolor sit amet.', metadata={'source': 'example_data/fake.docx'})]"
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]
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},
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"execution_count": 7,
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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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"data"
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]
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},
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{
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"cell_type": "markdown",
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"id": "8d40727d",
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"metadata": {},
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"source": [
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"## Using Unstructured"
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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": 8,
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"id": "721c48aa",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain.document_loaders import UnstructuredWordDocumentLoader"
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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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"id": "9d3d0e35",
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"metadata": {},
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"outputs": [],
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"source": [
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"loader = UnstructuredWordDocumentLoader(\"example_data/fake.docx\")"
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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": "06073f91",
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"metadata": {},
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"outputs": [],
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"source": [
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"data = loader.load()"
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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": "c9adc5cb",
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"metadata": {},
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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='Lorem ipsum dolor sit amet.', lookup_str='', metadata={'source': 'fake.docx'}, lookup_index=0)]"
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]
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},
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"execution_count": 4,
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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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"data"
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]
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},
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{
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"cell_type": "markdown",
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"id": "525d6b67",
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"metadata": {},
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"source": [
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"## Retain Elements\n",
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"\n",
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"Under the hood, Unstructured creates different \"elements\" for different chunks of text. By default we combine those together, but you can easily keep that separation by specifying `mode=\"elements\"`."
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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": "064f9162",
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"metadata": {},
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"outputs": [],
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"source": [
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"loader = UnstructuredWordDocumentLoader(\"example_data/fake.docx\", mode=\"elements\")"
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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": "abefbbdb",
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"metadata": {},
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"outputs": [],
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"source": [
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"data = loader.load()"
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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": 7,
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"id": "a547c534",
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"metadata": {},
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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='Lorem ipsum dolor sit amet.', lookup_str='', metadata={'source': 'fake.docx', 'filename': 'fake.docx', 'category': 'Title'}, lookup_index=0)"
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]
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},
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"execution_count": 7,
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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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"data[0]"
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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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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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