forked from Archives/langchain
87 lines
2.2 KiB
Plaintext
87 lines
2.2 KiB
Plaintext
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{
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Iugu\n",
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"\n",
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">[Iugu](https://www.iugu.com/) is a Brazilian services and software as a service (SaaS) company. It offers payment-processing software and application programming interfaces for e-commerce websites and mobile applications.\n",
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"\n",
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"This notebook covers how to load data from the `Iugu REST API` into a format that can be ingested into LangChain, along with example usage for vectorization."
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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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"metadata": {},
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"outputs": [],
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"source": [
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"import os\n",
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"\n",
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"\n",
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"from langchain.document_loaders import IuguLoader\n",
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"from langchain.indexes import VectorstoreIndexCreator"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"The Iugu API requires an access token, which can be found inside of the Iugu dashboard.\n",
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"\n",
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"This document loader also requires a `resource` option which defines what data you want to load.\n",
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"\n",
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"Following resources are available:\n",
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"\n",
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"`Documentation` [Documentation](https://dev.iugu.com/reference/metadados)\n"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"iugu_loader = IuguLoader(\"charges\")"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# Create a vectorstore retriver from the loader\n",
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"# see https://python.langchain.com/en/latest/modules/indexes/getting_started.html for more details\n",
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"\n",
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"index = VectorstoreIndexCreator().from_loaders([iugu_loader])\n",
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"iugu_doc_retriever = index.vectorstore.as_retriever()"
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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": "3.9.12"
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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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