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# -*- coding: utf-8 -*-
"""
Automatically generated by Colab.
Original file is located at
https://colab.research.google.com/drive/1iAhLoc8FxHXijhyljdKhrIJbn342bhPD
"""
# Commented out IPython magic to ensure Python compatibility.
# %pip install --upgrade langchain datasets
import requests
from bs4 import BeautifulSoup
CONFIG = {
'title': 'Constitución Española',
'url': "https://www.boe.es/diario_boe/xml.php?id=BOE-A-1978-31229",
'chunk_size': 1300,
'chunk_overlap': 150,
}
"""# Downloading BOE document"""
response = requests.get(CONFIG['url'])
response.raise_for_status()
soup = BeautifulSoup(response.text, "lxml")
filename = "constitucion.txt"
with open(filename, 'w') as fn:
text = soup.select_one("documento > texto").get_text()
fn.write(text)
"""# Splitting by chunks the document"""
from langchain_community.document_loaders import TextLoader
loader = TextLoader(filename)
document = loader.load()
from langchain.text_splitter import RecursiveCharacterTextSplitter
text_splitter = RecursiveCharacterTextSplitter(
chunk_size=CONFIG["chunk_size"],
chunk_overlap=CONFIG["chunk_overlap"],
)
docs_chunks = text_splitter.split_documents(document)
print(len(docs_chunks))
docs_chunks
"""# Loading chunks in a dataset"""
from datasets import Dataset
data_dict = {
'id': [],
'url': [],
'title': [],
'content': []
}
for idx, chunk in enumerate(docs_chunks):
data_dict['id'].append(idx)
data_dict['url'].append(CONFIG['url'])
data_dict['title'].append(CONFIG['title'])
data_dict['content'].append(chunk.page_content)
dataset = Dataset.from_dict(data_dict)
"""# Loading to HuggingFace"""
# !huggingface-cli login
dataset.push_to_hub("dariolopez/justicio-BOE-A-1978-31229-constitucion-100-chunks")
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