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EddyGiusepe
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b4e87ef
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Parent(s):
5a7b133
Duas funções: uma cria o DB e outra Delete o DB
Browse files- functions.py +67 -0
functions.py
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#!/usr/bin/env python3
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"""
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Data Scientist.: Dr. Eddy Giusepe Chirinos Isidro
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Execução deste script
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=====================
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$ python functions.py
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"""
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from langchain_community.document_loaders import PyPDFLoader
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from langchain_text_splitters import RecursiveCharacterTextSplitter
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from langchain_community.embeddings.sentence_transformer import (SentenceTransformerEmbeddings,
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)
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from langchain_chroma import Chroma
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import warnings
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warnings.filterwarnings('ignore')
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import shutil
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import os
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# Criando o Database:
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def create_db():
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loader = PyPDFLoader("files/CHATGPT Granularity_clustering.pdf")
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pages = loader.load()
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#print(len(pages))
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text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000,
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chunk_overlap=100,
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length_function=len,
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is_separator_regex=False
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)
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chunks = text_splitter.split_documents(pages)
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#print(len(chunks))
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ids = [str(i) for i in range(1, len(chunks) + 1)]
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#print(ids)
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# Crie a função de Embeddings de código aberto:
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embedding_function = SentenceTransformerEmbeddings(model_name="all-MiniLM-L6-v2",
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model_kwargs = {'device': 'cpu'}
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)
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# Crie o banco de dados Chroma com IDs:
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Chroma.from_documents(documents=chunks,
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embedding=embedding_function,
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persist_directory="./chroma_db",
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ids=ids
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)
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# Excluindo o banco de dados (Database):
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def delete_persisted_db():
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if "chroma_db" in os.listdir():
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shutil.rmtree("chroma_db")
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print(f"Banco de dados excluído e seu conteúdo.")
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else:
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raise FileNotFoundError("Banco de dados não encontrado.")
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# Testando o funcionamento deste script:
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if __name__ == "__main__":
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create_db()
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