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import tempfile
import os
from langchain.document_loaders import PyPDFLoader
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.document_loaders import DirectoryLoader, TextLoader
from langchain.vectorstores import Pinecone
from PyPDF2 import PdfReader
import pinecone
from dotenv import load_dotenv
from langchain.vectorstores import Chroma
load_dotenv()
openai_api_key=os.getenv('OPENAI_API_KEY')
def create_indexes(file: tempfile) -> str:
try:
file_path = file.name
reader = PyPDFLoader(file_path)
documents = reader.load_and_split()
embeddings = OpenAIEmbeddings(
openai_api_key=openai_api_key
)
persist_directory = './db_metadata'
vectordb = Chroma.from_documents(
documents=documents,
embedding=embeddings,
persist_directory=persist_directory
)
vectordb.persist()
return 'Document uploaded and index created successfully. You can chat now.'
except Exception as e:
return e
# def clear_indexes(pinecone_api_key: str, pinecone_environment: str, pinecone_index_name: str) -> str:
# try:
# pinecone.init(
# api_key=pinecone_api_key,
# environment=pinecone_environment
# )
# indexes_list = pinecone.list_indexes()
# if pinecone_index_name in indexes_list:
# pinecone.delete_index(name=pinecone_index_name)
# return 'Indexes cleared.', None
# except Exception as e:
# return e, None
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