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Shreyas
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Delete Ingest.py
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Ingest.py
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from langchain_community.document_loaders import PyPDFLoader,DirectoryLoader
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from langchain_community.embeddings import HuggingFaceEmbeddings
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from langchain.text_splitter import RecursiveCharacterTextSplitter
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from langchain_community.vectorstores import FAISS
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loader = DirectoryLoader('data', glob="./*.pdf", loader_cls=PyPDFLoader)
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documents = loader.load()
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text_splitter = RecursiveCharacterTextSplitter(chunk_size=1024, chunk_overlap=200)
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texts = text_splitter.split_documents(documents)
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embedings = HuggingFaceEmbeddings(model_name="nomic-ai/nomic-embed-text-v1",model_kwargs={"trust_remote_code":True,"revision":"289f532e14dbbbd5a04753fa58739e9ba766f3c7"})
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# Creates vector embeddings and saves it in the FAISS DB
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faiss_db = FAISS.from_documents(texts, embedings)
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# Saves and export the vector embeddings databse
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faiss_db.save_local("ipc_vector_db")
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