Create vector_store/vector_store.py
Browse files
src/vector_store/vector_store.py
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# src/vector_store.py
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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.vectorstores import FAISS
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from src.config import CHUNK_SIZE, CHUNK_OVERLAP
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from src.exceptions import DocumentProcessingError
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def build_vector_store(pdf_paths, embeddings, original_names=None):
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try:
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all_docs = []
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for i, path in enumerate(pdf_paths):
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loader = PyPDFLoader(path)
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docs = loader.load()
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if original_names and i < len(original_names):
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for doc in docs:
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doc.metadata["source"] = original_names[i]
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all_docs.extend(docs)
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splitter = RecursiveCharacterTextSplitter(
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chunk_size=CHUNK_SIZE,
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chunk_overlap=CHUNK_OVERLAP
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)
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splits = splitter.split_documents(all_docs)
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return FAISS.from_documents(splits, embeddings)
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except Exception as e:
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raise DocumentProcessingError(f"PDF processing failed: {e}")
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