AstraDBVectorStore add_documents() 返回异常“'dict'对象没有属性'page_content'”

Question

def store_embeddings_in_astradb(embeddings,text_chunks, metadata):

    vstore = AstraDBVectorStore(
        collection_name="test",
        embedding=embedding_model,
        token=os.getenv("ASTRA_DB_APPLICATION_TOKEN"),
        api_endpoint=os.getenv("ASTRA_DB_API_ENDPOINT"),
    )
    print("after Vstore")

    # Create documents with page content, embeddings, and metadata
    documents = [
        {
            "page_content": chunk,
            "metadata": metadata
        }
        for chunk in text_chunks
    ]
    for doc in documents:
        print(f"Document structure: {doc}")
    print("after documents")

    # Add documents to AstraDB vector store
    inserted_ids = vstore.add_documents(documents)
    return inserted_ids
# List of PDF files to process
pdf_files = ["WhatYouNeedToKnowAboutWOMENSHEALTH.pdf", "Womens-Health-Book.pdf"]

# Initialize embedding model
embedding_model = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")

# Process each PDF file
for pdf_file in pdf_files:
    if not os.path.isfile(pdf_file):
        raise ValueError(f"PDF file '{pdf_file}' not found.")

    print(f"Processing file: {pdf_file}")

    # Extract text from PDF
    text = extract_text_from_pdf(pdf_file)

    # Split text into chunks
    text_chunks = split_text_into_chunks(text)

    # Embed text chunks
    embeddings = embed_text_chunks(text_chunks, embedding_model)

    # Extract metadata
    metadata = extract_metadata(pdf_file)

    # Store embeddings in AstraDB
    try:
        inserted_ids = store_embeddings_in_astradb(embeddings,text_chunks, metadata)
        print(f"Inserted {len(inserted_ids)} embeddings from '{pdf_file}' into AstraDB.")
    except Exception as e:
        print(f"Failed to insert embeddings for '{pdf_file}': {e}")

这是我用来将文本块转换为嵌入然后将它们存储在 AstraDB 中的代码。在插入时我收到错误

'dict' object has no attribute 'page_content'

。怎么解决？

Answer 1

我正在努力理解你的代码，但我怀疑问题是变量范围不正确。如果您包含最小的代码示例以及复制问题的步骤，我很乐意帮助您解决问题。

作为旁注，我建议不要在函数中创建

AstraDBVectorStore

对象，因为这是没有必要的。您应该只实例化一次并在应用程序的整个生命周期内共享它。

此外，当您调用

AstraDBVectorStore.add_documents()

时，它会自动为每个文档生成嵌入，然后将其存储在 Astra DB 中，因此无需多次调用

embed_text_chunks()

。事实上，我看不到

embeddings

变量在任何地方使用。干杯！