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Answer: Use the Cloud Document AI API to extract information from the invoices and receipts.
The question requires extracting information from invoices and receipts with minimal custom code and training. Option B (Cloud Document AI API) is optimal because it is specifically designed for structured document processing like invoices and receipts, using pre-trained models to extract key fields (e.g., dates, amounts, vendors) without requiring custom training. The community discussion (100% consensus, upvoted comments) supports this, noting its purpose-built nature and efficiency. Option A (Cloud Vision API with NLP) is less suitable as it focuses on general text detection and requires additional NLP parsing, increasing complexity. Option C (Vertex AI Agent Builder with Layout Parser) is incorrect as Layout Parser is not a pre-built model in Agent Builder for this use case. Option D (AutoML Natural Language) is suboptimal because it requires training a custom model, contradicting the 'minimal training' requirement.
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You are building an application to extract information from invoices and receipts. You want to implement this application with minimal custom code and training. What should you do?
A
Use the Cloud Vision API with TEXT_DETECTION type to extract text from the invoices and receipts, and use a pre-built natural language processing (NLP) model to parse the extracted text.
B
Use the Cloud Document AI API to extract information from the invoices and receipts.
C
Use Vertex AI Agent Builder with the pre-built Layout Parser model to extract information from the invoices and receipts.
D
Train an AutoML Natural Language model to classify and extract information from the invoices and receipts.