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A Gen AI developer is implementing a Document AI solution to extract key fields from thousands of diverse PDF reports, which vary significantly in length and complexity. They use the '!PREDICT method with 'GET_PRESIGNED_URL' to process documents from an external stage. After initial testing, they observe two distinct types of errors in the query results: for other, lengthy PDF files. Which two of the following actions should the developer take to resolve these issues?
Correct Answer: B,C
The first error, 'Received HTTP 403 response for presigned URL. URL may be expired.', indicates that the presigned URLs generated by 'GET_PRESIGNED_URL' are expiring before the Document AI model can process the documents. The 'GET_PRESIGNED_URL' function has a default expiration time of 60 minutes. A recommended solution is to use several queries to process documents, effectively breaking the workload into smaller batches to complete within the URL's lifespan. The second error, 'Document has too many pages. Actual: 150. Maximum: 125.', directly indicates that some documents exceed Document AI's page limit of 125 pages per document. The solution is to ensure documents comply with this limit, possibly by splitting them. Option A is incorrect because scaling up the warehouse does not increase the speed of query processing for Document AI; X-Small, Small, or Medium warehouses are recommended, and larger warehouses may result in unnecessary costs. Option D relates to setting up continuous processing pipelines but does not directly address these specific extraction errors. Option E is applicable for internal stages requiring encryption, but the scenario specifies an external stage, which would have different encryption configurations (e.g., SAWS SSE SS for S3).