add custom pipeline

pipeline.py

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+from typing import Dict, Any
+from transformers import pipeline
+import holidays
+import PIL.Image
+import io
+
+class PreTrainedPipeline():
+    def __init__(self, model_path="PrimWong/layout_qa_hparam_tuning"):
+        # Initialize the document-question-answering pipeline with the specified model
+        self.pipeline = pipeline("document-question-answering", model=model_path)
+        self.holidays = holidays.US()
+
+    def __call__(self, data: Dict[str, Any]) -> str:
+        """
+        Process input data for document question answering with optional holiday checking.
+
+        Args:
+            data (Dict[str, Any]): Input data containing a 'text' field possibly along with 'image',
+                                   and optionally a 'date' field.
+
+        Returns:
+            str: The answer or processed information based on the text, or a holiday message if applicable.
+        """
+        text = data.get("inputs")
+        date = data.get("date")
+
+        # Check if the date is a holiday
+        if date and date in self.holidays:
+            return "Today is a holiday!"
+
+        # Run prediction using only the text input
+        prediction = self.pipeline(question=text, image="What information do you need?")
+        return prediction["answer"]  # Adjust based on actual output format of the model

requirements.txt

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+holidays