Update app.py

app.py

@@ -5,10 +5,10 @@ import json
 
 import datasets
 
-def save_to_dataset(images, questions, answer_p2s_base, answer_p2s_large, answer_layoutlm, answer_donut):
+def save_to_dataset(image_path, questions, answer_p2s_base, answer_p2s_large, answer_layoutlm, answer_donut):
     # Create a dataset dictionary
     dataset_dict = {
-        "image": images,
+        "image": image_path,
         "question": questions,
         "answer_p2s_base": answer_p2s_base, 
         "answer_p2s_large": answer_p2s_large, 
@@ -25,7 +25,10 @@ def save_to_dataset(images, questions, answer_p2s_base, answer_p2s_large, answer
 
 def generate_answer(image_path, question, model_name, space_id):
     try:
-        client = Client(f"https://{model_name}.hf.space/")
+        if model_name == "qtoino-pix2struct":
+            client = Client(f"https://{model_name}.hf.space/--replicas/uax51/")
+        else:
+            client = Client(f"https://{model_name}.hf.space/")
         result = client.predict(image_path, question, api_name="/predict")
         if result.endswith(".json"):
             with open(result, "rb") as json_file:
@@ -51,7 +54,7 @@ def generate_answers(image_path, question):
     answer_donut = generate_answer(image_path, question, model_name = "nielsr-donut-docvqa", space_id = "Donut DocVQA")
 
     # Save the data to the dataset
-    save_to_dataset(images, questions, answer_p2s_base, answer_p2s_large, answer_layoutlm, answer_donut)
+    save_to_dataset(image_path, questions, answer_p2s_base, answer_p2s_large, answer_layoutlm, answer_donut)
     
     return answer_p2s_base, answer_p2s_large, answer_layoutlm, answer_donut