Update app.py

app.py

@@ -71,25 +71,25 @@ def parse_ticket_image(image, question):
     
     # Use the model to answer each question
     answers = {}
-    for i, q in enumerate(questions): 
+    for q in questions: 
         answer_text = process_question(q, document)
         print(f"Answer Text extracted here: {answer_text}")
-        answers[i] = answer_text
+        answers[q] = answer_text
         
         
-    ticket_number = answers[0]
-    grain_type = answers[1]
-    date = answers[2]
-    time = answers[3]
-    gross_weight = answers[4]
-    tare_weight = answers[5]
-    net_weight = answers[6]
-    moisture = answers[7]
-    damage = answers[8]
-    gross_units = answers[9]
-    dock_units = answers[10]
-    comment = answers[11]
-    assembly_number = answers[12]
+    ticket_number = answers["What is the ticket number?"]
+    grain_type = answers["What is the type of grain (For example: corn, soy, wheat)?"]
+    date = answers["What is the date?"]
+    time = answers["What is the time?"]
+    gross_weight = answers["What is the gross weight?"]
+    tare_weight = answers["What is the tare weight?"]
+    net_weight = answers["What is the net weight?"]
+    moisture = answers["What is the moisture (moist) percentage?"]
+    damage = answers["What is the damage percentage?"]
+    gross_units = answers["What is the gross units?"]
+    dock_units = answers["What is the dock units?"]
+    comment = answers["What is the comment?"]
+    assembly_number = answers["What is the assembly number?"]
 
     
     # Create a structured format (like a table) using pandas