Updated to use different model, specifically designed for text-answers

app.py

@@ -11,7 +11,11 @@ def read_docx(file_path):
         text.append(paragraph.text) 
     return "\n".join(text)
 
-pipe = pipeline("question-answering")
+# Load model and processor 
+processor = AutoProcessor.from_pretrained("microsoft/udop-large", apply_ocr=False) 
+model = UdopForConditionalGeneration.from_pretrained("microsoft/udop-large")
+
+#pipe = pipeline("question-answering")
 #pipe = pipeline("text-generation")
 
 st.title("Adrega AI Help")
@@ -26,8 +30,12 @@ if st.button("Submit"):
         #text_inputs = f"Context: {context}\nQuestion: {user_input}\nAnswer:"
         #result = pipe(text_inputs, max_length=200, num_return_sequences=1)[0]['generated_text']
         #answer = result.split("Answer:")[1].strip()
-
-        answer = pipe(question=user_input, context=context)
+        encoding = processor(context, user_input, return_tensors="pt")
+        
+        #answer = pipe(question=user_input, context=context)
+        predicted_ids = model.generate(**encoding) 
+        answer = processor.batch_decode(predicted_ids, skip_special_tokens=True)[0]
+        
         st.write(f"Adrega AI: {answer}")
     else: 
         st.write("Please enter a question.")