Update app.py

app.py

@@ -46,6 +46,7 @@ def get_predictions(text, mode):
  num_beam_groups=3,
  min_length=10,
  max_length=100,
+ diversity_penalty=1.0,
  )
  elif mode == "Polish - RfC Detection":
  output = model_det_pl.generate(
@@ -70,8 +71,14 @@ if __name__ == "__main__":
  st.sidebar.image(img_short)
  st.image(img_full)
  st.title("VLT5 - Reason for Contact generator")
-
- generated_keywords = ""
+ st.markdown("### RfC Generation model.")
+ st.markdown("-- *Input*: Whole conversation. Should specify roles (e.g. **AGENT: Hello, how can I help you? CLIENT: Hi, I would like to report a stolen card.**")
+ st.markdown("-- *Output*: Reason for calling for the whole conversation.")
+ st.markdown("### RfC Detection model.")
+ st.markdown("-- *Input*: A single turn from the conversation e.g. **'Hello, how can I help you?'** or **'Hi, I would like to report a stolen card.'**")
+ st.markdown("-- *Output*: Model will return an empty string if a turn possibly does not includes Reason for Calling, or a sentence if the RfC is detected.")
+ 
+ generated_rfc = ""
  user_input = st.text_area(
  label=f"Input text (max {max_length} characters)",
  value="",
@@ -90,19 +97,12 @@ if __name__ == "__main__":
  )
 
  result = st.button("Find reason for contact")
- if mode == "Polish - RfC Generation (accepts whole conversation)":
- st.markdown("### You selected RfC Generation model.")
- st.markdown("-- *Input*: Whole conversation. Should specify roles (e.g. **AGENT: Hello, how can I help you? CLIENT: Hi, I would like to report a stolen card.**")
- st.markdown("-- *Output*: Reason for calling for the whole conversation.")
- text_area = "Put a whole conversation or full e-mail here."
- 
- elif mode == "Polish - RfC Detection (accepts one turn)":
- st.markdown("### You selected RfC Detection model.")
- st.markdown("-- *Input*: A single turn from the conversation e.g. **'Hello, how can I help you?'** or **'Hi, I would like to report a stolen card.'**")
- st.markdown("-- *Output*: Model will return an empty string if a turn possibly does not includes Reason for Calling, or a sentence if the RfC is detected.")
- text_area = "Put a single turn or a few sentences here."
- 
+
  if result:
+ if mode == "Polish - RfC Generation (accepts whole conversation)":
+ text_area = "Put a whole conversation or full e-mail here."
+ elif mode == "Polish - RfC Detection (accepts one turn)":
+ text_area = "Put a single turn or a few sentences here."
  generated_rfc = get_predictions(text=user_input, mode=mode)
  st.text_area(text_area, generated_rfc)
  print(f"Input: {user_input} ---> Reason for contact: {generated_rfc}")