ferdmartin commited on
Commit
0c09fe8
•
1 Parent(s): 71edabc

Update app.py

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Files changed (1) hide show
  1. app.py +4 -29
app.py CHANGED
@@ -108,6 +108,8 @@ def main():
108
 
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  # Check the model to use
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  option = st.selectbox("Select a model to use:", models_available)
 
 
111
 
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  # Load the selected trained model
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  if option in ("BERT-based model", "DistilBERT-based model (BERT light)"):
@@ -133,27 +135,6 @@ def main():
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  if text.strip() == "":
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  st.error("Please enter some text")
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  else:
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- # # Add a progress bar
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- # progress_bar = st.progress(0)
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-
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- # # Add a placeholder for the progress message
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- # status_text = st.empty()
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-
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- # # Simulate a long-running process
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- # for i in range(100):
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- # # Update the progress bar every 0.02 seconds
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- # time.sleep(0.05)
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- # progress_bar.progress(i + 1)
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-
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- # if i % 2 == 0:
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- # magic = "✨"
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- # else:
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- # magic = ""
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- # # Update the progress message
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- # status_text.write(f"Work in progress {i + 1}%... Wait for the magic 🪄🔮{magic}")
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- # # Clear the progress bar and status message
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- # progress_bar.empty()
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- # status_text.empty()
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  with st.spinner("Wait for the magic 🪄🔮"):
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  # Use model
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  if option in ("Naive Bayes", "Logistic Regression"):
@@ -171,18 +152,12 @@ def main():
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  st.session_state["text"] = text
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  # Print result
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- # st.write(f"<span style='font-size: 24px;'>I think this text is: {prediction}</span>",
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- # unsafe_allow_html=True)
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  st.markdown(f"I think this text is: **:{st.session_state['color_pred']}[{st.session_state['prediction']}]** (Prediction probability: {st.session_state['predict_proba'] * 100}%)")
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- # help=f"I estimate that its probability is {st.session_state['predict_proba'] * 100}%")
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  elif "prediction" in st.session_state:
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- # Display the stored result if available
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- # st.write(f"<span style='font-size: 24px;'>I think this text is: {st.session_state['prediction']}</span>", unsafe_allow_html=True)
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-
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  st.markdown(f"I think this text is: **:{st.session_state['color_pred']}[{st.session_state['prediction']}]** (Prediction probability: {st.session_state['predict_proba'] * 100}%)")
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- #help=f"I estimate that its probability is {st.session_state['predict_proba'] * 100}%")
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- #**:blue[colored]**
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  if st.button("Model Explanation"):
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  # Check if there's text in the session state
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  if "text" in st.session_state:
 
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  # Check the model to use
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  option = st.selectbox("Select a model to use:", models_available)
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+ if option and "prediction" in st.session_state:
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+ del st.session_state.prediction
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  # Load the selected trained model
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  if option in ("BERT-based model", "DistilBERT-based model (BERT light)"):
 
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  if text.strip() == "":
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  st.error("Please enter some text")
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  else:
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  with st.spinner("Wait for the magic 🪄🔮"):
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  # Use model
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  if option in ("Naive Bayes", "Logistic Regression"):
 
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  st.session_state["text"] = text
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  # Print result
 
 
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  st.markdown(f"I think this text is: **:{st.session_state['color_pred']}[{st.session_state['prediction']}]** (Prediction probability: {st.session_state['predict_proba'] * 100}%)")
 
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  elif "prediction" in st.session_state:
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+ # Display the stored result if available
 
 
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  st.markdown(f"I think this text is: **:{st.session_state['color_pred']}[{st.session_state['prediction']}]** (Prediction probability: {st.session_state['predict_proba'] * 100}%)")
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+
 
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  if st.button("Model Explanation"):
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  # Check if there's text in the session state
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  if "text" in st.session_state: