Create app.py

app.py

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+import streamlit as st
+import pandas as pd
+from transformers import pipeline, AutoTokenizer
+import base64
+
+# Load the EasyTerms/legalSummerizerET model from Hugging Face
+summarizer = pipeline("summarization", model="EasyTerms/legalSummerizerET")
+
+# Increase the maximum token limit
+tokenizer = AutoTokenizer.from_pretrained("EasyTerms/legalSummerizerET")
+summarizer.model.config.max_position_embeddings = tokenizer.model_max_length
+
+# Function to generate summary using the EasyTerms/legalSummerizerET model
+def generate_summary(contract_text):
+    summary = summarizer(contract_text, max_length=512, min_length=50, length_penalty=2.0, num_beams=4, early_stopping=True)
+    return summary[0]['summary_text']
+
+# Function to handle feedback and store it in a CSV file
+def handle_feedback(feedback_data, feedback_file):
+    feedback_df = pd.DataFrame(feedback_data, columns=['Contract', 'Summary', '👍', '👎'])
+
+    # Save the dataframe to the feedback CSV file
+    feedback_df.to_csv(feedback_file, mode='a', index=False, header=not st.session_state.feedback_csv_exists)
+
+    # Display a feedback collected message only if thumbs up or thumbs down is clicked
+    if '👍' in feedback_df['👍'].values or '👎' in feedback_df['👎'].values:
+        st.success("Feedback collected successfully!")
+
+        # Display a download button for the user
+        st.markdown(get_binary_file_downloader_html(feedback_file, 'Feedback Data'), unsafe_allow_html=True)
+
+# Function to create a download link for a binary file
+def get_binary_file_downloader_html(file_path, file_label):
+    with open(file_path, 'rb') as file:
+        file_content = file.read()
+    b64 = base64.b64encode(file_content).decode()
+    return f'<a href="data:file/csv;base64,{b64}" download="{file_label}.csv">Click here to download {file_label}</a>'
+
+# Main Streamlit app
+def main():
+    st.title("Legal Contract Summarizer with Feedback")
+
+    # Input area for legal contract
+    contract_text = st.text_area("Enter the legal contract:", height=200)  # Increase the height to handle larger contracts
+
+    # Button to generate summary
+    if st.button("Generate Summary"):
+        summary = generate_summary(contract_text)
+        st.subheader("Generated Summary:")
+        st.write(summary)
+
+        # Feedback section
+        st.subheader("Feedback:")
+        thumbs_up = st.button("👍")
+        thumbs_down = st.button("👎")
+
+        chosen = "👍" if thumbs_up else None
+        rejected = "👎" if thumbs_down else None
+
+        feedback_data.append((contract_text, summary, chosen, rejected))
+
+        # Handle feedback data
+        if feedback_data:
+            feedback_file = 'feedback.csv'
+            st.session_state.feedback_csv_exists = True
+            handle_feedback(feedback_data, feedback_file)
+
+# Initialize feedback data
+feedback_data = []
+
+# Run the app
+if __name__ == "__main__":
+    main()