Update app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+
+
+sentiment_pipeline = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")
+flagged_words = ["hate", "stupid", "ugly", "bad"]
+positive_flags = ["love", "amazing", "great"]
+negative_flags = ["awful", "terrible", "worst"]
+
+def analyze_message(message, custom_flagged_words, custom_positive_flags, custom_negative_flags):
+    flagged_list = custom_flagged_words.split(",") if custom_flagged_words else []
+    positive_list = custom_positive_flags.split(",") if custom_positive_flags else []
+    negative_list = custom_negative_flags.split(",") if custom_negative_flags else []
+
+    sentiment_result = sentiment_pipeline(message)
+    sentiment_label = sentiment_result[0]['label']
+    flagged_terms = [word for word in flagged_list if word in message.lower()]
+    positive_terms = [word for word in positive_list if word in message.lower()]
+    negative_terms = [word for word in negative_list if word in message.lower()]
+
+    flagged_status = "Yes" if flagged_terms else "No"
+
+    # Rule-based flagging
+    if sentiment_label == "POSITIVE" and positive_terms:
+        sentiment_label = "FLAGGED POSITIVE"
+    elif sentiment_label == "NEGATIVE" and negative_terms:
+        sentiment_label = "FLAGGED NEGATIVE"
+
+
+    return sentiment_label, ", ".join(flagged_terms) if flagged_terms else "None"
+
+    with gr.Blocks() as demo:
+    gr.Markdown("## Messaging Sentiment analysis")
+
+    with gr.Row():
+        input_text = gr.Textbox(label="Enter Message")
+        submit_btn = gr.Button("submit")
+
+    sentiment_output = gr.Textbox(label="Sentiment Category", interactive=False)
+    flagged_words_output = gr.Textbox(label="Flagged Words", interactive=False)
+
+    gr.Markdown("### Customize Flagging Rules")
+    custom_flagged_words = gr.Textbox(label="Custom Flagged Words", value=", ".join(flagged_words))
+    custom_positive_flags = gr.Textbox(label="Words to Flag Positive Messages", value=", ".join(positive_flags))
+    custom_negative_flags = gr.Textbox(label="Words to Flag Negative Messages", value=", ".join(negative_flags))
+
+    submit_btn.click(analyze_message,
+                     inputs=[input_text, custom_flagged_words, custom_positive_flags, custom_negative_flags],
+                     outputs=[sentiment_output, flagged_words_output])
+
+demo.launch()