Final final FINAL

app.py

@@ -1,36 +1,4 @@
-# import pandas as pd
-# from transformers import pipeline
-# import gradio as gr
-# import io
-
-# # Initialize sentiment analysis pipeline
-# sentiment_pipeline = pipeline('sentiment-analysis')
-
-# def process_csv(file):
-#     df = pd.read_csv(io.StringIO(file))
-#     sentiments = []
-#     for _, row in df.iterrows():
-#         text = row['Content']
-#         sentiment = analyze_sentiment(text)
-#         sentiments.append(sentiment)
-
-#     df['sentiment'] = sentiments
-
-#     return df.to_csv(index=False)
-
-# def analyze_sentiment(text):
-#     result = sentiment_pipeline(text)[0]
-#     sentiment = result['label']
-#     return sentiment
-
-# def analyze_text(text):
-#     sentiment = analyze_sentiment(text)
-#     return sentiment
-
-# iface = gr.Interface(fn=analyze_text, inputs=gr.inputs.Textbox(lines=13, label="Enter Text"), outputs="text")
-# iface.launch(share=True)
-
-
+ 
 
 import pandas as pd
 from transformers import pipeline
@@ -44,4 +12,4 @@ def analyze_text(text):
     return sentiment['label']
 
 iface = gr.Interface(fn=analyze_text, inputs=gr.inputs.Textbox(lines=13, label="Enter Text"), outputs="text")
-iface.launch(share=True)
+iface.launch()