Final final

app.py

@@ -1,34 +1,47 @@
+# 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
 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
+    sentiment = sentiment_pipeline(text)[0]
+    return sentiment['label']
 
 iface = gr.Interface(fn=analyze_text, inputs=gr.inputs.Textbox(lines=13, label="Enter Text"), outputs="text")
 iface.launch(share=True)
-
-
-