fix: the cahnges

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README.md

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----
-title: Streamlit
-emoji: 🏆
-colorFrom: indigo
-colorTo: indigo
-sdk: streamlit
-sdk_version: 1.42.1
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import streamlit as st
+import pandas as pd
+from transformers import pipeline, AutoModelForSequenceClassification, AutoTokenizer
+import time
+import matplotlib.pyplot as plt
+import os
+
+st.title("Sentiment Analysis App")
+st.write("Upload a CSV or Excel file containing text data for sentiment analysis.")
+
+# File uploader
+uploaded_file = st.file_uploader("Upload a CSV or Excel file", type=["csv", "xlsx"])
+
+# Load sentiment analysis model
+try:
+    sentiment_pipeline = pipeline(
+        "sentiment-analysis", 
+        model="distilbert-base-uncased-finetuned-sst-2-english"
+    )
+    st.success("Sentiment analysis model loaded successfully!")
+except Exception as e:
+    st.error(f"Error loading model: {e}")
+    st.stop()
+
+if uploaded_file:
+    # Check file type
+    if uploaded_file.name.endswith('.csv'):
+        df = pd.read_csv(uploaded_file)
+    elif uploaded_file.name.endswith('.xlsx'):
+        df = pd.read_excel(uploaded_file)
+    else:
+        st.error("Unsupported file format.")
+        st.stop()
+
+    st.write("Data Preview:", df.head())
+
+    # Check for 'text' column
+    if 'text' not in df.columns:
+        text_column = st.text_input("Enter the name of the column containing text values:")
+        if text_column not in df.columns:
+            st.error(f"Column '{text_column}' not found in the file.")
+            st.stop()
+        else:
+            df.rename(columns={text_column: 'text'}, inplace=True)
+    else:
+        text_column = 'text'
+
+    if st.button("Run Sentiment Analysis"):
+        # Progress bar
+        progress_bar = st.progress(0)
+
+        sentiments = []
+        for i, text in enumerate(df[text_column]):
+            try:
+                result = sentiment_pipeline(text)[0]
+                sentiments.append(result['label'])
+            except Exception as e:
+                sentiments.append("Error")
+                st.error(f"Error processing text at row {i + 1}: {e}")
+
+            progress_bar.progress((i + 1) / len(df))
+            time.sleep(0.1)  # Simulating processing time
+
+        df['Sentiment'] = sentiments
+        st.write("Sentiment Analysis Output:", df[['text', 'Sentiment']])
+
+        # Pie chart
+        sentiment_counts = df['Sentiment'].value_counts()
+        fig, ax = plt.subplots()
+        ax.pie(sentiment_counts, labels=sentiment_counts.index, autopct='%1.1f%%', startangle=90)
+        ax.axis('equal')
+        st.pyplot(fig)
+
+        # Clear progress bar
+        progress_bar.empty()
+