Update app.py

app.py

@@ -38,15 +38,36 @@ def sentiment_bar_chart(df):
 
 
 def read_reviews_and_analyze_sentiment(file_object):
-    # Load the Excel file into a DataFrame
-    df = pd.read_excel(file_object)
+    if file_object.name.endswith('.xlsx'):
+        # Load the Excel file into a DataFrame
+        df = pd.read_excel(file_object)
+    
+        # Check if 'Review' column is in the DataFrame
+        if 'Reviews' not in df.columns:
+            raise ValueError("Excel file must contain a 'Review' column.")
+
+        # Apply the get_sentiment function to each review in the DataFrame
+        df['Sentiment'] = df['Reviews'].apply(sentiment_analyzer)
+    elif file_object.name.endswith('.docx'):
+        # Read the content of the DOCX file
+        doc = Document(file_object)
+        reviews = [para.text for para in doc.paragraphs if para.text.strip()]
+        df = pd.DataFrame({'Reviews': reviews})
+        df['Sentiment'] = df['Reviews'].apply(sentiment_analyzer)
+    
+    elif file_object.name.endswith('.pdf'):
+        # Read the content of the PDF file
+        reader = PdfReader(file_object)
+        text = ""
+        for page in reader.pages:
+            text += page.extract_text()
+        reviews = text.split('\n')  # Assuming reviews are newline separated
+        df = pd.DataFrame({'Reviews': reviews})
+        df['Sentiment'] = df['Reviews'].apply(sentiment_analyzer)
+    
+    else:
+        raise ValueError("Unsupported file format. Please upload .xlsx, .pdf, or .docx files.")
 
-    # Check if 'Review' column is in the DataFrame
-    if 'Reviews' not in df.columns:
-        raise ValueError("Excel file must contain a 'Review' column.")
-
-    # Apply the get_sentiment function to each review in the DataFrame
-    df['Sentiment'] = df['Reviews'].apply(sentiment_analyzer)
     chart_object = sentiment_bar_chart(df)
     return df, chart_object
 
@@ -58,8 +79,8 @@ def read_reviews_and_analyze_sentiment(file_object):
 
 
 demo = gr.Interface(fn=read_reviews_and_analyze_sentiment,
-                    inputs=[gr.File(file_types=["xlsx"], label="Upload your review comment file")],
-                    outputs=[gr.Dataframe(label="Sentiments"), gr.Plot(label="Sentiment Analysis")],
+                    inputs=[gr.File(file_types=["xlsx", "pdf", "docx"], label="Upload your review comment file")],
+                    outputs=[gr.Dataframe(label="Sentiments"), gr.Plot(label="Sentiment Analysis"),gr.Textbox(label="Single Sentence Sentiment Analysis")],
                     title="@GenAILearniverse Project 3: Sentiment Analyzer",
                     description="THIS APPLICATION WILL BE USED TO ANALYZE THE SENTIMENT BASED ON FILE UPLAODED.")
 demo.launch()