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