Update app.py

app.py

@@ -410,7 +410,6 @@
 # #examples=[['manifestos/Bjp_Manifesto_2019.pdf','modi'],['AAP_Manifesto_2019.pdf','delhi'],['manifestos/Congress_Manifesto_2019.pdf','safety']])
 
 
-
 """
 # MANIFESTO ANALYSIS
 """
@@ -843,50 +842,71 @@ url="https://drive.google.com/uc?id=1HVZvTtYntl0YKLnE0cwu0CvAIRhXOv60&export=dow
 path_input = "./Congress_Manifesto_2019.pdf"
 urllib.request.urlretrieve(url, filename=path_input)
 '''
-def analysis(Manifesto,Search): 
-  raw_party = Parsing(Manifesto)
-  text_Party=clean_text(raw_party)
-  text_Party_processed = Preprocess(text_Party)
-
-  # Generate summary using LLM
-  summary = generate_summary(raw_party)
-
-  df = pd.DataFrame(raw_party.split('\n'), columns=['Content'])
-  df['Subjectivity'] = df['Content'].apply(getSubjectivity)
-  df['Polarity'] = df['Content'].apply(getPolarity)
-  df['Analysis on Polarity'] = df['Polarity'].apply(getAnalysis)
-  df['Analysis on Subjectivity'] = df['Subjectivity'].apply(getAnalysis)
-  plt.title('Sentiment Analysis')
-  plt.xlabel('Sentiment')
-  plt.ylabel('Counts')
-  plt.figure(figsize=(4,3))
-  df['Analysis on Polarity'].value_counts().plot(kind ='bar',color="#FF9F45")
-  plt.tight_layout()
-  buf = BytesIO()
-  plt.savefig(buf)
-  buf.seek(0)
-  img1 = Image.open(buf)
-  plt.clf() 
-  
-  plt.figure(figsize=(4,3))
-  df['Analysis on Subjectivity'].value_counts().plot(kind ='bar',color="#B667F1")
-  plt.tight_layout()
-  buf = BytesIO()
-  plt.savefig(buf)
-  buf.seek(0)
-  img2 = Image.open(buf)
-  plt.clf()
+def analysis(Manifesto, Search): 
+  '''
+  Main analysis function that processes the manifesto and generates all outputs
+  Manifesto: PDF file uploaded by the user
+  Search: Search term entered by the user
+  '''
+  try:
+    # Process the uploaded PDF
+    raw_party = Parsing(Manifesto)
+    text_Party = clean_text(raw_party)
+    text_Party_processed = Preprocess(text_Party)
+
+    # Generate summary using LLM
+    summary = generate_summary(raw_party)
+
+    # Sentiment analysis
+    df = pd.DataFrame(raw_party.split('\n'), columns=['Content'])
+    df['Subjectivity'] = df['Content'].apply(getSubjectivity)
+    df['Polarity'] = df['Content'].apply(getPolarity)
+    df['Analysis on Polarity'] = df['Polarity'].apply(getAnalysis)
+    df['Analysis on Subjectivity'] = df['Subjectivity'].apply(getAnalysis)
     
-  img3 = word_cloud_generator(Manifesto.name,text_Party_processed)
-  
-  fdist_Party=fDistance(text_Party_processed)
-  img4=fDistancePlot(text_Party_processed)
-  img5=DispersionPlot(text_Party_processed)
-  
-  searChRes=get_all_phases_containing_tar_wrd(Search,text_Party_processed)
-  searChRes=searChRes.replace(Search,"\u0332".join(Search))
-  plt.close('all') 
-  return searChRes,fdist_Party,img1,img2,img3,img4,img5,summary
+    # Generate sentiment analysis plot
+    plt.title('Sentiment Analysis')
+    plt.xlabel('Sentiment')
+    plt.ylabel('Counts')
+    plt.figure(figsize=(4,3))
+    df['Analysis on Polarity'].value_counts().plot(kind ='bar',color="#FF9F45")
+    plt.tight_layout()
+    buf = BytesIO()
+    plt.savefig(buf)
+    buf.seek(0)
+    img1 = Image.open(buf)
+    plt.clf() 
+    
+    # Generate subjectivity analysis plot
+    plt.figure(figsize=(4,3))
+    df['Analysis on Subjectivity'].value_counts().plot(kind ='bar',color="#B667F1")
+    plt.tight_layout()
+    buf = BytesIO()
+    plt.savefig(buf)
+    buf.seek(0)
+    img2 = Image.open(buf)
+    plt.clf()
+      
+    # Generate word cloud
+    img3 = word_cloud_generator(Manifesto.name, text_Party_processed)
+    
+    # Generate frequency distribution and dispersion plots
+    fdist_Party = fDistance(text_Party_processed)
+    img4 = fDistancePlot(text_Party_processed)
+    img5 = DispersionPlot(text_Party_processed)
+    
+    # Search for the term in the text
+    searChRes = get_all_phases_containing_tar_wrd(Search, text_Party_processed)
+    searChRes = searChRes.replace(Search, "\u0332".join(Search))
+    
+    plt.close('all') 
+    return searChRes, fdist_Party, img1, img2, img3, img4, img5, summary
+    
+  except Exception as e:
+    error_message = f"Error analyzing manifesto: {str(e)}"
+    print(error_message)
+    # Return placeholder values in case of error
+    return error_message, {}, None, None, None, None, None, "Error generating summary. Please check the console for details."
 
 
 Search_txt= "text"
@@ -954,6 +974,8 @@ with gr.Blocks(title='Manifesto Analysis') as demo:
 demo.launch(debug=True, share=False)
 
 
-#allow_screenshot=False,allow_flagging="never",
-#examples=[['manifestos/Bjp_Manifesto_2019.pdf','modi'],['AAP_Manifesto_2019.pdf','delhi'],['manifestos/Congress_Manifesto_2019.pdf','safety']])
+# Old interface code replaced by the Blocks implementation above
+# io=gr.Interface(fn=analysis, inputs=[filePdf,Search_txt], outputs=[text,mfw,plot1,plot2,plot3,plot4,plot5], title='Manifesto Analysis',examples=[['Example/AAP_Manifesto_2019.pdf','government'],['Example/Bjp_Manifesto_2019.pdf','environment'],['Example/Congress_Manifesto_2019.pdf','safety']])
+# io.launch(debug=True,share=False)
+