Update app.py

app.py

@@ -138,11 +138,77 @@ def evaluate(example, treshold):
     average_score_truth = "{:.0%}".format(average_score_truth)
     return average_score_predicted, predictions, labels, average_score_truth
 
+from google.colab import userdata 
+OPENAI_API_KEY=userdata.get("OPENAI_API_KEY") 
+os.environ["OPENAI_API_KEY"]=str(OPENAI_API_KEY)
+def read_html_file(file_path):
+    try:
+        with open(file_path, 'r', encoding='utf-8') as file:
+            html_content = file.read()
+            html_content = html_content.encode('ascii', 'ignore').decode('ascii')
+            html_content= html_content.replace("\n","")                 
+            html_content=re.sub( ">\s+<", "><" , html_content)
+        return html_content
+    except FileNotFoundError:
+        print(f"File not found: {file_path}")
+        return None
+    except Exception as e:
+        print(f"An error occurred: {str(e)}")
+        return None
+def createQuestions(documents):
+    questions = mqag_model.generate(context=document, do_sample=True, num_questions=3)
+    
+    return questions
+def detect(context, summary):
+    score = mqag_model.score(candidate=summary, reference=context, num_questions=3, verbose=True)
+    return score
+    
+def summarize(document):
+  response = client.chat.completions.create(
+    model="gpt-3.5-turbo",
+    messages=[
+      {
+        "role": "system",
+        "content": "Summarize content you are provided with for a second-grade student."
+      },
+      {
+        "role": "user",
+        "content":document
+      }
+    ],
+    temperature=0.7,
+    max_tokens=64,
+    top_p=1
+  )
+  return response.choices[0].message.content
+def detectRag(document,rags):
+  options = sorted([word.capitalize() for word in rags.split(",")])
+  print(options)
+  questions = [{'question': "what is the main topic of this?", 'options': options}]
+  probs = mqag_model.answer(questions=questions, context=document)
+  print(probs[0])
+  return probs[0]
+html_content = read_html_file("cookgpt.html")
 with gr.Blocks(theme=style) as demo:
     with gr.Tab("Maya"):
         gr.Markdown(title)
         gr.Markdown(description)
-        
+        with gr.Row():
+            with gr.Column():
+              context = gr.TextArea(label="Context" , value=document)                          
+              questions = gr.TextArea(label="Questions")
+              createQuestiobBTN = gr.Button("Create Questions")
+              createQuestiobBTN.click(createQuestions, inputs=context, outputs=questions)
+             
+        with gr.Row():
+            with gr.Column():
+              summaryTx = gr.TextArea(label="Summary" , value=summary)  
+              createSummaryBTN = gr.Button("Create Summary")
+              createSummaryBTN.click(summarize, inputs=context, outputs=summaryTx)
+              score = gr.TextArea(label="Score")
+              detectHallucinate = gr.Button("Detect Hallucination")  
+              detectHallucinate.click(detect, inputs=[context,summaryTx], outputs=score)   
+         gr.HTML(html_content)
     with gr.Tab("Mithya"):  
         gr.Markdown(title)
         gr.Markdown(description)
@@ -177,8 +243,15 @@ with gr.Blocks(theme=style) as demo:
         examples_dropdown.input(mirror, inputs=examples_dropdown, outputs=example_text)
         submit.click(evaluate, inputs=[examples_dropdown, treshold], outputs=[label, highlighted_prediction, highlighted_ground_truth, label_ground_truth])
     with gr.Tab("Router-Chain-Branch"):  
-        gr.Markdown(title)
-        gr.Markdown(description)
+        gr.Markdown(titleRAG)
+        gr.Markdown(descriptionRAG)
+        with gr.Row():
+            with gr.Column(): 
+              contextRAG = gr.TextArea(label="Context" , value=document)
+              ragDocuments = gr.TextArea(label="Comma Seperated RAG" , value="paneer,chicken,breakfast")  
+              findRAGDocument = gr.Button("Detect Document") 
+              rag = gr.TextArea(label="Rag Document to Look for")  
+              findRAGDocument.click(detectRag, inputs=[contextRAG,ragDocuments], outputs=rag)  
         
 theme=gr.themes.Base()            
 demo.launch(debug=True)