Update app.py

app.py

@@ -1,394 +1,4 @@
 
-# from ragatouille import RAGPretrainedModel
-# import subprocess
-# import json
-# import spaces
-# import firebase_admin
-# from firebase_admin import credentials, firestore
-# import logging
-# from pathlib import Path
-# from time import perf_counter
-# from datetime import datetime
-# import gradio as gr
-# from jinja2 import Environment, FileSystemLoader
-# import numpy as np
-
-# from huggingface_hub import InferenceClient
-# from os import getenv
-
-# from backend.query_llm import generate_hf, generate_openai
-
-# from huggingface_hub import InferenceClient
-
-
-# VECTOR_COLUMN_NAME = "vector"
-# TEXT_COLUMN_NAME = "text"
-# HF_TOKEN = getenv("HUGGING_FACE_HUB_TOKEN")
-# proj_dir = Path(__file__).parent
-# # Setting up the logging
-# logging.basicConfig(level=logging.INFO)
-# logger = logging.getLogger(__name__)
-# client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1",token=HF_TOKEN)
-# # Set up the template environment with the templates directory
-# env = Environment(loader=FileSystemLoader(proj_dir / 'templates'))
-
-# # Load the templates directly from the environment
-# template = env.get_template('template.j2')
-# template_html = env.get_template('template_html.j2')
-
-# def system_instructions(question_difficulty, topic,documents_str):
-#     return f"""<s> [INST] Your are a great teacher and your task is to create 10 questions with 4 choices with a {question_difficulty} difficulty  about topic request " {topic} " only from the below given documents, {documents_str} then create an answers. Index in JSON format, the questions as "Q#":"" to "Q#":"", the four choices as "Q#:C1":"" to "Q#:C4":"", and the answers as "A#":"Q#:C#" to "A#":"Q#:C#". [/INST]"""
-
-
-# RAG_db=gr.State()
-
-# with gr.Blocks(title="Quiz Maker", theme=gr.themes.Default(primary_hue="green", secondary_hue="green"), css="style.css") as QUIZBOT:
-#     def load_model():
-#         RAG= RAGPretrainedModel.from_pretrained("colbert-ir/colbertv2.0")
-#         RAG_db.value=RAG.from_index('.ragatouille/colbert/indexes/cbseclass10index')
-#         return 'Ready to Go!!'
-#     with gr.Column(scale=4):
-#         gr.HTML("""
-#     <center>
-#       <h1><span style="color: purple;">ADWITIYA</span> Customs Manual  Quizbot</h1>
-#       <h2>Generative AI-powered Capacity building for Training Officers</h2>
-#       <i>⚠️ NACIN Faculties create quiz from any topic dynamically for classroom evaluation after their sessions ! ⚠️</i>
-#     </center>
-#     """)
-#         #gr.Warning('Retrieving using ColBERT.. First time query will take a minute for model to load..pls wait')
-#     with gr.Column(scale=2):
-#         load_btn = gr.Button("Click to Load!🚀")
-#         load_text=gr.Textbox()
-#         load_btn.click(load_model,[],load_text)
-        
-   
-#     topic = gr.Textbox(label="Enter the Topic for Quiz", placeholder="Write any topic/details from Customs Manual")
-
-#     with gr.Row():
-#         radio = gr.Radio(
-#             ["easy", "average", "hard"], label="How difficult should the quiz be?"
-#         )
-
-
-#     generate_quiz_btn = gr.Button("Generate Quiz!🚀")
-#     quiz_msg=gr.Textbox()
-
-#     question_radios = [gr.Radio(visible=False), gr.Radio(visible=False), gr.Radio(
-#         visible=False), gr.Radio(visible=False), gr.Radio(visible=False), gr.Radio(visible=False), gr.Radio(visible=False), gr.Radio(
-#         visible=False), gr.Radio(visible=False), gr.Radio(visible=False)]
-
-#     print(question_radios)
-
-#     @spaces.GPU
-#     @generate_quiz_btn.click(inputs=[radio, topic], outputs=[quiz_msg]+question_radios, api_name="generate_quiz")
-#     def generate_quiz(question_difficulty, topic):
-#         top_k_rank=10
-#         RAG_db_=RAG_db.value
-#         documents_full=RAG_db_.search(topic,k=top_k_rank)
-#         gr.Warning('Generation of Quiz may take 1 to 2  minute. Pls wait')
-        
-
-#         generate_kwargs = dict(
-#             temperature=0.2,
-#             max_new_tokens=4000,
-#             top_p=0.95,
-#             repetition_penalty=1.0,
-#             do_sample=True,
-#             seed=42,
-#         )
-#         question_radio_list = []
-#         count=0
-#         while count<=3:
-#             try:
-#                 documents=[item['content'] for item in documents_full]
-#                 document_summaries = [f"[DOCUMENT {i+1}]: {summary}{count}" for i, summary in enumerate(documents)]
-#                 documents_str='\n'.join(document_summaries)
-#                 formatted_prompt = system_instructions(
-#                     question_difficulty, topic,documents_str)
-#                 print(formatted_prompt)
-#                 pre_prompt = [
-#                     {"role": "system", "content": formatted_prompt}
-#                 ]
-#                 response = client.text_generation(
-#                     formatted_prompt, **generate_kwargs, stream=False, details=False, return_full_text=False,
-#                 )
-#                 output_json = json.loads(f"{response}")
-                
-        
-#                 print(response)
-#                 print('output json', output_json)
-        
-#                 global quiz_data
-        
-#                 quiz_data = output_json
-        
-                
-        
-#                 for question_num in range(1, 11):
-#                     question_key = f"Q{question_num}"
-#                     answer_key = f"A{question_num}"
-        
-#                     question = quiz_data.get(question_key)
-#                     answer = quiz_data.get(quiz_data.get(answer_key))
-        
-#                     if not question or not answer:
-#                         continue
-        
-#                     choice_keys = [f"{question_key}:C{i}" for i in range(1, 5)]
-#                     choice_list = []
-#                     for choice_key in choice_keys:
-#                         choice = quiz_data.get(choice_key, "Choice not found")
-#                         choice_list.append(f"{choice}")
-        
-#                     radio = gr.Radio(choices=choice_list, label=question,
-#                                      visible=True, interactive=True)
-        
-#                     question_radio_list.append(radio)
-#                 if len(question_radio_list)==10:
-#                     break
-#                 else:
-#                     print('10 questions not generated . So trying again!')
-#                     count+=1
-#                     continue
-#             except Exception as e:
-#                 count+=1
-#                 print(f"Exception occurred: {e}")
-#                 if count==3:
-#                     print('Retry exhausted')
-#                     gr.Warning('Sorry. Pls try with another topic !')
-#                 else:
-#                     print(f"Trying again..{count} time...please wait")
-#                     continue
-
-#         print('Question radio list ' , question_radio_list)
-
-#         return ['Quiz Generated!']+ question_radio_list
-
-#     check_button = gr.Button("Check Score")
-
-#     score_textbox = gr.Markdown()
-
-#     @check_button.click(inputs=question_radios, outputs=score_textbox)
-#     def compare_answers(*user_answers):
-#         user_anwser_list = []
-#         user_anwser_list = user_answers
-
-#         answers_list = []
-
-#         for question_num in range(1, 20):
-#             answer_key = f"A{question_num}"
-#             answer = quiz_data.get(quiz_data.get(answer_key))
-#             if not answer:
-#                 break
-#             answers_list.append(answer)
-
-#         score = 0
-
-#         for item in user_anwser_list:
-#             if item in answers_list:
-#                 score += 1
-#         if score>5:
-#              message = f"### Good ! You got {score} over 10!"
-#         elif score>7:
-#              message = f"### Excellent ! You got {score} over 10!"
-#         else:
-#              message = f"### You got {score} over 10! Dont worry . You can prepare well and try better next time !"
-
-#         return message
-
-
-# QUIZBOT.queue()
-# QUIZBOT.launch(debug=True)
-
-
-# ################################################
-# from ragatouille import RAGPretrainedModel
-# import subprocess
-# import json
-# import spaces
-# import firebase_admin
-# from firebase_admin import credentials, firestore
-# import logging
-# from pathlib import Path
-# from time import perf_counter
-# from datetime import datetime
-# import gradio as gr
-# from jinja2 import Environment, FileSystemLoader
-# import numpy as np
-# from sentence_transformers import CrossEncoder
-# from os import getenv
-# from backend.query_llm import generate_hf, generate_openai
-# from backend.semantic_search import table, retriever
-# from gradio_client import Client  # Modified here
-
-# VECTOR_COLUMN_NAME = "vector"
-# TEXT_COLUMN_NAME = "text"
-# proj_dir = Path(__file__).parent
-
-# # Setting up the logging
-# logging.basicConfig(level=logging.INFO)
-# logger = logging.getLogger(__name__)
-
-# # Replace Mixtral client with Qwen Client
-# client = Client("Qwen/Qwen1.5-110B-Chat-demo")  # Modified here
-
-# # Set up the template environment with the templates directory
-# env = Environment(loader=FileSystemLoader(proj_dir / 'templates'))
-
-# # Load the templates directly from the environment
-# template = env.get_template('template.j2')
-# template_html = env.get_template('template_html.j2')
-
-# def system_instructions(question_difficulty, topic, documents_str):
-#     return f"""<s> [INST] You are a great teacher and your task is to create 10 questions with 4 choices with {question_difficulty} difficulty about the topic request "{topic}" only from the below given documents, {documents_str}. Then create answers. Index in JSON format, the questions as "Q#":"" to "Q#":"", the four choices as "Q#:C1":"" to "Q#:C4":"", and the answers as "A#":"Q#:C#" to "A#":"Q#:C#". example is 'A10':'Q10:C3' [/INST]"""
-
-# # RA
-# RAG_db = gr.State()
-
-# with gr.Blocks(title="Quiz Maker", theme=gr.themes.Default(primary_hue="green", secondary_hue="green"), css="style.css") as QUIZBOT:
-#     def load_model():
-#         RAG = RAGPretrainedModel.from_pretrained("colbert-ir/colbertv2.0")
-#         RAG_db.value = RAG.from_index('.ragatouille/colbert/indexes/cbseclass10index')
-#         return 'Ready to Go!!'
-
-#     with gr.Column(scale=4):
-#         gr.HTML("""
-#         <center>
-#             <h1><span style="color: purple;">ADWITIYA</span> Customs Manual Quizbot</h1>
-#             <h2>Generative AI-powered Capacity building for Training Officers</h2>
-#             <i>⚠️ NACIN Faculties create quiz from any topic dynamically for classroom evaluation after their sessions ! ⚠️</i>
-#         </center>
-#         """)
-
-#     with gr.Column(scale=2):
-#         load_btn = gr.Button("Click to Load!🚀")
-#         load_text = gr.Textbox()
-#         load_btn.click(load_model, [], load_text)
-
-#     topic = gr.Textbox(label="Enter the Topic for Quiz", placeholder="Write any topic/details from Customs Manual")
-
-#     with gr.Row():
-#         radio = gr.Radio(["easy", "average", "hard"], label="How difficult should the quiz be?")
-
-#     generate_quiz_btn = gr.Button("Generate Quiz!🚀")
-#     quiz_msg = gr.Textbox()
-
-#     question_radios = [gr.Radio(visible=False) for _ in range(10)]
-
-#     @spaces.GPU
-#     @generate_quiz_btn.click(inputs=[radio, topic], outputs=[quiz_msg] + question_radios, api_name="generate_quiz")
-#     def generate_quiz(question_difficulty, topic):
-#         top_k_rank = 10
-#         RAG_db_ = RAG_db.value
-#         documents_full = RAG_db_.search(topic, k=top_k_rank)
-
-#         gr.Warning('Generation of Quiz may take 1 to 2 minutes. Please wait.')
-
-#         question_radio_list = []
-#         count = 0
-#         while count <= 3:
-#             try:
-#                 documents = [item['content'] for item in documents_full]
-#                 document_summaries = [f"[DOCUMENT {i + 1}]: {summary}{count}" for i, summary in enumerate(documents)]
-#                 documents_str = '\n'.join(document_summaries)
-#                 formatted_prompt = system_instructions(question_difficulty, topic, documents_str)
-                
-#                 print(formatted_prompt)
-
-#                 # Use Qwen Client for quiz generation
-#                 response = client.predict(
-#                     query=formatted_prompt,
-#                     history=[],
-#                     system="You are a helpful assistant.",  # Modified to match Qwen's API
-#                     api_name="/model_chat"
-#                 )
-#                 print(response)
-#                 response1=response[1][0][1]
-#                 # Find the first and last curly braces
-#                 start_index = response1.find('{')
-#                 end_index = response1.rfind('}')
-                
-#                 # Extract only the JSON part
-#                 if start_index != -1 and end_index != -1:
-#                     cleaned_response = response1[start_index:end_index + 1]  # Include the last closing brace
-                
-#                     # Try parsing the cleaned JSON
-#                     try:
-#                         output_json = json.loads(cleaned_response)
-#                         print('Parsed JSON:', output_json)  # Successfully print the dictionary
-#                     except json.JSONDecodeError as e:
-#                         print(f"Failed to decode JSON: {e}")
-#                 else:
-#                     print("No valid JSON found in the response.")
-#                 # output_json = json.loads(f"{response}")
-#                 # print('output json', output_json)
-                  
-#                 global quiz_data
-#                 quiz_data = output_json
-
-#                 for question_num in range(1, 11):
-#                     question_key = f"Q{question_num}"
-#                     answer_key = f"A{question_num}"
-
-#                     question = quiz_data.get(question_key)
-#                     answer = quiz_data.get(quiz_data.get(answer_key))
-
-#                     if not question or not answer:
-#                         continue
-
-#                     choice_keys = [f"{question_key}:C{i}" for i in range(1, 5)]
-#                     choice_list = [quiz_data.get(choice_key, "Choice not found") for choice_key in choice_keys]
-
-#                     radio = gr.Radio(choices=choice_list, label=question, visible=True, interactive=True)
-#                     question_radio_list.append(radio)
-#                 print('question_radio_list',question_radio_list)
-
-#                 if len(question_radio_list) == 10:
-#                     break
-#                 else:
-#                     print('10 questions not generated. Trying again!')
-#                     count += 1
-#                     continue
-#             except Exception as e:
-#                 count += 1
-#                 print(f"Exception occurred: {e}")
-#                 if count == 3:
-#                     print('Retry exhausted')
-#                     gr.Warning('Sorry. Please try with another topic!')
-#                 else:
-#                     print(f"Trying again.. {count} time... please wait")
-#                     continue
-
-#         return ['Quiz Generated!'] + question_radio_list
-
-#     check_button = gr.Button("Check Score")
-#     score_textbox = gr.Markdown()
-
-#     @check_button.click(inputs=question_radios, outputs=score_textbox)
-#     def compare_answers(*user_answers):
-#         user_anwser_list = list(user_answers)
-#         answers_list = []
-
-#         for question_num in range(1, 20):
-#             answer_key = f"A{question_num}"
-#             answer = quiz_data.get(quiz_data.get(answer_key))
-#             if not answer:
-#                 break
-#             answers_list.append(answer)
-
-#         score = sum(1 for item in user_anwser_list if item in answers_list)
-
-#         if score > 5:
-#             message = f"### Good! You got {score} out of 10!"
-#         elif score > 7:
-#             message = f"### Excellent! You got {score} out of 10!"
-#         else:
-#             message = f"### You got {score} out of 10! Don't worry. You can prepare well and try better next time!"
-
-#         return message
-
-# QUIZBOT.queue()
-# QUIZBOT.launch(debug=True)
 # ##############??????????????????????????????
 # import pandas as pd
 # import json
@@ -667,8 +277,9 @@ def json_to_excel(output_json):
 
         question = output_json.get(question_key, '')
         correct_answer_key = output_json.get(answer_key, '')
-        correct_answer = correct_answer_key.split(':')[-1] if correct_answer_key else ''
-        
+        #correct_answer = correct_answer_key.split(':')[-1] if correct_answer_key else ''
+        correct_answer = correct_answer_key.split(':')[-1].replace('C', '').strip() if correct_answer_key else ''
+
         # Extract options
         option_keys = [f"{question_key}:C{i}" for i in range(1, 6)]
         options = [output_json.get(key, '') for key in option_keys]