Update app.py

app.py

@@ -226,1175 +226,4 @@ with gr.Blocks(title="Quiz Maker", theme=colorful_theme) as QUIZBOT:
 
 if __name__ == "__main__":
     QUIZBOT.queue().launch(server_name="0.0.0.0", server_port=7860)# import gradio as gr
-# from pathlib import Path
-# from sentence_transformers import CrossEncoder
-# import numpy as np
-# from time import perf_counter
-# from pydantic import BaseModel, Field
-# from phi.agent import Agent
-# from phi.model.groq import Groq
-# import os
-# import logging
-
-# # Set up logging
-# logging.basicConfig(level=logging.INFO)
-# logger = logging.getLogger(__name__)
-
-# # API Key setup
-# api_key = os.getenv("GROQ_API_KEY")
-# if not api_key:
-#     gr.Warning("GROQ_API_KEY not found. Set it in 'Repository secrets'.")
-#     logger.error("GROQ_API_KEY not found.")
-# else:
-#     os.environ["GROQ_API_KEY"] = api_key
-
-# # Pydantic Model for Quiz Structure
-# class QuizItem(BaseModel):
-#     question: str = Field(..., description="The quiz question")
-#     choices: list[str] = Field(..., description="List of 4 multiple-choice options")
-#     correct_answer: str = Field(..., description="The correct choice (e.g., 'C1')")
-
-# class QuizOutput(BaseModel):
-#     items: list[QuizItem] = Field(..., description="List of 10 quiz items")
-
-# # Initialize Agents
-# groq_agent = Agent(model=Groq(model="llama3-70b-8192", api_key=api_key), markdown=True)
-
-# quiz_generator = Agent(
-#     name="Quiz Generator",
-#     role="Generates structured quiz questions and answers",
-#     instructions=[
-#         "Create 10 questions with 4 choices each based on the provided topic and documents.",
-#         "Use the specified difficulty level (easy, average, hard) to adjust question complexity.",
-#         "Ensure questions are derived only from the provided documents.",
-#         "Return the output in a structured format using the QuizOutput Pydantic model.",
-#         "Each question should have a unique correct answer from the choices (labeled C1, C2, C3, C4)."
-#     ],
-#     model=Groq(id="llama3-70b-8192", api_key=api_key),
-#     response_model=QuizOutput,
-#     markdown=True
-# )
-
-# VECTOR_COLUMN_NAME = "vector"
-# TEXT_COLUMN_NAME = "text"
-# proj_dir = Path.cwd()
-
-# # Calling functions from backend (assuming they exist)
-# from backend.semantic_search import table, retriever
-
-# def generate_quiz_data(question_difficulty, topic, documents_str):
-#     prompt = f"""Generate a quiz with {question_difficulty} difficulty on topic '{topic}' using only the following documents:\n{documents_str}"""
-#     try:
-#         response = quiz_generator.run(prompt)
-#         return response.content
-#     except Exception as e:
-#         logger.error(f"Failed to generate quiz: {e}")
-#         return None
-
-# def retrieve_and_generate_quiz(question_difficulty, topic):
-#     gr.Warning('Generating quiz may take 1-2 minutes. Please wait.', duration=60)
-#     top_k_rank = 10
-#     documents = []
-
-#     document_start = perf_counter()
-#     query_vec = retriever.encode(topic)
-#     documents = [doc[TEXT_COLUMN_NAME] for doc in table.search(query_vec, vector_column_name=VECTOR_COLUMN_NAME).limit(top_k_rank).to_list()]
-    
-#     # Apply BGE reranker
-#     cross_encoder = CrossEncoder('BAAI/bge-reranker-base')
-#     query_doc_pair = [[topic, doc] for doc in documents]
-#     cross_scores = cross_encoder.predict(query_doc_pair)
-#     sim_scores_argsort = list(reversed(np.argsort(cross_scores)))
-#     documents = [documents[idx] for idx in sim_scores_argsort[:top_k_rank]]
-
-#     documents_str = '\n'.join(documents)
-#     quiz_data = generate_quiz_data(question_difficulty, topic, documents_str)
-#     return quiz_data
-
-# def update_quiz_components(quiz_data):
-#     if not quiz_data or not quiz_data.items:
-#         return [gr.update(visible=False) for _ in range(10)] + [gr.update(value="Error: Failed to generate quiz.", visible=True)]
-    
-#     radio_updates = []
-#     for i, item in enumerate(quiz_data.items[:10]):
-#         choices = item.choices
-#         radio_update = gr.update(visible=True, choices=choices, label=item.question, value=None)
-#         radio_updates.append(radio_update)
-#     return radio_updates + [gr.update(value="Please select answers and click 'Check Score'.", visible=True)]
-
-# # FIXED FUNCTION: Changed parameter signature to accept all arguments positionally
-# def collect_answers_and_calculate(*all_inputs):
-#     print(f"Total inputs received: {len(all_inputs)}")  # Debug print
-    
-#     # The last input is quiz_data, the first 10 are radio values
-#     radio_values = all_inputs[:10]  # First 10 inputs are radio button values
-#     quiz_data = all_inputs[10]      # Last input is quiz_data
-    
-#     print(f"Received radio_values: {radio_values}")  # Debug print
-#     print(f"Received quiz_data: {quiz_data}")       # Debug print
-    
-#     # Filter out None values but keep track of positions
-#     user_answer_list = list(radio_values)
-#     correct_answers = [item.correct_answer for item in quiz_data.items[:10]]
-    
-#     print(f"User answers: {user_answer_list}")      # Debug print
-#     print(f"Correct answers: {correct_answers}")    # Debug print
-    
-#     # Calculate score - only count answered questions
-#     score = 0
-#     answered_questions = 0
-#     for u, c in zip(user_answer_list, correct_answers):
-#         if u is not None:  # Only count if user answered
-#             answered_questions += 1
-#             if u == c:
-#                 score += 1
-    
-#     print(f"Calculated score: {score}/{answered_questions}")  # Debug print
-    
-#     if answered_questions == 0:
-#         message = "### Please answer at least one question!"
-#     elif score == answered_questions:
-#         message = f"### Perfect! You got {score} out of {answered_questions} correct!"
-#     elif score > answered_questions * 0.7:
-#         message = f"### Excellent! You got {score} out of {answered_questions} correct!"
-#     elif score > answered_questions * 0.5:
-#         message = f"### Good! You got {score} out of {answered_questions} correct!"
-#     else:
-#         message = f"### You got {score} out of {answered_questions} correct! Don't worry. You can prepare well and try better next time!"
-    
-#     return message
-
-# # Define a colorful theme
-# colorful_theme = gr.themes.Default(primary_hue="cyan", secondary_hue="yellow", neutral_hue="purple")
-
-# with gr.Blocks(title="Quiz Maker", theme=colorful_theme) as QUIZBOT:
-#     # Create a single row for the HTML and Image
-#     with gr.Row():
-#         with gr.Column(scale=2):
-#             gr.Image(value='logo.png', height=200, width=200)
-#         with gr.Column(scale=6):
-#             gr.HTML("""
-#             <center>
-#                 <h1><span style="color: purple;">GOVERNMENT HIGH SCHOOL,SUTHUKENY</span> STUDENTS QUIZBOT </h1>
-#                 <h2>Generative AI-powered Capacity building for STUDENTS</h2>
-#                 <i>⚠️ Students can create quiz from any topic from 10th Science and evaluate themselves! ⚠️</i>
-#             </center>
-#             """)
-
-#     topic = gr.Textbox(label="Enter the Topic for Quiz", placeholder="Write any CHAPTER NAME")
-
-#     with gr.Row():
-#         difficulty_radio = gr.Radio(["easy", "average", "hard"], label="How difficult should the quiz be?")
-#         model_radio = gr.Radio(choices=['(ACCURATE) BGE reranker'], value='(ACCURATE) BGE reranker', label="Embeddings")
-
-#     generate_quiz_btn = gr.Button("Generate Quiz!🚀")
-#     quiz_msg = gr.Textbox(label="Status", interactive=False)
-
-#     # Pre-defined radio buttons for 10 questions
-#     question_radios = [gr.Radio(visible=False, label="", choices=[""], value=None) for _ in range(10)]
-#     quiz_data_state = gr.State(value=None)
-#     check_score_btn = gr.Button("Check Score")
-#     score_output = gr.Markdown(visible=False)
-
-#     # Register the click event for Generate Quiz without @ decorator
-#     generate_quiz_btn.click(
-#         fn=retrieve_and_generate_quiz,
-#         inputs=[difficulty_radio, topic],
-#         outputs=[quiz_data_state]
-#     ).then(
-#         fn=update_quiz_components,
-#         inputs=[quiz_data_state],
-#         outputs=question_radios + [quiz_msg]
-#     )
-
-#     # FIXED: Register the click event for Check Score with correct input handling
-#     check_score_btn.click(
-#         fn=collect_answers_and_calculate,
-#         inputs=question_radios + [quiz_data_state],  # This creates a list of 11 inputs
-#         outputs=[score_output],
-#         api_name="check_score"
-#     )
-
-# if __name__ == "__main__":
-#     QUIZBOT.queue().launch(server_name="0.0.0.0", server_port=7860)
-# from pathlib import Path
-# from sentence_transformers import CrossEncoder
-# import numpy as np
-# from time import perf_counter
-# from pydantic import BaseModel, Field
-# from phi.agent import Agent
-# from phi.model.groq import Groq
-# import os
-# import logging
-
-# # Set up logging
-# logging.basicConfig(level=logging.INFO)
-# logger = logging.getLogger(__name__)
-
-# # API Key setup
-# api_key = os.getenv("GROQ_API_KEY")
-# if not api_key:
-#     gr.Warning("GROQ_API_KEY not found. Set it in 'Repository secrets'.")
-#     logger.error("GROQ_API_KEY not found.")
-# else:
-#     os.environ["GROQ_API_KEY"] = api_key
-
-# # Pydantic Model for Quiz Structure
-# class QuizItem(BaseModel):
-#     question: str = Field(..., description="The quiz question")
-#     choices: list[str] = Field(..., description="List of 4 multiple-choice options")
-#     correct_answer: str = Field(..., description="The correct choice (e.g., 'C1')")
-
-# class QuizOutput(BaseModel):
-#     items: list[QuizItem] = Field(..., description="List of 10 quiz items")
-
-# # Initialize Agents
-# groq_agent = Agent(model=Groq(model="llama3-70b-8192", api_key=api_key), markdown=True)
-
-# quiz_generator = Agent(
-#     name="Quiz Generator",
-#     role="Generates structured quiz questions and answers",
-#     instructions=[
-#         "Create 10 questions with 4 choices each based on the provided topic and documents.",
-#         "Use the specified difficulty level (easy, average, hard) to adjust question complexity.",
-#         "Ensure questions are derived only from the provided documents.",
-#         "Return the output in a structured format using the QuizOutput Pydantic model.",
-#         "Each question should have a unique correct answer from the choices (labeled C1, C2, C3, C4)."
-#     ],
-#     model=Groq(id="llama3-70b-8192", api_key=api_key),
-#     response_model=QuizOutput,
-#     markdown=True
-# )
-
-# VECTOR_COLUMN_NAME = "vector"
-# TEXT_COLUMN_NAME = "text"
-# proj_dir = Path.cwd()
-
-# # Calling functions from backend (assuming they exist)
-# from backend.semantic_search import table, retriever
-
-# def generate_quiz_data(question_difficulty, topic, documents_str):
-#     prompt = f"""Generate a quiz with {question_difficulty} difficulty on topic '{topic}' using only the following documents:\n{documents_str}"""
-#     try:
-#         response = quiz_generator.run(prompt)
-#         return response.content
-#     except Exception as e:
-#         logger.error(f"Failed to generate quiz: {e}")
-#         return None
-
-# def retrieve_and_generate_quiz(question_difficulty, topic):
-#     gr.Warning('Generating quiz may take 1-2 minutes. Please wait.', duration=60)
-#     top_k_rank = 10
-#     documents = []
-
-#     document_start = perf_counter()
-#     query_vec = retriever.encode(topic)
-#     documents = [doc[TEXT_COLUMN_NAME] for doc in table.search(query_vec, vector_column_name=VECTOR_COLUMN_NAME).limit(top_k_rank).to_list()]
-    
-#     # Apply BGE reranker
-#     cross_encoder = CrossEncoder('BAAI/bge-reranker-base')
-#     query_doc_pair = [[topic, doc] for doc in documents]
-#     cross_scores = cross_encoder.predict(query_doc_pair)
-#     sim_scores_argsort = list(reversed(np.argsort(cross_scores)))
-#     documents = [documents[idx] for idx in sim_scores_argsort[:top_k_rank]]
-
-#     documents_str = '\n'.join(documents)
-#     quiz_data = generate_quiz_data(question_difficulty, topic, documents_str)
-#     return quiz_data
-
-# def update_quiz_components(quiz_data):
-#     if not quiz_data or not quiz_data.items:
-#         return [gr.update(visible=False) for _ in range(10)] + [gr.update(value="Error: Failed to generate quiz.", visible=True)]
-    
-#     radio_updates = []
-#     for i, item in enumerate(quiz_data.items[:10]):
-#         choices = item.choices
-#         radio_update = gr.update(visible=True, choices=choices, label=item.question, value=None)
-#         radio_updates.append(radio_update)
-#     return radio_updates + [gr.update(value="Please select answers and click 'Check Score'.", visible=True)]
-
-# def calculate_score(*user_answers, quiz_data):  # quiz_data as a positional argument after *user_answers
-#     if not quiz_data or not quiz_data.items:
-#         return "Please generate a quiz first."
-#     user_answer_list = [ans for ans in user_answers[:-1] if ans]  # Exclude quiz_data from user_answers
-#     correct_answers = [item.correct_answer for item in quiz_data.items[:10]]
-#     score = sum(1 for u, c in zip(user_answer_list, correct_answers) if u == c)
-#     if score > 7:
-#         message = f"### Excellent! You got {score} out of 10!"
-#     elif score > 5:
-#         message = f"### Good! 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
-
-# # Define a colorful theme
-# colorful_theme = gr.themes.Default(primary_hue="cyan", secondary_hue="yellow", neutral_hue="purple")
-
-# with gr.Blocks(title="Quiz Maker", theme=colorful_theme) as QUIZBOT:
-#     # Create a single row for the HTML and Image
-#     with gr.Row():
-#         with gr.Column(scale=2):
-#             gr.Image(value='logo.png', height=200, width=200)
-#         with gr.Column(scale=6):
-#             gr.HTML("""
-#             <center>
-#                 <h1><span style="color: purple;">GOVERNMENT HIGH SCHOOL,SUTHUKENY</span> STUDENTS QUIZBOT </h1>
-#                 <h2>Generative AI-powered Capacity building for STUDENTS</h2>
-#                 <i>⚠️ Students can create quiz from any topic from 10th Science and evaluate themselves! ⚠️</i>
-#             </center>
-#             """)
-
-#     topic = gr.Textbox(label="Enter the Topic for Quiz", placeholder="Write any CHAPTER NAME")
-
-#     with gr.Row():
-#         difficulty_radio = gr.Radio(["easy", "average", "hard"], label="How difficult should the quiz be?")
-#         model_radio = gr.Radio(choices=['(ACCURATE) BGE reranker'], value='(ACCURATE) BGE reranker', label="Embeddings")
-
-#     generate_quiz_btn = gr.Button("Generate Quiz!🚀")
-#     quiz_msg = gr.Textbox(label="Status", interactive=False)
-
-#     # Pre-defined radio buttons for 10 questions
-#     question_radios = [gr.Radio(visible=False, label="", choices=[""], value=None) for _ in range(10)]
-#     quiz_data_state = gr.State(value=None)
-#     check_score_btn = gr.Button("Check Score")
-#     score_output = gr.Markdown(visible=False)
-
-#     # Register the click event for Generate Quiz without @ decorator
-#     generate_quiz_btn.click(
-#         fn=retrieve_and_generate_quiz,
-#         inputs=[difficulty_radio, topic],
-#         outputs=[quiz_data_state]
-#     ).then(
-#         fn=update_quiz_components,
-#         inputs=[quiz_data_state],
-#         outputs=question_radios + [quiz_msg]
-#     )
-
-#     # Register the click event for Check Score with explicit input mapping
-#     check_score_btn.click(
-#         fn=calculate_score,
-#         inputs=question_radios + [quiz_data_state],
-#         outputs=[score_output],
-#         api_name="check_score"  # Optional: for clarity
-#     )
-
-# if __name__ == "__main__":
-#     QUIZBOT.queue().launch(server_name="0.0.0.0", server_port=7860)# import gradio as gr
-# # from pathlib import Path
-# from sentence_transformers import CrossEncoder
-# import numpy as np
-# from time import perf_counter
-# from pydantic import BaseModel, Field
-# from phi.agent import Agent
-# from phi.model.groq import Groq
-# import os
-# import logging
-
-# # Set up logging
-# logging.basicConfig(level=logging.INFO)
-# logger = logging.getLogger(__name__)
-
-# # API Key setup
-# api_key = os.getenv("GROQ_API_KEY")
-# if not api_key:
-#     gr.Warning("GROQ_API_KEY not found. Set it in 'Repository secrets'.")
-#     logger.error("GROQ_API_KEY not found.")
-# else:
-#     os.environ["GROQ_API_KEY"] = api_key
-
-# # Pydantic Model for Quiz Structure
-# class QuizItem(BaseModel):
-#     question: str = Field(..., description="The quiz question")
-#     choices: list[str] = Field(..., description="List of 4 multiple-choice options")
-#     correct_answer: str = Field(..., description="The correct choice (e.g., 'C1')")
-
-# class QuizOutput(BaseModel):
-#     items: list[QuizItem] = Field(..., description="List of 10 quiz items")
-
-# # Initialize Agents
-# groq_agent = Agent(model=Groq(model="llama3-70b-8192", api_key=api_key), markdown=True)
-
-# quiz_generator = Agent(
-#     name="Quiz Generator",
-#     role="Generates structured quiz questions and answers",
-#     instructions=[
-#         "Create 10 questions with 4 choices each based on the provided topic and documents.",
-#         "Use the specified difficulty level (easy, average, hard) to adjust question complexity.",
-#         "Ensure questions are derived only from the provided documents.",
-#         "Return the output in a structured format using the QuizOutput Pydantic model.",
-#         "Each question should have a unique correct answer from the choices (labeled C1, C2, C3, C4)."
-#     ],
-#     model=Groq(id="llama3-70b-8192", api_key=api_key),
-#     response_model=QuizOutput,
-#     markdown=True
-# )
-
-# VECTOR_COLUMN_NAME = "vector"
-# TEXT_COLUMN_NAME = "text"
-# proj_dir = Path.cwd()
-
-# # Calling functions from backend (assuming they exist)
-# from backend.semantic_search import table, retriever
-
-# def generate_quiz_data(question_difficulty, topic, documents_str):
-#     prompt = f"""Generate a quiz with {question_difficulty} difficulty on topic '{topic}' using only the following documents:\n{documents_str}"""
-#     try:
-#         response = quiz_generator.run(prompt)
-#         return response.content
-#     except Exception as e:
-#         logger.error(f"Failed to generate quiz: {e}")
-#         return None
-
-# def retrieve_and_generate_quiz(question_difficulty, topic):
-#     gr.Warning('Generating quiz may take 1-2 minutes. Please wait.', duration=60)
-#     top_k_rank = 10
-#     documents = []
-
-#     document_start = perf_counter()
-#     query_vec = retriever.encode(topic)
-#     documents = [doc[TEXT_COLUMN_NAME] for doc in table.search(query_vec, vector_column_name=VECTOR_COLUMN_NAME).limit(top_k_rank).to_list()]
-    
-#     # Apply BGE reranker
-#     cross_encoder = CrossEncoder('BAAI/bge-reranker-base')
-#     query_doc_pair = [[topic, doc] for doc in documents]
-#     cross_scores = cross_encoder.predict(query_doc_pair)
-#     sim_scores_argsort = list(reversed(np.argsort(cross_scores)))
-#     documents = [documents[idx] for idx in sim_scores_argsort[:top_k_rank]]
-
-#     documents_str = '\n'.join(documents)
-#     quiz_data = generate_quiz_data(question_difficulty, topic, documents_str)
-#     return quiz_data
-
-# def update_quiz_components(quiz_data):
-#     if not quiz_data or not quiz_data.items:
-#         return [gr.update(visible=False) for _ in range(10)] + [gr.update(value="Error: Failed to generate quiz.", visible=True)]
-    
-#     radio_updates = []
-#     for i, item in enumerate(quiz_data.items[:10]):
-#         choices = item.choices
-#         radio_update = gr.update(visible=True, choices=choices, label=item.question, value=None)
-#         radio_updates.append(radio_update)
-#     return radio_updates + [gr.update(value="Please select answers and click 'Check Score'.", visible=True)]
-
-# def calculate_score(*user_answers, quiz_data):
-#     if not quiz_data or not quiz_data.items:
-#         return "Please generate a quiz first."
-#     user_answer_list = [ans for ans in user_answers[:-1] if ans]  # Exclude quiz_data from user_answers
-#     correct_answers = [item.correct_answer for item in quiz_data.items[:10]]
-#     score = sum(1 for u, c in zip(user_answer_list, correct_answers) if u == c)
-#     if score > 7:
-#         message = f"### Excellent! You got {score} out of 10!"
-#     elif score > 5:
-#         message = f"### Good! 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
-
-# # Define a colorful theme
-# colorful_theme = gr.themes.Default(primary_hue="cyan", secondary_hue="yellow", neutral_hue="purple")
-
-# with gr.Blocks(title="Quiz Maker", theme=colorful_theme) as QUIZBOT:
-#     # Create a single row for the HTML and Image
-#     with gr.Row():
-#         with gr.Column(scale=2):
-#             gr.Image(value='logo.png', height=200, width=200)
-#         with gr.Column(scale=6):
-#             gr.HTML("""
-#             <center>
-#                 <h1><span style="color: purple;">GOVERNMENT HIGH SCHOOL,SUTHUKENY</span> STUDENTS QUIZBOT </h1>
-#                 <h2>Generative AI-powered Capacity building for STUDENTS</h2>
-#                 <i>⚠️ Students can create quiz from any topic from 10th Science and evaluate themselves! ⚠️</i>
-#             </center>
-#             """)
-
-#     topic = gr.Textbox(label="Enter the Topic for Quiz", placeholder="Write any CHAPTER NAME")
-
-#     with gr.Row():
-#         difficulty_radio = gr.Radio(["easy", "average", "hard"], label="How difficult should the quiz be?")
-#         model_radio = gr.Radio(choices=['(ACCURATE) BGE reranker'], value='(ACCURATE) BGE reranker', label="Embeddings")
-
-#     generate_quiz_btn = gr.Button("Generate Quiz!🚀")
-#     quiz_msg = gr.Textbox(label="Status", interactive=False)
-
-#     # Pre-defined radio buttons for 10 questions
-#     question_radios = [gr.Radio(visible=False, label="", choices=[""], value=None) for _ in range(10)]
-#     quiz_data_state = gr.State(value=None)
-#     check_score_btn = gr.Button("Check Score")
-#     score_output = gr.Markdown(visible=False)
-
-#     # Register the click event for Generate Quiz without @ decorator
-#     generate_quiz_btn.click(
-#         fn=retrieve_and_generate_quiz,
-#         inputs=[difficulty_radio, topic],
-#         outputs=[quiz_data_state]
-#     ).then(
-#         fn=update_quiz_components,
-#         inputs=[quiz_data_state],
-#         outputs=question_radios + [quiz_msg]
-#     )
-
-#     # Register the click event for Check Score without @ decorator
-#     check_score_btn.click(
-#         fn=calculate_score,
-#         inputs=question_radios + [quiz_data_state],
-#         outputs=[score_output]
-#     )
-
-# if __name__ == "__main__":
-#     QUIZBOT.queue().launch(server_name="0.0.0.0", server_port=7860)# import gradio as gr
-# from pathlib import Path
-# from sentence_transformers import CrossEncoder
-# import numpy as np
-# from time import perf_counter
-# from pydantic import BaseModel, Field
-# from phi.agent import Agent
-# from phi.model.groq import Groq
-# import os
-# import logging
-
-# # Set up logging
-# logging.basicConfig(level=logging.INFO)
-# logger = logging.getLogger(__name__)
-
-# # API Key setup
-# api_key = os.getenv("GROQ_API_KEY")
-# if not api_key:
-#     gr.Warning("GROQ_API_KEY not found. Set it in 'Repository secrets'.")
-#     logger.error("GROQ_API_KEY not found.")
-# else:
-#     os.environ["GROQ_API_KEY"] = api_key
-
-# # Pydantic Model for Quiz Structure
-# class QuizItem(BaseModel):
-#     question: str = Field(..., description="The quiz question")
-#     choices: list[str] = Field(..., description="List of 4 multiple-choice options")
-#     correct_answer: str = Field(..., description="The correct choice (e.g., 'C1')")
-
-# class QuizOutput(BaseModel):
-#     items: list[QuizItem] = Field(..., description="List of 10 quiz items")
-
-# # Initialize Agents
-# groq_agent = Agent(model=Groq(model="llama3-70b-8192", api_key=api_key), markdown=True)
-
-# quiz_generator = Agent(
-#     name="Quiz Generator",
-#     role="Generates structured quiz questions and answers",
-#     instructions=[
-#         "Create 10 questions with 4 choices each based on the provided topic and documents.",
-#         "Use the specified difficulty level (easy, average, hard) to adjust question complexity.",
-#         "Ensure questions are derived only from the provided documents.",
-#         "Return the output in a structured format using the QuizOutput Pydantic model.",
-#         "Each question should have a unique correct answer from the choices (labeled C1, C2, C3, C4)."
-#     ],
-#     model=Groq(id="llama3-70b-8192", api_key=api_key),
-#     response_model=QuizOutput,
-#     markdown=True
-# )
-
-# VECTOR_COLUMN_NAME = "vector"
-# TEXT_COLUMN_NAME = "text"
-# proj_dir = Path.cwd()
-
-# # Calling functions from backend (assuming they exist)
-# from backend.semantic_search import table, retriever
-
-# def generate_quiz_data(question_difficulty, topic, documents_str):
-#     prompt = f"""Generate a quiz with {question_difficulty} difficulty on topic '{topic}' using only the following documents:\n{documents_str}"""
-#     try:
-#         response = quiz_generator.run(prompt)
-#         return response.content
-#     except Exception as e:
-#         logger.error(f"Failed to generate quiz: {e}")
-#         return None
-
-# def retrieve_and_generate_quiz(question_difficulty, topic):
-#     gr.Warning('Generating quiz may take 1-2 minutes. Please wait.', duration=60)
-#     top_k_rank = 10
-#     documents = []
-
-#     document_start = perf_counter()
-#     query_vec = retriever.encode(topic)
-#     documents = [doc[TEXT_COLUMN_NAME] for doc in table.search(query_vec, vector_column_name=VECTOR_COLUMN_NAME).limit(top_k_rank).to_list()]
-    
-#     # Apply BGE reranker
-#     cross_encoder = CrossEncoder('BAAI/bge-reranker-base')
-#     query_doc_pair = [[topic, doc] for doc in documents]
-#     cross_scores = cross_encoder.predict(query_doc_pair)
-#     sim_scores_argsort = list(reversed(np.argsort(cross_scores)))
-#     documents = [documents[idx] for idx in sim_scores_argsort[:top_k_rank]]
-
-#     documents_str = '\n'.join(documents)
-#     quiz_data = generate_quiz_data(question_difficulty, topic, documents_str)
-#     return quiz_data
-
-# def update_quiz_components(quiz_data):
-#     if not quiz_data or not quiz_data.items:
-#         return [gr.update(visible=False) for _ in range(10)] + [gr.update(value="Error: Failed to generate quiz.", visible=True)]
-    
-#     radio_updates = []
-#     for i, item in enumerate(quiz_data.items[:10]):
-#         choices = item.choices
-#         radio_update = gr.update(visible=True, choices=choices, label=item.question, value=None)
-#         radio_updates.append(radio_update)
-#     return radio_updates + [gr.update(value="Please select answers and click 'Check Score'.", visible=True)]
-
-# def calculate_score(*user_answers, quiz_data):
-#     if not quiz_data or not quiz_data.items:
-#         return "Please generate a quiz first."
-#     user_answer_list = [ans for ans in user_answers if ans]
-#     correct_answers = [item.correct_answer for item in quiz_data.items[:10]]
-#     score = sum(1 for u, c in zip(user_answer_list, correct_answers) if u == c)
-#     if score > 7:
-#         message = f"### Excellent! You got {score} out of 10!"
-#     elif score > 5:
-#         message = f"### Good! 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
-
-# with gr.Blocks(title="Quiz Generator Test") as QUIZBOT:
-#     with gr.Row():
-#         gr.Markdown("# Quiz Generator Test")
-
-#     topic = gr.Textbox(label="Enter Topic", placeholder="Write any topic from 9th Science CBSE")
-#     difficulty_radio = gr.Radio(["easy", "average", "hard"], label="How difficult should the quiz be?")
-    
-#     generate_quiz_btn = gr.Button("Generate Quiz")
-#     check_score_btn = gr.Button("Check Score")
-    
-#     # Pre-defined radio buttons for 10 questions
-#     question_radios = [gr.Radio(visible=False, label="", choices=[""], value=None) for _ in range(10)]
-#     quiz_data_state = gr.State(value=None)
-#     score_output = gr.Markdown(visible=False)
-
-#     # Register the click event for Generate Quiz without @ decorator
-#     generate_quiz_btn.click(
-#         fn=retrieve_and_generate_quiz,
-#         inputs=[difficulty_radio, topic],
-#         outputs=[quiz_data_state]
-#     ).then(
-#         fn=update_quiz_components,
-#         inputs=[quiz_data_state],
-#         outputs=question_radios + [score_output]
-#     )
-
-#     # Register the click event for Check Score without @ decorator
-#     check_score_btn.click(
-#         fn=calculate_score,
-#         inputs=question_radios + [quiz_data_state],
-#         outputs=[score_output]
-#     )
-
-# if __name__ == "__main__":
-#     QUIZBOT.queue().launch(server_name="0.0.0.0", server_port=7860)# import gradio as gr
-# # from pathlib import Path
-# # from sentence_transformers import CrossEncoder
-# # import numpy as np
-# # from time import perf_counter
-# # from pydantic import BaseModel, Field
-# # from phi.agent import Agent
-# # from phi.model.groq import Groq
-# # import os
-# # import logging
-
-# # # Set up logging
-# # logging.basicConfig(level=logging.INFO)
-# # logger = logging.getLogger(__name__)
-
-# # # API Key setup
-# # api_key = os.getenv("GROQ_API_KEY")
-# # if not api_key:
-# #     gr.Warning("GROQ_API_KEY not found. Set it in 'Repository secrets'.")
-# #     logger.error("GROQ_API_KEY not found.")
-# # else:
-# #     os.environ["GROQ_API_KEY"] = api_key
-
-# # # Pydantic Model for Quiz Structure
-# # class QuizItem(BaseModel):
-# #     question: str = Field(..., description="The quiz question")
-# #     choices: list[str] = Field(..., description="List of 4 multiple-choice options")
-# #     correct_answer: str = Field(..., description="The correct choice (e.g., 'C1')")
-
-# # class QuizOutput(BaseModel):
-# #     items: list[QuizItem] = Field(..., description="List of 10 quiz items")
-
-# # # Initialize Agents
-# # groq_agent = Agent(model=Groq(model="llama3-70b-8192", api_key=api_key), markdown=True)
-
-# # quiz_generator = Agent(
-# #     name="Quiz Generator",
-# #     role="Generates structured quiz questions and answers",
-# #     instructions=[
-# #         "Create 10 questions with 4 choices each based on the provided topic and documents.",
-# #         "Use the specified difficulty level (easy, average, hard) to adjust question complexity.",
-# #         "Ensure questions are derived only from the provided documents.",
-# #         "Return the output in a structured format using the QuizOutput Pydantic model.",
-# #         "Each question should have a unique correct answer from the choices (labeled C1, C2, C3, C4)."
-# #     ],
-# #     model=Groq(id="llama3-70b-8192", api_key=api_key),
-# #     response_model=QuizOutput,
-# #     markdown=True
-# # )
-
-# # VECTOR_COLUMN_NAME = "vector"
-# # TEXT_COLUMN_NAME = "text"
-# # proj_dir = Path.cwd()
-
-# # # Calling functions from backend (assuming they exist)
-# # from backend.semantic_search import table, retriever
-
-# # def generate_quiz_data(question_difficulty, topic, documents_str):
-# #     prompt = f"""Generate a quiz with {question_difficulty} difficulty on topic '{topic}' using only the following documents:\n{documents_str}"""
-# #     try:
-# #         response = quiz_generator.run(prompt)
-# #         return response.content
-# #     except Exception as e:
-# #         logger.error(f"Failed to generate quiz: {e}")
-# #         return None
-
-# # def retrieve_and_generate_quiz(question_difficulty, topic):
-# #     gr.Warning('Generating quiz may take 1-2 minutes. Please wait.', duration=60)
-# #     top_k_rank = 10
-# #     documents = []
-
-# #     document_start = perf_counter()
-# #     query_vec = retriever.encode(topic)
-# #     documents = [doc[TEXT_COLUMN_NAME] for doc in table.search(query_vec, vector_column_name=VECTOR_COLUMN_NAME).limit(top_k_rank).to_list()]
-    
-# #     # Apply BGE reranker
-# #     cross_encoder = CrossEncoder('BAAI/bge-reranker-base')
-# #     query_doc_pair = [[topic, doc] for doc in documents]
-# #     cross_scores = cross_encoder.predict(query_doc_pair)
-# #     sim_scores_argsort = list(reversed(np.argsort(cross_scores)))
-# #     documents = [documents[idx] for idx in sim_scores_argsort[:top_k_rank]]
-
-# #     documents_str = '\n'.join(documents)
-# #     quiz_data = generate_quiz_data(question_difficulty, topic, documents_str)
-# #     if not quiz_data or not quiz_data.items:
-# #         return gr.update(value="Error: Failed to generate quiz.", visible=True)
-
-# #     # Generate HTML for questions and choices
-# #     html_content = "<div style='font-family: Arial, sans-serif; padding: 10px;'>"
-# #     for i, item in enumerate(quiz_data.items[:10], 1):
-# #         html_content += f"<h3>Question {i}: {item.question}</h3>"
-# #         html_content += "<ul style='list-style-type: none;'>"
-# #         for j, choice in enumerate(item.choices, 1):
-# #             html_content += f"<li>C{j}: {choice}</li>"
-# #         html_content += "</ul>"
-# #     html_content += "</div>"
-
-# #     return gr.update(value=html_content, visible=True)
-
-# # with gr.Blocks(title="Quiz Generator Test") as QUIZBOT:
-# #     with gr.Row():
-# #         gr.Markdown("# Quiz Generator Test")
-
-# #     topic = gr.Textbox(label="Enter Topic", placeholder="Write any topic from 9th Science CBSE")
-# #     difficulty_radio = gr.Radio(["easy", "average", "hard"], label="How difficult should the quiz be?")
-    
-# #     generate_quiz_btn = gr.Button("Generate Quiz")
-# #     quiz_output = gr.HTML(visible=False)
-
-# #     # Register the click event without @ decorator
-# #     generate_quiz_btn.click(
-# #         fn=retrieve_and_generate_quiz,
-# #         inputs=[difficulty_radio, topic],
-# #         outputs=[quiz_output]
-# #     )
-
-# # if __name__ == "__main__":
-# #     QUIZBOT.queue().launch(server_name="0.0.0.0", server_port=7860)
-    
-# # import gradio as gr
-# # from pathlib import Path
-# # from tempfile import NamedTemporaryFile
-# # from sentence_transformers import CrossEncoder
-# # import numpy as np
-# # from time import perf_counter
-# # import pandas as pd
-# # from pydantic import BaseModel, Field
-# # from phi.agent import Agent
-# # from phi.model.groq import Groq
-# # import os
-# # import logging
-
-# # # Set up logging
-# # logging.basicConfig(level=logging.INFO)
-# # logger = logging.getLogger(__name__)
-
-# # # API Key setup
-# # api_key = os.getenv("GROQ_API_KEY")
-# # if not api_key:
-# #     gr.Warning("GROQ_API_KEY not found. Set it in 'Repository secrets'.")
-# #     logger.error("GROQ_API_KEY not found.")
-# # else:
-# #     os.environ["GROQ_API_KEY"] = api_key
-
-# # # Pydantic Model for Quiz Structure
-# # class QuizItem(BaseModel):
-# #     question: str = Field(..., description="The quiz question")
-# #     choices: list[str] = Field(..., description="List of 4 multiple-choice options")
-# #     correct_answer: str = Field(..., description="The correct choice (e.g., 'C1')")
-
-# # class QuizOutput(BaseModel):
-# #     items: list[QuizItem] = Field(..., description="List of 10 quiz items")
-
-# # # Initialize Agents
-# # groq_agent = Agent(model=Groq(model="llama3-70b-8192", api_key=api_key), markdown=True)
-
-# # quiz_generator = Agent(
-# #     name="Quiz Generator",
-# #     role="Generates structured quiz questions and answers",
-# #     instructions=[
-# #         "Create 10 questions with 4 choices each based on the provided topic and documents.",
-# #         "Use the specified difficulty level (easy, average, hard) to adjust question complexity.",
-# #         "Ensure questions are derived only from the provided documents.",
-# #         "Return the output in a structured format using the QuizOutput Pydantic model.",
-# #         "Each question should have a unique correct answer from the choices (labeled C1, C2, C3, C4)."
-# #     ],
-# #     model=Groq(id="llama3-70b-8192", api_key=api_key),
-# #     response_model=QuizOutput,
-# #     markdown=True
-# # )
-
-# # VECTOR_COLUMN_NAME = "vector"
-# # TEXT_COLUMN_NAME = "text"
-# # proj_dir = Path.cwd()
-
-# # # Calling functions from backend (assuming they exist)
-# # from backend.semantic_search import table, retriever
-
-# # def generate_quiz_data(question_difficulty, topic, documents_str):
-# #     prompt = f"""Generate a quiz with {question_difficulty} difficulty on topic '{topic}' using only the following documents:\n{documents_str}"""
-# #     try:
-# #         response = quiz_generator.run(prompt)
-# #         return response.content
-# #     except Exception as e:
-# #         logger.error(f"Failed to generate quiz: {e}")
-# #         return None
-
-# # def json_to_excel(quiz_data):
-# #     data = []
-# #     gr.Warning('Generating Shareable file link..', duration=30)
-# #     for i, item in enumerate(quiz_data.items, 1):
-# #         data.append([
-# #             item.question,
-# #             "Multiple Choice",
-# #             item.choices[0],
-# #             item.choices[1],
-# #             item.choices[2],
-# #             item.choices[3],
-# #             '',  # Option 5 (empty)
-# #             item.correct_answer.replace('C', ''),
-# #             30,
-# #             ''
-# #         ])
-# #     df = pd.DataFrame(data, columns=[
-# #         "Question Text", "Question Type", "Option 1", "Option 2", "Option 3", "Option 4", "Option 5", "Correct Answer", "Time in seconds", "Image Link"
-# #     ])
-# #     temp_file = NamedTemporaryFile(delete=True, suffix=".xlsx")
-# #     df.to_excel(temp_file.name, index=False)
-# #     return temp_file.name
-
-# # colorful_theme = gr.themes.Default(primary_hue="cyan", secondary_hue="yellow", neutral_hue="purple")
-
-# # with gr.Blocks(title="Quiz Maker", theme=colorful_theme) as QUIZBOT:
-# #     with gr.Row():
-# #         with gr.Column(scale=2):
-# #             gr.Image(value='logo.png', height=200, width=200)
-# #         with gr.Column(scale=6):
-# #             gr.HTML("""
-# #             <center>
-# #                 <h1><span style="color: purple;">GOVERNMENT HIGH SCHOOL,SUTHUKENY</span> STUDENTS QUIZBOT </h1>
-# #                 <h2>Generative AI-powered Capacity building for STUDENTS</h2>
-# #                 <i>⚠️ Students can create quiz from any topic from 9th Science and evaluate themselves! ⚠️</i>
-# #             </center>
-# #             """)
-
-# #     topic = gr.Textbox(label="Enter the Topic for Quiz", placeholder="Write any topic/details from 9TH Science CBSE")
-# #     with gr.Row():
-# #         difficulty_radio = gr.Radio(["easy", "average", "hard"], label="How difficult should the quiz be?")
-# #         model_radio = gr.Radio(choices=['(ACCURATE) BGE reranker'], value='(ACCURATE) BGE reranker', label="Embeddings")  # Removed ColBERT option
-
-# #     generate_quiz_btn = gr.Button("Generate Quiz!🚀")
-# #     quiz_msg = gr.Textbox(label="Status", interactive=False)
-# #     question_display = gr.HTML(visible=False)
-# #     download_excel = gr.File(label="Download Excel")
-
-# #     @generate_quiz_btn.click(inputs=[difficulty_radio, topic, model_radio], outputs=[quiz_msg, question_display, download_excel])
-# #     def generate_quiz(question_difficulty, topic, cross_encoder):
-# #         top_k_rank = 10
-# #         documents = []
-# #         gr.Warning('Generating Quiz may take 1-2 minutes. Please wait.', duration=60)
-
-# #         document_start = perf_counter()
-# #         query_vec = retriever.encode(topic)
-# #         documents = [doc[TEXT_COLUMN_NAME] for doc in table.search(query_vec, vector_column_name=VECTOR_COLUMN_NAME).limit(top_k_rank).to_list()]
-# #         if cross_encoder == '(ACCURATE) BGE reranker':
-# #             cross_encoder1 = CrossEncoder('BAAI/bge-reranker-base')
-# #             query_doc_pair = [[topic, doc] for doc in documents]
-# #             cross_scores = cross_encoder1.predict(query_doc_pair)
-# #             sim_scores_argsort = list(reversed(np.argsort(cross_scores)))
-# #             documents = [documents[idx] for idx in sim_scores_argsort[:top_k_rank]]
-
-# #         documents_str = '\n'.join(documents)
-# #         quiz_data = generate_quiz_data(question_difficulty, topic, documents_str)
-# #         if not quiz_data or not quiz_data.items:
-# #             return ["Error: Failed to generate quiz.", gr.HTML(visible=False), None]
-
-# #         excel_file = json_to_excel(quiz_data)
-# #         html_content = "<div>" + "".join(f"<h3>{i}. {item.question}</h3><p>{'<br>'.join(item.choices)}</p>" for i, item in enumerate(quiz_data.items[:10], 1)) + "</div>"
-# #         return ["Quiz Generated!", gr.HTML(value=html_content, visible=True), excel_file]
-
-# #     check_button = gr.Button("Check Score")
-# #     score_textbox = gr.Markdown()
-
-# #     @check_button.click(inputs=question_display, outputs=score_textbox)
-# #     def compare_answers(html_content):
-# #         if not quiz_data or not quiz_data.items:
-# #             return "Please generate a quiz first."
-# #         # Placeholder for user answers (adjust based on actual UI implementation)
-# #         user_answers = []  # Implement parsing logic if using radio inputs
-# #         correct_answers = [item.correct_answer for item in quiz_data.items[:10]]
-# #         score = sum(1 for u, c in zip(user_answers, correct_answers) if u == c)
-# #         if score > 7:
-# #             message = f"### Excellent! You got {score} out of 10!"
-# #         elif score > 5:
-# #             message = f"### Good! 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
-
-# # if __name__ == "__main__":
-# #     QUIZBOT.queue().launch(debug=True)
-
-# # # # Importing libraries
-# # # import pandas as pd
-# # # import json
-# # # import gradio as gr
-# # # from pathlib import Path
-# # # from ragatouille import RAGPretrainedModel
-# # # from gradio_client import Client
-# # # from tempfile import NamedTemporaryFile
-# # # from sentence_transformers import CrossEncoder
-# # # import numpy as np
-# # # from time import perf_counter
-# # # from sentence_transformers import CrossEncoder
-
-# # # #calling functions from other files - to call the knowledge database tables (lancedb for accurate mode) for creating quiz  
-# # # from backend.semantic_search import table, retriever
-
-# # # VECTOR_COLUMN_NAME = "vector"
-# # # TEXT_COLUMN_NAME = "text"
-# # # proj_dir = Path.cwd()
-
-# # # # Set up logging
-# # # import logging
-# # # logging.basicConfig(level=logging.INFO)
-# # # logger = logging.getLogger(__name__)
-
-# # # # Replace Mixtral client with Qwen Client
-# # # client = Client("Qwen/Qwen1.5-110B-Chat-demo")
-
-# # # 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: 'A10':'Q10:C3' [/INST]"""
-
-# # # # Ragatouille database for Colbert ie highly accurate mode
-# # # RAG_db = gr.State()
-# # # quiz_data = None
-
-
-# # # #defining a function to convert json file to excel file 
-# # # def json_to_excel(output_json):
-# # #     # Initialize list for DataFrame
-# # #     data = []
-# # #     gr.Warning('Generating Shareable file link..', duration=30)
-# # #     for i in range(1, 11):  # Assuming there are 10 questions
-# # #         question_key = f"Q{i}"
-# # #         answer_key = f"A{i}"
-
-# # #         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].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]
-        
-# # #         # Add data row
-# # #         data.append([
-# # #             question,                     # Question Text
-# # #             "Multiple Choice",            # Question Type
-# # #             options[0],                   # Option 1
-# # #             options[1],                   # Option 2
-# # #             options[2] if len(options) > 2 else '',  # Option 3
-# # #             options[3] if len(options) > 3 else '',  # Option 4
-# # #             options[4] if len(options) > 4 else '',  # Option 5
-# # #             correct_answer,               # Correct Answer
-# # #             30,                           # Time in seconds
-# # #             ''                            # Image Link
-# # #         ])
-
-# # #     # Create DataFrame
-# # #     df = pd.DataFrame(data, columns=[
-# # #         "Question Text",
-# # #         "Question Type",
-# # #         "Option 1",
-# # #         "Option 2",
-# # #         "Option 3",
-# # #         "Option 4",
-# # #         "Option 5",
-# # #         "Correct Answer",
-# # #         "Time in seconds",
-# # #         "Image Link"
-# # #     ])
-
-# # #     temp_file = NamedTemporaryFile(delete=False, suffix=".xlsx")
-# # #     df.to_excel(temp_file.name, index=False)
-# # #     return temp_file.name
-# # # # Define a colorful theme
-# # # colorful_theme = gr.themes.Default(
-# # #     primary_hue="cyan",      # Set a bright cyan as primary color
-# # #     secondary_hue="yellow", # Set a bright magenta as secondary color
-# # #     neutral_hue="purple"  # Optionally set a neutral color
-        
-# # # )
-
-# # # #gradio app creation for a user interface 
-# # # with gr.Blocks(title="Quiz Maker", theme=colorful_theme) as QUIZBOT:
-    
-    
-# # #     # Create a single row for the HTML and Image
-# # #     with gr.Row():
-# # #         with gr.Column(scale=2):
-# # #             gr.Image(value='logo.png', height=200, width=200)
-# # #         with gr.Column(scale=6):
-# # #             gr.HTML("""
-# # #             <center>
-# # #                 <h1><span style="color: purple;">GOVERNMENT HIGH SCHOOL,SUTHUKENY</span> STUDENTS QUIZBOT </h1>
-# # #                 <h2>Generative AI-powered Capacity building for STUDENTS</h2>
-# # #                 <i>⚠️ Students can create quiz from any topic from 10 science and evaluate themselves! ⚠️</i>
-# # #             </center>
-# # #             """)
-        
-
-
-    
-# # #     topic = gr.Textbox(label="Enter the Topic for Quiz", placeholder="Write any CHAPTER NAME")
-
-# # #     with gr.Row():
-# # #         difficulty_radio = gr.Radio(["easy", "average", "hard"], label="How difficult should the quiz be?")
-# # #         model_radio = gr.Radio(choices=[ '(ACCURATE) BGE reranker', '(HIGH ACCURATE) ColBERT'], 
-# # #                                value='(ACCURATE) BGE reranker', label="Embeddings", 
-# # #                                info="First query to ColBERT may take a little time")
-
-# # #     generate_quiz_btn = gr.Button("Generate Quiz!🚀")
-# # #     quiz_msg = gr.Textbox()
-
-# # #     question_radios = [gr.Radio(visible=False) for _ in range(10)]
-
-# # #     @generate_quiz_btn.click(inputs=[difficulty_radio, topic, model_radio], outputs=[quiz_msg] + question_radios + [gr.File(label="Download Excel")])
-# # #     def generate_quiz(question_difficulty, topic, cross_encoder):
-# # #         top_k_rank = 10
-# # #         documents = []
-# # #         gr.Warning('Generating Quiz may take 1-2 minutes. Please wait.', duration=60)
-
-# # #         if cross_encoder == '(HIGH ACCURATE) ColBERT':
-# # #             gr.Warning('Retrieving using ColBERT.. First-time query will take 2 minute for model to load.. please wait',duration=100)
-# # #             RAG = RAGPretrainedModel.from_pretrained("colbert-ir/colbertv2.0")
-# # #             RAG_db.value = RAG.from_index('.ragatouille/colbert/indexes/cbseclass10index')
-# # #             documents_full = RAG_db.value.search(topic, k=top_k_rank)
-# # #             documents = [item['content'] for item in documents_full]
-        
-# # #         else:
-# # #             document_start = perf_counter()
-# # #             query_vec = retriever.encode(topic)
-# # #             doc1 = table.search(query_vec, vector_column_name=VECTOR_COLUMN_NAME).limit(top_k_rank)
-
-# # #             documents = table.search(query_vec, vector_column_name=VECTOR_COLUMN_NAME).limit(top_k_rank).to_list()
-# # #             documents = [doc[TEXT_COLUMN_NAME] for doc in documents]
-
-# # #             query_doc_pair = [[topic, doc] for doc in documents]
-
-# # #             # if cross_encoder == '(FAST) MiniLM-L6v2':
-# # #             #     cross_encoder1 = CrossEncoder('cross-encoder/ms-marco-MiniLM-L-6-v2')
-# # #             if cross_encoder == '(ACCURATE) BGE reranker':
-# # #                 cross_encoder1 = CrossEncoder('BAAI/bge-reranker-base')
-            
-# # #             cross_scores = cross_encoder1.predict(query_doc_pair)
-# # #             sim_scores_argsort = list(reversed(np.argsort(cross_scores)))
-# # #             documents = [documents[idx] for idx in sim_scores_argsort[:top_k_rank]]
-
-# # #         #creating a text prompt to Qwen model combining the documents and system instruction 
-# # #         formatted_prompt = system_instructions(question_difficulty, topic, '\n'.join(documents))
-# # #         print('                      Formatted Prompt : ' ,formatted_prompt)
-# # #         try:
-# # #             response = client.predict(query=formatted_prompt, history=[], system="You are a helpful assistant.", api_name="/model_chat")
-# # #             response1 = response[1][0][1]
-            
-# # #             # Extract JSON
-# # #             start_index = response1.find('{')
-# # #             end_index = response1.rfind('}')
-# # #             cleaned_response = response1[start_index:end_index + 1] if start_index != -1 and end_index != -1 else ''
-# # #             print('Cleaned Response :',cleaned_response)
-# # #             output_json = json.loads(cleaned_response)
-# # #             # Assign the extracted JSON to quiz_data for use in the comparison function
-# # #             global quiz_data
-# # #             quiz_data = output_json
-# # #             # Generate the Excel file
-# # #             excel_file = json_to_excel(output_json)
-            
-
-# # #             #Create a Quiz display in app
-# # #             question_radio_list = []
-# # #             for question_num in range(1, 11):
-# # #                 question_key = f"Q{question_num}"
-# # #                 answer_key = f"A{question_num}"
-
-# # #                 question = output_json.get(question_key)
-# # #                 answer = output_json.get(output_json.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 = [output_json.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)
-
-# # #             return ['Quiz Generated!'] + question_radio_list + [excel_file]
-
-# # #         except json.JSONDecodeError as e:
-# # #             print(f"Failed to decode JSON: {e}")
-
-# # #     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_answer_list = list(user_answers)
-# # #         answers_list = []
-
-# # #         for question_num in range(1, 11):
-# # #             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_answer_list if item in answers_list)
-
-# # #         if score > 7:
-# # #             message = f"### Excellent! You got {score} out of 10!"
-# # #         elif score > 5:
-# # #             message = f"### Good! 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)