Update app.py

app.py

@@ -201,36 +201,214 @@
 # QUIZBOT.launch(debug=True)
 
 
-################################################
-from ragatouille import RAGPretrainedModel
-import subprocess
+# ################################################
+# 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
-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 pathlib import Path
+from ragatouille import RAGPretrainedModel
+from gradio_client import Client
 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
+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")  # Modified here
+client = Client("Qwen/Qwen1.5-110B-Chat-demo")
 
 # Set up the template environment with the templates directory
 env = Environment(loader=FileSystemLoader(proj_dir / 'templates'))
@@ -245,6 +423,55 @@ def system_instructions(question_difficulty, topic, documents_str):
 # RA
 RAG_db = gr.State()
 
+def json_to_excel(output_json):
+    # Initialize list for DataFrame
+    data = []
+
+    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 ''
+        
+        # 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"
+    ])
+
+    # Save to Excel file
+    excel_path = proj_dir / "quiz_questions.xlsx"
+    df.to_excel(excel_path, index=False)
+    return excel_path
+
 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")
@@ -275,8 +502,8 @@ with gr.Blocks(title="Quiz Maker", theme=gr.themes.Default(primary_hue="green",
 
     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")
+    @gr.dependencies.GPU
+    @generate_quiz_btn.click(inputs=[radio, topic], outputs=[quiz_msg] + question_radios + [gr.File(label="Download Excel")], api_name="generate_quiz")
     def generate_quiz(question_difficulty, topic):
         top_k_rank = 10
         RAG_db_ = RAG_db.value
@@ -285,6 +512,8 @@ with gr.Blocks(title="Quiz Maker", theme=gr.themes.Default(primary_hue="green",
         gr.Warning('Generation of Quiz may take 1 to 2 minutes. Please wait.')
 
         question_radio_list = []
+        excel_file = None
+
         count = 0
         while count <= 3:
             try:
@@ -299,56 +528,58 @@ with gr.Blocks(title="Quiz Maker", theme=gr.themes.Default(primary_hue="green",
                 response = client.predict(
                     query=formatted_prompt,
                     history=[],
-                    system="You are a helpful assistant.",  # Modified to match Qwen's API
+                    system="You are a helpful assistant.", 
                     api_name="/model_chat"
                 )
                 print(response)
-                response1=response[1][0][1]
+                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
+                    cleaned_response = response1[start_index:end_index + 1]
                 
                     # 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
+                        print('Parsed 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}"
+                        # Generate the Excel file
+                        excel_file = json_to_excel(output_json)
 
-                    question = quiz_data.get(question_key)
-                    answer = quiz_data.get(quiz_data.get(answer_key))
+                        for question_num in range(1, 11):
+                            question_key = f"Q{question_num}"
+                            answer_key = f"A{question_num}"
 
-                    if not question or not answer:
-                        continue
+                            question = quiz_data.get(question_key)
+                            answer = quiz_data.get(quiz_data.get(answer_key))
 
-                    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]
+                            if not question or not answer:
+                                continue
 
-                    radio = gr.Radio(choices=choice_list, label=question, visible=True, interactive=True)
-                    question_radio_list.append(radio)
-                print('question_radio_list',question_radio_list)
+                            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]
 
-                if len(question_radio_list) == 10:
-                    break
+                            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 json.JSONDecodeError as e:
+                        print(f"Failed to decode JSON: {e}")
                 else:
-                    print('10 questions not generated. Trying again!')
-                    count += 1
-                    continue
+                    print("No valid JSON found in the response.")
+                  
             except Exception as e:
                 count += 1
                 print(f"Exception occurred: {e}")
@@ -359,14 +590,14 @@ with gr.Blocks(title="Quiz Maker", theme=gr.themes.Default(primary_hue="green",
                     print(f"Trying again.. {count} time... please wait")
                     continue
 
-        return ['Quiz Generated!'] + question_radio_list
+        return ['Quiz Generated!'] + question_radio_list + [excel_file]
 
     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)
+        user_answer_list = list(user_answers)
         answers_list = []
 
         for question_num in range(1, 20):
@@ -376,12 +607,12 @@ with gr.Blocks(title="Quiz Maker", theme=gr.themes.Default(primary_hue="green",
                 break
             answers_list.append(answer)
 
-        score = sum(1 for item in user_anwser_list if item in answers_list)
+        score = sum(1 for item in user_answer_list if item in answers_list)
 
-        if score > 5:
-            message = f"### Good! You got {score} out of 10!"
-        elif score > 7:
+        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!"