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Upload 3 files
Browse files- requirements.txt +19 -0
- student_functions.py +356 -0
- teacher_function.py +168 -0
requirements.txt
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Flask==3.0.2
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Werkzeug==3.0.1
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selenium==4.18.1
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torch==1.10.0
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torchvision==0.11.1
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easyocr==1.4
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youtube-transcript-api==0.6.2
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pypdf==4.1.0
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Pillow
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PyPDF2==3.0.1
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pdf2image==1.17.0
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opencv-python-headless==4.8.1.78
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numpy==1.26.3
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pytesseract==0.3.10
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joblib==1.3.2
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requests==2.32.0
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ai71==0.0.18
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setuptools==69.0.3
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gtts
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student_functions.py
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@@ -0,0 +1,356 @@
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from gtts import gTTS
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import shutil
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from selenium import webdriver
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from selenium.webdriver.common.by import By
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from selenium.webdriver.common.keys import Keys
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from selenium.webdriver.support.ui import WebDriverWait
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from selenium.webdriver.support import expected_conditions as EC
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import json
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from youtube_transcript_api import YouTubeTranscriptApi
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from youtube_transcript_api.formatters import JSONFormatter
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from urllib.parse import urlparse, parse_qs
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from pypdf import PdfReader
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from ai71 import AI71
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import os
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AI71_API_KEY = "api71-api-652e5c6c-8edf-41d0-9c34-28522b07bef9"
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def extract_text_from_pdf_s(pdf_path):
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text = ""
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reader = PdfReader(pdf_path)
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for page in reader.pages:
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text += page.extract_text() + "\n"
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generate_speech_from_pdf(text[:len(text) // 2])
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return text
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def generate_response_from_pdf(query, pdf_text):
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response = ''
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for chunk in AI71(AI71_API_KEY).chat.completions.create(
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model="tiiuae/falcon-180b-chat",
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messages=[
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{"role": "system", "content": "You are a pdf questioning assistant."},
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{"role": "user",
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"content": f'''Answer the querry based on the given content.Content:{pdf_text},query:{query}'''},
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],
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stream=True,
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):
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if chunk.choices[0].delta.content:
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response += chunk.choices[0].delta.content
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return response.replace("###", '')
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def generate_quiz(subject, topic, count, difficult):
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quiz_output = ""
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for chunk in AI71(AI71_API_KEY).chat.completions.create(
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model="tiiuae/falcon-180b-chat",
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messages=[
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{"role": "system", "content": "You are a teaching assistant."},
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{"role": "user",
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"content": f'''Generate {count} multiple-choice questions in the subject of {subject} for the topic {topic} for students at a {difficult} level. Ensure the questions are well-diversified and cover various aspects of the topic. Format the questions as follows:
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Question: [Question text] [specific concept in a question]
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<<o>> [Option1]
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<<o>> [Option2]
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<<o>> [Option3]
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<<o>> [Option4],
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Answer: [Option number]'''},
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],
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stream=True,
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):
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if chunk.choices[0].delta.content:
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quiz_output += chunk.choices[0].delta.content
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print("Quiz generated")
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return quiz_output
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def generate_ai_response(query):
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ai_response = ''
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for chunk in AI71(AI71_API_KEY).chat.completions.create(
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model="tiiuae/falcon-180b-chat",
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messages=[
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{"role": "system", "content": "You are a teaching assistant."},
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{"role": "user", "content": f'Assist the user clearly for his questions: {query}.'},
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],
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stream=True,
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):
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if chunk.choices[0].delta.content:
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ai_response += chunk.choices[0].delta.content
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return ai_response.replace('###', '')
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def generate_project_idea(subject, topic, overview):
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string = ''
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for chunk in AI71(AI71_API_KEY).chat.completions.create(
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model="tiiuae/falcon-180b-chat",
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messages=[
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{"role": "system", "content": "You are a project building assistant."},
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{"role": "user",
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"content": f'''Give the different project ideas to build project in {subject} specifically in {topic} for school students. {overview}.'''},
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],
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stream=True,
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):
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if chunk.choices[0].delta.content:
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string += chunk.choices[0].delta.content
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return string
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+
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def generate_project_idea_questions(project_idea, query):
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project_idea_answer = ''
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for chunk in AI71(AI71_API_KEY).chat.completions.create(
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model="tiiuae/falcon-180b-chat",
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messages=[
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{"role": "system", "content": "You are a project building assistant."},
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{"role": "user",
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"content": f'''Assist me clearly for the following question for the given idea. Idea: {project_idea}. Question: {query}'''},
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],
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stream=True,
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):
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112 |
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if chunk.choices[0].delta.content:
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project_idea_answer += chunk.choices[0].delta.content
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return project_idea_answer
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+
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+
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def generate_step_by_step_explanation(query):
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explanation = ''
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for chunk in AI71(AI71_API_KEY).chat.completions.create(
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model="tiiuae/falcon-180b-chat",
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messages=[
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{"role": "system", "content": "You are the best teaching assistant."},
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{"role": "user",
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"content": f'''Provide me the clear step by step explanation answer for the following question. Question: {query}'''},
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],
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126 |
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stream=True,
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):
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128 |
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if chunk.choices[0].delta.content:
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explanation += chunk.choices[0].delta.content
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return explanation.replace('###', '')
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+
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133 |
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def study_plan(subjects, hours, arealag, goal):
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plan = ''
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for chunk in AI71(AI71_API_KEY).chat.completions.create(
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model="tiiuae/falcon-180b-chat",
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messages=[
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{"role": "system", "content": "You are the best teaching assistant."},
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{"role": "user",
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"content": f'''Provide me the clear personalised study plan for the subjects {subjects} i lag in areas like {arealag}, im available for {hours} hours per day and my study goal is to {goal}.Provide me like a timetable like day1,day2 for 5 days with concepts,also suggest some books'''},
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],
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stream=True,
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):
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if chunk.choices[0].delta.content:
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plan += chunk.choices[0].delta.content
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return plan.replace('\n', '<br>')
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147 |
+
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148 |
+
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class ConversationBufferMemory:
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def __init__(self, memory_key="chat_history"):
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self.memory_key = memory_key
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self.buffer = []
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153 |
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def add_to_memory(self, interaction):
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self.buffer.append(interaction)
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def get_memory(self):
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158 |
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return "\n".join([f"Human: {entry['user']}\nAssistant: {entry['assistant']}" for entry in self.buffer])
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159 |
+
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160 |
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161 |
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def spk_msg(user_input, memory):
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162 |
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chat_history = memory.get_memory()
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163 |
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msg = ''
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164 |
+
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165 |
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# Construct the message for the API request
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166 |
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messages = [
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167 |
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{"role": "system",
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"content": "You are a nice speaker having a conversation with a human.You ask the question the user choose the topic and let user answer.Provide the response only within 2 sentence"},
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169 |
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{"role": "user",
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"content": f"Previous conversation:\n{chat_history}\n\nNew human question: {user_input}\nResponse:"}
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171 |
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]
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173 |
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try:
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174 |
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for chunk in AI71(AI71_API_KEY).chat.completions.create(
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175 |
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model="tiiuae/falcon-180b-chat",
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176 |
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messages=messages,
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177 |
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stream=True,
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178 |
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):
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179 |
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if chunk.choices[0].delta.content:
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180 |
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msg += chunk.choices[0].delta.content
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181 |
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except Exception as e:
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182 |
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print(f"An error occurred: {e}")
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183 |
+
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184 |
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return msg
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185 |
+
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186 |
+
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187 |
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def get_first_youtube_video_link(query):
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188 |
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url = f'https://www.youtube.com/results?search_query={query}'
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189 |
+
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# Navigate to the URL
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191 |
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driver.get(url)
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192 |
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# Find the first video link
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194 |
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try:
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# Find the first video element
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first_video_element = driver.find_element(By.XPATH, '//a[@id="video-title"]')
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197 |
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video_link = first_video_element.get_attribute('href')
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198 |
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print(video_link)
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199 |
+
finally:
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200 |
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# Close the WebDriver
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201 |
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driver.quit()
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202 |
+
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203 |
+
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204 |
+
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205 |
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def content_translate(text):
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206 |
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translated_content = ''
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207 |
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for chunk in AI71(AI71_API_KEY).chat.completions.create(
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208 |
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model="tiiuae/falcon-180b-chat",
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209 |
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messages=[
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{"role": "system", "content": "You are the best teaching assistant."},
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211 |
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{"role": "user", "content": f'''Translate the text to hindi. Text: {text}'''},
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212 |
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],
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213 |
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stream=True,
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214 |
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):
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215 |
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if chunk.choices[0].delta.content:
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216 |
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translated_content += chunk.choices[0].delta.content
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217 |
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return translated_content
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218 |
+
|
219 |
+
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220 |
+
def get_video_id(url):
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221 |
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"""
|
222 |
+
Extract the video ID from a YouTube URL.
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223 |
+
"""
|
224 |
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parsed_url = urlparse(url)
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225 |
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if parsed_url.hostname == 'www.youtube.com' or parsed_url.hostname == 'youtube.com':
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226 |
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video_id = parse_qs(parsed_url.query).get('v')
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227 |
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if video_id:
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return video_id[0]
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229 |
+
elif parsed_url.hostname == 'youtu.be':
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230 |
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return parsed_url.path[1:]
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return None
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232 |
+
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233 |
+
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234 |
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def extract_captions(video_url):
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235 |
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"""
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Extract captions from a YouTube video URL.
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237 |
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"""
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238 |
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video_id = get_video_id(video_url)
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239 |
+
if not video_id:
|
240 |
+
print("Invalid YouTube URL.")
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241 |
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return
|
242 |
+
|
243 |
+
try:
|
244 |
+
transcript = YouTubeTranscriptApi.get_transcript(video_id)
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245 |
+
formatter = JSONFormatter()
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246 |
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formatted_transcript = formatter.format_transcript(transcript)
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247 |
+
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# Save captions to a file
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249 |
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with open(f'youtube_captions.json', 'w') as file:
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file.write(formatted_transcript)
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251 |
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252 |
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print("Captions have been extracted and saved as JSON.")
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253 |
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254 |
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except Exception as e:
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255 |
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print(f"An error occurred: {e}")
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256 |
+
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257 |
+
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258 |
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def extract_text_from_json(filename):
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259 |
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# Open and read the JSON file
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260 |
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with open(filename, 'r') as file:
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261 |
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data = json.load(file)
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262 |
+
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263 |
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# Extract and print the text fields
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264 |
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texts = [entry['text'] for entry in data]
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265 |
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return texts
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266 |
+
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267 |
+
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268 |
+
def get_simplified_explanation(text):
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269 |
+
prompt = (
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270 |
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f"The following is a transcript of a video: \n\n{text}\n\n"
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271 |
+
"Please provide a simplified explanation of the video for easy understanding."
|
272 |
+
)
|
273 |
+
|
274 |
+
response = ""
|
275 |
+
for chunk in AI71(AI71_API_KEY).chat.completions.create(
|
276 |
+
model="tiiuae/falcon-180b-chat",
|
277 |
+
messages=[
|
278 |
+
{"role": "system", "content": "You are a helpful assistant."},
|
279 |
+
{"role": "user", "content": prompt},
|
280 |
+
],
|
281 |
+
stream=True,
|
282 |
+
):
|
283 |
+
if chunk.choices[0].delta.content:
|
284 |
+
response += chunk.choices[0].delta.content
|
285 |
+
|
286 |
+
return response
|
287 |
+
|
288 |
+
|
289 |
+
def summarise_text(url):
|
290 |
+
extract_captions(url)
|
291 |
+
texts = extract_text_from_json(r'youtube_captions.json')
|
292 |
+
os.remove('youtube_captions.json')
|
293 |
+
|
294 |
+
first_half = (get_simplified_explanation(texts[:len(texts) // 2]))
|
295 |
+
second_half = (get_simplified_explanation(texts[len(texts) // 2:]))
|
296 |
+
return (first_half + second_half)
|
297 |
+
|
298 |
+
|
299 |
+
def generate_speech_from_pdf(content):
|
300 |
+
directory = 'speech'
|
301 |
+
keep_file = 'nil.txt'
|
302 |
+
|
303 |
+
# Check if the directory exists
|
304 |
+
if os.path.isdir(directory):
|
305 |
+
for filename in os.listdir(directory):
|
306 |
+
file_path = os.path.join(directory, filename)
|
307 |
+
|
308 |
+
# Check if the current file is not the one to keep and is a file
|
309 |
+
if filename != keep_file and os.path.isfile(file_path):
|
310 |
+
try:
|
311 |
+
os.remove(file_path) # Delete the file
|
312 |
+
print(f"Deleted {file_path}")
|
313 |
+
except Exception as e:
|
314 |
+
print(f"Error deleting {file_path}: {e}")
|
315 |
+
else:
|
316 |
+
print(f"Directory {directory} does not exist.")
|
317 |
+
|
318 |
+
speech = ''
|
319 |
+
for chunk in AI71(AI71_API_KEY).chat.completions.create(
|
320 |
+
model="tiiuae/falcon-180b-chat",
|
321 |
+
messages=[
|
322 |
+
{"role": "system", "content": "You are a summarising assistant."},
|
323 |
+
{"role": "user",
|
324 |
+
"content": f'''Summarise the given content for each chapter for 1 sentence.Content={content}'''},
|
325 |
+
],
|
326 |
+
stream=True,
|
327 |
+
):
|
328 |
+
if chunk.choices[0].delta.content:
|
329 |
+
speech += chunk.choices[0].delta.content
|
330 |
+
speech = speech[:-6].replace("###", '')
|
331 |
+
chapters = speech.split('\n\n')
|
332 |
+
pdf_audio(chapters[:4])
|
333 |
+
return
|
334 |
+
|
335 |
+
|
336 |
+
def pdf_audio(chapters):
|
337 |
+
for i in range(len(chapters)):
|
338 |
+
tts = gTTS(text=chapters[i], lang='en', slow=False)
|
339 |
+
tts.save(f'speech/chapter {i + 1}.mp3')
|
340 |
+
return
|
341 |
+
|
342 |
+
def content_translate(text):
|
343 |
+
|
344 |
+
|
345 |
+
translated_content = ''
|
346 |
+
for chunk in AI71(AI71_API_KEY).chat.completions.create(
|
347 |
+
model="tiiuae/falcon-180b-chat",
|
348 |
+
messages=[
|
349 |
+
{"role": "system", "content": "You are the best teaching assistant."},
|
350 |
+
{"role": "user", "content": f'''Translate the text to hindi. Text: {text}'''},
|
351 |
+
],
|
352 |
+
stream=True,
|
353 |
+
):
|
354 |
+
if chunk.choices[0].delta.content:
|
355 |
+
translated_content += chunk.choices[0].delta.content
|
356 |
+
return translated_content
|
teacher_function.py
ADDED
@@ -0,0 +1,168 @@
|
|
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|
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|
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|
|
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|
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|
|
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|
|
|
|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
from ai71 import AI71
|
2 |
+
from PyPDF2 import PdfReader
|
3 |
+
from pdf2image import convert_from_path
|
4 |
+
import cv2
|
5 |
+
import numpy as np
|
6 |
+
import pytesseract
|
7 |
+
import subprocess
|
8 |
+
from PIL import Image
|
9 |
+
AI71_API_KEY = "api71-api-652e5c6c-8edf-41d0-9c34-28522b07bef9"
|
10 |
+
|
11 |
+
subprocess.run(['apt-get','update'])
|
12 |
+
subprocess.run(['apt-get','install','-y','tesseract-ocr'])
|
13 |
+
|
14 |
+
def extract_text_from_pdf(pdf_file):
|
15 |
+
text = ""
|
16 |
+
reader = PdfReader(pdf_file)
|
17 |
+
for page in reader.pages:
|
18 |
+
text += page.extract_text()
|
19 |
+
return text
|
20 |
+
|
21 |
+
def generate_questions_from_text(text, no_of_questions, marks_per_part, no_parts):
|
22 |
+
ai71 = AI71(AI71_API_KEY)
|
23 |
+
messages = [
|
24 |
+
{"role": "system", "content": "You are a teaching assistant"},
|
25 |
+
{"role": "user",
|
26 |
+
"content": f"Give your own {no_of_questions} questions under each part for {no_parts} parts with {marks_per_part} marks for each part. Note that all questions must be from the topics of {text}"}
|
27 |
+
]
|
28 |
+
|
29 |
+
questions = []
|
30 |
+
for chunk in ai71.chat.completions.create(
|
31 |
+
model="tiiuae/falcon-180b-chat",
|
32 |
+
messages=messages,
|
33 |
+
stream=True,
|
34 |
+
):
|
35 |
+
if chunk.choices[0].delta.content:
|
36 |
+
questions.append(chunk.choices[0].delta.content)
|
37 |
+
|
38 |
+
return "".join(questions)
|
39 |
+
|
40 |
+
def extract_text_from_image(image_path):
|
41 |
+
# Load the image
|
42 |
+
img = cv2.imread(image_path)
|
43 |
+
|
44 |
+
# Ensure the image was loaded correctly
|
45 |
+
if img is None:
|
46 |
+
raise ValueError("Image not found or unable to load")
|
47 |
+
|
48 |
+
# Convert the image to RGB format
|
49 |
+
img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
|
50 |
+
|
51 |
+
# Extract text from the image
|
52 |
+
text = pytesseract.image_to_string(img_rgb)
|
53 |
+
|
54 |
+
return text
|
55 |
+
|
56 |
+
|
57 |
+
def evaluate(question, answer, max_marks):
|
58 |
+
prompt = f"""Questions: {question}
|
59 |
+
Answer: {answer}.
|
60 |
+
Evaluate answers strictly one by one(if there are multiple) for each question and assign marks out of {max_marks} based on below guidelines.
|
61 |
+
guidelines:
|
62 |
+
- If the answer is wrong or incorrect or irrelevent to topic, give 0 marks.
|
63 |
+
|
64 |
+
- If the answer is somewhat accurate, give total marks minus 2, and so on.
|
65 |
+
- If the answer is very accurate and complete, give total marks.
|
66 |
+
- If the answer is good but not completely accurate, give total marks minus 1.
|
67 |
+
|
68 |
+
|
69 |
+
Note:Provide only marks for each answers. dont provide anything other than that.
|
70 |
+
Format:
|
71 |
+
1.Question no: Marks,etc"""
|
72 |
+
|
73 |
+
messages = [
|
74 |
+
{"role": "system", "content": "You are a strict answer evaluator. "},
|
75 |
+
{"role": "user", "content": prompt}
|
76 |
+
]
|
77 |
+
|
78 |
+
response_content = ""
|
79 |
+
for chunk in AI71(AI71_API_KEY).chat.completions.create(
|
80 |
+
model="tiiuae/falcon-180b-chat",
|
81 |
+
messages=messages,
|
82 |
+
stream=True
|
83 |
+
):
|
84 |
+
if chunk.choices[0].delta.content:
|
85 |
+
response_content += chunk.choices[0].delta.content
|
86 |
+
print(response_content)
|
87 |
+
|
88 |
+
return response_content
|
89 |
+
|
90 |
+
def generate_student_report(name, age, cgpa, course, assigned_test, ai_test, interests, difficulty, courses_taken):
|
91 |
+
prompt = f"""
|
92 |
+
Name: {name}
|
93 |
+
Age: {age}
|
94 |
+
CGPA: {cgpa}
|
95 |
+
Course: {course}
|
96 |
+
Assigned Test Score: {assigned_test}
|
97 |
+
AI generated Test Score: {ai_test}
|
98 |
+
Interests: {interests}
|
99 |
+
Difficulty in: {difficulty}
|
100 |
+
Courses Taken: {courses_taken}
|
101 |
+
Use the above student data to generate a neat personalized report and suggested teaching methods."""
|
102 |
+
|
103 |
+
client = AI71(AI71_API_KEY)
|
104 |
+
|
105 |
+
response = client.chat.completions.create(
|
106 |
+
model="tiiuae/falcon-180B-chat",
|
107 |
+
messages=[
|
108 |
+
{"role": "system", "content": "You are a student report generator."},
|
109 |
+
{"role": "user", "content": prompt}
|
110 |
+
]
|
111 |
+
)
|
112 |
+
|
113 |
+
report = response.choices[0].message.content if response.choices and response.choices[
|
114 |
+
0].message else "No report generated."
|
115 |
+
print(report)
|
116 |
+
|
117 |
+
return report
|
118 |
+
def generate_timetable_module(data,hours_per_day,days_per_week,semester_end_date,subjects):
|
119 |
+
response = AI71(AI71_API_KEY).chat.completions.create(
|
120 |
+
model="tiiuae/falcon-180B-chat",
|
121 |
+
messages=[
|
122 |
+
{"role": "system", "content": "You are a helpful assistant."},
|
123 |
+
{"role": "user", "content": f"Create a timetable starting from Monday based on the following inputs:\n"
|
124 |
+
f"- Number of hours per day: {hours_per_day}\n"
|
125 |
+
f"- Number of days per week: {days_per_week}\n"
|
126 |
+
f"- Semester end date: {semester_end_date}\n"
|
127 |
+
f"- Subjects: {', '.join(subjects)}\n"}
|
128 |
+
]
|
129 |
+
)
|
130 |
+
|
131 |
+
# Access the response content correctly
|
132 |
+
return( response.choices[0].message.content if response.choices and response.choices[0].message else "No timetable generated.")
|
133 |
+
|
134 |
+
def cluster_topics(academic_topics):
|
135 |
+
prompt = (
|
136 |
+
"Please cluster the following academic topics into their respective subjects such as Mathematics, Physics, etc.: "
|
137 |
+
+ ", ".join(academic_topics))
|
138 |
+
response = ""
|
139 |
+
for chunk in AI71(AI71_API_KEY).chat.completions.create(
|
140 |
+
model="tiiuae/falcon-180b-chat",
|
141 |
+
messages=[
|
142 |
+
{"role": "system", "content": "You are a helpful assistant."},
|
143 |
+
{"role": "user", "content": prompt},
|
144 |
+
],
|
145 |
+
stream=True,
|
146 |
+
):
|
147 |
+
if chunk.choices[0].delta.content:
|
148 |
+
response += chunk.choices[0].delta.content
|
149 |
+
return response
|
150 |
+
|
151 |
+
def generate_timetable_weak(clustered_subjects, hours_per_day):
|
152 |
+
prompt = (
|
153 |
+
f"Using the following subjects and topics:\n{clustered_subjects}\n"
|
154 |
+
f"Generate a special class timetable for {hours_per_day} hours per day.\n"
|
155 |
+
f"Also provide reference books and methods to teach the slow learners for each subject"
|
156 |
+
)
|
157 |
+
response = ""
|
158 |
+
for chunk in AI71(AI71_API_KEY).chat.completions.create(
|
159 |
+
model="tiiuae/falcon-180b-chat",
|
160 |
+
messages=[
|
161 |
+
{"role": "system", "content": "You are a helpful assistant."},
|
162 |
+
{"role": "user", "content": prompt},
|
163 |
+
],
|
164 |
+
stream=True,
|
165 |
+
):
|
166 |
+
if chunk.choices[0].delta.content:
|
167 |
+
response += chunk.choices[0].delta.content
|
168 |
+
return response
|