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requirements.txt

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+Flask==3.0.2
+Werkzeug==3.0.1
+selenium==4.18.1
+torch==1.10.0
+torchvision==0.11.1
+easyocr==1.4
+youtube-transcript-api==0.6.2
+pypdf==4.1.0
+Pillow
+PyPDF2==3.0.1
+pdf2image==1.17.0
+opencv-python-headless==4.8.1.78
+numpy==1.26.3
+pytesseract==0.3.10
+joblib==1.3.2
+requests==2.32.0
+ai71==0.0.18
+setuptools==69.0.3
+gtts

student_functions.py

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+from gtts import gTTS
+import shutil
+from selenium import webdriver
+from selenium.webdriver.common.by import By
+from selenium.webdriver.common.keys import Keys
+from selenium.webdriver.support.ui import WebDriverWait
+from selenium.webdriver.support import expected_conditions as EC
+import json
+from youtube_transcript_api import YouTubeTranscriptApi
+from youtube_transcript_api.formatters import JSONFormatter
+from urllib.parse import urlparse, parse_qs
+from pypdf import PdfReader
+from ai71 import AI71
+import os
+
+AI71_API_KEY = "api71-api-652e5c6c-8edf-41d0-9c34-28522b07bef9"
+
+
+def extract_text_from_pdf_s(pdf_path):
+    text = ""
+    reader = PdfReader(pdf_path)
+    for page in reader.pages:
+        text += page.extract_text() + "\n"
+    generate_speech_from_pdf(text[:len(text) // 2])
+   
+    return text
+
+
+def generate_response_from_pdf(query, pdf_text):
+    response = ''
+    for chunk in AI71(AI71_API_KEY).chat.completions.create(
+            model="tiiuae/falcon-180b-chat",
+            messages=[
+                {"role": "system", "content": "You are a pdf questioning assistant."},
+                {"role": "user",
+                 "content": f'''Answer the querry based on the given content.Content:{pdf_text},query:{query}'''},
+            ],
+            stream=True,
+    ):
+        if chunk.choices[0].delta.content:
+            response += chunk.choices[0].delta.content
+    return response.replace("###", '')
+
+
+def generate_quiz(subject, topic, count, difficult):
+    quiz_output = ""
+
+    for chunk in AI71(AI71_API_KEY).chat.completions.create(
+            model="tiiuae/falcon-180b-chat",
+            messages=[
+                {"role": "system", "content": "You are a teaching assistant."},
+                {"role": "user",
+                 "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:
+Question: [Question text] [specific concept in a question] 
+<<o>> [Option1] 
+<<o>> [Option2] 
+<<o>> [Option3] 
+<<o>> [Option4], 
+Answer: [Option number]'''},
+            ],
+            stream=True,
+    ):
+        if chunk.choices[0].delta.content:
+            quiz_output += chunk.choices[0].delta.content
+    print("Quiz generated")
+    return quiz_output
+
+
+
+def generate_ai_response(query):
+    ai_response = ''
+    for chunk in AI71(AI71_API_KEY).chat.completions.create(
+            model="tiiuae/falcon-180b-chat",
+            messages=[
+                {"role": "system", "content": "You are a teaching assistant."},
+                {"role": "user", "content": f'Assist the user clearly for his questions: {query}.'},
+            ],
+            stream=True,
+    ):
+        if chunk.choices[0].delta.content:
+            ai_response += chunk.choices[0].delta.content
+    return ai_response.replace('###', '')
+
+
+def generate_project_idea(subject, topic, overview):
+    string = ''
+    for chunk in AI71(AI71_API_KEY).chat.completions.create(
+            model="tiiuae/falcon-180b-chat",
+            messages=[
+                {"role": "system", "content": "You are a project building assistant."},
+                {"role": "user",
+                 "content": f'''Give the different project ideas to build project in {subject} specifically in {topic} for school students. {overview}.'''},
+            ],
+            stream=True,
+    ):
+        if chunk.choices[0].delta.content:
+            string += chunk.choices[0].delta.content
+    return string
+
+
+def generate_project_idea_questions(project_idea, query):
+    project_idea_answer = ''
+    for chunk in AI71(AI71_API_KEY).chat.completions.create(
+            model="tiiuae/falcon-180b-chat",
+            messages=[
+                {"role": "system", "content": "You are a project building assistant."},
+                {"role": "user",
+                 "content": f'''Assist me clearly for the following question for the given idea. Idea: {project_idea}. Question: {query}'''},
+            ],
+            stream=True,
+    ):
+        if chunk.choices[0].delta.content:
+            project_idea_answer += chunk.choices[0].delta.content
+    return project_idea_answer
+
+
+def generate_step_by_step_explanation(query):
+    explanation = ''
+    for chunk in AI71(AI71_API_KEY).chat.completions.create(
+            model="tiiuae/falcon-180b-chat",
+            messages=[
+                {"role": "system", "content": "You are the best teaching assistant."},
+                {"role": "user",
+                 "content": f'''Provide me the clear step by step explanation answer for the following question. Question: {query}'''},
+            ],
+            stream=True,
+    ):
+        if chunk.choices[0].delta.content:
+            explanation += chunk.choices[0].delta.content
+    return explanation.replace('###', '')
+
+
+def study_plan(subjects, hours, arealag, goal):
+    plan = ''
+    for chunk in AI71(AI71_API_KEY).chat.completions.create(
+            model="tiiuae/falcon-180b-chat",
+            messages=[
+                {"role": "system", "content": "You are the best teaching assistant."},
+                {"role": "user",
+                 "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'''},
+            ],
+            stream=True,
+    ):
+        if chunk.choices[0].delta.content:
+            plan += chunk.choices[0].delta.content
+    return plan.replace('\n', '<br>')
+
+
+class ConversationBufferMemory:
+    def __init__(self, memory_key="chat_history"):
+        self.memory_key = memory_key
+        self.buffer = []
+
+    def add_to_memory(self, interaction):
+        self.buffer.append(interaction)
+
+    def get_memory(self):
+        return "\n".join([f"Human: {entry['user']}\nAssistant: {entry['assistant']}" for entry in self.buffer])
+
+
+def spk_msg(user_input, memory):
+    chat_history = memory.get_memory()
+    msg = ''
+
+    # Construct the message for the API request
+    messages = [
+        {"role": "system",
+         "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"},
+        {"role": "user",
+         "content": f"Previous conversation:\n{chat_history}\n\nNew human question: {user_input}\nResponse:"}
+    ]
+
+    try:
+        for chunk in AI71(AI71_API_KEY).chat.completions.create(
+                model="tiiuae/falcon-180b-chat",
+                messages=messages,
+                stream=True,
+        ):
+            if chunk.choices[0].delta.content:
+                msg += chunk.choices[0].delta.content
+    except Exception as e:
+        print(f"An error occurred: {e}")
+
+    return msg
+
+
+def get_first_youtube_video_link(query):
+    url = f'https://www.youtube.com/results?search_query={query}'
+
+    # Navigate to the URL
+    driver.get(url)
+
+    # Find the first video link
+    try:
+        # Find the first video element
+        first_video_element = driver.find_element(By.XPATH, '//a[@id="video-title"]')
+        video_link = first_video_element.get_attribute('href')
+        print(video_link)
+    finally:
+        # Close the WebDriver
+        driver.quit()
+
+
+
+def content_translate(text):
+    translated_content = ''
+    for chunk in AI71(AI71_API_KEY).chat.completions.create(
+            model="tiiuae/falcon-180b-chat",
+            messages=[
+                {"role": "system", "content": "You are the best teaching assistant."},
+                {"role": "user", "content": f'''Translate the text to hindi. Text: {text}'''},
+            ],
+            stream=True,
+    ):
+        if chunk.choices[0].delta.content:
+            translated_content += chunk.choices[0].delta.content
+    return translated_content
+
+
+def get_video_id(url):
+    """
+    Extract the video ID from a YouTube URL.
+    """
+    parsed_url = urlparse(url)
+    if parsed_url.hostname == 'www.youtube.com' or parsed_url.hostname == 'youtube.com':
+        video_id = parse_qs(parsed_url.query).get('v')
+        if video_id:
+            return video_id[0]
+    elif parsed_url.hostname == 'youtu.be':
+        return parsed_url.path[1:]
+    return None
+
+
+def extract_captions(video_url):
+    """
+    Extract captions from a YouTube video URL.
+    """
+    video_id = get_video_id(video_url)
+    if not video_id:
+        print("Invalid YouTube URL.")
+        return
+
+    try:
+        transcript = YouTubeTranscriptApi.get_transcript(video_id)
+        formatter = JSONFormatter()
+        formatted_transcript = formatter.format_transcript(transcript)
+
+        # Save captions to a file
+        with open(f'youtube_captions.json', 'w') as file:
+            file.write(formatted_transcript)
+
+        print("Captions have been extracted and saved as JSON.")
+
+    except Exception as e:
+        print(f"An error occurred: {e}")
+
+
+def extract_text_from_json(filename):
+    # Open and read the JSON file
+    with open(filename, 'r') as file:
+        data = json.load(file)
+
+    # Extract and print the text fields
+    texts = [entry['text'] for entry in data]
+    return texts
+
+
+def get_simplified_explanation(text):
+    prompt = (
+        f"The following is a transcript of a video: \n\n{text}\n\n"
+        "Please provide a simplified explanation of the video for easy understanding."
+    )
+
+    response = ""
+    for chunk in AI71(AI71_API_KEY).chat.completions.create(
+            model="tiiuae/falcon-180b-chat",
+            messages=[
+                {"role": "system", "content": "You are a helpful assistant."},
+                {"role": "user", "content": prompt},
+            ],
+            stream=True,
+    ):
+        if chunk.choices[0].delta.content:
+            response += chunk.choices[0].delta.content
+
+    return response
+
+
+def summarise_text(url):
+    extract_captions(url)
+    texts = extract_text_from_json(r'youtube_captions.json')
+    os.remove('youtube_captions.json')
+
+    first_half = (get_simplified_explanation(texts[:len(texts) // 2]))
+    second_half = (get_simplified_explanation(texts[len(texts) // 2:]))
+    return (first_half + second_half)
+
+
+def generate_speech_from_pdf(content):
+    directory = 'speech'
+    keep_file = 'nil.txt'
+    
+    # Check if the directory exists
+    if os.path.isdir(directory):
+        for filename in os.listdir(directory):
+            file_path = os.path.join(directory, filename)
+            
+            # Check if the current file is not the one to keep and is a file
+            if filename != keep_file and os.path.isfile(file_path):
+                try:
+                    os.remove(file_path)  # Delete the file
+                    print(f"Deleted {file_path}")
+                except Exception as e:
+                    print(f"Error deleting {file_path}: {e}")
+    else:
+        print(f"Directory {directory} does not exist.")
+
+    speech = ''
+    for chunk in AI71(AI71_API_KEY).chat.completions.create(
+            model="tiiuae/falcon-180b-chat",
+            messages=[
+                {"role": "system", "content": "You are a summarising assistant."},
+                {"role": "user",
+                 "content": f'''Summarise the given content for each chapter for 1 sentence.Content={content}'''},
+            ],
+            stream=True,
+    ):
+        if chunk.choices[0].delta.content:
+            speech += chunk.choices[0].delta.content
+    speech = speech[:-6].replace("###", '')
+    chapters = speech.split('\n\n')
+    pdf_audio(chapters[:4])
+    return
+
+
+def pdf_audio(chapters):
+    for i in range(len(chapters)):
+        tts = gTTS(text=chapters[i], lang='en', slow=False)
+        tts.save(f'speech/chapter {i + 1}.mp3')
+    return
+
+def content_translate(text):
+
+
+    translated_content = ''
+    for chunk in AI71(AI71_API_KEY).chat.completions.create(
+        model="tiiuae/falcon-180b-chat",
+        messages=[
+            {"role": "system", "content": "You are the best teaching assistant."},
+            {"role": "user", "content": f'''Translate the text to hindi. Text: {text}'''},
+        ],
+        stream=True,
+    ):
+        if chunk.choices[0].delta.content:
+            translated_content += chunk.choices[0].delta.content
+    return translated_content

teacher_function.py

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+from ai71 import AI71
+from PyPDF2 import PdfReader
+from pdf2image import convert_from_path
+import cv2
+import numpy as np
+import pytesseract
+import subprocess
+from PIL import Image
+AI71_API_KEY = "api71-api-652e5c6c-8edf-41d0-9c34-28522b07bef9"
+
+subprocess.run(['apt-get','update'])
+subprocess.run(['apt-get','install','-y','tesseract-ocr'])
+
+def extract_text_from_pdf(pdf_file):
+    text = ""
+    reader = PdfReader(pdf_file)
+    for page in reader.pages:
+        text += page.extract_text()
+    return text
+
+def generate_questions_from_text(text, no_of_questions, marks_per_part, no_parts):
+    ai71 = AI71(AI71_API_KEY)
+    messages = [
+        {"role": "system", "content": "You are a teaching assistant"},
+        {"role": "user",
+         "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}"}
+    ]
+
+    questions = []
+    for chunk in ai71.chat.completions.create(
+            model="tiiuae/falcon-180b-chat",
+            messages=messages,
+            stream=True,
+    ):
+        if chunk.choices[0].delta.content:
+            questions.append(chunk.choices[0].delta.content)
+
+    return "".join(questions)
+
+def extract_text_from_image(image_path):
+    # Load the image
+    img = cv2.imread(image_path)
+
+    # Ensure the image was loaded correctly
+    if img is None:
+        raise ValueError("Image not found or unable to load")
+
+    # Convert the image to RGB format
+    img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+
+    # Extract text from the image
+    text = pytesseract.image_to_string(img_rgb)
+    
+    return text
+
+
+def evaluate(question, answer, max_marks):
+    prompt = f"""Questions: {question}
+    Answer: {answer}.
+    Evaluate answers strictly one by one(if there are multiple) for each question and assign marks out of {max_marks} based on below guidelines.
+guidelines:
+- If the answer is wrong or incorrect or irrelevent to topic, give 0 marks.
+
+- If the answer is somewhat accurate, give total marks minus 2, and so on.
+- If the answer is very accurate and complete, give total marks.
+- If the answer is good but not completely accurate, give total marks minus 1.
+
+
+Note:Provide only marks for each answers. dont provide anything other than that.
+Format:
+1.Question no: Marks,etc"""
+
+    messages = [
+        {"role": "system", "content": "You are a strict answer evaluator. "},
+        {"role": "user", "content": prompt}
+    ]
+
+    response_content = ""
+    for chunk in  AI71(AI71_API_KEY).chat.completions.create(
+            model="tiiuae/falcon-180b-chat",
+            messages=messages,
+            stream=True
+    ):
+        if chunk.choices[0].delta.content:
+            response_content += chunk.choices[0].delta.content
+    print(response_content)
+
+    return response_content
+
+def generate_student_report(name, age, cgpa, course, assigned_test, ai_test, interests, difficulty, courses_taken):
+    prompt = f"""
+    Name: {name}
+    Age: {age}
+    CGPA: {cgpa}
+    Course: {course}
+    Assigned Test Score: {assigned_test}
+    AI generated Test Score: {ai_test}
+    Interests: {interests}
+    Difficulty in: {difficulty}
+    Courses Taken: {courses_taken}
+    Use the above student data to generate a neat personalized report and suggested teaching methods."""
+
+    client = AI71(AI71_API_KEY)
+
+    response = client.chat.completions.create(
+        model="tiiuae/falcon-180B-chat",
+        messages=[
+            {"role": "system", "content": "You are a student report generator."},
+            {"role": "user", "content": prompt}
+        ]
+    )
+
+    report = response.choices[0].message.content if response.choices and response.choices[
+        0].message else "No report generated."
+    print(report)
+
+    return report
+def generate_timetable_module(data,hours_per_day,days_per_week,semester_end_date,subjects):
+    response = AI71(AI71_API_KEY).chat.completions.create(
+            model="tiiuae/falcon-180B-chat",
+            messages=[
+                {"role": "system", "content": "You are a helpful assistant."},
+                {"role": "user", "content": f"Create a timetable starting from Monday based on the following inputs:\n"
+                                            f"- Number of hours per day: {hours_per_day}\n"
+                                            f"- Number of days per week: {days_per_week}\n"
+                                            f"- Semester end date: {semester_end_date}\n"
+                                            f"- Subjects: {', '.join(subjects)}\n"}
+            ]
+        )
+
+        # Access the response content correctly
+    return( response.choices[0].message.content if response.choices and response.choices[0].message else "No timetable generated.")
+
+def cluster_topics(academic_topics):
+    prompt = (
+            "Please cluster the following academic topics into their respective subjects such as Mathematics, Physics, etc.: "
+            + ", ".join(academic_topics))
+    response = ""
+    for chunk in AI71(AI71_API_KEY).chat.completions.create(
+            model="tiiuae/falcon-180b-chat",
+            messages=[
+                {"role": "system", "content": "You are a helpful assistant."},
+                {"role": "user", "content": prompt},
+            ],
+            stream=True,
+    ):
+        if chunk.choices[0].delta.content:
+            response += chunk.choices[0].delta.content
+    return response
+
+def generate_timetable_weak(clustered_subjects, hours_per_day):
+    prompt = (
+        f"Using the following subjects and topics:\n{clustered_subjects}\n"
+        f"Generate a special class timetable for {hours_per_day} hours per day.\n"
+        f"Also provide reference books and methods to teach the slow learners for each subject"
+    )
+    response = ""
+    for chunk in AI71(AI71_API_KEY).chat.completions.create(
+            model="tiiuae/falcon-180b-chat",
+            messages=[
+                {"role": "system", "content": "You are a helpful assistant."},
+                {"role": "user", "content": prompt},
+            ],
+            stream=True,
+    ):
+        if chunk.choices[0].delta.content:
+            response += chunk.choices[0].delta.content
+    return response