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| # import subprocess | |
| # subprocess.check_call(["pip", "install", "transformers==4.34.0"]) | |
| # subprocess.check_call(["pip", "install", "torch>=1.7.1"]) | |
| # subprocess.check_call(["pip", "install", "youtube_transcript_api>=0.6.3"]) | |
| # subprocess.check_call(["pip", "install", "pytube"]) | |
| # subprocess.check_call(["pip", "install", "huggingface_hub>=0.19.0"]) | |
| # subprocess.check_call(["pip", "install", "PyPDF2>=3.0.1"]) | |
| # subprocess.check_call(["pip", "install", "google-generativeai"]) | |
| # subprocess.check_call(["pip", "install", "textblob>=0.17.1"]) | |
| # subprocess.check_call(["pip", "install", "python-dotenv>=1.0.0"]) | |
| # subprocess.check_call(["pip", "install", "genai"]) | |
| # subprocess.check_call(["pip", "install", "google-cloud-aiplatform==1.34.0"]) | |
| # subprocess.check_call(["pip", "install", "google-api-python-client>=2.0.0"]) | |
| # import transformers | |
| # import torch | |
| # import os | |
| # import youtube_transcript_api | |
| # import pytube | |
| # import gradio | |
| # import PyPDF2 | |
| # import pathlib | |
| # import pandas | |
| # import numpy | |
| # import textblob | |
| # import gradio as gr | |
| # from youtube_transcript_api import YouTubeTranscriptApi | |
| # import google.generativeai as genai | |
| # from googleapiclient.discovery import build | |
| # import requests | |
| # from textblob import TextBlob | |
| # import re | |
| # #from google.cloud import generativeai | |
| # from googleapiclient.discovery import build | |
| # from huggingface_hub import login | |
| # from youtube_transcript_api import YouTubeTranscriptApi, TranscriptsDisabled, NoTranscriptFound | |
| # def install_missing_packages(): | |
| # required_packages = { | |
| # "torch":">=1.11.0", | |
| # "transformers":">=4.34.0", | |
| # "youtube_transcript_api" :">=0.6.3" , | |
| # "pytube":None, | |
| # "huggingface_hub": ">=0.19.0", | |
| # "PyPDF2": ">=3.0.1", | |
| # "textblob":">=0.17.1", | |
| # "python-dotenv":">=1.0.0", | |
| # "genai":None, | |
| # "google-generativeai": None, | |
| # "google-cloud-aiplatform":"==1.34.0", | |
| # "google-api-python-client": ">=2.0.0" | |
| # } | |
| # for package, version in required_packages.items(): | |
| # try: | |
| # __import__(package) | |
| # except ImportError: | |
| # package_name = f"{package}{version}" if version else package | |
| # subprocess.check_call(["pip", "install", package_name]) | |
| # install_missing_packages() | |
| # # Configuration | |
| # hf_token = os.getenv("HF_TOKEN") | |
| # if hf_token: | |
| # login(hf_token) | |
| # else: | |
| # raise ValueError("HF_TOKEN environment variable not set.") | |
| # # Configuration | |
| # USER_CREDENTIALS = { | |
| # "admin": "password123", | |
| # "teacher": "teach2024", | |
| # "student": "learn2024" | |
| # } | |
| # import os | |
| # from youtube_transcript_api import YouTubeTranscriptApi, TranscriptsDisabled, NoTranscriptFound | |
| # # Use environment variables | |
| # GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY") | |
| # YOUTUBE_API_KEY = os.getenv("YOUTUBE_API_KEY") | |
| # if not GOOGLE_API_KEY or not YOUTUBE_API_KEY: | |
| # raise ValueError("Please set GOOGLE_API_KEY and YOUTUBE_API_KEY environment variables") | |
| # genai.configure(api_key=GOOGLE_API_KEY) | |
| # # Database | |
| # students_data = [ | |
| # (1, "Alice", "A", "Computer Science"), | |
| # (2, "Aliaa", "B", "Mathematics"), | |
| # (3, "Charlie", "A", "Machine Learning"), | |
| # (4, "Daan", "A", "Physics"), | |
| # (5, "Jhon", "C", "Math"), | |
| # (6, "Emma", "A+", "Computer Science") | |
| # ] | |
| # teachers_data = [ | |
| # (1, "Dr. Smith", "Math", "MS Mathematics"), | |
| # (2, "Ms. Johnson", "Science", "MSc Physics"), | |
| # (3, "Ms. Jack", "Artificial Intelligence Engineer", "MSc AI"), | |
| # (4, "Ms. Evelyn", "Computer Science", "MSc Computer Science"), | |
| # ] | |
| # courses_data = [ | |
| # (1, "Algebra", "Dr. Smith", "Advanced"), | |
| # (2, "Biology", "Ms. Mia", "Intermediate"), | |
| # (3, "Machine Learning", "Ms. Jack", "Intermediate"), | |
| # (4, "Computer Science", "Ms. Evelyn", "Intermediate"), | |
| # (5, "Mathematics", "Ms. Smith", "Intermediate") | |
| # ] | |
| # def sanitize_text(text): | |
| # """Remove invalid Unicode characters.""" | |
| # return text.encode("utf-8", "replace").decode("utf-8") | |
| # def extract_video_id(url): | |
| # if not url: | |
| # return None | |
| # patterns = [ | |
| # r'(?:v=|\/videos\/|embed\/|youtu.be\/|\/v\/|\/e\/|watch\?v=|\/watch\?v=)([^#\&\?]*)' | |
| # ] | |
| # for pattern in patterns: | |
| # match = re.search(pattern, url) | |
| # if match: | |
| # return match.group(1) | |
| # return None | |
| # from textblob import TextBlob | |
| # from youtube_transcript_api import YouTubeTranscriptApi, TranscriptsDisabled, NoTranscriptFound | |
| # import re | |
| # from collections import Counter | |
| # from googleapiclient.discovery import build | |
| # def extract_video_id(url): | |
| # match = re.search(r"(?:v=|\/)([0-9A-Za-z_-]{11})", url) | |
| # return match.group(1) if match else None | |
| # def get_video_metadata(video_id): | |
| # try: | |
| # youtube = build("youtube", "v3", developerKey=YOUTUBE_API_KEY) | |
| # request = youtube.videos().list(part="snippet", id=video_id) | |
| # response = request.execute() | |
| # if "items" in response and len(response["items"]) > 0: | |
| # snippet = response["items"][0]["snippet"] | |
| # return { | |
| # "title": snippet.get("title", "No title available"), | |
| # "description": snippet.get("description", "No description available"), | |
| # } | |
| # return {} | |
| # except Exception as e: | |
| # return {"title": "Error fetching metadata", "description": str(e)} | |
| # def clean_text_for_analysis(text): | |
| # return " ".join(text.split()) | |
| # def extract_subtitle_info(text): | |
| # try: | |
| # sentences = text.split(". ") | |
| # words = text.split() | |
| # common_words = Counter(words).most_common(10) | |
| # key_topics = ", ".join([word for word, count in common_words]) | |
| # info = f"Key topics discussed: {key_topics}. \nNumber of sentences: {len(sentences)}. \nTotal words: {len(words)}." | |
| # return info | |
| # except Exception as e: | |
| # return f"Error extracting subtitle information: {str(e)}" | |
| # def get_recommendations(keywords, max_results=5): | |
| # if not keywords: | |
| # return "Please provide search keywords" | |
| # try: | |
| # response = requests.get( | |
| # "https://www.googleapis.com/youtube/v3/search", | |
| # params={ | |
| # "part": "snippet", | |
| # "q": f"educational {keywords}", | |
| # "type": "video", | |
| # "maxResults": max_results, | |
| # "relevanceLanguage": "en", | |
| # "key": YOUTUBE_API_KEY | |
| # } | |
| # ).json() | |
| # results = [] | |
| # for item in response.get("items", []): | |
| # title = item["snippet"]["title"] | |
| # channel = item["snippet"]["channelTitle"] | |
| # video_id = item["id"]["videoId"] | |
| # results.append(f"📺 {title}\n👤 {channel}\n🔗 https://youtube.com/watch?v={video_id}\n") | |
| # return "\n".join(results) if results else "No recommendations found" | |
| # except Exception as e: | |
| # return f"Error: {str(e)}" | |
| # def process_youtube_video(url, keywords): | |
| # try: | |
| # thumbnail = None | |
| # summary = "No transcript available" | |
| # sentiment_label = "N/A" | |
| # recommendations = "" | |
| # video_id = extract_video_id(url) | |
| # if not video_id: | |
| # return None, "Invalid YouTube URL", "N/A", "", "" | |
| # thumbnail = f"https://img.youtube.com/vi/{video_id}/maxresdefault.jpg" | |
| # try: | |
| # transcript_list = YouTubeTranscriptApi.list_transcripts(video_id) | |
| # transcript = None | |
| # try: | |
| # transcript = transcript_list.find_transcript(['en']) | |
| # except: | |
| # transcript = transcript_list.find_generated_transcript(['en']) | |
| # text = " ".join([t['text'] for t in transcript.fetch()]) | |
| # if not text.strip(): | |
| # raise ValueError("Transcript is empty") | |
| # cleaned_text = clean_text_for_analysis(text) | |
| # sentiment = TextBlob(cleaned_text).sentiment | |
| # sentiment_label = f"{'Positive' if sentiment.polarity > 0 else 'Negative' if sentiment.polarity < 0 else 'Neutral'} ({sentiment.polarity:.2f})" | |
| # summary = f"Summary: {cleaned_text[:400]}..." | |
| # except (TranscriptsDisabled, NoTranscriptFound): | |
| # metadata = get_video_metadata(video_id) | |
| # summary = metadata.get("description", "No subtitles available") | |
| # sentiment_label = "N/A" | |
| # if keywords.strip(): | |
| # recommendations = get_recommendations(keywords) | |
| # return thumbnail, summary, sentiment_label, recommendations | |
| # except Exception as e: | |
| # return None, f"Error: {str(e)}", "N/A", "" | |
| # # def get_recommendations(keywords, max_results=5): | |
| # # if not keywords: | |
| # # return "Please provide search keywords" | |
| # # try: | |
| # # response = requests.get( | |
| # # "https://www.googleapis.com/youtube/v3/search", | |
| # # params={ | |
| # # "part": "snippet", | |
| # # "q": f"educational {keywords}", | |
| # # "type": "video", | |
| # # "maxResults": max_results, | |
| # # "relevanceLanguage": "en", | |
| # # "key": YOUTUBE_API_KEY | |
| # # } | |
| # # ).json() | |
| # # results = [] | |
| # # for item in response.get("items", []): | |
| # # title = item["snippet"]["title"] | |
| # # channel = item["snippet"]["channelTitle"] | |
| # # video_id = item["id"]["videoId"] | |
| # # results.append(f"📺 {title}\n👤 {channel}\n🔗 https://youtube.com/watch?v={video_id}\n") | |
| # # return "\n".join(results) if results else "No recommendations found" | |
| # # except Exception as e: | |
| # # return f"Error: {str(e)}" | |
| # # Gradio Interface | |
| # with gr.Blocks(theme=gr.themes.Soft()) as app: | |
| # # Login Page | |
| # with gr.Group() as login_page: | |
| # gr.Markdown("# 🎓 Educational Learning Management System") | |
| # username = gr.Textbox(label="Username") | |
| # password = gr.Textbox(label="Password", type="password") | |
| # login_btn = gr.Button("Login", variant="primary") | |
| # login_msg = gr.Markdown() | |
| # # Main Interface | |
| # with gr.Group(visible=False) as main_page: | |
| # with gr.Row(): | |
| # with gr.Column(scale=1): | |
| # gr.Markdown("### 📋 Navigation") | |
| # nav_dashboard = gr.Button("📊 Dashboard", variant="primary") | |
| # nav_students = gr.Button("👥 Students") | |
| # nav_teachers = gr.Button("👨🏫 Teachers") | |
| # nav_courses = gr.Button("📚 Courses") | |
| # nav_youtube = gr.Button("🎥 YouTube Tool") | |
| # logout_btn = gr.Button("🚪 Logout", variant="stop") | |
| # with gr.Column(scale=3): | |
| # # Dashboard Content | |
| # dashboard_page = gr.Group() | |
| # with dashboard_page: | |
| # gr.Markdown("## 📊 Dashboard") | |
| # gr.Markdown(f""" | |
| # ### System Overview | |
| # - 👥 Total Students: {len(students_data)} | |
| # - 👨🏫 Total Teachers: {len(teachers_data)} | |
| # - 📚 Total Courses: {len(courses_data)} | |
| # ### Quick Actions | |
| # - View student performance | |
| # - Access course materials | |
| # - Generate learning insights | |
| # """) | |
| # # Students Content | |
| # students_page = gr.Group(visible=False) | |
| # with students_page: | |
| # gr.Markdown("## 👥 Students") | |
| # gr.DataFrame( | |
| # value=students_data, | |
| # headers=["ID", "Name", "Grade", "Program"] | |
| # ) | |
| # # Teachers Content | |
| # teachers_page = gr.Group(visible=False) | |
| # with teachers_page: | |
| # gr.Markdown("## 👨🏫 Teachers") | |
| # gr.DataFrame( | |
| # value=teachers_data, | |
| # headers=["ID", "Name", "Subject", "Qualification"] | |
| # ) | |
| # # Courses Content | |
| # courses_page = gr.Group(visible=False) | |
| # with courses_page: | |
| # gr.Markdown("## 📚 Courses") | |
| # gr.DataFrame( | |
| # value=courses_data, | |
| # headers=["ID", "Name", "Instructor", "Level"] | |
| # ) | |
| # # YouTube Tool Content | |
| # youtube_page = gr.Group(visible=False) | |
| # with youtube_page: | |
| # gr.Markdown("## Agent for YouTube Content Exploration") | |
| # with gr.Row(): | |
| # with gr.Column(scale=2): | |
| # video_url = gr.Textbox( | |
| # label="YouTube URL", | |
| # placeholder="https://youtube.com/watch?v=..." | |
| # ) | |
| # keywords = gr.Textbox( | |
| # label="Keywords for Recommendations", | |
| # placeholder="e.g., python programming, machine learning" | |
| # ) | |
| # analyze_btn = gr.Button("🔍 Analyze Video", variant="primary") | |
| # with gr.Column(scale=1): | |
| # video_thumbnail = gr.Image(label="Video Preview") | |
| # with gr.Row(): | |
| # with gr.Column(): | |
| # summary = gr.Textbox(label="📝 Summary", lines=8) | |
| # sentiment = gr.Textbox(label="😊 Content Sentiment") | |
| # with gr.Column(): | |
| # recommendations = gr.Textbox(label="🎯 Related Videos", lines=10) | |
| # def login_check(user, pwd): | |
| # if USER_CREDENTIALS.get(user) == pwd: | |
| # return { | |
| # login_page: gr.update(visible=False), | |
| # main_page: gr.update(visible=True), | |
| # login_msg: "" | |
| # } | |
| # return { | |
| # login_page: gr.update(visible=True), | |
| # main_page: gr.update(visible=False), | |
| # login_msg: "❌ Invalid credentials" | |
| # } | |
| # def show_page(page_name): | |
| # updates = { | |
| # dashboard_page: gr.update(visible=False), | |
| # students_page: gr.update(visible=False), | |
| # teachers_page: gr.update(visible=False), | |
| # courses_page: gr.update(visible=False), | |
| # youtube_page: gr.update(visible=False) | |
| # } | |
| # updates[page_name] = gr.update(visible=True) | |
| # return updates | |
| # # Event Handlers | |
| # login_btn.click( | |
| # login_check, | |
| # inputs=[username, password], | |
| # outputs=[login_page, main_page, login_msg] | |
| # ) | |
| # nav_dashboard.click(lambda: show_page(dashboard_page), outputs=list(show_page(dashboard_page).keys())) | |
| # nav_students.click(lambda: show_page(students_page), outputs=list(show_page(students_page).keys())) | |
| # nav_teachers.click(lambda: show_page(teachers_page), outputs=list(show_page(teachers_page).keys())) | |
| # nav_courses.click(lambda: show_page(courses_page), outputs=list(show_page(courses_page).keys())) | |
| # nav_youtube.click(lambda: show_page(youtube_page), outputs=list(show_page(youtube_page).keys())) | |
| # analyze_btn.click( | |
| # process_youtube_video, | |
| # inputs=[video_url, keywords], | |
| # outputs=[video_thumbnail, summary, sentiment, recommendations] | |
| # ) | |
| # logout_btn.click( | |
| # lambda: { | |
| # login_page: gr.update(visible=True), | |
| # main_page: gr.update(visible=False) | |
| # }, | |
| # outputs=[login_page, main_page] | |
| # ) | |
| # if __name__ == "__main__": | |
| # app.launch() | |
| import subprocess | |
| subprocess.check_call(["pip", "install", "transformers==4.34.0"]) | |
| subprocess.check_call(["pip", "install", "torch>=1.7.1"]) | |
| subprocess.check_call(["pip", "install", "youtube_transcript_api>=0.6.3"]) | |
| subprocess.check_call(["pip", "install", "pytube"]) | |
| subprocess.check_call(["pip", "install", "huggingface_hub>=0.19.0"]) | |
| subprocess.check_call(["pip", "install", "PyPDF2>=3.0.1"]) | |
| subprocess.check_call(["pip", "install", "google-generativeai"]) | |
| subprocess.check_call(["pip", "install", "textblob>=0.17.1"]) | |
| subprocess.check_call(["pip", "install", "python-dotenv>=1.0.0"]) | |
| subprocess.check_call(["pip", "install", "genai"]) | |
| subprocess.check_call(["pip", "install", "google-cloud-aiplatform==1.34.0"]) | |
| subprocess.check_call(["pip", "install", "google-api-python-client>=2.0.0"]) | |
| import transformers | |
| import torch | |
| import os | |
| import youtube_transcript_api | |
| import pytube | |
| import gradio | |
| import PyPDF2 | |
| import pathlib | |
| import pandas | |
| import numpy | |
| import textblob | |
| import gradio as gr | |
| from youtube_transcript_api import YouTubeTranscriptApi | |
| import google.generativeai as genai | |
| from googleapiclient.discovery import build | |
| import requests | |
| from textblob import TextBlob | |
| import re | |
| #from google.cloud import generativeai | |
| from googleapiclient.discovery import build | |
| from huggingface_hub import login | |
| from youtube_transcript_api import YouTubeTranscriptApi, TranscriptsDisabled, NoTranscriptFound | |
| def install_missing_packages(): | |
| required_packages = { | |
| "torch":">=1.11.0", | |
| "transformers":">=4.34.0", | |
| "youtube_transcript_api" :">=0.6.3" , | |
| "pytube":None, | |
| "huggingface_hub": ">=0.19.0", | |
| "PyPDF2": ">=3.0.1", | |
| "textblob":">=0.17.1", | |
| "python-dotenv":">=1.0.0", | |
| "genai":None, | |
| "google-generativeai": None, | |
| "google-cloud-aiplatform":"==1.34.0", | |
| "google-api-python-client": ">=2.0.0" | |
| } | |
| for package, version in required_packages.items(): | |
| try: | |
| __import__(package) | |
| except ImportError: | |
| package_name = f"{package}{version}" if version else package | |
| subprocess.check_call(["pip", "install", package_name]) | |
| install_missing_packages() | |
| # Configuration | |
| hf_token = os.getenv("HF_TOKEN") | |
| if hf_token: | |
| login(hf_token) | |
| else: | |
| raise ValueError("HF_TOKEN environment variable not set.") | |
| YOUTUBE_API_KEY = "AIzaSyD_SDF4lC3vpHVAMnBOcN2ZCTz7dRjUc98" # Replace with your YouTube API Key | |
| USER_CREDENTIALS = {"admin": "password"} # Example user credentials | |
| import os | |
| from youtube_transcript_api import YouTubeTranscriptApi, TranscriptsDisabled, NoTranscriptFound | |
| # Use environment variables | |
| GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY") | |
| YOUTUBE_API_KEY = os.getenv("YOUTUBE_API_KEY") | |
| if not GOOGLE_API_KEY or not YOUTUBE_API_KEY: | |
| raise ValueError("Please set GOOGLE_API_KEY and YOUTUBE_API_KEY environment variables") | |
| genai.configure(api_key=GOOGLE_API_KEY) | |
| # Database | |
| students_data = [ | |
| (1, "Alice", "A", "Computer Science"), | |
| (2, "Aliaa", "B", "Mathematics"), | |
| (3, "Charlie", "A", "Machine Learning"), | |
| (4, "Daan", "A", "Physics"), | |
| (5, "Jhon", "C", "Math"), | |
| (6, "Emma", "A+", "Computer Science") | |
| ] | |
| teachers_data = [ | |
| (1, "Dr. Smith", "Math", "MS Mathematics"), | |
| (2, "Ms. Johnson", "Science", "MSc Physics"), | |
| (3, "Ms. Jack", "Artificial Intelligence Engineer", "MSc AI"), | |
| (4, "Ms. Evelyn", "Computer Science", "MSc Computer Science"), | |
| ] | |
| courses_data = [ | |
| (1, "Algebra", "Dr. Smith", "Advanced"), | |
| (2, "Biology", "Ms. Mia", "Intermediate"), | |
| (3, "Machine Learning", "Ms. Jack", "Intermediate"), | |
| (4, "Computer Science", "Ms. Evelyn", "Intermediate"), | |
| (5, "Mathematics", "Ms. Smith", "Intermediate") | |
| ] | |
| def extract_video_id(url): | |
| match = re.search(r"(?:v=|\/|be\/|embed\/|watch\?v=)([0-9A-Za-z_-]{11})", url) | |
| return match.group(1) if match else None | |
| def get_video_metadata(video_id): | |
| try: | |
| youtube = build("youtube", "v3", developerKey=YOUTUBE_API_KEY) | |
| request = youtube.videos().list(part="snippet", id=video_id) | |
| response = request.execute() | |
| if "items" in response and len(response["items"]) > 0: | |
| snippet = response["items"][0]["snippet"] | |
| return { | |
| "title": snippet.get("title", "No title available"), | |
| "description": snippet.get("description", "No description available"), | |
| } | |
| return {} | |
| except Exception as e: | |
| return {"title": "Error fetching metadata", "description": str(e)} | |
| def clean_text_for_analysis(text): | |
| return " ".join(text.split()) | |
| def process_youtube_video(url): | |
| try: | |
| video_id = extract_video_id(url) | |
| if not video_id: | |
| return None, "Invalid YouTube URL" | |
| thumbnail = f"https://img.youtube.com/vi/{video_id}/maxresdefault.jpg" | |
| try: | |
| transcript_list = YouTubeTranscriptApi.list_transcripts(video_id) | |
| transcript = None | |
| try: | |
| transcript = transcript_list.find_transcript(['en']) | |
| except: | |
| transcript = transcript_list.find_generated_transcript(['en']) | |
| text = " ".join([t['text'] for t in transcript.fetch()]) | |
| if not text.strip(): | |
| raise ValueError("Transcript is empty") | |
| cleaned_text = clean_text_for_analysis(text) | |
| summary = f"Summary: {cleaned_text[:400]}..." | |
| return thumbnail, summary | |
| except (TranscriptsDisabled, NoTranscriptFound): | |
| metadata = get_video_metadata(video_id) | |
| summary = metadata.get("description", "No subtitles available") | |
| return thumbnail, summary | |
| except Exception as e: | |
| return None, f"Error: {str(e)}" | |
| def analyze_sentiment(url): | |
| try: | |
| video_id = extract_video_id(url) | |
| if not video_id: | |
| return "Invalid YouTube URL", "N/A" | |
| try: | |
| transcript_list = YouTubeTranscriptApi.list_transcripts(video_id) | |
| transcript = None | |
| try: | |
| transcript = transcript_list.find_transcript(['en']) | |
| except: | |
| transcript = transcript_list.find_generated_transcript(['en']) | |
| text = " ".join([t['text'] for t in transcript.fetch()]) | |
| if not text.strip(): | |
| raise ValueError("Transcript is empty") | |
| cleaned_text = clean_text_for_analysis(text) | |
| sentiment = TextBlob(cleaned_text).sentiment | |
| sentiment_label = f"{'Positive' if sentiment.polarity > 0 else 'Negative' if sentiment.polarity < 0 else 'Neutral'} ({sentiment.polarity:.2f})" | |
| return "Sentiment Analysis Completed", sentiment_label | |
| except (TranscriptsDisabled, NoTranscriptFound): | |
| return "No transcript available", "N/A" | |
| except Exception as e: | |
| return f"Error: {str(e)}", "N/A" | |
| # Gradio Interface | |
| # Gradio Interface | |
| with gr.Blocks(theme=gr.themes.Soft()) as app: | |
| # Login Page | |
| with gr.Group() as login_page: | |
| gr.Markdown("# 🎓 Educational Learning Management System") | |
| username = gr.Textbox(label="Username") | |
| password = gr.Textbox(label="Password", type="password") | |
| login_btn = gr.Button("Login", variant="primary") | |
| login_msg = gr.Markdown() | |
| # Main Interface | |
| with gr.Group(visible=False) as main_page: | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| gr.Markdown("### 📋 Navigation") | |
| nav_dashboard = gr.Button("📊 Dashboard", variant="primary") | |
| nav_youtube = gr.Button("🎥 YouTube Tool") | |
| logout_btn = gr.Button("🚪 Logout", variant="stop") | |
| with gr.Column(scale=3): | |
| dashboard_page = gr.Group() | |
| with dashboard_page: | |
| gr.Markdown("## 📊 Dashboard") | |
| youtube_page = gr.Group(visible=False) | |
| with youtube_page: | |
| gr.Markdown("## Agent for YouTube Content Exploration") | |
| with gr.Row(): | |
| with gr.Column(scale=2): | |
| video_url = gr.Textbox( | |
| label="YouTube URL", | |
| placeholder="https://youtube.com/watch?v=..." | |
| ) | |
| analyze_btn = gr.Button("🔍 Analyze Video", variant="primary") | |
| sentiment_btn = gr.Button("😊 Analyze Sentiment", variant="primary") | |
| with gr.Column(scale=1): | |
| video_thumbnail = gr.Image(label="Video Preview") | |
| with gr.Row(): | |
| with gr.Column(): | |
| summary = gr.Textbox(label="📝 Summary", lines=8) | |
| sentiment = gr.Textbox(label="😊 Content Sentiment") | |
| def login_check(user, pwd): | |
| if USER_CREDENTIALS.get(user) == pwd: | |
| return { | |
| login_page: gr.update(visible=False), | |
| main_page: gr.update(visible=True), | |
| login_msg: "" | |
| } | |
| return { | |
| login_page: gr.update(visible=True), | |
| main_page: gr.update(visible=False), | |
| login_msg: "❌ Invalid credentials" | |
| } | |
| def show_page(page_name): | |
| updates = { | |
| dashboard_page: gr.update(visible=False), | |
| youtube_page: gr.update(visible=False) | |
| } | |
| updates[page_name] = gr.update(visible=True) | |
| return updates | |
| login_btn.click( | |
| login_check, | |
| inputs=[username, password], | |
| outputs=[login_page, main_page, login_msg] | |
| ) | |
| nav_dashboard.click(lambda: show_page(dashboard_page), outputs=list(show_page(dashboard_page).keys())) | |
| nav_youtube.click(lambda: show_page(youtube_page), outputs=list(show_page(youtube_page).keys())) | |
| analyze_btn.click( | |
| process_youtube_video, | |
| inputs=[video_url], | |
| outputs=[video_thumbnail, summary] | |
| ) | |
| sentiment_btn.click( | |
| analyze_sentiment, | |
| inputs=[video_url], | |
| outputs=[summary, sentiment] | |
| ) | |
| logout_btn.click( | |
| lambda: { | |
| login_page: gr.update(visible=True), | |
| main_page: gr.update(visible=False) | |
| }, | |
| outputs=[login_page, main_page] | |
| ) | |
| if __name__ == "__main__": | |
| app.launch() | |
| # def extract_video_id(url): | |
| # # Improved regex to handle various YouTube URL formats | |
| # match = re.search(r"(?:v=|\/|be\/|embed\/|watch\?v=)([0-9A-Za-z_-]{11})", url) | |
| # return match.group(1) if match else None | |
| # def get_video_metadata(video_id): | |
| # try: | |
| # youtube = build("youtube", "v3", developerKey=YOUTUBE_API_KEY) | |
| # request = youtube.videos().list(part="snippet", id=video_id) | |
| # response = request.execute() | |
| # if "items" in response and len(response["items"]) > 0: | |
| # snippet = response["items"][0]["snippet"] | |
| # return { | |
| # "title": snippet.get("title", "No title available"), | |
| # "description": snippet.get("description", "No description available"), | |
| # } | |
| # return {} | |
| # except Exception as e: | |
| # return {"title": "Error fetching metadata", "description": str(e)} | |
| # def clean_text_for_analysis(text): | |
| # return " ".join(text.split()) | |
| # def get_recommendations(keywords, max_results=5): | |
| # if not keywords: | |
| # return "Please provide search keywords" | |
| # try: | |
| # response = requests.get( | |
| # "https://www.googleapis.com/youtube/v3/search", | |
| # params={ | |
| # "part": "snippet", | |
| # "q": f"educational {keywords}", | |
| # "type": "video", | |
| # "maxResults": max_results, | |
| # "relevanceLanguage": "en", | |
| # "key": YOUTUBE_API_KEY | |
| # } | |
| # ).json() | |
| # results = [] | |
| # for item in response.get("items", []): | |
| # title = item["snippet"]["title"] | |
| # channel = item["snippet"]["channelTitle"] | |
| # video_id = item["id"]["videoId"] | |
| # results.append(f"📺 {title}\n👤 {channel}\n🔗 https://youtube.com/watch?v={video_id}\n") | |
| # return "\n".join(results) if results else "No recommendations found" | |
| # except Exception as e: | |
| # return f"Error: {str(e)}" | |
| # def process_youtube_video(url): | |
| # import re | |
| # from youtube_transcript_api import YouTubeTranscriptApi, TranscriptsDisabled, NoTranscriptFound | |
| # from textblob import TextBlob | |
| # try: | |
| # # Extract video ID | |
| # video_id = extract_video_id(url) | |
| # if not video_id: | |
| # return None, "Invalid YouTube URL", "N/A" | |
| # # Generate thumbnail URL | |
| # thumbnail = f"https://img.youtube.com/vi/{video_id}/maxresdefault.jpg" | |
| # # Initialize default values | |
| # summary = "No transcript available" | |
| # sentiment_label = "N/A" | |
| # try: | |
| # # Fetch transcript | |
| # print(f"Fetching transcript for video ID: {video_id}") | |
| # transcript_list = YouTubeTranscriptApi.list_transcripts(video_id) | |
| # transcript = None | |
| # try: | |
| # transcript = transcript_list.find_transcript(['en']) | |
| # except: | |
| # transcript = transcript_list.find_generated_transcript(['en']) | |
| # # Combine transcript into text | |
| # text = " ".join([t['text'] for t in transcript.fetch()]) | |
| # if not text.strip(): | |
| # raise ValueError("Transcript is empty") | |
| # # Clean and analyze text | |
| # print(f"Transcript fetched successfully. Length: {len(text)} characters") | |
| # cleaned_text = clean_text_for_analysis(text) | |
| # sentiment = TextBlob(cleaned_text).sentiment | |
| # sentiment_label = f"{'Positive' if sentiment.polarity > 0 else 'Negative' if sentiment.polarity < 0 else 'Neutral'} ({sentiment.polarity:.2f})" | |
| # # Summarize text | |
| # summary = f"Summary: {cleaned_text[:400]}..." | |
| # print(f"Sentiment analysis completed: {sentiment_label}") | |
| # except (TranscriptsDisabled, NoTranscriptFound): | |
| # # Fall back to metadata if no transcript | |
| # print(f"No transcript found for video ID: {video_id}") | |
| # metadata = get_video_metadata(video_id) | |
| # summary = metadata.get("description", "No subtitles available") | |
| # sentiment_label = "N/A" | |
| # return thumbnail, summary, sentiment_label | |
| # except Exception as e: | |
| # print(f"Error processing video: {e}") | |
| # return None, f"Error: {str(e)}", "N/A" | |
| # # Test the function | |
| # url = "https://www.youtube.com/watch?v=q1XFm21I-VQ" | |
| # thumbnail, summary, sentiment = process_youtube_video(url) | |
| # print(f"Thumbnail: {thumbnail}\n") | |
| # print(f"Summary:\n{summary}\n") | |
| # print(f"Sentiment: {sentiment}") | |
| # # Gradio Interface | |
| # with gr.Blocks(theme=gr.themes.Soft()) as app: | |
| # # Login Page | |
| # with gr.Group() as login_page: | |
| # gr.Markdown("# 🎓 Educational Learning Management System") | |
| # username = gr.Textbox(label="Username") | |
| # password = gr.Textbox(label="Password", type="password") | |
| # login_btn = gr.Button("Login", variant="primary") | |
| # login_msg = gr.Markdown() | |
| # # Main Interface | |
| # with gr.Group(visible=False) as main_page: | |
| # with gr.Row(): | |
| # with gr.Column(scale=1): | |
| # gr.Markdown("### 📋 Navigation") | |
| # nav_dashboard = gr.Button("📊 Dashboard", variant="primary") | |
| # nav_students = gr.Button("👥 Students") | |
| # nav_teachers = gr.Button("👨🏫 Teachers") | |
| # nav_courses = gr.Button("📚 Courses") | |
| # nav_youtube = gr.Button("🎥 YouTube Tool") | |
| # logout_btn = gr.Button("🚪 Logout", variant="stop") | |
| # with gr.Column(scale=3): | |
| # # Dashboard Content | |
| # dashboard_page = gr.Group() | |
| # with dashboard_page: | |
| # gr.Markdown("## 📊 Dashboard") | |
| # gr.Markdown(f""" | |
| # ### System Overview | |
| # - 👥 Total Students: {len(students_data)} | |
| # - 👨🏫 Total Teachers: {len(teachers_data)} | |
| # - 📚 Total Courses: {len(courses_data)} | |
| # ### Quick Actions | |
| # - View student performance | |
| # - Access course materials | |
| # - Generate learning insights | |
| # """) | |
| # # Students Content | |
| # students_page = gr.Group(visible=False) | |
| # with students_page: | |
| # gr.Markdown("## 👥 Students") | |
| # gr.DataFrame( | |
| # value=students_data, | |
| # headers=["ID", "Name", "Grade", "Program"] | |
| # ) | |
| # # Teachers Content | |
| # teachers_page = gr.Group(visible=False) | |
| # with teachers_page: | |
| # gr.Markdown("## 👨🏫 Teachers") | |
| # gr.DataFrame( | |
| # value=teachers_data, | |
| # headers=["ID", "Name", "Subject", "Qualification"] | |
| # ) | |
| # # Courses Content | |
| # courses_page = gr.Group(visible=False) | |
| # with courses_page: | |
| # gr.Markdown("## 📚 Courses") | |
| # gr.DataFrame( | |
| # value=courses_data, | |
| # headers=["ID", "Name", "Instructor", "Level"] | |
| # ) | |
| # # YouTube Tool Content | |
| # youtube_page = gr.Group(visible=False) | |
| # with youtube_page: | |
| # gr.Markdown("## Agent for YouTube Content Exploration") | |
| # with gr.Row(): | |
| # with gr.Column(scale=2): | |
| # video_url = gr.Textbox( | |
| # label="YouTube URL", | |
| # placeholder="https://youtube.com/watch?v=..." | |
| # ) | |
| # keywords = gr.Textbox( | |
| # label="Keywords for Recommendations", | |
| # placeholder="e.g., python programming, machine learning" | |
| # ) | |
| # analyze_btn = gr.Button("🔍 Analyze Video", variant="primary") | |
| # recommend_btn = gr.Button("🔎 Get Recommendations", variant="primary") | |
| # with gr.Column(scale=1): | |
| # video_thumbnail = gr.Image(label="Video Preview") | |
| # with gr.Row(): | |
| # with gr.Column(): | |
| # summary = gr.Textbox(label="📝 Summary", lines=8) | |
| # sentiment = gr.Textbox(label="😊 Content Sentiment") | |
| # with gr.Column(): | |
| # recommendations = gr.Textbox(label="🎯 Related Videos", lines=10) | |
| # def login_check(user, pwd): | |
| # if USER_CREDENTIALS.get(user) == pwd: | |
| # return { | |
| # login_page: gr.update(visible=False), | |
| # main_page: gr.update(visible=True), | |
| # login_msg: "" | |
| # } | |
| # return { | |
| # login_page: gr.update(visible=True), | |
| # main_page: gr.update(visible=False), | |
| # login_msg: "❌ Invalid credentials" | |
| # } | |
| # def show_page(page_name): | |
| # updates = { | |
| # dashboard_page: gr.update(visible=False), | |
| # students_page: gr.update(visible=False), | |
| # teachers_page: gr.update(visible=False), | |
| # courses_page: gr.update(visible=False), | |
| # youtube_page: gr.update(visible=False) | |
| # } | |
| # updates[page_name] = gr.update(visible=True) | |
| # return updates | |
| # # Event Handlers | |
| # login_btn.click( | |
| # login_check, | |
| # inputs=[username, password], | |
| # outputs=[login_page, main_page, login_msg] | |
| # ) | |
| # nav_dashboard.click(lambda: show_page(dashboard_page), outputs=list(show_page(dashboard_page).keys())) | |
| # nav_students.click(lambda: show_page(students_page), outputs=list(show_page(students_page).keys())) | |
| # nav_teachers.click(lambda: show_page(teachers_page), outputs=list(show_page(teachers_page).keys())) | |
| # nav_courses.click(lambda: show_page(courses_page), outputs=list(show_page(courses_page).keys())) | |
| # nav_youtube.click(lambda: show_page(youtube_page), outputs=list(show_page(youtube_page).keys())) | |
| # analyze_btn.click( | |
| # process_youtube_video, | |
| # inputs=[video_url], | |
| # outputs=[video_thumbnail, summary, sentiment] | |
| # ) | |
| # recommend_btn.click( | |
| # get_recommendations, | |
| # inputs=[keywords], | |
| # outputs=[recommendations] | |
| # ) | |
| # logout_btn.click( | |
| # lambda: { | |
| # login_page: gr.update(visible=True), | |
| # main_page: gr.update(visible=False) | |
| # }, | |
| # outputs=[login_page, main_page] | |
| # ) | |
| # if __name__ == "__main__": | |
| # app.launch() | |