Update app.py

app.py

@@ -32,7 +32,7 @@ from youtube_transcript_api import YouTubeTranscriptApi
 import requests
 from textblob import TextBlob
 import re
-#from google.cloud import generativeai
+
 from huggingface_hub import login
 from youtube_transcript_api import YouTubeTranscriptApi, TranscriptsDisabled, NoTranscriptFound
 def install_missing_packages():
@@ -356,187 +356,7 @@ def install_missing_packages():
 # if __name__ == "__main__":
 #     app.launch()
 
-import os
-import subprocess
-from youtube_transcript_api import YouTubeTranscriptApi, TranscriptsDisabled, NoTranscriptFound
-from transformers import T5ForConditionalGeneration, T5Tokenizer
-from nltk.sentiment.vader import SentimentIntensityAnalyzer
-import nltk
-import requests
-import gradio as gr
-import re
-
-# Download NLTK VADER data
-nltk.download('vader_lexicon')
-
-# Install Missing Packages
 
-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",
-        "nltk": None
-    }
-
-    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
-USER_CREDENTIALS = {
-    "admin": "password123",
-    "teacher": "teach2024",
-    "student": "learn2024"
-}
-
-YOUTUBE_API_KEY = os.getenv("YOUTUBE_API_KEY")
-if not YOUTUBE_API_KEY:
-    raise ValueError("YOUTUBE_API_KEY environment variable not set.")
-
-# Functions
-
-def sanitize_text(text):
-    """Remove invalid Unicode characters."""
-    return text.encode("utf-8", "replace").decode("utf-8")
-
-def extract_video_id(url):
-    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
-
-def get_youtube_transcript(video_url):
-    video_id = extract_video_id(video_url)
-    if not video_id:
-        raise ValueError("Invalid YouTube URL")
-    try:
-        transcript = YouTubeTranscriptApi.get_transcript(video_id)
-        return " ".join([entry['text'] for entry in transcript])
-    except (TranscriptsDisabled, NoTranscriptFound):
-        raise ValueError("Transcript not available for this video.")
-
-def summarize_text(text, model_name="t5-small", max_length=150, min_length=40):
-    tokenizer = T5Tokenizer.from_pretrained(model_name)
-    model = T5ForConditionalGeneration.from_pretrained(model_name)
-
-    input_text = "summarize: " + text
-    inputs = tokenizer.encode(input_text, return_tensors="pt", max_length=512, truncation=True)
-
-    summary_ids = model.generate(
-        inputs, max_length=max_length, min_length=min_length,
-        length_penalty=2.0, num_beams=4, early_stopping=True
-    )
-    return tokenizer.decode(summary_ids[0], skip_special_tokens=True)
-
-def analyze_sentiment(text):
-    sid = SentimentIntensityAnalyzer()
-    return sid.polarity_scores(text)
-
-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(video_url, keywords):
-    try:
-        transcript = get_youtube_transcript(video_url)
-        summary = summarize_text(transcript)
-        sentiment = analyze_sentiment(transcript)
-        recommendations = get_recommendations(keywords)
-
-        # Return results to the corresponding Gradio outputs
-        return summary, str(sentiment), recommendations
-    except Exception as e:
-        # Return error message for the Summary output, and empty for others
-        return str(e), "", ""
-
-# Gradio Interface
-with gr.Blocks(theme=gr.themes.Soft()) as app:
-    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()
-
-    with gr.Group(visible=False) as main_page:
-        with gr.Row():
-            with gr.Column(scale=1):
-                nav_youtube = gr.Button("🎥 YouTube Tool")
-                logout_btn = gr.Button("🚪 Logout", variant="stop")
-            with gr.Column(scale=3):
-                youtube_page = gr.Group()
-                with youtube_page:
-                    gr.Markdown("## 🎥 YouTube Tool")
-                    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")
-                    analyze_btn = gr.Button("Analyze Video", variant="primary")
-
-                    summary = gr.Textbox(label="Summary", lines=5)
-                    sentiment = gr.Textbox(label="Sentiment Analysis")
-                    recommendations = gr.Textbox(label="Recommendations", 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_msg: "Invalid credentials"}
-
-    def show_youtube_page():
-        return {youtube_page: gr.update(visible=True)}
-
-    login_btn.click(login_check, inputs=[username, password], outputs=[login_page, main_page, login_msg])
-    nav_youtube.click(show_youtube_page, outputs=[youtube_page])
-
-    analyze_btn.click(
-    process_youtube_video,
-    inputs=[video_url, keywords],
-    outputs=[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()