Update app.py

app.py

@@ -1,105 +1,136 @@
 import gradio as gr
-import requests
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import feedparser
+import threading
+from datetime import datetime
+import json
+import os
+
+# Initialize Llama 2 model and tokenizer
+model_name = "meta-llama-2-1b"  # Replace with your actual model name
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+def fetch_news_from_rss(interests):
+    """Fetch news from RSS feeds based on interests"""
+    # Example RSS feeds - you can expand this list
+    rss_feeds = {
+        "Technology": "https://feeds.feedburner.com/TechCrunch",
+        "Business": "https://feeds.feedburner.com/BusinessInsider",
+        "Sports": "https://www.espn.com/espn/rss/news",
+    }
+    
+    articles = []
+    for interest in interests:
+        if interest in rss_feeds:
+            feed = feedparser.parse(rss_feeds[interest])
+            articles.extend(feed.entries[:3])  # Get top 3 articles per interest
+    
+    return articles
 
-GUARDIAN_API_KEY = "d042cafb-0d94-4ce8-b10b-16f69cbb4cd6"
-GUARDIAN_API_URL = "https://content.guardianapis.com/search"
+def generate_summary(text, language="English"):
+    """Generate summary using Llama 2"""
+    prompt = f"""Please provide a concise summary of the following news article in {language}. 
+    Focus on the main points and key details:
 
-# Global user data storage
-user_data = {}
+    Article: {text}
 
-def get_news(language, interests):
-    """
-    Fetch news articles based on user preferences using the Guardian API
-    """
-    params = {
-        "api-key": GUARDIAN_API_KEY,
-        "q": ",".join(interests),
-        "page-size": 3,
-        "order-by": "newest",
-        "show-fields": "headline,standfirst,thumbnail"
-    }
+    Summary:"""
     
-    response = requests.get(GUARDIAN_API_URL, params=params)
-    data = response.json()
+    inputs = tokenizer(prompt, return_tensors="pt", max_length=512, truncation=True)
+    outputs = model.generate(
+        inputs["input_ids"],
+        max_length=150,
+        min_length=50,
+        temperature=0.7,
+        num_return_sequences=1
+    )
     
-    if data["response"]["status"] == "ok":
-        articles = data["response"]["results"]
-        return "\n\n".join([article["fields"]["headline"] + "\n" + article["fields"]["standfirst"] for article in articles])
-    else:
-        return "Error fetching news articles."
-
-def generate_summary(text, max_length=130):
-    """
-    Generate summary for the provided text
-    """
-    if not text:
-        return "Please enter some text to summarize!"
-    # For now, just return a portion of the text
-    return f"Demo summary (first {max_length} characters):\n{text[:max_length]}"
+    summary = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return summary.split("Summary:")[1].strip()
 
-def save_preferences(name, language, interests):
-    """
-    Save user preferences for personalization
-    """
+def save_user_preferences(name, language, interests):
+    """Save user preferences to a JSON file"""
     if not name or not language or not interests:
         return "Please fill in all fields!"
-    user_data["name"] = name
-    user_data["language"] = language
-    user_data["interests"] = interests
-    return f"Welcome {name}! Your preferences have been saved. Language: {language}, Interests: {', '.join(interests)}"
-
-def get_daily_news_summary():
-    """
-    Fetch and summarize the daily news for the user
-    """
-    if "name" not in user_data or "language" not in user_data or "interests" not in user_data:
-        return "Please set your preferences first."
     
-    news_text = get_news(user_data["language"], user_data["interests"])
-    summary = generate_summary(news_text)
-    return summary
-
-with gr.Blocks() as demo:
-    gr.Markdown("# News Summary Application")
-
-    with gr.Accordion("Set Your Preferences", open=True):
-        name_input = gr.Textbox(label="Your Name")
-        submit_name_button = gr.Button("Next")
-        name_output = gr.Textbox(label="Status")
-
-        submit_name_button.click(
-            save_preferences,
-            inputs=[name_input],
-            outputs=[name_output, name_input]
+    preferences = {
+        "name": name,
+        "language": language,
+        "interests": interests,
+        "last_updated": datetime.now().isoformat()
+    }
+    
+    with open(f"preferences_{name}.json", "w") as f:
+        json.dump(preferences, f)
+    
+    return f"Preferences saved for {name}!"
+
+def get_personalized_summary(name):
+    """Get personalized news summary based on user preferences"""
+    try:
+        with open(f"preferences_{name}.json", "r") as f:
+            preferences = json.load(f)
+    except FileNotFoundError:
+        return "Please set your preferences first!"
+
+    # Fetch news based on interests
+    articles = fetch_news_from_rss(preferences["interests"])
+    
+    summaries = []
+    for article in articles:
+        title = article.get("title", "")
+        content = article.get("description", "")
+        
+        # Generate summary using Llama 2
+        summary = generate_summary(
+            content, 
+            language=preferences["language"]
         )
+        
+        summaries.append(f"📰 {title}\n\n{summary}\n\n---")
+    
+    return "\n".join(summaries)
 
-    with gr.Accordion("Select Language and Interests", open=False):
+# Create Gradio interface
+with gr.Blocks(title="Llama 2 News Summarizer") as demo:
+    gr.Markdown("# 📰 AI News Summarizer powered by Llama 2")
+    
+    with gr.Tab("Set Preferences"):
+        name_input = gr.Textbox(label="Your Name")
         language_dropdown = gr.Dropdown(
-            choices=["English", "Arabic", "Spanish", "French"],
+            choices=["English", "Spanish", "French", "Arabic"],
             label="Preferred Language"
         )
         interests_checkboxes = gr.CheckboxGroup(
-            choices=["Technology", "Sports", "Politics", "Business", "Entertainment"],
+            choices=["Technology", "Business", "Sports", "Science", "Politics"],
             label="News Interests"
         )
-        save_preferences_button = gr.Button("Save Preferences")
+        save_button = gr.Button("Save Preferences")
         preferences_output = gr.Textbox(label="Status")
-
-        save_preferences_button.click(
-            save_preferences,
+        
+        save_button.click(
+            save_user_preferences,
             inputs=[name_input, language_dropdown, interests_checkboxes],
             outputs=[preferences_output]
         )
-
-    with gr.Accordion("Daily News Summary", open=False):
-        news_summary_output = gr.Textbox(label="News Summary")
-
-        gr.Button("Get Today's News").click(
-            get_daily_news_summary,
-            outputs=news_summary_output
+    
+    with gr.Tab("Get News Summary"):
+        name_check = gr.Textbox(label="Enter your name to get summary")
+        get_summary_button = gr.Button("Get Summary")
+        summary_output = gr.Textbox(
+            label="Your Personalized News Summary",
+            lines=10
+        )
+        
+        get_summary_button.click(
+            get_personalized_summary,
+            inputs=[name_check],
+            outputs=[summary_output]
         )
 
-demo.launch()
+if __name__ == "__main__":
+    demo.launch()