Update app.py

app.py

@@ -1,20 +1,37 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
+import requests
+from bs4 import BeautifulSoup
 
-# Initialize Hugging Face client with your model
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
-
-# Define the task for each bot
+# Function to perform a simple web search (this is just a placeholder)
 def search_web(query):
-    # Simulating web search (replace with actual search logic)
-    return f"Searching for: {query}..."
+    # Simulate an actual web search (use a real API like Google Custom Search or scraping)
+    search_url = f"https://www.google.com/search?q={query}"
+    
+    headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3'}
+    
+    # Send a request to Google search (this is just an example; it won't fetch proper results without scraping limits)
+    response = requests.get(search_url, headers=headers)
+    
+    # Parse the response with BeautifulSoup
+    soup = BeautifulSoup(response.text, 'html.parser')
+    
+    # Extract the first search result (this is just a simplified demo)
+    search_results = soup.find_all('h3')
+    
+    if search_results:
+        return f"Found results: {search_results[0].get_text()}"
+    else:
+        return "No search results found."
 
+# Function to summarize content (simulating summarization for now)
 def summarize_content(content):
-    # Simulating summarization (replace with actual summarization logic)
-    return f"Summary: {content[:50]}..."  # Simple truncation for demo
+    # Placeholder logic for summarization (you can integrate a model here)
+    # For now, just truncate to the first 100 characters
+    return content[:100] + "..." if len(content) > 100 else content
 
+# Function to provide a final review (simulated for now)
 def final_review(summary):
-    # Simulating final review of the summary (replace with actual review logic)
+    # Placeholder logic for final review
     return f"Final Overview: {summary}"
 
 # Define the process button callback function
@@ -49,4 +66,3 @@ with gr.Blocks() as demo:
 
 # Launch the Gradio interface
 demo.launch()
-