Update app.py

app.py

@@ -3,6 +3,7 @@ from newspaper import Article
 from modules.online_search import search_online
 from modules.validation import calculate_truthfulness_score
 from modules.knowledge_graph import search_kg
+from modules.generate_explanation import generate_explanation  # Import the explanation generator
 from dotenv import load_dotenv
 import os
 from concurrent.futures import ThreadPoolExecutor
@@ -18,7 +19,7 @@ SEARCH_BASE_URL = os.getenv("SEARCH_BASE_URL")
 SEARCH_MODEL = os.getenv("SEARCH_MODEL")
 
 # Initialize ThreadPoolExecutor
-executor = ThreadPoolExecutor(max_workers=2)
+executor = ThreadPoolExecutor(max_workers=3)  # Increased workers to accommodate explanation task
 
 # Function to process input and evaluate truthfulness
 def evaluate_news(news_input):
@@ -49,12 +50,13 @@ def evaluate_news(news_input):
         online_search_results = future_online.result()
 
         # Combine context from KG and online search
-        context = online_search_results['message_content'] + '\n' + kg_content
+        context = online_search_results['message_content'] + '\n' + kg_content + '\n' + 'Device set to use cpu'
+        # print(context)  # Debug log
 
         # Calculate truth score
         truth_score = calculate_truthfulness_score(info=news_text, context=context)
 
-        # Generate explanation based on score
+        # Determine truthfulness status and recommendation
         if truth_score > 0.7:
             status = "likely true"
             recommendation = "You can reasonably trust this information, but further verification is always recommended for critical decisions."
@@ -65,11 +67,30 @@ def evaluate_news(news_input):
             status = "unlikely to be true"
             recommendation = "It is recommended to verify this information through multiple reliable sources before trusting it."
 
-        # Final Output
+        # Display initial result with score
         result = f"**News**: \"{news_text[:300]}...\"\n\n"
         result += f"**Truthfulness Score**: {truth_score:.2f} (**{status.capitalize()}**)\n\n"
         result += f"**Analysis**: {recommendation}\n\n"
-        yield result
+        yield result  # Immediately display score and recommendation
+
+        # Generate explanation asynchronously
+        future_explanation = executor.submit(generate_explanation, news_text, context, truth_score)
+
+        # Add explanation and sources once available
+        explanation = future_explanation.result()  # Wait for explanation result
+        if explanation:
+            result += f"**Explanation**: {explanation}\n\n"  # Append explanation
+
+            # Add sources from the online search results (top 5 sources)
+            sources = online_search_results.get('sources', [])
+            if sources:
+                result += "\n**Sources**:\n"
+                # Ensure we only show up to 5 sources
+                for i, source in enumerate(sources[:5]):
+                    result += f"{i + 1}. {source}\n"
+                result += "\n*Please make sure to do your own research for more confirmation and to cross-check the information.*"
+
+            yield result  # Update UI with explanation and sources
 
     except Exception as e:
         yield f"**Error occurred while processing the input:** {str(e)}"
@@ -77,25 +98,32 @@ def evaluate_news(news_input):
 
 # Gradio Interface
 with gr.Blocks() as demo:
-    gr.Markdown("# 📰 EchoTruth: Amplifying Authenticity in Live Broadcasts")
-    gr.Markdown("### Enter a piece of news or a URL below to validate its authenticity.")
-
-    # Input options
+    gr.Markdown("# 📰 EchoTruth: Verify News Authenticity in Real-Time")
+    gr.Markdown("### Enter a piece of news or a URL below, and we'll help you evaluate its truthfulness using advanced AI.")
+    
+    gr.Markdown("### How to Use:")
+    gr.Markdown("1. Paste a news article link or type in the text.")
+    gr.Markdown("2. Click **Check Truthfulness** to analyze the authenticity of the news.")
+    gr.Markdown("3. Get your truthfulness score along with explanations and sources.")
+    
     with gr.Row():
-        input_box = gr.Textbox(placeholder="Enter news text or URL here...", label="Input News or URL")
+        input_box = gr.Textbox(
+            placeholder="Enter news text or URL here... (e.g., https://example.com)",
+            label="Input News or URL",
+            lines=5
+        )
 
-    # Output display
-    output_box = gr.Markdown()
-
-    # Submit button
     submit_btn = gr.Button("Check Truthfulness")
 
-    # Trigger function with spinner
+    output_box = gr.Markdown()
+
     submit_btn.click(
         fn=evaluate_news,
         inputs=[input_box],
         outputs=[output_box]
     )
 
-# Launch Gradio App
-demo.launch()
+    gr.Markdown("### **About EchoTruth**")
+    gr.Markdown("EchoTruth uses AI to help users verify news authenticity in real-time. We recommend checking multiple sources before making decisions based on news.")
+    
+demo.launch()