Update app.py

app.py

@@ -76,10 +76,20 @@ class NewsCache:
 
 cache = NewsCache(CACHE_SIZE)
 
-def fetch_rss_news(**category_sources):
+def fetch_rss_news(tech_sources, business_sources, science_sources, world_sources, sports_sources, health_sources):
     articles = []
     cutoff_time = datetime.now(pytz.UTC) - RSS_FETCH_INTERVAL
     
+    # Create a mapping of selected sources
+    category_sources = {
+        "Technology": tech_sources if tech_sources else [],
+        "Business": business_sources if business_sources else [],
+        "Science": science_sources if science_sources else [],
+        "World News": world_sources if world_sources else [],
+        "Sports": sports_sources if sports_sources else [],
+        "Health": health_sources if health_sources else []
+    }
+    
     logger.info(f"Selected sources: {category_sources}")
     
     for category, sources in category_sources.items():
@@ -156,23 +166,25 @@ def summarize_articles(articles, model_name):
         """)
     return "\n".join(summaries)
 
-def generate_summary(**kwargs):
-    model_name = kwargs.pop('model_name')  # Extract model_name from kwargs
-    
-    logger.info(f"Generating summary with sources: {kwargs} and model: {model_name}")
-    
-    # Check if any sources are selected
-    if not any(kwargs.values()):
-        return "Please select at least one news source."
-    
+def get_summary(tech_sources, business_sources, science_sources, world_sources, 
+                sports_sources, health_sources, selected_model):
     try:
-        articles = fetch_rss_news(**kwargs)
+        # Check if any sources are selected
+        if not any([tech_sources, business_sources, science_sources, 
+                   world_sources, sports_sources, health_sources]):
+            return "Please select at least one news source."
+        
+        model_name = SUMMARIZER_MODELS[selected_model]
+        articles = fetch_rss_news(tech_sources, business_sources, science_sources,
+                                world_sources, sports_sources, health_sources)
+        
         if not articles:
             return "No recent news found from the selected sources."
+            
         return summarize_articles(articles, model_name)
     except Exception as e:
-        logger.error(f"Error in generate_summary: {str(e)}")
-        return f"An error occurred while generating the summary. Please try again."
+        logger.error(f"Error in get_summary: {str(e)}")
+        return "An error occurred while processing your request. Please try again."
 
 # Gradio Interface
 demo = gr.Blocks()
@@ -181,16 +193,50 @@ with demo:
     gr.Markdown("# 📰 AI News Summarizer")
     
     with gr.Row():
-        checkbox_groups = {}
         with gr.Column():
-            # Create checkbox groups for each category
-            for category in CATEGORIES:
-                checkbox_groups[category.lower().replace(" ", "_") + "_sources"] = gr.CheckboxGroup(
-                    choices=list(NEWS_SOURCES[category].keys()),
-                    label=f"{category} Sources",
-                    value=[]
-                )
-        
+            # Technology sources
+            tech_sources = gr.CheckboxGroup(
+                choices=list(NEWS_SOURCES["Technology"].keys()),
+                label="Technology Sources",
+                value=[]
+            )
+            
+            # Business sources
+            business_sources = gr.CheckboxGroup(
+                choices=list(NEWS_SOURCES["Business"].keys()),
+                label="Business Sources",
+                value=[]
+            )
+            
+            # Science sources
+            science_sources = gr.CheckboxGroup(
+                choices=list(NEWS_SOURCES["Science"].keys()),
+                label="Science Sources",
+                value=[]
+            )
+            
+        with gr.Column():
+            # World News sources
+            world_sources = gr.CheckboxGroup(
+                choices=list(NEWS_SOURCES["World News"].keys()),
+                label="World News Sources",
+                value=[]
+            )
+            
+            # Sports sources
+            sports_sources = gr.CheckboxGroup(
+                choices=list(NEWS_SOURCES["Sports"].keys()),
+                label="Sports Sources",
+                value=[]
+            )
+            
+            # Health sources
+            health_sources = gr.CheckboxGroup(
+                choices=list(NEWS_SOURCES["Health"].keys()),
+                label="Health Sources",
+                value=[]
+            )
+            
         with gr.Column():
             model_selector = gr.Radio(
                 choices=list(SUMMARIZER_MODELS.keys()),
@@ -201,19 +247,18 @@ with demo:
     summarize_button = gr.Button("Get News Summary")
     summary_output = gr.Textbox(label="News Summary", lines=20)
 
-    def get_summary(**kwargs):
-        try:
-            selected_model = kwargs.pop('model_selector')
-            model_name = SUMMARIZER_MODELS[selected_model]
-            return generate_summary(model_name=model_name, **kwargs)
-        except Exception as e:
-            logger.error(f"Error in get_summary: {str(e)}")
-            return "An error occurred while processing your request. Please try again."
-
     # Connect the components to the summary function
     summarize_button.click(
         get_summary,
-        inputs=dict(list(checkbox_groups.items()) + [("model_selector", model_selector)]),
+        inputs=[
+            tech_sources,
+            business_sources,
+            science_sources,
+            world_sources,
+            sports_sources,
+            health_sources,
+            model_selector
+        ],
         outputs=summary_output
     )