Update app.py

app.py

@@ -267,11 +267,10 @@ class ChatBot:
         self.score_threshold = 0.8
         self.temperature = 0.1
         self.history = []
-        self.base_url = "https://shreyas094-searxng-local.hf.space/search"
+        self.base_url = "http://localhost:8888"
         self.headers = {
             "X-Searx-API-Key": "f9f07f93b37b8483aadb5ba717f556f3a4ac507b281b4ca01e6c6288aa3e3ae5"
         }
-        # Default search engines in case we can't fetch from SearxNG
         self.default_engines = ["google", "bing", "duckduckgo", "brave"]
 
     async def get_search_results(self, 
@@ -402,53 +401,63 @@ class ChatBot:
 def create_gradio_interface() -> gr.Interface:
     chatbot = ChatBot()
     
-    with gr.Blocks(theme=gr.themes.Soft()) as demo:
-        gr.Markdown("# Research Assistant")
-        gr.Markdown("Enter your search query, and I'll search, analyze, and summarize relevant articles for you.")
-        
+    # Create the interface with advanced styling
+    iface = gr.ChatInterface(
+        chatbot.chat,
+        title="Web Scraper for News with Sentinel AI",
+        description="Ask Sentinel any question. It will search the web for recent information or use its knowledge base as appropriate.",
+        theme=gr.Theme.from_hub("allenai/gradio-theme"),
+        additional_inputs=[
+            gr.Slider(minimum=5, maximum=30, value=10, step=1, label="Number of Results"),
+            gr.Slider(minimum=1000, maximum=50000, value=10000, step=1000, label="Max Characters per Article"),
+            gr.Slider(minimum=0.0, maximum=1.0, value=0.8, step=0.05, label="Score Threshold"),
+            gr.Slider(minimum=0.0, maximum=1.0, value=0.1, step=0.05, label="Temperature"),
+            gr.Radio(["BM25", "TF-IDF", "Combined"], value="Combined", label="Scoring Method"),
+            gr.CheckboxGroup(
+                choices=["google", "bing", "duckduckgo", "brave", "wikipedia"],
+                value=["google", "bing", "duckduckgo"],
+                label="Search Engines"
+            )
+        ],
+        additional_inputs_accordion=gr.Accordion("⚙️ Advanced Parameters", open=True),
+        retry_btn="Retry",
+        undo_btn="Undo",
+        clear_btn="Clear",
+        chatbot=gr.Chatbot(
+            show_copy_button=True,
+            likeable=True,
+            layout="bubble",
+            height=500,
+        )
+    )
+    
+    return iface
+
+def create_parameter_description():
+    return """
+    ### Parameter Descriptions
+    
+    - **Number of Results**: Number of search results to fetch
+    - **Max Characters**: Maximum characters to analyze per article
+    - **Score Threshold**: Minimum relevance score (0-1) for including articles
+    - **Temperature**: Controls creativity in summary generation (0=focused, 1=creative)
+    - **Scoring Method**: Algorithm for ranking article relevance
+        - BM25: Traditional keyword-based ranking
+        - TF-IDF: Semantic similarity-based ranking
+        - Combined: Balanced approach using both methods
+    - **Search Engines**: Select which search engines to use
+    """
+
+if __name__ == "__main__":
+    iface = create_gradio_interface()
+    
+    # Create the layout with two columns
+    with gr.Blocks(theme=gr.Theme.from_hub("allenai/gradio-theme")) as demo:
         with gr.Row():
             with gr.Column(scale=3):
-                chatbot_interface = gr.ChatInterface(
-                    fn=chatbot.chat,
-                    additional_inputs=[
-                        gr.Slider(minimum=5, maximum=30, value=10, step=1, label="Number of Results"),
-                        gr.Slider(minimum=1000, maximum=50000, value=10000, step=1000, label="Max Characters per Article"),
-                        gr.Slider(minimum=0.0, maximum=1.0, value=0.8, step=0.05, label="Score Threshold"),
-                        gr.Slider(minimum=0.0, maximum=1.0, value=0.1, step=0.05, label="Temperature"),
-                        gr.Radio(["BM25", "TF-IDF", "Combined"], value="Combined", label="Scoring Method"),
-                        gr.CheckboxGroup(
-                            choices=["google", "bing", "duckduckgo", "brave", "wikipedia"],
-                            value=["google", "bing", "duckduckgo"],
-                            label="Search Engines"
-                        )
-                    ],
-                    examples=[
-                        ["What are the latest developments in quantum computing?"],
-                        ["Explain the impact of artificial intelligence on healthcare"],
-                        ["What are the current trends in renewable energy?"]
-                    ]
-                )
-            
+                iface.render()
             with gr.Column(scale=1):
-                gr.Markdown("### Parameter Descriptions")
-                gr.Markdown("""
-                - **Number of Results**: Number of search results to fetch
-                - **Max Characters**: Maximum characters to analyze per article
-                - **Score Threshold**: Minimum relevance score (0-1) for including articles
-                - **Temperature**: Controls creativity in summary generation (0=focused, 1=creative)
-                - **Scoring Method**: Algorithm for ranking article relevance
-                    - BM25: Traditional keyword-based ranking
-                    - TF-IDF: Semantic similarity-based ranking
-                    - Combined: Balanced approach using both methods
-                - **Search Engines**: Select which search engines to use
-                """)
-
-    return demo
-
-if __name__ == "__main__":
-    # Configure logging
-    logging.basicConfig(level=logging.INFO, format='%(asctime)s %(levelname)s: %(message)s')
+                gr.Markdown(create_parameter_description())
     
-    # Create and launch the interface
-    demo = create_gradio_interface()
-    demo.launch(share=True)
+    # Launch the interface
+    demo.launch(server_name="0.0.0.0", server_port=7862, share=True)