Create app.py

app.py

@@ -0,0 +1,48 @@
+import gradio as gr
+from smolagents import CodeAgent, HfApiClient, DuckDuckGoSearchTool
+
+# Initialize search capability
+search_tool = DuckDuckGoSearchTool()
+
+# Set up Zquery1 agent with a highly optimized model for search task handling
+agent = CodeAgent(
+    tools=[search_tool],
+    model=HfApiClient("Qwen/Qwen2.5-72B-Instruct"),
+    system_prompt=(
+        "You are Zquery1, an advanced AI search engine. "
+        "Your task is to search the web for the user's query, extract relevant facts, "
+        "and synthesize a clean response. Always include clickable source links "
+        "using markdown format: [Site Name](URL). Never use raw URLs."
+    )
+)
+
+def respond(message, history):
+    try:
+        # Run agent search pipeline
+        bot_response = agent.run(message)
+        return str(bot_response)
+    except Exception as e:
+        return f"An error occurred while fetching live data: {str(e)}"
+
+# Custom CSS styling to make the embedded UI sleek and seamless
+custom_css = """
+footer {visibility: hidden}
+.gradio-container {background-color: transparent !important;}
+"""
+
+# Build interface configured for embedding
+with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# <center>🔍 Zquery1 Web Search Engine</center>")
+    
+    gr.ChatInterface(
+        fn=respond,
+        examples=[
+            "What are the top space discoveries this week?",
+            "Latest news about open source AI models",
+            "What is the current stock price of Apple?"
+        ],
+        cache_examples=False
+    )
+
+if __name__ == "__main__":
+    demo.launch()