Create app.py

app.py

@@ -0,0 +1,122 @@
+import gradio as gr
+from gradio import ChatMessage
+import time
+import random
+
+def calculator_tool(expression):
+    """Simple calculator tool"""
+    try:
+        return eval(expression)
+    except:
+        return "Error: Could not evaluate expression"
+
+def weather_tool(location):
+    """Simulated weather tool"""
+    conditions = ["sunny", "cloudy", "rainy", "snowy"]
+    temp = random.randint(0, 35)
+    return f"{random.choice(conditions)}, {temp}°C in {location}"
+
+def agent_with_tools(query, history):
+    
+    # Initial thinking
+    thinking = ChatMessage(
+        role="assistant",
+        content="Let me think about this query...",
+        metadata={"title": "🧠 Thinking", "id": 1}
+    )
+    history.append(thinking)
+    yield history
+    
+    # Decide which tool to use based on query
+    if "calculate" in query.lower() or any(op in query for op in ['+', '-', '*', '/']):
+        # Extract the expression (simplified for demo)
+        expression = query.split("calculate")[-1].strip() if "calculate" in query.lower() else query
+        
+        # Show tool usage as nested thought
+        tool_call = ChatMessage(
+            role="assistant",
+            content=f"Expression to evaluate: {expression}",
+            metadata={
+                "title": "🧮 Calculator Tool", 
+                "parent_id": 1,
+                "id": 2,
+                "status": "pending"
+            }
+        )
+        history.append(tool_call)
+        yield history
+        
+        # Simulate calculation time
+        time.sleep(1)
+        
+        # Get result and update tool call
+        result = calculator_tool(expression)
+        tool_call.content = f"Expression: {expression}\nResult: {result}"
+        tool_call.metadata["status"] = "done"
+        tool_call.metadata["duration"] = 0.8  # Simulated duration
+        yield history
+        
+        # Final response
+        response = ChatMessage(
+            role="assistant",
+            content=f"I calculated that for you. The result is {result}."
+        )
+        
+    elif "weather" in query.lower():
+        # Extract location (simplified)
+        location = query.split("weather in")[-1].strip() if "weather in" in query.lower() else "your location"
+        
+        # Show tool usage
+        tool_call = ChatMessage(
+            role="assistant",
+            content=f"Checking weather for: {location}",
+            metadata={
+                "title": "🌤️ Weather Tool", 
+                "parent_id": 1,
+                "id": 2,
+                "status": "pending"
+            }
+        )
+        history.append(tool_call)
+        yield history
+        
+        # Simulate API call
+        time.sleep(1.5)
+        
+        # Get result and update tool call
+        result = weather_tool(location)
+        tool_call.content = f"Location: {location}\nCurrent conditions: {result}"
+        tool_call.metadata["status"] = "done"
+        tool_call.metadata["duration"] = 1.2  # Simulated duration
+        yield history
+        
+        # Final response
+        response = ChatMessage(
+            role="assistant",
+            content=f"I checked the weather for you. It's currently {result}."
+        )
+    else:
+        # Default response for other queries
+        time.sleep(1)
+        response = ChatMessage(
+            role="assistant",
+            content=f"I understand you're asking about '{query}', but I don't have a specific tool for that. I can help with calculations or weather."
+        )
+    
+    # Add final response
+    history.append(response)
+    yield history
+
+demo = gr.ChatInterface(
+    agent_with_tools,
+    title="Sample Agents with Tool Visualization using gr.ChatMessage",
+    description="Ask me to calculate something or check the weather!",
+    examples=[
+        "Calculate 145 * 32", 
+        "What's the weather in Tokyo?",
+        "Tell me about quantum physics"
+    ],
+    type="messages"
+)
+
+demo.launch()