Update app.py

app.py

@@ -3,7 +3,7 @@ import gradio as gr
 import datetime
 import pytz
 import asyncio
-from typing import List, Dict
+from gradio import ChatMessage
 
 # Framework 1: LlamaIndex
 from llama_index.core.agent.workflow import AgentWorkflow
@@ -18,11 +18,11 @@ HF_TOKEN = os.getenv("HF_TOKEN")
 MODEL_ID = "Qwen/Qwen2.5-7B-Instruct"
 
 # ==========================================
-# AGENT SETUP
+# PART 1: AGENT LOGIC
 # ==========================================
 li_llm = HuggingFaceInferenceAPI(model_name=MODEL_ID, token=HF_TOKEN, provider="together")
 li_agent = AgentWorkflow.from_tools_or_functions(
-    [FunctionTool.from_defaults(fn=lambda: f"Time: {datetime.datetime.now(pytz.timezone('Asia/Tokyo'))}")],
+    [FunctionTool.from_defaults(fn=lambda: f"Current time: {datetime.datetime.now(pytz.timezone('Asia/Tokyo'))}")],
     llm=li_llm,
 )
 
@@ -30,68 +30,57 @@ smol_model = InferenceClientModel(model_id=MODEL_ID, token=HF_TOKEN, provider="t
 smol_agent = CodeAgent(model=smol_model, tools=[DuckDuckGoSearchTool()])
 
 # ==========================================
-# CHAT LOGIC (Gradio 6.0 Compatible)
+# PART 2: UI WRAPPERS (Gradio 6.0 Style)
 # ==========================================
 async def chat_llama(message, history):
-    # LlamaIndex run
+    # Workflow-based logic
     result = await li_agent.run(user_msg=message)
-    # We yield the final response
-    yield str(result)
+    return str(result)
 
 def chat_smol(message, history):
-    """
-    Simulates a 'Thinking' block before the final answer.
-    """
-    # 1. Send an initial 'Thinking' message using Gradio 6.0 Metadata
-    yield gr.ChatMessage(
+    # We yield a 'Thought' block first
+    yield ChatMessage(
         role="assistant", 
-        content="Searching for information and executing code...", 
-        metadata={"title": "🧠 Agent is thinking"}
+        content="I am searching the web and writing Python code to verify the details...",
+        metadata={"title": "🧠 Thinking Process", "status": "pending"}
     )
     
     try:
-        # 2. Run the actual agent
+        # Run agent
         response = smol_agent.run(message)
-        # 3. Yield the final answer as a normal message
-        yield str(response)
+        # Yield the final result (this replaces the previous yield in the UI)
+        yield ChatMessage(role="assistant", content=str(response))
     except Exception as e:
-        yield f"❌ Error: {str(e)}"
+        yield ChatMessage(role="assistant", content=f"❌ Error: {str(e)}")
 
 # ==========================================
-# ENHANCED UI LAYOUT
+# PART 3: THE UI LAYOUT
 # ==========================================
 with gr.Blocks(fill_height=True) as demo:
-    # Sidebar for Specs
-    with gr.Sidebar():
-        gr.Markdown("## 🛠️ Global Settings")
-        gr.Dropdown([MODEL_ID], label="Active Model", value=MODEL_ID)
-        gr.Markdown("---")
-        gr.Markdown("### Agent Capabilities")
-        gr.CheckboxGroup(["Search", "Time", "Python Code"], label="Tools Enabled", value=["Search", "Time", "Python Code"], interactive=False)
-        gr.Info("LlamaIndex is best for structured workflows. smolagents is best for dynamic code tasks.")
+    with gr.Row():
+        gr.Markdown(f"# 🤖 Multi-Agent Hub\nRunning `{MODEL_ID}` via Together AI", elem_id="header")
 
-    with gr.Column():
-        gr.Markdown(f"# 🤖 Multi-Agent Hub")
-        
-        with gr.Tabs():
-            # TAB 1: LLAMAINDEX
-            with gr.Tab("🏗️ LlamaIndex Workflow"):
-                gr.ChatInterface(
-                    fn=chat_llama,
-                    description="Specializes in persistent workflows and structured tool calling.",
-                    examples=["What's the current time in Tokyo?"],
-                    container=False
-                )
+    with gr.Tabs():
+        with gr.Tab("🏗️ LlamaIndex (Workflow)"):
+            gr.ChatInterface(
+                fn=chat_llama,
+                examples=["What time is it in Tokyo?"],
+                # 'container' removed to fix your error
+            )
+            gr.Info("Best for structured, multi-step business logic.")
 
-            # TAB 2: SMOLAGENTS
-            with gr.Tab("💻 smolagents CodeAgent"):
-                gr.ChatInterface(
-                    fn=chat_smol,
-                    description="Writes and runs Python code to solve complex reasoning tasks.",
-                    examples=["How many people live in Paris and New York combined?"],
-                    container=False
-                )
+        with gr.Tab("💻 smolagents (Code)"):
+            gr.ChatInterface(
+                fn=chat_smol,
+                examples=["Search for the latest stock price of Nvidia."],
+                # Customizing the chatbot component to look cleaner
+                chatbot=gr.Chatbot(label="Code Execution Agent", show_label=False)
+            )
+            gr.Warning("Best for dynamic problem solving and web searching.")
 
+# Launch with theme and CSS
 if __name__ == "__main__":
-    # Using a professional monochrome theme for the UI
-    demo.launch(theme=gr.themes.Monochrome())
+    demo.launch(
+        theme=gr.themes.Soft(),
+        css="#header { text-align: center; padding: 20px; }"
+    )