Update app.py

app.py

@@ -3,6 +3,7 @@ import gradio as gr
 import datetime
 import pytz
 import asyncio
+from typing import List, Dict
 
 # Framework 1: LlamaIndex
 from llama_index.core.agent.workflow import AgentWorkflow
@@ -16,79 +17,81 @@ from smolagents import CodeAgent, DuckDuckGoSearchTool, tool, InferenceClientMod
 HF_TOKEN = os.getenv("HF_TOKEN")
 MODEL_ID = "Qwen/Qwen2.5-7B-Instruct"
 
-# CUSTOM CSS for centering the header
-custom_css = ".agent-header { text-align: center; margin-bottom: 20px; }"
-
 # ==========================================
-# PART 1: LLAMAINDEX AGENT
+# AGENT SETUP
 # ==========================================
 li_llm = HuggingFaceInferenceAPI(model_name=MODEL_ID, token=HF_TOKEN, provider="together")
-
-def get_tokyo_time() -> str:
-    """Returns the current time in Tokyo, Japan."""
-    tz = pytz.timezone('Asia/Tokyo')
-    return f"The current time in Tokyo is {datetime.datetime.now(tz).strftime('%H:%M:%S')}"
-
 li_agent = AgentWorkflow.from_tools_or_functions(
-    [FunctionTool.from_defaults(fn=get_tokyo_time)],
+    [FunctionTool.from_defaults(fn=lambda: f"Time: {datetime.datetime.now(pytz.timezone('Asia/Tokyo'))}")],
     llm=li_llm,
 )
 
-async def chat_llama(message, history):
-    try:
-        # history is now a list of dicts, but LlamaIndex run() handles the new message
-        result = await li_agent.run(user_msg=message)
-        return str(result)
-    except Exception as e:
-        return f"❌ LlamaIndex Error: {str(e)}"
+smol_model = InferenceClientModel(model_id=MODEL_ID, token=HF_TOKEN, provider="together")
+smol_agent = CodeAgent(model=smol_model, tools=[DuckDuckGoSearchTool()])
 
 # ==========================================
-# PART 2: SMOLAGENTS
+# CHAT LOGIC (Gradio 6.0 Compatible)
 # ==========================================
-smol_model = InferenceClientModel(model_id=MODEL_ID, token=HF_TOKEN, provider="together")
+async def chat_llama(message, history):
+    # LlamaIndex run
+    result = await li_agent.run(user_msg=message)
+    # We yield the final response
+    yield str(result)
 
-@tool
-def weather_tool(location: str) -> str:
+def chat_smol(message, history):
     """
-    Get the current weather for a location.
-
-    Args:
-        location: The city and country, e.g., 'London, UK'.
+    Simulates a 'Thinking' block before the final answer.
     """
-    return f"The weather in {location} is currently sunny and 22°C."
-
-smol_agent = CodeAgent(
-    model=smol_model,
-    tools=[weather_tool, DuckDuckGoSearchTool()]
-)
-
-def chat_smol(message, history):
+    # 1. Send an initial 'Thinking' message using Gradio 6.0 Metadata
+    yield gr.ChatMessage(
+        role="assistant", 
+        content="Searching for information and executing code...", 
+        metadata={"title": "🧠 Agent is thinking"}
+    )
+    
     try:
-        # smol_agent.run returns the final answer string
+        # 2. Run the actual agent
         response = smol_agent.run(message)
-        return str(response)
+        # 3. Yield the final answer as a normal message
+        yield str(response)
     except Exception as e:
-        return f"❌ Smolagents Error: {str(e)}"
+        yield f"❌ Error: {str(e)}"
 
 # ==========================================
-# PART 3: GRADIO 6.0 UI
+# ENHANCED UI LAYOUT
 # ==========================================
-with gr.Blocks() as demo:
-    gr.Markdown(f"# 🤖 AI Agent Playground\n**Model:** `{MODEL_ID}`", elem_classes="agent-header")
-
-    with gr.Tabs():
-        with gr.Tab("🏗️ LlamaIndex (Workflows)"):
-            gr.ChatInterface(
-                fn=chat_llama,
-                examples=["What time is it in Tokyo?"]
-            )
+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.Column():
+        gr.Markdown(f"# 🤖 Multi-Agent Hub")
         
-        with gr.Tab("💻 smolagents (Code Execution)"):
-            gr.ChatInterface(
-                fn=chat_smol,
-                examples=["What is the weather in Paris?", "Search for 2026 AI trends."]
-            )
+        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
+                )
+
+            # 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
+                )
 
 if __name__ == "__main__":
-    # In Gradio 6.0, theme and css MUST go in launch()
-    demo.launch(theme=gr.themes.Soft(), css=custom_css)
+    # Using a professional monochrome theme for the UI
+    demo.launch(theme=gr.themes.Monochrome())