Update app.py

app.py

@@ -5,6 +5,7 @@ import os
 import base64
 import io
 from PIL import Image
+from typing import List, Dict
 
 # --- 1. CONFIGURATION ---
 NEBIUS_API_KEY = os.environ.get("NEBIUS_API_KEY")
@@ -40,7 +41,7 @@ def tool_generate_image(prompt: str):
             n=1,
             size="1024x1024",
             response_format="b64_json",
-            style="flat",
+            style="flat", # Note: Check if your API supports this specific param, standard OpenAI doesn't always
         )
         b64_data = response.data[0].b64_json
         image_bytes = base64.b64decode(b64_data)
@@ -119,11 +120,17 @@ def run_autonomous_agent(company_name, business_type, style, progress=gr.Progres
 
 # --- 4. BRAND CONSULTANT CHATBOT ---
 def chat_response(message, history):
+    # History in Gradio 'type="messages"' is a list of dicts: [{'role':'user', 'content':'...'}, ...]
     system_message = "You are a creative brand consultant."
     messages = [{"role": "system", "content": system_message}]
+    
+    # Append existing history
     for msg in history:
-        messages.append({"role": msg["role"], "content": msg["content"]})
+        messages.append(msg)
+    
+    # Append current message
     messages.append({"role": "user", "content": message})
+    
     try:
         response = nebius_client.chat.completions.create(
             messages=messages,
@@ -131,6 +138,10 @@ def chat_response(message, history):
             max_tokens=300,
         )
         bot_reply = response.choices[0].message.content
+        
+        # In Gradio type="messages", we return the text for the specific turn if we are using an iterator, 
+        # OR we return the updated history list.
+        # Here we manually update history and return it + empty string for input clearing.
         history.append({"role": "user", "content": message})
         history.append({"role": "assistant", "content": bot_reply})
         return history, ""
@@ -138,8 +149,10 @@ def chat_response(message, history):
         history.append({"role": "assistant", "content": f"Error: {e}"})
         return history, ""
 
-# --- 5. GRADIO 6 UI ---
-with gr.Blocks() as demo:
+# --- 5. GRADIO UI ---
+# Moved 'title' here inside Blocks()
+with gr.Blocks(title="AutoBrand MCP Studio", theme=gr.themes.Soft()) as demo:
+    
     # --- Custom CSS for colors & style ---
     gr.HTML("""
     <style>
@@ -152,7 +165,7 @@ with gr.Blocks() as demo:
     # HEADER
     with gr.Column(elem_id="main-header"):
         gr.Markdown("# 🖼️ AutoBrand Studio")
-        gr.Markdown("Autonomous Agent powered by AI Models, MCP Tools & Web Search. Connect Claude Desktop to use these tools!")
+        gr.Markdown("Autonomous Agent powered by AI Models, MCP Tools & Web Search.")
 
     with gr.Row():
         # LEFT PANEL
@@ -161,7 +174,9 @@ with gr.Blocks() as demo:
             company_input = gr.Textbox(label="Company Name", value="Lumina")
             type_input = gr.Textbox(label="Business Type", value="Organic Candle Shop")
             style_input = gr.Textbox(label="Style / Vibe", value="Minimalist, calming")
+            
             generate_btn = gr.Button("✨ Generate Brand Kit", variant="primary")
+            
             gr.Markdown("### ⚙️ System Logs")
             out_log = gr.TextArea(label="Agent Log", lines=15)
 
@@ -175,7 +190,8 @@ with gr.Blocks() as demo:
                     out_copy = gr.TextArea(label="Generated Social Content", lines=15, interactive=False)
 
                 with gr.TabItem("💬 Brand Consultant"):
-                    chatbot = gr.Chatbot(label="AI Consultant", height=650)
+                    # Updated to type="messages" to support List[Dict] history
+                    chatbot = gr.Chatbot(label="AI Consultant", height=600, type="messages")
                     chat_input = gr.Textbox(show_label=False, placeholder="Ask something...")
                     chat_btn = gr.Button("Send")
 
@@ -196,7 +212,7 @@ with gr.Blocks() as demo:
     chat_btn.click(chat_response, [chat_input, chatbot], [chatbot, chat_input])
     chat_input.submit(chat_response, [chat_input, chatbot], [chatbot, chat_input])
 
-    # MCP TOOLS (Hidden)
+    # MCP TOOLS (Hidden elements to expose API endpoints)
     with gr.Row(visible=False):
         search_in = gr.Textbox()
         search_out = gr.Textbox()
@@ -214,4 +230,6 @@ with gr.Blocks() as demo:
         btn_summarize.click(tool_summarize_market_insights, inputs=summarize_in, outputs=summarize_out, api_name="summarize_market_insights")
 
 if __name__ == "__main__":
-    demo.launch(title="AutoBrand MCP Studio", ssr_mode=False, mcp_server=True)
+    # Removed 'title' from launch()
+    # Removed 'mcp_server' (unless you are using a specific custom fork, standard Gradio launch doesn't take this kwarg)
+    demo.launch(ssr_mode=False)