Update app.py

app.py

@@ -1,28 +1,31 @@
 import gradio as gr
-from utils.run_pipeline_and_save import run_pipeline_and_save
+from utils.langgraph_pipeline import run_pipeline_and_save
 from utils.zip_output import zip_output
 
-import os
-os.environ["PYTORCH_SDP_ATTENTION"] = "math"
-
-def run_agents(prompt):
-    if not prompt.strip():
-        return "Please enter a prompt.", None, None
+def handle_run(prompt):
     chat_log, final_output = run_pipeline_and_save(prompt)
-    log_str = "\n\n".join([f"### {list(item.keys())[0]}\n{list(item.values())[0]}" for item in chat_log])
-    zip_path = zip_output()
-    return log_str, zip_path, "output/agent_log.json"
+    return (
+        [(f"{agent}", msg) for step in chat_log for agent, msg in step.items()],
+        "output/index.html",
+        "output/agent_log.json",
+        zip_output()
+    )
+
+with gr.Blocks() as demo:
+    gr.Markdown("# 🔗 Multi-Agent Collaboration with LangGraph")
+
+    prompt_input = gr.Textbox(label="Enter your prompt", lines=4, placeholder="Describe your product idea...")
+    submit_btn = gr.Button("Run Agents")
+
+    chatbox = gr.Chatbot(label="Agent Conversation Log")
+    html_out = gr.File(label="index.html")
+    log_out = gr.File(label="Agent Log")
+    zip_out = gr.File(label="ZIP Output")
 
-iface = gr.Interface(
-    fn=run_agents,
-    inputs=gr.Textbox(lines=10, label="Enter your product idea prompt"),
-    outputs=[
-        gr.Textbox(label="Agent Conversation Log", lines=20),
-        gr.File(label="Download UI Files (ZIP)"),
-        gr.File(label="Download Agent Log (JSON)"),
-    ],
-    title="Multi-Agent UI Generator",
-)
+    submit_btn.click(
+        fn=handle_run,
+        inputs=prompt_input,
+        outputs=[chatbox, html_out, log_out, zip_out]
+    )
 
-if __name__ == "__main__":
-    iface.launch()
+demo.launch()