Create app.py

app.py

@@ -0,0 +1,55 @@
+import gradio as gr
+from orchestrator import run_workflow
+
+def launch_app(problem, agent_order, bias_mode, human_override, human_text):
+    outputs = run_workflow(problem, agent_order, bias_mode)
+
+    final = outputs["Final Recommendation"]
+
+    if human_override:
+        final = f"HUMAN OVERRIDE APPLIED:\n\n{human_text}"
+
+    return (
+        outputs.get("Market", ""),
+        outputs.get("Finance", ""),
+        outputs.get("Risk", ""),
+        outputs.get("Ethics", ""),
+        final
+    )
+
+with gr.Blocks(title="AI Strategy Lab") as demo:
+    gr.Markdown("# 🧠 AI Strategy Lab")
+    gr.Markdown("**Multi-Agent AI | Workflow Order | Human-in-the-Loop**")
+
+    problem = gr.Textbox(label="Problem Statement", lines=4)
+
+    agent_order = gr.CheckboxGroup(
+        ["Market", "Finance", "Risk", "Ethics"],
+        value=["Market", "Finance", "Risk", "Ethics"],
+        label="Agent Execution Order (ORDER MATTERS!)"
+    )
+
+    bias_mode = gr.Checkbox(label="Inject Market Optimism Bias")
+    human_override = gr.Checkbox(label="Enable Human Override")
+    human_text = gr.Textbox(label="Human Decision", lines=3)
+
+    run = gr.Button("🚀 Run AI Strategy Lab")
+
+    with gr.Tab("Market Agent"):
+        market_out = gr.Textbox(lines=10)
+    with gr.Tab("Finance Agent"):
+        finance_out = gr.Textbox(lines=10)
+    with gr.Tab("Risk Agent"):
+        risk_out = gr.Textbox(lines=10)
+    with gr.Tab("Ethics Agent"):
+        ethics_out = gr.Textbox(lines=10)
+    with gr.Tab("Final Decision"):
+        final_out = gr.Textbox(lines=12)
+
+    run.click(
+        launch_app,
+        inputs=[problem, agent_order, bias_mode, human_override, human_text],
+        outputs=[market_out, finance_out, risk_out, ethics_out, final_out]
+    )
+
+demo.launch()