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gradio_app.py

@@ -133,15 +133,7 @@ def build_score_bars(obs):
 def do_reset(task_name):
     """Reset environment with selected task."""
     global current_obs, step_history
-    task_map = {
-        "Bell State (Easy)": "easy", 
-        "GHZ State (Medium)": "medium", 
-        "Unitary Approx (Hard)": "hard",
-        "Imperfect but Efficient": "efficient",
-        "Noise-Dominant": "noisy",
-        "Budgeted Optimization": "budget",
-        "Approximate Target": "approx"
-    }
+    task_map = {"Bell State (Easy)": "easy", "GHZ State (Medium)": "medium", "Unitary Approx (Hard)": "hard"}
     task_id = task_map.get(task_name, "easy")
     current_obs = env.reset(task_id=task_id)
     step_history = []
@@ -258,98 +250,6 @@ def do_step(action_type, gate_type, qubit_0, qubit_1, parameter):
         "\n".join(step_history),
     )
 
-def do_premade_scenario(scenario_name):
-    """Fast-forward through a preconfigured set of gates for visual demonstration."""
-    global current_obs, step_history
-    
-    scenarios = {
-        "Optimal Bell State": {
-            "task": "easy",
-            "actions": [
-                QuantumAction(action_type=ActionType.ADD, gate=GateType.H, qubits=[0]),
-                QuantumAction(action_type=ActionType.ADD, gate=GateType.CNOT, qubits=[0, 1]),
-                QuantumAction(action_type=ActionType.STOP)
-            ]
-        },
-        "Optimal GHZ State": {
-            "task": "medium",
-            "actions": [
-                QuantumAction(action_type=ActionType.ADD, gate=GateType.H, qubits=[0]),
-                QuantumAction(action_type=ActionType.ADD, gate=GateType.CNOT, qubits=[0, 1]),
-                QuantumAction(action_type=ActionType.ADD, gate=GateType.CNOT, qubits=[1, 2]),
-                QuantumAction(action_type=ActionType.STOP)
-            ]
-        },
-        "Budget Overflow (Failure Simulation)": {
-            "task": "budget",
-            "actions": [
-                QuantumAction(action_type=ActionType.ADD, gate=GateType.H, qubits=[0]),
-                QuantumAction(action_type=ActionType.ADD, gate=GateType.CNOT, qubits=[0, 1]),
-                QuantumAction(action_type=ActionType.ADD, gate=GateType.X, qubits=[1]),
-                QuantumAction(action_type=ActionType.ADD, gate=GateType.H, qubits=[2]),
-                QuantumAction(action_type=ActionType.STOP)
-            ]
-        },
-        "Noise Deep Circuit (Failure Simulation)": {
-            "task": "noisy",
-            "actions": [
-                QuantumAction(action_type=ActionType.ADD, gate=GateType.H, qubits=[0]),
-                QuantumAction(action_type=ActionType.ADD, gate=GateType.CNOT, qubits=[0, 1]),
-                QuantumAction(action_type=ActionType.ADD, gate=GateType.X, qubits=[1]),
-                QuantumAction(action_type=ActionType.ADD, gate=GateType.X, qubits=[1]),
-                QuantumAction(action_type=ActionType.ADD, gate=GateType.X, qubits=[1]),
-                QuantumAction(action_type=ActionType.ADD, gate=GateType.X, qubits=[1]),
-                QuantumAction(action_type=ActionType.STOP)
-            ]
-        }
-    }
-    
-    if scenario_name not in scenarios:
-         return "Invalid Scenario", "(none)", "", "{}", ""
-         
-    conf = scenarios[scenario_name]
-    
-    # Reset
-    current_obs = env.reset(task_id=conf["task"])
-    step_history = [f"--- Running Scenario: {scenario_name} ---"]
-    
-    for act in conf["actions"]:
-        current_obs = env.step(act)
-        
-        gate_str = ""
-        if act.gate:
-            gate_str = f" {act.gate.value}({','.join(str(q) for q in act.qubits)})"
-            
-        step_entry = (
-            f"Step {current_obs.steps_taken}: {act.action_type.value}"
-            + gate_str
-            + f" -> fid={current_obs.fidelity:.4f} score={current_obs.score:.4f}"
-            + f" reward={current_obs.reward:+.4f}"
-            + (" [DONE]" if current_obs.done else "")
-        )
-        step_history.append(step_entry)
-        
-    obs_json = format_obs_json(current_obs)
-    circuit_text = format_circuit_display(current_obs)
-    score_html = build_score_bars(current_obs)
-    
-    status = (
-        f"Scenario Complete: {scenario_name}\n"
-        + f"Step {current_obs.steps_taken}/{current_obs.max_steps}"
-        + f" | Fidelity: {current_obs.fidelity:.4f}"
-        + f" | Score: {current_obs.score:.4f}"
-        + f"\n\nEPISODE COMPLETE! Final score: {current_obs.score:.4f}"
-    )
-    
-    return (
-        status,
-        circuit_text,
-        score_html,
-        json.dumps(obs_json, indent=2),
-        "\n".join(step_history),
-    )
-
-
 
 # ---------------------------------------------------------------------------
 # Build Gradio UI
@@ -388,30 +288,13 @@ def create_gradio_app():
             with gr.Column(scale=1):
                 gr.Markdown("### 1. Select Task & Reset")
                 task_dropdown = gr.Dropdown(
-                    choices=[
-                        "Bell State (Easy)", "GHZ State (Medium)", "Unitary Approx (Hard)",
-                        "Imperfect but Efficient", "Noise-Dominant", 
-                        "Budgeted Optimization", "Approximate Target"
-                    ],
+                    choices=["Bell State (Easy)", "GHZ State (Medium)", "Unitary Approx (Hard)"],
                     value="Bell State (Easy)",
                     label="Task",
                 )
                 reset_btn = gr.Button("Reset Environment", variant="primary", size="lg")
 
-                gr.Markdown("### 2. Pre-made Scenarios")
-                scenario_dropdown = gr.Dropdown(
-                    choices=[
-                        "Optimal Bell State", 
-                        "Optimal GHZ State", 
-                        "Budget Overflow (Failure Simulation)", 
-                        "Noise Deep Circuit (Failure Simulation)"
-                    ],
-                    value="Optimal Bell State",
-                    label="Select Scenario"
-                )
-                scenario_btn = gr.Button("Run Scenario Fast-Forward", variant="secondary")
-
-                gr.Markdown("### 3. Build Circuit Manually")
+                gr.Markdown("### 2. Build Circuit")
                 action_dropdown = gr.Dropdown(
                     choices=["ADD", "REMOVE", "SWAP", "PARAM", "STOP"],
                     value="ADD",
@@ -457,8 +340,6 @@ def create_gradio_app():
         reset_outputs = [status_box, circuit_display, score_bars, json_display, history_display]
         reset_btn.click(fn=do_reset, inputs=[task_dropdown], outputs=reset_outputs)
 
-        scenario_btn.click(fn=do_premade_scenario, inputs=[scenario_dropdown], outputs=reset_outputs)
-
         step_outputs = [status_box, circuit_display, score_bars, json_display, history_display]
         step_btn.click(
             fn=do_step,

server/app.py

@@ -470,20 +470,9 @@ def create_gradio_app():
 
 
 # ---------------------------------------------------------------------------
-# ASGI Setup for Uvicorn Deployment on Hugging Face
+# Standalone entry point
 # ---------------------------------------------------------------------------
-from fastapi import FastAPI
-
-fastapi_app = FastAPI()
-
-@fastapi_app.get("/health")
-def health_check():
-    return {"status": "ok"}
-
-gradio_demo = create_gradio_app()
-app = gr.mount_gradio_app(fastapi_app, gradio_demo, path="/")
-
-
 if __name__ == "__main__":
-    import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=8000)
+    demo = create_gradio_app()
+    demo.launch(server_name="0.0.0.0", server_port=7860)
+