Default sponsor model passes on

app.py

@@ -1088,27 +1088,27 @@ with gr.Blocks() as demo:
     with gr.Sidebar():
         gr.LoginButton()
         use_model_summary = gr.Checkbox(
-            value=False,
+            value=True,
             label="Add optional Mellum model summary",
-            info="Deterministic review works without network or GPU. OAuth/HF_TOKEN enables the sponsor-model summary.",
+            info="Tries local /data checkpoint first, then OAuth/HF_TOKEN provider, with deterministic fallback.",
         )
         use_nemotron_router = gr.Checkbox(
-            value=False,
+            value=True,
             label="Run Nemotron 3 Nano router",
-            info=f"Uses {NEMOTRON_MODEL} when OAuth/HF_TOKEN is available.",
+            info=f"Uses local /data checkpoint or {NEMOTRON_MODEL}.",
         )
         use_tiny_titan = gr.Checkbox(
-            value=False,
+            value=True,
             label="Run Tiny Titan 4B checker",
-            info=f"Uses {TINY_TITAN_MODEL} when OAuth/HF_TOKEN is available.",
+            info=f"Uses local /data checkpoint or {TINY_TITAN_MODEL}.",
         )
         use_minicpm_vision = gr.Checkbox(
-            value=False,
+            value=True,
             label="Run MiniCPM-V 4.6 vision",
-            info=f"Uses {MINICPM_MODEL} on uploaded PR images.",
+            info=f"Uses uploaded PR images with local /data checkpoint or {MINICPM_MODEL}.",
         )
         use_modal_bridge = gr.Checkbox(
-            value=False,
+            value=True,
             label="Send payload to Modal bridge",
             info="Uses DIFFSENSE_MODAL_ENDPOINT when configured.",
         )
@@ -1136,7 +1136,7 @@ with gr.Blocks() as demo:
                 label="Reviewer summary",
             )
             agent_output = gr.Markdown(
-                value="Enable Nemotron or MiniCPM-V to see model-agent traces here.",
+                value="### Model Runtime Status\n\n" + render_model_runtime_status(),
                 label="Model agent trace",
             )
             json_output = gr.JSON(label="Structured findings")