Remove model status and run-complete banner

app.py

@@ -16,16 +16,11 @@ from config import ADAPTER_MODEL, AGENT_MAX_STEPS, DATA_DIR
 from examples import DEMO_DATASETS, DEMO_EXAMPLES
 
 MODEL, TOKENIZER = None, None
-MODEL_STATUS = "⏳ Model not loaded yet"
 STORY_URL = "https://datasense-e2b.netlify.app/"
 LINKEDIN_POST_URL = (
     "https://www.linkedin.com/posts/sanjaymalladi_buildsmall-huggingface-modal-share-7471993638814654464-47hY/"
 )
 
-
-def get_model_status() -> str:
-    return MODEL_STATUS
-
 CUSTOM_CSS = """
 @import url('https://fonts.googleapis.com/css2?family=IBM+Plex+Mono:wght@400;500&family=Newsreader:ital,opsz,wght@0,6..72,400;0,6..72,600;1,6..72,400&display=swap');
 
@@ -66,15 +61,6 @@ CUSTOM_CSS = """
   padding: 0.2rem 0.65rem;
   margin-bottom: 0.75rem;
 }
-#ds-status {
-  font-family: 'IBM Plex Mono', monospace;
-  font-size: 0.85rem;
-  background: var(--ds-surface);
-  border-left: 3px solid var(--ds-accent);
-  padding: 0.65rem 1rem;
-  border-radius: 0 8px 8px 0;
-  margin-bottom: 1rem;
-}
 #ds-panel {
   background: var(--ds-surface);
   border: 1px solid var(--ds-border);
@@ -117,12 +103,11 @@ def build_theme() -> gr.Theme:
 
 
 def _load_model():
-    global MODEL, TOKENIZER, MODEL_STATUS
+    global MODEL, TOKENIZER
     if MODEL is None or TOKENIZER is None:
         from model_loader import load_model_and_tokenizer
 
         MODEL, TOKENIZER = load_model_and_tokenizer()
-        MODEL_STATUS = f"✅ **SFT v1 ready** — `{ADAPTER_MODEL}`"
     return MODEL, TOKENIZER
 
 
@@ -155,15 +140,14 @@ def run_task(
     max_steps: int,
     progress=gr.Progress(),
 ):
-    empty = ("", "")
     if not task.strip():
-        return "⚠️ Enter a task question.", *empty
+        return "⚠️ Enter a task question.", ""
 
     progress(0.05, desc="Resolving dataset…")
     data_path = _resolve_data_path(data_mode, dataset_name, upload_file)
     if data_path is None:
         msg = "⚠️ Upload a `.csv` file first." if data_mode == "Upload your CSV" else f"⚠️ Dataset not found: {dataset_name}"
-        return msg, *empty
+        return msg, ""
 
     try:
         progress(0.15, desc="Loading Gemma-4 + SFT LoRA…")
@@ -178,32 +162,18 @@ def run_task(
             progress=progress,
         )
     except Exception as exc:
-        return f"**Error:** {exc}", *empty
+        return f"**Error:** {exc}", ""
 
     answer_block = f"## {result['answer']}" if result["answer"] else "_Could not parse an answer — check the execution trace._"
     if result.get("summary"):
         answer_block += f"\n\n{result['summary']}"
-    status = (
-        f"✅ **Live inference complete** — `{data_path.name}` · "
-        f"{int(max_steps)} max steps · real model + sandbox execution (not canned)"
-    )
 
-    return (
-        status,
-        answer_block,
-        result["steps_markdown"],
-    )
+    return answer_block, result["steps_markdown"]
 
 
 @spaces.GPU(duration=300)
 def preload_model():
-    global MODEL_STATUS
-    MODEL_STATUS = "⏳ Loading Gemma-4 + SFT LoRA on GPU…"
-    try:
-        _load_model()
-    except Exception as exc:
-        MODEL_STATUS = f"⚠️ **Model load failed:** {exc}"
-        raise
+    _load_model()
 
 
 def build_ui() -> gr.Blocks:
@@ -216,7 +186,6 @@ def build_ui() -> gr.Blocks:
                 """
 # DataSense E2B
 **Live inference** — Gemma-4 2B + SFT v1 writes Python, runs it on your CSV, reads real stdout/errors.
-Not canned responses; each run is a fresh agent loop on GPU.
                 """
             )
             gr.Markdown(
@@ -225,8 +194,6 @@ Not canned responses; each run is a fresh agent loop on GPU.
                 f"LoRA [`DataSense-Modal-E2B-SFT`](https://huggingface.co/{ADAPTER_MODEL})",
             )
 
-        model_status = gr.Markdown(get_model_status(), elem_id="ds-status")
-
         with gr.Row(equal_height=False):
             with gr.Column(scale=4, elem_id="ds-panel"):
                 gr.Markdown("### Configure")
@@ -274,7 +241,6 @@ Not canned responses; each run is a fresh agent loop on GPU.
                 )
 
             with gr.Column(scale=6):
-                run_status = gr.Markdown("_Ready — click Run to start live inference._", elem_id="ds-status")
                 with gr.Tabs():
                     with gr.Tab("✅ Answer"):
                         answer_out = gr.Markdown()
@@ -286,11 +252,9 @@ Not canned responses; each run is a fresh agent loop on GPU.
         run_btn.click(
             fn=run_task,
             inputs=[data_mode, dataset, upload, task, max_steps],
-            outputs=[run_status, answer_out, steps_out],
+            outputs=[answer_out, steps_out],
             show_progress="full",
-        ).then(fn=get_model_status, outputs=model_status)
-
-        demo.load(fn=get_model_status, outputs=model_status)
+        )
 
     return demo