fix: remove cache_git submodule, update format and submission logic

.gitignore

@@ -1,4 +1,6 @@
 __pycache__/
 **/__pycache__/
 cache_hf
-.gradio
+.gradio
+cache_git
+

app.py

@@ -265,7 +265,7 @@ def submit_model(model, revision, private, compute_dtype, model_size_input):
     giving the user real-time progress updates.
     """
     if not model or model.strip() == "":
-        yield styled_error("Please enter a model name."); return
+        styled_error("Please enter a model name.")
     model_params_manual, err = _parse_model_size_input(model_size_input)
     if err:
         yield err; return
@@ -282,7 +282,7 @@ def submit_quant(model, revision, private, quant_scheme, model_size_input):
     giving the user real-time progress updates.
     """
     if not model or model.strip() == "":
-        yield styled_error("Please enter a model name."); return
+        styled_error("Please enter a model name.")
     model_params_manual, err = _parse_model_size_input(model_size_input)
     if err:
         yield err; return

src/display/formatting.py

@@ -1,3 +1,5 @@
+import gradio as gr
+
 def model_hyperlink(link, model_name):
     return f'<a target="_blank" href="{link}" style="color: var(--link-text-color); text-decoration: underline;text-decoration-style: dotted;">{model_name}</a>'
 
@@ -14,33 +16,57 @@ def make_clickable_model(model_name, result_file=""):
     return model_hyperlink(link, model_name) + "  " + model_hyperlink(details_link, "📑")
 
 def styled_error(error):
-    # Inject a JS alert so the message pops up, plus show inline as fallback
-    safe = error.replace("'", "\\'").replace("\n", " ")
-    return (
-        f"<script>setTimeout(function(){{alert('❌ ' + '{safe}');}}, 50);</script>"
-        f"<p style='color: red; font-size: 15px; text-align: center; margin-top: 8px;'>❌ {error}</p>"
-    )
+    raise gr.Error(error)
 
 
 def styled_warning(warn):
-    return f"<p style='color: orange; font-size: 20px; text-align: center;'>{warn}</p>"
+    raise gr.Warning(warn)
 
 
 def styled_message(message):
-    return f"<p style='color: green; font-size: 20px; text-align: center;'>{message}</p>"
+    gr.Info(message)
+    return ""
 
 
 def styled_progress(step: int, total: int, message: str) -> str:
     """Return a styled progress indicator (HTML)."""
     pct = int(step / total * 100) if total > 0 else 0
+    # Dots indicator: filled for completed steps, hollow for remaining
+    dots = "".join(
+        "<span style='display:inline-block;width:10px;height:10px;border-radius:50%;"
+        f"background:{'#2563eb' if i < step else '#cbd5e1'};"
+        "margin:0 3px;transition:background 0.3s;'></span>"
+        for i in range(total)
+    )
     return (
-        f"<div style='text-align:center; padding:10px;'>"
-        f"<p style='color: #2196F3; font-size: 16px; margin-bottom: 8px;'>⏳ {message}</p>"
-        f"<div style='background:#e0e0e0; border-radius:8px; height:20px; width:80%; margin:0 auto;'>"
-        f"<div style='background: linear-gradient(90deg, #2196F3, #21CBF3); height:100%; "
-        f"border-radius:8px; width:{pct}%; transition: width 0.3s;'></div>"
+        f"<div style='"
+        f"font-family:Manrope,sans-serif;"
+        f"background:linear-gradient(135deg,#eff6ff 0%,#f0fdf4 100%);"
+        f"border:1px solid #bfdbfe;"
+        f"border-radius:16px;"
+        f"padding:20px 28px;"
+        f"max-width:520px;"
+        f"margin:16px auto;"
+        f"box-shadow:0 4px 16px rgba(37,99,235,0.10);"
+        f"'>"
+        # Step label
+        f"<div style='display:flex;align-items:center;justify-content:space-between;margin-bottom:12px;'>"
+        f"<span style='font-size:14px;font-weight:600;color:#1e3a8a;'>⚙ {message}</span>"
+        f"<span style='font-size:12px;font-weight:700;color:#2563eb;"
+        f"background:#dbeafe;border-radius:20px;padding:2px 10px;'>{step}/{total}</span>"
+        f"</div>"
+        # Progress bar
+        f"<div style='background:#e2e8f0;border-radius:999px;height:8px;overflow:hidden;'>"
+        f"<div style='height:100%;width:{pct}%;"
+        f"background:linear-gradient(90deg,#2563eb,#38bdf8);"
+        f"border-radius:999px;"
+        f"transition:width 0.4s cubic-bezier(.4,0,.2,1);'>"
+        f"</div></div>"
+        # Dots + percentage
+        f"<div style='display:flex;align-items:center;justify-content:space-between;margin-top:10px;'>"
+        f"<div>{dots}</div>"
+        f"<span style='font-size:12px;color:#64748b;font-weight:600;'>{pct}%</span>"
         f"</div>"
-        f"<p style='color: #666; font-size: 13px; margin-top: 4px;'>{step}/{total} — {pct}%</p>"
         f"</div>"
     )
 

src/submission/submit.py

@@ -327,7 +327,7 @@ def add_new_eval(
     )
 
     if (not model_on_hub or model_config is None) and (not gguf_on_hub or gguf_files is None):
-        yield styled_error(f'Model "{model}" {hub_error}'); return
+        styled_error(f'Model "{model}" {hub_error}')
 
     if model_config is not None:
         architectures = getattr(model_config, "architectures", None)
@@ -353,10 +353,10 @@ def add_new_eval(
         )
         if scheme is None:
             supported = ", ".join(SUPPORTED_QUANT_SCHEMES.keys())
-            yield styled_error(
+            styled_error(
                 f'Unsupported quantization scheme "{compute_dtype}". '
                 f"Currently supported: {supported}."
-            ); return
+            )
         if not is_valid:
             msg = (
                 f"Only {scheme.name} quantized models are supported for evaluation. "
@@ -368,14 +368,14 @@ def add_new_eval(
                 + " Please submit a model quantized with GPTQ, AWQ, AutoRound, "
                 "BitsAndBytes (NF4/FP4), HQQ, or a similar method."
             )
-            yield styled_error(msg); return
+            styled_error(msg)
 
     # ── Fetch model info / license / model card ──────────────────────
     try:
         model_info = API.model_info(repo_id=model, revision=revision)
     except Exception:
         logger.error("Failed to fetch model info for %s", model, exc_info=True)
-        yield styled_error("Could not get your model information. Please fill it up properly."); return
+        styled_error("Could not get your model information. Please fill it up properly.")
 
     license_str = _get_license(model_info)
     _ok, _err, model_card = check_model_card(model)
@@ -409,11 +409,11 @@ def add_new_eval(
         )
 
     if not model_params:
-        yield styled_error(
+        styled_error(
             "Could not determine model parameter count automatically. "
             "Please enter the model size (in billions of parameters) in the "
             "'Model size' input field and re-submit."
-        ); return
+        )
 
     size_err = check_model_size_limit(model_params)
     if size_err:
@@ -484,7 +484,7 @@ def add_new_eval(
     # ── Duplicate check ──────────────────────────────────────────────
     dedup_key = f"{model}_{revision}_{quant_type}_{precision}_{weight_dtype}_{compute_dtype}"
     if dedup_key in _EVAL_REQUESTED:
-        yield styled_warning("This model has been already submitted."); return
+        styled_warning("This model has been already submitted.")
 
     # ── Upload ───────────────────────────────────────────────────────
     file_tag = (
@@ -494,7 +494,7 @@ def add_new_eval(
     try:
         _upload_to_hub(eval_entry, user_name, model_path, file_tag, model, task_label="eval")
     except Exception:
-        yield styled_error("Submission upload failed. Please try again later."); return
+        styled_error("Submission upload failed. Please try again later.")
 
     yield styled_message(
         "Your request has been submitted to the evaluation queue!\n"
@@ -548,10 +548,10 @@ def add_new_quant(
     scheme = SUPPORTED_QUANT_SCHEMES.get(quant_scheme)
     if scheme is None:
         supported = ", ".join(SUPPORTED_QUANT_SCHEMES.keys())
-        yield styled_error(
+        styled_error(
             f'Unsupported quantization scheme "{quant_scheme}". '
             f"Currently supported: {supported}."
-        ); return
+        )
 
     # ── Step 1b: Validate input model (must be FP, not quantized) ────
     yield styled_progress(3, TOTAL_STEPS, "Checking model on HuggingFace Hub …")
@@ -559,7 +559,7 @@ def add_new_quant(
         model_name=model, revision=revision, test_tokenizer=True,
     )
     if not model_on_hub or model_config is None:
-        yield styled_error(f'Model "{model}" {hub_error}'); return
+        styled_error(f'Model "{model}" {hub_error}')
 
     architecture = "?"
     architectures = getattr(model_config, "architectures", None)
@@ -570,11 +570,11 @@ def add_new_quant(
 
     quantization_config = getattr(model_config, "quantization_config", None)
     if quantization_config:
-        yield styled_error(
+        styled_error(
             "The submitted model appears to already be quantized. "
             "auto_quant expects a full-precision (float32/float16/bfloat16) model as input. "
             "If you want to evaluate an already-quantized model, use auto_eval instead."
-        ); return
+        )
 
     # Detect input dtype
     torch_dtype = getattr(model_config, "torch_dtype", None)
@@ -582,17 +582,17 @@ def add_new_quant(
     input_bits = SUPPORTED_INPUT_DTYPES.get(input_dtype)
     if input_bits is None:
         supported_dtypes = ", ".join(SUPPORTED_INPUT_DTYPES.keys())
-        yield styled_error(
+        styled_error(
             f'Model dtype "{input_dtype}" is not supported for quantization. '
             f"Supported input dtypes: {supported_dtypes}."
-        ); return
+        )
 
     # ── Fetch model info / license / model card ──────────────────────
     try:
         model_info = API.model_info(repo_id=model, revision=revision)
     except Exception:
         logger.error("Failed to fetch model info for %s", model, exc_info=True)
-        yield styled_error("Could not get your model information. Please fill it up properly."); return
+        styled_error("Could not get your model information. Please fill it up properly.")
 
     license_str = _get_license(model_info)
     _ok, _err, model_card = check_model_card(model)
@@ -607,11 +607,11 @@ def add_new_quant(
         fp_label = "16bit" if input_bits == 16 else "32bit"
         model_params, model_weight_gb = get_model_size(model_info, precision=fp_label)
         if not model_params:
-            yield styled_error(
+            styled_error(
                 "Could not determine model parameter count automatically. "
                 "Please enter the model size (in billions of parameters) in the "
                 "'Model size' input field and re-submit."
-            ); return
+            )
 
     size_err = check_model_size_limit(model_params)
     if size_err:
@@ -626,10 +626,10 @@ def add_new_quant(
     yield styled_progress(5, TOTAL_STEPS, "Estimating VRAM & selecting GPU …")
     num_layers = get_num_layers(model_config)
     if num_layers is None or num_layers <= 0:
-        yield styled_error(
+        styled_error(
             "Could not determine the number of layers in the model. "
             "This is required to estimate quantization memory."
-        ); return
+        )
 
     quant_memory_gb = estimate_quantization_memory_gb(
         model_weight_gb=model_weight_gb,
@@ -717,7 +717,7 @@ def add_new_quant(
     # ── Duplicate check ──────────────────────────────────────────────
     dedup_key = f"{model}_{revision}_{scheme.name}_{scheme.precision}_{scheme.weight_dtype}_{scheme.hardware}"
     if dedup_key in _QUANT_REQUESTED:
-        yield styled_warning("This model has been already submitted for quantization."); return
+        styled_warning("This model has been already submitted for quantization.")
 
     # ── Upload ───────────────────────────────────────────────────────
     file_tag = (
@@ -727,7 +727,7 @@ def add_new_quant(
     try:
         _upload_to_hub(quant_entry, user_name, model_path, file_tag, model, task_label="quant")
     except Exception:
-        yield styled_error("Quantization submission upload failed. Please try again later."); return
+        styled_error("Quantization submission upload failed. Please try again later.")
 
     yield styled_message(
         "Your quantization request has been submitted!\n"