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app.py

@@ -151,6 +151,16 @@ CSS = """
   color: var(--ink);
 }
 
+.metric-card a {
+  color: var(--ink);
+  text-decoration: none;
+}
+
+.metric-card a:hover {
+  color: var(--accent-deep);
+  text-decoration: underline;
+}
+
 .guide-grid {
   display: grid;
   grid-template-columns: repeat(3, minmax(0, 1fr));
@@ -255,6 +265,15 @@ CSS = """
   box-shadow: var(--shadow);
 }
 
+.results-shell,
+.results-shell *,
+.results-shell p,
+.results-shell li,
+.results-shell strong,
+.results-shell code {
+  color: var(--ink) !important;
+}
+
 .explain-grid {
   display: grid;
   grid-template-columns: repeat(3, minmax(0, 1fr));
@@ -569,29 +588,21 @@ def _decorate_valid_rows(valid_rows: list[dict[str, Any]]) -> list[dict[str, Any
 
 def _build_summary(query_text: str, valid_rows: list[dict[str, Any]], invalid_rows: list[dict[str, Any]], warning: str | None) -> str:
     best = valid_rows[0] if valid_rows else None
-    score_range = None
-    if valid_rows:
-        raw_scores = [float(row["score"]) for row in valid_rows]
-        score_range = max(raw_scores) - min(raw_scores)
     chunks = [
-        "### Ranking Summary",
-        f"- Model repo: `{MODEL_REPO_ID}`",
-        f"- Assay fields serialized into `{len(query_text.split())}` words",
-        f"- Valid molecules ranked: `{len(valid_rows)}`",
-        f"- Invalid molecules rejected: `{len(invalid_rows)}`",
+        "### Ranked shortlist",
+        f"- Ranked candidates: `{len(valid_rows)}`",
     ]
+    if invalid_rows:
+        chunks.append(f"- Rejected inputs: `{len(invalid_rows)}`")
     if best is not None:
         chunks.append(
-            f"- Top hit: `{best['canonical_smiles']}` · `{best['priority_band']}` · list-relative score `{best['relative_score']:.1f}/100`"
+            f"- Top candidate: `{best['canonical_smiles']}` · `{best['priority_band']}` · relative score `{best['relative_score']:.1f}/100`"
         )
-    if score_range is not None:
-        chunks.append(f"- Score spread across this submitted list: `{score_range:.2f}` model-score units")
     if warning:
         chunks.append(f"- Warning: {warning}")
     chunks.append("")
     chunks.append(
-        "Use the **priority band** and **list-relative score** first. The raw model score is an uncalibrated logit-like ranking value. "
-        "A candidate with `relative score 100` is the strongest item in your submitted list, not in all chemistry."
+        "Use **priority** and **relative score** as the decision surface. `model_score` is an internal compatibility logit and should only be compared within this submitted list."
     )
     return "\n".join(chunks)
 
@@ -759,7 +770,7 @@ with gr.Blocks(title="BioAssayAlign Compatibility Explorer", analytics_enabled=F
             gr.HTML(
                 f"""
 <div class="metric-strip">
-  <div class="metric-card"><span>Model</span><strong>Qwen3-Embedding-0.6B compatibility scorer</strong></div>
+  <div class="metric-card"><span>Model</span><strong><a href="https://huggingface.co/{MODEL_REPO_ID}" target="_blank" rel="noopener">Qwen3-Embedding-0.6B compatibility scorer</a></strong></div>
   <div class="metric-card"><span>Input contract</span><strong>1 assay definition + up to {MAX_INPUT_SMILES} candidate SMILES</strong></div>
   <div class="metric-card"><span>Score semantics</span><strong>Use rank and relative score within the submitted list</strong></div>
 </div>