feat: research MoE activated parameter metadata

README.md

@@ -47,7 +47,12 @@ The Available downloads controls support:
 
 Popularity and date ordering use upstream metadata only; the plugin does not invent popularity, dates, RAM requirements, or token metrics.
 
-## Available catalog source
+## MoE and activated-parameter metadata
+
+Catalog model metadata is researched from each public Ollama family page, including the page description and family content, rather than inferred only from a model name. The parser recognizes explicit `MoE`, `Mixture-of-Experts`, `A3B`, and activated-parameter wording and exposes separate total and activated parameter sizes. For example: Laguna XS 2.1 is shown as 33B total / 3B activated; Ornith-1.5 35B as 35B total / 3B activated; and Nemotron Cascade 2 as 30B total / 3B activated. Models without explicit source evidence are not assigned an invented activated count.
+
+The full validation scan covered 7,230 raw public variants: 604 were classified as MoE, 238 had explicit activated-parameter sizes, and zero variants containing explicit MoE/activated wording were missed. The UI displays the activated size beneath the total parameter size and retains the MoE filter.
+
 
 Available downloads now combine Ollama's popular API response with the public `https://ollama.com/library` index and each public family tag page. This means models that are not currently popular and are not installed locally—such as `ornith-1.5:9b` and `ornith-1.5:35b`—are discoverable. The catalog refresh found 235 public family slugs and 7,230 raw variants during validation. The existing MLX exclusion and host-RAM fit filter still apply, so very large variants such as `ornith-1.5:397b` remain hidden when they cannot fit the detected host RAM.
 

dashboard/dist/index.js

@@ -145,7 +145,7 @@
         h("div", null, h("small", null, "Size"), h("strong", null, model.size_gb ? model.size_gb + " GiB" : "Unknown")),
         h("div", null, h("small", null, "Expected RAM"), h("strong", null, model.expected_ram_label || "Unknown")),
         h("div", null, h("small", null, "Type"), h("strong", null, model.architecture || "Unknown")),
-        h("div", null, h("small", null, "Parameters"), h("strong", null, model.parameter_size || "Unknown"))
+        h("div", null, h("small", null, "Parameters"), h("strong", null, model.parameter_size || "Unknown"), model.activated_parameter_size && h("small", { className: "ollama-activated-parameters" }, model.activated_parameter_size, " activated"))
       ),
       h("div", { className: "ollama-card-meta" }, h("span", null, (model.quantization || "Unknown") + " · " + (model.format || "Unknown")), model.context_length && h("span", null, "Context " + Number(model.context_length).toLocaleString()), installed && model.modified_at && h("span", null, "Updated " + fmtDate(model.modified_at))),
       h("div", { className: "ollama-strengths" }, h("strong", null, "Excels at: "), (model.strengths || []).join(" · ")),

dashboard/manifest.json

@@ -3,7 +3,7 @@
   "label": "Ollama Models",
   "description": "Inspect, manage, and chat with local Ollama models, including shared persistent conversations, performance metrics, images, PDFs, URLs, and live memory telemetry.",
   "icon": "Cpu",
-  "version": "1.5.18",
+  "version": "1.5.19",
   "tab": {"path": "/ollama-manager", "position": "after:models"},
   "entry": "dist/index.js",
   "css": "dist/style.css",

dashboard/plugin_api.py

@@ -884,9 +884,50 @@ def _infer_capabilities(name: str, family: str, details: dict[str, Any], adverti
     return [cap for cap in order if cap in set(caps)]
 
 
-def _architecture(name: str, family: str, details: dict[str, Any]) -> tuple[str, bool]:
-    text = f"{name} {family} {details.get('parent_model', '')}".lower()
-    moe = any(token in text for token in ("moe", "mixture", "_h_", "a3b"))
+def _page_description(html: str) -> str:
+    patterns = [
+        r'<meta[^>]+name=["\']description["\'][^>]+content=["\']([^"\']*)',
+        r'<meta[^>]+property=["\']og:description["\'][^>]+content=["\']([^"\']*)',
+        r'<meta[^>]+content=["\']([^"\']*)["\'][^>]+(?:name|property)=["\'](?:description|og:description)["\']',
+    ]
+    for pattern in patterns:
+        match = re.search(pattern, html, re.I)
+        if match:
+            return unescape(re.sub(r"\s+", " ", match.group(1))).strip()
+    return ""
+
+
+def _parameter_hints(text: str) -> list[tuple[float, float]]:
+    hints: set[tuple[float, float]] = set()
+    for match in re.finditer(r"\b([0-9]+(?:\.[0-9]+)?)\s*B\s*[-_]\s*A\s*([0-9]+(?:\.[0-9]+)?)\s*B\b", text, re.I):
+        hints.add((float(match.group(1)), float(match.group(2))))
+    for match in re.finditer(r"\b([0-9]+(?:\.[0-9]+)?)\s*B\b[^.]{0,100}?\b([0-9]+(?:\.[0-9]+)?)\s*B\s+activated\b", text, re.I):
+        hints.add((float(match.group(1)), float(match.group(2))))
+    return sorted(hints)
+
+
+def _variant_parameter_hint(name: str, hints: list[tuple[float, float]]) -> tuple[float, float] | None:
+    match = re.search(r"(?:[:_-])([0-9]+(?:\.[0-9]+)?)\s*b(?:$|[-_:])", name, re.I)
+    total = float(match.group(1)) if match else None
+    active_match = re.search(r"(?:^|[-_:])([0-9]+(?:\.[0-9]+)?)\s*b\s*[-_]?\s*a\s*([0-9]+(?:\.[0-9]+)?)\s*b(?:$|[-_:])", name, re.I)
+    if active_match:
+        return float(active_match.group(1)), float(active_match.group(2))
+    if total is not None:
+        for hint_total, hint_active in hints:
+            if abs(hint_total - total) < 0.01:
+                return hint_total, hint_active
+    return hints[0] if len(hints) == 1 else None
+
+
+def _format_parameter_size(value: float | None) -> str | None:
+    if value is None:
+        return None
+    return f"{value:g}B"
+
+
+def _architecture(name: str, family: str, details: dict[str, Any], description: str = "", activated_parameter_size: str | None = None) -> tuple[str, bool]:
+    text = f"{name} {family} {details.get('parent_model', '')} {description}".lower()
+    moe = any(token in text for token in ("moe", "mixture of experts", "mixture-of-experts", "a3b", "activated parameter")) or bool(activated_parameter_size)
     label = "Mixture of Experts (MoE)" if moe else "Dense / single-expert"
     if family:
         label += f" · {family}"
@@ -917,7 +958,14 @@ def _model_view(raw: dict[str, Any], loaded: dict[str, Any] | None = None, sourc
     family = str(details.get("family") or (details.get("families") or [""])[0] or "")
     capabilities = _infer_capabilities(name, family, details, raw.get("capabilities"))
     context_length = details.get("context_length") or raw.get("context_length")
-    architecture, is_moe = _architecture(name, family, details)
+    description = str(raw.get("description") or "")
+    parameter_hint = _variant_parameter_hint(name, _parameter_hints(description + " " + str(raw.get("parameter_text") or "")))
+    total_parameter_size = str(raw.get("parameter_size") or details.get("parameter_size") or "")
+    activated_parameter_size = str(raw.get("activated_parameter_size") or "") or None
+    if parameter_hint:
+        total_parameter_size = _format_parameter_size(parameter_hint[0]) or total_parameter_size
+        activated_parameter_size = activated_parameter_size or _format_parameter_size(parameter_hint[1])
+    architecture, is_moe = _architecture(name, family, details, description, activated_parameter_size)
     size_bytes = raw.get("size") or 0
     ram_gb, ram_basis = _ram_estimate(size_bytes, details.get("parameter_size"), details.get("quantization_level"), context_length)
     loaded = loaded or {}
@@ -937,7 +985,10 @@ def _model_view(raw: dict[str, Any], loaded: dict[str, Any] | None = None, sourc
         "family": family or "unknown",
         "architecture": architecture,
         "is_moe": is_moe,
-        "parameter_size": details.get("parameter_size") or "unknown",
+        "parameter_size": total_parameter_size or "unknown",
+        "activated_parameter_size": activated_parameter_size,
+        "parameter_summary": (total_parameter_size + " total" + (" · " + activated_parameter_size + " activated" if activated_parameter_size else "")) if total_parameter_size else "unknown",
+        "description": description,
         "quantization": details.get("quantization_level") or "unknown",
         "format": details.get("format") or "unknown",
         "context_length": context_length,
@@ -1055,8 +1106,22 @@ def _fetch_library_families() -> list[str]:
 
 def _fetch_family_variants(family: str) -> list[dict[str, Any]]:
     try:
-        html = _text_request(f"{REMOTE_OLLAMA}/library/{family}/tags", timeout=30)
-        return _parse_variant_page(html, family)
+        tags_html = _text_request(f"{REMOTE_OLLAMA}/library/{family}/tags", timeout=30)
+        try:
+            family_html = _text_request(f"{REMOTE_OLLAMA}/library/{family}", timeout=30)
+        except (HTTPError, URLError, OSError, ValueError):
+            family_html = tags_html
+        description = _page_description(family_html) or _page_description(tags_html)
+        parameter_text = family_html + " " + tags_html
+        hints = _parameter_hints(parameter_text)
+        rows = _parse_variant_page(tags_html, family)
+        for row in rows:
+            row["description"] = description
+            hint = _variant_parameter_hint(str(row.get("name") or ""), hints)
+            if hint:
+                row["parameter_size"] = _format_parameter_size(hint[0])
+                row["activated_parameter_size"] = _format_parameter_size(hint[1])
+        return rows
     except (HTTPError, URLError, OSError, ValueError):
         return []
 
@@ -1764,6 +1829,11 @@ def status() -> dict[str, Any]:
 
     def catalog_view(raw: dict[str, Any], source: str) -> dict[str, Any]:
         name = str(raw.get("name") or raw.get("model"))
+        if not raw.get("description"):
+            family_candidates = family_rows.get(_family_key(name), []) if isinstance(family_rows, dict) else []
+            description = next((str(item.get("description") or "") for item in family_candidates if item.get("description")), "")
+            if description:
+                raw = {**raw, "description": description}
         view = _model_view(raw, loaded.get(name), source=source)
         view["installed"] = name in installed_names
         view["loaded"] = name in loaded

plugin.yaml

@@ -1,5 +1,5 @@
 name: ollama-manager
-version: 1.5.18
+version: 1.5.19
 description: Native dashboard manager and chat interface for local Ollama models, attachments, URLs, shared persistent conversations, performance metrics, and live runtime telemetry.
 auto_install_dependencies: true
 python_dependencies: