chore: auto-commit (61 archivos)

- docs/capabilities/INDEX.md
- docs/capabilities/comfyui.md
- python/functions/browser/comfyui_export_workflow_ui.md
- python/functions/browser/comfyui_export_workflow_ui.py
- python/functions/browser/comfyui_load_workflow_ui.md
- python/functions/browser/comfyui_load_workflow_ui.py
- python/functions/browser/comfyui_queue_prompt_ui.md
- python/functions/browser/comfyui_queue_prompt_ui.py
- python/functions/browser/comfyui_refresh_nodes_ui.md
- python/functions/browser/comfyui_refresh_nodes_ui.py
- ...

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

python/functions/ml/comfyui_search_civitai_models.py

@@ -0,0 +1,101 @@
+"""Busca modelos / LoRAs en Civitai via su API publica GET /api/v1/models.
+
+Normaliza cada resultado a un dict pequeno y reutilizable
+({name, type, base_model, version_id, download_url, nsfw}) tomando la primera
+version del modelo. La busqueda publica funciona sin token; pasar un token solo
+sube el rate limit y desbloquea modelos restringidos.
+
+Impura: red (HTTP GET a civitai.com). Solo stdlib (urllib, json).
+"""
+import json
+import urllib.error
+import urllib.parse
+import urllib.request
+
+_API = "https://civitai.com/api/v1/models"
+_TIMEOUT = 30.0
+
+
+def comfyui_search_civitai_models(
+    query: str,
+    *,
+    types: str = "Checkpoint",
+    base_model: str | None = None,
+    sort: str = "Highest Rated",
+    limit: int = 20,
+    token: str | None = None,
+) -> dict:
+    """Busca modelos en Civitai y devuelve resultados normalizados.
+
+    Args:
+        query: texto de busqueda (nombre del modelo, ej. "dreamshaper").
+        types: tipo(s) de modelo, CSV. Valores Civitai: Checkpoint, LORA,
+            TextualInversion, Controlnet, VAE, Upscaler, ... keyword-only.
+        base_model: filtra por modelo base (ej. "SD 1.5", "SDXL 1.0"). None no
+            filtra. keyword-only.
+        sort: orden Civitai ("Highest Rated", "Most Downloaded", "Newest").
+            keyword-only.
+        limit: numero maximo de resultados (1-100). keyword-only.
+        token: API token de Civitai (header Authorization Bearer). Opcional: la
+            busqueda publica funciona sin el. No hardcodear: pasar desde
+            pass/vault. keyword-only.
+
+    Returns:
+        dict {ok, items, count, error}. items es una lista de
+        {name, type, base_model, version_id, download_url, nsfw} (la primera
+        version de cada modelo). ok=False con error si la peticion falla; una
+        busqueda sin resultados devuelve ok=True con items=[] (no es error).
+    """
+    params = [
+        ("query", query),
+        ("limit", str(max(1, min(int(limit), 100)))),
+        ("sort", sort),
+    ]
+    for t in str(types).split(","):
+        t = t.strip()
+        if t:
+            params.append(("types", t))
+    if base_model:
+        for bm in (base_model if isinstance(base_model, (list, tuple)) else [base_model]):
+            params.append(("baseModels", str(bm)))
+
+    url = f"{_API}?{urllib.parse.urlencode(params)}"
+    headers = {"User-Agent": "fn-registry/comfyui_search_civitai_models"}
+    if token:
+        headers["Authorization"] = f"Bearer {token}"
+
+    try:
+        req = urllib.request.Request(url, headers=headers)
+        with urllib.request.urlopen(req, timeout=_TIMEOUT) as resp:
+            data = json.loads(resp.read())
+    except urllib.error.HTTPError as exc:
+        body = exc.read().decode(errors="replace")[:300]
+        return {"ok": False, "items": [], "count": 0,
+                "error": f"HTTP {exc.code} en {url}: {body}"}
+    except urllib.error.URLError as exc:
+        return {"ok": False, "items": [], "count": 0,
+                "error": f"no se pudo conectar a civitai.com: {exc.reason}"}
+    except json.JSONDecodeError as exc:
+        return {"ok": False, "items": [], "count": 0,
+                "error": f"respuesta no es JSON valido: {exc}"}
+
+    items = []
+    for model in data.get("items", []) or []:
+        versions = model.get("modelVersions") or []
+        v0 = versions[0] if versions else {}
+        items.append({
+            "name": model.get("name"),
+            "type": model.get("type"),
+            "base_model": v0.get("baseModel"),
+            "version_id": v0.get("id"),
+            "download_url": v0.get("downloadUrl"),
+            "nsfw": bool(model.get("nsfw", False)),
+        })
+    return {"ok": True, "items": items, "count": len(items), "error": ""}
+
+
+if __name__ == "__main__":
+    out = comfyui_search_civitai_models("dreamshaper", limit=5)
+    print(out["ok"], out["count"])
+    for it in out["items"]:
+        print(f"  {it['name']} [{it['base_model']}] v{it['version_id']} -> {it['download_url']}")