feat(v9): Phase 10 Schritt 2 — Capability-Chips + Facetten-Filter im Cookbook
- Profi-Suche: HF-Suche mit &full=true (liefert Tags); Multi-Capability-Chips (Code/Bild/Logik/MoE·aktiv/Tools(yes|likely)/Chat) aus Name + HF-Tags. - Facetten-Filter (Mehrfachauswahl: Tools/MoE/Logik/Bild/Code) statt Einzel-Kategorie — clientseitig auf den Treffern (Index für Fit/Best bleibt). - Discover: dieselben Chips; Backend liefert HF-Tags je Modell mit. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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@@ -421,6 +421,7 @@ def refresh_discover(ram_gb: float) -> dict:
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by_cat[role].append({
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"name": rid.split("/")[-1], "author": rid.split("/")[0], "repo": rid,
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"role": role, "params_b": params_b, "quant": quant,
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"tags": [str(t) for t in (m.get("tags") or [])], # HF-Tags für Capability-Erkennung (Phase 10)
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"downloads": int(m.get("downloads") or 0), "likes": int(m.get("likes") or 0),
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"lastModified": m.get("lastModified"),
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"fit": fit, "optimal_ctx": max_ctx_for(params_b, quant, ram_gb),
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