Phase 2: wire Wan 2.1-1.3B into small lane, Wan 2.2 A14B into production lane

spi/renderers/registry.py

@@ -1,11 +1,13 @@
 """ModelRouter (§13): chooses a renderer by capability/quality/cost/VRAM, respecting SPI_MODE.
-Phase 1 registers mock renderers; Phase 2 registers Wan/LTX adapters behind the same interface."""
+Renderer construction is lazy (models load on first generate), so registering the real
+Wan adapters here costs nothing on CPU-only test environments."""
 from __future__ import annotations
 
 from typing import Any
 
 from spi.renderers.base import Renderer, RendererError
 from spi.renderers.mock import MockAudioRenderer, MockImageRenderer, MockVideoRenderer
+from spi.renderers.wan import WanRenderer
 
 DEFAULT_REGISTRIES: dict[str, dict[str, Renderer]] = {
     "mock": {
@@ -14,12 +16,14 @@ DEFAULT_REGISTRIES: dict[str, dict[str, Renderer]] = {
         "audio": MockAudioRenderer(),
     },
     "small": {
-        "video": MockVideoRenderer(),  # until Phase 2 wires Wan2.1-1.3B / LTX-Video-2B adapters
+        # real backend: Wan 2.1 T2V 1.3B (Apache-2.0, ~8.2 GB VRAM) — Phase 2 deliverable
+        "video": WanRenderer("Wan-AI/Wan2.1-T2V-1.3B-Diffusers"),
         "image": MockImageRenderer(),
         "audio": MockAudioRenderer(),
     },
     "production": {
-        "video": MockVideoRenderer(),  # placeholder; Wan 2.2 adapter is the Phase 2 deliverable
+        # placeholder quality lane: loads on first use, needs ~80 GB VRAM (Phase 10 hardware)
+        "video": WanRenderer("Wan-AI/Wan2.2-T2V-A14B-Diffusers"),
         "image": MockImageRenderer(),
         "audio": MockAudioRenderer(),
     },
@@ -61,7 +65,7 @@ class ModelRouter:
                 elif req_key not in caps:
                     score += 10  # cannot satisfy: deprioritize hard
             vram = caps.get("vram_gb", 999)
-            score += 0 if vram == 0 else min(vram, 20)  # cheap-first bias
+            score += 0 if vram == 0 else min(int(vram), 20)  # cheap-first bias
             scored.append((score, renderer))
         scored.sort(key=lambda pair: (pair[0], pair[1].name))
         return scored[0][1]