Fix API to match actual ltx-pipelines 1.1.5 interface

- Use DistilledPipeline constructor (not from_config)
- Use ImageConditioningInput namedtuple for image conditioning
- Use LoraPathStrengthAndSDOps for LoRA config
- Use QuantizationPolicy with fp8_cast sd_ops directly
- Update spatial_upsampler to required x2-1.1 model
- Update gemma_root to google/gemma-3-12b-it-qat-q4_0-unquantized
- Handle video output as Iterator[torch.Tensor] from pipeline
- Flesh out README with all model download commands, endpoint docs, env vars, frame/resolution tables

app/config.py

@@ -12,14 +12,13 @@ class Settings(BaseSettings):
     port: int = 8000
     reload: bool = True
 
-    # LTX-2.3 model paths (update after downloading models)
+    # LTX-2.3 model paths (update after downloading from HuggingFace)
     ltx_distilled_checkpoint: str = "models/ltx-2.3-22b-distilled-1.1.safetensors"
-    ltx_gemma_root: str = "models/gpt-4o-5805-ava-gguf-model"
-    ltx_spatial_upsampler: str | None = None
+    ltx_gemma_root: str = "models/gemma-3-12b-it-qat-q4_0-unquantized"
+    ltx_spatial_upsampler: str = "models/ltx-2.3-spatial-upscaler-x2-1.1.safetensors"
     ltx_device: str = "cuda"
     ltx_quantization: str = "fp8_cast"
 
-    # LoRA paths (list of "path:scale" strings, env: REVIDS_LTX_LORAS="models/my-lora.safetensors:1.0")
     ltx_loras: list[str] = []
 
     video_output_dir: str = os.path.join(os.path.dirname(os.path.dirname(__file__)), "videos")