"""Wan2.1 T2V program (design_v3 §13, §15a): text_encode → diffusion_denoise → vae_decode.

The text-encode node demonstrates the content-hash feature cache (design_v3 §7.2, §10): the
same prompt across requests (e.g. a K=24 RL group) encodes once and reuses — the 24× text-encode
reduction the vendored RL sampler cannot express.
"""
from __future__ import annotations

from v2.program import ComponentNode, ModelLoopNode, Program, ProgramKind
from v2.models.common import text_encode_node_fn as _text_encode


def _vae_decode(instance, slots, request, ctx) -> None:
    latents = slots["denoise_out"]["latents"]
    slots["video"] = instance.component("vae").decode(latents)


def build_wan_t2v_program() -> Program:
    return Program(
        program_id="wan.t2v.inline", kind=ProgramKind.INLINE,
        nodes=[
            ComponentNode("text_encode", fn=_text_encode, writes=("text_embeds", "neg_text_embeds")),
            ModelLoopNode("denoise", loop_id="diffusion_denoise", output_slot="denoise_out",
                          reads=("text_embeds", "neg_text_embeds"), writes=("denoise_out",)),
            ComponentNode("vae_decode", fn=_vae_decode, reads=("denoise_out",), writes=("video",)),
        ],
        output_artifacts={"video": "video", "latents": "denoise_out"},
    ).validate()