feat(minimax-h3): default workflows; starter-model decision documented (PR 5/5) - #142
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Summary
PR 5 of 5 in the MiniMax H3 stack (on top of #141): default workflows, plus a documented decision on the starter-model entry. Two commits, deliberately separated so the license-sensitive part stays droppable.
Commit 1 — default workflows
video_latents/audio_latentsand the video+audio VAE edges. Form exposes model, prompt, width/height, frames, steps. Notes cover the 17n+5 frame grid, fixed 24 fps, 32-px dimension grid, muxed AAC audio, and the absence of a negative prompt.minimax_h3_frame_conditioning. The backend's keyframe-coupling contract is enforced structurally: a single image node feedsfirst_imageon both the prompt and frame-conditioning nodes, and shared width/height integer nodes feed prompt + frame conditioning + denoise — form edits cannot desynchronize them.Commit 2 — starter model: documented TODO, no entry
Neither expressible install source works, so no entry ships yet:
MiniMaxAI/MiniMax-H3source downloads ~498 GB —filter_fileskeeps everymodel*.safetensorsacross all subtrees, includingFL2VA/,Ref2VA/, andtransformer_ref/.::subfolder+subfoldersyntax keeps only files inside the listed subfolders and silently drops the rootmodular_model_index.jsonthat the H3 probe hard-requires — the install would land as an unknown model.The TODO in
starter_models.pyrecords both unblock paths (a root-config-awarefilter_files, or an upstream FL2VA-only repo) and the MiniMax H3 Community License constraints (territory exclusions extend to outputs; "MiniMax H3" attribution). Until then, users install the model manually by pointing the Model Manager at a locally assembled fl2va folder (~42.5 GB working set).Testing
tests/app/services/model_install+tests/app/services/workflow_records+tests/model_identification: 146 passed, 0 failures; ruff clean.WorkflowValidator.validate_json, and every edge handle was checked against the actual invocation input/output models.🤖 Generated with Claude Code