The selector path previously hid the custom-workflow feature: video_selector
filtered tools on per-operation readiness (bundled WAN models) and both
selectors only chose ToolStatus.AVAILABLE providers, so comfyui_image/
comfyui_video — DEGRADED when bundled model metadata is missing — were
dropped even when the ComfyUI server was up and the caller supplied a full
workflow_json/workflow_path plus output_node.
- Add a custom-workflow readiness path to both selectors: when a custom
workflow is supplied, eligibility is based on server availability (status
!= UNAVAILABLE) for any provider advertising supports.custom_workflow,
not on bundled-model readiness. A custom workflow also restricts routing
to custom-workflow-capable providers, since the graph JSON is ComfyUI
specific.
- Expose workflow_json, workflow_path, output_node, workflow_name,
workflow_model, and workflow_model_stack in both selector schemas so
agents can discover the feature without bypassing the selectors.
- image_selector only forwards the workflow inputs to providers that
declare them.
- Add contract tests for the new eligibility path and schema exposure.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
- Client queries ComfyUI /object_info to discover installed models
(checkpoints, diffusion models, VAE, CLIP, LoRAs)
- Each tool declares its required models and checks them on execute()
- get_status() returns DEGRADED when server is up but models are missing
- Clear error messages tell the user exactly which models to download
- When COMFYUI_SERVER_URL is not set, error message tells the user to
configure it in .env instead of silently failing on localhost:8188
- 8 new tests covering URL config, error messages, and model requirements
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Adds three new BaseTool providers that delegate GPU work to a running
ComfyUI server via its REST API. This avoids the need to install
PyTorch/diffusers directly, which is critical on hardware where the
ecosystem hasn't caught up (e.g. NVIDIA Blackwell / DGX Spark, aarch64
+ CUDA 13.0).
New files:
- tools/_comfyui/client.py — shared REST client (submit/poll/download)
- tools/_comfyui/workflows/ — 4 bundled workflow templates
- tools/graphics/comfyui_image.py — FLUX 2 Dev NVFP4 text-to-image
- tools/video/comfyui_video.py — WAN 2.2 14B t2v + i2v (4-step LightX2V)
- tools/audio/comfyui_music.py — ACE-Step 3.5B music generation
- tests/contracts/test_comfyui_tools.py — 41 contract tests
- docs/comfyui-adapter-plan.md — design document
Zero changes to existing tools, selectors, registry, or pipelines.
Tools are auto-discovered and selectors pick them up via capability match.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Google's TTS and Imagen tools advertised service-account auth
(GOOGLE_APPLICATION_CREDENTIALS) but only ever authenticated with an API
key string, so users with a service-account JSON could not use either tool.
google_tts.get_status() also over-reported availability when the JSON was
set, then failed at execute() — a silent-availability bug.
Separately, both hand-rolled _load_dotenv parsers kept inline comments as
values, so after `cp .env.example .env` every keyed tool falsely reported
"available" with no real credentials.
Changes:
- Add tools/google_credentials.py: lazy google-auth Bearer-token helper.
- google_tts: authenticate via Cloud TTS Bearer token when only a service
account is configured; make get_status() honest.
- google_imagen: route service-account auth to Vertex AI
({location}-aiplatform.googleapis.com) with project/location resolution,
alongside the existing AI Studio API-key path.
- Fix both _load_dotenv parsers to strip inline comments (quote-aware).
- Add google-auth to requirements; document the new env vars in .env.example.
- .gitignore: never commit GCP service-account key files.
Verified locally with a real service account: TTS produced a valid MP3 and
Imagen produced a valid 1408x768 PNG via Vertex AI. Existing test suite
passes (2 unrelated pre-existing failures only).
Closes#131
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Separates creative grammar (renderer_family) from technical engine
(render_runtime) so HyperFrames can stand alongside Remotion as a
first-class runtime instead of masquerading as a Remotion sub-case.
Locks runtime choice at proposal stage and enforces it end-to-end: the
schemas require it, video_compose routes by it, the reviewer fails
closed on silent swaps, and a parametrized contract test walks every
pipeline manifest to ensure each planning-stage skill explains the
conversation to the user. Adds hyperframes_compose (scaffold/lint/
validate/render/doctor/add_block), a playbook -> CSS style bridge, and
vendored HyperFrames Layer 3 skills from commit d291358, pinned via
PROVENANCE.md for future re-sync. Final_review now records
render_runtime_used and runtime_swap_detected so compose lies are
catchable after the fact.
Compose-director had contradictory instructions: Step 2 described Remotion
captions/audio, but Steps 5/5b gave detailed FFmpeg code that agents followed
instead. This caused three failures in production: FFmpeg subtitles instead of
Remotion CaptionOverlay, missing audio (mixed externally but never embedded in
Remotion props), and skipped audio verification in post-render review.
Changes:
- compose-director: Remotion is now DEFAULT for audio, captions, text overlays;
FFmpeg is labeled FALLBACK only. Post-render review has mandatory ffprobe gate
and audio transcription with explicit stop conditions.
- remotion.md: routing table updated (captions/audio → Remotion), added universal
Post-Render Verification Protocol for all pipelines (only 2/10 had one).
- scene-director, asset-director: added pitfall for AI-generated text in CTA
screens — must use Remotion text_card for verbatim text.
- image-provider-usage: added Recraft V4 caveat (style param causes 422 on fal.ai).
- recraft_image.py: documented the style parameter 422 issue inline.
Implements the 2026-04-02 transformation spec (Phases 1-8) and fixes all
critical bugs found during 5-pipeline E2E testing.
Governance & Decision Intelligence:
- Pipeline-specific stage order in checkpoint (replaces global STAGES list)
- Provider scoring engine (lib/scoring.py) with 7-dimension weighted ranking
- Decision log artifact enforced at proposal/idea stage across all 10 pipelines
- Delivery promise classifier prevents silent motion-to-still downgrades
- Structured shot language in scene_plan schema (camera, lens, lighting, DOF)
- Variation checker and slideshow risk scorer block samey output before render
- Creative intake, capability extension, and creative-intake meta skills
- Final self-review artifact with 5 mandatory checks before presenting output
- Source media review contract for user-supplied footage
Render & Theme System:
- Remotion AnimatedBackground now derives colors from playbook (no more hardcoded
dark blue fintech gradient on every video)
- video_compose builds custom ThemeConfig from playbook YAML colors/fonts —
custom playbooks flow through to Remotion automatically
- Explainer component wires theme to all child components (charts, cards, etc.)
- resolveAsset() handles absolute paths on Windows/Unix via file:// URIs
- RENDERER_FAMILY_MAP synced with actual Remotion compositions
Critical Bug Fixes:
- Windows npx subprocess: run_command() resolves .cmd wrappers via shutil.which()
- Silent renderer downgrade: Remotion failure now returns explicit error with
options instead of silently falling back to FFmpeg
- .env inline comment parsing strips trailing # comments from API keys
- concat_path UnboundLocalError in video_compose finally block
- audio_mixer and showcase_card capture=True kwarg bug
- Selector estimate_cost() calls fixed (_select_tool -> _select_best_tool)
- asset_manifest schema expanded with provider, license, subtype fields
- screen-demo subtitle_gen moved from required to optional tools
- Duration drift detection in post-render final review (>25% warns)
Two new provider tools following the BaseTool pattern with auto-discovery:
- google_imagen: Imagen 4 image generation via Generative Language REST API
- google_tts: Google Cloud TTS with 700+ voices across 50+ languages
Both share GOOGLE_API_KEY env var. Selectors auto-discover them — no
selector code changes needed. Docs and contract tests updated.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
