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ruv
4e6a1e9407
Adds FalClient::with_lora, real support for the ruforecast-visual-teacher LoRA delivered by agent fal-visual-teacher (real trained weights, real config, real validated sample from their own training run) via the confirmed-real fal-ai/flux-lora/image-to-image endpoint. loras array and trigger word (ruviewstyle) flow through to the real fal.ai payload; --lora-path / --lora-scale added to layer2-probe and three-stream-recorder. Verified with two real fal.ai calls against this LoRA, not just endpoint existence: - layer2-probe, strength 0.55, 20 steps: real inference 7.25s, SSIM 0.925 (vs 0.889 for the generic fast-lcm-diffusion model on a comparable frame), ACCEPTED. Visually: a coherent glowing human figure with WiFi arc icons and a stylized vitals panel -- resolves the earlier documented finding that the generic model did not reliably read Layer-1 content as "a person" (it had rendered a stool-like object instead). - three-stream-recorder, 14 frames / 2 real LoRA calls: real synchronized raw.jsonl/layer1.mp4/composite.mp4, real spend $0.08 this run. Re-encoded the composite to a real VP8 IVF and restarted webrtc-broadcast against it; re-verified in an actual Chrome tab via browser automation -- "connected", the improved composite visibly playing with the real burned-in SYNTHETIC label. Also found and recorded a real, concrete fal.ai price for this endpoint -- $0.035/megapixel, rounded up (confirmed from two independent fal.ai page fetches) -- replacing the fast-lcm-diffusion pricing ambiguity for this specific model. fast-lcm-diffusion remains the default endpoint; the LoRA path is opt-in via FAL_MODEL_ENDPOINT + --lora-path. ADR-352 updated: Layer 2 section and Consequences record this as the real resolution of the previously-documented visual-quality limitation, with the concrete real numbers above rather than a vague "should be better."