MLA 027 The AI Media Pipeline: Voice, Music, ComfyUI, APIs, and Finishing

How to automate AI media end to end: clone your own voice on open TTS, pick music that's actually licensed, run ComfyUI graphs headless, design around fal, Replicate and provider queues, finish with ffmpeg, and stay inside licensing at every layer.

Links

• More OCDevel shows - this one has siblings, each on its own subject and produced the same way
• Companion show. This episode is the overview of the media pipeline. For weekly, hands-on coverage of the video half, from a first usable clip to scenes that cut together, listen to AI Video Generation on Gnothi.
• Try a walking desk - stay healthy & sharp while you learn & code

Pipeline, not prompt

Once you need thirty clips with the same character, a narrator who sounds identical every episode, a matched music bed, word-accurate captions and a platform-safe export, the prompt is one node in a graph and the graph is the product. The engineering lives in the edges: how one model's output becomes the next model's input, how failures retry, what each job cost, and whether the run is reproducible next week. Model choice at the nodes is covered in the two sibling episodes; this one covers everything else: voice with ElevenLabs and Qwen3-TTS, licensed music, ComfyUI on your own card, the fal and Replicate APIs, ffmpeg assembly, and licensing.

Voice: cloning, open TTS, and consent

ElevenLabs remains the reference point (current flagship Eleven v3, character-based pricing). Professional voice cloning is locked to the requester's own voice behind a live voice check, and the terms require consent attestation for any uploaded voice. On the open side, Breeze TTS 2 topped the open-weights column of the Artificial Analysis speech arena in August 2026, ahead of Fish Audio's S2 Pro; the code is Apache 2.0 but the weights are research/non-commercial, so it is not a commercial self-hosting option. The working set for programmers: Qwen3-TTS (Apache 2.0, 0.6B/1.7B, cloning from seconds of reference audio; the preset-speaker variant does not clone, see my Qwen3-TTS voice cloning guide), Chatterbox (MIT, emotion control, watermarked output), and Kokoro (82M parameters, Apache 2.0, faster than real time on CPU). Fish Audio plays both sides with open weights and a cheap hosted API. Quantized Qwen3-TTS runs podcast-length synthesis on CPU-only instances; see Quantized Qwen3-TTS on CPU and the broader open-source TTS roundup. Hosted alternatives for prototyping: OpenAI text-to-speech and Gemini speech generation.

Consent is the legal boundary. Tennessee's ELVIS Act added voice to right of publicity; the federal NO FAKES Act cleared Senate Judiciary in June 2026; EU AI Act Article 50 transparency duties apply from 2 August 2026; Denmark is amending copyright law to cover a person's face and voice.

Music and sound effects

Warner settled with both Suno and Udio; Universal settled with Udio, which became a no-download walled garden; UMG and Sony are still litigating against Suno, whose terms now grant commercial rights rather than ownership to paid subscribers. Eleven Music is trained on licensed data via Merlin and Kobalt deals and cleared for commercial use on self-serve plans, excluding film, TV and larger games; ElevenLabs sound effects are cleared on any paid plan and support loops. Google exposes Lyria and Lyria RealTime through the Gemini API. Open models: ACE-Step 1.5, YuE, Stable Audio Open (community license, best open option for short effects), HeartMuLa, and Meta's MusicGen, which is non-commercial.

ComfyUI and local generation

ComfyUI is a workflow runtime with a GUI for designing graphs. Comfy raised $30M at a $500M valuation in April 2026 and ships a desktop app, Comfy Cloud, and API nodes that call paid providers from inside a local graph. Programmatic use is the same /prompt endpoint and websocket the front end uses: export the workflow in API format, patch fields, post, poll. Wrappers like comfyui-api and comfy-pack turn a graph into a scalable service. Alternatives: SwarmUI, InvokeAI, the Krita AI plugin.

Hardware: full-precision Flux.2 and Qwen-Image do not fit consumer cards; fp8 and GGUF quantization bring them to 16 to 24 GB. For video, the open Wan releases lag the API versions; the 5B variant does 720p on 24 GB (about 8 GB with Comfy offloading), the 14B variant officially wants 80 GB at full precision and needs GGUF to be consumer-viable, and Wan2GP targets low-VRAM cards. Rule: local for iteration, cloud for volume.

APIs and aggregators

Start with an aggregator, move to a provider API only for a feature or price it lacks. fal is queue-first: submit, get a request ID, poll or webhook, per-output pricing on popular models, per GPU-second for custom deployments. Replicate has the broader catalog beyond image and video, bills per second of compute for open models, packages custom models with Cog, and joined Cloudflare with the same API. RunPod serverless is the raw GPU option for a custom ComfyUI graph. Provider APIs have converged on the same shape: Veo via the Gemini API (billed per output second, audio included), Kling API (post, store task_id, poll /v1/tasks), Runway API, ElevenLabs API.

Design rules: every generation is a job in a durable queue keyed on a hash of inputs, model and seed; store the provider's request ID next to your job ID; honor 429 retry-after with a token bucket per provider; persist prompt, seed, inputs and outputs in object storage; route to a second provider on 5xx. Cost per usable second is list price times your rejection rate.

Assembly and finishing

ffmpeg is the programmer's editor: concat, overlay, sidechain ducking, caption burn-in, crop to 9:16, loudnorm and export. Human-in-the-loop editors: DaVinci Resolve (free version is a real editor; Studio unlocks most Neural Engine features), Descript with its transcript-as-timeline and Underlord assistant, and CapCut for short-form auto-captions, with a caution about its June 2025 terms change. Upscaling: Topaz retired Video AI for the subscription Topaz Video with the Astra model; open-side, SeedVR2 is single-step, runs on 8 GB and plugs into ComfyUI; Real-ESRGAN for clean stills; RIFE for frame interpolation. Captions: WhisperX gives word timestamps within about 50 ms via forced alignment plus diarization, emitting SRT/VTT; generate styled word-pop overlays from its JSON. Delivery: 1080x1920 9:16, H.264/AAC, roughly 10 to 12 Mbps, 30 fps; YouTube recommended upload settings; target -14 LUFS integrated with a -1 dBTP ceiling as the last pipeline step.

Licensing across the stack

Five layers, and the output is only as clean as the dirtiest node. Weights: Apache/MIT models (Qwen3-TTS, Kokoro, Chatterbox, open Wan) are clean; FLUX.2 dev is non-commercial without a separate license; Stability's community license allows commercial use under a revenue threshold; MusicGen is non-commercial. Output: the Copyright Office holds that prompts alone are not authorship, and the Supreme Court denied cert in Thaler v. Perlmutter in March 2026, so keep evidence of the human selection and editing. Training data: licensed models are the safe path while label suits continue. People: right of publicity, get written consent. Disclosure: YouTube auto-labels via SynthID and C2PA content credentials since May 2026, and labels on Veo and C2PA-stamped content are permanent. Attach credentials and disclose.

Two pipelines

Social clip (30 s, 9:16, run 200 times): character sheet from an image-editing model stored with prompt and seed -> templated script -> Qwen3-TTS narration with word timings -> per-shot image-to-video jobs via fal keyed on input hash, webhook completion -> cached licensed music bed -> ffmpeg concat, duck, styled captions from timing JSON, crop, loudnorm, 1080x1920 export -> content credentials and disclosure -> human review queue.

Narrated explainer (8 min, 16:9, weekly): human-written script (where copyright rests) -> chunked TTS stitched with short silences -> LLM shot list with timestamps tagged diagram/image/video -> deterministic diagrams, styled images, a few video clips upscaled with SeedVR2 -> licensed music and SFX generated once -> Resolve or ffmpeg assembly, captions from narration timings, loudnorm, 1080p/4K export -> title, chapters from the shot list, disclosure, credentials. Both are the same graph with different shot counts and aspect ratios.

Related episodes

• AI Image Generation and Editing in 2026
• AI Video Generation in 2026
• AI Agents covers agent orchestration of pipelines like these

The companion show for the video half of this pipeline is AI Video Generation on Gnothi.