Phase 7: Multi-Model Pipeline Orchestration · 50 min · Python · asyncio

The Orchestration Challenge

Chaining 14+ models across modalities with different APIs, latencies, and failure modes — that's the core engineering challenge in generative media.

Real-world application: Understanding the orchestration challenge (14+ models, dependency graphs, failure modes) is what separates engineers who can build production generative media systems from those who can only call APIs.

What you will learn

Understand the 14+ model problem: image, video, audio, 3D, post-processing, quality — each with different APIs, latencies, and failure modes
Design dependency graphs: which steps can run in parallel, which must be sequential
Manage state: tracking intermediate outputs across pipeline steps
Classify failure modes: API timeouts, content policy rejections, quality failures, GPU OOM

Objective

Compose media stages with explicit state, routing, retry, cost, and quality boundaries. In the paired studio lab, build a dependency graph builder for a multi-model pipeline. Define a pipeline with at least 5 steps (e.g., generate image → remove background → upscale → generate video from image → generate audio), identify which steps can run in parallel, and visualize the dependency graph.

The Problem

A team needs to build a complete generative media pipeline for a marketing campaign:

LLM (GPT-4) → generate creative copy and image prompts
Image (FLUX) → generate hero images from prompts
Background removal (rembg) → remove backgrounds for product shots
Upscaling (ESRGAN) → upscale to 4K for print
Video (Runway/Kling) → animate hero images into video clips
Audio (ElevenLabs) → generate voiceover from copy
Music (Suno) → generate background music
SFX (Stable Audio) → generate sound effects
3D (Tripo) → generate 3D product models
Post-production (FFmpeg) → combine video + audio + music + SFX
Quality check (CLIP score) → evaluate output quality
Thumbnail (FLUX) → generate social media thumbnails
Format conversion → export for web, mobile, print
CDN upload → deliver to users

That's 14+ models, each with different APIs, latencies (5s to 180s), failure modes, and costs. How do you orchestrate this?

What you'll build
Understand the 14+ model problem. Design dependency graphs (parallel vs sequential). Manage state across pipeline steps. Classify failure modes (timeouts, content policy, quality, GPU OOM).

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Key terms in this lesson

Orchestration