Genmedia workflow production

Runtime: All endpoint calls run via the genmedia CLI. See the genmedia skill for command syntax; run genmedia init once if not yet installed.

Use this skill when a single model call is not enough. A workflow is a planned sequence of genmedia calls with clear inputs, outputs, dependencies, and quality checks.

Load references as needed:

• references/pipeline-patterns.md
• references/node-rules.md
• references/utility-endpoints.md
• references/recipes.md
• model-routing for creative model defaults

Use model-routing for default creative model choices. Still inspect schemas, check pricing when cost matters, and use exact endpoint fields.

Inputs to collect

Ask only for missing information that changes the pipeline:

• Final deliverable: image set, video, clips, audio, subtitles, dataset, social batch, product campaign, storyboard, style exploration.
• Source assets: product images, character references, first frames, video, audio, logo, transcript, brand guide.
• Runtime limits: quality target, cost sensitivity, number of variants, duration, aspect ratios, deadline.
• Continuity requirements: product identity, character face, scene layout, voice, color grade.
• Model preference: ask the user only when quality, speed, cost, or audio tradeoffs are not clear from the brief.

Core workflow

1. Write a short pipeline graph before running anything.

text input assets -> planner -> generation nodes -> utility nodes -> QA -> final outputs

2. Resolve endpoints for each role. Check known endpoint IDs first.

bash genmedia models --endpoint_id openai/gpt-image-2 --json genmedia models --endpoint_id fal-ai/nano-banana-pro/edit --json genmedia models --endpoint_id bytedance/seedance-2.0/image-to-video --json genmedia models --endpoint_id xai/grok-imagine-video/image-to-video --json genmedia models --endpoint_id veed/fabric-1.0 --json

Use text search only as fallback discovery for roles not covered by model-routing or the utility reference:

bash genmedia models "image generation product photography" --json genmedia models "image editing reference preservation" --json genmedia models "image to video" --json genmedia models "subtitle video utility" --json genmedia docs "fal.ai workflow utility endpoints" --json

3. Inspect every endpoint before use.

bash genmedia schema <endpoint_id> --json genmedia pricing <endpoint_id> --json

4. Upload local files once and reuse returned URLs.

bash genmedia upload ./input.png --json genmedia upload ./voiceover.wav --json

5. Run each node with JSON output. Use async for slow generation.

bash genmedia run <endpoint_id> --<field> "<value>" --json genmedia run <endpoint_id> --<field> "<value>" --async --json genmedia status <endpoint_id> <request_id> --download "./outputs/workflow/{request_id}_{index}.{ext}" --json

6. For downstream nodes, pass the media URL from the previous result when it is available. If you only have a local file path, upload it first.

7. Download final assets with templates that cannot collide.

bash --download "./outputs/workflow/{request_id}_{index}.{ext}"

8. Return a compact manifest.

json { "goal": "short deliverable description", "nodes": [ { "id": "shot_01", "role": "image_to_video", "endpoint_id": "...", "request_id": "...", "input_urls": ["..."], "output_urls": ["..."], "downloaded_files": ["..."], "notes": "continuity or defect notes" } ], "final_files": ["..."] }

Pipeline rules

• Keep one node responsible for one clear transformation.
• Fan out independent generation, crop, upscale, subtitle, or variation nodes.
• Keep sequential chains only when node B needs node A output.
• For consistency, prefer reference/edit or image-to-video over independent text-only generations.
• For default creative model choices, follow model-routing unless the user names a model.
• Use utility endpoints for deterministic work: crop, resize, grid, composite, audio merge, subtitle, speed change, compression.
• Record endpoint, schema-relevant parameters, request ID, and output path for every node.
• If a 422 error occurs, read validation_errors, inspect schema again, then fix the exact field.

Quality gate

Before returning, verify:

• The pipeline graph matches the requested deliverable.
• No generation model was chosen from memory alone.
• All local source files were uploaded before use.
• Final files were saved through --download.
• Utility endpoints used exact schema fields.
• Continuity anchors were repeated where identity or product fidelity matters.
• Each node output is either accepted, retried, or marked with a defect.

If the workflow becomes too complex, stop expanding and ask the user to choose between faster iteration, higher fidelity, or broader variation.