Reve, Reve AI's image family on Scenario, splits into two members that share a brand and little else: v2.1 is a reasoning-driven generator and instruction editor (a top-2 text-to-image arena entry at authoring time), Remix a fast, cheap compositor that blends several images into one. Discover them with search and treat model_schema_get as the contract: they disagree on field names, prompt caps, and ratio lists.
Connection and the core loop: see the scenario skill in this repo; model-agnostic image work: the scenario-image skill. If a sibling skill named here is missing from your available skills, ask the user to install it (npx skills add scenario-labs/skills --skill <name>); unattended, proceed from tool schemas and flag the gap.
At authoring time (the live schema wins):
\n| Member | \nCapabilities | \nReferences | \nPrompt cap | \nAspect ratios | \n
|---|---|---|---|---|
| Reve v2.1 | \ntxt2img, img2img | \nreferences, optional | \n4000 | \n18 values, 4:1 through 1:4, default auto | \n
| Reve Remix | \nimg2img | \nreferenceImages, required, 1 to 6 | \n2560 | \n7 values, 16:9 through 9:16, default 3:2 | \n
Three parameters each: the prompt, the reference array, aspectRatio. Neither member has a mask, seed, width and height, negative prompt, or batch-count field, so an edit is scoped by wording and size comes only as a ratio. auto (v2.1 only) picks a fitting shape; pass an explicit ratio when the deliverable demands one.
Pick by job. v2.1 covers generation from a prompt alone and precise edits: swap the text on a poster, recolor a product, change a material, relight or restyle, merge references while every subject stays consistent. Remix blends photos, illustrations, or design assets into one cohesive composite. Where either would do, dry_run both: at authoring time a v2.1 run cost several times a Remix run and took over a minute at p50 against Remix's twenty-odd seconds.
In a v2.1 prompt, a reference is addressed with a <frame>N</frame> tag, numbered from 0 in the order the assets appear in references: the first is <frame>0</frame>, the second <frame>1</frame>. Use the tags whenever more than one reference is in play; without them the model guesses which image you mean. Remix documents no tag syntax: name subjects in plain words (\"the bottle from the first image, the lighting from the second\").
Neither member takes a mask, so the prompt carries the whole edit: state what changes and what must stay untouched. v2.1's reasoning rewards specific plain-language instructions over keyword lists, and its 4000-character budget leaves room for constraints. For masked inpainting on an exact region, use a model that exposes a mask field (see scenario-image).
search with target=\"models\", query=\"reve\", public=true. At authoring time the hits were model_reve-v2-1 (generation and instruction edits) and model_reve-remix (multi-image blends); re-discover each session.model_schema_get on the pick: field names, caps, and the ratio list before anything else.upload_asset the poster (see the scenario skill) to get an asset id.model_run with that model_id, dry_run=true, and parameters={\"prompt\": \"Replace the headline on the poster in <frame>0</frame> with 'SUMMER SALE', matching the original font, perspective, and lighting. Change nothing else.\", \"references\": [\"asset_x\"], \"aspectRatio\": \"auto\"} for the cost estimate.model_run with wait=false, then jobs_wait with the returned job id, re-called with pending_job_ids on timeout, never a second model_run.asset_display to check the swap, then asset_download to save.<frame>1</frame> is the second reference; the first is <frame>0</frame>.references, Remix takes referenceImages; each schema lists only its own.referenceImages is required (1 to 6 at authoring time); prompt-only generation belongs to v2.1.aspectRatio is the only size control.jobs_wait timeout as an error: p50 latency topped a minute at authoring time; re-call with pending_job_ids.