modellix

Integrate Modellix's unified API for AI image, video, and audio workflows. Use this skill whenever the user wants to generate or edit images, create or transform videos, synthesize speech, transcribe audio, clone a voice, do virtual try-on, or call any Modellix model API. Also trigger when the user mentions Modellix, model-as-a-service for media generation, or providers such as Qwen, Wan, Seedream, Seedance, Kling, Hailuo, MiniMax, Whisper, or CosyVoice through a unified API. Prefer modellix-cli (model run --wait, task download, doctor, model list) over hand-rolled REST polling whenever the CLI is available.

Modellix Skill

Modellix is a Model-as-a-Service (MaaS) platform for asynchronous image, video, and audio workflows. Prefer the official CLI (modellix-cli) so submit, wait, and download stay one coherent workflow. Persistent session guardrails also ship as Open Plugins rules under rules/*.mdc.

Official Docs

• AI Onboarding: https://docs.modellix.ai/get-started.md
• REST API: https://docs.modellix.ai/ways-to-use/api.md
• Full Models Index: https://docs.modellix.ai/llms.txt
• Docs MCP (search / read docs): https://docs.modellix.ai/mcp
• CLI package (source of truth for CLI behavior): https://www.npmjs.com/package/modellix-cli

Documentation lookup policy

This plugin may expose the Modellix Docs MCP (.mcp.json → https://docs.modellix.ai/mcp). It is a read-only documentation server (search_modellix, docs filesystem query, optional feedback). It does not submit generation tasks, poll, download, or handle API keys.

When looking up product/API/install docs or request-body schema:

1. Prefer Docs MCP when the host has it connected (search, then read the matching page / OpenAPI chunk).
2. Else use modellix-cli model describe <slug> --json → docs_url, or browse https://docs.modellix.ai/llms.txt and fetch the model .md.
3. For CLI command syntax and flags, prefer this skill, references/cli-playbook.md, the npm README, or modellix-cli --help — do not trust website CLI pages over the CLI package (docs can lag).

If the Docs MCP exposes a skill resource, treat this SKILL.md as the execution policy source of truth (CLI-first, defaults, paid-submit safety).

Do not rely on the website CLI guide page for command syntax.

Execution Policy (CLI-first)

Choose the path in this order:

1. CLI when modellix-cli is available (install with npm i -g modellix-cli@latest if missing and install is allowed).
2. REST only when CLI is not installed, unsuitable, or missing a needed capability.
3. Prefer machine-readable output (--json or --quiet) for automation.

Canonical single-task flow:

bash

modellix-cli doctor --json
modellix-cli model run \
  --model-slug <provider/model> \
  --body '<json>' \
  --wait --timeout 5m --json
modellix-cli task download <task_id> --output-dir ./outputs --json

model invoke is a compatibility alias of model run. New commands should use model run.

Do not reinvent polling loops when CLI wait is available. Do not invent deprecated flags (for example --model-type). Use --help only when behavior is unclear.

Default Models

When the user does not name a model, use these defaults immediately (do not scan the catalog first):

Task Type	Default Model Slug
Text-to-image (T2I)	google/nano-banana-2-lite
Text-to-video (T2V)	bytedance/seedance-2.0-mini-t2v
Image editing / I2I	google/nano-banana-2-lite-edit
Image-to-video / I2V	bytedance/seedance-2.0-fast-i2v
Video-to-video (V2V)	bytedance/seedance-2.0-fast-v2v
Text-to-speech (TTS)	alibaba/qwen-audio-3.0-tts-flash
Speech-to-text (STT)	openai/whisper-1
Speech-to-speech (STS)	alibaba/cosyvoice-clone

API Key Lifecycle Policy

Handle credentials as: discover -> request -> use-session -> (optional) persist.

1) Discover existing key first

Before asking the user:

1. Session / process env MODELLIX_API_KEY
2. Saved CLI profile (modellix-cli auth status / doctor — key via --profile or MODELLIX_PROFILE or currentProfile)
3. If still missing, request a key from the user

Never ask again when a usable key is already discoverable. CLI key resolution order is: --api-key → MODELLIX_API_KEY → selected saved profile.

2) Request key only when missing

• Ask for a key from Modellix Console.
• Do not print or echo key values.
• Prefer session env for the current run.

3) Optional persistence

Default: do not persist automatically.

When the user explicitly asks to persist:

1. Preferred: modellix-cli auth login or modellix-cli init (CLI validates and stores the profile securely).
2. Alternative: user-level MODELLIX_API_KEY only if they insist on env persistence.
3. Do not write system-level env or other agents' config files.

4) Key rotation

If the user provides a new key: update session first; if they requested persistence, replace via auth login/init (or user-level env). Re-check with modellix-cli doctor --json (or scripts/preflight.py --json) before continuing.

Preflight and Deterministic Execution

Preferred checks:

bash

modellix-cli doctor --json

Bundled helpers (optional):

1. scripts/preflight.py — wraps doctor when CLI exists; otherwise lightweight env/which checks and recommends cli or rest.
2. scripts/invoke_and_poll.py — CLI path uses model run --wait; REST path keeps submit+poll fallback.

When preflight/doctor reports missing credentials, apply the lifecycle above.

When CLI is unavailable:

1. Use REST (references/rest-playbook.md).
2. After the task, recommend: npm i -g modellix-cli@latest.

Core Workflow

1) Ready the environment

• Discover or request API key (lifecycle above).
• Run modellix-cli doctor --json when CLI is present.
• Continue only when auth and connectivity look healthy (or REST key is set).

2) Select model

1. If the user did not specify a model: use the Default Models table (do not scan the catalog first).
2. If they named a model or need discovery: modellix-cli model list / modellix-cli model describe <slug> (describe returns docs_url).
3. For request body schema: prefer Docs MCP when available; else fetch the model doc (docs_url or the matching link from https://docs.modellix.ai/llms.txt) and read the OpenAPI path / model_id. Do not invent slugs from filenames (decimals often matter, e.g. bytedance/seedance-2.0-mini-t2v).
4. If CLI is unavailable for discovery: use Docs MCP or browse llms.txt, then fetch the target model .md.

3) Run and wait

Default (single task):

bash

modellix-cli model run \
  --model-slug google/nano-banana-2-lite \
  --body '{"prompt":"A cinematic sunset over a futuristic city skyline"}' \
  --wait --timeout 5m --json

Split flow when useful (pipelines, concurrency):

bash

TASK_ID=$(modellix-cli model run --model-slug ... --body '...' --output task-id)
modellix-cli task wait "$TASK_ID" --timeout 10m --json

Batch (paid guard required): modellix-cli model batch tasks.jsonl --max-tasks N [--wait].

Manual REST: references/rest-playbook.md. Optional helper: scripts/invoke_and_poll.py.

4) Download results

bash

modellix-cli task download <task_id> --output-dir ./outputs --json

If download fails with Resource host resolves to a private or reserved network address (common when a local proxy/VPN maps CDN hosts like file.modellix.ai into 198.18.0.0/15), retry with --allow-private-network for trusted Modellix CDN hosts, or fall back to downloading the result.resources[].url with curl/wget.

Resource URLs expire in about 7 days — persist promptly. If downloading manually (REST path), name files:

text

modellix-{model_slug}-{timestamp}.{ext}

(replace / in the slug with -).

Examples:

• modellix-google-nano-banana-2-lite-20260430-113000.png
• modellix-bytedance-seedance-2.0-mini-t2v-20260430-113500.mp4

Quick Examples

T2I (default model) — prompt required:

bash

modellix-cli model run \
  --model-slug google/nano-banana-2-lite \
  --body '{"prompt":"A cinematic sunset over a futuristic city skyline"}' \
  --wait --timeout 5m --json

T2V (default model) — prompt required:

bash

modellix-cli model run \
  --model-slug bytedance/seedance-2.0-mini-t2v \
  --body '{"prompt":"A cat playing in a sunny garden"}' \
  --wait --timeout 10m --json

I2I — prompt + image array:

bash

modellix-cli model run \
  --model-slug google/nano-banana-2-lite-edit \
  --body '{"prompt":"Convert to watercolor style","image":["https://example.com/input.jpg"]}' \
  --wait --timeout 5m --json

I2V — at least one image param (first_frame_image, last_frame_image, or reference_images):

bash

modellix-cli model run \
  --model-slug bytedance/seedance-2.0-fast-i2v \
  --body '{"prompt":"A cat playing in the garden","first_frame_image":"https://example.com/frame.jpg"}' \
  --wait --timeout 10m --json

V2V — video_urls array:

bash

modellix-cli model run \
  --model-slug bytedance/seedance-2.0-fast-v2v \
  --body '{"video_urls":["https://example.com/source.mp4"]}' \
  --wait --timeout 10m --json

TTS (default model) — text + voice required (verify voice against the model doc; Flash voices only):

bash

modellix-cli model run \
  --model-slug alibaba/qwen-audio-3.0-tts-flash \
  --body '{"text":"There is a large garden behind my house.","voice":"longanhuan_v3.6"}' \
  --wait --timeout 5m --json

STT (default model) — public audio url required:

bash

modellix-cli model run \
  --model-slug openai/whisper-1 \
  --body '{"url":"https://example.com/meeting.mp3"}' \
  --wait --timeout 5m --json

STS (default model) — clone reference url + synthesis text + target CosyVoice model:

bash

modellix-cli model run \
  --model-slug alibaba/cosyvoice-clone \
  --body '{"model":"cosyvoice-v3.5-plus","url":"https://example.com/reference.wav","text":"There is a large garden behind my house."}' \
  --wait --timeout 5m --json

5) Post-task CLI recommendation

If this session used REST because CLI was missing, suggest installing the CLI afterward.

Progressive Reference Routing

Read only what the task needs:

• references/cli-playbook.md — install, auth, run/wait/download, batch, recovery
• references/rest-playbook.md — REST submit/poll when CLI is unavailable
• references/capability-matrix.md — CLI ↔ REST mapping and fallback rules

Bundled Assets

• assets/output/task-result.schema.json

Credential and Data Egress

• Primary credential: MODELLIX_API_KEY (also via CLI profiles).
• Network egress: https://api.modellix.ai (override only with trusted --base-url / MODELLIX_BASE_URL).
• User prompts and media inputs may be sent to Modellix during invocation.
• Never expose API keys in logs, screenshots, transcripts, or commits.
• Default to session-only credentials; persistent writes need explicit user approval.

Error / Retry Policy

Situation	Action
HTTP/API 400	Do not retry. Fix parameters or body.
401	Do not retry. Fix key (doctor, auth login).
402	Do not retry. Insufficient balance.
404	Do not retry. Verify task_id or model slug.
429 / read-only 5xx	CLI already retries safe GETs within deadline; do not blindly re-POST paid submits.
Paid submit outcome unknown	Do not immediately re-run the same model run. Check task history, console activity, and any printed task ID first.
Exit 124	Local wait timeout; remote task may still run — recover with task wait / task get, then task download.
Exit 2	Argument or safety guard (e.g. batch cost limit) — fix flags.

Verification Checklist

• Doctor/preflight passed or REST key ready
• Model chosen (default table or user/catalog)
• Body schema checked against model doc when non-trivial
• Used model run --wait (or task wait) instead of hand-rolled poll loops
• Results downloaded (task download or manual persist before 7-day expiry)
• No blind retry after unknown paid submission
• REST used only when CLI path unavailable