ergouzi-video-gen

name	ergouzi-video-gen
description	Submit and complete Ergouzi video generation, animation, avatar, and person-replacement tasks through ergouzi.life, including tasks that use local media files or HTTPS URLs. Use when Codex must call an ergouzi/e-video* model, poll the asynchronous task, download its output, resume a task ID, or cancel a video task.
license	MIT
compatibility	Requires Python 3.10+ and network access to https://ergouzi.life.
metadata	{"version":"0.3.1","author":"aiman-labs"}

Ergouzi Video Gen

Use this Skill as a thin adapter between Codex and the existing Ergouzi video API. Codex prepares the model input; the scripts only handle credentials, local file conversion, request submission, task polling, and result download.

Prerequisites

• Require Python 3.10 or newer and network access to https://ergouzi.life.
• Use the initialized user config by default. ERGOUZI_MEDIA_API_KEY and ERGOUZI_MEDIA_BASE_URL are explicit runtime overrides; generic ERGOUZI_API_KEY and ERGOUZI_BASE_URL are accepted when no config exists.
• If credentials are missing, ask the user to initialize them locally with python scripts/configure.py. Never ask the user to paste a key into chat.
• If the optional ergouzi-media-mcp Codex plugin is installed, prefer its check_configuration, list_models, get_model_schema, create_prediction, get_prediction, cancel_prediction, and download_prediction tools for the API lifecycle. Keep the Python runner as the fallback when the MCP tools are unavailable.
• Accept supported media as directly downloadable HTTPS URLs, data URIs, or local files that fit the existing 4 MiB JSON request limit: JPEG/PNG/WebP images, MP4 video, and FLAC/MP3/WAV audio. Use --image, --video, --audio, or --last-frame-image for common local-file workflows. In input JSON, put { "$local_file": "C:/path/media.ext" } in place of a media URL. The runner converts local files to data URIs; use an HTTPS URL when the expanded request would exceed the API limit.

Workflow

1. Submit a paid prediction only when the user explicitly asks to generate or transform a video.
2. Honor an explicit model choice. Otherwise let Codex select one of the four models from the task's required input/output capability; do not hide models or apply server-routing policy.
3. Read references/model-reference.md for the selected model's objective API contract. Use --prompt only for ergouzi/e-video; other models expose model-specific text fields through --input-file, --input-json, or stdin. Supply the complete model input object without the outer { "input": ... } envelope. Convenience arguments override the corresponding JSON fields. The runner resolves $local_file objects before submission and otherwise leaves input values unchanged. Prefer a UTF-8 JSON file for structured input across operating systems; files and stdin may include a UTF-8 BOM.
4. Prefer the MCP tools when available. Otherwise run scripts/run.py predict. Both paths create one logical task, reuse the same idempotency key for bounded transport retries, record the task_* ID, poll to a terminal state, and download successful outputs.
5. Report the model, task ID, terminal status, and absolute saved paths.
6. If execution was interrupted or timed out, resume with status --wait --download. Do not create a replacement task unless the user explicitly asks.

Commands

python scripts/configure.py
python scripts/configure.py --check
python scripts/run.py predict --model ergouzi/e-video --prompt "<prompt>"
python scripts/run.py predict --model ergouzi/e-video --prompt "<prompt>" --image <path-or-url>
python scripts/run.py predict --model ergouzi/e-video-animate --image <path-or-url> --video <path-or-url>
python scripts/run.py predict --model ergouzi/e-video-avatar --input-file <input.json> --output <result.mp4>
python scripts/run.py status --task-id <task_id> --wait --download --output <result.mp4>
python scripts/run.py cancel --task-id <task_id>

For structured stdin, detect the active shell and use its native JSON command. On Windows PowerShell, set the native pipe encoding first so non-ASCII prompts survive Windows PowerShell 5.1 as well as PowerShell 7:

$OutputEncoding = [System.Text.UTF8Encoding]::new($false)
@{ prompt = '让画面动起来'; duration = 5 } | ConvertTo-Json -Compress |
  python scripts/run.py predict --model ergouzi/e-video --input-file -

On macOS/Linux with zsh, bash, or sh:

printf '%s' '{"prompt":"Animate the scene","duration":5}' |
  python3 scripts/run.py predict --model ergouzi/e-video --input-file -

Use python3 on macOS/Linux and python on Windows unless the environment exposes Python 3.10+ under a different command. Keep --input-json for direct argv callers; avoid nested shell quoting when --input-file or stdin is available.

Use --output for an exact .mp4 path, or --output-dir for automatic result naming. Otherwise keep outputs under output/ergouzi-video-gen/ in the current working directory.

Adapter Boundary

• Keep the scripts transport-only. Do not add prompt rewriting, model ranking, aesthetic defaults, pricing, scheduling, billing, channel selection, or service-side behavior.
• Support local files by inlining data URIs only. Do not add upload, hosting, proxy-storage, or persistent media-management capabilities.
• Let Codex decide the model and construct the request from user intent. The API remains responsible for model validation and generation.
• Do not send the Ergouzi Authorization header to external output URLs.
• Treat references/ai-guide.md as optional advice. Read it only when the user asks for model-selection or prompting advice; it never overrides user input.