Task Router Skill
Task Router
Generate images from text with a free-quota-first multi-provider workflow. Use this skill when a user asks for text-to-image generation that needs provider routing (Hugging Face, Gitee, ModelScope, A4F, OpenAI-compatible private endpoints), token pooling with automatic rotation on quota/auth failures, public API fallback for Hugging Face, prompt optimization, model fallback, batch generation in one command, and structured generation outputs.
请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。
SkillHub CLI
skillhub install chiayengu/free-quota-image-skill打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。
将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。
Use this skill to run a provider-agnostic text-to-image pipeline with free-quota-first routing, token rotation, and prompt enhancement.
{baseDir}/assets/config.example.yaml or user-provided config.--provider auto follows routing.provider_order).requested -> z-image-turbo -> provider default).--count > 1, and rotate provider/token start position per image to spread load.Install dependencies:
python -m pip install -r {baseDir}/scripts/requirements.txt
Run generation:
python {baseDir}/scripts/run_text2img.py --prompt "cinematic rainy tokyo alley" --json
Run with explicit provider/model:
python {baseDir}/scripts/run_text2img.py --prompt "a fox astronaut" --provider gitee --model flux-2 --json
Save image locally:
python {baseDir}/scripts/run_text2img.py --prompt "retro sci-fi city" --output ./out.png
Generate multiple images in one run:
python {baseDir}/scripts/run_text2img.py --prompt "anime passport portrait" --count 4 --json
Use {baseDir}/scripts/run_text2img.py with the fixed contract:
--prompt (required)--provider (auto|huggingface|gitee|modelscope|a4f|openai_compatible, default auto)--model (default z-image-turbo)--aspect-ratio (default 1:1)--seed (optional int)--steps (optional int)--guidance-scale (optional float)--enable-hd (flag)--optimize-prompt / --no-optimize-prompt (default on)...这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。
# Free Quota Image Skill
## Overview
Use this skill to run a provider-agnostic text-to-image pipeline with free-quota-first routing, token rotation, and prompt enhancement.
## Workflow
1. Load config from `{baseDir}/assets/config.example.yaml` or user-provided config.
2. Resolve provider order (`--provider auto` follows `routing.provider_order`).
3. Resolve model candidates per provider (`requested -> z-image-turbo -> provider default`).
4. Prepare prompt for each attempt:
- optionally auto-translate for target models
- optionally optimize prompt with provider text model
5. Execute generation request.
6. On quota/auth failures, rotate token; if exhausted, move to next provider.
7. Repeat the generation flow when `--count > 1`, and rotate provider/token start position per image to spread load.
8. Return stable JSON output fields or direct URL output.
## Commands
Install dependencies:
```bash
python -m pip install -r {baseDir}/scripts/requirements.txt
```
Run generation:
```bash
python {baseDir}/scripts/run_text2img.py --prompt "cinematic rainy tokyo alley" --json
```
Run with explicit provider/model:
```bash
python {baseDir}/scripts/run_text2img.py --prompt "a fox astronaut" --provider gitee --model flux-2 --json
```
Save image locally:
```bash
python {baseDir}/scripts/run_text2img.py --prompt "retro sci-fi city" --output ./out.png
```
Generate multiple images in one run:
```bash
python {baseDir}/scripts/run_text2img.py --prompt "anime passport portrait" --count 4 --json
```
## CLI contract
Use `{baseDir}/scripts/run_text2img.py` with the fixed contract:
- `--prompt` (required)
- `--provider` (`auto|huggingface|gitee|modelscope|a4f|openai_compatible`, default `auto`)
- `--model` (default `z-image-turbo`)
- `--aspect-ratio` (default `1:1`)
- `--seed` (optional int)
- `--steps` (optional int)
- `--guidance-scale` (optional float)
- `--enable-hd` (flag)
- `--optimize-prompt` / `--no-optimize-prompt` (default on)...Task Router
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