Bridge 图像生成技能: gs2-sdxl (GS-2 SDXL) + gs1-flux (GS-1 FLUX)
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admin9webs
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---
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name: gs1-flux
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description: 调用 GS-1 (192.168.9.113) ComfyUI FLUX.1-dev 图像生成 — txt2img/img2img/填充。GGUF Q5_K_S 模型,V100 双卡。触发:FLUX 出图、高质量图片、复杂构图、产品图、图生图、局部重绘、inpaint。
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version: 1.0.0
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author: 9Webs
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license: internal
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platforms: [linux]
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triggers:
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- FLUX
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- flux1
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- 高质量出图
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- ComfyUI
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- inpaint
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- 局部重绘
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- 图生图
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---
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# GS-1 FLUX.1-dev 图像生成 (ComfyUI API)
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用 GS-1 的 ComfyUI + FLUX.1-dev (GGUF Q5_K_S) 生成高质量图片。直连 `192.168.9.113:8188` 即可。
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## 服务拓扑
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| 项 | 值 |
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|----|----|
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| 节点 | GS-1 = 192.168.9.113 (2× Tesla V100-SXM2-16GB) |
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| ComfyUI | `http://192.168.9.113:8188` (v0.25.0) |
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| UNet | `flux1-dev-Q5_K_S.gguf` (GGUF, V100 无 bf16 用 Q5) |
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| 填充模型 | `flux1-fill-dev-Q5_K_S.gguf` (inpaint/局部重绘) |
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| CLIP | `t5-v1_1-xxl-encoder-Q5_K_M.gguf` + `clip_l.safetensors` (type=flux) |
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| VAE | `ae.safetensors` |
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## 调用方式 (ComfyUI REST API)
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1. **POST `/prompt`** 提交 API 格式工作流 (见 workflows/flux_txt2img.json),返回 `prompt_id`
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2. **轮询 `GET /history/{prompt_id}`** 直到 `status.completed == true`
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3. **取图 `GET /view?filename=<name>&type=output`** 下载 PNG
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### 参考参数 (已实测)
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- **steps 20** (18-28 均可;GGUF 量化,步数低会糊)
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- **cfg 1.0** (FLUX 用 cfg≈1 + guidance;标准 KSampler 下 cfg 1.0 即可)
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- **1024×1024** (FLUX 原生;V100 16GB 上限约 1024,超高会 OOM)
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- **sampler `euler` / scheduler `simple`**, seed 可固定
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- **耗时约 100-120 秒/张** (V100 无 flash-attention;首次调用含模型加载更慢)
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### 脚本 (scripts/flux_txt2img.py)
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```bash
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python3 ~/.hermes/skills/gs1-flux/scripts/flux_txt2img.py "prompt here" [--steps 20] [--seed -1]
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# 输出: /tmp/flux_out/flux_*.png
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```
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## 健康检查
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```bash
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curl -s http://192.168.9.113:8188/system_stats | head -c 200 # 返回 JSON = 正常
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curl -s http://192.168.9.113:8188/object_info/UnetLoaderGGUF | grep -o 'flux1[^"]*' # 模型在位
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curl -s http://192.168.9.113:8188/queue | python3 -c "import json,sys; d=json.load(sys.stdin); print('running:', len(d['queue_running']), 'pending:', len(d['queue_pending']))"
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```
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## 排障
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- **提交 400** → 工作流节点错误,读 `node_errors` 详情 (常见: CLIPTextEncodeFlux 需 clip_l/t5xxl/guidance 三个输入)
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- **长时间不出图** → 查队列 `queue` 是否堆积;单实例顺序执行,批量任务排队
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- **OOM** → 降到 768×768 或减少 batch
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- **换风格/复杂提示** → FLUX 对提示词敏感,直接写详细英文描述;负向提示基本不需要
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## 服务端排障
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```bash
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sshpass -p 'Tt123456!' ssh admin9webs@192.168.9.113 'systemctl --user status comfyui* --no-pager | head -20'
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```
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## 陷阱
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1. **Q5_K_S 量化**:图片质量略低于 fp8/bf16,但 V100 无 bf16 只能跑 GGUF;复杂文字/人脸注意检查。
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2. **每次约 2 分钟**:批量任务要轮询串行,不要并发提交同实例。
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3. **图片在 ComfyUI output 目录** (`~/ComfyUI/output/`),推荐客户端用 /view 下载,不依赖服务端目录。
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4. **Flux Fill** (flux1-fill-dev) 用于局部重绘/inpaint,需配合 mask 工作流。
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## 相关
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- SDXL 出图用 `gs2-sdxl` 技能 (GS-2 :7861/:7862,快但质量略低)
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- 配图策略: 快速草图用 SDXL,最终成品/复杂构图用 FLUX
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@@ -0,0 +1,35 @@
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import json, urllib.request, urllib.error, time
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BASE = 'http://192.168.9.113:8188'
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wf = {
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"1": {"class_type": "UnetLoaderGGUF", "inputs": {"unet_name": "flux1-dev-Q5_K_S.gguf"}},
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"2": {"class_type": "DualCLIPLoaderGGUF", "inputs": {"clip_name1": "t5-v1_1-xxl-encoder-Q5_K_M.gguf", "clip_name2": "clip_l.safetensors", "type": "flux"}},
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"3": {"class_type": "VAELoader", "inputs": {"vae_name": "ae.safetensors"}},
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"4": {"class_type": "CLIPTextEncode", "inputs": {"clip": ["2", 0], "text": "a red apple on a wooden table, product photo, studio lighting"}},
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"5": {"class_type": "CLIPTextEncode", "inputs": {"clip": ["2", 0], "text": "blurry, low quality"}},
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"6": {"class_type": "EmptyLatentImage", "inputs": {"width": 1024, "height": 1024, "batch_size": 1}},
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"7": {"class_type": "KSampler", "inputs": {"model": ["1", 0], "positive": ["4", 0], "negative": ["5", 0], "latent_image": ["6", 0], "seed": 12345, "steps": 20, "cfg": 1.0, "sampler_name": "euler", "scheduler": "simple", "denoise": 1.0}},
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"8": {"class_type": "VAEDecode", "inputs": {"samples": ["7", 0], "vae": ["3", 0]}},
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"9": {"class_type": "SaveImage", "inputs": {"filename_prefix": "flux_test", "images": ["8", 0]}},
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}
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req = urllib.request.Request(BASE + '/prompt', data=json.dumps({"prompt": wf}).encode(), headers={'Content-Type': 'application/json'})
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try:
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r = json.loads(urllib.request.urlopen(req, timeout=30).read())
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pid = r.get('prompt_id')
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print('prompt_id:', pid, '| node_errors:', r.get('node_errors'))
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if not pid: raise SystemExit(1)
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for i in range(60):
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time.sleep(5)
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try:
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h = json.loads(urllib.request.urlopen(BASE + '/history/' + pid, timeout=10).read())
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except Exception: continue
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if pid in h:
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st = h[pid].get('status', {})
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if st.get('completed') or st.get('status_str') == 'success':
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for nid, o in h[pid].get('outputs', {}).items():
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for img in o.get('images', []):
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print('出图:', img.get('filename'), '| 节点', nid)
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print('FLUX 生成成功!'); raise SystemExit(0)
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elif st.get('status_str') == 'error':
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print('FLUX 错误:', json.dumps(st)[:500]); raise SystemExit(1)
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except urllib.error.HTTPError as e:
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print('HTTP', e.code, e.read().decode()[:600])
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