xhs_factory/sd_service.py
zhoujie dbe695b551 feat(automation): 新增自动化运营防重复机制与统计功能
- 新增操作历史记录,防止对同一笔记重复评论、点赞、收藏和回复
- 新增每日操作统计与限额管理,包含评论、点赞、收藏、发布和回复的独立上限
- 新增错误冷却机制,连续错误后自动暂停操作一段时间
- 新增运营时段控制,允许设置每日自动运营的开始和结束时间
- 新增收藏功能,支持一键收藏和定时自动收藏
- 新增随机人设池,提供25种预设小红书博主风格人设,支持随机切换
- 扩充主题池、风格池和评论关键词池,增加运营多样性
- 优化自动化调度器,显示下次执行时间和实时统计摘要
- 优化发布功能,增加本地备份机制,失败时保留文案和图片

🐛 fix(llm): 修复绘图提示词中的人物特征要求

- 在绘图提示词模板中明确要求人物必须是东亚面孔的中国人
- 添加具体的人物特征描述,如黑发、深棕色眼睛、精致五官等
- 禁止出现西方人或欧美人特征
- 调整整体画面风格偏向东方审美、清新淡雅和小红书风格
2026-02-09 20:50:05 +08:00

159 lines
5.2 KiB
Python

"""
Stable Diffusion 服务模块
封装对 SD WebUI API 的调用,支持 txt2img 和 img2img
"""
import requests
import base64
import io
import logging
from PIL import Image
logger = logging.getLogger(__name__)
SD_TIMEOUT = 900 # 图片生成可能需要较长时间
# 默认反向提示词(针对 JuggernautXL / SDXL 优化,偏向东方审美)
DEFAULT_NEGATIVE = (
"nsfw, nudity, lowres, bad anatomy, bad hands, text, error, missing fingers, "
"extra digit, fewer digits, cropped, worst quality, low quality, normal quality, "
"jpeg artifacts, signature, watermark, blurry, deformed, mutated, disfigured, "
"ugly, duplicate, morbid, mutilated, poorly drawn face, poorly drawn hands, "
"extra limbs, fused fingers, too many fingers, long neck, username, "
"out of frame, distorted, oversaturated, underexposed, overexposed, "
"western face, european face, caucasian, deep-set eyes, high nose bridge, "
"blonde hair, red hair, blue eyes, green eyes, freckles, thick body hair"
)
class SDService:
"""Stable Diffusion WebUI API 封装"""
def __init__(self, sd_url: str = "http://127.0.0.1:7860"):
self.sd_url = sd_url.rstrip("/")
def check_connection(self) -> tuple[bool, str]:
"""检查 SD 服务是否可用"""
try:
resp = requests.get(f"{self.sd_url}/sdapi/v1/sd-models", timeout=5)
if resp.status_code == 200:
count = len(resp.json())
return True, f"SD 已连接,{count} 个模型可用"
return False, f"SD 返回异常状态: {resp.status_code}"
except requests.exceptions.ConnectionError:
return False, "SD WebUI 未启动或端口错误"
except Exception as e:
return False, f"SD 连接失败: {e}"
def get_models(self) -> list[str]:
"""获取 SD 模型列表"""
resp = requests.get(f"{self.sd_url}/sdapi/v1/sd-models", timeout=5)
resp.raise_for_status()
return [m["title"] for m in resp.json()]
def switch_model(self, model_name: str):
"""切换 SD 模型"""
try:
requests.post(
f"{self.sd_url}/sdapi/v1/options",
json={"sd_model_checkpoint": model_name},
timeout=60,
)
except Exception as e:
logger.warning("模型切换失败: %s", e)
def txt2img(
self,
prompt: str,
negative_prompt: str = DEFAULT_NEGATIVE,
model: str = None,
steps: int = 30,
cfg_scale: float = 5.0,
width: int = 832,
height: int = 1216,
batch_size: int = 2,
seed: int = -1,
sampler_name: str = "DPM++ 2M",
scheduler: str = "Karras",
) -> list[Image.Image]:
"""文生图(参数针对 JuggernautXL 优化)"""
if model:
self.switch_model(model)
payload = {
"prompt": prompt,
"negative_prompt": negative_prompt,
"steps": steps,
"cfg_scale": cfg_scale,
"width": width,
"height": height,
"batch_size": batch_size,
"seed": seed,
"sampler_name": sampler_name,
"scheduler": scheduler,
}
resp = requests.post(
f"{self.sd_url}/sdapi/v1/txt2img",
json=payload,
timeout=SD_TIMEOUT,
)
resp.raise_for_status()
images = []
for img_b64 in resp.json().get("images", []):
img = Image.open(io.BytesIO(base64.b64decode(img_b64)))
images.append(img)
return images
def img2img(
self,
init_image: Image.Image,
prompt: str,
negative_prompt: str = DEFAULT_NEGATIVE,
denoising_strength: float = 0.5,
steps: int = 30,
cfg_scale: float = 5.0,
sampler_name: str = "DPM++ 2M",
scheduler: str = "Karras",
) -> list[Image.Image]:
"""图生图(参数针对 JuggernautXL 优化)"""
# 将 PIL Image 转为 base64
buf = io.BytesIO()
init_image.save(buf, format="PNG")
init_b64 = base64.b64encode(buf.getvalue()).decode("utf-8")
payload = {
"init_images": [init_b64],
"prompt": prompt,
"negative_prompt": negative_prompt,
"denoising_strength": denoising_strength,
"steps": steps,
"cfg_scale": cfg_scale,
"width": init_image.width,
"height": init_image.height,
"sampler_name": sampler_name,
"scheduler": scheduler,
}
resp = requests.post(
f"{self.sd_url}/sdapi/v1/img2img",
json=payload,
timeout=SD_TIMEOUT,
)
resp.raise_for_status()
images = []
for img_b64 in resp.json().get("images", []):
img = Image.open(io.BytesIO(base64.b64decode(img_b64)))
images.append(img)
return images
def get_lora_models(self) -> list[str]:
"""获取可用的 LoRA 模型列表"""
try:
resp = requests.get(f"{self.sd_url}/sdapi/v1/loras", timeout=5)
resp.raise_for_status()
return [lora["name"] for lora in resp.json()]
except Exception:
return []