350 lines
13 KiB
Python
350 lines
13 KiB
Python
import asyncio
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import hashlib
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import json
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import logging
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import mimetypes
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import os
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import random
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import re
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from pathlib import Path
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from typing import Dict, List, Optional
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from urllib.parse import urlparse
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import httpx
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from dotenv import load_dotenv
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from PIL import Image
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from db.customer_db import CustomerDatabase
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from db.image_tasks_db import TaskStatus, db as task_db
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from services.service_gemini import GeminiExtractV2Service
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from services.service_tuhui_upload import upload_to_tuhui
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from services.service_wecom_bot import wecom_bot_service
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load_dotenv()
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logger = logging.getLogger("cs_agent")
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AUTO_PROCESS_PRICE = int(os.getenv("AUTO_PROCESS_DEFAULT_PRICE", "12"))
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AUTO_PROCESS_CATEGORY = os.getenv("AUTO_PROCESS_CATEGORY", "设计素材")
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AUTO_PROCESS_ROOT = Path(
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os.getenv("AUTO_PROCESS_ROOT", str(Path(__file__).resolve().parents[1] / "runtime" / "auto_processed"))
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)
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_DOWNLOAD_REFERERS = (
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"https://www.taobao.com/",
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"https://item.taobao.com/",
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"https://detail.tmall.com/",
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)
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_DOWNLOAD_HEADERS = {
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"User-Agent": (
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"Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
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"AppleWebKit/537.36 (KHTML, like Gecko) "
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"Chrome/133.0.0.0 Safari/537.36"
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),
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"Accept": "image/avif,image/webp,image/apng,image/svg+xml,image/*,*/*;q=0.8",
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"Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8",
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"Cache-Control": "no-cache",
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"Pragma": "no-cache",
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}
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_CONTENT_TYPE_SUFFIX = {
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"image/jpeg": ".jpg",
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"image/jpg": ".jpg",
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"image/png": ".png",
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"image/webp": ".webp",
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"image/avif": ".avif",
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"image/gif": ".gif",
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}
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_DESIGNER_ALIAS_PREFIXES = ("青木", "星野", "白川", "南栀", "言川", "木也", "安可", "拾光", "云岸", "知禾")
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_DESIGNER_ALIAS_SUFFIXES = ("设计", "studio", "视觉", "创意", "图像", "工坊", "素材", "像素")
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def _safe_name(text: str, fallback: str = "image") -> str:
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cleaned = re.sub(r"[^0-9A-Za-z\u4e00-\u9fa5_-]+", "_", str(text or "").strip())
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cleaned = cleaned.strip("_")
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return cleaned[:40] or fallback
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def _suffix_from_url(url: str) -> str:
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path = urlparse(str(url or "")).path
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suffix = Path(path).suffix.lower()
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if suffix in {".png", ".jpg", ".jpeg", ".webp"}:
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return suffix
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return ".png"
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def _build_processing_prompt(intent: str, requirement_text: str, analysis: Dict) -> str:
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base_prompt = str((analysis or {}).get("gemini_prompt") or "").strip()
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req = str(requirement_text or "").strip()
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if base_prompt:
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return base_prompt
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if intent == "repair":
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return f"根据客户需求“{req or '高清修复'}”，保留主体和构图，做高清修复并补足细节。"
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return f"根据客户需求“{req or '找原图'}”，严格参考原图元素与构图，生成完整干净的高质量素材图。"
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def _build_upload_title(intent: str, analysis: Dict, requirement_text: str, idx: int) -> str:
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analysis = analysis or {}
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suggested = _safe_name(str(analysis.get("title_suggest") or ""), "")
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if suggested:
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return suggested
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subject = _safe_name(str(analysis.get("subject") or ""), "")
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proc_type = _safe_name(str(analysis.get("proc_type") or ""), "")
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parts = [part for part in (subject, proc_type) if part]
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if parts:
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base = "_".join(parts[:2])
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else:
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base = "图片素材"
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return base
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def _build_designer_alias() -> str:
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return f"{random.choice(_DESIGNER_ALIAS_PREFIXES)}{random.choice(_DESIGNER_ALIAS_SUFFIXES)}"
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class AutoImagePipelineService:
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def __init__(self):
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self.customer_db = CustomerDatabase()
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@staticmethod
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def _resolve_download_path(dest_path: Path, content_type: str, image_url: str) -> Path:
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normalized_type = str(content_type or "").split(";", 1)[0].strip().lower()
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suffix = _CONTENT_TYPE_SUFFIX.get(normalized_type, "")
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if not suffix:
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guessed, _ = mimetypes.guess_type(str(image_url or ""))
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suffix = _CONTENT_TYPE_SUFFIX.get(str(guessed or "").lower(), "")
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suffix = suffix or dest_path.suffix or ".bin"
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return dest_path.with_suffix(suffix)
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@staticmethod
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def _normalize_image_for_gemini(image_path: Path) -> Path:
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suffix = image_path.suffix.lower()
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with Image.open(image_path) as img:
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is_animated = bool(getattr(img, "is_animated", False)) or int(getattr(img, "n_frames", 1) or 1) > 1
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needs_convert = suffix in {".avif", ".webp", ".gif"} or is_animated or img.mode not in ("RGB", "L")
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if not needs_convert:
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return image_path
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normalized_path = image_path.with_suffix(".jpg")
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if is_animated:
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try:
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img.seek(0)
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except Exception:
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pass
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if img.mode not in ("RGB", "L"):
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img = img.convert("RGB")
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img.save(normalized_path, format="JPEG", quality=95)
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logger.info(
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f"[AutoImagePipeline] 已转换图片格式供Gemini使用: src={image_path} normalized={normalized_path}"
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)
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return normalized_path
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async def _download_image(self, image_url: str, dest_path: Path) -> Path:
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dest_path.parent.mkdir(parents=True, exist_ok=True)
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timeout = httpx.Timeout(60.0, connect=20.0)
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last_error: Optional[Exception] = None
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async with httpx.AsyncClient(timeout=timeout, follow_redirects=True) as client:
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for referer in _DOWNLOAD_REFERERS:
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for attempt in range(1, 4):
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headers = dict(_DOWNLOAD_HEADERS)
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headers["Referer"] = referer
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try:
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response = await client.get(image_url, headers=headers)
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if response.status_code in (403, 420, 429):
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raise httpx.HTTPStatusError(
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f"download blocked status={response.status_code}",
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request=response.request,
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response=response,
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)
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response.raise_for_status()
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resolved_path = self._resolve_download_path(
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dest_path,
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response.headers.get("content-type", ""),
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image_url,
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)
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resolved_path.write_bytes(response.content)
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logger.info(
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f"[AutoImagePipeline] 图片下载成功 status={response.status_code} "
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f"referer={referer} path={resolved_path}"
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)
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return resolved_path
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except Exception as e:
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last_error = e
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logger.warning(
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f"[AutoImagePipeline] 图片下载失败 attempt={attempt}/3 "
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f"referer={referer} url={image_url} err={e}"
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)
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if attempt < 3:
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await asyncio.sleep(attempt)
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raise RuntimeError(f"下载原图失败: {last_error}")
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@staticmethod
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def _format_transfer_notice(
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customer_id: str,
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acc_id: str,
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designer_name: str,
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requirement_text: str,
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intent: str,
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image_urls: List[str],
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) -> str:
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lines = [
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"【AI自动转设计师】",
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f"店铺：{acc_id or '-'}",
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f"客户：{customer_id or '-'}",
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f"需求：{requirement_text or '-'}",
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f"类型：{'高清修复' if intent == 'repair' else '找原图'}",
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f"默认价格：{AUTO_PROCESS_PRICE}元",
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]
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if image_urls:
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lines.append("原图URL：")
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lines.extend(image_urls[:5])
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return "\n".join(lines)
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@staticmethod
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def _format_finish_notice(
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customer_id: str,
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acc_id: str,
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designer_name: str,
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links: List[Dict[str, str]],
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failures: List[str],
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) -> str:
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lines = [
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"【AI处理完成】",
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f"店铺：{acc_id or '-'}",
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f"客户：{customer_id or '-'}",
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f"默认价格：{AUTO_PROCESS_PRICE}元",
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]
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if links:
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lines.append("处理结果：")
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for idx, item in enumerate(links, 1):
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lines.append(f"{idx}. 图绘链接：{item.get('download_url') or '-'}")
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lines.append(f" 处理后图片：{item.get('image_url') or '-'}")
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lines.append(f" 原图URL：{item.get('source_url') or '-'}")
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if failures:
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lines.append("失败项：")
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lines.extend(failures[:5])
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return "\n".join(lines)
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async def process_and_notify(
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self,
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*,
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session_key: str,
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customer_id: str,
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acc_id: str,
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designer_name: str,
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requirement_text: str,
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image_urls: List[str],
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intent: str = "",
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) -> Dict:
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image_urls = [str(url).strip() for url in (image_urls or []) if str(url).strip()]
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if not image_urls:
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return {"success": False, "message": "no_images"}
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image_urls = image_urls[:1]
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profile = self.customer_db.get_customer(session_key)
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analysis = {}
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if getattr(profile, "last_image_analysis", ""):
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try:
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analysis = json.loads(profile.last_image_analysis)
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except Exception:
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analysis = {}
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if not intent:
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intent = "repair" if "修复" in requirement_text else "find_original"
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await wecom_bot_service.send_text(
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self._format_transfer_notice(
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customer_id=customer_id,
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acc_id=acc_id,
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designer_name=designer_name,
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requirement_text=requirement_text,
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intent=intent,
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image_urls=image_urls,
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)
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)
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pipeline_root = AUTO_PROCESS_ROOT / _safe_name(customer_id, "customer")
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pipeline_root.mkdir(parents=True, exist_ok=True)
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gemini_service = GeminiExtractV2Service()
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uploaded_links: List[Dict[str, str]] = []
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failures: List[str] = []
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for idx, image_url in enumerate(image_urls, 1):
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digest = hashlib.md5(f"{customer_id}|{acc_id}|{image_url}".encode("utf-8")).hexdigest()[:10]
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input_path = pipeline_root / f"{digest}_src{_suffix_from_url(image_url)}"
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output_path = pipeline_root / f"{digest}_out.png"
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title = _build_upload_title(intent, analysis, requirement_text, idx)
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prompt = _build_processing_prompt(intent, requirement_text, analysis)
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task_id = task_db.add_task(
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customer_id=customer_id,
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platform="qianniu",
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original_image=image_url,
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operation=intent or "auto_process",
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requirements=requirement_text,
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status=TaskStatus.PROCESSING.value,
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)
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try:
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input_path = await self._download_image(image_url, input_path)
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input_path = self._normalize_image_for_gemini(input_path)
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success, message, data = await gemini_service.extract_pattern(
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str(input_path),
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str(output_path),
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custom_prompt=prompt,
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aspect_ratio=str((analysis or {}).get("aspect_ratio") or "1:1"),
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)
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if not success or not output_path.exists():
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if task_id:
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task_db.update_status(task_id, TaskStatus.FAILED.value)
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failures.append(f"{idx}. Gemini失败：{message}")
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continue
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upload_result = await upload_to_tuhui(
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image_path=str(output_path),
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title=title,
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description=requirement_text or prompt[:120],
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price=AUTO_PROCESS_PRICE,
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category=AUTO_PROCESS_CATEGORY,
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tags="AI处理,自动转接",
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designer_name=_build_designer_alias(),
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)
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if not upload_result.success:
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if task_id:
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task_db.update_status(task_id, TaskStatus.FAILED.value)
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failures.append(f"{idx}. 图绘上传失败：{upload_result.message}")
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continue
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if task_id:
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task_db.update_status(task_id, TaskStatus.COMPLETED.value, upload_result.download_url)
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uploaded_links.append(
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{
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"download_url": upload_result.download_url,
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"image_url": upload_result.image_url,
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"source_url": image_url,
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"work_id": str(upload_result.work_id),
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}
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)
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except Exception as e:
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if task_id:
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task_db.update_status(task_id, TaskStatus.FAILED.value)
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failures.append(f"{idx}. 处理异常：{e}")
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await wecom_bot_service.send_text(
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self._format_finish_notice(
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customer_id=customer_id,
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acc_id=acc_id,
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designer_name=designer_name,
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links=uploaded_links,
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failures=failures,
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)
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)
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return {
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"success": bool(uploaded_links),
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"uploaded": uploaded_links,
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"failures": failures,
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}
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auto_image_pipeline_service = AutoImagePipelineService()
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