823 lines
28 KiB
Python
823 lines
28 KiB
Python
"""AI 图片生成服务：后端请求 + 本地缓存管理。
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后端接口（生产/测试环境）：
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POST {API_BASE_URL}{API_GENERATE_PATH}
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body: {"user_message": str, "session_id": str, "upload_image_url"?: str}
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resp: {"code": 200, "message": "", "data": {"imageUrl": "..."}}
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POST {API_BASE_URL}{API_UPLOAD_PATH} # multipart/form-data, field: file
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resp: {"code": 200, "message": "", "data": {"upload_image_url": "..."}}
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带 ``upload_image_url`` 启用"图生图"模式；多轮对话需将上一轮返回的 imageUrl
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作为下一轮请求的 upload_image_url（由 panel 通过会话级缓存自动维护）。
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缓存目录：``settings/ai_image_cache/``，每张图片有同名的 ``.json`` 侧车记录。
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"""
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from __future__ import annotations
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import datetime as _dt
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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 sys
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import shutil
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import threading
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import time
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import uuid
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from io import BytesIO
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from dataclasses import dataclass, asdict
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from typing import Callable, List, Optional
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from urllib.error import HTTPError
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from urllib.parse import urlparse
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from urllib.request import Request, urlopen
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from PIL import Image
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logger = logging.getLogger(__name__)
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# ---------- 常量 ----------
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_CACHE_DIRNAME = os.path.join("settings", "ai_image_cache")
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_META_SUFFIX = ".json"
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_SUPPORTED_IMG_EXT = (".png", ".jpg", ".jpeg", ".bmp", ".webp")
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# 测试环境后端
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# API_BASE_URL = "http://10.201.44.70:9008/ai-agent/"
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API_BASE_URL = "https://rd-mokadisplay.tcl.com/ai-agent/"
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API_GENERATE_PATH = "api/v1/pqtest/generate"
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API_UPLOAD_PATH = "api/v1/pqtest/upload"
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API_TIMEOUT = 300.0 # 后端最长 120s，留余量
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API_UPLOAD_TIMEOUT = 60.0
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# 上传接口限制（来自接口文档）
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UPLOAD_MAX_BYTES = 10 * 1024 * 1024
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UPLOAD_MAX_PIXELS = 4096
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UPLOAD_ALLOWED_EXT = (".png", ".jpg", ".jpeg")
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# 兼容旧名（如其他模块仍引用）
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API_PATH = API_GENERATE_PATH
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# 进程级会话 id（多轮对话需保持一致），可通过 ``reset_session`` 重置
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_session_id: str = str(uuid.uuid4())
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_session_lock = threading.Lock()
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def get_session_id() -> str:
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with _session_lock:
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return _session_id
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def set_session_id(session_id: str) -> str:
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"""切换到指定会话。空值会抛错"""
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global _session_id
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sid = (session_id or "").strip()
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if not sid:
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raise ValueError("session_id 不能为空")
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with _session_lock:
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old = _session_id
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_session_id = sid
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return _session_id
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def reset_session() -> str:
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"""开启新一轮会话，返回新的 session_id。"""
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global _session_id
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with _session_lock:
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old = _session_id
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_session_id = str(uuid.uuid4())
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return _session_id
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def _mask_sid(sid: str) -> str:
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"""日志安全展示：仅保留前 8 位。"""
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if not sid:
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return "(none)"
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return f"{sid[:8]}…"
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def _truncate(text: str, n: int = 80) -> str:
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s = (text or "").replace("\n", " ").strip()
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return s if len(s) <= n else s[:n] + "…"
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# ---------- 数据结构 ----------
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@dataclass
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class AIImageRecord:
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"""一条缓存记录。
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字段说明：
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- ``id``: 唯一 id，等同于磁盘文件名（不含扩展名），格式 ``{时间戳}_{md5前8}``。
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- ``prompt``: 用户原始输入（完整保留，用于回溯/调试，不应被改写）。
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- ``title``: 用户自定义展示标题（重命名时写入），UI 优先使用，留空则回退 prompt 第一行截断。
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- ``image_path``: 图片在缓存目录中的绝对路径。
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- ``created_at``: ISO8601 时间字符串。
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- ``extra``: 其它元数据，至少包含 ``source`` 与 ``session_id``（标识属于哪一轮对话）。
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"""
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id: str
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prompt: str
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image_path: str
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created_at: str # ISO8601
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extra: Optional[dict] = None
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title: Optional[str] = None
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def to_json(self) -> str:
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return json.dumps(asdict(self), ensure_ascii=False, indent=2)
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@property
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def display_name(self) -> str:
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"""UI 展示名：title 优先，否则回退 prompt 第一行。"""
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if self.title:
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return self.title.strip()
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first = (self.prompt or "").strip().splitlines()[0] if self.prompt else ""
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return first or "(未命名)"
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@property
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def session_id(self) -> str:
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if isinstance(self.extra, dict):
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return str(self.extra.get("session_id") or "")
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return ""
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# ---------- 后端 API ----------
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def _api_endpoint(path: str = API_GENERATE_PATH) -> str:
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base = API_BASE_URL if API_BASE_URL.endswith("/") else API_BASE_URL + "/"
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return base + path.lstrip("/")
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def _pretty_json_text(value) -> str:
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"""把对象或 JSON 字符串格式化为易读文本；失败则回退原始字符串。"""
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try:
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if isinstance(value, (dict, list)):
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return json.dumps(value, ensure_ascii=False, indent=2)
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text = "" if value is None else str(value)
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parsed = json.loads(text)
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return json.dumps(parsed, ensure_ascii=False, indent=2)
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except Exception:
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return "" if value is None else str(value)
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def _call_pqtest_generate(
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user_message: str,
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session_id: str,
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upload_image_url: Optional[str] = None,
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timeout: float = API_TIMEOUT,
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) -> str:
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"""调用后端 ``api/v1/pqtest/generate``，返回 imageUrl。失败抛异常。
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``upload_image_url`` 传入时启用"图生图"模式。
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"""
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body: dict = {"user_message": user_message, "session_id": session_id}
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if upload_image_url:
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body["upload_image_url"] = upload_image_url
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payload = json.dumps(body, ensure_ascii=False).encode("utf-8")
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request_headers = {
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"Content-Type": "application/json; charset=utf-8",
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"Accept": "application/json",
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"User-Agent": "pqAutomationApp/1.0",
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}
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endpoint = _api_endpoint(API_GENERATE_PATH)
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logger.info(
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"[AIImage] 请求生成 sid=%s mode=%s prompt_len=%d prompt=%r ref=%s",
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_mask_sid(session_id),
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"img2img" if upload_image_url else "txt2img",
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len(user_message or ""),
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_truncate(user_message),
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upload_image_url or "-",
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)
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logger.info(
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"[AIImage][REQUEST]\nendpoint=%s\nmethod=POST\ntimeout=%.1fs\nheaders=%s\nbody=%s",
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endpoint,
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timeout,
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_pretty_json_text(request_headers),
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_pretty_json_text(payload.decode("utf-8", errors="replace")),
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)
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request = Request(
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endpoint,
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data=payload,
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method="POST",
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headers=request_headers,
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)
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t0 = time.monotonic()
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try:
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with urlopen(request, timeout=timeout) as response:
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raw = response.read()
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http_status = response.status
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response_headers = dict(response.headers.items())
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raw_text = raw.decode("utf-8", errors="replace")
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logger.info(
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"[AIImage][RESPONSE]\nstatus=%s\nheaders=%s\nbody=%s",
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http_status,
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_pretty_json_text(response_headers),
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_pretty_json_text(raw_text),
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)
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except HTTPError as exc:
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elapsed = time.monotonic() - t0
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err_raw = b""
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try:
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err_raw = exc.read() or b""
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except Exception:
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err_raw = b""
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err_text = err_raw.decode("utf-8", errors="replace") if err_raw else ""
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err_headers = {}
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try:
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if exc.headers is not None:
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err_headers = dict(exc.headers.items())
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except Exception:
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err_headers = {}
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logger.error(
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"[AIImage][RESPONSE_ERROR] sid=%s elapsed=%.2fs status=%s reason=%s\nheaders=%s\nbody=%s",
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_mask_sid(session_id),
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elapsed,
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getattr(exc, "code", "?"),
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str(exc),
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_pretty_json_text(err_headers),
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_pretty_json_text(err_text),
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)
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raise
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except Exception as exc:
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elapsed = time.monotonic() - t0
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logger.error(
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"[AIImage] 请求异常 sid=%s elapsed=%.2fs %s: %s",
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_mask_sid(session_id), elapsed, type(exc).__name__, exc,
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)
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raise
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elapsed = time.monotonic() - t0
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logger.info("[AIImage] HTTP %s 收到 %d bytes elapsed=%.2fs", http_status, len(raw), elapsed)
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try:
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result = json.loads(raw.decode("utf-8"))
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except Exception as exc:
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raw_text = raw.decode("utf-8", errors="replace")
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logger.error("[AIImage] 响应解析失败 sid=%s raw=%s", _mask_sid(session_id), raw_text)
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raise RuntimeError(f"AI 接口返回非 JSON：{raw_text}") from exc
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code = result.get("code")
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message = result.get("message") or ""
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data = result.get("data") or {}
|
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image_url = (data.get("imageUrl") or "").strip()
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if code != 200 or not image_url:
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logger.warning(
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"[AIImage] 接口失败 sid=%s code=%s msg=%r",
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_mask_sid(session_id), code, message,
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)
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raise RuntimeError(f"AI 接口失败 code={code} msg={message or '生成失败'}")
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logger.info(
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"[AIImage] 生成成功 sid=%s elapsed=%.2fs url=%s",
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_mask_sid(session_id), elapsed, image_url,
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)
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return image_url
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|
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|
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def _call_pqtest_upload(file_path: str, timeout: float = API_UPLOAD_TIMEOUT, auto_resize: bool = True) -> str:
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"""以 multipart/form-data 上传本地图片，返回 ``upload_image_url``。失败抛异常。
|
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|
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参数：
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auto_resize: True 时，若图片超过 4096×4096 或 10MB 则自动缩放/重压
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"""
|
||
if not file_path or not os.path.isfile(file_path):
|
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raise FileNotFoundError(f"图片文件不存在: {file_path}")
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ext = os.path.splitext(file_path)[1].lower()
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if ext not in UPLOAD_ALLOWED_EXT:
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raise ValueError(f"不支持的图片格式 ({ext})，仅支持 PNG/JPG/JPEG")
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try:
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with Image.open(file_path) as img:
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iw, ih = img.size
|
||
except Exception as exc:
|
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raise ValueError(f"无法读取图片: {exc}") from exc
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|
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# 检查大小，如需则缩放
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size = os.path.getsize(file_path)
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needs_resize = (iw > UPLOAD_MAX_PIXELS or ih > UPLOAD_MAX_PIXELS or size > UPLOAD_MAX_BYTES)
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if needs_resize:
|
||
if not auto_resize:
|
||
if iw > UPLOAD_MAX_PIXELS or ih > UPLOAD_MAX_PIXELS:
|
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raise ValueError(f"分辨率超过 4096×4096（当前 {iw}×{ih}）")
|
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else:
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raise ValueError(f"图片超过 10MB 限制（当前 {size/1024/1024:.2f}MB）")
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|
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# 自动缩放：等比例缩放至 4096×4096 以内
|
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logger.info("[AIImage][UPLOAD] 自动缩放 %dx%d (%.1fMB) 至 ≤4096×4096",
|
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iw, ih, size/1024/1024)
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scale = min(UPLOAD_MAX_PIXELS / iw, UPLOAD_MAX_PIXELS / ih, 1.0)
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||
new_w, new_h = max(1, int(iw * scale)), max(1, int(ih * scale))
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with Image.open(file_path) as img:
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img_resized = img.resize((new_w, new_h), Image.LANCZOS)
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# 重压至 10MB 以下
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# 首先尝试原格式
|
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tmp_io = BytesIO()
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fmt = "PNG" if ext == ".png" else "JPEG"
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save_kw = {"format": fmt}
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img_resized.save(tmp_io, **save_kw)
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tmp_bytes = tmp_io.getvalue()
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||
|
||
if len(tmp_bytes) <= UPLOAD_MAX_BYTES:
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file_bytes = tmp_bytes
|
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else:
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# 原格式太大，转换为 JPEG 并压缩
|
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logger.info("[AIImage][UPLOAD] 原格式超过限制，转为 JPEG 并压缩")
|
||
quality = 95
|
||
while quality >= 50:
|
||
tmp_io = BytesIO()
|
||
img_resized.save(tmp_io, format="JPEG", quality=quality, optimize=True)
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tmp_bytes = tmp_io.getvalue()
|
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if len(tmp_bytes) <= UPLOAD_MAX_BYTES:
|
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file_bytes = tmp_bytes
|
||
break
|
||
quality -= 5
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else:
|
||
# 即使 quality=50 还是太大，也用这个版本上传（后端会处理）
|
||
file_bytes = tmp_bytes
|
||
|
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logger.info("[AIImage][UPLOAD] 缩放完成 %dx%d (%.1fMB)",
|
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new_w, new_h, len(file_bytes)/1024/1024)
|
||
iw, ih = new_w, new_h
|
||
else:
|
||
with open(file_path, "rb") as f:
|
||
file_bytes = f.read()
|
||
|
||
mime = mimetypes.guess_type(file_path)[0] or "application/octet-stream"
|
||
boundary = "----pqAuto" + uuid.uuid4().hex
|
||
filename = os.path.basename(file_path)
|
||
crlf = b"\r\n"
|
||
body = b"".join([
|
||
b"--", boundary.encode("ascii"), crlf,
|
||
b'Content-Disposition: form-data; name="file"; filename="',
|
||
filename.encode("utf-8"), b'"', crlf,
|
||
b"Content-Type: ", mime.encode("ascii"), crlf, crlf,
|
||
file_bytes, crlf,
|
||
b"--", boundary.encode("ascii"), b"--", crlf,
|
||
])
|
||
|
||
endpoint = _api_endpoint(API_UPLOAD_PATH)
|
||
headers = {
|
||
"Content-Type": f"multipart/form-data; boundary={boundary}",
|
||
"Accept": "application/json",
|
||
"User-Agent": "pqAutomationApp/1.0",
|
||
"Content-Length": str(len(body)),
|
||
}
|
||
logger.info(
|
||
"[AIImage][UPLOAD] file=%s size=%dB mime=%s wh=%dx%d -> %s",
|
||
filename, len(file_bytes), mime, iw, ih, endpoint,
|
||
)
|
||
request = Request(endpoint, data=body, method="POST", headers=headers)
|
||
t0 = time.monotonic()
|
||
try:
|
||
with urlopen(request, timeout=timeout) as response:
|
||
raw = response.read()
|
||
http_status = response.status
|
||
raw_text = raw.decode("utf-8", errors="replace")
|
||
logger.info("[AIImage][UPLOAD_RESP]\nstatus=%s\nbody=%s",
|
||
http_status, _pretty_json_text(raw_text))
|
||
except HTTPError as exc:
|
||
err_raw = b""
|
||
try:
|
||
err_raw = exc.read() or b""
|
||
except Exception:
|
||
pass
|
||
err_text = err_raw.decode("utf-8", errors="replace") if err_raw else ""
|
||
logger.error("[AIImage][UPLOAD_ERR] status=%s reason=%s body=%s",
|
||
getattr(exc, "code", "?"), str(exc), _pretty_json_text(err_text))
|
||
raise
|
||
except Exception as exc:
|
||
logger.error("[AIImage][UPLOAD_ERR] %s: %s", type(exc).__name__, exc)
|
||
raise
|
||
elapsed = time.monotonic() - t0
|
||
try:
|
||
result = json.loads(raw.decode("utf-8"))
|
||
except Exception as exc:
|
||
raise RuntimeError(f"上传接口返回非 JSON：{raw_text}") from exc
|
||
code = result.get("code")
|
||
message = result.get("message") or ""
|
||
data = result.get("data") or {}
|
||
url = (data.get("upload_image_url") or "").strip()
|
||
if code != 200 or not url:
|
||
raise RuntimeError(f"上传失败 code={code} msg={message or '未知错误'}")
|
||
logger.info("[AIImage][UPLOAD_OK] elapsed=%.2fs url=%s", elapsed, url)
|
||
return url
|
||
|
||
|
||
# ---------- 缓存路径工具 ----------
|
||
|
||
|
||
def get_cache_dir(base_dir: Optional[str] = None) -> str:
|
||
"""返回缓存目录，如不存在则创建。``base_dir`` 留空时使用应用根目录。"""
|
||
if base_dir:
|
||
root = base_dir
|
||
elif getattr(sys, "frozen", False):
|
||
root = os.path.dirname(sys.executable)
|
||
else:
|
||
root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
|
||
path = os.path.join(root, _CACHE_DIRNAME)
|
||
os.makedirs(path, exist_ok=True)
|
||
return path
|
||
|
||
|
||
def _make_id(prompt: str) -> str:
|
||
stamp = _dt.datetime.now().strftime("%Y%m%d_%H%M%S_%f")
|
||
digest = hashlib.md5(prompt.encode("utf-8")).hexdigest()[:8]
|
||
return f"{stamp}_{digest}"
|
||
|
||
|
||
def _meta_path_for(image_path: str) -> str:
|
||
return os.path.splitext(image_path)[0] + _META_SUFFIX
|
||
|
||
|
||
def _sanitize_image_bytes(image_bytes: bytes, image_ext: str) -> bytes:
|
||
"""规范化图片字节，尽量去掉已知有问题的 PNG ICC profile。"""
|
||
ext = (image_ext or "").lower()
|
||
if ext not in {".png", ".jpg", ".jpeg", ".bmp", ".webp"}:
|
||
return image_bytes
|
||
try:
|
||
with Image.open(BytesIO(image_bytes)) as img:
|
||
img.load()
|
||
normalized = img.copy()
|
||
output = BytesIO()
|
||
save_kwargs = {}
|
||
if ext == ".png":
|
||
save_kwargs["icc_profile"] = None
|
||
normalized.save(output, format=normalized.format or ext.lstrip(".").upper(), **save_kwargs)
|
||
result = output.getvalue()
|
||
if result:
|
||
return result
|
||
except Exception as exc:
|
||
logger.warning("[AIImage] 图片规范化失败 ext=%s %s: %s", ext, type(exc).__name__, exc)
|
||
return image_bytes
|
||
|
||
|
||
# ---------- 读写 ----------
|
||
|
||
|
||
def list_records(base_dir: Optional[str] = None) -> List[AIImageRecord]:
|
||
"""列出缓存目录下的所有记录，按创建时间倒序（最新在前）。"""
|
||
cache_dir = get_cache_dir(base_dir)
|
||
records: List[AIImageRecord] = []
|
||
for name in os.listdir(cache_dir):
|
||
full = os.path.join(cache_dir, name)
|
||
if not (os.path.isfile(full) and name.lower().endswith(_SUPPORTED_IMG_EXT)):
|
||
continue
|
||
meta_path = _meta_path_for(full)
|
||
prompt = ""
|
||
created_at = ""
|
||
extra = None
|
||
title = None
|
||
rec_id = os.path.splitext(name)[0]
|
||
if os.path.isfile(meta_path):
|
||
try:
|
||
with open(meta_path, "r", encoding="utf-8") as f:
|
||
data = json.load(f)
|
||
prompt = data.get("prompt", "")
|
||
created_at = data.get("created_at", "")
|
||
extra = data.get("extra")
|
||
title = data.get("title")
|
||
rec_id = data.get("id", rec_id)
|
||
except Exception:
|
||
pass
|
||
if not created_at:
|
||
# fallback 到文件 mtime
|
||
try:
|
||
mtime = os.path.getmtime(full)
|
||
created_at = _dt.datetime.fromtimestamp(mtime).isoformat()
|
||
except Exception:
|
||
created_at = ""
|
||
records.append(
|
||
AIImageRecord(
|
||
id=rec_id,
|
||
prompt=prompt,
|
||
image_path=full,
|
||
created_at=created_at,
|
||
extra=extra,
|
||
title=title,
|
||
)
|
||
)
|
||
records.sort(key=lambda r: r.created_at, reverse=True)
|
||
return records
|
||
|
||
|
||
def save_image_to_cache(
|
||
prompt: str,
|
||
image_bytes: bytes,
|
||
image_ext: str = ".png",
|
||
extra: Optional[dict] = None,
|
||
base_dir: Optional[str] = None,
|
||
title: Optional[str] = None,
|
||
) -> AIImageRecord:
|
||
"""把生成的图片字节写入缓存，返回记录。"""
|
||
if not image_ext.startswith("."):
|
||
image_ext = "." + image_ext
|
||
if image_ext.lower() not in _SUPPORTED_IMG_EXT:
|
||
image_ext = ".png"
|
||
image_bytes = _sanitize_image_bytes(image_bytes, image_ext)
|
||
cache_dir = get_cache_dir(base_dir)
|
||
rec_id = _make_id(prompt)
|
||
image_path = os.path.join(cache_dir, f"{rec_id}{image_ext}")
|
||
with open(image_path, "wb") as f:
|
||
f.write(image_bytes)
|
||
|
||
record = AIImageRecord(
|
||
id=rec_id,
|
||
prompt=prompt,
|
||
image_path=image_path,
|
||
created_at=_dt.datetime.now().isoformat(timespec="seconds"),
|
||
extra=extra,
|
||
title=title,
|
||
)
|
||
try:
|
||
with open(_meta_path_for(image_path), "w", encoding="utf-8") as f:
|
||
f.write(record.to_json())
|
||
except Exception:
|
||
pass
|
||
return record
|
||
|
||
|
||
def import_image_from_url(
|
||
image_url: str,
|
||
prompt: Optional[str] = None,
|
||
extra: Optional[dict] = None,
|
||
base_dir: Optional[str] = None,
|
||
timeout: float = 20.0,
|
||
) -> AIImageRecord:
|
||
"""下载远程图片并写入缓存。"""
|
||
url = (image_url or "").strip()
|
||
if not url:
|
||
raise ValueError("图片地址不能为空")
|
||
|
||
request = Request(
|
||
url,
|
||
headers={
|
||
"User-Agent": "pqAutomationApp/1.0",
|
||
"Accept": "image/*,*/*;q=0.8",
|
||
},
|
||
)
|
||
with urlopen(request, timeout=timeout) as response:
|
||
image_bytes = response.read()
|
||
if not image_bytes:
|
||
raise ValueError("下载结果为空")
|
||
|
||
image_ext = _guess_image_ext(
|
||
image_url=url,
|
||
content_type=response.headers.get_content_type(),
|
||
)
|
||
merged_extra = dict(extra or {})
|
||
merged_extra.update(
|
||
{
|
||
"source": "remote-url",
|
||
"source_url": url,
|
||
"content_type": response.headers.get_content_type(),
|
||
}
|
||
)
|
||
|
||
record_prompt = (prompt or _default_prompt_from_url(url)).strip()
|
||
return save_image_to_cache(
|
||
prompt=record_prompt,
|
||
image_bytes=image_bytes,
|
||
image_ext=image_ext,
|
||
extra=merged_extra,
|
||
base_dir=base_dir,
|
||
)
|
||
|
||
|
||
def delete_record(record: AIImageRecord) -> bool:
|
||
"""删除一条缓存记录（图片 + 侧车）。返回是否成功。"""
|
||
ok = True
|
||
for p in (record.image_path, _meta_path_for(record.image_path)):
|
||
try:
|
||
if os.path.isfile(p):
|
||
os.remove(p)
|
||
except Exception:
|
||
ok = False
|
||
return ok
|
||
|
||
|
||
def export_record(record: AIImageRecord, dest_path: str) -> None:
|
||
"""把缓存中的图片另存到 ``dest_path``。"""
|
||
shutil.copyfile(record.image_path, dest_path)
|
||
|
||
|
||
def update_record_title(record: AIImageRecord, new_title: Optional[str]) -> bool:
|
||
"""更新记录的展示标题并写回侧车 JSON。空串/None 视为清除标题。"""
|
||
title = (new_title or "").strip() or None
|
||
meta_path = _meta_path_for(record.image_path)
|
||
try:
|
||
data: dict = {}
|
||
if os.path.isfile(meta_path):
|
||
with open(meta_path, "r", encoding="utf-8") as f:
|
||
data = json.load(f) or {}
|
||
if title is None:
|
||
data.pop("title", None)
|
||
else:
|
||
data["title"] = title
|
||
with open(meta_path, "w", encoding="utf-8") as f:
|
||
json.dump(data, f, ensure_ascii=False, indent=2)
|
||
except Exception:
|
||
return False
|
||
record.title = title
|
||
return True
|
||
|
||
|
||
def group_records_by_session(records: List[AIImageRecord]) -> List[dict]:
|
||
"""按 ``session_id`` 分组。
|
||
|
||
返回元素：``{"session_id", "records", "started_at", "latest_at"}``。
|
||
会话按"最近使用时间"倒序，组内记录按时间倒序。
|
||
没有 session_id 的记录归到空串 ``""`` 组。
|
||
"""
|
||
buckets: dict = {}
|
||
for rec in records:
|
||
buckets.setdefault(rec.session_id, []).append(rec)
|
||
sessions = []
|
||
for sid, recs in buckets.items():
|
||
recs.sort(key=lambda r: r.created_at, reverse=True)
|
||
started_at = min((r.created_at for r in recs if r.created_at), default="")
|
||
sessions.append(
|
||
{
|
||
"session_id": sid,
|
||
"records": recs,
|
||
"started_at": started_at,
|
||
"latest_at": recs[0].created_at if recs else "",
|
||
}
|
||
)
|
||
sessions.sort(key=lambda s: s["latest_at"], reverse=True)
|
||
return sessions
|
||
|
||
|
||
# ---------- 异步请求 ----------
|
||
|
||
|
||
def request_image_async(
|
||
prompt: str,
|
||
on_success: Callable[[AIImageRecord], None],
|
||
on_error: Callable[[Exception], None],
|
||
base_dir: Optional[str] = None,
|
||
session_id: Optional[str] = None,
|
||
cancel_event: Optional[threading.Event] = None,
|
||
upload_image_url: Optional[str] = None,
|
||
) -> threading.Thread:
|
||
"""在后台线程调用后端 API → 下载图片 → 写入缓存 → 回调。
|
||
|
||
``on_success`` / ``on_error`` 会在 **工作线程** 中被调用；UI 侧若需
|
||
切回主线程，请在回调内部自行用 ``root.after(0, ...)``。
|
||
|
||
``session_id`` 留空则使用进程级会话 id（保证多轮对话上下文）。
|
||
``upload_image_url`` 传入后启用"图生图"模式。
|
||
"""
|
||
|
||
sid = session_id or get_session_id()
|
||
cancel = cancel_event
|
||
ref_url = (upload_image_url or "").strip() or None
|
||
|
||
def _worker():
|
||
try:
|
||
if cancel is not None and cancel.is_set():
|
||
logger.info("[AIImage] 任务已取消（请求前） sid=%s", _mask_sid(sid))
|
||
return
|
||
image_url = _call_pqtest_generate(prompt, sid, upload_image_url=ref_url)
|
||
if cancel is not None and cancel.is_set():
|
||
logger.info("[AIImage] 任务已取消（生成后） sid=%s", _mask_sid(sid))
|
||
return
|
||
extra = {
|
||
"source": "ai-api",
|
||
"session_id": sid,
|
||
"mode": "img2img" if ref_url else "txt2img",
|
||
}
|
||
if ref_url:
|
||
extra["upload_image_url"] = ref_url
|
||
record = import_image_from_url(
|
||
image_url=image_url,
|
||
prompt=prompt,
|
||
extra=extra,
|
||
base_dir=base_dir,
|
||
)
|
||
if cancel is not None and cancel.is_set():
|
||
logger.info("[AIImage] 任务已取消（下载后） sid=%s", _mask_sid(sid))
|
||
return
|
||
logger.info(
|
||
"[AIImage] 已写入缓存 sid=%s id=%s path=%s",
|
||
_mask_sid(sid), record.id, record.image_path,
|
||
)
|
||
on_success(record)
|
||
except Exception as exc:
|
||
if cancel is not None and cancel.is_set():
|
||
logger.info("[AIImage] 任务已取消（异常忽略） sid=%s", _mask_sid(sid))
|
||
return
|
||
logger.error(
|
||
"[AIImage] 生成流程失败 sid=%s %s: %s",
|
||
_mask_sid(sid), type(exc).__name__, exc,
|
||
)
|
||
on_error(exc)
|
||
|
||
t = threading.Thread(target=_worker, daemon=True)
|
||
t.start()
|
||
return t
|
||
|
||
|
||
def import_image_from_url_async(
|
||
image_url: str,
|
||
on_success: Callable[[AIImageRecord], None],
|
||
on_error: Callable[[Exception], None],
|
||
prompt: Optional[str] = None,
|
||
extra: Optional[dict] = None,
|
||
base_dir: Optional[str] = None,
|
||
timeout: float = 20.0,
|
||
cancel_event: Optional[threading.Event] = None,
|
||
) -> threading.Thread:
|
||
"""在后台线程下载远程图片并写入缓存"""
|
||
|
||
def _worker():
|
||
try:
|
||
if cancel_event is not None and cancel_event.is_set():
|
||
logger.info("[AIImage] URL 导入任务已取消（请求前）")
|
||
return
|
||
record = import_image_from_url(
|
||
image_url=image_url,
|
||
prompt=prompt,
|
||
extra=extra,
|
||
base_dir=base_dir,
|
||
timeout=timeout,
|
||
)
|
||
if cancel_event is not None and cancel_event.is_set():
|
||
logger.info("[AIImage] URL 导入任务已取消（下载后）")
|
||
return
|
||
on_success(record)
|
||
except Exception as exc:
|
||
if cancel_event is not None and cancel_event.is_set():
|
||
logger.info("[AIImage] URL 导入任务已取消（异常忽略）")
|
||
return
|
||
on_error(exc)
|
||
|
||
t = threading.Thread(target=_worker, daemon=True)
|
||
t.start()
|
||
return t
|
||
|
||
|
||
def upload_image_async(
|
||
file_path: str,
|
||
on_success: Callable[[str], None],
|
||
on_error: Callable[[Exception], None],
|
||
cancel_event: Optional[threading.Event] = None,
|
||
timeout: float = API_UPLOAD_TIMEOUT,
|
||
auto_resize: bool = True,
|
||
) -> threading.Thread:
|
||
"""后台上传本地图片到后端，成功回调返回 ``upload_image_url``。
|
||
|
||
参数：
|
||
auto_resize: True 时自动缩放超大图片
|
||
"""
|
||
|
||
def _worker():
|
||
try:
|
||
if cancel_event is not None and cancel_event.is_set():
|
||
return
|
||
url = _call_pqtest_upload(file_path, timeout=timeout, auto_resize=auto_resize)
|
||
if cancel_event is not None and cancel_event.is_set():
|
||
return
|
||
on_success(url)
|
||
except Exception as exc:
|
||
if cancel_event is not None and cancel_event.is_set():
|
||
return
|
||
on_error(exc)
|
||
|
||
t = threading.Thread(target=_worker, daemon=True)
|
||
t.start()
|
||
return t
|
||
|
||
|
||
def is_remote_image_url(value: str) -> bool:
|
||
"""判断输入是否为 http/https 图片地址。"""
|
||
url = (value or "").strip()
|
||
if not url:
|
||
return False
|
||
parsed = urlparse(url)
|
||
return parsed.scheme in {"http", "https"} and bool(parsed.netloc)
|
||
|
||
|
||
def _guess_image_ext(image_url: str, content_type: Optional[str]) -> str:
|
||
if content_type:
|
||
guessed = mimetypes.guess_extension(content_type)
|
||
if guessed == ".jpe":
|
||
guessed = ".jpg"
|
||
if guessed and guessed.lower() in _SUPPORTED_IMG_EXT:
|
||
return guessed.lower()
|
||
|
||
url_path = urlparse(image_url).path
|
||
ext = os.path.splitext(url_path)[1].lower()
|
||
if ext in _SUPPORTED_IMG_EXT:
|
||
return ext
|
||
return ".png"
|
||
|
||
|
||
def _default_prompt_from_url(image_url: str) -> str:
|
||
path = urlparse(image_url).path
|
||
name = os.path.splitext(os.path.basename(path))[0].strip()
|
||
return name or "远程导入图片"
|