"""OpenAI 图像后端（生成设计稿 + 三图合成）。 支持 OpenAI images/generations（文生图）与 images/edits（img2img 多参考图）， 兼容两类网关返回： 1) 同步：{"data": [{"b64_json" | "url"}]} 2) 异步任务（ai-media.vip 等重负载自动转异步）： 提交返回 202 + {"object":"image.task","task_id","poll_url","poll_after_ms"}， 需轮询 GET {base}/images/tasks/{task_id} 直到 succeeded，再从成功响应取图。 所有请求跳过环境代理（NO_PROXY），适配用户挂 VPN 时直连国内/自建网关。 """ import base64 import json import time from pathlib import Path from typing import Optional import requests import os # 模型调用一律直连：用户常开 VPN（系统代理），网关多为国内/自建，走代理会被拦截或变慢。 # 环境变量级 NO_PROXY 双保险（requests/urllib3 均读取），Google 采集（pytrends）不受影响。 os.environ.setdefault('NO_PROXY', '*') os.environ.setdefault('no_proxy', '*') from .base import ImageBackend # 直连策略：忽略环境代理（用户挂 VPN 时代理会拦截国内/自建网关的请求） NO_PROXY = {"http": None, "https": None} _FINAL_STATUS = ("succeeded", "completed", "done") _FAIL_STATUS = ("failed", "error") def _retry_after(resp, attempt: int) -> int: """429 限流等待秒数：优先取网关 Retry-After 头，否则指数退避（3/6/9s）。""" ra = resp.headers.get("Retry-After") try: if ra is not None and ra.isdigit(): return min(int(ra), 30) except Exception: # noqa: BLE001 pass return 3 * (attempt + 1) def _shrink_blob_to_2mb(img_path: str, blob: bytes, max_bytes: int = 2 * 1024 * 1024) -> bytes: """把大图压缩到 max_w or img.height > max_h: img.thumbnail((max_w, max_h)) has_alpha = img.mode in ("RGBA", "LA") if not has_alpha: img = img.convert("RGB") for q in (88, 70, 50, 35): buf = io.BytesIO() if has_alpha: img.save(buf, format="PNG", optimize=True) else: img.save(buf, format="JPEG", quality=q) if buf.tell() <= max_bytes: return buf.getvalue() # 保底：最小质量 PNG/JPEG buf = io.BytesIO() if has_alpha: img.save(buf, format="PNG", optimize=True) else: img.save(buf, format="JPEG", quality=30) return buf.getvalue() except Exception as e: # noqa: BLE001 print(f"[img] 图片压缩失败（用原图）: {e}") return blob def _save_from_response(j: dict, out_path: str) -> str: """从同步/异步最终响应提取图片（data[].b64_json 或 url）并保存。""" data_item = (j.get("data") or [{}])[0] b64 = data_item.get("b64_json") if b64: Path(out_path).parent.mkdir(parents=True, exist_ok=True) Path(out_path).write_bytes(base64.b64decode(b64)) return out_path url = data_item.get("url") if not url: raise RuntimeError(f"图像 API 返回无 b64_json/url: {str(j)[:200]}") img_resp = requests.get(url, proxies=NO_PROXY, timeout=120) img_resp.raise_for_status() Path(out_path).parent.mkdir(parents=True, exist_ok=True) Path(out_path).write_bytes(img_resp.content) return out_path def _wait_task(base_url: str, headers: dict, task_id: str, poll_after_ms: int, timeout: int = 60) -> dict: """轮询异步图像任务直到完成；uncertain（结果暂时不确定）继续等，不重复提交。 timeout 默认 60s：异步路径不稳定（ai-media 网关常 uncertain/task not found）， 超时即抛异常由调用方重试同步提交。""" deadline = time.time() + timeout last = "" while time.time() < deadline: time.sleep(max(int(poll_after_ms or 2000), 2000) / 1000.0) try: resp = requests.get(f"{base_url}/images/tasks/{task_id}", headers=headers, timeout=60, proxies=NO_PROXY) if resp.status_code >= 400: continue j = resp.json() except Exception as e: # noqa: BLE001 print(f"[img] 任务轮询异常（重试）: {e}") continue st = j.get("status") if st != last: print(f"[img] 异步任务 {task_id[:20]}… status={st}") last = st if st in _FINAL_STATUS: return j if st in _FAIL_STATUS: raise RuntimeError(f"图像异步任务失败: {j.get('error')} {j.get('error_code')}") # queued / running / uncertain → 继续等 raise RuntimeError(f"图像异步任务超时（{timeout}s）") def _resolve_task_or_sync(j: dict, base_url: str, headers: dict, out_path: str) -> str: """提交后的统一处理：异步任务则轮询，然后提取图片保存。""" if j.get("object") == "image.task" or j.get("task_id") or j.get("id", "").startswith("imgtask"): tid = j.get("task_id") or j.get("id") or "" if not tid: raise RuntimeError(f"异步任务无 task_id: {str(j)[:200]}") j = _wait_task(base_url, headers, tid, int(j.get("poll_after_ms") or 2000)) return _save_from_response(j, out_path) class OpenAIImageBackend(ImageBackend): name = "openai" def __init__(self): self._cfg: dict = {} def bind_config(self, cfg: dict): self._cfg = cfg or {} def _base_url(self) -> str: return str(self._cfg.get("base_url") or "https://api.openai.com/v1").rstrip("/") def print(self, prompt: str, base_image: str, out_path: str, negative: str = "", extra_images=None, size: str = "", seed: Optional[int] = None) -> str: """img2img 编辑：参考图 base_image（+ 可选 extra_images 多参考图）按 prompt 生成新图。 - 平铺服装图：base_image=平铺衣服底图(图3)，extra_images=[印花设计稿(图2)] - 三图模特合成：base_image=模特图(图1)，extra_images=[印花设计稿(图2), 平铺底图(图3)] 提交顺序即图1→图2→图3，与提示词中的图片角色一一对应。 size: 显式尺寸覆盖（如 "1536x2048"）；留空用配置 size（默认 1024x1024）。 seed: 随机种子（None=不传，网关随机；固定值=可复现，网关支持才生效）。 """ cfg = self._cfg api_key = cfg.get("api_key", "") model = cfg.get("model", "gpt-image-1") if not api_key: raise RuntimeError("compose.api_key 未配置，无法调用 OpenAI 图像后端。") full_prompt = prompt + (f"\nNegative: {negative}" if negative else "") base_url = self._base_url() headers = {"Authorization": f"Bearer {api_key}"} # 必须把文件读成 bytes 再提交（句柄随 with 关闭会导致 "read of closed file"）； # 输入图（模特/设计/底图）先压缩校验：>2MB 压缩到 <2MB 再上传，避免大图拖垮网关导致超时 file_payloads = [] for img_path in [base_image] + list(extra_images or []): blob = Path(img_path).read_bytes() if len(blob) > 2 * 1024 * 1024: shrunk = _shrink_blob_to_2mb(img_path, blob) print(f"[img] 输入图压缩: {Path(img_path).name} {len(blob)//1024}KB → {len(shrunk)//1024}KB（<2MB）") blob = shrunk file_payloads.append((Path(img_path).name, blob)) files = [("image", (name, blob, "image/png")) for name, blob in file_payloads] data = { "prompt": full_prompt, "n": 1, "size": size or cfg.get("size", "1024x1024"), "model": model, } # execution_mode 仅对明确支持的网关（如 ai-media）传；yunfei 等标准 OpenAI 网关 # 不认识该参数，硬传会导致空响应，故默认不传，仅 config 显式配置时才带上 em = str(cfg.get("execution_mode") or "").strip() if em: data["execution_mode"] = em if seed is not None: data["seed"] = seed # 提交重试：异步路径不稳定 → 失败重试同步提交（最多 3 次）； # 内容政策拦截（content_policy_violation）多为网关误判 → 等待后重试 last_err: Optional[str] = None for attempt in range(3): resp = requests.post(f"{base_url}/images/edits", headers=headers, files=files, data=data, timeout=300, proxies=NO_PROXY) if resp.status_code == 429: # 限流：尊重网关负载退避等待再重试，避免硬撞雪崩 wait = _retry_after(resp, attempt) print(f"[img] 图像 API 429 限流，等待 {wait}s 重试 {attempt + 1}/3") time.sleep(wait) continue if resp.status_code >= 500: # 5xx 服务端错误（500/502/503/504 超时等）：网关临时故障/过载，退避后重试 body = resp.text or "" last_err = f"图像 API {resp.status_code}: {body[:300]}" wait = 3 * (attempt + 1) print(f"[img] 图像 API {resp.status_code}（网关临时故障/超时），等待 {wait}s 重试 {attempt + 1}/3") time.sleep(wait) continue if resp.status_code >= 400: body = resp.text or "" if "content_policy" in body and attempt < 2: print(f"[img] 内容政策拦截（可能误判），等待后重试 {attempt + 2}/3") time.sleep(2) continue if attempt == 0: data.pop("execution_mode", None) # 网关不认识该参数（官方 OpenAI）→ 去掉重试 continue raise RuntimeError(f"图像 API {resp.status_code}: {body[:300]}") try: return _resolve_task_or_sync(resp.json(), base_url, headers, out_path) except json.JSONDecodeError as e: # 空/非 JSON 响应：多为网关过载返回空 body → 退避后重试， # 避免即时重压触发网关 429（用户实测空响应风暴 → 429） last_err = str(e) wait = 3 * (attempt + 1) print(f"[img] 网关空响应（JSON 解析失败），等待 {wait}s 重试提交 {attempt + 1}/3: {e}") time.sleep(wait) except Exception as e: # noqa: BLE001 last_err = str(e) print(f"[img] 第 {attempt + 1} 次提交异步失败，等待后重试同步提交: {e}") time.sleep(2 * (attempt + 1)) raise RuntimeError(f"图像合成多次提交均失败: {last_err}") def generate(self, prompt: str, out_path: str, negative: str = "", size: str = "", seed: Optional[int] = None) -> str: """纯文生图：生成白底纯印花设计稿（standalone pure print design）。 size: 显式尺寸覆盖（印花设计统一 1024x1024）；留空用配置 size。 seed: 随机种子（None=不传，网关随机；固定值=可复现，网关支持才生效）。""" cfg = self._cfg api_key = cfg.get("api_key", "") model = cfg.get("model", "gpt-image-1") if not api_key: raise RuntimeError("compose.api_key 未配置，无法调用 OpenAI 图像后端。") full_prompt = prompt + (f"\nNegative: {negative}" if negative else "") base_url = self._base_url() headers = {"Authorization": f"Bearer {api_key}"} data = { "prompt": full_prompt, "n": 1, "size": size or cfg.get("size", "1024x1024"), "model": model, "response_format": "b64_json", } # execution_mode 仅对明确支持的网关（如 ai-media）传；yunfei 等标准 OpenAI 网关 # 不认识该参数，硬传会导致空响应，故默认不传，仅 config 显式配置时才带上 em = str(cfg.get("execution_mode") or "").strip() if em: data["execution_mode"] = em if seed is not None: data["seed"] = seed last_err: Optional[str] = None for attempt in range(3): resp = requests.post(f"{base_url}/images/generations", headers=headers, json=data, timeout=300, proxies=NO_PROXY) if resp.status_code == 429: # 限流：尊重网关负载退避等待再重试，避免硬撞雪崩 wait = _retry_after(resp, attempt) print(f"[img] 图像 API 429 限流，等待 {wait}s 重试 {attempt + 1}/3") time.sleep(wait) continue if resp.status_code >= 500: # 5xx 服务端错误（500/502/503/504 超时等）：网关临时故障/过载，退避后重试 body = resp.text or "" last_err = f"图像 API {resp.status_code}: {body[:300]}" wait = 3 * (attempt + 1) print(f"[img] 图像 API {resp.status_code}（网关临时故障/超时），等待 {wait}s 重试 {attempt + 1}/3") time.sleep(wait) continue if resp.status_code >= 400: body = resp.text or "" if "content_policy" in body and attempt < 2: print(f"[img] 内容政策拦截（可能误判），等待后重试 {attempt + 2}/3") time.sleep(2) continue if attempt == 0: data.pop("execution_mode", None) # 网关不认识该参数（官方 OpenAI）→ 去掉重试 continue raise RuntimeError(f"图像 API {resp.status_code}: {body[:300]}") try: return _resolve_task_or_sync(resp.json(), base_url, headers, out_path) except json.JSONDecodeError as e: # 空/非 JSON 响应：多为网关过载返回空 body → 退避后重试， # 避免即时重压触发网关 429（用户实测空响应风暴 → 429） last_err = str(e) wait = 3 * (attempt + 1) print(f"[img] 网关空响应（JSON 解析失败），等待 {wait}s 重试生成 {attempt + 1}/3: {e}") time.sleep(wait) except Exception as e: # noqa: BLE001 last_err = str(e) print(f"[img] 第 {attempt + 1} 次生成异步失败，等待后重试同步提交: {e}") time.sleep(2 * (attempt + 1)) raise RuntimeError(f"图像生成多次提交均失败: {last_err}")