auto-save 2026-05-18 06:44 (~3)
This commit is contained in:
142
api/main.py
142
api/main.py
@@ -2540,6 +2540,42 @@ def start_audio_processing(job_id: str, manage_job_status: bool = True) -> bool:
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return True
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def _image_is_capacity_error(status_code: int, body: str) -> bool:
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lower = body.lower()
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return (
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status_code == 429
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or (
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status_code in (500, 502, 503, 504)
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and any(token in lower for token in ("saturated", "rate", "quota", "capacity", "overload", "timeout", "繁忙", "饱和", "过载"))
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)
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)
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def _image_retry_delay(attempt: int, status_code: int = 0, body: str = "", retry_after: str | None = None) -> float:
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if retry_after:
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try:
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return max(1.0, min(60.0, float(retry_after)))
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except ValueError:
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pass
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if _image_is_capacity_error(status_code, body):
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return [6.0, 14.0, 30.0, 45.0][min(attempt, 3)]
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return [1.0, 2.0, 4.0, 8.0][min(attempt, 3)]
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def _image_failure_message(kind: str, attempts: int, last_err: str, capacity_seen: bool) -> str:
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if capacity_seen:
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return (
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f"{kind} failed after {attempts} attempts: gpt-image-2 上游负载饱和，"
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f"已自动退避重试仍失败，请稍后点重试。最后错误：{last_err}"
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)
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return f"{kind} failed after {attempts} attempts: {last_err}"
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def _image_error_status(error: Exception) -> int:
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msg = str(error)
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return 503 if ("上游负载饱和" in msg or "HTTP 429" in msg or "saturated" in msg.lower()) else 500
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def _image_edit_call(
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image_path: Path,
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prompt: str,
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@@ -2574,9 +2610,6 @@ def _image_edit_call(
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except Exception:
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# PIL 失败兜底走原文件
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img_bytes_in = image_path.read_bytes()
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img_b64 = b64lib.b64encode(img_bytes_in).decode("ascii")
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data_uri = f"data:image/jpeg;base64,{img_b64}"
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plan: list[str] = ["edit"] * max_attempts
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if fallback_text:
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plan.append("text")
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@@ -2584,18 +2617,22 @@ def _image_edit_call(
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last_err = ""
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resp_data: dict = {}
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effective_mode = "edit"
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capacity_seen = False
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for attempt, current_mode in enumerate(plan):
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current_model = models_cycle[min(attempt, len(models_cycle) - 1)]
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status_code = 0
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body = ""
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retry_after: str | None = None
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try:
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if current_mode == "edit":
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with httpx.Client(timeout=120) as client:
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r = client.post(
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f"{IMAGE_BASE_URL}/images/generations",
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f"{IMAGE_BASE_URL}/images/edits",
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headers={
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"Authorization": f"Bearer {IMAGE_API_KEY}",
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"Content-Type": "application/json",
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},
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json={"model": current_model, "prompt": prompt, "image": data_uri, "n": 1},
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data={"model": current_model, "prompt": prompt, "n": "1"},
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files={"image": ("reference.jpg", img_bytes_in, "image/jpeg")},
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)
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r.raise_for_status()
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resp_data = r.json()
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@@ -2610,23 +2647,32 @@ def _image_edit_call(
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last_err = f"empty data · {err_obj.get('code', '')} · {str(err_obj.get('message', ''))[:200]} · model={current_model}"
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except httpx.HTTPStatusError as e:
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body = e.response.text
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sc = e.response.status_code
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fatal = sc in (401, 403)
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last_err = f"HTTP {sc}: {body[:200]} · model={current_model}"
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status_code = e.response.status_code
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retry_after = e.response.headers.get("retry-after")
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capacity_seen = capacity_seen or _image_is_capacity_error(status_code, body)
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fatal = status_code in (401, 403)
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last_err = f"HTTP {status_code}: {body[:200]} · model={current_model}"
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if fatal:
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raise RuntimeError(f"image edit HTTP {sc}: {body[:300]}")
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raise RuntimeError(f"image edit HTTP {status_code}: {body[:300]}")
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except Exception as e:
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last_err = f"{type(e).__name__}: {e} · model={current_model}"
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if attempt < len(plan) - 1:
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tag = f"retry {attempt + 1}/{len(plan)} → {GPT_IMAGE_MODEL}"
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print(f"[image edit {tag}] {last_err}", flush=True)
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_time.sleep(1.0)
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delay = _image_retry_delay(attempt, status_code, body, retry_after)
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print(f"[image edit {tag}, sleep {delay:.0f}s] {last_err}", flush=True)
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_time.sleep(delay)
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data_arr = resp_data.get("data", [])
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if not data_arr:
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raise RuntimeError(f"image edit failed after {len(plan)} attempts: {last_err}")
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b64 = data_arr[0].get("b64_json")
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raise RuntimeError(_image_failure_message("image edit", len(plan), last_err, capacity_seen))
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item = data_arr[0]
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b64 = item.get("b64_json")
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if not b64 and item.get("url"):
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with httpx.Client(timeout=120) as client:
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image_resp = client.get(item["url"])
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image_resp.raise_for_status()
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return image_resp.content, effective_mode
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if not b64:
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raise RuntimeError("image edit returned no b64_json")
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return b64lib.b64decode(b64), effective_mode
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@@ -2646,8 +2692,11 @@ def _image_text_call(
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models_cycle = [GPT_IMAGE_MODEL]
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last_err = ""
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resp_data: dict = {}
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capacity_seen = False
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for attempt in range(max_attempts):
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current_model = models_cycle[min(attempt, len(models_cycle) - 1)]
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status_code = 0
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body = ""
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try:
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resp = image_llm().images.generate(model=current_model, prompt=prompt, n=1)
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resp_data = resp.model_dump() if hasattr(resp, "model_dump") else {"data": [{"b64_json": resp.data[0].b64_json}]}
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@@ -2659,10 +2708,14 @@ def _image_text_call(
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last_err = f"empty data · {err_obj.get('code', '')} · {str(err_obj.get('message', ''))[:200]} · model={current_model}"
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except Exception as e:
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last_err = f"{type(e).__name__}: {e} · model={current_model}"
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body = str(e)
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status_code = 429 if "429" in body or "saturated" in body.lower() or "饱和" in body else 0
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capacity_seen = capacity_seen or _image_is_capacity_error(status_code, body)
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if attempt < max_attempts - 1:
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print(f"[image text retry {attempt + 1}/{max_attempts} → {GPT_IMAGE_MODEL}] {last_err}", flush=True)
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_time.sleep(1.0)
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raise RuntimeError(f"image text failed after {max_attempts} attempts: {last_err}")
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delay = _image_retry_delay(attempt, status_code, body)
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print(f"[image text retry {attempt + 1}/{max_attempts} → {GPT_IMAGE_MODEL}, sleep {delay:.0f}s] {last_err}", flush=True)
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_time.sleep(delay)
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raise RuntimeError(_image_failure_message("image text", max_attempts, last_err, capacity_seen))
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# ---------- API 路由 ----------
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@@ -3166,9 +3219,9 @@ def generate_image(job_id: str, idx: int, req: GenerateReq) -> Job:
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import time as _time
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import httpx
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img_b64: str | None = None
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img_bytes_in: bytes | None = None
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if req.mode == "edit":
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img_b64 = b64lib.b64encode(reference_path.read_bytes()).decode("ascii")
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img_bytes_in = reference_path.read_bytes()
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# 尝试 i2i 最多 3 次，全失败时降级 text-only 再试 1 次
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plan: list[str] = ([req.mode] * 3) if req.mode == "edit" else [req.mode]
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@@ -3177,24 +3230,23 @@ def generate_image(job_id: str, idx: int, req: GenerateReq) -> Job:
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resp_data: dict = {}
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last_err = ""
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effective_mode = req.mode
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capacity_seen = False
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for attempt, current_mode in enumerate(plan):
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status_code = 0
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body = ""
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retry_after: str | None = None
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try:
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if current_mode == "edit":
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data_uri = f"data:image/jpeg;base64,{img_b64}"
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# OpenAI SDK 不直接支持 image 参数，用底层 httpx
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if img_bytes_in is None:
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raise RuntimeError("edit mode reference image missing")
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with httpx.Client(timeout=120) as client:
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r = client.post(
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f"{IMAGE_BASE_URL}/images/generations",
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f"{IMAGE_BASE_URL}/images/edits",
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headers={
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"Authorization": f"Bearer {IMAGE_API_KEY}",
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"Content-Type": "application/json",
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},
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json={
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"model": model,
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"prompt": full_prompt,
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"image": data_uri,
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"n": 1,
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},
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data={"model": model, "prompt": full_prompt, "n": "1"},
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files={"image": ("reference.jpg", img_bytes_in, "image/jpeg")},
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)
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r.raise_for_status()
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resp_data = r.json()
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@@ -3210,15 +3262,20 @@ def generate_image(job_id: str, idx: int, req: GenerateReq) -> Job:
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last_err = f"empty data · {err_obj.get('code', '')} · {str(err_obj.get('message', ''))[:200]}"
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except httpx.HTTPStatusError as e:
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body = e.response.text
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status_code = e.response.status_code
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retry_after = e.response.headers.get("retry-after")
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capacity_seen = capacity_seen or _image_is_capacity_error(status_code, body)
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transient = (
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e.response.status_code >= 500
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status_code == 429
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or status_code >= 500
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or "incomplete_generation" in body
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or "rate_limit" in body
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or "timeout" in body.lower()
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or _image_is_capacity_error(status_code, body)
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)
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last_err = f"HTTP {e.response.status_code}: {body[:200]}"
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last_err = f"HTTP {status_code}: {body[:200]}"
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if not transient:
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raise HTTPException(500, f"image gen HTTP {e.response.status_code}: {body[:300]}")
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raise HTTPException(500, f"image gen HTTP {status_code}: {body[:300]}")
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except Exception as e:
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last_err = f"{type(e).__name__}: {e}"
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@@ -3226,22 +3283,29 @@ def generate_image(job_id: str, idx: int, req: GenerateReq) -> Job:
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next_mode = plan[attempt + 1]
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tag = f"fallback → {next_mode}" if next_mode != current_mode else f"retry {attempt + 1}/{len(plan)}"
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print(f"[image gen {tag}] {last_err}", flush=True)
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_time.sleep(1.5 * (attempt + 1))
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_time.sleep(_image_retry_delay(attempt, status_code, body, retry_after))
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data_arr = resp_data.get("data", [])
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if not data_arr:
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raise HTTPException(500, f"image gen failed after {len(plan)} attempts: {last_err}")
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raise HTTPException(503 if capacity_seen else 500, _image_failure_message("image gen", len(plan), last_err, capacity_seen))
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item = data_arr[0]
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b64 = item.get("b64_json")
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if not b64:
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if b64:
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out_bytes = b64lib.b64decode(b64)
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elif item.get("url"):
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with httpx.Client(timeout=120) as client:
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image_resp = client.get(item["url"])
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image_resp.raise_for_status()
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out_bytes = image_resp.content
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else:
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raise HTTPException(500, "image gen returned no b64_json")
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# 保存到本地 jobs/<id>/gen/<idx>_<gen_id>.jpg
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gen_dir = job_dir(job_id) / "gen"
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gen_dir.mkdir(parents=True, exist_ok=True)
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out_path = gen_dir / f"{idx:03d}_{gen_id}.jpg"
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out_path.write_bytes(b64lib.b64decode(b64))
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out_path.write_bytes(out_bytes)
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new_gen = GeneratedImage(
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id=gen_id,
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@@ -4073,7 +4137,7 @@ def generate_subject_assets(job_id: str, idx: int, element_id: str, req: Generat
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try:
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img_bytes, _mode = _image_edit_call(model_src, prompt, models=models, fallback_text=False, max_attempts=3, max_side=1280)
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except RuntimeError as e:
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raise HTTPException(500, f"subject asset {view} failed: {e}")
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raise HTTPException(_image_error_status(e), f"subject asset {view} failed: {e}")
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asset_id = f"subject_{idx:03d}_{element_id}_{view}_{uuid.uuid4().hex[:8]}"
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out_path = job_dir(job_id) / "assets" / f"{asset_id}.jpg"
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@@ -5073,9 +5137,9 @@ def generate_product_angle_asset(job_id: str, req: GenerateProductAngleAssetReq)
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)
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models = [GPT_IMAGE_MODEL]
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try:
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img_bytes, _mode = _image_edit_call(source_path, prompt, models=models, fallback_text=False, max_attempts=3, max_side=1280)
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img_bytes, _mode = _image_edit_call(source_path, prompt, models=models, fallback_text=False, max_attempts=5, max_side=1280)
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except RuntimeError as e:
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raise HTTPException(500, f"product angle generation failed: {e}")
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raise HTTPException(_image_error_status(e), f"product angle generation failed: {e}")
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asset_id = f"product_angle_{uuid.uuid4().hex[:10]}"
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out_path = job_dir(job_id) / "assets" / f"{asset_id}.jpg"
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_normalize_asset_image(img_bytes, out_path, source_path, "1024", "white", square=True, fill_subject=True)
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