Плагин GPT Image 2 для Coze

from runtime import Args
from typings.gptimage2.gptimage2 import Input, Output
import requests
import base64
import io
import oss2
import uuid
import re


# ╔══════════════════════════════════════════════════════════╗
# ║           API易 线路配置（按需切换）                      ║
# ╚══════════════════════════════════════════════════════════╝
API_BASE = "https://api.apiyi.com/v1"
# 也可切换为: "https://b.apiyi.com/v1"

# ╔══════════════════════════════════════════════════════════╗
# ║              阿里云 OSS 配置（请修改为你的值）            ║
# ╚══════════════════════════════════════════════════════════╝
ACCESS_KEY_ID = ""          # 填入你的阿里云 Access Key ID
ACCESS_KEY_SECRET = ""      # 填入你的阿里云 Access Key Secret
BUCKET_NAME = ""            # 填入你的阿里云 OSS Bucket 名称
ENDPOINT = "oss-cn-beijing.aliyuncs.com"  # 填入你的 OSS Endpoint

# ╔══════════════════════════════════════════════════════════╗
# ║       质量超时配置（GPT Image 2 基于 quality 分级）       ║
# ╚══════════════════════════════════════════════════════════╝
TIMEOUT = {
    "low": 180,     # 低质量快速出图（3-8 秒实际耗时）
    "medium": 360,  # 中等质量（20-40 秒实际耗时，推荐）
    "high": 900,    # 高质量精细渲染（145-280 秒实际耗时）
}

# ╔══════════════════════════════════════════════════════════╗
# ║     分辨率 → 尺寸映射表（宽高比 × 分辨率 → W×H）          ║
# ╚══════════════════════════════════════════════════════════╝
RESOLUTION_SIZES = {
    "1:1":  {"1K": "1024x1024", "2K": "2048x2048", "4K": "3840x2160"},
    "16:9": {"1K": "1536x1024", "2K": "2048x1152", "4K": "3840x2160"},
    "9:16": {"1K": "1024x1536", "2K": "1152x2048", "4K": "2160x3840"},
    "4:3":  {"1K": "1024x768",  "2K": "2048x1536", "4K": "3264x2448"},
    "3:2":  {"1K": "1536x1024", "2K": "2048x1360", "4K": "3456x2304"},
    "3:1":  {"1K": "1536x512",  "2K": "3072x1024", "4K": "3840x1280"},
    "1:3":  {"1K": "512x1536",  "2K": "1024x3072", "4K": "1280x3840"},
}


# ==============================
# OSS 上传工具
# ==============================

def upload_base64_to_oss(image_base64: str) -> str:
    """
    将 base64 图片上传到阿里云 OSS 并返回公网 URL
    支持带 data:image/...;base64, 前缀和纯 base64 两种情况
    """
    base64_str = re.sub(r"^data:image/[^;]+;base64,", "", image_base64)
    image_data = base64.b64decode(base64_str)
    image_io = io.BytesIO(image_data)

    auth = oss2.Auth(ACCESS_KEY_ID, ACCESS_KEY_SECRET)
    bucket = oss2.Bucket(auth, ENDPOINT, BUCKET_NAME)
    object_name = f"coze/gptimage2_{uuid.uuid4().hex}.png"
    bucket.put_object(object_name, image_io)

    return f"https://{BUCKET_NAME}.{ENDPOINT}/{object_name}"


# ==============================
# 工具函数
# ==============================

def get_size(aspect_ratio: str, resolution: str) -> str:
    """根据宽高比和分辨率获取推荐尺寸"""
    ratio_map = RESOLUTION_SIZES.get(aspect_ratio, RESOLUTION_SIZES["1:1"])
    return ratio_map.get(resolution, ratio_map.get("1K", "1024x1024"))


def guess_mime_from_url(url: str) -> str:
    """根据 URL 后缀猜测 MIME 类型"""
    url_lower = url.lower()
    if url_lower.endswith(".png"):
        return "image/png"
    if url_lower.endswith(".jpg") or url_lower.endswith(".jpeg"):
        return "image/jpeg"
    if url_lower.endswith(".webp"):
        return "image/webp"
    if url_lower.endswith(".gif"):
        return "image/gif"
    return "image/png"


# ==============================
# 核心：GPT Image 2 生图 / 编辑
# ==============================

def generate_image(prompt: str, aspect_ratio: str, resolution: str,
                   quality: str, apikey: str, output_format: str = "png",
                   moderation: str = "auto", image_urls=None):
    """
    GPT Image 2 文生图 / 图生图核心函数

    - image_urls 为空：纯文生图 → API易 /v1/images/generations（JSON）
    - image_urls 不为空：参考图编辑 → API易 /v1/images/edits（multipart/form-data）
    """

    size = get_size(aspect_ratio, resolution)
    headers = {
        "Authorization": f"Bearer {apikey}",
        "Content-Type": "application/json"
    }

    # ── 分支 1：有参考图 → 图生图（编辑） ──
    if image_urls:
        return _generate_edit(prompt, size, quality, apikey,
                              output_format, moderation, image_urls, headers)

    # ── 分支 2：无参考图 → 文生图（/v1/images/generations，JSON）──
    payload = {
        "model": "gpt-image-2",
        "prompt": prompt,
        "size": size,
    }
    if quality and quality != "auto":
        payload["quality"] = quality
    if output_format and output_format != "png":
        payload["output_format"] = output_format
    if moderation and moderation != "auto":
        payload["moderation"] = moderation

    timeout_seconds = TIMEOUT.get(quality, 360)
    api_url = f"{API_BASE}/images/generations"

    try:
        response = requests.post(
            api_url,
            headers=headers,
            json=payload,
            timeout=timeout_seconds
        )

        # ── HTTP 错误分发 ──
        if response.status_code in (400, 403):
            try:
                err_body = response.json()
                err = err_body.get("error", {})
                err_msg = err.get("message", "")
            except Exception:
                err_msg = response.text

            if "moderation" in err_msg.lower() or response.status_code == 403:
                return {
                    "success": False,
                    "errorType": "MODERATION_BLOCKED",
                    "error": "❌ 内容安全审核不通过\n"
                             "您的提示词触发了内容安全策略，"
                             "请修改提示词后重试（不要用原提示词重试）",
                }
            return {
                "success": False,
                "errorType": "BAD_REQUEST",
                "error": f"❌ 请求参数错误: {err_msg[:500]}\n"
                         "常见原因：误传了 input_fidelity，或 background:transparent 配了 output_format:jpeg",
            }

        if response.status_code == 401:
            return {
                "success": False,
                "errorType": "INVALID_API_KEY",
                "error": "❌ API Key 无效\n请检查您的 API易 API 密钥是否正确，"
                        "或是否已过期。可在 https://api.apiyi.com/token 查看",
            }

        if response.status_code == 429:
            return {
                "success": False,
                "errorType": "RATE_LIMIT",
                "error": "❌ 请求频率超限\nAPI 调用过于频繁，"
                        "可尝试切换线路或降低并发",
            }

        if response.status_code in (500, 502, 503):
            return {
                "success": False,
                "errorType": "SERVER_ERROR",
                "error": f"❌ 服务端故障（HTTP {response.status_code}），"
                        "请稍后重试或尝试切换线路",
            }

        if response.status_code != 200:
            return {
                "success": False,
                "errorType": "HTTP_ERROR",
                "error": f"HTTP {response.status_code}: "
                        f"{(response.text or '')[:500]}",
            }

        # ── JSON 解析 ──
        try:
            data = response.json()
        except ValueError:
            return {
                "success": False,
                "errorType": "INVALID_JSON",
                "error": "响应不是有效 JSON",
            }

        images = data.get("data", [])
        if not isinstance(images, list) or len(images) == 0:
            return {
                "success": False,
                "errorType": "NO_DATA",
                "error": "生成失败：未返回图片数据（可能触发了 output filter）",
                "response": data,
            }

        # ── 提取 b64_json（API易 返回纯 base64，无 data:image 前缀）──
        image_b64 = images[0].get("b64_json", "")
        if not image_b64:
            return {
                "success": False,
                "errorType": "NO_IMAGE_DATA",
                "error": "生成失败：b64_json 为空（可能被 content_filter 过滤）",
                "response": data,
            }

        return {"success": True, "image_data": image_b64}

    except requests.exceptions.Timeout:
        return {
            "success": False,
            "errorType": "TIMEOUT",
            "error": f"图片生成请求超时"
                     f"（超过 {timeout_seconds} 秒，"
                     f"当前 quality={quality}）\n"
                     f"建议降低 quality 或 resolution 重试",
        }
    except Exception as e:
        return {
            "success": False,
            "errorType": "EXCEPTION",
            "error": f"图片生成请求失败: {str(e)}",
        }


def _generate_edit(prompt: str, size: str, quality: str,
                   apikey: str, output_format: str, moderation: str,
                   image_urls: list, headers: dict):
    """
    GPT Image 2 图生图（编辑）子函数
    调用 API易 /v1/images/edits 端点（multipart/form-data 方式上传参考图）

    注意：API易 的 /v1/images/edits 要求 Content-Type: multipart/form-data，
    通过 -F "image[]=@file" 方式传图，不支持 JSON base64 data URI。
    参考图数量最多 16 张，单张 ≤ 50MB（建议压到 1.5MB 以内）。
    """

    # ── 下载参考图到内存 ──
    image_files = []
    for i, url in enumerate(image_urls):
        try:
            resp = requests.get(url, timeout=180)
            if resp.status_code != 200:
                return {
                    "success": False,
                    "errorType": "IMAGE_DOWNLOAD_FAILED",
                    "error": f"图片获取失败（{url}）HTTP {resp.status_code}",
                }
            mime = guess_mime_from_url(url)
            ext = mime.split("/")[-1]  # png / jpeg / webp
            if ext == "jpeg":
                ext = "jpg"
            image_files.append(
                ("image[]", (f"image{i}.{ext}", io.BytesIO(resp.content), mime))
            )
        except Exception as e:
            return {
                "success": False,
                "errorType": "IMAGE_DOWNLOAD_FAILED",
                "error": f"图片获取失败（{url}）: {e}",
            }

    # ── 构造 multipart/form-data 请求（-F 方式）──
    form_data = {
        "model": "gpt-image-2",
        "prompt": prompt,
    }
    if size:
        form_data["size"] = size
    if quality and quality != "auto":
        form_data["quality"] = quality
    if output_format and output_format != "png":
        form_data["output_format"] = output_format
    if moderation and moderation != "auto":
        form_data["moderation"] = moderation

    # multipart/form-data 不传 Content-Type（让 requests 自动生成 boundary）
    auth_headers = {
        "Authorization": headers["Authorization"],
    }

    timeout_seconds = TIMEOUT.get(quality, 360)
    api_url = f"{API_BASE}/images/edits"

    try:
        response = requests.post(
            api_url,
            headers=auth_headers,
            data=form_data,
            files=image_files,
            timeout=timeout_seconds
        )

        # ── 错误处理 ──
        if response.status_code in (400, 403):
            try:
                err = response.json().get("error", {})
                err_msg = err.get("message", "")
            except Exception:
                err_msg = response.text[:500]
            if "moderation" in err_msg.lower() or response.status_code == 403:
                return {
                    "success": False,
                    "errorType": "MODERATION_BLOCKED",
                    "error": "❌ 内容安全审核不通过",
                }
            return {
                "success": False,
                "errorType": "EDIT_FAILED",
                "error": f"图片编辑请求参数错误: {err_msg[:500]}\n"
                         "常见原因：误传了 input_fidelity、"
                         "超过 16 张参考图或单张超过 50MB",
            }

        if response.status_code == 401:
            return {
                "success": False,
                "errorType": "INVALID_API_KEY",
                "error": "❌ API Key 无效",
            }

        if response.status_code == 429:
            return {
                "success": False,
                "errorType": "RATE_LIMIT",
                "error": "❌ 请求频率超限，可尝试切换线路重试",
            }

        if response.status_code in (500, 502, 503):
            return {
                "success": False,
                "errorType": "SERVER_ERROR",
                "error": f"❌ 服务端故障（HTTP {response.status_code}）",
            }

        if response.status_code != 200:
            try:
                err = response.json().get("error", {}).get("message", "")
            except Exception:
                err = response.text[:500]
            return {
                "success": False,
                "errorType": "EDIT_FAILED",
                "error": f"图片编辑失败（HTTP {response.status_code}）: {err}",
            }

        # ── 提取图片（b64_json 是纯 base64，无前缀）──
        data = response.json()
        images = data.get("data", [])
        if not images:
            return {
                "success": False,
                "errorType": "NO_DATA",
                "error": "编辑结果为空",
            }

        image_b64 = images[0].get("b64_json", "")
        if not image_b64:
            return {
                "success": False,
                "errorType": "NO_IMAGE_DATA",
                "error": "编辑结果图片数据为空",
            }

        return {"success": True, "image_data": image_b64}

    except requests.exceptions.Timeout:
        return {
            "success": False,
            "errorType": "TIMEOUT",
            "error": f"图片编辑请求超时（超过 {timeout_seconds} 秒）",
        }
    except Exception as e:
        return {
            "success": False,
            "errorType": "EXCEPTION",
            "error": f"图片编辑请求失败: {str(e)}",
        }


# ==============================
# Coze Node 入口
# ==============================

def handler(args: Args[Input]) -> Output:
    """
    Coze / GPT Image 2（API易 代理）节点入口

    - args.input.cleantext:    用户文字提示词
    - args.input.fileurls:     参考图 URL 列表（用于图生图）
    - args.input.aspect_ratio: 宽高比，如 "1:1" / "16:9" / "9:16"
    - args.input.resolution:   分辨率，如 "1K" / "2K" / "4K"
    - args.input.quality:      质量等级，如 "low" / "medium" / "high"（默认 auto）
    - args.input.moderation:   审核强度，如 "auto" / "low"（默认 auto）
    - args.input.output_format: 输出格式，如 "png" / "jpeg" / "webp"（默认 png）
    - args.input.apikey:       API易 API Key（sk-开头）
    """
    API_KEY = args.input.apikey
    cleantext = args.input.cleantext or ""
    fileurls = args.input.fileurls or []
    aspect_ratio = args.input.aspect_ratio or "1:1"
    resolution = args.input.resolution or "1K"
    quality = getattr(args.input, 'quality', None) or "auto"
    output_format = getattr(args.input, 'output_format', None) or "png"
    moderation = getattr(args.input, 'moderation', None) or "auto"

    prompt = cleantext.strip()
    if not prompt:
        prompt = "根据参考图片进行合理的编辑与优化。"

    # 调用 GPT Image 2 生图 / 编辑
    result = generate_image(
        prompt=prompt,
        aspect_ratio=aspect_ratio,
        resolution=resolution,
        quality=quality,
        apikey=API_KEY,
        output_format=output_format,
        moderation=moderation,
        image_urls=fileurls if fileurls else None
    )

    if result["success"]:
        image_base64 = result["image_data"]
        oss_url = upload_base64_to_oss(image_base64)
        return {
            "analysis": "图片生成成功",
            "url": oss_url,
            "error": None,
        }
    else:
        return {
            "analysis": "图片生成失败",
            "url": None,
            "error": result.get("error", "未知错误"),
        }