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feat: 添加 Antigravity 图像生成 API (OpenAI 兼容)
- 实现 /v1/images/generations 端点 - 添加 ImageGenerationRequest/Response 数据模型 - 实现 OpenAI 到 Antigravity 请求/响应转换器 - 支持 dall-e-3/dall-e-2 模型名映射到 gemini-3-pro-image - 支持 b64_json 和 url 两种响应格式 - 添加 Python SDK 集成测试脚本
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liubu
Executable
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#!/usr/bin/env python3
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"""
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OpenAI 兼容图像生成 API 测试脚本
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使用 OpenAI Python SDK 测试 Antigravity 图像生成 API。
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使用方法:
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# 安装依赖
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pip install openai
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# 运行测试（需要先启动 API Server）
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python scripts/test_image_api.py
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# 指定自定义 API 地址和密钥
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python scripts/test_image_api.py --base-url http://localhost:8999 --api-key your-key
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环境变量:
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PROXYCAST_BASE_URL: API 服务器地址（默认: http://localhost:8999）
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PROXYCAST_API_KEY: API 密钥（默认: pc_LXZbIv3o78WpHuQwqgmwC0U4G0cY5UtQ）
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"""
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import argparse
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import base64
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import os
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import sys
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from datetime import datetime
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try:
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from openai import OpenAI
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except ImportError:
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print("错误: 请先安装 openai 库")
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print("运行: pip install openai")
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sys.exit(1)
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def test_image_generation_url(client: OpenAI, prompt: str) -> bool:
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"""
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测试 URL 响应格式的图像生成
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Args:
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client: OpenAI 客户端
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prompt: 图像生成提示词
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Returns:
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测试是否通过
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"""
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print("\n" + "=" * 60)
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print("测试 1: URL 响应格式")
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print("=" * 60)
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print(f"提示词: {prompt}")
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try:
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response = client.images.generate(
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model="dall-e-3", # 会被映射到 gemini-3-pro-image
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prompt=prompt,
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n=1,
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size="1024x1024",
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response_format="url"
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)
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# 验证响应结构
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print(f"\n响应时间戳: {response.created}")
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print(f"生成图片数量: {len(response.data)}")
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if len(response.data) == 0:
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print("❌ 错误: 没有生成图片")
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return False
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image = response.data[0]
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# 验证 URL 格式
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if image.url:
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print(f"URL 长度: {len(image.url)} 字符")
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if image.url.startswith("data:image/"):
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print("✅ URL 格式正确 (data URL)")
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else:
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print(f"⚠️ URL 格式: {image.url[:50]}...")
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else:
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print("❌ 错误: URL 为空")
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return False
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# 验证 revised_prompt
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if image.revised_prompt:
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print(f"修订提示词: {image.revised_prompt[:100]}...")
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else:
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print("ℹ️ 没有修订提示词")
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print("\n✅ 测试 1 通过")
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return True
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except Exception as e:
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print(f"\n❌ 测试 1 失败: {e}")
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return False
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def test_image_generation_b64(client: OpenAI, prompt: str) -> bool:
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"""
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测试 b64_json 响应格式的图像生成
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Args:
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client: OpenAI 客户端
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prompt: 图像生成提示词
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Returns:
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测试是否通过
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"""
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print("\n" + "=" * 60)
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print("测试 2: b64_json 响应格式")
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print("=" * 60)
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print(f"提示词: {prompt}")
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try:
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response = client.images.generate(
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model="gemini-3-pro-image-preview", # 直接使用 Gemini 模型名
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prompt=prompt,
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n=1,
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response_format="b64_json"
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)
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# 验证响应结构
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print(f"\n响应时间戳: {response.created}")
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print(f"生成图片数量: {len(response.data)}")
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if len(response.data) == 0:
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print("❌ 错误: 没有生成图片")
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return False
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image = response.data[0]
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# 验证 b64_json 格式
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if image.b64_json:
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print(f"Base64 数据长度: {len(image.b64_json)} 字符")
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# 尝试解码验证
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try:
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decoded = base64.b64decode(image.b64_json)
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print(f"解码后大小: {len(decoded)} 字节")
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# 检查图片魔数
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if decoded[:8] == b'\x89PNG\r\n\x1a\n':
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print("✅ 图片格式: PNG")
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elif decoded[:2] == b'\xff\xd8':
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print("✅ 图片格式: JPEG")
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elif decoded[:4] == b'GIF8':
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print("✅ 图片格式: GIF")
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elif decoded[:4] == b'RIFF':
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print("✅ 图片格式: WebP")
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else:
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print(f"⚠️ 未知图片格式: {decoded[:8].hex()}")
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except Exception as e:
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print(f"⚠️ Base64 解码失败: {e}")
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else:
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print("❌ 错误: b64_json 为空")
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return False
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# 验证 revised_prompt
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if image.revised_prompt:
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print(f"修订提示词: {image.revised_prompt[:100]}...")
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else:
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print("ℹ️ 没有修订提示词")
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print("\n✅ 测试 2 通过")
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return True
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except Exception as e:
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print(f"\n❌ 测试 2 失败: {e}")
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return False
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def test_error_handling(client: OpenAI) -> bool:
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"""
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测试错误处理
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Args:
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client: OpenAI 客户端
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Returns:
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测试是否通过
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"""
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print("\n" + "=" * 60)
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print("测试 3: 错误处理")
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print("=" * 60)
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try:
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# 测试空提示词
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print("测试空提示词...")
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try:
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response = client.images.generate(
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model="dall-e-3",
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prompt="", # 空提示词
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n=1
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)
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print("❌ 错误: 应该拒绝空提示词")
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return False
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except Exception as e:
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error_msg = str(e).lower()
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if "prompt" in error_msg or "empty" in error_msg or "required" in error_msg:
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print(f"✅ 正确拒绝空提示词: {e}")
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else:
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print(f"⚠️ 收到错误但消息不明确: {e}")
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print("\n✅ 测试 3 通过")
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return True
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except Exception as e:
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print(f"\n❌ 测试 3 失败: {e}")
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return False
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def test_response_structure(client: OpenAI, prompt: str) -> bool:
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"""
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测试响应结构符合 OpenAI 规范
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Args:
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client: OpenAI 客户端
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prompt: 图像生成提示词
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Returns:
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测试是否通过
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"""
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print("\n" + "=" * 60)
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print("测试 4: 响应结构验证")
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print("=" * 60)
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print(f"提示词: {prompt}")
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try:
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response = client.images.generate(
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model="dall-e-3",
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prompt=prompt,
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n=1,
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response_format="url"
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)
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# 验证 created 字段
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if response.created:
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print(f"✅ created 字段存在: {response.created}")
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# 验证是有效的 Unix 时间戳
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if response.created > 0:
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dt = datetime.fromtimestamp(response.created)
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print(f" 时间: {dt}")
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else:
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print("❌ created 不是有效时间戳")
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return False
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else:
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print("❌ created 字段缺失")
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return False
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# 验证 data 字段
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if response.data is not None:
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print(f"✅ data 字段存在: {len(response.data)} 项")
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if len(response.data) > 0:
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print("✅ data 数组非空")
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else:
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print("❌ data 数组为空")
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return False
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else:
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print("❌ data 字段缺失")
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return False
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# 验证每个图片项
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for i, image in enumerate(response.data):
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print(f"\n图片 {i + 1}:")
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has_url = image.url is not None
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has_b64 = image.b64_json is not None
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if has_url:
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print(f" ✅ url 字段存在")
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if has_b64:
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print(f" ✅ b64_json 字段存在")
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if not has_url and not has_b64:
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print(f" ❌ 缺少 url 和 b64_json")
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return False
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if image.revised_prompt:
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print(f" ✅ revised_prompt 字段存在")
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else:
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print(f" ℹ️ revised_prompt 字段为空")
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print("\n✅ 测试 4 通过")
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return True
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except Exception as e:
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print(f"\n❌ 测试 4 失败: {e}")
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return False
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def main():
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parser = argparse.ArgumentParser(
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description="测试 OpenAI 兼容图像生成 API"
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)
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parser.add_argument(
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"--base-url",
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default=os.environ.get("PROXYCAST_BASE_URL", "http://localhost:8999"),
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help="API 服务器地址"
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)
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parser.add_argument(
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"--api-key",
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default=os.environ.get("PROXYCAST_API_KEY", "pc_LXZbIv3o78WpHuQwqgmwC0U4G0cY5UtQ"),
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help="API 密钥"
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)
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parser.add_argument(
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"--prompt",
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default="A cute fluffy cat sitting on a windowsill, looking at the sunset",
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help="测试用的图像生成提示词"
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)
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parser.add_argument(
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"--skip-generation",
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action="store_true",
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help="跳过实际图像生成测试（仅测试错误处理）"
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)
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args = parser.parse_args()
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print("=" * 60)
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print("OpenAI 兼容图像生成 API 测试")
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print("=" * 60)
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print(f"API 地址: {args.base_url}")
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print(f"API 密钥: {args.api_key[:8]}...")
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print(f"测试提示词: {args.prompt[:50]}...")
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# 创建 OpenAI 客户端
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client = OpenAI(
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base_url=f"{args.base_url}/v1",
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api_key=args.api_key
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)
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results = []
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if not args.skip_generation:
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# 测试 1: URL 响应格式
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results.append(("URL 响应格式", test_image_generation_url(client, args.prompt)))
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# 测试 2: b64_json 响应格式
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results.append(("b64_json 响应格式", test_image_generation_b64(client, args.prompt)))
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# 测试 4: 响应结构验证
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results.append(("响应结构验证", test_response_structure(client, args.prompt)))
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# 测试 3: 错误处理
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results.append(("错误处理", test_error_handling(client)))
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# 打印总结
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print("\n" + "=" * 60)
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print("测试总结")
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print("=" * 60)
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passed = 0
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failed = 0
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for name, result in results:
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status = "✅ 通过" if result else "❌ 失败"
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print(f" {name}: {status}")
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if result:
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passed += 1
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else:
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failed += 1
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print(f"\n总计: {passed} 通过, {failed} 失败")
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if failed > 0:
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sys.exit(1)
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else:
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print("\n🎉 所有测试通过!")
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sys.exit(0)
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if __name__ == "__main__":
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main()
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