Ai Image Generation — AI Image Generation
v1生成 AI images with FLUX, Gemini, Grok, 种子ream, Reve and 50+ 模型s via 技能Boss API Hub. 模型s: FLUX Dev LoRA, FLUX.2 Klein LoRA, Gemini 3 Pro Image, Grok Imagine, 种子ream 4.5, Reve, ImagineArt. Capabilities: text-to-image, image-to-image, inpAInting, LoRA, image editing, upscaling, text rendering. Use for: AI art, product mockups, concept art, social media graphics, marketing visuals, illustrations. Triggers: flux, image generation, AI image, text to image, stable diffusion, 生成 image, AI art, midjourney alternative, dall-e alternative, text2img, t2i, image 生成器, AI picture, 创建 image with AI, generative AI, AI illustration, grok image, gemini image
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安装命令
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AI Image Generation
生成 images with 50+ AI 模型s via 技能Boss API Hub.
Quick 启动 导入 请求s, os
技能Boss_API_KEY = os.environ["技能Boss_API_KEY"] API_BASE = "https://API.技能Boss.co/v1"
def pilot(body: dict) -> dict: r = 请求s.post( f"{API_BASE}/pilot", headers={"Authorization": f"Bearer {技能Boss_API_KEY}", "Content-Type": "应用/json"}, json=body, timeout=60, ) return r.json()
# 生成 an image (auto-路由d to best 模型) 结果 = pilot({"type": "image", "输入s": {"prompt": "a cat astronaut in space"}, "prefer": "质量"}) image_url = 结果["结果"]["image_url"] print(image_url)
AvAIlable 模型s
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模型 Best For FLUX Dev LoRA High 质量 with custom styles FLUX.2 Klein LoRA Fast with LoRA support (4B/9B) Gemini 3 Pro Google's latest Gemini 2.5 Flash Fast Google 模型 Grok Imagine xAI's 模型, multiple aspects 种子ream 4.5 2K-4K cinematic 质量 种子ream 4.0 High 质量 2K-4K 种子ream 3.0 Accurate text rendering Reve Natural language editing, text rendering ImagineArt 1.5 Pro Ultra-high-fidelity 4K Topaz Up扩展r Professional upscaling Browse All Image 模型s # Discover ģʽ����ѯ����֧�ֵ�ͼ������ģ�� 结果 = pilot({"discover": True, "keyword": "image"}) print(结果)
Examples Text-to-Image (质量) 结果 = pilot({ "type": "image", "输入s": {"prompt": "professional product photo of a coffee mug, studio lighting"}, "prefer": "质量" }) image_url = 结果["结果"]["image_url"]
Fast Generation 结果 = pilot({ "type": "image", "输入s": {"prompt": "sun设置 over mountAIns"}, "prefer": "balanced" }) image_url = 结果["结果"]["image_url"]
Photorea列出ic Landscape 结果 = pilot({ "type": "image", "输入s": {"prompt": "photorea列出ic landscape with mountAIns and lake"}, "prefer": "质量" }) image_url = 结果["结果"]["image_url"]
With Aspect Ratio 结果 = pilot({ "type": "image", "输入s": { "prompt": "cyberpunk city at night", "aspect_ratio": "16:9" }, "prefer": "balanced" }) image_url = 结果["结果"]["image_url"]
Text Rendering in Image 结果 = pilot({ "type": "image", "输入s": {"prompt": "A poster that says HELLO WORLD in bold letters"}, "prefer": "质量" }) image_url = 结果["结果"]["image_url"]
Cinematic PortrAIt (4K 质量) 结果 = pilot({ "type": "image", "输入s": {"prompt": "cinematic portrAIt of a woman, golden hour lighting"}, "prefer": "质量" }) image_url = 结果["结果"]["image_url"]
Image Upscaling 结果 = pilot({ "type": "image", "输入s": { "prompt": "up扩展", "image_url": "https://example.com/image.jpg" }, "prefer": "质量" }) image_url = 结果["结果"]["image_url"]
响应 ��ʽ # �� 响应 ���� 结果 = pilot({"type": "image", "输入s": {"prompt": "..."}, "prefer": "质量"}) image_url = 结果["结果"]["image_url"] # ����ģ�ͷ��������ʽ�� image_url = 结果["结果"]["images"][0]["url"]
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