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ChinesePollinations.ai Image Generation
Pollinations.ai 图片生成
Free, open-source AI image generation through simple URL parameters. No API key or signup required.
通过简单的URL参数实现免费、开源的AI图片生成。无需API密钥或注册。
When to use this skill
何时使用该技能
- Quick prototyping: Generate placeholder images instantly
- Marketing assets: Create hero images, banners, social media content
- Creative exploration: Test multiple styles and compositions rapidly
- No-budget projects: Free alternative to paid image generation services
- Automated workflows: Script-friendly URL-based API
- 快速原型制作:即时生成占位图片
- 营销素材制作:生成首页横幅、广告图、社交媒体内容
- 创意探索:快速测试多种风格和构图
- 零预算项目:付费图片生成服务的免费替代方案
- 自动化工作流:支持脚本调用的基于URL的API
Instructions
使用说明
Step 1: Understand the API Structure
步骤1:了解API结构
Pollinations.ai uses a simple URL-based API:
https://image.pollinations.ai/prompt/{YOUR_PROMPT}?{PARAMETERS}No authentication required - just construct the URL and fetch the image.
Available Parameters:
- /
width: Resolution (default: 1024x1024)height - : AI model (
model,flux,turbo)stable-diffusion - : Number for reproducible results
seed - :
nologoto remove watermark (if supported)true - :
enhancefor automatic prompt enhancementtrue
Pollinations.ai 使用简单的基于URL的API:
https://image.pollinations.ai/prompt/{YOUR_PROMPT}?{PARAMETERS}无需身份验证 - 只需构造URL即可获取图片。
可用参数:
- /
width: 分辨率(默认值:1024x1024)height - : AI模型(
model,flux,turbo)stable-diffusion - : 用于生成可复现结果的数值
seed - : 设置为
nologo以移除水印(若支持)true - : 设置为
enhance以自动优化提示词true
Step 2: Craft Your Prompt
步骤2:编写提示词
Use descriptive prompts with specific details:
Good prompt structure:
[Subject], [Style], [Lighting], [Mood], [Composition], [Quality modifiers]Example:
A father welcoming a beautiful holiday, warm golden hour lighting,
cozy interior background with festive decorations, 8k resolution,
highly detailed, cinematic depth of fieldPrompt styles:
- Photorealistic: "photorealistic shot, 8k resolution, highly detailed, cinematic"
- Illustrative: "digital illustration, soft pastel colors, disney style animation"
- Minimalist: "minimalist vector art, flat design, simple geometric shapes"
使用包含具体细节的描述性提示词:
优质提示词结构:
[主体], [风格], [光线], [氛围], [构图], [画质修饰词]示例:
一位父亲迎接美好假期,温暖的黄金时段光线,带有节日装饰的温馨室内背景,8K分辨率,细节丰富,电影级景深提示词风格:
- 写实风格:"写实拍摄,8K分辨率,细节丰富,电影质感"
- 插画风格:"数字插画,柔和马卡龙色调,迪士尼动画风格"
- 极简风格:"极简矢量图,扁平化设计,简单几何图形"
Step 3: Generate via URL (Browser Method)
步骤3:通过URL生成(浏览器方法)
Simply open the URL in a browser or use :
curlbash
undefined直接在浏览器中打开URL,或使用命令:
curlbash
undefinedBasic generation
基础生成
curl "https://image.pollinations.ai/prompt/A_serene_mountain_landscape" -o mountain.jpg
curl "https://image.pollinations.ai/prompt/A_serene_mountain_landscape" -o mountain.jpg
With parameters
带参数生成
curl "https://image.pollinations.ai/prompt/A_serene_mountain_landscape?width=1920&height=1080&model=flux&seed=42" -o mountain-hd.jpg
undefinedcurl "https://image.pollinations.ai/prompt/A_serene_mountain_landscape?width=1920&height=1080&model=flux&seed=42" -o mountain-hd.jpg
undefinedStep 4: Generate and Save (Python Method)
步骤4:生成并保存(Python方法)
For automation and file management:
python
import requests
from urllib.parse import quote
def generate_image(prompt, output_file, width=1920, height=1080, model="flux", seed=None):
"""
Generate image using Pollinations.ai and save to file
Args:
prompt: Description of the image to generate
output_file: Path to save the image
width: Image width in pixels
height: Image height in pixels
model: AI model ('flux', 'turbo', 'stable-diffusion')
seed: Optional seed for reproducibility
"""
# Encode prompt for URL
encoded_prompt = quote(prompt)
url = f"https://image.pollinations.ai/prompt/{encoded_prompt}"
# Build parameters
params = {
"width": width,
"height": height,
"model": model,
"nologo": "true"
}
if seed:
params["seed"] = seed
# Generate and save
print(f"Generating: {prompt[:50]}...")
response = requests.get(url, params=params)
if response.status_code == 200:
with open(output_file, "wb") as f:
f.write(response.content)
print(f"✓ Saved to {output_file}")
return True
else:
print(f"✗ Error: {response.status_code}")
return False适用于自动化和文件管理场景:
python
import requests
from urllib.parse import quote
def generate_image(prompt, output_file, width=1920, height=1080, model="flux", seed=None):
"""
使用Pollinations.ai生成图片并保存到文件
参数:
prompt: 要生成的图片描述
output_file: 图片保存路径
width: 图片宽度(像素)
height: 图片高度(像素)
model: AI模型('flux', 'turbo', 'stable-diffusion')
seed: 可选参数,用于结果复现
"""
# 对提示词进行URL编码
encoded_prompt = quote(prompt)
url = f"https://image.pollinations.ai/prompt/{encoded_prompt}"
# 构建参数
params = {
"width": width,
"height": height,
"model": model,
"nologo": "true"
}
if seed:
params["seed"] = seed
# 生成并保存
print(f"生成中: {prompt[:50]}...")
response = requests.get(url, params=params)
if response.status_code == 200:
with open(output_file, "wb") as f:
f.write(response.content)
print(f"✓ 已保存到 {output_file}")
return True
else:
print(f"✗ 错误: {response.status_code}")
return FalseExample usage
使用示例
generate_image(
prompt="A father welcoming a beautiful holiday, warm lighting, festive decorations",
output_file="holiday_father.jpg",
width=1920,
height=1080,
model="flux",
seed=12345
)
undefinedgenerate_image(
prompt="一位父亲迎接美好假期,温暖光线,节日装饰",
output_file="holiday_father.jpg",
width=1920,
height=1080,
model="flux",
seed=12345
)
undefinedStep 5: Batch Generation
步骤5:批量生成
Generate multiple variations:
python
prompts = [
"photorealistic shot of a father at front door, warm lighting, festive decorations",
"digital illustration of a father in snow, magical winter wonderland, disney style",
"minimalist silhouette of father and child, holiday fireworks, flat design"
]
for i, prompt in enumerate(prompts):
generate_image(
prompt=prompt,
output_file=f"variant_{i+1}.jpg",
width=1920,
height=1080,
model="flux"
)生成多张变体图片:
python
prompts = [
"父亲在前门的写实照片,温暖光线,节日装饰",
"父亲在雪地中的数字插画,梦幻冬日仙境,迪士尼风格",
"父子的极简剪影,节日烟花,扁平化设计"
]
for i, prompt in enumerate(prompts):
generate_image(
prompt=prompt,
output_file=f"variant_{i+1}.jpg",
width=1920,
height=1080,
model="flux"
)Step 6: Document Your Generations
步骤6:记录生成信息
Save metadata for reproducibility:
python
import json
from datetime import datetime
metadata = {
"prompt": prompt,
"model": "flux",
"width": 1920,
"height": 1080,
"seed": 12345,
"output_file": "holiday_father.jpg",
"timestamp": datetime.now().isoformat()
}
with open("generation_metadata.json", "w") as f:
json.dump(metadata, f, indent=2)保存元数据以便复现:
python
import json
from datetime import datetime
metadata = {
"prompt": prompt,
"model": "flux",
"width": 1920,
"height": 1080,
"seed": 12345,
"output_file": "holiday_father.jpg",
"timestamp": datetime.now().isoformat()
}
with open("generation_metadata.json", "w") as f:
json.dump(metadata, f, indent=2)Examples
示例
Example 1: Hero Image for Website
示例1:网站首页横幅图片
python
generate_image(
prompt="serene mountain landscape at sunset, wide 16:9, minimal style, soft gradients in blue tones, clean lines, modern aesthetic",
output_file="hero-image.jpg",
width=1920,
height=1080,
model="flux"
)Expected output: 16:9 landscape image, minimal style, blue color palette
python
generate_image(
prompt="日落时分的宁静山地景观,16:9宽幅,极简风格,蓝色调柔和渐变,简洁线条,现代美学",
output_file="hero-image.jpg",
width=1920,
height=1080,
model="flux"
)预期输出:16:9比例的景观图片,极简风格,蓝色调色板
Example 2: Product Thumbnail
示例2:产品缩略图
python
generate_image(
prompt="futuristic dashboard UI, 1:1 square, clean interface, soft lighting, professional feel, dark theme, subtle glow effects",
output_file="product-thumb.jpg",
width=1024,
height=1024,
model="flux"
)Expected output: Square thumbnail, dark theme, app store ready
python
generate_image(
prompt="未来感仪表盘UI,1:1正方形,简洁界面,柔和光线,专业质感,深色主题,微妙发光效果",
output_file="product-thumb.jpg",
width=1024,
height=1024,
model="flux"
)预期输出:正方形缩略图,深色主题,符合应用商店规范
Example 3: Social Media Banner
示例3:社交媒体横幅
python
generate_image(
prompt="LinkedIn banner for SaaS startup, modern gradient background, abstract geometric shapes, colors from purple to blue, space for text on left side",
output_file="linkedin-banner.jpg",
width=1584,
height=396,
model="flux"
)Expected output: LinkedIn-optimized dimensions (1584x396), text-safe zone
python
generate_image(
prompt="SaaS初创公司的LinkedIn横幅,现代渐变背景,抽象几何图形,紫蓝色调,左侧预留文字空间",
output_file="linkedin-banner.jpg",
width=1584,
height=396,
model="flux"
)预期输出:符合LinkedIn尺寸要求(1584x396),带有安全文字区域
Example 4: Batch Variations with Seeds
示例4:带种子值的批量变体生成
python
undefinedpython
undefinedGenerate 4 variations of the same prompt with different seeds
使用不同种子值生成同提示词的4种变体
base_prompt = "A father welcoming a beautiful holiday, cinematic lighting"
for seed in [100, 200, 300, 400]:
generate_image(
prompt=base_prompt,
output_file=f"variation_seed_{seed}.jpg",
width=1920,
height=1080,
model="flux",
seed=seed
)
**Expected output**: 4 similar images with subtle variations
---base_prompt = "一位父亲迎接美好假期,电影级光线"
for seed in [100, 200, 300, 400]:
generate_image(
prompt=base_prompt,
output_file=f"variation_seed_{seed}.jpg",
width=1920,
height=1080,
model="flux",
seed=seed
)
**预期输出**:4张相似但略有差异的图片
---Best practices
最佳实践
- Use specific prompts: Include style, lighting, mood, and quality modifiers
- Specify dimensions early: Prevents unintended cropping
- Use seeds for consistency: Same seed + prompt = same image
- Model selection:
- : Highest quality, slower
flux - : Fast iterations
turbo - : Balanced
stable-diffusion
- Save metadata: Track prompts, seeds, and parameters for reproducibility
- Batch similar requests: Generate style sets with consistent parameters
- URL encode prompts: Use for special characters
urllib.parse.quote()
- 使用具体提示词:包含风格、光线、氛围和画质修饰词
- 提前指定尺寸:避免意外裁剪
- 使用种子值保证一致性:相同种子值+提示词=相同图片
- 模型选择:
- : 画质最高,速度较慢
flux - : 快速迭代
turbo - : 平衡画质与速度
stable-diffusion
- 保存元数据:记录提示词、种子值和参数以便复现
- 批量相似请求:使用一致参数生成风格统一的图片集
- 对提示词进行URL编码:使用处理特殊字符
urllib.parse.quote()
Common pitfalls
常见误区
- Vague prompts: Add specific details about style, lighting, and composition
- Ignoring aspect ratios: Check target platform requirements (Instagram 1:1, LinkedIn 1584x396, etc.)
- Overly complex scenes: Simplify for clarity and better results
- Not saving metadata: Difficult to reproduce or iterate on successful images
- Forgetting URL encoding: Special characters break URLs
- 模糊的提示词:补充关于风格、光线和构图的具体细节
- 忽略宽高比:确认目标平台的要求(Instagram 1:1,LinkedIn 1584x396等)
- 过于复杂的场景:简化描述以获得更清晰、更好的结果
- 未保存元数据:难以复现或优化成功生成的图片
- 忘记URL编码:特殊字符会导致URL失效
Troubleshooting
故障排除
Issue: Inconsistent outputs
问题:输出结果不一致
Cause: No seed specified
Solution: Use a fixed seed for reproducible results
python
generate_image(prompt="...", seed=12345, ...) # Same output every time原因:未指定种子值
解决方案:使用固定种子值确保结果可复现
python
generate_image(prompt="...", seed=12345, ...) # 每次输出都相同Issue: Wrong aspect ratio
问题:宽高比错误
Cause: Incorrect width/height parameters
Solution: Use platform-specific dimensions
python
undefined原因:width/height参数设置错误
解决方案:使用平台专属尺寸
python
undefinedInstagram: 1:1
Instagram: 1:1
generate_image(prompt="...", width=1080, height=1080)
generate_image(prompt="...", width=1080, height=1080)
LinkedIn banner: ~4:1
LinkedIn横幅: ~4:1
generate_image(prompt="...", width=1584, height=396)
generate_image(prompt="...", width=1584, height=396)
YouTube thumbnail: 16:9
YouTube缩略图: 16:9
generate_image(prompt="...", width=1280, height=720)
undefinedgenerate_image(prompt="...", width=1280, height=720)
undefinedIssue: Image doesn't match brand colors
问题:图片与品牌色调不符
Cause: No color specification in prompt
Solution: Include HEX codes or color names
python
prompt = "landscape with brand colors deep blue #2563EB and purple #8B5CF6"原因:提示词中未指定颜色
解决方案:包含十六进制颜色码或颜色名称
python
prompt = "包含品牌色深蓝色#2563EB和紫色#8B5CF6的景观图"Issue: Request fails (HTTP error)
问题:请求失败(HTTP错误)
Cause: Network issue or service downtime
Solution: Add retry logic
python
import time
def generate_with_retry(prompt, output_file, max_retries=3):
for attempt in range(max_retries):
if generate_image(prompt, output_file):
return True
print(f"Retry {attempt + 1}/{max_retries}...")
time.sleep(2)
return False原因:网络问题或服务停机
解决方案:添加重试逻辑
python
import time
def generate_with_retry(prompt, output_file, max_retries=3):
for attempt in range(max_retries):
if generate_image(prompt, output_file):
return True
print(f"重试 {attempt + 1}/{max_retries}...")
time.sleep(2)
return FalseOutput format
输出格式
markdown
undefinedmarkdown
undefinedImage Generation Report
图片生成报告
Request
请求信息
- Prompt: [full prompt text]
- Model: flux
- Dimensions: 1920x1080
- Seed: 12345
- 提示词:[完整提示词文本]
- 模型:flux
- 尺寸:1920x1080
- 种子值:12345
Output Files
输出文件
- - Primary variant
hero-image-v1.jpg - - Alternative style
hero-image-v2.jpg - - Different lighting
hero-image-v3.jpg
- - 主要变体
hero-image-v1.jpg - - 替代风格
hero-image-v2.jpg - - 不同光线效果
hero-image-v3.jpg
Metadata
元数据
- Generated: 2026-02-13T14:30:00Z
- Iterations: 3
- Selected: hero-image-v1.jpg
- 生成时间:2026-02-13T14:30:00Z
- 迭代次数:3
- 选中版本:hero-image-v1.jpg
Usage Notes
使用说明
- Best for: Website hero section
- Format: JPEG, 1920x1080
- Reproducible: Yes (seed: 12345)
---- 最佳用途:网站首页横幅
- 格式:JPEG,1920x1080
- 可复现:是(种子值:12345)
---Multi-Agent Workflow
多Agent工作流
Validation & Quality Check
验证与质量检查
-
Round 1 (Orchestrator - Claude):
- Validate prompt completeness
- Check dimension requirements
- Verify seed consistency
-
Round 2 (Executor - Codex):
- Execute generation script
- Save files with proper naming
- Generate metadata JSON
-
Round 3 (Analyst - Gemini):
- Review style consistency
- Check brand alignment
- Suggest prompt improvements
-
第一轮(协调器 - Claude):
- 验证提示词完整性
- 检查尺寸要求
- 确认种子值一致性
-
第二轮(执行器 - Codex):
- 执行生成脚本
- 按规范命名并保存文件
- 生成元数据JSON
-
第三轮(分析师 - Gemini):
- 检查风格一致性
- 验证品牌契合度
- 提供提示词优化建议
Agent Roles
Agent角色
| Agent | Role | Tools |
|---|---|---|
| Claude | Prompt engineering, quality validation | Write, Read |
| Codex | Script execution, batch processing | Bash, Write |
| Gemini | Style analysis, brand consistency check | Read, ask-gemini |
| Agent | 角色 | 工具 |
|---|---|---|
| Claude | 提示词工程、质量验证 | 编写、读取 |
| Codex | 脚本执行、批量处理 | Bash、编写 |
| Gemini | 风格分析、品牌一致性检查 | 读取、ask-gemini |
Example Multi-Agent Workflow
多Agent工作流示例
bash
undefinedbash
undefined1. Claude: Generate prompts and script
1. Claude:生成提示词和脚本
2. Codex: Execute generation
2. Codex:执行生成任务
bash -c "python generate_images.py"
bash -c "python generate_images.py"
3. Gemini: Review outputs
3. Gemini:审核输出结果
ask-gemini "@outputs/ Analyze brand consistency of generated images"
---ask-gemini "@outputs/ 分析生成图片的品牌一致性"
---Metadata
元数据
Version
版本
- Current Version: 1.0.0
- Last Updated: 2026-02-13
- Compatible Platforms: Claude, ChatGPT, Gemini, Codex
- 当前版本:1.0.0
- 最后更新:2026-02-13
- 兼容平台:Claude、ChatGPT、Gemini、Codex
Related Skills
相关技能
- image-generation - MCP-based image generation
- design-system - Design system implementation
- presentation-builder - Presentation creation
- image-generation - 基于MCP的图片生成
- design-system - 设计系统实现
- presentation-builder - 演示文稿制作
API Documentation
API文档
- Official Site: https://pollinations.ai
- API Endpoint: https://image.pollinations.ai/prompt/{prompt}
- Models: flux, turbo, stable-diffusion
- 官方网站:https://pollinations.ai
- API端点:https://image.pollinations.ai/prompt/{prompt}
- 支持模型:flux、turbo、stable-diffusion
Tags
标签
#pollinations#image-generation#free#api#url-based#no-signup#creative#pollinations#image-generation#free#api#url-based#no-signup#creative