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Agent Skill · 图像处理

nano-banana-image-editor(纳米香蕉图像编辑器)

用于辅助图像生成、图片编辑、视觉素材处理或图像模型工作流。它适合让 Agent 根据文本生成图片、处理背景、整理视觉提示词或调用相关图像工具。使用时需要确认输入图片、版权来源、输出格式和模型限制;涉及人物、品牌、商品或公开展示素材时,应额外核对授权、真实性和内容合规边界。

nano-banana-image-editor 是图像处理类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描有未通过项,按安装量在图像处理类的 1,562 个 Skill 里排第 1,486。

总安装 235周安装 10GitHub Stars 13下载 82核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:nano-banana-image-editor(纳米香蕉图像编辑器)
来源仓库:https://github.com/emdashcodes/claude-code-plugins
仓库路径:skills/nano-banana-image-editor
安装命令:
npx skills add https://github.com/emdashcodes/claude-code-plugins --skill nano-banana-image-editor
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/emdashcodes/claude-code-plugins --skill nano-banana-image-editor

这个 Skill 是做什么的

图像处理类 Skill 处理生成、裁剪、压缩和批量转换图片的任务。

用于辅助图像生成、图片编辑和视觉素材处理。nano-banana-image-editor 属于图像处理类 Skill,可作为该场景下的辅助能力补充。适合根据文本生成图片、处理背景或整理视觉提示词。调用相关图像工具前需确认输入图片、版权来源和模型限制。涉及人物或品牌素材时应核对授权与内容合规边界。

安装需通过 GitHub 仓库并指定技能名称。

来源仓库内路径:skills/nano-banana-image-editor

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/emdashcodes/claude-code-plugins --skill nano-b…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

nano-banana-image-editor 怎么安装?

在终端执行 npx skills add https://github.com/emdashcodes/claude-code-plugins --skill nano-banana-imag…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

nano-banana-image-editor 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

nano-banana-image-editor 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

nano-banana-image-editor 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

nano-banana-image-editor 用的人多吗?

公开数据是累计安装 235 次,近一周安装 10 次,下载 82 次,GitHub 13 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

nano-banana-image-editor 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理图像处理类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

图像处理类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
ai-image-generation

AI 图像生成 · Codex、Claude

4,365,552382调用外部服务未明确有提醒
openai-image-gen

OpenAI 图像生成 · OpenClaw

1,906,88432需要联网MIT-0有提醒
image

图像 · OpenClaw

525,99926需要联网MIT-0通过
baoyu-cover-image

宝玉封面图 · Codex、Claude

474,24016,779只读MIT有提醒
baoyu-image-gen

宝玉图像生成器 · Codex、Claude

468,00716,778接触敏感数据MIT通过
nano-banana-image-editor

纳米香蕉图像编辑器 · 本页

23513接触敏感数据未明确未通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Image Editor

This skill enables AI-powered image editing and creation using Google's Gemini 3 Pro Image model (nicknamed "Nano Banana Pro"). It allows editing existing images or creating new images from scratch through natural language instructions.

When to Use This Skill

Use this skill when users request:

  • Generate icons, images, and illustrations
  • Removing text, logos, or watermarks from images
  • Removing speaker overlays or video conference windows from slides
  • Changing backgrounds, objects, or colors
  • Cropping, resizing, or adjusting image composition
  • Adding or modifying visual elements
  • Style transfers or artistic transformations
  • Any image manipulation describable in natural language

Prerequisites

If needed, run the following script to install dependencies:

${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/scripts/install_dependencies.sh

This creates a Python virtual environment and installs the required packages (google-genai, Pillow).

Virtual environment location:

  • Default: ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv/
  • Override: Set NANO_BANANA_VENV env var for multi-platform support (e.g., Docker containers)

API Key Setup:

  1. Get an API key from Google AI Studio
  2. Run the setup script to save the key to the plugin config: ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv/bin/${NANO_BANANA_VENV:-${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv}/bin/python3 ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/scripts/setup-gemini-token.py YOUR_API_KEY The script will:

- Test the API key to verify it works - Save it to .nano-banana-config.json in the plugin directory - Confirm that Gemini 3 Pro Image model is available

All script examples below use ${NANO_BANANA_VENV:-${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv}/bin/python3 to ensure the venv's Python interpreter is used.

How to Use

Creating New Images from Scratch

Use the create_image.py script to generate new images from natural language prompts:

${NANO_BANANA_VENV:-${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv}/bin/python3 ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/scripts/create_image.py \
  OUTPUT_IMAGE "creation instruction" --resolution 1K --aspect-ratio 1:1

Example: Create an icon

${NANO_BANANA_VENV:-${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv}/bin/python3 ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/scripts/create_image.py \
  cat-icon.png "A playful orange tabby cat icon, simple and clean design" \
  --resolution 1K --aspect-ratio 1:1

Example: Create a high-resolution illustration

${NANO_BANANA_VENV:-${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv}/bin/python3 ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/scripts/create_image.py \
  sunset.png "A vibrant sunset over mountains with purple and orange sky" \
  --resolution 4K --aspect-ratio 16:9

Example: Create with reference images for style

${NANO_BANANA_VENV:-${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv}/bin/python3 ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/scripts/create_image.py \
  landscape.png "A mountain landscape in this artistic style" \
  --reference style.png --resolution 2K --aspect-ratio 3:2

Prompting Tips:

  • Be specific about colors, style, and composition
  • Specify the desired mood or atmosphere
  • Use reference images to demonstrate desired style or composition
  • Important: See references/prompting_guide.md for comprehensive prompting strategies

Editing Existing Images

Use the edit_image.py script to edit existing images with natural language prompts:

${NANO_BANANA_VENV:-${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv}/bin/python3 ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/scripts/edit_image.py \
  INPUT_IMAGE OUTPUT_IMAGE "editing instruction" --resolution 1K --aspect-ratio 1:1

Example: Remove text overlay

${NANO_BANANA_VENV:-${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv}/bin/python3 ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/scripts/edit_image.py \
  slide.png slide-cleaned.png \
  "Remove the text labels from the top of this diagram"

Example: Background removal with high resolution

${NANO_BANANA_VENV:-${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv}/bin/python3 ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/scripts/edit_image.py \
  photo.jpg photo-no-bg.png \
  "Remove the background and make it transparent white" \
  --resolution 2K --aspect-ratio 4:3

Example: Style transfer with reference image

${NANO_BANANA_VENV:-${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv}/bin/python3 ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/scripts/edit_image.py \
  photo.jpg artistic.png \
  "Apply the artistic style from the reference to this photo" \
  --reference style.png --resolution 2K

Advanced Multi-Image Features

Recreating Templates with Different Characters

Important: When recreating memes, comics, or templates with different characters, always pass both the template AND the character references.

${NANO_BANANA_VENV:-${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv}/bin/python3 ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/scripts/create_image.py \
  output.png "Recreate this meme template using these characters" \
  --reference template.png --reference character1.png --reference character2.png \
  --resolution 2K --aspect-ratio 16:9

Why both?

  • The template/meme reference provides the composition, layout, poses, and panel structure
  • The character references provide facial features, hairstyles, and distinctive characteristics to maintain

Example: Recreating a two-panel comic meme

${NANO_BANANA_VENV:-${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv}/bin/python3 ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/scripts/create_image.py \
  my-meme.png "Recreate this two-panel comic using these two women as the characters. Maintain the exact composition and poses from the template." \
  --reference original-meme.png --reference my-characters.png \
  --resolution 2K --aspect-ratio 16:9
Character Consistency (Up to 5 People)

Create group photos maintaining facial resemblance:

${NANO_BANANA_VENV:-${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv}/bin/python3 ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/scripts/create_image.py \
  group.png "Office group photo of these people making funny faces" \
  --reference person1.png --reference person2.png --reference person3.png \
  --resolution 2K --aspect-ratio 5:4
Object Composition (Up to 6 Objects)

Blend multiple objects with high fidelity:

${NANO_BANANA_VENV:-${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv}/bin/python3 ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/scripts/create_image.py \
  product.png "Product showcase featuring these items on a marble surface" \
  --reference item1.png --reference item2.png --reference item3.png \
  --resolution 4K --aspect-ratio 16:9
Advanced Editing with References

Edit an image while using additional references:

${NANO_BANANA_VENV:-${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv}/bin/python3 ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/scripts/edit_image.py \
  background.jpg composite.png \
  "Add these people to the scene, natural lighting" \
  --reference person1.png --reference person2.png \
  --resolution 2K

Google Search Grounding

Enable real-time information for factual content:

${NANO_BANANA_VENV:-${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv}/bin/python3 ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/scripts/create_image.py \
  weather.png "An infographic about today's weather in San Francisco" \
  --search --resolution 2K --aspect-ratio 3:4
${NANO_BANANA_VENV:-${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv}/bin/python3 ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/scripts/create_image.py \
  plant-guide.png "Create an educational infographic about String of Turtles houseplant care" \
  --search --resolution 2K --aspect-ratio 3:4

When to use --search:

  • Weather visualizations and forecasts
  • Current events and news graphics
  • Scientific diagrams requiring factual accuracy
  • Educational infographics about real-world subjects
  • Sports statistics and data visualizations

Resolution and Aspect Ratio Selection

Resolution Options:

  • 1K (default) - Fast, good for iteration and testing (1024×1024 at 1:1)
  • 2K - Professional quality (2048×2048 at 1:1)
  • 4K - Maximum quality, studio-grade (4096×4096 at 1:1)

Common Aspect Ratios:

  • 1:1 - Social media posts, profile pictures, icons
  • 16:9 - Presentations, YouTube thumbnails, desktop wallpapers
  • 9:16 - Instagram Stories, TikTok, mobile vertical content
  • 4:3 - Traditional displays, print media
  • 3:2 - Standard photography
  • 21:9 - Ultra-wide cinematic shots

Example with custom resolution and aspect ratio:

${NANO_BANANA_VENV:-${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv}/bin/python3 ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/scripts/create_image.py \
  banner.png "A website hero banner with mountains and sunrise" \
  --resolution 4K --aspect-ratio 21:9

Workflow

  1. Identify the task - Determine if the user wants to create a new image or edit an existing one
  2. Check for dependencies and API key - If errors occur, verify the API key is configured in the config file and that dependencies are installed
  3. Prepare the prompt - Translate the user's request into a clear, specific natural language instruction
  4. Run the appropriate script:

- Use create_image.py for generating new images - Use edit_image.py for modifying existing images

  1. Review the output - Check if the result meets expectations; iterate if needed

Tips for Effective Prompts

  • Be specific: "Remove the red text in the top-left corner" is better than "clean up the image"
  • Describe desired outcome: "Replace the blue background with white" vs just "change background"
  • Iterative editing: Make one change at a time for better results
  • Reference locations: Use "top left", "bottom right", "center" to specify areas
  • Use reference images: Provide style examples, object references, or character photos when appropriate
  • Pass ALL relevant references: When recreating templates/memes with different characters, pass both the template image AND the character images as references
  • Enable search for facts: Add --search when generating content requiring real-time information

For comprehensive prompting strategies, see references/prompting_guide.md For best practices and workflow optimization, see references/best_practices.md

Model Capabilities

Gemini 3 Pro Image supports:

  • Object removal and addition with advanced reasoning
  • Background changes and removal
  • Accurate and legible text rendering in multiple languages
  • Color adjustments and advanced color grading
  • Studio-quality lighting controls (day/night, bokeh effects)
  • Camera angle and focus adjustments
  • Style transfers and artistic transformations
  • Multi-image blending (up to 14 reference images)
  • Character/subject consistency for up to 5 people across edits
  • Sketch-to-product and blueprint-to-3D transformations
  • Real-time data grounding via Google Search (recipes, weather, sports)
  • High-resolution output (2K and 4K with multiple aspect ratios)

Technical Specifications

Input Limits:

  • Maximum images per prompt: 14 total

- Up to 6 images for object fidelity - Up to 5 images for character consistency

  • Maximum file size: 7 MB per image
  • Supported formats: PNG, JPEG, WebP

Output Specifications:

  • Resolution options: 1K, 2K, 4K
  • Supported aspect ratios: 1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9
  • All generated images include SynthID watermarking

Resolution Examples:

  • 1K at 1:1 = 1024×1024 pixels
  • 2K at 1:1 = 2048×2048 pixels
  • 4K at 1:1 = 4096×4096 pixels
  • 4K at 16:9 = 5504×3072 pixels
  • 4K at 21:9 = 6336×2688 pixels

Troubleshooting

"No Gemini API key configured" error:

  • Run the setup script: ${NANO_BANANA_VENV:-${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv}/bin/python3 ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/scripts/setup-gemini-token.py YOUR_API_KEY

"No image in response" message:

  • The model may have returned text instead of an edited image
  • Try rephrasing the prompt more specifically
  • Check API rate limits or quota

Poor edit quality:

  • Be more specific in the prompt
  • Try breaking complex edits into multiple steps
  • Ensure input image quality is sufficient

"MALFORMED_FUNCTION_CALL" error when editing:

  • Do NOT request watermark removal - Gemini blocks prompts mentioning "remove watermark" to protect SynthID watermarks
  • Avoid prompts like "remove the watermark" or "clean up watermarks"
  • This is a content policy restriction, not a technical limitation

Prompts with dollar signs or special characters getting stripped:

  • Problem: Dollar signs ($3, $4.50) and other bash special characters get removed from prompts
  • Cause: When using double quotes in bash, $variable syntax triggers variable expansion
  • Solutions:

- Use single quotes instead of double quotes: 'Espresso $3, Latte $4' - Escape dollar signs with backslash: "Espresso \\$3, Latte \\$4" - Other special characters to watch: exclamation marks, backticks, backslashes, dollar signs, quotes

Example:

# ❌ Wrong - dollar signs get expanded as variables
${NANO_BANANA_VENV:-${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv}/bin/python3 ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/scripts/create_image.py \
  menu.png "Coffee menu: Espresso $3, Latte $4"

# ✅ Correct - use single quotes
${NANO_BANANA_VENV:-${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv}/bin/python3 ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/scripts/create_image.py \
  menu.png 'Coffee menu: Espresso $3, Latte $4'

# ✅ Also correct - escape the dollar signs
${NANO_BANANA_VENV:-${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv}/bin/python3 ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/scripts/create_image.py \
  menu.png "Coffee menu: Espresso \$3, Latte \$4"

Non-AI Alternatives for Quick Edits

For simple, deterministic image operations, you can also use PIL/Pillow (Python) instead of the AI model. This is faster, free, and more predictable for basic tasks:

Quick Crop Script (Recommended)

Use the included quick_crop.py script for fast, precise cropping:

# Remove 100px from the right edge
${NANO_BANANA_VENV:-${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv}/bin/python3 ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/scripts/quick_crop.py \
  input.png output.png --remove-right 100

# Exact crop box
${NANO_BANANA_VENV:-${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv}/bin/python3 ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/scripts/quick_crop.py \
  input.png output.png --left 0 --top 0 --right 1200 --bottom 800

# Remove pixels from bottom
${NANO_BANANA_VENV:-${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/.venv}/bin/python3 ${CLAUDE_PLUGIN_ROOT}/skills/nano-banana-image-editor/scripts/quick_crop.py \
  input.png output.png --remove-bottom 50

Manual PIL/Pillow Code

For custom operations, use PIL directly:

from PIL import Image

img = Image.open('input.png')
# Crop: (left, top, right, bottom)
cropped = img.crop((0, 0, img.size[0] - 100, img.size[1]))  # Remove 100px from right
cropped.save('output.png')

Resizing

from PIL import Image

img = Image.open('input.png')
resized = img.resize((1920, 1080))
resized.save('output.png')

Rotating

from PIL import Image

img = Image.open('input.png')
rotated = img.rotate(90, expand=True)
rotated.save('output.png')

References

Essential Guides

references/prompting_guide.md

  • Photorealistic scenes with photography terminology
  • Stylized illustrations and stickers
  • Accurate text rendering in images
  • Product mockups and commercial photography
  • Minimalist and negative space design
  • Sequential art (comic panels, storyboards)
  • Image editing strategies (adding/removing elements, style transfer, composition)
  • Multi-image prompting techniques
  • Google Search grounding examples

references/best_practices.md

  • Writing hyper-specific prompts for maximum control
  • Iterative refinement through multi-turn conversations
  • Step-by-step instructions for complex compositions
  • Using photography and camera terminology effectively
  • Multiple reference images best practices (character consistency, object fidelity, style transfer)
  • Resolution strategy (when to use 1K vs 2K vs 4K)
  • Aspect ratio selection for different use cases
  • When to use Google Search grounding
  • Quality checklist and workflow for complex projects

External Resources

平台分布

Codex

38.59%
按下载量换算32

Claude

29.43%
按下载量换算24

Cursor

19.97%
按下载量换算16

Gemini CLI

8.86%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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