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corespeed-nanobanana

该 Skill 通过 Corespeed AI Gateway 调用 Google Gemini 模型，用脚本实现文生图、图片编辑与多图合成，也可调用文本模型分析图片或生成文本。输出类型由文件扩展名决定，支持结构化 JSON 结果，需配置网关地址与令牌环境变量。

zypher-agent
zypher-agent
热度 57.65
最近更新 2026-05-11 17:34:02
分类：创作依赖：代码执行 / 读写文件 / 第三方 API / 内部调用大模型应用场景：图像生成

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add corespeed-nanobanana
Metadata
name
corespeed-nanobanana
description
Generate and edit images using Google Gemini models via Corespeed AI Gateway. Supports text-to-image generation, image editing, multi-image input, and text rendering in images using gemini-2.5-flash-image. Also supports text generation and image analysis with gemini-2.5-flash, gemini-2.5-pro, and gemini-2.5-flash-lite. Use when a user asks to create images, edit photos, analyze images, or generate text with Gemini models.
metadata
{"openclaw":{"emoji":"🍌","requires":{"bins":["uv"],"env":["CS_AI_GATEWAY_BASE_URL","CS_AI_GATEWAY_API_TOKEN"]},"install":[{"id":"uv-pip","kind":"shell","command":"pip install uv || pip3 install uv","bins":["uv"],"label":"Install uv via pip (https://github.com/astral-sh/uv)"}]}}

Corespeed NanoBanana — Gemini Image & Text Generation

Auth: Set CS_AI_GATEWAY_BASE_URL and CS_AI_GATEWAY_API_TOKEN environment variables.

Workflow

  1. Pick a model from the table below (default: gemini-2.5-flash-image for image generation)
  2. Run the script with your prompt

Usage

uv run {baseDir}/scripts/gemini.py --prompt "your prompt" -f output.ext [-i input.ext] [--model MODEL]
  • --prompt, -p — Text prompt (required)
  • --filename, -f — Output filename (required)
  • --input, -i — Input image file(s), repeat for multiple
  • --model, -m — Model name (default: gemini-2.5-flash-image)
  • --modalities — Response type: auto, image, text, image+text (default: auto)
  • --json — Output structured JSON (recommended for agent consumption)

Output format is determined by file extension: .png/.jpg → image generation, .txt/.md → text output.

Image Generation

# Text-to-image
uv run {baseDir}/scripts/gemini.py -p "a watercolor fox in autumn forest" -f fox.png

# Image editing
uv run {baseDir}/scripts/gemini.py -p "Remove background, add beach sunset" -f edited.png -i photo.jpg

# Multi-image compositing
uv run {baseDir}/scripts/gemini.py -p "Blend these two scenes together" -f blend.png -i scene1.png -i scene2.png

Image Analysis

# Describe an image
uv run {baseDir}/scripts/gemini.py -p "Describe this image" -f desc.txt -i photo.jpg --model gemini-2.5-flash

# Compare images
uv run {baseDir}/scripts/gemini.py -p "What are the differences?" -f diff.txt -i before.jpg -i after.jpg --model gemini-2.5-flash

Text Generation

# Use the most capable model for complex tasks
uv run {baseDir}/scripts/gemini.py -p "Write a haiku about coding" -f haiku.txt --model gemini-2.5-pro

Models

Model Type Best For
gemini-2.5-flash-image Image + Text Image generation & editing (default)
gemini-2.5-flash Text Fast analysis, vision, general tasks
gemini-2.5-pro Text Complex reasoning, highest quality
gemini-2.5-flash-lite Text Fastest, simple tasks

Notes

  • No manual Python setup required. The script uses PEP 723 inline metadata. uv run automatically creates an isolated virtual environment and installs the google-genai dependency on first run.
  • Image output is returned inline as base64 from the Gemini API — no separate download step.
  • Use timestamps in filenames: yyyy-mm-dd-hh-mm-ss-name.ext.
  • Script prints MEDIA: line for OpenClaw to auto-attach generated images.
  • Do not read generated media back; report the saved path only.
  • Only gemini-2.5-flash-image can generate images. Other models are text-only.
  • Use --json for structured output: {"ok": true, "files": [...], "text": "...", "model": "...", "tokens": {...}}

Support

Built by Corespeed. If you need help or run into issues: