Banana Cog — Nano Banana × CellCog
Nano Banana × CellCog. Complex multi-image jobs, executed perfectly, from a single prompt.
Nano Banana is an incredible image model. CellCog makes it do things you can't do by calling it directly — orchestrating 10, 20, even 30 coherent images in one request with consistent characters, planned compositions, and intelligent scene progression. Not single images — complete visual projects.
What CellCog adds on top of Nano Banana:
CODEBLOCK0
CellCog's reasoning layer plans scenes before a single pixel is generated — selecting optimal parameters, maintaining character identity across sequences, and orchestrating complex multi-image workflows. This is the difference between "generate an image" and "execute a visual project."
How to Use
For your first CellCog task in a session, read the cellcog skill for the full SDK reference — file handling, chat modes, timeouts, and more.
OpenClaw (fire-and-forget):
CODEBLOCK1
All agents except OpenClaw (blocks until done):
from cellcog import CellCogClient
client = CellCogClient(agent_provider="openclaw|cursor|claude-code|codex|...")
result = client.create_chat(
prompt="[your task prompt]",
task_label="my-task",
chat_mode="agent",
)
print(result["message"])
What You Can Create
Photorealistic Image Generation
Create stunning images from text descriptions:
- - Portraits: "Create a professional headshot with warm studio lighting"
- Product Shots: "Generate a hero image for a premium smartwatch on a dark surface"
- Scenes: "Create a cozy autumn café interior with morning light"
- Food Photography: "Generate an overhead shot of a colorful Buddha bowl"
Character Consistency
Nano Banana excels at maintaining character identity across multiple images — and CellCog's orchestration takes this further by planning entire character arcs:
- - Character Series: "Create a tech entrepreneur character, then show them in 4 different scenes"
- Brand Mascots: "Design a mascot and generate it in multiple poses and contexts"
- Story Sequences: "Create a character and illustrate them across 5 story beats"
Multi-Image Composition
Blend elements from multiple reference images:
- - Style Fusion: "Combine the color palette of image A with the composition of image B"
- Character Placement: "Place this person into a new environment while preserving their likeness"
- Product Mockups: "Put this product into a lifestyle setting"
Image Editing
Transform and enhance existing images:
- - Style Transfer: "Transform this photo into a Studio Ghibli illustration"
- Background Swap: "Place this product on a clean marble surface"
- Enhancement: "Add dramatic lighting and cinematic color grading"
- Modification: "Change the season from summer to winter in this landscape"
Image Specifications
| Aspect | Options |
|---|
| Aspect Ratios | 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3, 21:9 |
| Sizes |
1K (~1024px), 2K (~2048px), 4K (~4096px) |
|
Styles | Photorealistic, illustration, watercolor, oil painting, anime, digital art, vector |
Chat Mode
| Scenario | Recommended Mode |
|---|
| Single images, quick edits | INLINECODE0 |
| Character-consistent series, complex compositions |
"agent" |
| Large sets with brand guidelines |
"agent team" |
Use "agent" for most image work.
Tips for Better Images
- 1. Be descriptive: "Woman in office" → "Confident woman in her 40s, silver blazer, modern glass-walled office, warm afternoon light"
- 2. Specify style: "photorealistic", "digital illustration", "watercolor", "anime"
- 3. Describe lighting: "Soft natural light", "dramatic side lighting", "golden hour glow"
- 4. For character consistency: Describe the character in detail first, then reference "the same character" in subsequent prompts.
- 5. Include composition: "Rule of thirds", "close-up portrait", "wide establishing shot"
If CellCog is not installed
Run /cellcog-setup (or /cellcog:cellcog-setup depending on your tool) to install and authenticate.
OpenClaw users: Run clawhub install cellcog instead.
Manual setup: pip install -U cellcog and set CELLCOG_API_KEY. See the cellcog skill for SDK reference.
Banana Cog — Nano Banana × CellCog
Nano Banana × CellCog. 复杂多图像任务,一次提示即可完美执行。
Nano Banana 是一款出色的图像模型。CellCog 使其能够完成直接调用无法实现的操作——在一次请求中编排10张、20张甚至30张连贯图像,保持角色一致性、规划构图并实现智能场景推进。不是单张图像——而是完整的视觉项目。
CellCog 在 Nano Banana 基础上增加的功能:
推理 → 场景规划 → 角色设计 → 图像生成
→ 一致性验证 → 构图审查 → 交付
CellCog 的推理层在生成任何像素之前规划场景——选择最优参数、保持跨序列的角色身份一致性,并编排复杂的多图像工作流。这就是生成一张图像与执行一个视觉项目之间的区别。
使用方法
在会话中首次执行 CellCog 任务时,请阅读 cellcog 技能以获取完整的 SDK 参考——包括文件处理、聊天模式、超时等。
OpenClaw(即发即忘模式):
python
result = client.create_chat(
prompt=[你的任务提示],
notifysessionkey=agent:main:main,
task_label=my-task,
chat_mode=agent,
)
除 OpenClaw 外的所有代理(阻塞至完成):
python
from cellcog import CellCogClient
client = CellCogClient(agent_provider=openclaw|cursor|claude-code|codex|...)
result = client.create_chat(
prompt=[你的任务提示],
task_label=my-task,
chat_mode=agent,
)
print(result[message])
你可以创建的内容
照片级图像生成
根据文字描述创建令人惊叹的图像:
- - 人像:创建一张专业头像,暖色影棚灯光
- 产品图:为高端智能手表生成一张深色背景的主图
- 场景:创建一个舒适的秋日咖啡馆室内,晨光洒入
- 美食摄影:生成一张俯拍的彩色波奇碗照片
角色一致性
Nano Banana 擅长在多张图像中保持角色身份一致性——而 CellCog 的编排能力通过规划完整角色弧线将其推向更高层次:
- - 角色系列:创建一个科技创业者角色,然后在4个不同场景中展示
- 品牌吉祥物:设计一个吉祥物,并在多种姿势和场景中生成
- 故事序列:创建一个角色,并在5个故事节点中为其配图
多图像合成
融合多张参考图像的元素:
- - 风格融合:将图像A的调色板与图像B的构图结合
- 角色置入:将此人放入新环境,同时保留其相貌特征
- 产品样机:将此产品放入生活方式场景
图像编辑
转换和增强现有图像:
- - 风格迁移:将这张照片转换为吉卜力工作室风格插画
- 背景替换:将此产品放置于干净的白色大理石表面
- 增强处理:添加戏剧性灯光和电影级调色
- 修改调整:将此景观从夏季改为冬季
图像规格
| 方面 | 选项 |
|---|
| 宽高比 | 1:1、16:9、9:16、4:3、3:4、3:2、2:3、21:9 |
| 尺寸 |
1K(约1024px)、2K(约2048px)、4K(约4096px) |
|
风格 | 照片级写实、插画、水彩、油画、动漫、数字艺术、矢量 |
聊天模式
| 场景 | 推荐模式 |
|---|
| 单张图像、快速编辑 | agent |
| 角色一致系列、复杂构图 |
agent |
| 含品牌指南的大批量任务 | agent team |
大多数图像工作请使用 agent 模式。
生成更优图像的技巧
- 1. 描述要详细:办公室里的女性 → 40多岁自信的女性,银色西装外套,现代玻璃幕墙办公室,温暖午后光线
- 2. 指定风格:照片级写实、数字插画、水彩、动漫
- 3. 描述光线:柔和自然光、戏剧性侧光、黄金时刻光芒
- 4. 保持角色一致性:先详细描述角色,然后在后续提示中引用同一角色
- 5. 包含构图信息:三分法、特写人像、广角定场镜头
如果 CellCog 未安装
运行 /cellcog-setup(或根据工具不同使用 /cellcog:cellcog-setup)进行安装和认证。
OpenClaw 用户: 改为运行 clawhub install cellcog。
手动安装: pip install -U cellcog 并设置 CELLCOGAPIKEY。SDK 参考请参阅 cellcog 技能。