Add gemini-imagegen skill and fix component counts
- Add gemini-imagegen skill for image generation with Gemini API - Fix component counts: 17 agents (was 15), 6 commands, 1 skill - Add comprehensive README documenting all components - Add CHANGELOG tracking version history - Bump version to 1.1.0 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
Kieran Klaassen
@@ -1,7 +1,7 @@
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{
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"name": "compounding-engineering",
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"version": "1.0.0",
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"description": "AI-powered development tools that get smarter with every use. Make each unit of engineering work easier than the last. Includes 15 specialized agents and 6 commands.",
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"version": "1.1.0",
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"description": "AI-powered development tools that get smarter with every use. Make each unit of engineering work easier than the last. Includes 17 specialized agents, 6 commands, and 1 skill.",
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"author": {
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"name": "Kieran Klaassen",
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"email": "kieran@every.to",
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@@ -16,6 +16,7 @@
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"workflow-automation",
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"code-review",
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"quality",
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"knowledge-management"
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"knowledge-management",
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"image-generation"
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]
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}
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25
plugins/compounding-engineering/CHANGELOG.md
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25
plugins/compounding-engineering/CHANGELOG.md
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# Changelog
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## [1.1.0] - 2024-11-22
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### Added
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- **gemini-imagegen skill** - Generate and edit images using Google's Gemini API
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- Text-to-image generation
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- Image editing and manipulation
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- Multi-turn refinement via chat
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- Multiple reference image composition (up to 14 images)
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- Supports both `gemini-2.5-flash-image` and `gemini-3-pro-image-preview` models
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### Fixed
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- Corrected component counts in documentation (17 agents, not 15)
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### Documentation
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- Added comprehensive README with all components listed
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- Added this changelog
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## [1.0.0] - 2024-10-09
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### Added
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- Initial release with 17 specialized agents
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- 6 slash commands for common workflows
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- MIT license
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76
plugins/compounding-engineering/README.md
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76
plugins/compounding-engineering/README.md
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@@ -0,0 +1,76 @@
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# Compounding Engineering Plugin
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AI-powered development tools that get smarter with every use. Make each unit of engineering work easier than the last.
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## Components
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- **17 Agents** - Specialized AI agents for code review, research, and analysis
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- **6 Commands** - Slash commands for common workflows
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- **1 Skill** - Image generation with Gemini API
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## Agents
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### Code Review
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- **kieran-rails-reviewer** - Rails code review with strict conventions
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- **kieran-python-reviewer** - Python code review with strict conventions
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- **kieran-typescript-reviewer** - TypeScript code review with strict conventions
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- **dhh-rails-reviewer** - Rails review from DHH's perspective
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- **code-simplicity-reviewer** - Final pass for simplicity and minimalism
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### Analysis & Research
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- **framework-docs-researcher** - Research framework documentation and best practices
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- **best-practices-researcher** - Gather external best practices and examples
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- **pattern-recognition-specialist** - Analyze code for patterns and anti-patterns
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- **repo-research-analyst** - Research repository structure and conventions
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- **git-history-analyzer** - Analyze git history and code evolution
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### Architecture & Security
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- **architecture-strategist** - Analyze architectural decisions and compliance
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- **security-sentinel** - Security audits and vulnerability assessments
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- **performance-oracle** - Performance analysis and optimization
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- **data-integrity-guardian** - Database migrations and data integrity
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### Workflow
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- **every-style-editor** - Edit content to conform to Every's style guide
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- **pr-comment-resolver** - Address PR comments and implement fixes
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- **feedback-codifier** - Codify feedback patterns into reviewer agents
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## Commands
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- **/review** - Run a comprehensive code review
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- **/plan** - Create an implementation plan
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- **/work** - Execute work items systematically
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- **/triage** - Triage issues and prioritize work
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- **/resolve_todo_parallel** - Resolve todos in parallel
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- **/generate_command** - Generate new slash commands
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## Skills
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### gemini-imagegen
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Generate and edit images using Google's Gemini API.
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**Features:**
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- Text-to-image generation
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- Image editing and manipulation
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- Multi-turn refinement
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- Multiple reference image composition
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**Requirements:**
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- `GEMINI_API_KEY` environment variable
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- Python packages: `google-genai`, `pillow`
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**Usage:**
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```bash
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python scripts/generate_image.py "A cat wearing a wizard hat" output.png
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python scripts/edit_image.py input.png "Add a rainbow" output.png
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```
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## Installation
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```bash
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claude /plugin install compounding-engineering
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```
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## License
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MIT
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176
plugins/compounding-engineering/skills/gemini-imagegen/SKILL.md
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176
plugins/compounding-engineering/skills/gemini-imagegen/SKILL.md
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---
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name: gemini-imagegen
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description: Generate and edit images using the Gemini API (Nano Banana). Use this skill when creating images from text prompts, editing existing images, applying style transfers, generating logos with text, creating stickers, product mockups, or any image generation/manipulation task. Supports text-to-image, image editing, multi-turn refinement, and composition from multiple reference images.
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---
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# Gemini Image Generation (Nano Banana)
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Generate and edit images using Google's Gemini API. The environment variable `GEMINI_API_KEY` must be set.
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## Available Models
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| Model | Alias | Resolution | Best For |
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|-------|-------|------------|----------|
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| `gemini-2.5-flash-image` | Nano Banana | 1024px | Speed, high-volume tasks |
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| `gemini-3-pro-image-preview` | Nano Banana Pro | Up to 4K | Professional assets, complex instructions, text rendering |
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## Quick Start Scripts
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### Text-to-Image
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```bash
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python scripts/generate_image.py "A cat wearing a wizard hat" output.png
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```
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### Edit Existing Image
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```bash
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python scripts/edit_image.py input.png "Add a rainbow in the background" output.png
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```
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### Multi-Turn Chat (Iterative Refinement)
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```bash
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python scripts/multi_turn_chat.py
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```
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## Core API Pattern
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All image generation uses the `generateContent` endpoint with `responseModalities: ["TEXT", "IMAGE"]`:
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```python
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import os
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import base64
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from google import genai
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client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
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response = client.models.generate_content(
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model="gemini-2.5-flash-image",
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contents=["Your prompt here"],
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)
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for part in response.parts:
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if part.text:
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print(part.text)
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elif part.inline_data:
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image = part.as_image()
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image.save("output.png")
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```
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## Image Configuration Options
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Control output with `image_config`:
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```python
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from google.genai import types
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response = client.models.generate_content(
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model="gemini-3-pro-image-preview",
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contents=[prompt],
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config=types.GenerateContentConfig(
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response_modalities=['TEXT', 'IMAGE'],
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image_config=types.ImageConfig(
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aspect_ratio="16:9", # 1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9
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image_size="2K" # 1K, 2K, 4K (Pro only for 4K)
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),
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)
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)
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```
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## Editing Images
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Pass existing images with text prompts:
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```python
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from PIL import Image
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img = Image.open("input.png")
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response = client.models.generate_content(
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model="gemini-2.5-flash-image",
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contents=["Add a sunset to this scene", img],
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)
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```
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## Multi-Turn Refinement
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Use chat for iterative editing:
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```python
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from google.genai import types
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chat = client.chats.create(
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model="gemini-2.5-flash-image",
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config=types.GenerateContentConfig(response_modalities=['TEXT', 'IMAGE'])
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)
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response = chat.send_message("Create a logo for 'Acme Corp'")
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# Save first image...
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response = chat.send_message("Make the text bolder and add a blue gradient")
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# Save refined image...
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```
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## Prompting Best Practices
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### Photorealistic Scenes
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Include camera details: lens type, lighting, angle, mood.
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> "A photorealistic close-up portrait, 85mm lens, soft golden hour light, shallow depth of field"
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### Stylized Art
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Specify style explicitly:
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> "A kawaii-style sticker of a happy red panda, bold outlines, cel-shading, white background"
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### Text in Images
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Be explicit about font style and placement. Use `gemini-3-pro-image-preview` for best results:
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> "Create a logo with text 'Daily Grind' in clean sans-serif, black and white, coffee bean motif"
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### Product Mockups
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Describe lighting setup and surface:
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> "Studio-lit product photo on polished concrete, three-point softbox setup, 45-degree angle"
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## Advanced Features (Pro Model Only)
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### Google Search Grounding
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Generate images based on real-time data:
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```python
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response = client.models.generate_content(
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model="gemini-3-pro-image-preview",
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contents=["Visualize today's weather in Tokyo as an infographic"],
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config=types.GenerateContentConfig(
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response_modalities=['TEXT', 'IMAGE'],
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tools=[{"google_search": {}}]
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)
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)
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```
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### Multiple Reference Images (Up to 14)
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Combine elements from multiple sources:
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```python
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response = client.models.generate_content(
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model="gemini-3-pro-image-preview",
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contents=[
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"Create a group photo of these people in an office",
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Image.open("person1.png"),
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Image.open("person2.png"),
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Image.open("person3.png"),
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],
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)
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```
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## REST API (curl)
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```bash
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curl -s -X POST \
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"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image:generateContent" \
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-H "x-goog-api-key: $GEMINI_API_KEY" \
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-H "Content-Type: application/json" \
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-d '{
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"contents": [{"parts": [{"text": "A serene mountain landscape"}]}]
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}' | jq -r '.candidates[0].content.parts[] | select(.inlineData) | .inlineData.data' | base64 --decode > output.png
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```
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## Notes
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- All generated images include SynthID watermarks
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- Image-only mode (`responseModalities: ["IMAGE"]`) won't work with Google Search grounding
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- For editing, describe changes conversationally—the model understands semantic masking
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157
plugins/compounding-engineering/skills/gemini-imagegen/scripts/compose_images.py
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157
plugins/compounding-engineering/skills/gemini-imagegen/scripts/compose_images.py
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#!/usr/bin/env python3
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"""
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Compose multiple images into a new image using Gemini API.
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Usage:
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python compose_images.py "instruction" output.png image1.png [image2.png ...]
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Examples:
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python compose_images.py "Create a group photo of these people" group.png person1.png person2.png
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python compose_images.py "Put the cat from the first image on the couch from the second" result.png cat.png couch.png
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python compose_images.py "Apply the art style from the first image to the scene in the second" styled.png style.png photo.png
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Note: Supports up to 14 reference images (Gemini 3 Pro only).
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Environment:
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GEMINI_API_KEY - Required API key
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"""
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import argparse
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import os
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import sys
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from PIL import Image
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from google import genai
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from google.genai import types
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def compose_images(
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instruction: str,
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output_path: str,
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image_paths: list[str],
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model: str = "gemini-3-pro-image-preview",
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aspect_ratio: str | None = None,
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image_size: str | None = None,
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) -> str | None:
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"""Compose multiple images based on instructions.
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Args:
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instruction: Text description of how to combine images
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output_path: Path to save the result
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image_paths: List of input image paths (up to 14)
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model: Gemini model to use (pro recommended)
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aspect_ratio: Output aspect ratio
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image_size: Output resolution
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Returns:
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Any text response from the model, or None
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"""
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api_key = os.environ.get("GEMINI_API_KEY")
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if not api_key:
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raise EnvironmentError("GEMINI_API_KEY environment variable not set")
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if len(image_paths) > 14:
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raise ValueError("Maximum 14 reference images supported")
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if len(image_paths) < 1:
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raise ValueError("At least one image is required")
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# Verify all images exist
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for path in image_paths:
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if not os.path.exists(path):
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raise FileNotFoundError(f"Image not found: {path}")
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client = genai.Client(api_key=api_key)
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# Load images
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images = [Image.open(path) for path in image_paths]
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# Build contents: instruction first, then images
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contents = [instruction] + images
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# Build config
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config_kwargs = {"response_modalities": ["TEXT", "IMAGE"]}
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image_config_kwargs = {}
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if aspect_ratio:
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image_config_kwargs["aspect_ratio"] = aspect_ratio
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if image_size:
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image_config_kwargs["image_size"] = image_size
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if image_config_kwargs:
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config_kwargs["image_config"] = types.ImageConfig(**image_config_kwargs)
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config = types.GenerateContentConfig(**config_kwargs)
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response = client.models.generate_content(
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model=model,
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contents=contents,
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config=config,
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)
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text_response = None
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image_saved = False
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for part in response.parts:
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if part.text is not None:
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text_response = part.text
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elif part.inline_data is not None:
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image = part.as_image()
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image.save(output_path)
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image_saved = True
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if not image_saved:
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raise RuntimeError("No image was generated.")
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return text_response
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def main():
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parser = argparse.ArgumentParser(
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description="Compose multiple images using Gemini API",
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formatter_class=argparse.RawDescriptionHelpFormatter,
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epilog=__doc__
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)
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parser.add_argument("instruction", help="Composition instruction")
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parser.add_argument("output", help="Output file path")
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parser.add_argument("images", nargs="+", help="Input images (up to 14)")
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parser.add_argument(
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"--model", "-m",
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default="gemini-3-pro-image-preview",
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choices=["gemini-2.5-flash-image", "gemini-3-pro-image-preview"],
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help="Model to use (pro recommended for composition)"
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)
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parser.add_argument(
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"--aspect", "-a",
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choices=["1:1", "2:3", "3:2", "3:4", "4:3", "4:5", "5:4", "9:16", "16:9", "21:9"],
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help="Output aspect ratio"
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)
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parser.add_argument(
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"--size", "-s",
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choices=["1K", "2K", "4K"],
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help="Output resolution"
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)
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args = parser.parse_args()
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||||
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try:
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text = compose_images(
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instruction=args.instruction,
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output_path=args.output,
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image_paths=args.images,
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||||
model=args.model,
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aspect_ratio=args.aspect,
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||||
image_size=args.size,
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)
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print(f"Composed image saved to: {args.output}")
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if text:
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print(f"Model response: {text}")
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except Exception as e:
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print(f"Error: {e}", file=sys.stderr)
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sys.exit(1)
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||||
if __name__ == "__main__":
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main()
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144
plugins/compounding-engineering/skills/gemini-imagegen/scripts/edit_image.py
Executable file
144
plugins/compounding-engineering/skills/gemini-imagegen/scripts/edit_image.py
Executable file
@@ -0,0 +1,144 @@
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#!/usr/bin/env python3
|
||||
"""
|
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Edit existing images using Gemini API.
|
||||
|
||||
Usage:
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python edit_image.py input.png "edit instruction" output.png [options]
|
||||
|
||||
Examples:
|
||||
python edit_image.py photo.png "Add a rainbow in the sky" edited.png
|
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python edit_image.py room.jpg "Change the sofa to red leather" room_edited.jpg
|
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python edit_image.py portrait.png "Make it look like a Van Gogh painting" artistic.png --model gemini-3-pro-image-preview
|
||||
|
||||
Environment:
|
||||
GEMINI_API_KEY - Required API key
|
||||
"""
|
||||
|
||||
import argparse
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||||
import os
|
||||
import sys
|
||||
|
||||
from PIL import Image
|
||||
from google import genai
|
||||
from google.genai import types
|
||||
|
||||
|
||||
def edit_image(
|
||||
input_path: str,
|
||||
instruction: str,
|
||||
output_path: str,
|
||||
model: str = "gemini-2.5-flash-image",
|
||||
aspect_ratio: str | None = None,
|
||||
image_size: str | None = None,
|
||||
) -> str | None:
|
||||
"""Edit an existing image based on text instructions.
|
||||
|
||||
Args:
|
||||
input_path: Path to the input image
|
||||
instruction: Text description of edits to make
|
||||
output_path: Path to save the edited image
|
||||
model: Gemini model to use
|
||||
aspect_ratio: Output aspect ratio
|
||||
image_size: Output resolution
|
||||
|
||||
Returns:
|
||||
Any text response from the model, or None
|
||||
"""
|
||||
api_key = os.environ.get("GEMINI_API_KEY")
|
||||
if not api_key:
|
||||
raise EnvironmentError("GEMINI_API_KEY environment variable not set")
|
||||
|
||||
if not os.path.exists(input_path):
|
||||
raise FileNotFoundError(f"Input image not found: {input_path}")
|
||||
|
||||
client = genai.Client(api_key=api_key)
|
||||
|
||||
# Load input image
|
||||
input_image = Image.open(input_path)
|
||||
|
||||
# Build config
|
||||
config_kwargs = {"response_modalities": ["TEXT", "IMAGE"]}
|
||||
|
||||
image_config_kwargs = {}
|
||||
if aspect_ratio:
|
||||
image_config_kwargs["aspect_ratio"] = aspect_ratio
|
||||
if image_size:
|
||||
image_config_kwargs["image_size"] = image_size
|
||||
|
||||
if image_config_kwargs:
|
||||
config_kwargs["image_config"] = types.ImageConfig(**image_config_kwargs)
|
||||
|
||||
config = types.GenerateContentConfig(**config_kwargs)
|
||||
|
||||
response = client.models.generate_content(
|
||||
model=model,
|
||||
contents=[instruction, input_image],
|
||||
config=config,
|
||||
)
|
||||
|
||||
text_response = None
|
||||
image_saved = False
|
||||
|
||||
for part in response.parts:
|
||||
if part.text is not None:
|
||||
text_response = part.text
|
||||
elif part.inline_data is not None:
|
||||
image = part.as_image()
|
||||
image.save(output_path)
|
||||
image_saved = True
|
||||
|
||||
if not image_saved:
|
||||
raise RuntimeError("No image was generated. Check your instruction and try again.")
|
||||
|
||||
return text_response
|
||||
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser(
|
||||
description="Edit images using Gemini API",
|
||||
formatter_class=argparse.RawDescriptionHelpFormatter,
|
||||
epilog=__doc__
|
||||
)
|
||||
parser.add_argument("input", help="Input image path")
|
||||
parser.add_argument("instruction", help="Edit instruction")
|
||||
parser.add_argument("output", help="Output file path")
|
||||
parser.add_argument(
|
||||
"--model", "-m",
|
||||
default="gemini-2.5-flash-image",
|
||||
choices=["gemini-2.5-flash-image", "gemini-3-pro-image-preview"],
|
||||
help="Model to use (default: gemini-2.5-flash-image)"
|
||||
)
|
||||
parser.add_argument(
|
||||
"--aspect", "-a",
|
||||
choices=["1:1", "2:3", "3:2", "3:4", "4:3", "4:5", "5:4", "9:16", "16:9", "21:9"],
|
||||
help="Output aspect ratio"
|
||||
)
|
||||
parser.add_argument(
|
||||
"--size", "-s",
|
||||
choices=["1K", "2K", "4K"],
|
||||
help="Output resolution"
|
||||
)
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
try:
|
||||
text = edit_image(
|
||||
input_path=args.input,
|
||||
instruction=args.instruction,
|
||||
output_path=args.output,
|
||||
model=args.model,
|
||||
aspect_ratio=args.aspect,
|
||||
image_size=args.size,
|
||||
)
|
||||
|
||||
print(f"Edited image saved to: {args.output}")
|
||||
if text:
|
||||
print(f"Model response: {text}")
|
||||
|
||||
except Exception as e:
|
||||
print(f"Error: {e}", file=sys.stderr)
|
||||
sys.exit(1)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
263
plugins/compounding-engineering/skills/gemini-imagegen/scripts/gemini_images.py
Executable file
263
plugins/compounding-engineering/skills/gemini-imagegen/scripts/gemini_images.py
Executable file
@@ -0,0 +1,263 @@
|
||||
"""
|
||||
Gemini Image Generation Library
|
||||
|
||||
A simple Python library for generating and editing images with the Gemini API.
|
||||
|
||||
Usage:
|
||||
from gemini_images import GeminiImageGenerator
|
||||
|
||||
gen = GeminiImageGenerator()
|
||||
gen.generate("A sunset over mountains", "sunset.png")
|
||||
gen.edit("input.png", "Add clouds", "output.png")
|
||||
|
||||
Environment:
|
||||
GEMINI_API_KEY - Required API key
|
||||
"""
|
||||
|
||||
import os
|
||||
from pathlib import Path
|
||||
from typing import Literal
|
||||
|
||||
from PIL import Image
|
||||
from google import genai
|
||||
from google.genai import types
|
||||
|
||||
|
||||
AspectRatio = Literal["1:1", "2:3", "3:2", "3:4", "4:3", "4:5", "5:4", "9:16", "16:9", "21:9"]
|
||||
ImageSize = Literal["1K", "2K", "4K"]
|
||||
Model = Literal["gemini-2.5-flash-image", "gemini-3-pro-image-preview"]
|
||||
|
||||
|
||||
class GeminiImageGenerator:
|
||||
"""High-level interface for Gemini image generation."""
|
||||
|
||||
FLASH = "gemini-2.5-flash-image"
|
||||
PRO = "gemini-3-pro-image-preview"
|
||||
|
||||
def __init__(self, api_key: str | None = None, model: Model = FLASH):
|
||||
"""Initialize the generator.
|
||||
|
||||
Args:
|
||||
api_key: Gemini API key (defaults to GEMINI_API_KEY env var)
|
||||
model: Default model to use
|
||||
"""
|
||||
self.api_key = api_key or os.environ.get("GEMINI_API_KEY")
|
||||
if not self.api_key:
|
||||
raise EnvironmentError("GEMINI_API_KEY not set")
|
||||
|
||||
self.client = genai.Client(api_key=self.api_key)
|
||||
self.model = model
|
||||
|
||||
def _build_config(
|
||||
self,
|
||||
aspect_ratio: AspectRatio | None = None,
|
||||
image_size: ImageSize | None = None,
|
||||
google_search: bool = False,
|
||||
) -> types.GenerateContentConfig:
|
||||
"""Build generation config."""
|
||||
kwargs = {"response_modalities": ["TEXT", "IMAGE"]}
|
||||
|
||||
img_config = {}
|
||||
if aspect_ratio:
|
||||
img_config["aspect_ratio"] = aspect_ratio
|
||||
if image_size:
|
||||
img_config["image_size"] = image_size
|
||||
|
||||
if img_config:
|
||||
kwargs["image_config"] = types.ImageConfig(**img_config)
|
||||
|
||||
if google_search:
|
||||
kwargs["tools"] = [{"google_search": {}}]
|
||||
|
||||
return types.GenerateContentConfig(**kwargs)
|
||||
|
||||
def generate(
|
||||
self,
|
||||
prompt: str,
|
||||
output: str | Path,
|
||||
*,
|
||||
model: Model | None = None,
|
||||
aspect_ratio: AspectRatio | None = None,
|
||||
image_size: ImageSize | None = None,
|
||||
google_search: bool = False,
|
||||
) -> tuple[Path, str | None]:
|
||||
"""Generate an image from a text prompt.
|
||||
|
||||
Args:
|
||||
prompt: Text description
|
||||
output: Output file path
|
||||
model: Override default model
|
||||
aspect_ratio: Output aspect ratio
|
||||
image_size: Output resolution
|
||||
google_search: Enable Google Search grounding (Pro only)
|
||||
|
||||
Returns:
|
||||
Tuple of (output path, optional text response)
|
||||
"""
|
||||
output = Path(output)
|
||||
config = self._build_config(aspect_ratio, image_size, google_search)
|
||||
|
||||
response = self.client.models.generate_content(
|
||||
model=model or self.model,
|
||||
contents=[prompt],
|
||||
config=config,
|
||||
)
|
||||
|
||||
text = None
|
||||
for part in response.parts:
|
||||
if part.text:
|
||||
text = part.text
|
||||
elif part.inline_data:
|
||||
part.as_image().save(output)
|
||||
|
||||
return output, text
|
||||
|
||||
def edit(
|
||||
self,
|
||||
input_image: str | Path | Image.Image,
|
||||
instruction: str,
|
||||
output: str | Path,
|
||||
*,
|
||||
model: Model | None = None,
|
||||
aspect_ratio: AspectRatio | None = None,
|
||||
image_size: ImageSize | None = None,
|
||||
) -> tuple[Path, str | None]:
|
||||
"""Edit an existing image.
|
||||
|
||||
Args:
|
||||
input_image: Input image (path or PIL Image)
|
||||
instruction: Edit instruction
|
||||
output: Output file path
|
||||
model: Override default model
|
||||
aspect_ratio: Output aspect ratio
|
||||
image_size: Output resolution
|
||||
|
||||
Returns:
|
||||
Tuple of (output path, optional text response)
|
||||
"""
|
||||
output = Path(output)
|
||||
|
||||
if isinstance(input_image, (str, Path)):
|
||||
input_image = Image.open(input_image)
|
||||
|
||||
config = self._build_config(aspect_ratio, image_size)
|
||||
|
||||
response = self.client.models.generate_content(
|
||||
model=model or self.model,
|
||||
contents=[instruction, input_image],
|
||||
config=config,
|
||||
)
|
||||
|
||||
text = None
|
||||
for part in response.parts:
|
||||
if part.text:
|
||||
text = part.text
|
||||
elif part.inline_data:
|
||||
part.as_image().save(output)
|
||||
|
||||
return output, text
|
||||
|
||||
def compose(
|
||||
self,
|
||||
instruction: str,
|
||||
images: list[str | Path | Image.Image],
|
||||
output: str | Path,
|
||||
*,
|
||||
model: Model | None = None,
|
||||
aspect_ratio: AspectRatio | None = None,
|
||||
image_size: ImageSize | None = None,
|
||||
) -> tuple[Path, str | None]:
|
||||
"""Compose multiple images into one.
|
||||
|
||||
Args:
|
||||
instruction: Composition instruction
|
||||
images: List of input images (up to 14)
|
||||
output: Output file path
|
||||
model: Override default model (Pro recommended)
|
||||
aspect_ratio: Output aspect ratio
|
||||
image_size: Output resolution
|
||||
|
||||
Returns:
|
||||
Tuple of (output path, optional text response)
|
||||
"""
|
||||
output = Path(output)
|
||||
|
||||
# Load images
|
||||
loaded = []
|
||||
for img in images:
|
||||
if isinstance(img, (str, Path)):
|
||||
loaded.append(Image.open(img))
|
||||
else:
|
||||
loaded.append(img)
|
||||
|
||||
config = self._build_config(aspect_ratio, image_size)
|
||||
contents = [instruction] + loaded
|
||||
|
||||
response = self.client.models.generate_content(
|
||||
model=model or self.PRO, # Pro recommended for composition
|
||||
contents=contents,
|
||||
config=config,
|
||||
)
|
||||
|
||||
text = None
|
||||
for part in response.parts:
|
||||
if part.text:
|
||||
text = part.text
|
||||
elif part.inline_data:
|
||||
part.as_image().save(output)
|
||||
|
||||
return output, text
|
||||
|
||||
def chat(self) -> "ImageChat":
|
||||
"""Start an interactive chat session for iterative refinement."""
|
||||
return ImageChat(self.client, self.model)
|
||||
|
||||
|
||||
class ImageChat:
|
||||
"""Multi-turn chat session for iterative image generation."""
|
||||
|
||||
def __init__(self, client: genai.Client, model: Model):
|
||||
self.client = client
|
||||
self.model = model
|
||||
self._chat = client.chats.create(
|
||||
model=model,
|
||||
config=types.GenerateContentConfig(response_modalities=["TEXT", "IMAGE"]),
|
||||
)
|
||||
self.current_image: Image.Image | None = None
|
||||
|
||||
def send(
|
||||
self,
|
||||
message: str,
|
||||
image: Image.Image | str | Path | None = None,
|
||||
) -> tuple[Image.Image | None, str | None]:
|
||||
"""Send a message and optionally an image.
|
||||
|
||||
Returns:
|
||||
Tuple of (generated image or None, text response or None)
|
||||
"""
|
||||
contents = [message]
|
||||
if image:
|
||||
if isinstance(image, (str, Path)):
|
||||
image = Image.open(image)
|
||||
contents.append(image)
|
||||
|
||||
response = self._chat.send_message(contents)
|
||||
|
||||
text = None
|
||||
img = None
|
||||
for part in response.parts:
|
||||
if part.text:
|
||||
text = part.text
|
||||
elif part.inline_data:
|
||||
img = part.as_image()
|
||||
self.current_image = img
|
||||
|
||||
return img, text
|
||||
|
||||
def reset(self):
|
||||
"""Reset the chat session."""
|
||||
self._chat = self.client.chats.create(
|
||||
model=self.model,
|
||||
config=types.GenerateContentConfig(response_modalities=["TEXT", "IMAGE"]),
|
||||
)
|
||||
self.current_image = None
|
||||
133
plugins/compounding-engineering/skills/gemini-imagegen/scripts/generate_image.py
Executable file
133
plugins/compounding-engineering/skills/gemini-imagegen/scripts/generate_image.py
Executable file
@@ -0,0 +1,133 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Generate images from text prompts using Gemini API.
|
||||
|
||||
Usage:
|
||||
python generate_image.py "prompt" output.png [--model MODEL] [--aspect RATIO] [--size SIZE]
|
||||
|
||||
Examples:
|
||||
python generate_image.py "A cat in space" cat.png
|
||||
python generate_image.py "A logo for Acme Corp" logo.png --model gemini-3-pro-image-preview --aspect 1:1
|
||||
python generate_image.py "Epic landscape" landscape.png --aspect 16:9 --size 2K
|
||||
|
||||
Environment:
|
||||
GEMINI_API_KEY - Required API key
|
||||
"""
|
||||
|
||||
import argparse
|
||||
import os
|
||||
import sys
|
||||
|
||||
from google import genai
|
||||
from google.genai import types
|
||||
|
||||
|
||||
def generate_image(
|
||||
prompt: str,
|
||||
output_path: str,
|
||||
model: str = "gemini-2.5-flash-image",
|
||||
aspect_ratio: str | None = None,
|
||||
image_size: str | None = None,
|
||||
) -> str | None:
|
||||
"""Generate an image from a text prompt.
|
||||
|
||||
Args:
|
||||
prompt: Text description of the image to generate
|
||||
output_path: Path to save the generated image
|
||||
model: Gemini model to use
|
||||
aspect_ratio: Aspect ratio (1:1, 16:9, 9:16, etc.)
|
||||
image_size: Resolution (1K, 2K, 4K - 4K only for pro model)
|
||||
|
||||
Returns:
|
||||
Any text response from the model, or None
|
||||
"""
|
||||
api_key = os.environ.get("GEMINI_API_KEY")
|
||||
if not api_key:
|
||||
raise EnvironmentError("GEMINI_API_KEY environment variable not set")
|
||||
|
||||
client = genai.Client(api_key=api_key)
|
||||
|
||||
# Build config
|
||||
config_kwargs = {"response_modalities": ["TEXT", "IMAGE"]}
|
||||
|
||||
image_config_kwargs = {}
|
||||
if aspect_ratio:
|
||||
image_config_kwargs["aspect_ratio"] = aspect_ratio
|
||||
if image_size:
|
||||
image_config_kwargs["image_size"] = image_size
|
||||
|
||||
if image_config_kwargs:
|
||||
config_kwargs["image_config"] = types.ImageConfig(**image_config_kwargs)
|
||||
|
||||
config = types.GenerateContentConfig(**config_kwargs)
|
||||
|
||||
response = client.models.generate_content(
|
||||
model=model,
|
||||
contents=[prompt],
|
||||
config=config,
|
||||
)
|
||||
|
||||
text_response = None
|
||||
image_saved = False
|
||||
|
||||
for part in response.parts:
|
||||
if part.text is not None:
|
||||
text_response = part.text
|
||||
elif part.inline_data is not None:
|
||||
image = part.as_image()
|
||||
image.save(output_path)
|
||||
image_saved = True
|
||||
|
||||
if not image_saved:
|
||||
raise RuntimeError("No image was generated. Check your prompt and try again.")
|
||||
|
||||
return text_response
|
||||
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser(
|
||||
description="Generate images from text prompts using Gemini API",
|
||||
formatter_class=argparse.RawDescriptionHelpFormatter,
|
||||
epilog=__doc__
|
||||
)
|
||||
parser.add_argument("prompt", help="Text prompt describing the image")
|
||||
parser.add_argument("output", help="Output file path (e.g., output.png)")
|
||||
parser.add_argument(
|
||||
"--model", "-m",
|
||||
default="gemini-2.5-flash-image",
|
||||
choices=["gemini-2.5-flash-image", "gemini-3-pro-image-preview"],
|
||||
help="Model to use (default: gemini-2.5-flash-image)"
|
||||
)
|
||||
parser.add_argument(
|
||||
"--aspect", "-a",
|
||||
choices=["1:1", "2:3", "3:2", "3:4", "4:3", "4:5", "5:4", "9:16", "16:9", "21:9"],
|
||||
help="Aspect ratio"
|
||||
)
|
||||
parser.add_argument(
|
||||
"--size", "-s",
|
||||
choices=["1K", "2K", "4K"],
|
||||
help="Image resolution (4K only available with pro model)"
|
||||
)
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
try:
|
||||
text = generate_image(
|
||||
prompt=args.prompt,
|
||||
output_path=args.output,
|
||||
model=args.model,
|
||||
aspect_ratio=args.aspect,
|
||||
image_size=args.size,
|
||||
)
|
||||
|
||||
print(f"Image saved to: {args.output}")
|
||||
if text:
|
||||
print(f"Model response: {text}")
|
||||
|
||||
except Exception as e:
|
||||
print(f"Error: {e}", file=sys.stderr)
|
||||
sys.exit(1)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,216 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Interactive multi-turn image generation and refinement using Gemini API.
|
||||
|
||||
Usage:
|
||||
python multi_turn_chat.py [--model MODEL] [--output-dir DIR]
|
||||
|
||||
This starts an interactive session where you can:
|
||||
- Generate images from prompts
|
||||
- Iteratively refine images through conversation
|
||||
- Load existing images for editing
|
||||
- Save images at any point
|
||||
|
||||
Commands:
|
||||
/save [filename] - Save current image
|
||||
/load <path> - Load an image into the conversation
|
||||
/clear - Start fresh conversation
|
||||
/quit - Exit
|
||||
|
||||
Environment:
|
||||
GEMINI_API_KEY - Required API key
|
||||
"""
|
||||
|
||||
import argparse
|
||||
import os
|
||||
import sys
|
||||
from datetime import datetime
|
||||
from pathlib import Path
|
||||
|
||||
from PIL import Image
|
||||
from google import genai
|
||||
from google.genai import types
|
||||
|
||||
|
||||
class ImageChat:
|
||||
"""Interactive chat session for image generation and refinement."""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
model: str = "gemini-2.5-flash-image",
|
||||
output_dir: str = ".",
|
||||
):
|
||||
api_key = os.environ.get("GEMINI_API_KEY")
|
||||
if not api_key:
|
||||
raise EnvironmentError("GEMINI_API_KEY environment variable not set")
|
||||
|
||||
self.client = genai.Client(api_key=api_key)
|
||||
self.model = model
|
||||
self.output_dir = Path(output_dir)
|
||||
self.output_dir.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
self.chat = None
|
||||
self.current_image = None
|
||||
self.image_count = 0
|
||||
|
||||
self._init_chat()
|
||||
|
||||
def _init_chat(self):
|
||||
"""Initialize or reset the chat session."""
|
||||
config = types.GenerateContentConfig(
|
||||
response_modalities=["TEXT", "IMAGE"]
|
||||
)
|
||||
self.chat = self.client.chats.create(
|
||||
model=self.model,
|
||||
config=config,
|
||||
)
|
||||
self.current_image = None
|
||||
|
||||
def send_message(self, message: str, image: Image.Image | None = None) -> tuple[str | None, Image.Image | None]:
|
||||
"""Send a message and optionally an image, return response text and image."""
|
||||
contents = []
|
||||
if message:
|
||||
contents.append(message)
|
||||
if image:
|
||||
contents.append(image)
|
||||
|
||||
if not contents:
|
||||
return None, None
|
||||
|
||||
response = self.chat.send_message(contents)
|
||||
|
||||
text_response = None
|
||||
image_response = None
|
||||
|
||||
for part in response.parts:
|
||||
if part.text is not None:
|
||||
text_response = part.text
|
||||
elif part.inline_data is not None:
|
||||
image_response = part.as_image()
|
||||
self.current_image = image_response
|
||||
|
||||
return text_response, image_response
|
||||
|
||||
def save_image(self, filename: str | None = None) -> str | None:
|
||||
"""Save the current image to a file."""
|
||||
if self.current_image is None:
|
||||
return None
|
||||
|
||||
if filename is None:
|
||||
self.image_count += 1
|
||||
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
|
||||
filename = f"image_{timestamp}_{self.image_count}.png"
|
||||
|
||||
filepath = self.output_dir / filename
|
||||
self.current_image.save(filepath)
|
||||
return str(filepath)
|
||||
|
||||
def load_image(self, path: str) -> Image.Image:
|
||||
"""Load an image from disk."""
|
||||
img = Image.open(path)
|
||||
self.current_image = img
|
||||
return img
|
||||
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser(
|
||||
description="Interactive multi-turn image generation",
|
||||
formatter_class=argparse.RawDescriptionHelpFormatter,
|
||||
epilog=__doc__
|
||||
)
|
||||
parser.add_argument(
|
||||
"--model", "-m",
|
||||
default="gemini-2.5-flash-image",
|
||||
choices=["gemini-2.5-flash-image", "gemini-3-pro-image-preview"],
|
||||
help="Model to use"
|
||||
)
|
||||
parser.add_argument(
|
||||
"--output-dir", "-o",
|
||||
default=".",
|
||||
help="Directory to save images"
|
||||
)
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
try:
|
||||
chat = ImageChat(model=args.model, output_dir=args.output_dir)
|
||||
except Exception as e:
|
||||
print(f"Error initializing: {e}", file=sys.stderr)
|
||||
sys.exit(1)
|
||||
|
||||
print(f"Gemini Image Chat ({args.model})")
|
||||
print("Commands: /save [name], /load <path>, /clear, /quit")
|
||||
print("-" * 50)
|
||||
|
||||
while True:
|
||||
try:
|
||||
user_input = input("\nYou: ").strip()
|
||||
except (EOFError, KeyboardInterrupt):
|
||||
print("\nGoodbye!")
|
||||
break
|
||||
|
||||
if not user_input:
|
||||
continue
|
||||
|
||||
# Handle commands
|
||||
if user_input.startswith("/"):
|
||||
parts = user_input.split(maxsplit=1)
|
||||
cmd = parts[0].lower()
|
||||
arg = parts[1] if len(parts) > 1 else None
|
||||
|
||||
if cmd == "/quit":
|
||||
print("Goodbye!")
|
||||
break
|
||||
|
||||
elif cmd == "/clear":
|
||||
chat._init_chat()
|
||||
print("Conversation cleared.")
|
||||
continue
|
||||
|
||||
elif cmd == "/save":
|
||||
path = chat.save_image(arg)
|
||||
if path:
|
||||
print(f"Image saved to: {path}")
|
||||
else:
|
||||
print("No image to save.")
|
||||
continue
|
||||
|
||||
elif cmd == "/load":
|
||||
if not arg:
|
||||
print("Usage: /load <path>")
|
||||
continue
|
||||
try:
|
||||
chat.load_image(arg)
|
||||
print(f"Loaded: {arg}")
|
||||
print("You can now describe edits to make.")
|
||||
except Exception as e:
|
||||
print(f"Error loading image: {e}")
|
||||
continue
|
||||
|
||||
else:
|
||||
print(f"Unknown command: {cmd}")
|
||||
continue
|
||||
|
||||
# Send message to model
|
||||
try:
|
||||
# If we have a loaded image and this is first message, include it
|
||||
image_to_send = None
|
||||
if chat.current_image and not chat.chat.history:
|
||||
image_to_send = chat.current_image
|
||||
|
||||
text, image = chat.send_message(user_input, image_to_send)
|
||||
|
||||
if text:
|
||||
print(f"\nGemini: {text}")
|
||||
|
||||
if image:
|
||||
# Auto-save
|
||||
path = chat.save_image()
|
||||
print(f"\n[Image generated: {path}]")
|
||||
|
||||
except Exception as e:
|
||||
print(f"\nError: {e}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Reference in New Issue
Block a user