Image Generation Pipeline
Course Description
graph TB
direction TB
AA(["\n INPUT \n\n"]):::output
B("Prompt Task")
C("Image Generation Task"):::tool
I("View Image Task"):::main
AA --> B --> C --> I
classDef main fill:#4274ff1a, stroke:#426eff
classDef dash stroke-dasharray: 5 5
classDef tool stroke:#f06090
classDef tool-dash stroke:#f06090,stroke-dasharray: 5 5
classDef output fill:#5552,stroke:#555
Welcome to our course on Griptape Pipelines, where we'll be exploring this powerful feature through the practical example of image generation. In this course, you'll learn how to use Griptape Pipelines to seamlessly link together various tasks to create a cohesive workflow.
Our focus will be on how to set up a pipeline that can take a concept, apply a specific style, and incorporate a description to generate an image. Plus, we'll show you how to use a CodeExecutionTask to display the image after it's created.
This course is designed to be approachable and informative, ideal for anyone looking to understand the fundamentals of Griptape Pipelines. Whether you're a developer, a hobbyist, or just curious about how pipelines can enhance your projects, this course will provide you with the practical skills and knowledge needed to get started. So let's jump in and explore the exciting possibilities that Griptape Pipelines have to offer!
Who is this course for
This course is aimed at intermediate level Python developers who are interested in learning about Griptape Pipelines and how to handle parent/child task relationships, Griptape Tasks, and image generation.
Prerequisites
Before beginning this course, you will need:
- An OpenAI API Key (available here: OpenAI)
- Python 3.9+ installed on your machine
- An IDE (such as Visual Studio Code or PyCharm) to write and manage your code
If you don't have those items available, it's highly recommended you go through the Griptape Setup - Visual Studio Code course to set up your environment.
It's also recommended to view the Compare Movies Workflow course if you haven't viewed it before, as it contains some similar concepts to the Pipeline course.
Image Generation Drivers
The course will cover some of the Image Generation Drivers available for Griptape, including OpenAI DALL·E 3, Leonardo.AI, and Image Generation Drivers running on Amazon Bedrock
DALL·E 3
- DALL·E 3 is available with an OpenAI API key.
Leonardo.ai
- Sign up for a Leonardo.Ai account
- Save your
LEONARDO_API_KEY
in your.env
file.
Amazon Bedrock
- Ensure you have an AWS account
- Ensure you have access to the appropriate model by following the Amazon Documentation
- Add the following environment variables to your
.env
file:AWS_REGION_NAME
AWS_ACCESS_KEY_ID
AWS_SECRET_ACCESS_KEY
Course Outline
The course will cover:
- Creating Griptape Pipelines
- Creating Griptape Tasks
- Investigate Image Generation Drivers
- Using a
CodeExecutionTask
to display the resulting image
Useful Resources and Links
- Griptape Documentation
- Visual Studio Code
- Jinja2 Documentation
- Amazon Image Generation Documentation
- Leonardo.Ai
- Compare Movies Workflow
Next Steps
Get yourself all set up and ready by moving on to Setup.