# phodal/understand-prompt

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5,455 stars · 434 forks · Jupyter Notebook

## Links

- GitHub: https://github.com/phodal/understand-prompt
- awesome-repositories: https://awesome-repositories.com/repository/phodal-understand-prompt.md

## Topics

`ai` `aigc` `chatgpt` `github-copilot` `stable-diffusion`

## Description

This project provides methodologies and guides for structured prompt engineering, generative workflows, and specialized image generation strategies. It serves as a framework for optimizing inputs to large language models across coding, writing, and analysis tasks, as well as a library of techniques for controlling diffusion models.

The project distinguishes itself through an AI-driven software design framework that converts business requirements into technical architectures and code using domain-driven prompting. It also implements generative AI workflow patterns that use sequential prompt pipelines and cognitive frameworks to ensure predictable model outputs.

The capability surface covers software architecture through domain-driven API modeling and the generation of custom domain-specific languages. It further extends to image generation, including structural image binding, personalized model training, and iterative inpainting refinement to correct visual artifacts.

The project is implemented as a series of Jupyter Notebooks.

## Tags

### Artificial Intelligence & ML

- [Prompt Engineering Guides](https://awesome-repositories.com/f/artificial-intelligence-ml/prompt-engineering-guides.md) — Offers a comprehensive guide to optimizing inputs for large language models across coding, writing, and analysis tasks.
- [Prompt-Based Design Methodologies](https://awesome-repositories.com/f/artificial-intelligence-ml/prompt-engineering/software-engineering-prompt-libraries/prompt-based-design-methodologies.md) — Provides an AI-driven software design framework that converts business requirements into technical architectures using structured prompting. ([source](https://github.com/phodal/understand-prompt#readme))
- [AI Code Generators](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-code-generators.md) — Provides techniques for generating source code and technical artifacts from natural language descriptions using large language models. ([source](https://github.com/phodal/understand-prompt/tree/master/codeai))
- [AI Coding Assistant Guidance](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-coding-assistants/ai-coding-assistant-guidance.md) — Uses AI to transform functional requirements into source code, API designs, and structured software architectures.
- [Code Generation Prompts](https://awesome-repositories.com/f/artificial-intelligence-ml/code-generation-prompts.md) — Provides curated prompting strategies specifically designed for generating, refactoring, and analyzing source code. ([source](https://github.com/phodal/understand-prompt/blob/master/codeai.ipynb))
- [Cognitive Frameworks](https://awesome-repositories.com/f/artificial-intelligence-ml/complex-problem-solving/cognitive-frameworks.md) — Applies logical organization principles like the Pyramid Principle to prompt structures for improved model reasoning.
- [Conversational Structure Optimization](https://awesome-repositories.com/f/artificial-intelligence-ml/conversational-ai-frameworks/conversational-structure-optimization.md) — Implements cognitive frameworks to organize AI inputs and improve the logical flow of generative responses. ([source](https://github.com/phodal/understand-prompt/blob/master/README.md))
- [Prompt-Based Code Synthesis](https://awesome-repositories.com/f/artificial-intelligence-ml/generative-ai-resources/generative-ai-development/prompt-based-code-synthesis.md) — Transforms functional requirements into executable code by treating prompts as a specialized language for synthesis.
- [AI Workflow Patterns](https://awesome-repositories.com/f/artificial-intelligence-ml/language-model-orchestration/ai-workflow-patterns.md) — Provides standardized structural approaches for chaining and routing LLM interactions to ensure predictable outputs.
- [Sequential Prompt Pipelines](https://awesome-repositories.com/f/artificial-intelligence-ml/prompt-design-strategies/sequential-prompt-pipelines.md) — Organizes complex tasks into sequential workflows to achieve consistent and predictable model outputs. ([source](https://github.com/phodal/understand-prompt/tree/master/chatgpt))
- [Prompt Engineering](https://awesome-repositories.com/f/artificial-intelligence-ml/prompt-engineering.md) — Provides methodologies for creating and optimizing structured text instructions to improve LLM output quality.
- [Iterative Image Inpainting](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-systems-frameworks/agentic-workflows/iterative-refinement-workflows/mask-refinement-loops/iterative-image-inpainting.md) — Provides iterative inpainting refinement techniques to fix localized image errors and anatomical artifacts.
- [AI Writing Assistants](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-writing-assistants.md) — Organizes context and prompts for high-quality article generation using structured writing frameworks. ([source](https://github.com/phodal/understand-prompt#readme))
- [Artistic Style Integration](https://awesome-repositories.com/f/artificial-intelligence-ml/custom-model-training/artistic-style-integration.md) — Integrates specific artistic styles and personal characteristics into models for personalized imagery. ([source](https://github.com/phodal/understand-prompt/blob/master/README.md))
- [Image Inpainting](https://awesome-repositories.com/f/artificial-intelligence-ml/generative-ai-resources/diffusion-visual-models/generative-ai-pipelines/text-to-image-generators/image-inpainting.md) — Implements generative filling of specific image regions using masks and prompts to correct visual artifacts. ([source](https://github.com/phodal/understand-prompt#readme))
- [Image Composition Controls](https://awesome-repositories.com/f/artificial-intelligence-ml/image-composition-controls.md) — Controls image composition and pose using depth maps and skeleton guides as constraints.
- [Keyword-Based Image Guidance](https://awesome-repositories.com/f/artificial-intelligence-ml/keyword-based-image-guidance.md) — Implements a system of positive and negative keyword lists to control visual elements and filter image artifacts.
- [Image Description Generators](https://awesome-repositories.com/f/artificial-intelligence-ml/prompt-variation-generators/image-description-generators.md) — Provides tools and methods for generating detailed descriptive prompts to guide AI image generators. ([source](https://github.com/phodal/understand-prompt#readme))
- [Prompt Optimizers](https://awesome-repositories.com/f/artificial-intelligence-ml/prompt-variation-generators/prompt-optimizers.md) — Refines natural language descriptions into optimized keyword-based prompts to improve image quality and detail. ([source](https://github.com/phodal/understand-prompt/blob/master/README.md))
- [Likeness Training](https://awesome-repositories.com/f/artificial-intelligence-ml/text-to-image-model-training/likeness-training.md) — Incorporates specific individual likenesses into image models to create customized visual outputs. ([source](https://github.com/phodal/understand-prompt#readme))

### Part of an Awesome List

- [Keyword Strategies](https://awesome-repositories.com/f/awesome-lists/ai/stable-diffusion-tools/keyword-strategies.md) — Provides a library of keyword strategies and techniques for controlling image generation in Stable Diffusion.
- [AI Content Generation](https://awesome-repositories.com/f/awesome-lists/ai/ai-content-generation.md) — Organizes complex information and writing tasks using cognitive frameworks for AI-generated text.

### Development Tools & Productivity

- [Sequential Pipelines](https://awesome-repositories.com/f/development-tools-productivity/task-pipeline-managers/sequential-pipelines.md) — Organizes complex AI tasks into ordered sequential prompt pipelines to ensure consistent and predictable outputs.
- [Boilerplate Generators](https://awesome-repositories.com/f/development-tools-productivity/code-generators/boilerplate-generators.md) — Offers guidance on producing boilerplate code, API implementations, and unit tests based on natural language prompts. ([source](https://github.com/phodal/understand-prompt#readme))

### Programming Languages & Runtimes

- [Prompt-Driven DSL Definition](https://awesome-repositories.com/f/programming-languages-runtimes/programming-language-varieties/domain-specific-languages/dsl-implementation-toolkits/prompt-driven-dsl-definition.md) — Defines formal syntax and rules using natural language to create custom domain-specific languages for automation. ([source](https://github.com/phodal/understand-prompt/blob/master/README.md))
- [Prompt-Based DSL Generation](https://awesome-repositories.com/f/programming-languages-runtimes/source-code-generators/specification-from-code-generators/natural-language-code-generators/template-based-code-generators/prompt-based-dsl-generation.md) — Defines formal syntax rules using natural language prompts to automate the creation of domain-specific languages.

### Software Engineering & Architecture

- [Requirement to Code Generators](https://awesome-repositories.com/f/software-engineering-architecture/requirement-to-task-decomposition/requirement-to-code-generators.md) — Transforms high-level functional requirements into executable code snippets and technical tables through structured prompt pipelines. ([source](https://github.com/phodal/understand-prompt/blob/master/README.md))
- [Domain-Driven Designs](https://awesome-repositories.com/f/software-engineering-architecture/software-architecture/architectural-patterns/abstraction-domain-modeling/domain-driven-designs.md) — Decomposes business scenarios into technical specifications using sequential prompting and domain-driven design. ([source](https://github.com/phodal/understand-prompt/blob/master/README.md))
- [AI-Driven Design Frameworks](https://awesome-repositories.com/f/software-engineering-architecture/software-architecture/architectural-patterns/abstraction-domain-modeling/domain-driven-designs/ai-driven-design-frameworks.md) — Implements a comprehensive framework for converting business requirements into technical architectures and code via domain-driven prompting.
- [API Modeling](https://awesome-repositories.com/f/software-engineering-architecture/software-architecture/architectural-patterns/abstraction-domain-modeling/domain-driven-designs/api-modeling.md) — Breaks down complex requirements into structured APIs and system architectures using domain-driven design. ([source](https://github.com/phodal/understand-prompt#readme))
- [Domain-Driven Prompting](https://awesome-repositories.com/f/software-engineering-architecture/software-architecture/architectural-patterns/abstraction-domain-modeling/domain-driven-designs/domain-driven-prompting.md) — Maps business domain models and event storming patterns directly into structured prompts for software architecture generation.

### Graphics & Multimedia

- [Stable Diffusion Workflows](https://awesome-repositories.com/f/graphics-multimedia/stable-diffusion-workflows.md) — Provides specialized strategies and workflows for generating and refining high-quality imagery using Stable Diffusion.