# trigaten/learn_prompting

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4,709 stars · 669 forks · MDX · NOASSERTION

## Links

- GitHub: https://github.com/trigaten/Learn_Prompting
- Homepage: https://learnprompting.org
- awesome-repositories: https://awesome-repositories.com/repository/trigaten-learn-prompting.md

## Topics

`chatgpt` `chatgpt-api` `deep-learning` `gpt-3` `gpt-4` `gpt-4-api` `gpt3` `large-language-models` `llm` `machine-learning` `nlp` `openai-api` `prompt-engineering` `prompt-toolkit` `prompt-tuning` `prompting` `transformers`

## Description

Learn_Prompting is an educational project focused on prompt engineering, providing the principles and techniques required to craft effective inputs and improve the quality of generative AI outputs.

The project covers advanced prompting strategies to enhance reasoning, reliability, and output quality. This includes techniques for task decomposition, chain-of-thought reasoning, and the use of few-shot and zero-shot guidance. It also addresses model security through the study of prompt hacking, vulnerability analysis, and privacy auditing to prevent sensitive data leaks.

The scope extends to the practical application of generative AI across diverse media and workflows, including text generation, photorealistic image creation, and audio-visual production. It further covers the development of autonomous agents, AI-assisted programming, and the automation of business workflows for marketing and communications.

The project provides resources for model optimization, evaluation, and the management of prompt lifecycles within an interactive experimentation environment.

## Tags

### Part of an Awesome List

- [Autonomous AI Agents](https://awesome-repositories.com/f/awesome-lists/ai/autonomous-ai-agents.md) — Provides the foundational principles for building AI systems that decompose complex goals into executable sub-tasks.
- [AI Security and Red Teaming](https://awesome-repositories.com/f/awesome-lists/ai/ai-security-and-red-teaming.md) — Covers red teaming and prompt hacking techniques to identify vulnerabilities and prevent sensitive data leaks in AI systems.
- [Role-Based Prompting](https://awesome-repositories.com/f/awesome-lists/ai/few-shot-adaptation/role-based-prompting.md) — Uses role assignment and shot-based examples to control the tone and behavior of responses. ([source](https://learnprompting.org/docs/basics/intro))
- [Code Generation and Assistance](https://awesome-repositories.com/f/awesome-lists/ai/code-generation-and-assistance.md) — Provides guidance on using natural language instructions to write, debug, and optimize software code.
- [Prompt-Based Audio Generation](https://awesome-repositories.com/f/awesome-lists/media/music-and-audio-generation/prompt-based-audio-generation.md) — Teaches specific prompting techniques to generate original audio and musical compositions. ([source](https://learnprompting.org/docs/miscl/introduction))

### Education & Learning Resources

- [Prompt Engineering Curricula](https://awesome-repositories.com/f/education-learning-resources/prompt-engineering-curricula.md) — Offers comprehensive educational material and curricula on the discipline and techniques of prompt engineering.
- [Research Workflow Automation](https://awesome-repositories.com/f/education-learning-resources/research-workflow-automation.md) — Automates research workflows including decoding scientific literature and summarizing articles. ([source](https://learnprompting.org/docs/products))

### Artificial Intelligence & ML

- [AI Content Workflow Automation](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-content-workflow-automation.md) — Provides methodologies for integrating large language models into automated pipelines for text and media synthesis.
- [Chain-of-Thought Prompting](https://awesome-repositories.com/f/artificial-intelligence-ml/chain-of-thought-prompting.md) — Provides comprehensive instruction on using intermediate reasoning steps to solve complex logical problems.
- [Retrieval-Augmented Generation](https://awesome-repositories.com/f/artificial-intelligence-ml/conversational-interfaces/retrieval-augmented-generation.md) — Provides principles for grounding model responses using retrieved external documents and real-time data.
- [Dynamic Reasoning Adaptations](https://awesome-repositories.com/f/artificial-intelligence-ml/dynamic-reasoning-adaptations.md) — The project adjusts the chain-of-thought process dynamically based on the specific characteristics of the input. ([source](https://learnprompting.org/docs/new_techniques/introduction))
- [Prompt Experimentation](https://awesome-repositories.com/f/artificial-intelligence-ml/experimentation-frameworks/prompt-experimentation.md) — Provides an interactive environment for testing and refining different prompt variations in real time. ([source](https://learnprompting.org/docs/basics/intro))
- [LLM Hallucination Mitigations](https://awesome-repositories.com/f/artificial-intelligence-ml/llm-hallucination-mitigations.md) — Applies calibration and verification techniques to reduce hallucinations and biases in AI completions. ([source](https://learnprompting.org/docs/reliability/introduction))
- [Model Limitation Mitigations](https://awesome-repositories.com/f/artificial-intelligence-ml/model-bias-mitigation/model-limitation-mitigations.md) — Provides techniques to identify and work around hallucinations, biases, and prompt hacking. ([source](https://learnprompting.org/docs/basics/intro))
- [Self-Correction Loops](https://awesome-repositories.com/f/artificial-intelligence-ml/multi-step-goal-execution/self-correction-loops.md) — Implements internal critique and recursive reasoning loops where models verify and correct their own logic. ([source](https://learnprompting.org/docs/advanced/introduction))
- [Prompt Elements](https://awesome-repositories.com/f/artificial-intelligence-ml/prompt-elements.md) — Teaches the arrangement of instructions, context, and constraints to produce precise outputs. ([source](https://learnprompting.org/docs/intermediate/introduction))
- [Multimodal Prompting](https://awesome-repositories.com/f/artificial-intelligence-ml/prompt-engineering-guides/multimodal-prompting.md) — Enables the creation of prompts for both text-based and text-to-image models. ([source](https://learnprompting.org/docs/introduction))
- [Prompt Iteration Workflows](https://awesome-repositories.com/f/artificial-intelligence-ml/prompt-iteration-workflows.md) — Offers an interactive environment for testing and refining prompt variations to compare model outputs.
- [Task Decompositions](https://awesome-repositories.com/f/artificial-intelligence-ml/task-decompositions.md) — Provides methods for breaking down complex objectives into smaller, manageable sub-tasks to improve reliability. ([source](https://learnprompting.org/docs/advanced/introduction))
- [Few-Shot Pattern Exemplification](https://awesome-repositories.com/f/artificial-intelligence-ml/zero-and-few-shot-learning/few-shot-pattern-exemplification.md) — Teaches how to provide input-output examples within prompts to guide model behavior and formatting.
- [Zero-Shot Generalization](https://awesome-repositories.com/f/artificial-intelligence-ml/zero-shot-generalization-tuning/zero-shot-generalization.md) — Teaches how to perform tasks using only pre-existing model knowledge without prior demonstrations. ([source](https://learnprompting.org/docs/advanced/introduction))
- [Agent Knowledge Bases](https://awesome-repositories.com/f/artificial-intelligence-ml/agent-knowledge-bases.md) — Explains how to build conversational agents that retrieve and respond to queries based on specific document sets. ([source](https://learnprompting.org/docs/basic_applications/introduction))
- [AI Image Generation](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-image-generation.md) — Instructs on using specific prompting techniques and style modifiers to produce high-quality AI visual assets.
- [Multimodal Input Processing](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-model-inference/multimodal-input-processing.md) — Covers the processing of combined text, image, and audio prompts to generate diverse AI assets.
- [AI Text Detectors](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-text-detectors.md) — Provides resources for identifying whether text was produced by a human or a language model. ([source](https://learnprompting.org/docs/miscl/introduction))
- [Presentation Generators](https://awesome-repositories.com/f/artificial-intelligence-ml/artificial-intelligence-tooling/automated-content-generation/presentation-generators.md) — Provides techniques for transforming outlines or voice requests into structured AI-generated slide decks. ([source](https://learnprompting.org/docs/products))
- [Automated Knowledge Synthesis Tools](https://awesome-repositories.com/f/artificial-intelligence-ml/automated-knowledge-synthesis-tools.md) — Guides the creation of factual summaries and supporting points before answering queries to increase accuracy. ([source](https://learnprompting.org/docs/intermediate/introduction))
- [Autonomous AI Agent Frameworks](https://awesome-repositories.com/f/artificial-intelligence-ml/autonomous-ai-agent-frameworks.md) — Provides guidance on building self-directed agents that can decompose complex goals into independent sub-tasks. ([source](https://learnprompting.org/docs/hot_topics))
- [Thought Chain Harmonizations](https://awesome-repositories.com/f/artificial-intelligence-ml/chain-of-thought-prompting/thought-chain-harmonizations.md) — Compares multiple internal chains of thought to resolve contradictions and improve consistency. ([source](https://learnprompting.org/docs/new_techniques/introduction))
- [External Tool Integration](https://awesome-repositories.com/f/artificial-intelligence-ml/external-tool-integration.md) — Demonstrates how to enable language models to interact with external APIs and databases for precise computations. ([source](https://learnprompting.org/docs/agents/introduction))
- [Text-to-Image Generators](https://awesome-repositories.com/f/artificial-intelligence-ml/generative-ai-resources/diffusion-visual-models/generative-ai-pipelines/text-to-image-generators.md) — Demonstrates how to convert written natural language descriptions into visual imagery using diffusion models. ([source](https://learnprompting.org/docs/tooling/IDEs/DALLE))
- [Generative Problem Solving](https://awesome-repositories.com/f/artificial-intelligence-ml/generative-problem-solving.md) — Implements a structured methodology to identify tools and refine prompts for multimodal tasks. ([source](https://learnprompting.org/docs/basics/intro))
- [Image Generation](https://awesome-repositories.com/f/artificial-intelligence-ml/image-generation.md) — Teaches the application of style modifiers and prompting techniques to generate high-quality visual content. ([source](https://learnprompting.org/docs/image_prompting/introduction))
- [Image Editing](https://awesome-repositories.com/f/artificial-intelligence-ml/image-generation/image-editing.md) — Provides instructions for modifying existing images and extending boundaries using outpainting techniques. ([source](https://learnprompting.org/docs/tooling/IDEs/DALLE))
- [Logical and Arithmetic Reasoning](https://awesome-repositories.com/f/artificial-intelligence-ml/logical-and-arithmetic-reasoning.md) — Applies structured logic and formal reasoning patterns to improve the accuracy of model deductions. ([source](https://learnprompting.org/docs/new_techniques/introduction))
- [Long-Form Text Generation](https://awesome-repositories.com/f/artificial-intelligence-ml/long-form-text-generation.md) — Provides techniques for producing extended, coherent sequences of natural language text like articles and blog posts. ([source](https://learnprompting.org/docs/basic_applications/introduction))
- [Context Window Management](https://awesome-repositories.com/f/artificial-intelligence-ml/long-form-text-generation/context-window-management.md) — Handles large amounts of text exceeding context windows through chunking and summarization. ([source](https://learnprompting.org/docs/intermediate/introduction))
- [Model Comparison Interfaces](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning/infrastructure/model-evaluation-analysis/machine-learning-evaluation/model-comparison-interfaces.md) — Provides analytical and visual comparison of outputs generated by different foundation models. ([source](https://learnprompting.org/docs/models/introduction))
- [Hyperparameter Optimization](https://awesome-repositories.com/f/artificial-intelligence-ml/model-optimization/training-efficiency/hyperparameter-optimization.md) — Teaches how to adjust parameters like temperature and top-p to control the randomness of generated text. ([source](https://learnprompting.org/docs/intermediate/introduction))
- [Natural Language Code Editing](https://awesome-repositories.com/f/artificial-intelligence-ml/natural-language-code-generators/natural-language-code-editing.md) — Enables real-time function suggestions, unit test generation, and code refactoring using natural language. ([source](https://learnprompting.org/docs/products))
- [Model Behavior Evaluation](https://awesome-repositories.com/f/artificial-intelligence-ml/pre-trained-model-application/model-behavior-evaluation.md) — Analyzes the relationship between inputs and outputs to diagnose and evaluate model alignment issues. ([source](https://learnprompting.org/docs/language-model-inversion/introduction))
- [Prompt Libraries](https://awesome-repositories.com/f/artificial-intelligence-ml/prompt-libraries.md) — Provides a curated library of pre-written examples and community templates to accelerate development. ([source](https://learnprompting.org/docs/additional))
- [Prompt Lifecycle Management](https://awesome-repositories.com/f/artificial-intelligence-ml/prompt-lifecycle-management.md) — Provides methods for building and logging optimized prompts to ensure generative AI output consistency. ([source](https://learnprompting.org/docs/products))
- [Real-time Context Augmentation](https://awesome-repositories.com/f/artificial-intelligence-ml/real-time-context-augmentation.md) — Teaches methods for connecting models to live external data sources to provide real-time context during inference. ([source](https://learnprompting.org/docs/retrieval_augmented_generation/introduction))
- [Reasoning Path Architectures](https://awesome-repositories.com/f/artificial-intelligence-ml/reasoning-models/reasoning-pipelines/reasoning-model-integrations/reasoning-step-outputs/reasoning-path-architectures.md) — Guides the logic process through a directed graph of steps to solve intricate problems. ([source](https://learnprompting.org/docs/new_techniques/introduction))
- [Recursive Task Decomposers](https://awesome-repositories.com/f/artificial-intelligence-ml/recursive-task-decomposers.md) — Explains techniques for breaking down complex objectives into hierarchical trees of executable sub-tasks.
- [Short-Form Text Generation](https://awesome-repositories.com/f/artificial-intelligence-ml/short-form-text-generation.md) — Provides prompting strategies for creating concise responses and social media content. ([source](https://learnprompting.org/docs/basic_applications/introduction))
- [Style Adapters](https://awesome-repositories.com/f/artificial-intelligence-ml/style-adapters.md) — Explains how to use style adapters and prompting to rewrite text to match specific voices, tones, or personas. ([source](https://learnprompting.org/docs/basic_applications/introduction))

### Development Tools & Productivity

- [Prompt Playgrounds](https://awesome-repositories.com/f/development-tools-productivity/human-in-the-loop-interfaces/interactive-prompts/prompt-playgrounds.md) — Provides an interactive sandbox for testing prompt versions and comparing model outputs in real time. ([source](https://learnprompting.org/docs/intermediate/introduction))
- [AI Coding Assistants](https://awesome-repositories.com/f/development-tools-productivity/ai-coding-assistants.md) — Facilitates writing, debugging, and optimizing programming code through targeted prompts. ([source](https://learnprompting.org/docs/basic_applications/introduction))

### Security & Cryptography

- [Privacy Audits](https://awesome-repositories.com/f/security-cryptography/inference-data-privacy/privacy-audits.md) — Identifies whether sensitive instructions are leaking through model outputs to detect privacy risks. ([source](https://learnprompting.org/docs/language-model-inversion/introduction))
- [LLM Security Enhancements](https://awesome-repositories.com/f/security-cryptography/llm-security-enhancements.md) — Enhances model reliability and identifies vulnerabilities through prompt hacking techniques. ([source](https://learnprompting.org/docs/introduction))
- [Prompt Recoveries](https://awesome-repositories.com/f/security-cryptography/prompt-recoveries.md) — Reconstructs hidden instructions used to generate an output by analyzing text patterns. ([source](https://learnprompting.org/docs/language-model-inversion/introduction))
- [Prompt Hacking Analysis](https://awesome-repositories.com/f/security-cryptography/vulnerability-analysis/prompt-hacking-analysis.md) — Analyzes how malicious inputs trick models into bypassing safeguards to leak sensitive data. ([source](https://learnprompting.org/docs/prompt_hacking/introduction))

### Content Management & Publishing

- [Generative Marketing Asset Suites](https://awesome-repositories.com/f/content-management-publishing/content-aggregation-curation/automated-social-media-assets/generative-marketing-asset-suites.md) — Offers guidance on creating professional advertisements and digital marketing assets using generative AI. ([source](https://learnprompting.org/docs/basic_applications/introduction))
- [AI Content Generators](https://awesome-repositories.com/f/content-management-publishing/dynamic-text-generation/ai-content-generators.md) — Demonstrates how to use AI content generators to produce blogs, stories, and various written documents. ([source](https://learnprompting.org/docs/products))
- [Email Content Generations](https://awesome-repositories.com/f/content-management-publishing/media-management/media-automation-tools/document-generation/ai-content-generation/email-content-generations.md) — Provides methods for generating full professional emails and communication blocks from natural language prompts. ([source](https://learnprompting.org/docs/basic_applications/introduction))

### Data & Databases

- [Tabular Data Organization](https://awesome-repositories.com/f/data-databases/tabular-data-organization.md) — Teaches how to use prompting to transform raw, unstructured text into organized tabular formats. ([source](https://learnprompting.org/docs/basic_applications/introduction))
- [Unstructured Text Processing](https://awesome-repositories.com/f/data-databases/text-processing-utilities/text-processing-tools/unstructured-text-processing.md) — Provides methods for transforming unstructured text into structured formats and extracting qualitative insights. ([source](https://learnprompting.org/docs/products))

### Game Development

- [Generative Game Asset Design](https://awesome-repositories.com/f/game-development/custom-game-asset-design/generative-game-asset-design.md) — Covers the use of text prompts to create consistent images and interactive characters for games. ([source](https://learnprompting.org/docs/products))

### Graphics & Multimedia

- [Generative Photorealistic Rendering](https://awesome-repositories.com/f/graphics-multimedia/photorealistic-object-rendering/generative-photorealistic-rendering.md) — Teaches how to create photorealistic images, avatars, and product photography from text descriptions. ([source](https://learnprompting.org/docs/products))
- [Synthetic Media Generation](https://awesome-repositories.com/f/graphics-multimedia/synthetic-media-generation.md) — Explains how to compose original music and generate synthetic video clips from text descriptions. ([source](https://learnprompting.org/docs/products))

### Networking & Communication

- [Generative](https://awesome-repositories.com/f/networking-communication/bulk-emailing-tools/email-personalization/generative.md) — Teaches how to generate professional email drafts tailored to specific scenarios and recipients. ([source](https://learnprompting.org/docs/basic_applications/writing_emails))