Practical overview
When it fits
Use it as a learning and research starting point when you want to connect prompt concepts and papers with examples and introductory LLM programming guidance.
Who it is for
- Readers studying in-context learning, prompt engineering, agents or foundation models.
- Developers seeking introductory guidance on using LLMs in programs.
- People looking for prompt examples and resources for experimenting with LLM prompts.
Documented uses
- Browse papers organized around in-context learning and related LLM topics.
- Review prompt-engineering techniques and example ChatGPT prompts.
- Explore a resource described as a playground for LLM prompt experimentation.
- Follow annotated LangChain tutorial material to learn about using LLMs in programs.
Requirements & limits
The project is a public GitHub repository identified as open source under the MIT license.
- The repository is a guide and resource collection, not a model or API implementation.
- Its materials point to external papers and learning resources; the LangChain tutorial is supplied as a Jupyter notebook.
- The README describes the playground as enabling prompt experimentation but does not establish its setup or execution requirements.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Browse the guide’s prompt-engineering resources
Use the repository’s curated materials to explore prompt techniques, examples, research papers, and prompt experimentation resources.
Before you start
- Access to the public GitHub repository.
Steps
Open the repository README.
Choose a resource from its navigation links: Papers, Playground, Prompt Engineering, or ChatGPT Prompt.
Use the selected resource to explore its listed papers, techniques, examples, or prompt-experimentation material.
Expected outcome
You can navigate the guide’s curated learning and prompt-experimentation resources.
Guide limitations
- The README identifies these resources but does not document setup steps or a specific procedure for running the playground.
- The repository is a guide and resource collection, not a model or API implementation.
Open the LangChain introductory usage tutorial
Follow the repository’s linked tutorial for getting started with large language model usage through LangChain.
Before you start
- Access to the public GitHub repository.
- A way to open the linked Jupyter notebook.
Steps
Open the repository README.
Follow the link labeled LLMs Usage Guide to the LangChain tutorial notebook.
Use the tutorial’s annotated code examples as its introduction to LLM usage.
Expected outcome
You reach the project’s introductory LangChain tutorial and its code examples.
Guide limitations
- The available instructions point to the tutorial but do not specify environment setup, dependencies, credentials, or notebook execution steps.
- The tutorial’s described examples include document query, Auto-Agent, and Auto-GPT; this guide does not claim they were run or verified.
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 11 October 2026
- Original website title
- EgoAlpha/prompt-in-context-learning · Official homepage title · retained in its source language