prompt-in-context-learning
Resources for in-context learning and prompt engineering with LLMs like ChatGPT and GPT-3
GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
prompt-in-context-learning offers specialized resources for mastering large language models through advanced prompt engineering and in-context learning techniques.
Good fit when
- Use when seeking to enhance the capabilities of AI agents specifically using cutting-edge prompt engineering techniques such as those used with ChatGPT, GPT-3, or FlanT5.
- Ideal if your focus is on up-to-date methodologies for optimizing language model performance in real-world applications.
Avoid when
- Not recommended if you require functionalities specific to other AI frameworks that do not align with the prompt engineering techniques focused on here.
- Avoid this resource if your project strictly focuses on areas outside of in-context learning and advanced LLMs like ChatGPT or GPT-3.
- Requirements:
- Operates in Jupyter Notebook environments.
Observed Jul 17, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Slowing (114d since push)
- As of Sep 20, 2026
- Provenance
- Not a fork · Personal account
- As of Sep 20, 2026
- Security (OSV)
- No lockfile
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
git clone https://github.com/EgoAlpha/prompt-in-context-learningSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Provides resources and tools focused on mastery of large language models through contemporary prompt engineering techniques including in-context learning, aimed at enhancing the capabilities of AI agents.
Capability facts
- Languages
- jupyter notebook
Source: github.language · Sep 20, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Sep 20, 2026)
🎉*: The method for quickly getting started with large language models by using LangChain.Source link
Source: README excerpt (regex_v1, Sep 20, 2026)
<a href="./chatgptprompt.md">🌍 ChatGPT Prompt</a> ｜Source link
Tags
README
<div align="center" <img src="./figures/Prompt EgoAlpha white.svg" width="600px" <div align="center" </div An Open Source Engineering Guide for Prompt in context learning from EgoAlpha Lab. <img width="200%" src="./figures/hr.gif" / <p align="center" <a href=" 📜 papers" 📝 Paper...
For agents
This page has a .md twin and JSON over the API.