Educhain is a Python package designed to streamline the creation of educational content using generative AI. It caters to educators, content creators, and developers looking to integrate AI into learning platforms or generate custom study materials. The library simplifies tasks like generating quizzes, lesson plans, and study notes, offering flexibility in question types and output formats.

How It Works

Educhain acts as an abstraction layer over various Large Language Models (LLMs), including those from Google (Gemini) and OpenAI. Users interact with the Educhain client, specifying content generation tasks such as creating multiple-choice questions or lesson plans. The package handles prompt engineering, LLM interaction, and response parsing, allowing for customization through prompt templates and the integration of custom LLM models via LLMConfig. It supports generating content from various sources, including text, URLs, PDFs, and even YouTube videos.

Quick Start & Requirements

• Primary install: pip install educhain
• Prerequisites: Python 3.x, API keys for supported LLMs (e.g., Google API key, OpenAI API key).
• Documentation: Educhain Website

Highlighted Details

• Supports generation of Multiple Choice, True/False, Fill in the Blank, and Short Answer questions.
• Can generate content from URLs, PDFs, text files, and YouTube video transcripts.
• Offers export options for generated content to JSON, PDF, and CSV formats.
• Allows integration of custom LLM models and customizable prompt templates for fine-grained control.

Maintenance & Community

• Developed by Buildfastwithai.
• Contact for technical support: satvik@buildfastwithai.com.
• Follow on Twitter.

Licensing & Compatibility

• License: MIT License.
• Compatible with commercial use and closed-source linking due to its permissive MIT license.

Limitations & Caveats

The roadmap indicates that integration with Learning Management Systems (LMS) and a mobile app are future features, suggesting these are not currently supported. The library relies on external LLM APIs, which may incur costs and are subject to their respective terms of service.