educhain 0.3.8

A Python package for generating educational content using Generative AI

Educhain 🎓🔗

Website | Documentation

Educhain is a powerful Python package that leverages Generative AI to create engaging and personalized educational content. From generating multiple-choice questions to crafting comprehensive lesson plans, Educhain makes it easy to apply AI in various educational scenarios.

🚀 Features

• 📝 Generate Multiple Choice Questions (MCQs)
• 📊 Create Lesson Plans
• 🔄 Support for various LLM models
• 📁 Export questions to JSON, PDF, and CSV formats
• 🎨 Customizable prompt templates
• 📚 Generate questions from text/PDF/URL files
• 📹 Generate questions from YouTube videos
• 🥽 Generate questions from images

📈 Workflow

Reimagining Education with AI 🤖

• 📜 QnA Engine: Generates an infinte variety of Questions
• 📰 Content Engine: One-stop content generation - lesson plans, flashcards, notes etc
• 📌 Personalization Engine: Adapts to your individual level of understanding for a tailored experience.

🛠 Installation

pip install educhain

🎮 Usage

Starter Guide

Quick Start

Get started with content generation in < 3 lines!

from educhain import Educhain

client = Educhain()

ques = client.qna_engine.generate_questions(topic="Newton's Law of Motion",
                                            num=5)
print(ques)
ques.json() # ques.dict()

Supports Different Question Types

Generates different types of questions. See the advanced guide to create a custom question type.

# Supports "Multiple Choice" (default); "True/False"; "Fill in the Blank"; "Short Answer"

from educhain import Educhain

client = Educhain()

ques = client.qna_engine.generate_questions(topic = "Psychology", 
                                            num = 10,
                                            question_type="Fill in the Blank"
                                            custom_instructions = "Only basic questions")

print(ques)
ques.json() #ques.dict()

Use Different LLM Models

To use a custom model, you can pass a model configuration through the LLMConfig class

Here's an example using the Gemini Model

from langchain_google_genai import ChatGoogleGenerativeAI
from educhain import Educhain, LLMConfig

gemini_flash = ChatGoogleGenerativeAI(
    model="gemini-1.5-flash-exp-0827",
    google_api_key="GOOGLE_API_KEY")

flash_config = LLMConfig(custom_model=gemini_flash)

client = Educhain(flash_config) #using gemini model with educhain

ques = client.qna_engine.generate_questions(topic="Psychology",
                                            num=10)

print(ques)
ques.json() #ques.dict()

Customizable Prompt Templates

Configure your prompt templates for more control over input parameters and output quality.

from educhain import Educhain

client = Educhain()

custom_template = """
Generate {num} multiple-choice question (MCQ) based on the given topic and level.
Provide the question, four answer options, and the correct answer.
Topic: {topic}
Learning Objective: {learning_objective}
Difficulty Level: {difficulty_level}
"""

ques = client.qna_engine.generate_questions(
    topic="Python Programming",
    num=2,
    learning_objective="Usage of Python classes",
    difficulty_level="Hard",
    prompt_template=custom_template,
)

print(ques)

Generate Questions from Data Sources

Ingest your own data to create content. Currently supports URL/PDF/TXT.

from educhain import Educhain
client = Educhain()

ques = client.qna_engine.generate_questions_from_data(
    source="https://en.wikipedia.org/wiki/Big_Mac_Index",
    source_type="url",
    num=5)

print(ques)
ques.json() # ques.dict()

Generate Lesson Plans

Create interactive and detailed lesson plans.

from educhain import Educhain

client = Educhain()

plan = client.content_engine.generate_lesson_plan(
                              topic = "Newton's Law of Motion")

print(plan)
plan.json()  # plan.dict()

📊 Supported Question Types

• Multiple Choice Questions (MCQ)
• Short Answer Questions
• True/False Questions
• Fill in the Blank Questions

🔧 Advanced Configuration

Educhain offers advanced configuration options to fine-tune its behavior. Check our advanced guide for more details. (coming soon!)

🌟 Success Stories

Educators worldwide are using Educhain to transform their teaching. Read our case studies to learn more.

📈 Usage Statistics

Educhain's adoption has been growing rapidly:

🗺 Roadmap

• Bulk Generation
• Outputs in JSON format
• Custom Prompt Templates
• Custom Response Models using Pydantic
• Exports questions to JSON/PDF/CSV
• Support for other LLM models
• Generate questions from text/PDF file
• Integration with popular Learning Management Systems
• Mobile app for on-the-go content generation

🤝 Open Source Contributions Welcome!

We invite you to help enhance our library. If you have any ideas, improvements, or suggestions for enhancements to contribute, please open a GitHub issue or submit a pull request. Be sure to adhere to our existing project structure and include a detailed README.md for any new Contribution.

Thank you for your continued support, community!

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

📬 Contact

• For general inquiries: educhain.in
• For technical support: [e-mail]
• Follow us on Twitter

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www.educhain.in

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