educhain 0.2.9

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 files

📈 Performance

Educhain consistently outperforms traditional methods in content generation speed and quality:

🛠 Installation

pip install educhain

🎮 Usage

Generate MCQs

Quick Start

from educhain import qna_engine

questions = qna_engine.generate_mcq(
    topic="Indian History",
    level="Beginner",
    num=5
)
print(questions)

Using Custom Prompt Templates

from educhain import qna_engine

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}
"""

result = qna_engine.generate_mcq(
    topic="Python Programming",
    num=2,
    learning_objective="Usage of Python classes",
    difficulty_level="Hard",
    prompt_template=custom_template,
)
print(result)

Using Different LLM Models

from educhain import qna_engine
from langchain_openai import ChatOpenAI

llama3_groq = ChatOpenAI(
    model="llama3-70b-8192",
    openai_api_base="https://api.groq.com/openai/v1",
    openai_api_key="GROQ_API_KEY"
)

questions = qna_engine.generate_mcq(
    topic="Chess",
    level="Hard",
    num=5,
    llm=llama3_groq
)
print(questions)

Generate Questions from Data Sources

from educhain import qna_engine

questions = qna_engine.generate_mcqs_from_data(
    source="https://example.com/article",
    source_type="url",
    num=5,
    learning_objective="Understand key concepts",
    difficulty_level="Intermediate"
)
print(questions)

Export Questions

from educhain import to_json, to_pdf, to_csv

to_json(questions, "questions.json")  # Export questions to JSON
to_pdf(questions, "questions.pdf")    # Export questions to PDF
to_csv(questions, "questions.csv")    # Export questions to CSV

Generate Lesson Plans

from educhain import content_engine

topic = "Medieval History"
level = "Beginner"
lesson_plan = content_engine.generate_lesson_plan(topic, level)
print(lesson_plan)

📊 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 configuration guide for more details.

🌟 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
• Finetuned Model for question generation
• Integration with popular Learning Management Systems
• Mobile app for on-the-go content generation

🤝 Contributing

We welcome contributions! Please see our Contribution Guide for more details.

📄 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

For bug reports or feature requests, please open an issue on our GitHub repository.

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www.educhain.in