from educhain import qna_engine

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

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)

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)

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)

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

from educhain import content_engine

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