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import requests
import gradio as gr
from dotenv import load_dotenv
import os
from openai import OpenAI
import spacy
import random
# Load environment variables from .env file
load_dotenv()
# Access the env
HF_TOKEN = os.getenv('HUGGING_FACE_TOKEN')
# openai setup
client = OpenAI(
api_key=os.getenv('OPENAI_API_KEY')
)
# Global variable to control debug printing
DEBUG_MODE = True
def debug_print(*args, **kwargs):
if DEBUG_MODE:
print(*args, **kwargs)
def generate_questions(input_topic, num_questions, difficulty_level):
"""
Generates EFL questions based on the input topic
"""
# Adjusting the prompt based on the chosen difficulty level
difficulty_instruction = {
"Easy": "using very simple English",
"Medium": "using moderately simple English",
"Hard": "that challenge comprehension and critical thinking"
}
prompt=f"Generate {num_questions} questions {difficulty_instruction[difficulty_level]} for an EFL (English as a Foreign Language) student based on the following topic: {input_topic}"
response = client.chat.completions.create(
messages=[
{"role": "system", "content": ""},
{"role": "user", "content": prompt}
],
model="gpt-3.5-turbo",
)
questions = response.choices[0].message.content
debug_print("GPT output:", questions)
return questions
with gr.Blocks() as app:
with gr.Column():
gr.Markdown("### EFL Question Generator")
input_text = gr.Textbox(label="Topic", lines=1, placeholder="Type or paste your topic here...", value="Hobbies")
with gr.Row():
num_questions_dropdown = gr.Dropdown(label="Number of Questions", choices=[5, 10, 15, 20], value=5)
difficulty_dropdown = gr.Dropdown(label="Difficulty Level", choices=["Easy", "Medium", "Hard"], value="Easy")
output_questions = gr.Textbox(label="Generated Questions", lines=5)
generate_btn = gr.Button("Generate Questions")
generate_btn.click(fn=generate_questions, inputs=[input_text, num_questions_dropdown, difficulty_dropdown], outputs=output_questions)
app.launch()
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