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import os
import gradio as gr
from anthropic import Anthropic
from datetime import datetime, timedelta
from collections import deque
import random
# Initialize Anthropic client
anthropic = Anthropic(
api_key=os.environ.get('ANTHROPIC_API_KEY')
)
# Request tracking
MAX_REQUESTS_PER_DAY = 25
request_history = deque(maxlen=1000)
def check_api_key():
"""Verify API key is configured"""
if not os.environ.get('ANTHROPIC_API_KEY'):
raise ValueError("Anthropic API key not found. Please configure it in HuggingFace Spaces settings.")
def check_rate_limit():
"""Check if we're within rate limits"""
now = datetime.now()
while request_history and (now - request_history[0]) > timedelta(days=1):
request_history.popleft()
return len(request_history) < MAX_REQUESTS_PER_DAY
def clean_latex(text):
"""Simple LaTeX cleaning"""
text = text.replace('\n', '\n\n')
return text
def create_latex_document(content, questions_only=False):
"""Create a complete LaTeX document"""
latex_header = r"""\documentclass{article}
\usepackage{amsmath,amssymb}
\usepackage[margin=1in]{geometry}
\begin{document}
\title{Mathematics Test}
\maketitle
"""
latex_footer = r"\end{document}"
if questions_only:
# Extract only the questions (everything before "Solution:")
processed_content = []
current_question = []
for line in content.split('\n'):
if 'Solution:' in line:
processed_content.append('\n'.join(current_question))
current_question = []
continue
if any(line.startswith(f"{i})") for i in range(1, 4)):
if current_question:
processed_content.append('\n'.join(current_question))
current_question = [line]
elif current_question:
current_question.append(line)
if current_question:
processed_content.append('\n'.join(current_question))
content = '\n\n'.join(processed_content)
return f"{latex_header}\n{content}\n{latex_footer}"
def generate_test(subject):
"""Generate a math test"""
try:
check_api_key()
if not check_rate_limit():
return "Daily request limit reached. Please try again tomorrow.", None, None
request_history.append(datetime.now())
topics = {
"Single Variable Calculus": ["limits", "derivatives", "integrals", "series", "applications"],
"Multivariable Calculus": ["partial derivatives", "multiple integrals", "vector fields", "optimization"],
"Linear Algebra": ["matrices", "vector spaces", "eigenvalues", "linear transformations"],
# ... add topics for other subjects
}
selected_topics = random.sample(topics.get(subject, ["general"]), min(3, len(topics.get(subject, ["general"]))))
difficulty_distribution = random.choice([
"one easy, one medium, one challenging",
"two medium, one very challenging",
"one medium, two challenging"
])
system_prompt = f"""You will write math exam questions. Follow these requirements EXACTLY:
1. Write exactly 3 university-level questions focusing on these specific topics: {', '.join(selected_topics)}
2. Make the questions {difficulty_distribution}
3. ALL questions must be computational or proof-based problems. NO conceptual or explanation questions.
4. Each question must require mathematical work, calculations, or formal proofs
5. For LaTeX math formatting:
- Use $ for simple inline math
- For equations and solution steps, use $$ on separate lines
- For multi-step solutions, put each step on its own line in $$ $$
- DO NOT use \\begin{{aligned}} or any other environments
6. Number each question as 1), 2), 3)
7. Include detailed solutions after each question
8. Keep formatting simple and clear
Important: Every question must require mathematical computation or proof. Do not ask for explanations, descriptions, or concepts."""
message = anthropic.messages.create(
model="claude-3-opus-20240229",
max_tokens=1500,
temperature=0.7,
messages=[{
"role": "user",
"content": f"{system_prompt}\n\nWrite an exam for {subject}."
}]
)
if hasattr(message, 'content') and len(message.content) > 0:
response_text = message.content[0].text
cleaned_text = clean_latex(response_text)
# Create both versions of the LaTeX document
full_latex = create_latex_document(cleaned_text, questions_only=False)
questions_latex = create_latex_document(cleaned_text, questions_only=True)
return cleaned_text, questions_latex, full_latex
else:
return "Error: No content in response", None, None
except Exception as e:
return f"Error: {str(e)}", None, None
subjects = [
"Single Variable Calculus",
"Multivariable Calculus",
"Linear Algebra",
"Differential Equations",
"Real Analysis",
"Complex Analysis",
"Abstract Algebra",
"Probability Theory",
"Numerical Analysis",
"Topology"
]
# Create Gradio interface
with gr.Blocks() as interface:
gr.Markdown("# Advanced Mathematics Test Generator")
gr.Markdown("""Generates unique university-level mathematics exam questions with solutions using Claude 3 Opus.
Each test features different topics and difficulty levels. Limited to 25 requests per day.""")
with gr.Row():
subject_dropdown = gr.Dropdown(
choices=subjects,
label="Select Mathematics Subject",
info="Choose a subject for the exam questions"
)
generate_btn = gr.Button("Generate Test")
output_text = gr.Markdown(
label="Generated Test",
latex_delimiters=[
{"left": "$$", "right": "$$", "display": True},
{"left": "$", "right": "$", "display": False}
]
)
with gr.Row():
with gr.Column():
gr.Markdown("### Download LaTeX Files")
questions_file = gr.File(label="Questions Only (LaTeX)")
full_file = gr.File(label="Full Test with Solutions (LaTeX)")
def generate_and_prepare_files(subject):
preview, questions_latex, full_latex = generate_test(subject)
# Create temporary files for download
questions_file = {"content": questions_latex.encode(), "name": "questions.tex"}
full_file = {"content": full_latex.encode(), "name": "full_test.tex"}
return preview, questions_file, full_file
generate_btn.click(
generate_and_prepare_files,
inputs=[subject_dropdown],
outputs=[output_text, questions_file, full_file]
)
if __name__ == "__main__":
interface.launch() |