app.py

import os
import gradio as gr
from anthropic import Anthropic
from datetime import datetime, timedelta
from collections import deque
import random
import logging
import tempfile
from pathlib import Path
from sympy import *
import json
from pathlib import Path

# Set up logging
logging.basicConfig(
    level=logging.DEBUG,
    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)
logger = logging.getLogger(__name__)

# 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)

SYMPY_GUIDELINES = """
When writing SymPy code to verify solutions:

NOTE: For eigenvalue problems, use 'lam = Symbol('lam')' instead of importing from sympy.abc

1. Variable Declaration and Expressions:
   - ALWAYS create symbolic expressions instead of literal numbers when working with mathematical operations:
     ```python
     # CORRECT:
     x = Symbol('x')
     expr = x + 1  # Creates a symbolic expression
     
     # INCORRECT:
     expr = 1  # This is just a number, can't be differentiated
     ```
   - For polynomials and functions:
     ```python
     # CORRECT:
     x = Symbol('x')
     p = x**2 + 2*x + 1  # Creates a polynomial expression
     
     # INCORRECT:
     p = 1  # This won't work for operations like diff()
     ```
   - When verifying operator actions:
     ```python
     # CORRECT:
     x = Symbol('x')
     def verify_operator(p):
         x = Symbol('x')  # Always use Symbol inside functions too
         return p.subs(x, 1)  # Substitute values after creating expression
     
     # INCORRECT:
     def verify_operator(p):
         return p  # Passing raw numbers won't work
     ```
   - For integration bounds:
     ```python
     # CORRECT:
     t = Symbol('t')
     expr = t**2
     result = integrate(expr, (t, 0, 1))
     
     # INCORRECT:
     result = integrate(2, (t, 0, 1))  # Can't integrate a number
     ```
     
2. Solving and Computing:
   - Never use strings in solve() or other SymPy functions:
     CORRECT:   solve(eq, x)
     INCORRECT: solve(eq, 'x')
   - Define equations symbolically:
     CORRECT:   eq = 2*sqrt(h) - sqrt(12) + 5*k
     INCORRECT: eq = 2*sqrt('h') - sqrt(12) + 5*k

3. Printing and Output:
   - Include print statements for ALL calculations and results
   - Print intermediate steps and final answers
   - Print variable values after they are computed
   - Use simple print statements instead of f-strings for SymPy expressions
   - Print expressions with labels on separate lines:
     ```python
     print("Expression label:")
     print(expression)
     ```

4. Numeric Calculations:
   - Use Float() for decimal numbers in calculations
   - Use float() for final printing of results
   - Avoid evalf() as it may cause errors
   - For numeric results:
     ```python
     result = expression.evalf()
     print("Result:")
     print(float(result))
     ```

5. Working with Series and Sequences:
   - Use Float() for sequence terms
   - Convert sums to float() before printing
   - For series calculations, print intermediate terms   

6. Matrix Operations and Systems of Equations:
   - Never use symbolic variables as matrix indices:
     ```python
     # CORRECT:
     i, j = 0, 1  # Use integers for indexing
     M = Matrix([[1, 2], [3, 4]])
     element = M[i, j]
     
     # INCORRECT:
     x = Symbol('x')
     element = M[x, 0]  # This will raise an error
     ```

   - For matrix analysis, always convert equations to Matrix form:
     ```python
     # CORRECT:
     A = Matrix([[1, 2], [3, 4]])
     eigenvals = A.eigenvals()
     
     # For system of equations:
     x, y = symbols('x y')
     system = Matrix([[2, 1], [1, -1]])
     b = Matrix([5, 1])
     solution = system.solve(b)
     ```
     
   - For matrix operations with variables:
     ```python
     # CORRECT:
     x = Symbol('x')
     M = Matrix([[x, 1], [2, 3]])
     result = M * M  # Matrix multiplication
     
     # INCORRECT:
     M[Symbol('i'), Symbol('j')] = x  # Don't use symbolic indices     
     ```
   - For systems of equations that might be linearly dependent, use row reduction instead of matrix inversion. Here's the template for handling such systems:

```python
from sympy import Matrix, symbols, solve

def analyze_system(A, b):
    'Analyze a system Ax = b using row reduction. Returns whether solution exists and if it's unique.'
    # Augmented matrix [A|b]
    aug = Matrix(A.row_join(b))
    
    # Get row echelon form
    rref, pivots = aug.rref()
    
    print("Row reduced augmented matrix:")
    print(rref)
    print("\\nPivot columns:", pivots)
    
    # Get rank of coefficient matrix and augmented matrix
    rank_A = Matrix(A).rank()
    rank_aug = aug.rank()
    
    print(f"\\nRank of coefficient matrix: {rank_A}")
    print(f"Rank of augmented matrix: {rank_aug}")
    
    if rank_aug > rank_A:
        print("\\nNo solution exists")
        return None
    elif rank_A < A.cols:
        print("\\nInfinitely many solutions exist")
        return "infinite"
    else:
        print("\\nUnique solution exists")
        return "unique"

# When solving a system Ax = b:
A = Matrix([[...], [...], [...]])  # coefficient matrix
b = Matrix([[...], [...], [...]])  # right-hand side

# Analyze system
result = analyze_system(A, b)

if result == "infinite":
    # Get parametric form of solution
    aug = Matrix(A.row_join(b))
    rref, pivots = aug.rref()
    
    # Get free variables
    vars = symbols('x y z')  # adjust variable names as needed
    free_vars = [var for i, var in enumerate(vars) if i not in pivots]
    
    print("\\nParametric solution (t is free parameter):")
    for i, var in enumerate(vars):
        if i in pivots:
            row = pivots.index(i)
            expr = rref[row, -1]
            for j, free_var in enumerate(free_vars):
                expr -= rref[row, pivots[-1] + 1 + j] * free_var
            print(f"{var} = {expr}")
        else:
            print(f"{var} = t")  # use different parameter names for multiple free variables
```
Always use this template when working with systems of equations to handle potential linear dependence correctly. """

def load_proof_repository():
    """Load the proof repository from the repository file"""
    repo_path = Path("Lebl-theorems-all.json")
    try:
        with open(repo_path, "r") as f:
            return json.load(f)
    except Exception as e:
        logger.error(f"Error loading proof repository: {str(e)}")
        return None

TOPIC_MAPPINGS = {
    "integration": ["integral", "integrable", "riemann", "integrate", "antiderivative"],
    "continuity": ["continuous", "discontinuous", "discontinuity", "uniformly continuous"],
    "sequences": ["sequence", "convergent", "divergent", "monotone", "subsequence"],
    "series": ["series", "sum", "convergent series", "power series"],
    "differentiation": ["derivative", "differentiable", "differential"],
    "limits": ["limit", "cluster point", "accumulation"],
    "functions": ["function", "mapping", "surjective", "injective", "bijective"],
    "bounded": ["bound", "bounded above", "bounded below", "supremum", "infimum"]
}

def get_related_terms(topic):
    """Get all related terms for a given topic"""
    # Get direct mappings
    related = TOPIC_MAPPINGS.get(topic.lower(), [])
    # Add the original topic
    related.append(topic.lower())
    # Remove duplicates while preserving order
    return list(dict.fromkeys(related))

def matches_topic(text, topic_terms):
    """Check if any topic terms appear in the text"""
    text_lower = text.lower()
    return any(term in text_lower for term in topic_terms)

def get_relevant_proofs(topic):
    """Get relevant proofs from repository based on topic, randomly selecting examples"""
    repository = load_proof_repository()
    if not repository:
        logger.error("Failed to load proof repository")
        return []
    
    logger.debug(f"Searching for proofs related to topic: {topic}")
    topic_terms = get_related_terms(topic)
    logger.debug(f"Related terms: {topic_terms}")
    
    relevant_proofs = []
    for theorem in repository.get("dataset", {}).get("theorems", []):
        # Check categories
        categories = theorem.get("categories", [])
        category_match = any(matches_topic(cat, topic_terms) for cat in categories)
        
        # Check contents
        contents = theorem.get("contents", [])
        content_match = any(matches_topic(content, topic_terms) for content in contents)
        
        # Check title
        title = theorem.get("title", "")
        title_match = matches_topic(title, topic_terms)
        
        if (category_match or content_match or title_match):
            if theorem.get("contents") and theorem.get("proofs"):
                proof_content = {
                    "title": theorem.get("title", ""),
                    "contents": theorem.get("contents", []),
                    "proofs": [p.get("contents", []) for p in theorem.get("proofs", [])]
                }
                relevant_proofs.append(proof_content)
                logger.debug(f"Found matching proof: {proof_content['title']}")
                logger.debug(f"Matched via: {'categories' if category_match else 'contents' if content_match else 'title'}")

    logger.debug(f"Found {len(relevant_proofs)} relevant proofs before sampling")
    
    # Randomly select 3 proofs if we have more than 3
    if len(relevant_proofs) > 3:
        selected = random.sample(relevant_proofs, 3)
        logger.debug("Selected proofs for enhancement:")
        for proof in selected:
            logger.debug(f"- {proof['title']}")
        return selected
    return relevant_proofs
    
def enhance_prompt_with_proofs(system_prompt, subject, topic):
    """Enhance the system prompt with relevant proofs if subject is Real Analysis"""
    if subject != "Real Analysis":
        logger.debug("Skipping proof enhancement - not Real Analysis")
        return system_prompt
        
    relevant_proofs = get_relevant_proofs(topic)
    if not relevant_proofs:
        logger.debug(f"No relevant proofs found for topic: {topic}")
        return system_prompt
    
    logger.debug(f"Enhancing prompt with {len(relevant_proofs)} proofs")
    
    # Add proof examples to the prompt
    proof_examples = "\n\nReference these proof examples for style and approach:\n"
    for proof in relevant_proofs:
        logger.debug(f"Adding proof: {proof['title']}")
        proof_examples += f"\nTheorem: {proof['title']}\n"
        proof_examples += "Statement: " + " ".join(proof['contents']) + "\n"
        if proof['proofs']:
            first_proof = " ".join(proof['proofs'][0])
            logger.debug(f"Proof length: {len(first_proof)} characters")
            proof_examples += "Proof: " + first_proof + "\n"
    
    # Add specific instructions for using the examples
    enhanced_prompt = f"""{system_prompt}
ADDITIONAL PROOF GUIDELINES:
1. Consider the following proof examples from established textbooks
2. Maintain similar level of rigor and detail
3. Use similar proof techniques where applicable
4. Follow similar notation and presentation style
{proof_examples}"""
    
    return enhanced_prompt
    

def get_difficulty_parameters(difficulty_level):
    """Return specific parameters and constraints based on difficulty level"""
    parameters = {
        1: {  # Very Easy
            "description": "very easy, suitable for beginners",
            "constraints": [
                "Use only basic concepts and straightforward calculations",
                "Break complex problems into smaller, guided steps",
                "Provide hints within the question when needed",
                "Use simple numbers and avoid complex algebraic expressions"
            ],
            "example_style": "Similar to standard homework problems",
            "model": "claude-3-5-sonnet-20241022"
        },
        2: {  # Easy
            "description": "easy, but requiring some thought",
            "constraints": [
                "Use basic concepts with minor complications",
                "Include two-step problems",
                "Minimal guidance provided",
                "Use moderately complex numbers or expressions"
            ],
            "example_style": "Similar to quiz questions",
            "model": "claude-3-5-sonnet-20241022"
        },
        3: {  # Intermediate
            "description": "intermediate difficulty, testing deeper understanding",
            "constraints": [
                "Combine 2-3 related concepts",
                "Include some non-obvious solution paths",
                "Require multi-step reasoning",
                "Use moderate algebraic complexity"
            ],
            "example_style": "Similar to midterm exam questions",
            "model": "claude-3-5-sonnet-20241022"
        },
        4: {  # Difficult
            "description": "challenging, requiring strong mathematical maturity",
            "constraints": [
                "Combine multiple concepts creatively",
                "Require insight and deep understanding",
                "Include non-standard approaches",
                "Use sophisticated mathematical reasoning"
            ],
            "example_style": "Similar to final exam questions",
            "model": "claude-3-5-sonnet-20241022"
        },
        5: {  # Very Difficult
            "description": "very challenging, testing mastery and creativity at a graduate level",
            "constraints": [
                "Create novel applications of theoretical concepts",
                "Require graduate-level mathematical reasoning",
                "Combine multiple advanced topics in unexpected ways",
                "Demand creative problem-solving approaches",
                "Include rigorous proof construction",
                "Require synthesis across mathematical domains",
                "Test deep theoretical understanding"
            ],
            "example_style": "Similar to graduate qualifying exams or advanced competition problems",
            "model": "claude-3-5-sonnet-20241022"
        }
    }
    
    return parameters.get(difficulty_level)

def create_latex_document(content, questions_only=False):
    """Create a complete LaTeX document"""
    try:
        latex_header = r"""\documentclass{article}
\usepackage{amsmath,amssymb}
\usepackage[margin=1in]{geometry}
\begin{document}
\title{Mathematics Question}
\maketitle
"""
        latex_footer = r"\end{document}"
        
        if questions_only:
            # Modified to handle single question
            processed_content = content.split('Solution:')[0]
            content = processed_content
        
        full_document = f"{latex_header}\n{content}\n{latex_footer}"
        logger.debug(f"Created {'questions-only' if questions_only else 'full'} LaTeX document")
        return full_document
    except Exception as e:
        logger.error(f"Error creating LaTeX document: {str(e)}")
        raise

def save_to_temp_file(content, filename):
    """Save content to a temporary file and return the path"""
    try:
        temp_dir = Path(tempfile.gettempdir()) / "math_test_files"
        temp_dir.mkdir(exist_ok=True)
        file_path = temp_dir / filename
        file_path.write_text(content, encoding='utf-8')
        logger.debug(f"Saved content to temporary file: {file_path}")
        return str(file_path)
    except Exception as e:
        logger.error(f"Error saving temporary file: {str(e)}")
        raise

def get_problem_type_addition(question_type):
    """Return specific requirements based on problem type"""
    problem_type_additions = {
        "application": """
The application question MUST:
- Present a real-world scenario or practical problem
- Require modeling the situation mathematically
- Connect abstract mathematical concepts to concrete situations
- Include realistic context and data
- Require students to:
    1. Identify relevant mathematical concepts
    2. Translate the practical problem into mathematical terms
    3. Solve using appropriate mathematical techniques
    4. Interpret the results in the context of the original problem
Example contexts might include:
- Physics applications (motion, forces, work)
- Engineering scenarios (optimization, rates of change)
- Economics problems (cost optimization, growth models)
- Biological systems (population growth, reaction rates)
- Business applications (profit maximization, inventory management)
- Social science applications (demographic models, social network analysis)
- Data science applications (regression, statistical analysis)
""",
        "proof": """
The proof question MUST:
- Require a formal mathematical proof
- Focus on demonstrating logical reasoning
- Require justification for each step
- Emphasize theoretical understanding
The proof question MAY NOT:
- Include Real-world applications or scenarios
- Include Pure computation problems
- Ask only for numerical answers
""",
        "computation": """
The computation question MUST:
- Require specific algebraic calculations
- Focus on mathematical techniques
- Have concrete answers in the form of algebraic expressions (about half of questions) or numbers (about half of questions)
- Test procedural knowledge
The computation question MAY NOT:
- Include extended real-world applications or scenarios
- Ask for a proof
"""
    }
    return problem_type_additions.get(question_type, "")

def generate_question(subject, difficulty, question_type):
    """Generate a single math question with additional verification for difficulty 5"""
    try:
        if not os.environ.get('ANTHROPIC_API_KEY'):
            logger.error("Anthropic API key not found")
            return "Error: Anthropic API key not configured", None, None
        
        logger.debug(f"Generating {question_type} question for subject: {subject} at difficulty level: {difficulty}")
        
        # Check rate limit
        now = datetime.now()
        while request_history and (now - request_history[0]) > timedelta(days=1):
            request_history.popleft()
        if len(request_history) >= MAX_REQUESTS_PER_DAY:
            return "Daily request limit reached. Please try again tomorrow.", None, None
        
        request_history.append(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"],
            "Differential Equations": ["first order equations", "second order equations", "systems", "stability analysis"],
            "Real Analysis": ["sequences", "series", "continuity", "differentiation", "integration"],
            "Complex Analysis": ["complex functions", "analyticity", "contour integration", "residues"],
            "Abstract Algebra": ["groups", "rings", "fields", "homomorphisms"],
            "Probability Theory": ["probability spaces", "random variables", "distributions", "limit theorems"],
            "Numerical Analysis": ["approximation", "interpolation", "numerical integration", "error analysis"],
            "Topology": ["metric spaces", "continuity", "compactness", "connectedness"]
        }
        
        selected_topic = random.choice(topics.get(subject, ["general"]))
        logger.debug(f"Selected topic: {selected_topic}")
        
        difficulty_params = get_difficulty_parameters(difficulty)
        problem_type_addition = get_problem_type_addition(question_type)

        system_prompt = f"""You are an expert mathematics professor creating a {difficulty_params['description']} exam question.
STRICT REQUIREMENTS:
1. Write exactly 1 {question_type} question on {subject} covering {selected_topic}.
2. Difficulty Level Guidelines:
   {difficulty_params['description'].upper()}
   Follow these specific constraints:
   {chr(10).join(f'   - {c}' for c in difficulty_params['constraints'])}
   
   {problem_type_addition}
3. Style Reference:
   Question should be {difficulty_params['example_style']}
4. For LaTeX formatting:
   - Make sure that the question statement uses proper LaTeX math mode 
   - Use $ for inline math
   - Use $$ on separate lines for equations and solutions
   - Put each solution step on its own line in $$ $$
   - DO NOT use \\begin{{aligned}} or similar environments
5. Include a detailed solution
   - Begin the solution with a heading in bold and larger font size: Original Solution
   - If the question involves geometry make sure to identify any general geometric formulas that apply, For example:
        * Areas/volumes of common shapes and solids
        * Cross-sectional areas of geometric figures
        * Arc lengths and sector areas
   - When setting up differential equations either in calculus or differential equation applications
        * carefully consider the direction of change in variables
        * ensure integration bounds align with the physical direction of the process being modeled
6. Maintain clear formatting
7. At the end of the solution output, print SymPy code that you would use to solve or verify the main equations in the question 
   and give this section a heading in bold and larger font size: SymPy Verification
8. Observe the folloiwng SymPy Guidelines
{SYMPY_GUIDELINES}"""

#Consider
   #When writing SymPy code:
   #- Use FiniteSet(1, 2, 3) instead of Set([1, 2, 3]) for finite sets
   #- Import specific functions instead of using 'from sympy import *'
   #- Print results of each calculation step

   # Enhance the prompt with proof examples if applicable
        if subject == "Real Analysis" and question_type == "proof":
            system_prompt = enhance_prompt_with_proofs(system_prompt, subject, selected_topic)
    
        logger.debug("Sending request to Anthropic API")
        message = anthropic.messages.create(
            model=difficulty_params['model'],
            max_tokens=4096,
            temperature=0.7,
            messages=[{
                "role": "user",
                "content": f"{system_prompt}\n\nWrite a question for {subject}."
            }]
        )
        
        if not hasattr(message, 'content') or not message.content:
            logger.error("No content received from Anthropic API")
            return "Error: No content received from API", None, None
        
        response_text = message.content[0].text
        logger.debug("Successfully received response from Anthropic API")

        # Execute SymPy code and append results
        sympy_output = extract_and_run_sympy_code_simple(response_text)

        if sympy_output:
            # Check if SymPy ran successfully
            if "Error" not in sympy_output:
                resolution_text, has_discrepancy, revised_solution = check_and_resolve_discrepancy(response_text, sympy_output)
                response_text = f"{response_text}\n\nSymPy Verification Results:\n```\n{sympy_output}\n```\n\nVerification Analysis:\n{resolution_text}"
                
                # For difficulty level 5 AND when there's a discrepancy with a revised solution
                if has_discrepancy and revised_solution:
                    logger.debug("Performing final verification for difficulty 5 problem with discrepancy")
                    final_verification = perform_final_verification(revised_solution)
                    response_text += "\n\nFinal Expert Verification:\n" + final_verification
            else:
                response_text += f"\n\nSymPy Verification Results:\n```\n{sympy_output}\n```"
        
        # Create LaTeX content
        questions_latex = create_latex_document(response_text, questions_only=True)
        full_latex = create_latex_document(response_text, questions_only=False)
        
        # Save to temporary files
        questions_path = save_to_temp_file(questions_latex, "question.tex")
        full_path = save_to_temp_file(full_latex, "full_question.tex")
        
        logger.debug("Successfully created temporary files")
        
        return response_text, questions_path, full_path
            
    except Exception as e:
        logger.error(f"Error generating question: {str(e)}")
        return f"Error: {str(e)}", None, None
 
def extract_and_run_sympy_code_simple(response_text):
    """
    Extract SymPy code from the response and execute it.
    """
    try:
        # Extract code
        sympy_start = response_text.find('```python')
        if sympy_start == -1:
            return "No SymPy code found in the response."
        
        code_start = response_text.find('\n', sympy_start) + 1
        code_end = response_text.find('```', code_start)
        if code_end == -1:
            return "Malformed SymPy code block."
        
        sympy_code = response_text[code_start:code_end].strip()
        
        # Import SymPy at the module level
        import sympy
        
        # Create globals dict with all SymPy functions
        globals_dict = {}
        globals_dict.update(vars(sympy))
        globals_dict.update({
            'print': print,
            'float': float,
            'Symbol': sympy.Symbol,
            'symbols': sympy.symbols,
            'solve': sympy.solve,
            'sqrt': sympy.sqrt,
            'pi': sympy.pi,
            'diff': sympy.diff,
            'integrate': sympy.integrate,
            'simplify': sympy.simplify,
            'Matrix': sympy.Matrix
        })
        
        # Remove the sympy import line from the code if present
        lines = sympy_code.split('\n')
        filtered_lines = [line for line in lines if not line.strip().startswith('from sympy import') and not line.strip().startswith('import sympy')]
        modified_code = '\n'.join(filtered_lines)
        
        # Capture output
        import io
        from contextlib import redirect_stdout
        
        output_buffer = io.StringIO()
        with redirect_stdout(output_buffer):
            exec(modified_code, globals_dict)
        return output_buffer.getvalue().strip() or "No output produced"
    
    except Exception as e:
        return f"Error executing SymPy code: {str(e)}"

def check_and_resolve_discrepancy(initial_response, sympy_output):
    """
    Compare the SymPy output with the initial response and resolve any discrepancies.
    Returns tuple of (resolution_text, has_discrepancy, revised_solution)
    """
    try:
        resolution_prompt = f"""Here is a mathematics question with two answers.
        The first, called Original solution, is a complete solution.
        The second, called SymPy Verification, will only provide the final answer.

        Begin this section with a heading in bold and larger font size: Comparison of SymPy Verifiation with Original Solution
        
        If the SymPy Verification answer is consistent with the final answer Original solution,
        then please say that they are consistent and briefly explain why. 
        
        If the two answers are inconsistent with each other then please:
        1. Identify which solution is correct
        2. Explain the error in the incorrect solution
        3. Write "Here is the revised complete solution:" and then write out the ENTIRE solution from beginning 
           to end, including all parts that were correct and the corrections for any incorrect parts. 
           Do not refer to the original solution or say things like "the rest remains the same" - write 
           out everything in full. Begin this section with a heading in bold and larger font size: Revised Complete Solution

Original solution:
{initial_response}

SymPy Verification Results:
{sympy_output}

Please maintain the same LaTeX formatting as the original solution."""

        # Make API call for resolution
        message = anthropic.messages.create(
            model="claude-3-5-sonnet-20241022",
            max_tokens=4096,
            temperature=0.2,
            messages=[{
                "role": "user",
                "content": resolution_prompt
            }]
        )
        
        resolution_text = message.content[0].text
        
        # Check if resolution contains new SymPy code
        if "```python" in resolution_text:
            new_sympy_output = extract_and_run_sympy_code_simple(resolution_text)
            resolution_text += "\n\nNew SymPy Verification Results:\n```\n" + new_sympy_output + "\n```"
        
        # Determine if there was a discrepancy that required a revised solution
        # Check for any indication of inconsistency or error
        inconsistency_phrases = [
            "inconsistent", "inconsistency", "incorrect", "error", "wrong",
            "differs", "different", "discrepancy", "mistaken", "mistake"
        ]
        has_discrepancy = any(phrase in resolution_text.lower() for phrase in inconsistency_phrases)
        
        # Look for the required marker phrase and extract the solution after it
        marker = "Here is the revised complete solution:"
        revised_solution = None
        
        if has_discrepancy:
            # Split at the marker
            if marker in resolution_text:
                parts = resolution_text.split(marker, maxsplit=1)
                if len(parts) > 1:
                    revised_solution = parts[1].strip()
                    # If the solution seems too short (might be partial), don't accept it
                    if len(revised_solution) < 100:  # Rough minimum length for a complete solution
                        revised_solution = None
            
            # If we didn't find a complete solution, force a recheck
            if not revised_solution:
                logger.debug("Initial solution extraction failed, requesting a complete solution")
                # Make a new API call specifically requesting a complete solution
                complete_solution_prompt = f"""The previous solution had inconsistencies. Please provide a complete solution 
                from beginning to end. Start your response with exactly this phrase:
                "Here is the revised complete solution:"
                Then write out the entire solution, including all parts both correct and corrected.
                Do not refer to the original solution or say any parts remain the same.
                
                Original problem and verification results:
                {initial_response}
                
                SymPy Results:
                {sympy_output}"""
                
                try:
                    message = anthropic.messages.create(
                        model="claude-3-5-sonnet-20241022",
                        max_tokens=4096,
                        temperature=0.2,
                        messages=[{"role": "user", "content": complete_solution_prompt}]
                    )
                    
                    new_response = message.content[0].text
                    if marker in new_response:
                        parts = new_response.split(marker, maxsplit=1)
                        if len(parts) > 1:
                            revised_solution = parts[1].strip()
                except Exception as e:
                    logger.error(f"Error in solution recheck: {str(e)}")
        
        return resolution_text, has_discrepancy, revised_solution
            
    except Exception as e:
        logger.error(f"Error in discrepancy resolution: {str(e)}")
        return f"Error in resolution: {str(e)}", False, None

def perform_final_verification(revised_solution):
    """
    Perform a final verification of the revised solution for difficulty level 5 problems.
    """
    verification_prompt = f"""As an expert mathematician, please carefully verify this revised solution to an advanced mathematics problem.

Revised Solution to Verify:
{revised_solution}

Please follow these steps exactly:

1. First, analyze the solution for:
   - Mathematical correctness
   - Missing cases or assumptions
   - Completeness and rigor
   - Necessary conditions and edge cases
   - Any subtle errors or oversights

2. After your analysis, write exactly this phrase:
   "Here is the complete verified solution:"

3. Then write out the ENTIRE solution from beginning to end, including:
   - All correct parts from the original solution
   - All needed corrections
   - All additional cases and verifications
   - Any missing steps or assumptions
   - Any necessary additional proofs or derivations

Your complete solution must:
- Be completely self-contained
- Not refer to the original solution
- Show every step of the calculation
- Include all necessary verifications
- Maintain proper LaTeX formatting with $ for inline math and $ on separate lines
- Include any relevant SymPy code for verification

Begin this section with a heading in bold and larger font size: Final Verified Solution
Remember to write out the complete solution even if you only need to add a few steps - the goal is to have a single, complete, verified solution that includes everything necessary for full mathematical rigor."""

    try:
        # Make API call for final verification
        message = anthropic.messages.create(
            model="claude-3-5-sonnet-20241022",
            max_tokens=4096,
            temperature=0.2,
            messages=[{
                "role": "user",
                "content": verification_prompt
            }]
        )
        
        verification_result = message.content[0].text
        
        # If verification includes new SymPy code, run it
        if "```python" in verification_result:
            new_sympy_output = extract_and_run_sympy_code_simple(verification_result)
            verification_result += "\n\nFinal SymPy Verification:\n```\n" + new_sympy_output + "\n```"
        
        return verification_result
    except Exception as e:
        logger.error(f"Error in final verification: {str(e)}")
        return f"Error in final verification: {str(e)}"
        
# Create Gradio interface
with gr.Blocks() as interface:
    gr.Markdown("# Advanced Mathematics Question Generator")
    gr.Markdown("""Generates a unique university-level mathematics question with solution using Claude 3.
    Each question features different topics and difficulty levels. Limited to 25 requests per day.""")
    
    with gr.Row():
        with gr.Column():
            subject_dropdown = gr.Dropdown(
                choices=[
                    "Single Variable Calculus",
                    "Multivariable Calculus", 
                    "Linear Algebra",
                    "Differential Equations",
                    "Real Analysis",
                    "Complex Analysis",
                    "Abstract Algebra",
                    "Probability Theory",
                    "Numerical Analysis",
                    "Topology"
                ],
                label="Select Mathematics Subject",
                info="Choose a subject for the question"
            )
            
            difficulty_slider = gr.Slider(
                minimum=1,
                maximum=5,
                step=1,
                value=3,
                label="Difficulty Level",
                info="1: Very Easy, 2: Easy, 3: Moderate, 4: Difficult, 5: Very Difficult"
            )
            
            question_type = gr.Radio(
                choices=["computation", "proof", "application"],
                label="Question Type",
                info="Select the type of question you want",
                value="computation"
            )
    
    generate_btn = gr.Button("Generate Question")
    
    output_text = gr.Markdown(
        label="Generated Question Preview",
        latex_delimiters=[
            {"left": "$$", "right": "$$", "display": True},
            {"left": "$", "right": "$", "display": False}
        ]
    )
    
    with gr.Row():
        questions_file = gr.File(label="Question Only (LaTeX)")
        full_file = gr.File(label="Question with Solution (LaTeX)")
    
    generate_btn.click(
        generate_question,
        inputs=[
            subject_dropdown,
            difficulty_slider,
            question_type
        ],
        outputs=[output_text, questions_file, full_file]
    )

if __name__ == "__main__":
    logger.info("Starting application")
    interface.launch()