Update app.py

app.py

@@ -25,6 +25,75 @@ anthropic = Anthropic(
 MAX_REQUESTS_PER_DAY = 25
 request_history = deque(maxlen=1000)
 
+import json
+from pathlib import Path
+
+def load_proof_repository():
+    """Load the proof repository from the repository file"""
+    repo_path = Path("naturalproofs_trench.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
+
+def get_relevant_proofs(topic):
+    """Get relevant proofs from repository based on topic, randomly selecting examples"""
+    repository = load_proof_repository()
+    if not repository:
+        return []
+    
+    # Extract relevant proofs based on topic
+    relevant_proofs = []
+    for theorem in repository.get("dataset", {}).get("theorems", []):
+        # Add proofs that match the topic
+        if any(topic.lower() in content.lower() for content in theorem.get("contents", [])):
+            # Only include if it has both contents and proofs
+            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)
+    
+    # Randomly select 3 proofs if we have more than 3
+    if len(relevant_proofs) > 3:
+        return random.sample(relevant_proofs, 3)
+    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":
+        return system_prompt
+        
+    relevant_proofs = get_relevant_proofs(topic)
+    if not relevant_proofs:
+        return system_prompt
+        
+    # Add proof examples to the prompt
+    proof_examples = "\n\nReference these proof examples for style and approach:\n"
+    for proof in relevant_proofs[:3]:  # Limit to 3 examples to manage token usage
+        proof_examples += f"\nTheorem: {proof['title']}\n"
+        proof_examples += "Statement: " + " ".join(proof['contents']) + "\n"
+        if proof['proofs']:
+            proof_examples += "Proof: " + " ".join(proof['proofs'][0]) + "\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 = {
@@ -282,7 +351,11 @@ STRICT REQUIREMENTS:
    #- 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'],