Upload 3 files

core/dependencies.py

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+"""
+FastAPI Dependencies
+"""
+
+from fastapi import Depends, HTTPException, Request
+from services.polar_service import PolarService
+from core.exceptions import RateLimitException
+
+async def get_current_user(request: Request):
+    # Extract user from request (simplified)
+    user_id = request.headers.get("X-User-ID", "anonymous")
+    return user_id
+
+async def verify_premium(user_id: str = Depends(get_current_user)):
+    # This would check Polar subscription
+    return True  # Placeholder
+
+def rate_limit_check(user_id: str = Depends(get_current_user)):
+    # Implement rate limiting logic here
+    pass

core/exceptions.py

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+"""
+Custom Exceptions for NeuraPrompt
+"""
+
+class NeuraPromptException(Exception):
+    """Base exception for all NeuraPrompt errors"""
+    def __init__(self, message: str, code: str = "INTERNAL_ERROR"):
+        self.message = message
+        self.code = code
+        super().__init__(self.message)
+
+
+class RateLimitException(NeuraPromptException):
+    def __init__(self, message: str = "Rate limit exceeded"):
+        super().__init__(message, "RATE_LIMIT")
+
+
+class ModelNotFoundException(NeuraPromptException):
+    def __init__(self, model_id: str):
+        super().__init__(f"Model '{model_id}' not found", "MODEL_NOT_FOUND")
+
+
+class PolarVerificationException(NeuraPromptException):
+    def __init__(self, message: str = "Polar verification failed"):
+        super().__init__(message, "POLAR_ERROR")

core/logging_config.py

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+"""
+Centralized Logging Configuration
+"""
+
+import logging
+import sys
+from datetime import datetime
+
+def setup_logging():
+    logging.basicConfig(
+        level=logging.INFO,
+        format="%(asctime)s | %(levelname)-8s | %(name)s | %(message)s",
+        handlers=[
+            logging.StreamHandler(sys.stdout),
+            logging.FileHandler("neuraprompt.log", encoding="utf-8")
+        ]
+    )
+    
+    # Reduce noise from libraries
+    logging.getLogger("httpx").setLevel(logging.WARNING)
+    logging.getLogger("pymongo").setLevel(logging.WARNING)
+    
+    return logging.getLogger("neuraprompt")