Delete compile_model.py

compile_model.py

@@ -1,73 +0,0 @@
-# compile_model.py
-"""
-With transformers, model downloading and caching is automatic.
-This script just performs a warmup to:
-1. Download model during Docker build
-2. Compile CUDA kernels
-3. Verify installation
-"""
-import os
-import logging
-from datetime import datetime
-
-logging.basicConfig(level=logging.INFO)
-logger = logging.getLogger(__name__)
-
-# Import shared model manager
-from shared_models import get_shared_llama
-
-HF_TOKEN = os.getenv("HF_TOKEN") or os.getenv("HUGGINGFACEHUB_API_TOKEN")
-
-def warmup_model():
-    """
-    Warmup Llama-3.2-3B model:
-    - Downloads from HuggingFace Hub
-    - Loads with 4-bit quantization
-    - Runs test inference
-    """
-    logger.info("="*60)
-    logger.info("LLAMA-3.2-3B WARMUP")
-    logger.info("="*60)
-    
-    try:
-        # Get shared model instance
-        llama = get_shared_llama()
-        
-        # This triggers model download and loading
-        logger.info("Running warmup inference...")
-        
-        test_response = llama.generate(
-            system_prompt="You are a helpful educational assistant.",
-            user_message="Hello, this is a test warmup message.",
-            max_tokens=20,
-            temperature=0.7,
-        )
-        
-        logger.info(f"✅ Warmup successful")
-        logger.info(f"   Response preview: {test_response[:80]}...")
-        
-        # Get model info
-        info = llama.get_model_info()
-        logger.info("="*60)
-        logger.info("MODEL INFO")
-        logger.info("="*60)
-        for key, value in info.items():
-            logger.info(f"  {key}: {value}")
-        
-        logger.info("="*60)
-        logger.info("✅ MODEL READY FOR PRODUCTION")
-        logger.info("="*60)
-        
-        return True
-        
-    except Exception as e:
-        logger.error(f"❌ Warmup failed: {e}")
-        import traceback
-        traceback.print_exc()
-        return False
-
-
-if __name__ == "__main__":
-    success = warmup_model()
-    if not success:
-        exit(1)