from transformers import pipeline
import torch

# Try multiple fallback options
model_options = [
    "microsoft/DialoGPT-medium",
    "microsoft/DialoGPT-small", 
    "gpt2",
    "distilgpt2"
]

pipe = None
model_id = None

for model in model_options:
    try:
        print(f"🔄 Trying to load model: {model}")
        pipe = pipeline(
            "text-generation",
            model=model,
            torch_dtype="auto",
            device_map="auto",
        )
        model_id = model
        print(f"✅ Model '{model_id}' loaded successfully!")
        break
    except Exception as e:
        print(f"❌ Failed to load {model}: {e}")
        continue

if pipe is None:
    print("❌ Could not load any model. Please check your internet connection.")
    # Create a dummy pipeline for testing
    class DummyPipe:
        def __call__(self, *args, **kwargs):
            return [{"generated_text": "I'm sorry, but I cannot connect to download the AI model. Please check your internet connection and try again."}]
        
        @property
        def tokenizer(self):
            class DummyTokenizer:
                eos_token_id = None
            return DummyTokenizer()
    
    pipe = DummyPipe()
    model_id = "dummy"