test_llm.py

# Quick test for LLM integration
from transformers import pipeline
import warnings

warnings.filterwarnings('ignore')

print("Testing LLM integration...")
print("Loading model...")

try:
    llm_generator = pipeline(
        "text-generation",
        model="distilgpt2",
        max_length=200,
        device=-1
    )
    print("✅ Model loaded successfully!")
    
    # Test generation
    prompt = """As an agricultural expert for Maharashtra, provide specific farming recommendations:

Weather: 6 warning days with overcast conditions
Severity: WARNING conditions on Saturday, Tuesday, Wednesday, Thursday, Friday, Sunday. 

Recommendations for farmers:
1. Crop protection:"""
    
    print("\nGenerating test recommendation...")
    response = llm_generator(
        prompt,
        max_new_tokens=100,
        num_return_sequences=1,
        temperature=0.7,
        do_sample=True,
        pad_token_id=50256
    )
    
    generated_text = response[0]['generated_text']
    recommendations = generated_text[len(prompt):].strip()
    
    print("\n✅ Generated Recommendation:")
    print(recommendations)
    print("\n✅ LLM integration test successful!")
    
except Exception as e:
    print(f"❌ Error: {e}")