example.py

#!/usr/bin/env python3
"""
Quick example script demonstrating LLM Playground usage.

Run this after setting up to verify everything works.
"""

import sys
from pathlib import Path

# Add project root to path
sys.path.insert(0, str(Path(__file__).parent))

from models import get_model
from logger import get_logger
from experiments.zero_shot import run_zero_shot_experiment
from experiments.few_shot import run_few_shot_experiment
from experiments.sampling_params import run_temperature_experiment


def print_section(title):
    """Print a formatted section header."""
    print("\n" + "="*80)
    print(f"  {title}")
    print("="*80 + "\n")


def main():
    """Run example experiments."""
    print_section("🚀 LLM Playground - Example Experiments")
    
    # Initialize
    print("Initializing...")
    logger = get_logger()
    
    try:
        # Connect to model
        print("Connecting to Ollama (llama2)...")
        model = get_model("ollama", "llama2")
        print("✅ Connected!\n")
        
        # Example 1: Simple generation
        print_section("Example 1: Simple Text Generation")
        
        prompt = "Explain what a neural network is in one sentence."
        print(f"Prompt: {prompt}\n")
        
        response = model.generate(
            prompt=prompt,
            temperature=0.7,
            max_tokens=100,
        )
        
        print(f"Response: {response.text}")
        print(f"\nMetrics: {response.total_tokens} tokens in {response.latency_ms:.0f}ms")
        
        logger.log_interaction(
            prompt=prompt,
            response=response,
            parameters={"temperature": 0.7, "max_tokens": 100},
            experiment_type="example_simple",
        )
        
        # Example 2: Zero-shot experiment
        print_section("Example 2: Zero-Shot Sentiment Analysis")
        
        task = 'Classify sentiment as Positive, Negative, or Neutral: "This product is amazing!"'
        print(f"Task: {task}\n")
        
        response = run_zero_shot_experiment(
            model=model,
            task=task,
            logger=logger,
            temperature=0.3,  # Lower for more deterministic
            max_tokens=10,
        )
        
        print(f"Classification: {response.text}")
        
        # Example 3: Temperature comparison
        print_section("Example 3: Temperature Effects")
        
        creative_prompt = "Write a creative opening line for a sci-fi story:"
        print(f"Prompt: {creative_prompt}")
        print("\nTesting temperatures: 0.1, 0.7, 1.5\n")
        
        temps = [0.1, 0.7, 1.5]
        results = run_temperature_experiment(
            model=model,
            prompt=creative_prompt,
            temperatures=temps,
            logger=logger,
            max_tokens=50,
            num_samples=1,
        )
        
        for temp in sorted(results.keys()):
            response = results[temp][0]
            print(f"Temperature {temp}:")
            print(f"  → {response.text[:100]}...")
            print()
        
        # Example 4: Few-shot learning
        print_section("Example 4: Few-Shot vs Zero-Shot")
        
        task = "It works fine, nothing special."
        examples = [
            ("I loved it!", "Positive"),
            ("Waste of money.", "Negative"),
        ]
        
        print("Examples provided:")
        for inp, out in examples:
            print(f"  \"{inp}\" → {out}")
        print(f"\nTest case: \"{task}\"\n")
        
        zero_shot_resp, few_shot_resp = run_few_shot_experiment(
            model=model,
            task=task,
            examples=examples,
            logger=logger,
            temperature=0.3,
            max_tokens=10,
        )
        
        print(f"Zero-shot result: {zero_shot_resp.text}")
        print(f"Few-shot result:  {few_shot_resp.text}")
        
        # Summary
        print_section("✅ Examples Complete!")
        
        print(f"All interactions logged to: {logger.get_log_file_path()}")
        print("\nNext steps:")
        print("  1. Run the Streamlit app: streamlit run app.py")
        print("  2. Try the CLI: python cli.py --help")
        print("  3. Read CONCEPTS.md for theory")
        print("  4. Check logs/ directory for detailed logs")
        print("\nHappy experimenting! 🎉\n")
        
    except Exception as e:
        print(f"\n❌ Error: {e}")
        print("\nTroubleshooting:")
        print("  1. Make sure Ollama is running: ollama serve")
        print("  2. Check that llama2 is installed: ollama pull llama2")
        print("  3. Verify connection: curl http://localhost:11434/api/tags")
        sys.exit(1)


if __name__ == "__main__":
    main()