config.py

"""
Configuration management for LLM Playground.
"""

import os
from pathlib import Path

# Project directories
PROJECT_ROOT = Path(__file__).parent
LOGS_DIR = PROJECT_ROOT / "logs"
EXPERIMENTS_DIR = PROJECT_ROOT / "experiments"

# Ensure directories exist
LOGS_DIR.mkdir(exist_ok=True)
EXPERIMENTS_DIR.mkdir(exist_ok=True)

# Default model settings
DEFAULT_PROVIDER = "ollama"
DEFAULT_MODEL = "llama2"
DEFAULT_TEMPERATURE = 0.7
DEFAULT_MAX_TOKENS = 256
DEFAULT_TOP_P = 0.9

# Ollama settings
OLLAMA_BASE_URL = os.getenv("OLLAMA_BASE_URL", "http://localhost:11434")

# OpenAI settings (optional)
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY", "")

# Logging settings
LOG_TO_FILE = True
LOG_TO_CONSOLE = False
LOG_FORMAT = "json"  # "json" or "csv"

# UI settings (for Streamlit)
APP_TITLE = "🚀 LLM Playground"
APP_DESCRIPTION = """
Experiment with Large Language Models and understand their behavior.

Select a model, adjust parameters, and observe how they affect outputs.
All interactions are logged for later analysis.
"""

# Available experiments
EXPERIMENTS = {
    "zero_shot": {
        "name": "Zero-Shot Prompting",
        "description": "Test model's ability to perform tasks without examples",
    },
    "few_shot": {
        "name": "Few-Shot Prompting",
        "description": "Compare performance with and without examples",
    },
    "temperature": {
        "name": "Temperature Effects",
        "description": "See how temperature affects creativity and determinism",
    },
    "context_window": {
        "name": "Context Window Analysis",
        "description": "Test behavior with varying prompt lengths",
    },
    "prompt_sensitivity": {
        "name": "Prompt Sensitivity",
        "description": "Observe how small changes affect outputs",
    },
}

# Sampling parameter ranges
TEMPERATURE_RANGE = (0.0, 2.0)
TEMPERATURE_STEP = 0.1
TOP_P_RANGE = (0.0, 1.0)
TOP_P_STEP = 0.05
MAX_TOKENS_RANGE = (1, 2048)
MAX_TOKENS_DEFAULT = 256

# Cost tracking (for OpenAI)
TRACK_COSTS = True

# Performance
REQUEST_TIMEOUT = 300  # seconds