feat: update package exports and environment configuration

Export LLMBot class and add environment variables for LiteLLM proxy configuration.

Co-Authored-By: Claude <noreply@anthropic.com>

Author: S1M0N38

.envrc.example

@@ -2,7 +2,7 @@
 # Copy this file to .envrc and fill in your actual values.
 
 # Load the virtual environment
-# source .venv/bin/activate
+source .venv/bin/activate
 
 # Example environment variables:
 # export MY_VARIABLE="some_value"
@@ -12,9 +12,45 @@
 export PYTHONUNBUFFERED="1"
 export PYTHONPATH="${PWD}/src:${PYTHONPATH}"
 
+# Disable git lfs
+export GIT_LFS_SKIP_SMUDGE=1
+
 # Example: Django settings module
 # export DJANGO_SETTINGS_MODULE="myproject.settings.local"
 
 # Example: Flask app
 # export FLASK_APP="myapp:create_app()"
 # export FLASK_ENV="development"
+
+# LITELLM PROXY CONFIGURATION
+# The bot now uses LiteLLM proxy for unified model access
+export LITELLM_MODEL="cerebras-gpt-oss-120b"           # Available models: cerebras-gpt-oss-120b, groq-qwen32b, local-deepseek, openai-gpt4o, anthropic-sonnet
+export LITELLM_PROXY_URL="http://localhost:4000"
+export LITELLM_API_KEY="sk-balatrollm-proxy-key"
+
+# PROVIDER API KEYS (used by LiteLLM proxy)
+# You need to set the API keys for the providers you want to use
+
+# CEREBRAS
+export CEREBRAS_API_KEY="your-cerebras-api-key"
+
+# GROQ
+export GROQ_API_KEY="your-groq-api-key"
+
+# OPENAI (optional)
+export OPENAI_API_KEY="your-openai-api-key"
+
+# ANTHROPIC (optional)
+export ANTHROPIC_API_KEY="your-anthropic-api-key"
+
+# LMSTUDIO (for local-deepseek model)
+# No API key needed, just make sure LM Studio is running on localhost:1234
+
+# TTS
+
+# Edge-TTS
+export TTS_API_KEY="your_api_key_here"
+export TTS_MODEL="tts-1"
+export TTS_VOICE="en-US-AvaNeural"
+export TTS_SPEED=1.0
+export TTS_BASE_URL="https://api.groq.com/openai/v1"

src/balatrollm/__init__.py

@@ -1,5 +1,125 @@
 """Balatrollm project."""
 
+import argparse
+import asyncio
+import os
+import sys
+from pathlib import Path
+
+from .llm import LLMBot
+
 
 def main() -> None:
-    print("Hello from balatrollm!")
+    """Main CLI entry point for balatrollm."""
+    parser = argparse.ArgumentParser(
+        description="LLM-powered Balatro bot using LiteLLM proxy",
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog="""
+Examples:
+  balatrollm --model cerebras-gpt-oss-120b
+  balatrollm --model groq-qwen32b --proxy-url http://localhost:4000
+  balatrollm --list-models
+        """,
+    )
+
+    parser.add_argument(
+        "--model",
+        default=os.getenv("LITELLM_MODEL", "cerebras-gpt-oss-120b"),
+        help="Model name to use from LiteLLM proxy (default: cerebras-gpt-oss-120b)",
+    )
+
+    parser.add_argument(
+        "--proxy-url",
+        default=os.getenv("LITELLM_PROXY_URL", "http://localhost:4000"),
+        help="LiteLLM proxy URL (default: http://localhost:4000)",
+    )
+
+    parser.add_argument(
+        "--api-key",
+        default=os.getenv("LITELLM_API_KEY", "sk-balatrollm-proxy-key"),
+        help="LiteLLM proxy API key (default: sk-balatrollm-proxy-key)",
+    )
+
+    parser.add_argument(
+        "--list-models",
+        action="store_true",
+        help="List available models from the proxy and exit",
+    )
+
+    parser.add_argument(
+        "--config",
+        default="config/litellm.yaml",
+        help="Path to LiteLLM configuration file (default: config/litellm.yaml)",
+    )
+
+    parser.add_argument(
+        "--verbose", "-v", action="store_true", help="Enable verbose logging"
+    )
+
+    args = parser.parse_args()
+
+    # Configure logging
+    import logging
+
+    level = logging.DEBUG if args.verbose else logging.INFO
+    logging.basicConfig(
+        level=level, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s"
+    )
+    logger = logging.getLogger(__name__)
+
+    # Check if config file exists
+    config_path = Path(args.config)
+    if not config_path.exists():
+        logger.error(f"LiteLLM config file not found: {config_path}")
+        logger.error(f"Please create the config file or start the proxy manually:")
+        logger.error(f"  litellm --config {config_path}")
+        sys.exit(1)
+
+    # Create and run the bot
+    asyncio.run(run_bot(args))
+
+
+async def run_bot(args) -> None:
+    """Run the Balatro bot with the given arguments."""
+    bot = LLMBot(model=args.model, proxy_url=args.proxy_url, api_key=args.api_key)
+
+    # List models if requested
+    if args.list_models:
+        print("Checking available models from LiteLLM proxy...")
+        if not await bot.validate_proxy_connection():
+            print(f"❌ Cannot connect to LiteLLM proxy at {args.proxy_url}")
+            print(f"Please start the proxy with: litellm --config {args.config}")
+            sys.exit(1)
+
+        models = await bot.list_available_models()
+        if models:
+            print("✅ Available models:")
+            for model in models:
+                print(f"  - {model}")
+        else:
+            print("❌ No models available or failed to retrieve models")
+        return
+
+    # Validate proxy connection and model before starting game
+    print(f"🤖 Starting Balatro LLM Bot with model: {args.model}")
+
+    if not await bot.validate_proxy_connection():
+        print(f"❌ Cannot connect to LiteLLM proxy at {args.proxy_url}")
+        print(f"Please start the proxy with: litellm --config {args.config}")
+        sys.exit(1)
+
+    if not await bot.validate_model_exists():
+        print(f"❌ Model '{args.model}' not available")
+        print("Use --list-models to see available models")
+        sys.exit(1)
+
+    print("✅ Proxy connection validated, starting game...")
+
+    try:
+        with bot:
+            await bot.play_game()
+    except KeyboardInterrupt:
+        print("\n🛑 Game interrupted by user")
+    except Exception as e:
+        print(f"❌ Game failed: {e}")
+        sys.exit(1)