import os from dotenv import load_dotenv, set_key from rich.panel import Panel from rich.prompt import Confirm, Prompt from skyvern.analytics import capture_setup_event from skyvern.utils.env_paths import resolve_backend_env_path from .console import console def update_or_add_env_var(key: str, value: str) -> None: """Update or add environment variable in .env file.""" env_path = resolve_backend_env_path() if not env_path.exists(): env_path.touch() defaults = { "ENV": "local", "ENABLE_OPENAI": "false", "OPENAI_API_KEY": "", "ENABLE_ANTHROPIC": "false", "ANTHROPIC_API_KEY": "", "ENABLE_AZURE": "false", "AZURE_DEPLOYMENT": "", "AZURE_API_KEY": "", "AZURE_API_BASE": "", "AZURE_API_VERSION": "", "ENABLE_AZURE_GPT4O_MINI": "false", "AZURE_GPT4O_MINI_DEPLOYMENT": "", "AZURE_GPT4O_MINI_API_KEY": "", "AZURE_GPT4O_MINI_API_BASE": "", "AZURE_GPT4O_MINI_API_VERSION": "", "ENABLE_GEMINI": "false", "GEMINI_API_KEY": "", "LLM_KEY": "", "SECONDARY_LLM_KEY": "", "BROWSER_TYPE": "chromium-headful", "MAX_SCRAPING_RETRIES": "0", "VIDEO_PATH": "./videos", "BROWSER_ACTION_TIMEOUT_MS": "5000", "MAX_STEPS_PER_RUN": "50", "LOG_LEVEL": "INFO", "LITELLM_LOG": "CRITICAL", "DATABASE_STRING": "postgresql+psycopg://skyvern@localhost/skyvern", "PORT": "8000", "ANALYTICS_ID": "anonymous", "ENABLE_LOG_ARTIFACTS": "false", } for k, v in defaults.items(): set_key(env_path, k, v) load_dotenv(env_path) set_key(env_path, key, value) os.environ[key] = value def setup_llm_providers() -> None: """Configure Large Language Model (LLM) Providers.""" console.print(Panel("[bold magenta]LLM Provider Configuration[/bold magenta]", border_style="purple")) console.print("[italic]Note: All information provided here will be stored only on your local machine.[/italic]") capture_setup_event("llm-start") model_options: list[str] = [] enabled_providers: list[str] = [] console.print("\n[bold blue]--- OpenAI Configuration ---[/bold blue]") console.print("To enable OpenAI, you must have an OpenAI API key.") enable_openai = Confirm.ask("Do you want to enable OpenAI?") if enable_openai: openai_api_key = Prompt.ask("Enter your OpenAI API key", password=True) if not openai_api_key: console.print("[red]Error: OpenAI API key is required. OpenAI will not be enabled.[/red]") else: update_or_add_env_var("OPENAI_API_KEY", openai_api_key) update_or_add_env_var("ENABLE_OPENAI", "true") enabled_providers.append("openai") model_options.extend( [ "OPENAI_GPT5_4", "OPENAI_GPT5", "OPENAI_GPT5_2", "OPENAI_GPT4_1", "OPENAI_O3", "OPENAI_O4_MINI", "OPENAI_GPT4O", ] ) else: update_or_add_env_var("ENABLE_OPENAI", "false") console.print("\n[bold blue]--- Anthropic Configuration ---[/bold blue]") console.print("To enable Anthropic, you must have an Anthropic API key.") enable_anthropic = Confirm.ask("Do you want to enable Anthropic?") if enable_anthropic: anthropic_api_key = Prompt.ask("Enter your Anthropic API key", password=True) if not anthropic_api_key: console.print("[red]Error: Anthropic API key is required. Anthropic will not be enabled.[/red]") else: update_or_add_env_var("ANTHROPIC_API_KEY", anthropic_api_key) update_or_add_env_var("ENABLE_ANTHROPIC", "true") enabled_providers.append("anthropic") model_options.extend( [ "ANTHROPIC_CLAUDE4.6_OPUS", "ANTHROPIC_CLAUDE4.5_OPUS", "ANTHROPIC_CLAUDE4.5_SONNET", "ANTHROPIC_CLAUDE4.5_HAIKU", ] ) else: update_or_add_env_var("ENABLE_ANTHROPIC", "false") console.print("\n[bold blue]--- Azure Configuration ---[/bold blue]") console.print("To enable Azure, you must have an Azure deployment name, API key, base URL, and API version.") enable_azure = Confirm.ask("Do you want to enable Azure?") if enable_azure: azure_deployment = Prompt.ask("Enter your Azure deployment name") azure_api_key = Prompt.ask("Enter your Azure API key", password=True) azure_api_base = Prompt.ask("Enter your Azure API base URL") azure_api_version = Prompt.ask("Enter your Azure API version") if not all([azure_deployment, azure_api_key, azure_api_base, azure_api_version]): console.print("[red]Error: All Azure fields must be populated. Azure will not be enabled.[/red]") else: update_or_add_env_var("AZURE_DEPLOYMENT", azure_deployment) update_or_add_env_var("AZURE_API_KEY", azure_api_key) update_or_add_env_var("AZURE_API_BASE", azure_api_base) update_or_add_env_var("AZURE_API_VERSION", azure_api_version) update_or_add_env_var("ENABLE_AZURE", "true") enabled_providers.append("azure") model_options.append("AZURE_OPENAI") else: update_or_add_env_var("ENABLE_AZURE", "false") console.print("\n[bold blue]--- Gemini Configuration ---[/bold blue]") console.print("To enable Gemini, you must have a Gemini API key.") enable_gemini = Confirm.ask("Do you want to enable Gemini?") if enable_gemini: gemini_api_key = Prompt.ask("Enter your Gemini API key", password=True) if not gemini_api_key: console.print("[red]Error: Gemini API key is required. Gemini will not be enabled.[/red]") else: update_or_add_env_var("GEMINI_API_KEY", gemini_api_key) update_or_add_env_var("ENABLE_GEMINI", "true") enabled_providers.append("gemini") else: update_or_add_env_var("ENABLE_GEMINI", "false") console.print("\n[bold blue]--- Ollama / Local LLM Configuration ---[/bold blue]") console.print("Use any locally-running model via Ollama (e.g. llama3, mistral, qwen).") console.print("[dim]Requires Ollama running locally: https://ollama.com[/dim]") enable_ollama = Confirm.ask("Do you want to enable a local Ollama model?") if enable_ollama: ollama_server_url = Prompt.ask( "Enter Ollama server URL", default="http://localhost:11434", ) ollama_model = Prompt.ask( "Enter model name (e.g. llama3.3, mistral, qwen2.5)", ) if not ollama_model: console.print("[red]Error: Model name is required. Ollama will not be enabled.[/red]") else: ollama_vision = Confirm.ask("Does this model support vision?", default=False) update_or_add_env_var("OLLAMA_SERVER_URL", ollama_server_url) update_or_add_env_var("OLLAMA_MODEL", ollama_model) update_or_add_env_var("OLLAMA_SUPPORTS_VISION", str(ollama_vision).lower()) update_or_add_env_var("ENABLE_OLLAMA", "true") enabled_providers.append("ollama") model_options.append("OLLAMA") else: update_or_add_env_var("ENABLE_OLLAMA", "false") if not model_options: capture_setup_event( "llm-no-provider", success=False, error_type="no_provider_enabled", error_message="No LLM providers were enabled during setup", ) console.print( Panel( "[bold red]No LLM providers enabled.[/bold red]\n" "You won't be able to run Skyvern unless you enable at least one provider.\n" "You can re-run this script to enable providers or manually update the .env file.", border_style="red", ) ) else: console.print("\n[bold green]Available LLM models based on your selections:[/bold green]") for i, model in enumerate(model_options, 1): console.print(f" [cyan]{i}.[/cyan] [green]{model}[/green]") chosen_model_idx = Prompt.ask( f"Choose a model by number (e.g., [cyan]1[/cyan] for [green]{model_options[0]}[/green])", choices=[str(i) for i in range(1, len(model_options) + 1)], default="1", ) chosen_model = model_options[int(chosen_model_idx) - 1] console.print(f"🎉 [bold green]Chosen LLM Model: {chosen_model}[/bold green]") update_or_add_env_var("LLM_KEY", chosen_model) capture_setup_event( "llm-complete", success=True, extra_data={ "enabled_providers": enabled_providers, "chosen_model": chosen_model, "provider_count": len(enabled_providers), }, ) console.print("✅ [green]LLM provider configurations updated in .env.[/green]")