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Skyvern/skyvern/cli/llm_setup.py
Suchintan 0afc59348e
Streamline CLI quickstart: browser setup, LLM models, Ollama support (#5214) 
Co-authored-by: Suchintan Singh <suchintan@skyvern.com>
2026-03-23 23:42:52 -04:00

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Python
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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]")
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