openswarm/backend/apps/settings/models.py

from pydantic import BaseModel, Field
from typing import Optional, Any, Literal

DEFAULT_SYSTEM_PROMPT = (
    "You are a personal AI assistant running inside OpenSwarm.\n\n"
    "## Core Behavior\n"
    "Act, don't ask. When a tool can accomplish the task, call it immediately; "
    "do not describe what you would do, do not ask for confirmation, just execute. "
    "The user expects results, not plans.\n"
    "If ANY available tool is relevant to the user's request, use it. Never respond "
    'with "I can do X for you" or "Would you like me to..."; just do it. '
    "A tool call is always better than a text explanation of what the tool would do.\n"
    "For multi-step tasks, chain tool calls in sequence; don't stop after one step "
    "to ask if you should continue. Complete the entire task, then report the results.\n"
    "Be adaptable. If one approach fails, try a different tool or strategy instead of "
    "giving up or repeating the same action. Always stay focused on what the user "
    "actually wants to accomplish; their intent matters more than the specific method.\n\n"
    "## Tool Priority\n"
    "1. Connected MCP tools; fastest and most reliable. To reach an integration you "
    "don't already see, use MCPSearch then MCPActivate; never ToolSearch for it.\n"
    "2. WebSearch / WebFetch; for general web lookups when no MCP tool fits.\n"
    "3. BrowserAgent; last resort, only for visual interaction with websites, "
    "filling forms, or tasks no other tool can handle.\n\n"
    "## Style\n"
    "Do not narrate routine tool calls; just call the tool.\n"
    "After tool calls complete, present the results directly. Do not recap which "
    "tools you called or why; the user can see tool calls in the UI.\n"
    "Keep responses brief and direct. Use plain language.\n"
    "If you genuinely need clarification on something ambiguous, use the "
    "AskUserQuestion tool. Never ask questions inline in plain text.\n"
)


# Fresh-install / unset-fallback model. "opus-5" is the plain row: cc/ sub lane for subscription users, API key otherwise.
DEFAULT_MODEL = "opus-5"


class AppSettings(BaseModel):
    default_system_prompt: Optional[str] = DEFAULT_SYSTEM_PROMPT
    default_folder: Optional[str] = None
    default_model: str = DEFAULT_MODEL
    default_mode: str = "agent"
    default_max_turns: Optional[int] = None
    default_thinking_level: Literal["off", "low", "medium", "high", "auto"] = "auto"
    zoom_sensitivity: float = 50.0
    # What a plain MOUSE wheel does on the canvas. "zoom" is the Google-Maps model we ship; "scroll"
    # suits people who expect a wheel to move the page, and swaps the pair so cmd/ctrl+wheel zooms
    # instead. A trackpad two-finger scroll pans either way, since that gesture is already a pan
    # everywhere else on the machine.
    mouse_wheel_action: Literal["zoom", "scroll"] = "zoom"
    # Root font-size multiplier (0.9/1/1.1/1.2 from Settings > Interface); the whole rem type scale rides it.
    ui_font_scale: float = 1.0
    theme: str = "light"
    # Shared across App Builder workspaces (each runs its own vite port / localStorage origin); null = follow system.
    app_template_theme_override: Optional[Literal["light", "dark"]] = None
    new_agent_shortcut: str = "Meta+l"
    # None = platform default (Cmd/Ctrl+Shift+D); parts format matches new_agent_shortcut.
    dictation_shortcut: Optional[str] = None
    voice_hold_to_talk: bool = True
    # Whisper model id from the desktop catalog (electron/voice/whisperModels.js); None = its default.
    dictation_model: Optional[str] = None
    anthropic_api_key: Optional[str] = None
    browser_homepage: str = "https://www.google.com"
    # Opt-in: let a blocked browser agent borrow the sign-in you already have in your everyday
    # browser instead of stopping to ask you to log in again. Default OFF because reading your real
    # browser's session is your decision to make once, explicitly, not ours to assume.
    browser_import_signins: bool = False
    openai_api_key: Optional[str] = None
    google_api_key: Optional[str] = None
    openrouter_api_key: Optional[str] = None
    custom_providers: list["CustomProvider"] = Field(default_factory=list)
    auto_select_mode_on_new_agent: bool = False
    expand_new_chats_in_dashboard: bool = True
    auto_reveal_sub_agents: bool = True
    dev_mode: bool = False
    allow_experimental_updates: bool = False
    claude_subscription_token: Optional[str] = None
    openai_subscription_token: Optional[str] = None
    gemini_subscription_token: Optional[str] = None
    user_name: Optional[str] = None
    user_email: Optional[str] = None
    user_use_case: Optional[str] = None
    user_referral_source: Optional[str] = None
    # Onboarding v3 lifecycle: None = never seen, "done"/"skipped" once resolved.
    onboarding_v3: Optional[str] = None
    # User-picked accent hex from the onboarding theme pad; None = stock accent.
    accent_color: Optional[str] = None
    # Multi-stop gradient from the theme pad (2-3 hexes); washes the canvas.
    accent_gradient: Optional[list[str]] = None
    personalized_greeting: Optional[str] = None
    # Short one-glance identity hook for the reveal's focal beat (greeting is the longer warm read).
    personalized_headline: Optional[str] = None
    personalized_starters: list["PersonalizedStarter"] = Field(default_factory=list)
    personalized_automations: list["PersonalizedAutomation"] = Field(default_factory=list)
    # The hero's two-level menu: 4 general categories, each holding 4 starters tailored to this user.
    personalized_menu: Optional["PersonalizedMenu"] = None
    # Distilled from the user's provider chat history the first time they open ChatGPT/Claude in-app; re-feeds prep to sharpen suggestions.
    personalized_usage_summary: Optional[str] = None
    # Suppresses preflight suggestion modal entries the user dismissed; keyed by ToolDefinition.name, value ISO timestamp.
    dismissed_mcp_suggestions: dict[str, str] = Field(default_factory=dict)
    analytics_opt_in: bool = True
    installation_id: Optional[str] = None
    # Minted once by the analytics SDK's register() and reused forever; server-owned.
    analytics_token: Optional[str] = None
    # Renderer-reported browser Intl values, stamped on analytics submissions; server-owned.
    timezone: Optional[str] = None
    locale: Optional[str] = None
    first_opened_at: Optional[str] = None
    connection_mode: str = "own_key"
    openswarm_bearer_token: Optional[str] = None
    openswarm_proxy_url: Optional[str] = None
    # Zero-config free trial: server-funded runs for a brand-new user with no key and no subscription. connection_mode flips to "free-trial" while armed; the token + remaining count are server-owned (minted by the cloud, sticky per machine). remaining is cached for the onboarding "runs low" nudge.
    free_trial_token: Optional[str] = None
    free_trial_remaining: Optional[int] = None
    free_trial_runs_limit: Optional[int] = None
    # Epoch seconds when the rolling window refills to a fresh allotment; lets the spent-trial nudge say "fresh runs in ~3h" instead of a vague "for now". Server-owned.
    free_trial_resets_at: Optional[float] = None
    openswarm_subscription_plan: Optional[str] = None
    openswarm_subscription_expires: Optional[str] = None
    openswarm_usage_cached: Optional[dict] = None
    # Server-validated identity from /api/auth/signin-activate; user_email above is the self-reported onboarding value.
    user_id: Optional[str] = None
    signin_method: Optional[Literal["google", "stripe", "email"]] = None
    # Runtime preflight (electron/preflight.js). Default-on; users opt out via this flag, env var OPENSWARM_DISABLE_PREFLIGHT=1, or the cloud-side cohort rollout knocking preflight_rollout_pct down.
    preflight_enabled: bool = True
    # 0-100; the cohort gate compares (hash(installation_id) % 100) < pct. 100 = everyone, 0 = nobody, used as the kill switch if a staged rollout finds a false-positive spike.
    preflight_rollout_pct: int = 100


class CustomProvider(BaseModel):
    name: str
    base_url: str
    api_key: str = ""
    models: list[dict[str, Any]] = Field(default_factory=list)


class PersonalizedStarter(BaseModel):
    title: str
    prompt: str
    # One short clause tying this task to something real we saw about the user; the reveal shows it off.
    reason: str = ""


class PersonalizedAutomation(BaseModel):
    title: str
    prompt: str
    # 'daily' | 'weekday' | 'weekly'; the frontend maps this to a workflow schedule.
    cadence: str = "weekly"


class PersonalizedMenu(BaseModel):
    computer: list[PersonalizedStarter] = Field(default_factory=list)
    research: list[PersonalizedStarter] = Field(default_factory=list)
    web: list[PersonalizedStarter] = Field(default_factory=list)
    build: list[PersonalizedStarter] = Field(default_factory=list)