"""Pydantic schemas — API request/response contracts.

Mirrors the TypeScript types from the Electron app (src/shared/api-types.ts).
"""

from __future__ import annotations

from enum import Enum
from typing import Any, Literal

from pydantic import BaseModel, Field


# ── Billing ──────────────────────────────────────────────────────────

BillingTier = Literal["free", "pro", "power", "team"]


# ── Auth ─────────────────────────────────────────────────────────────

class AuthTokens(BaseModel):
    access_token: str
    refresh_token: str
    expires_at: int


class UserProfile(BaseModel):
    id: str
    email: str
    name: str | None = None
    surname: str | None = None
    tier: BillingTier


# ── Chat ─────────────────────────────────────────────────────────────

class ChatContext(BaseModel):
    user_profile: dict[str, Any] = Field(default_factory=dict)
    relevant_documents: list[str] = Field(default_factory=list)
    recent_tasks: list[dict[str, Any]] = Field(default_factory=list)
    conversation_history: list[dict[str, Any]] = Field(default_factory=list)


class ChatRequest(BaseModel):
    message: str
    context: ChatContext = Field(default_factory=ChatContext)


class ChatResponse(BaseModel):
    response: str


# ── WebSocket Frame Protocol ──────────────────────────────────────────

class WsFrameType(str, Enum):
    # ── v2 frame types (kept for backward compat) ──────────────────────
    chat_request = "chat_request"
    text_chunk = "text_chunk"
    tool_call = "tool_call"
    tool_result = "tool_result"
    final = "final"
    ping = "ping"
    device_hello = "device_hello"
    # ── v3 frame types ─────────────────────────────────────────────────
    home_request = "home_request"
    floating_request = "floating_request"
    stream_start = "stream_start"
    stream_text = "stream_text"
    stream_end = "stream_end"
    floating_domain = "floating_domain"
    data_request = "data_request"
    data_response = "data_response"
    mutation = "mutation"
    # ── v4 journey frame types ────────────────────────────────────────
    journey_start = "journey_start"
    journey_message = "journey_message"
    journey_reply = "journey_reply"


class WsToolCall(BaseModel):
    """Server → Client: requests a CRUD/vector operation on the local DB."""

    type: Literal[WsFrameType.tool_call] = WsFrameType.tool_call
    id: str
    action: str
    table: str | None = None
    data: dict[str, Any] | None = None
    filters: dict[str, Any] | None = None
    vector: list[float] | None = None
    limit: int | None = None


class WsToolResult(BaseModel):
    """Client → Server: result of a CRUD/vector operation."""

    type: Literal[WsFrameType.tool_result] = WsFrameType.tool_result
    id: str
    row: dict[str, Any] | None = None
    rows: list[dict[str, Any]] | None = None
    results: list[dict[str, Any]] | None = None
    deleted: bool | None = None
    ok: bool | None = None
    error: str | None = None


class WsTextChunk(BaseModel):
    """Server → Client: incremental LLM response text."""

    type: Literal[WsFrameType.text_chunk] = WsFrameType.text_chunk
    text: str


class WsFinal(BaseModel):
    """Server → Client: signals end of response with the complete text."""

    type: Literal[WsFrameType.final] = WsFrameType.final
    response: str


# ── WebSocket Agent Frame Protocol ────────────────────────────────────

class WsDeviceHello(BaseModel):
    """Client → Server: device identification on WS connect."""

    type: Literal[WsFrameType.device_hello] = WsFrameType.device_hello
    device_id: str
    agent_ids: list[str] = Field(default_factory=list)



# ── WebSocket v3 Frame Models ─────────────────────────────────────────

class WsFloatingScope(BaseModel):
    """Scope for a floating request — narrows the agent to a specific entity."""

    type: Literal["task", "project", "note", "timeline"]
    id: str | None = None


class WsHomeRequest(BaseModel):
    """Client → Server: Home chat message."""

    type: Literal[WsFrameType.home_request] = WsFrameType.home_request
    message: str
    conversation_history: list[dict[str, Any]] = Field(default_factory=list)


class WsFloatingRequest(BaseModel):
    """Client → Server: Floating chat message scoped to an entity."""

    type: Literal[WsFrameType.floating_request] = WsFrameType.floating_request
    message: str
    scope: WsFloatingScope


class WsStreamStart(BaseModel):
    """Server → Client: signals start of a streaming response."""

    type: Literal[WsFrameType.stream_start] = WsFrameType.stream_start
    request_id: str


class WsStreamText(BaseModel):
    """Server → Client: streamed text token."""

    type: Literal[WsFrameType.stream_text] = WsFrameType.stream_text
    request_id: str
    chunk: str


class WsStreamEnd(BaseModel):
    """Server → Client: signals end of a streaming response."""

    type: Literal[WsFrameType.stream_end] = WsFrameType.stream_end
    request_id: str


class WsDomain(BaseModel):
    """Structured floating domain payload for UI routing decisions."""

    type: Literal["task", "timeline", "project", "node"]
    id: str | None = None
    section: Literal["task", "timeline", "note"] | None = None


class WsFloatingDomain(BaseModel):
    """Server → Client: domain determined for a floating request."""

    type: Literal[WsFrameType.floating_domain] = WsFrameType.floating_domain
    request_id: str
    domain: WsDomain


# ── Agent Config V2 ───────────────────────────────────────────────────


class ContentTypeConfig(BaseModel):
    """Per-type extraction config produced by the journey chatbot."""

    id: str
    label: str = ""
    detection_hint: str = ""
    preprocessing: str = "generic"  # handler name: "email_html", "plain_text", ...
    extraction_prompt: str


class AgentConfig(BaseModel):
    """Structured agent configuration (replaces freeform prompt_template)."""

    content_types: list[ContentTypeConfig] = []
    global_rules: list[str] = []
    data_types: list[str] = []


# ── Agent Catalog ─────────────────────────────────────────────────────

class AgentCatalogItem(BaseModel):
    type: str
    name: str
    description: str


class AgentCreationCheckRequest(BaseModel):
    active_agents: int = Field(ge=0, default=0)


class AgentCreationCheckResponse(BaseModel):
    allowed: bool
    tier: BillingTier
    active_agents: int
    limit: int


class AgentTriggerRequest(BaseModel):
    directory: str = Field(min_length=1)
    device_id: str = Field(default="")
    agent_id: str | None = None  # FE stable agent ID (electron-store UUID)
    what_to_extract: list[str] = Field(min_length=1)
    actions_by_type: dict[str, list[str]] | None = None
    batch_interval: str = Field(min_length=1)
    custom_agent_prompt: str = Field(min_length=1)
    active_agents: int = Field(ge=0, default=0)


# ── Agent Run Log ─────────────────────────────────────────────────────

class AgentRunLogResponse(BaseModel):
    id: str
    agent_id: str
    agent_type: Literal["local", "cloud"]
    status: Literal["running", "success", "error", "partial"]
    items_processed: int
    items_created: int
    errors: list[str]
    started_at: int
    completed_at: int | None


# ── Chatbot Journey ───────────────────────────────────────────────────