fbd308d288
WsDeviceHello.agent_ids → scout_ids in Pydantic schema, device_ws.py handler, and all test fixtures (test_device_ws, test_ws_unified, test_memory_middleware). Also fixes stale CloudAgentConfig reference in gmail.py docstring. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
278 lines
9.6 KiB
Python
278 lines
9.6 KiB
Python
"""Pydantic schemas — API request/response contracts.
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Mirrors the TypeScript types from the Electron app (src/shared/api-types.ts).
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"""
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from __future__ import annotations
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from enum import Enum
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from typing import Any, Literal
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from pydantic import BaseModel, Field
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# ── Billing ──────────────────────────────────────────────────────────
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BillingTier = Literal["free", "pro", "power", "team"]
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# ── Auth ─────────────────────────────────────────────────────────────
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class AuthTokens(BaseModel):
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access_token: str
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refresh_token: str
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expires_at: int
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class UserProfile(BaseModel):
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id: str
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email: str
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name: str | None = None
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surname: str | None = None
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tier: BillingTier
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avatar_url: str | None = None
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has_password: bool = True
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onboarding_completed_at: int | None = None # epoch ms, null = not onboarded
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memory: dict[str, str] = Field(default_factory=dict) # decrypted core memory k/v
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class OAuthAccountInfo(BaseModel):
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provider: str
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provider_email: str | None = None
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created_at: int # epoch ms
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# ── Chat ─────────────────────────────────────────────────────────────
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class ChatContext(BaseModel):
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user_profile: dict[str, Any] = Field(default_factory=dict)
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relevant_documents: list[str] = Field(default_factory=list)
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recent_tasks: list[dict[str, Any]] = Field(default_factory=list)
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conversation_history: list[dict[str, Any]] = Field(default_factory=list)
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class ChatRequest(BaseModel):
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message: str
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context: ChatContext = Field(default_factory=ChatContext)
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class ChatResponse(BaseModel):
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response: str
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# ── WebSocket Frame Protocol ──────────────────────────────────────────
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class WsFrameType(str, Enum):
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# ── v2 frame types (kept for backward compat) ──────────────────────
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chat_request = "chat_request"
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text_chunk = "text_chunk"
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tool_call = "tool_call"
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tool_result = "tool_result"
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final = "final"
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ping = "ping"
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device_hello = "device_hello"
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# ── v3 frame types ─────────────────────────────────────────────────
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home_request = "home_request"
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stream_start = "stream_start"
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stream_text = "stream_text"
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stream_end = "stream_end"
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data_request = "data_request"
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data_response = "data_response"
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mutation = "mutation"
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# ── v4 journey frame types ────────────────────────────────────────
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journey_start = "journey_start"
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journey_message = "journey_message"
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journey_reply = "journey_reply"
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# ── v5 brief frame types ──────────────────────────────────────────
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brief_request = "brief_request"
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# ── v6 task brief frame types ─────────────────────────────────────
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task_brief_request = "task_brief_request"
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# ── v7 folder index frame types ───────────────────────────────────
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index_session_start = "index_session_start"
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index_file_batch = "index_file_batch"
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index_session_cancel = "index_session_cancel"
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index_file_result = "index_file_result"
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index_session_progress = "index_session_progress"
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index_session_done = "index_session_done"
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# ── v8 contextual sidebar frame types ────────────────────────────
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contextual_request = "contextual_request"
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contextual_scope_update = "contextual_scope_update"
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contextual_scope_ack = "contextual_scope_ack"
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class WsToolCall(BaseModel):
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"""Server → Client: requests a CRUD/vector operation on the local DB."""
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type: Literal[WsFrameType.tool_call] = WsFrameType.tool_call
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id: str
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action: str
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table: str | None = None
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data: dict[str, Any] | None = None
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filters: dict[str, Any] | None = None
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vector: list[float] | None = None
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limit: int | None = None
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class WsToolResult(BaseModel):
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"""Client → Server: result of a CRUD/vector operation."""
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type: Literal[WsFrameType.tool_result] = WsFrameType.tool_result
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id: str
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row: dict[str, Any] | None = None
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rows: list[dict[str, Any]] | None = None
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results: list[dict[str, Any]] | None = None
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deleted: bool | None = None
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ok: bool | None = None
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error: str | None = None
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class WsTextChunk(BaseModel):
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"""Server → Client: incremental LLM response text."""
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type: Literal[WsFrameType.text_chunk] = WsFrameType.text_chunk
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text: str
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class WsFinal(BaseModel):
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"""Server → Client: signals end of response with the complete text."""
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type: Literal[WsFrameType.final] = WsFrameType.final
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response: str
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# ── WebSocket Agent Frame Protocol ────────────────────────────────────
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class WsDeviceHello(BaseModel):
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"""Client → Server: device identification on WS connect."""
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type: Literal[WsFrameType.device_hello] = WsFrameType.device_hello
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device_id: str
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scout_ids: list[str] = Field(default_factory=list)
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# ── WebSocket v3 Frame Models ─────────────────────────────────────────
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class FormatPrefsModel(BaseModel):
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"""User display preferences sent by Electron on each request."""
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timezone: str = "UTC"
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date_format: str = "dd/MM/yyyy"
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time_format: str = "24h"
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locale: str = "en-US"
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now_iso: str = ""
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class WsHomeRequest(BaseModel):
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"""Client → Server: Home chat message."""
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type: Literal[WsFrameType.home_request] = WsFrameType.home_request
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message: str
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conversation_history: list[dict[str, Any]] = Field(default_factory=list)
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format_prefs: FormatPrefsModel | None = None
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class WsBriefRequest(BaseModel):
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"""Client → Server: Request a plain-text brief (home or project)."""
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type: Literal[WsFrameType.brief_request] = WsFrameType.brief_request
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request_id: str | None = None
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session_id: str | None = None
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mode: Literal["home", "project"]
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project_id: str | None = None
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format_prefs: FormatPrefsModel | None = None
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class WsStreamStart(BaseModel):
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"""Server → Client: signals start of a streaming response."""
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type: Literal[WsFrameType.stream_start] = WsFrameType.stream_start
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request_id: str
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class WsStreamText(BaseModel):
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"""Server → Client: streamed text token."""
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type: Literal[WsFrameType.stream_text] = WsFrameType.stream_text
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request_id: str
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chunk: str
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class WsStreamEnd(BaseModel):
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"""Server → Client: signals end of a streaming response."""
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type: Literal[WsFrameType.stream_end] = WsFrameType.stream_end
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request_id: str
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error: str | None = None
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mutations: list[dict[str, Any]] | None = None
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# ── Scout Config V2 ───────────────────────────────────────────────────
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class ScoutContentTypeConfig(BaseModel):
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"""Per-type extraction config produced by the journey chatbot."""
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id: str
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label: str = ""
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detection_hint: str = ""
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preprocessing: str = "generic" # handler name: "email_html", "plain_text", ...
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extraction_prompt: str
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class ScoutConfig(BaseModel):
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"""Structured scout configuration (replaces freeform prompt_template)."""
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content_types: list[ScoutContentTypeConfig] = []
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global_rules: list[str] = []
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data_types: list[str] = []
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# ── Scout Catalog ─────────────────────────────────────────────────────
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class ScoutCatalogItem(BaseModel):
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type: str
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name: str
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description: str
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class ScoutCreationCheckRequest(BaseModel):
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active_agents: int = Field(ge=0, default=0)
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class ScoutCreationCheckResponse(BaseModel):
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allowed: bool
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tier: BillingTier
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active_agents: int
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limit: int
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class ScoutTriggerRequest(BaseModel):
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directory: str = Field(min_length=1)
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device_id: str = Field(default="")
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agent_id: str | None = None # FE stable agent ID (electron-store UUID)
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what_to_extract: list[str] = Field(min_length=1)
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batch_interval: str = Field(min_length=1)
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custom_agent_prompt: str | None = None
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agent_config: dict | None = None
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active_agents: int = Field(ge=0, default=0)
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last_run_at: int | None = None # epoch ms from FE — enables incremental scanning
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# ── Scout Run Log ─────────────────────────────────────────────────────
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class ScoutRunLogResponse(BaseModel):
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id: str
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agent_id: str
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agent_type: Literal["local", "cloud"]
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status: Literal["running", "success", "error", "partial"]
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items_processed: int
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items_created: int
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errors: list[str]
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started_at: int
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completed_at: int | None
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# ── Chatbot Journey ───────────────────────────────────────────────────
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