4592e35732
Brain Service: - Playwright stealth crawler replacing browserless (og:image, Readability, Reddit JSON API) - AI classification with tag definitions and folder assignment - YouTube video download via yt-dlp - Karakeep migration complete (96 items) - Taxonomy management (folders with icons/colors, tags) - Discovery shuffle, sort options, search (Meilisearch + pgvector) - Item tag/folder editing, card color accents RSS Reader Service: - Custom FastAPI reader replacing Miniflux - Feed management (add/delete/refresh), category support - Full article extraction via Readability - Background content fetching for new entries - Mark all read with confirmation - Infinite scroll, retention cleanup (30/60 day) - 17 feeds migrated from Miniflux iOS App (SwiftUI): - Native iOS 17+ app with @Observable architecture - Cookie-based auth, configurable gateway URL - Dashboard with custom background photo + frosted glass widgets - Full fitness module (today/templates/goals/food library) - AI assistant chat (fitness + brain, raw JSON state management) - 120fps ProMotion support AI Assistants (Gateway): - Unified dispatcher with fitness/brain domain detection - Fitness: natural language food logging, photo analysis, multi-item splitting - Brain: save/append/update/delete notes, search & answer, undo support - Madiha user gets fitness-only (brain disabled) Firefox Extension: - One-click save to Brain from any page - Login with platform credentials - Right-click context menu (save page/link/image) - Notes field for URL saves - Signed and published on AMO Other: - Reader bookmark button routes to Brain (was Karakeep) - Fitness food library with "Add" button + add-to-meal popup - Kindle send file size check (25MB SMTP2GO limit) - Atelier UI as default (useAtelierShell=true) - Mobile upload box in nav drawer Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
132 lines
2.9 KiB
Python
132 lines
2.9 KiB
Python
"""Pydantic schemas for API request/response."""
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from __future__ import annotations
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from datetime import datetime
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from typing import Optional
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from pydantic import BaseModel, Field
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# ── Request schemas ──
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class ItemCreate(BaseModel):
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type: str = "link"
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url: Optional[str] = None
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raw_content: Optional[str] = None
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title: Optional[str] = None
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folder: Optional[str] = None
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tags: Optional[list[str]] = None
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class ItemUpdate(BaseModel):
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title: Optional[str] = None
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folder: Optional[str] = None
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tags: Optional[list[str]] = None
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raw_content: Optional[str] = None
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class ItemAdditionCreate(BaseModel):
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content: str
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source: Optional[str] = "assistant"
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kind: Optional[str] = "append"
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metadata_json: Optional[dict] = None
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class SearchQuery(BaseModel):
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q: str
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folder: Optional[str] = None
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tags: Optional[list[str]] = None
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type: Optional[str] = None
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limit: int = Field(default=20, le=100)
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offset: int = 0
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class SemanticSearchQuery(BaseModel):
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q: str
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folder: Optional[str] = None
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type: Optional[str] = None
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limit: int = Field(default=20, le=100)
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class HybridSearchQuery(BaseModel):
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q: str
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folder: Optional[str] = None
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tags: Optional[list[str]] = None
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type: Optional[str] = None
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limit: int = Field(default=20, le=100)
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# ── Response schemas ──
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class AssetOut(BaseModel):
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id: str
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asset_type: str
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filename: str
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content_type: Optional[str] = None
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size_bytes: Optional[int] = None
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created_at: datetime
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model_config = {"from_attributes": True}
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class ItemAdditionOut(BaseModel):
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id: str
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item_id: str
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source: str
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kind: str
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content: str
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metadata_json: Optional[dict] = None
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created_at: datetime
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updated_at: datetime
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model_config = {"from_attributes": True}
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class ItemOut(BaseModel):
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id: str
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type: str
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title: Optional[str] = None
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url: Optional[str] = None
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raw_content: Optional[str] = None
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extracted_text: Optional[str] = None
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folder: Optional[str] = None
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tags: Optional[list[str]] = None
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summary: Optional[str] = None
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confidence: Optional[float] = None
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processing_status: str
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processing_error: Optional[str] = None
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metadata_json: Optional[dict] = None
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created_at: datetime
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updated_at: datetime
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assets: list[AssetOut] = []
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model_config = {"from_attributes": True}
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class ItemList(BaseModel):
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items: list[ItemOut]
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total: int
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class SearchResult(BaseModel):
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items: list[ItemOut]
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total: int
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query: str
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class ConfigOut(BaseModel):
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folders: list[str]
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tags: list[str]
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# ── OpenAI classification schema ──
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class ClassificationResult(BaseModel):
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"""What the AI returns for each item."""
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folder: str
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tags: list[str] = Field(min_length=2, max_length=3)
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title: str
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summary: str
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confidence: float = Field(ge=0.0, le=1.0)
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