mirror of
https://github.com/wahyd4/hey-search.git
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117 lines
2.9 KiB
Python
117 lines
2.9 KiB
Python
"""Result models for search engines."""
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from __future__ import annotations
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import uuid
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from datetime import datetime, timezone
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from pydantic import BaseModel, Field
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class WebResult(BaseModel):
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"""A single web search result."""
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result_id: str = Field(default_factory=lambda: uuid.uuid4().hex[:12])
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title: str
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url: str
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content: str = ""
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engine: str = ""
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rank: int = 0
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published_date: str = "" # ISO 8601 date (YYYY-MM-DD) or empty
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class ImageResult(BaseModel):
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"""A single image search result."""
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result_id: str = Field(default_factory=lambda: uuid.uuid4().hex[:12])
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title: str
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url: str
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img_src: str
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thumbnail_src: str = ""
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source: str = ""
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engine: str = ""
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rank: int = 0
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width: int = 0
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height: int = 0
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published_date: str = "" # ISO 8601 date (YYYY-MM-DD) or empty
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class EngineError(BaseModel):
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"""An error from a search engine."""
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engine: str
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message: str
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is_timeout: bool = False
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code: str = "engine_error"
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details: str = ""
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retry_hint: str = ""
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class EngineStat(BaseModel):
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"""Per-engine statistics for a single search."""
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engine: str
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display_name: str
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result_count: int
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status: str = "ok" # "ok" | "error" | "timeout"
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error_message: str = ""
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class SearchResponse(BaseModel):
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"""Aggregated search response from all engines."""
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query: str
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category: str = "web"
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page: int = 1
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results: list[WebResult | ImageResult] = Field(default_factory=list)
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errors: list[EngineError] = Field(default_factory=list)
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suggestions: list[str] = Field(default_factory=list)
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engine_stats: list[EngineStat] = Field(default_factory=list)
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timestamp: str = Field(default_factory=lambda: datetime.now(timezone.utc).isoformat())
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total_results: int = 0
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has_next: bool = True
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cached: bool = False
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class EngineInfo(BaseModel):
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"""Engine metadata for management."""
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name: str
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display_name: str
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enabled: bool = True
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supports_web: bool = True
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supports_images: bool = True
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order: int = 0
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class APIError(BaseModel):
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"""Standard error response."""
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code: str
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message: str
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details: str = ""
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retry_hint: str = ""
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# --- LLM-optimised response models ---
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class LLMWebResult(BaseModel):
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"""A single web result stripped to the fields LLMs need."""
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title: str
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url: str
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snippet: str = ""
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date: str = ""
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class LLMImageResult(BaseModel):
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"""A single image result stripped to the fields LLMs need."""
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title: str
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url: str
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img_src: str
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date: str = ""
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class LLMSearchResponse(BaseModel):
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"""Minimal search response for LLM / AI-agent consumption.
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Contains only the fields needed for RAG and tool-calling workflows.
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Omits engine metadata, error details, and other browser-UI noise.
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"""
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query: str
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category: str = "web"
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results: list[LLMWebResult | LLMImageResult] = Field(default_factory=list)
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total_results: int = 0
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