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65dfa4b da17d99 65dfa4b da17d99 65dfa4b 854be79 65dfa4b 854be79 65dfa4b 854be79 65dfa4b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 | """Pydantic models for API request/response schemas."""
from pydantic import BaseModel, Field
# ── Request models ───────────────────────────────────────────────────
class SearchRequest(BaseModel):
"""RAG search query."""
query: str = Field(..., min_length=1, max_length=2000)
top_k: int = Field(default=5, ge=1, le=50)
year_min: int | None = Field(default=None, ge=1900, le=2100)
year_max: int | None = Field(default=None, ge=1900, le=2100)
venue: str | None = None
class PaperBrowseRequest(BaseModel):
"""Filters for browsing papers."""
venue: str | None = None
volume: str | None = None
year: int | None = Field(default=None, ge=1900, le=2100)
method: str | None = None
dataset: str | None = None
author: str | None = None
limit: int = Field(default=20, ge=1, le=100)
offset: int = Field(default=0, ge=0)
class TrendRequest(BaseModel):
"""Request for tracking a specific entity trend over time."""
name: str = Field(..., min_length=1, max_length=500)
# ── Response models ──────────────────────────────────────────────────
class SourcePaper(BaseModel):
"""A paper cited as a source in a RAG response."""
paper_id: str
title: str
year: int
venue: str | None
chunk_type: str
authors: list[str] = Field(default_factory=list)
used_in_answer: bool = False
class SearchResponse(BaseModel):
"""RAG search result."""
answer: str
sources: list[SourcePaper]
model: str
usage: dict = Field(default_factory=dict)
class PaperDetail(BaseModel):
"""Full paper with authors and enrichment data."""
id: str
title: str
abstract: str | None
year: int | None
venue: str | None
url: str | None
authors: list[str] = Field(default_factory=list)
methods: list[dict] = Field(default_factory=list)
datasets: list[dict] = Field(default_factory=list)
class PaperSummary(BaseModel):
"""Paper listing with basic metadata."""
id: str
title: str
abstract: str | None
year: int | None
venue: str | None
url: str | None
authors: list[str] = Field(default_factory=list)
class PaperListResponse(BaseModel):
"""Paginated paper listing."""
papers: list[PaperSummary]
count: int
limit: int
offset: int
class TrendPoint(BaseModel):
"""A single year's data point in a trend."""
year: int
paper_count: int
class TrendResponse(BaseModel):
"""Trend data for an entity over time."""
name: str
trend: list[TrendPoint]
class RankedEntity(BaseModel):
"""An entity (method/dataset/task/topic) with count and rank."""
name: str
year: int
count: int
rank: int
class CooccurrenceRow(BaseModel):
"""A co-occurrence pair with frequency."""
entity_a: str
entity_b: str
co_count: int
class EnrichmentStatsResponse(BaseModel):
"""Database enrichment statistics."""
total_papers: int
total_methods: int
total_datasets: int
total_tasks: int
total_topics: int
papers_with_methods: int
class GrowthPoint(BaseModel):
"""Year-over-year growth data."""
year: int
paper_count: int
prev_count: int | None
growth_pct: float | None
class EntityListItem(BaseModel):
"""A unique entity name with its paper count."""
name: str
count: int
class HealthResponse(BaseModel):
"""System health status."""
status: str
paper_count: int
chunk_count: int
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