feat(graph): daily-digest (יומון) discovery layer (corpus graph PR E) #132
@@ -51,6 +51,7 @@ const NODE_COLORS: Record<string, string> = {
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topic: "#a97d3a", // gold — hubs stand out
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practice_area: "#475569", // slate
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gap: "#94a3b8", // faint slate — research gap (not in corpus)
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digest: "#2f6f7a", // teal — daily-digest (יומון) discovery layer
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};
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const TREATMENT_COLORS: Record<string, string> = {
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@@ -114,6 +115,7 @@ export function colorForNode(n: GraphNode, colorBy: ColorBy): string {
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export function radiusForNode(n: GraphNode, sizeBy: SizeBy): number {
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if (n.type === "topic" || n.type === "practice_area") return 5;
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if (n.type === "digest") return 4;
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if (sizeBy === "pagerank" && n.pagerank != null) {
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return 3 + Math.sqrt(n.pagerank) * 18;
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}
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@@ -301,6 +303,9 @@ export function GraphCanvas({
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if (link.type === "tagged" || link.type === "in_area") {
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return "rgba(169,125,58,0.16)";
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}
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if (link.type === "covers") {
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return "rgba(47,111,122,0.45)"; // teal — digest → ruling
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}
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return "rgba(80,90,110,0.22)";
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},
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[activeId],
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@@ -44,6 +44,7 @@ export type GraphControls = {
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showPracticeAreas: boolean;
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showHalachot: boolean;
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showGaps: boolean;
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showDigests: boolean;
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};
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const ALL = "__all__";
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@@ -265,6 +266,11 @@ export function GraphFilterPanel({
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checked={controls.showGaps}
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onCheckedChange={(v) => onChange({ showGaps: v })}
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/>
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<ToggleRow
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label="יומונים (כל יום)"
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checked={controls.showDigests}
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onCheckedChange={(v) => onChange({ showDigests: v })}
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/>
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<ToggleRow
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label="הלכות (שלב ב׳)"
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checked={controls.showHalachot}
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@@ -20,6 +20,7 @@ const TYPE_LABELS: Record<string, string> = {
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topic: "נושא",
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practice_area: "תחום",
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gap: "פסיקה חסרה",
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digest: "יומון",
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};
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const GAP_STATUS_LABELS: Record<string, string> = {
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@@ -52,6 +53,7 @@ export function GraphNodePanel({
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}) {
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const isPrecedentLike = node.type === "precedent" || node.type === "halacha";
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const isGap = node.type === "gap";
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const isDigest = node.type === "digest";
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return (
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<Card className="bg-surface border-rule shadow-sm w-80 shrink-0 overflow-y-auto">
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<CardContent className="space-y-4 p-4">
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@@ -98,7 +100,19 @@ export function GraphNodePanel({
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</p>
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</>
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)}
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{!isPrecedentLike && !isGap && (
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{isDigest && (
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<>
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{node.note && (
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<p className="text-ink text-sm leading-relaxed m-0">{node.note}</p>
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)}
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{node.court && <Row label="ערכאה" value={node.court} />}
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{node.date && <Row label="תאריך" value={node.date.slice(0, 10)} />}
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<p className="text-ink-muted text-xs leading-relaxed m-0">
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סיכום יומי מ״כל יום״ — מצביע על הפסיקה שהוא מנתח.
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</p>
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</>
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)}
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{!isPrecedentLike && !isGap && !isDigest && (
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<p className="text-ink-muted text-xs leading-relaxed m-0">
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לחיצה על נקודה זו מתמקדת בשכניה — כל הפסיקות המשויכות אליה.
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</p>
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@@ -122,6 +136,15 @@ export function GraphNodePanel({
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</Link>
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</Button>
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)}
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{isDigest && (
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<Button asChild variant="outline" className="w-full">
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<Link href="/digests">
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<ExternalLink className="size-4 me-2" />
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לעמוד היומונים
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</Link>
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</Button>
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)}
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</CardContent>
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</Card>
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);
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@@ -66,6 +66,7 @@ export function GraphView() {
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showPracticeAreas: true,
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showHalachot: false,
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showGaps: false,
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showDigests: false,
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});
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const facets = useGraphFacets().data;
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const [selectedNode, setSelectedNode] = useState<GraphNode | null>(null);
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@@ -80,12 +81,14 @@ export function GraphView() {
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if (controls.showPracticeAreas) t.push("practice_area");
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if (controls.showHalachot) t.push("halacha");
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if (controls.showGaps) t.push("gap");
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if (controls.showDigests) t.push("digest");
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return t.join(",");
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}, [
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controls.showTopics,
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controls.showPracticeAreas,
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controls.showHalachot,
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controls.showGaps,
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controls.showDigests,
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]);
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// Metrics are needed when colouring by cluster or sizing by a centrality.
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@@ -19,7 +19,8 @@ export type GraphNodeType =
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| "halacha"
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| "topic"
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| "practice_area"
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| "gap";
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| "gap"
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| "digest";
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export type GraphEdgeType =
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| "cites"
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@@ -27,7 +28,8 @@ export type GraphEdgeType =
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| "tagged"
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| "in_area"
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| "corroborates"
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| "equivalent";
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| "equivalent"
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| "covers";
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export type GraphNode = {
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id: string;
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@@ -45,6 +47,8 @@ export type GraphNode = {
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community: number | null; // dense cluster id, 0 = largest
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gap_status: string | null; // gap nodes only — open|uploaded|closed|irrelevant
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missing_precedent_id: string | null; // gap nodes only
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note: string | null; // digest nodes only — the holding line
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digest_id: string | null; // digest nodes only
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};
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export type GraphFacets = {
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106
web/graph_api.py
106
web/graph_api.py
@@ -38,7 +38,7 @@ from pydantic import BaseModel
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from web import graph_metrics
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# ── Node-type vocabulary ─────────────────────────────────────────────
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VALID_NODE_TYPES = {"precedent", "halacha", "topic", "practice_area", "gap"}
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VALID_NODE_TYPES = {"precedent", "halacha", "topic", "practice_area", "gap", "digest"}
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DEFAULT_NODE_TYPES = ("precedent", "topic", "practice_area")
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NODE_CAP_DEFAULT = 400
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NODE_CAP_MAX = 1500
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@@ -72,6 +72,9 @@ class GraphNode(BaseModel):
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# Gap nodes only — research-gap status from missing_precedents (best-effort).
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gap_status: str | None = None # open | uploaded | closed | irrelevant
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missing_precedent_id: str | None = None
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# Digest nodes only — the holding line from the daily יומון.
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note: str | None = None
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digest_id: str | None = None # for deep-link to /digests
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class GraphFacets(BaseModel):
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@@ -306,6 +309,97 @@ async def _gap_nodes_and_edges(
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return nodes, edges
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async def _digest_nodes_and_edges(
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conn: asyncpg.Connection,
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prec_ids: list,
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) -> tuple[list[GraphNode], list[GraphEdge], list[GraphNode]]:
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"""Daily-digest (יומון) discovery layer. Each digest ``covers`` the ruling
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it analyses: a corpus precedent (``linked_case_law_id``) when we have it, or
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a ``gap`` node synthesized from ``underlying_citation`` when we don't — so
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the digest doubles as a research signal ("the feed flagged this ruling").
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Returns (digest_nodes, covers_edges, gap_target_nodes). The caller dedups
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gap nodes against the gap layer (real in-degree there wins over size=1)."""
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digest_nodes: list[GraphNode] = []
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edges: list[GraphEdge] = []
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gap_nodes: list[GraphNode] = []
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if not prec_ids:
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return digest_nodes, edges, gap_nodes
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prec_set = {str(x) for x in prec_ids}
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rows = await conn.fetch(
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"""
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SELECT id, yomon_number, concept_tag, headline_holding,
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underlying_citation, underlying_court, underlying_date,
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digest_date, practice_area, linked_case_law_id,
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regexp_replace(btrim(underlying_citation), '\\s+', ' ', 'g') AS u_num
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FROM digests
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WHERE extraction_status = 'completed'
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AND (linked_case_law_id = ANY($1::uuid[])
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OR (linked_case_law_id IS NULL AND btrim(underlying_citation) <> ''))
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ORDER BY digest_date DESC NULLS LAST
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LIMIT 400
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""",
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prec_ids,
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)
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seen_gap: set[str] = set()
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for r in rows:
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did = f"dig:{r['id']}"
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linked = r["linked_case_law_id"]
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if linked is not None and str(linked) in prec_set:
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target = f"cl:{linked}"
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elif r["u_num"]:
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target = f"gap:{r['u_num']}"
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if r["u_num"] not in seen_gap:
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seen_gap.add(r["u_num"])
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gap_nodes.append(
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GraphNode(
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id=target,
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type="gap",
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label=(r["underlying_citation"] or "").strip() or r["u_num"],
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size=1,
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)
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)
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else:
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continue
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label = (r["concept_tag"] or "").strip() or (
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f"יומון {r['yomon_number']}" if r["yomon_number"] else "יומון"
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)
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d = r["underlying_date"] or r["digest_date"]
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digest_nodes.append(
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GraphNode(
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id=did,
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type="digest",
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label=label[:48],
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note=((r["headline_holding"] or "").strip()[:160] or None),
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court=(r["underlying_court"] or None),
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date=(d.isoformat() if d else None),
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practice_area=(r["practice_area"] or None),
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digest_id=str(r["id"]),
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)
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)
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edges.append(GraphEdge(source=did, target=target, type="covers"))
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return digest_nodes, edges, gap_nodes
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async def _add_digests(
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conn: asyncpg.Connection,
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prec_ids: list,
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nodes: list[GraphNode],
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edges: list[GraphEdge],
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) -> None:
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"""Append the digest layer in place, adding digest-target gap nodes only if
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they aren't already present (the gap layer's real in-degree wins)."""
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dig_nodes, dig_edges, gap_targets = await _digest_nodes_and_edges(conn, prec_ids)
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existing = {n.id for n in nodes}
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for g in gap_targets:
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if g.id not in existing:
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nodes.append(g)
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existing.add(g.id)
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nodes.extend(dig_nodes)
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edges.extend(dig_edges)
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# ── Endpoints' core logic ────────────────────────────────────────────
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async def build_corpus_graph(
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pool: asyncpg.Pool,
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@@ -379,12 +473,15 @@ async def build_corpus_graph(
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total_available = int(prec_rows[0]["total_available"]) if prec_rows else 0
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nodes = [_precedent_node(r) for r in prec_rows]
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prec_id_list = [r["id"] for r in prec_rows]
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hub_nodes, edges = await _edges_and_hubs(conn, prec_rows, types)
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nodes.extend(hub_nodes)
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if "gap" in types:
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gap_nodes, gap_edges = await _gap_nodes_and_edges(conn, [r["id"] for r in prec_rows])
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gap_nodes, gap_edges = await _gap_nodes_and_edges(conn, prec_id_list)
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nodes.extend(gap_nodes)
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edges.extend(gap_edges)
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if "digest" in types:
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await _add_digests(conn, prec_id_list, nodes, edges)
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if metrics:
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_stamp_metrics(nodes, edges)
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@@ -516,12 +613,15 @@ async def build_node_neighborhood(
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ids,
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)
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nodes = [_precedent_node(r) for r in prec_rows]
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prec_id_list = [r["id"] for r in prec_rows]
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hub_nodes, edges = await _edges_and_hubs(conn, prec_rows, forced_types)
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nodes.extend(hub_nodes)
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if "gap" in forced_types:
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gap_nodes, gap_edges = await _gap_nodes_and_edges(conn, [r["id"] for r in prec_rows])
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gap_nodes, gap_edges = await _gap_nodes_and_edges(conn, prec_id_list)
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nodes.extend(gap_nodes)
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edges.extend(gap_edges)
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if "digest" in forced_types:
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await _add_digests(conn, prec_id_list, nodes, edges)
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return CorpusGraph(
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nodes=nodes,
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