Merge pull request 'feat(graph): daily-digest (יומון) discovery layer (corpus graph PR E)' (#132) from worktree-graph-digests into main

web-ui/src/components/graph/graph-canvas.tsx

@@ -51,6 +51,7 @@ const NODE_COLORS: Record<string, string> = {
   topic: "#a97d3a", // gold — hubs stand out
   practice_area: "#475569", // slate
   gap: "#94a3b8", // faint slate — research gap (not in corpus)
+  digest: "#2f6f7a", // teal — daily-digest (יומון) discovery layer
 };
 
 const TREATMENT_COLORS: Record<string, string> = {
@@ -114,6 +115,7 @@ export function colorForNode(n: GraphNode, colorBy: ColorBy): string {
 
 export function radiusForNode(n: GraphNode, sizeBy: SizeBy): number {
   if (n.type === "topic" || n.type === "practice_area") return 5;
+  if (n.type === "digest") return 4;
   if (sizeBy === "pagerank" && n.pagerank != null) {
     return 3 + Math.sqrt(n.pagerank) * 18;
   }
@@ -301,6 +303,9 @@ export function GraphCanvas({
       if (link.type === "tagged" || link.type === "in_area") {
         return "rgba(169,125,58,0.16)";
       }
+      if (link.type === "covers") {
+        return "rgba(47,111,122,0.45)"; // teal — digest → ruling
+      }
       return "rgba(80,90,110,0.22)";
     },
     [activeId],

web-ui/src/components/graph/graph-filter-panel.tsx

@@ -44,6 +44,7 @@ export type GraphControls = {
   showPracticeAreas: boolean;
   showHalachot: boolean;
   showGaps: boolean;
+  showDigests: boolean;
 };
 
 const ALL = "__all__";
@@ -265,6 +266,11 @@ export function GraphFilterPanel({
             checked={controls.showGaps}
             onCheckedChange={(v) => onChange({ showGaps: v })}
           />
+          <ToggleRow
+            label="יומונים (כל יום)"
+            checked={controls.showDigests}
+            onCheckedChange={(v) => onChange({ showDigests: v })}
+          />
           <ToggleRow
             label="הלכות (שלב ב׳)"
             checked={controls.showHalachot}

web-ui/src/components/graph/graph-node-panel.tsx

@@ -20,6 +20,7 @@ const TYPE_LABELS: Record<string, string> = {
   topic: "נושא",
   practice_area: "תחום",
   gap: "פסיקה חסרה",
+  digest: "יומון",
 };
 
 const GAP_STATUS_LABELS: Record<string, string> = {
@@ -52,6 +53,7 @@ export function GraphNodePanel({
 }) {
   const isPrecedentLike = node.type === "precedent" || node.type === "halacha";
   const isGap = node.type === "gap";
+  const isDigest = node.type === "digest";
   return (
     <Card className="bg-surface border-rule shadow-sm w-80 shrink-0 overflow-y-auto">
       <CardContent className="space-y-4 p-4">
@@ -98,7 +100,19 @@ export function GraphNodePanel({
               </p>
             </>
           )}
-          {!isPrecedentLike && !isGap && (
+          {isDigest && (
+            <>
+              {node.note && (
+                <p className="text-ink text-sm leading-relaxed m-0">{node.note}</p>
+              )}
+              {node.court && <Row label="ערכאה" value={node.court} />}
+              {node.date && <Row label="תאריך" value={node.date.slice(0, 10)} />}
+              <p className="text-ink-muted text-xs leading-relaxed m-0">
+                סיכום יומי מ״כל יום״ — מצביע על הפסיקה שהוא מנתח.
+              </p>
+            </>
+          )}
+          {!isPrecedentLike && !isGap && !isDigest && (
             <p className="text-ink-muted text-xs leading-relaxed m-0">
               לחיצה על נקודה זו מתמקדת בשכניה — כל הפסיקות המשויכות אליה.
             </p>
@@ -122,6 +136,15 @@ export function GraphNodePanel({
             </Link>
           </Button>
         )}
+
+        {isDigest && (
+          <Button asChild variant="outline" className="w-full">
+            <Link href="/digests">
+              <ExternalLink className="size-4 me-2" />
+              לעמוד היומונים
+            </Link>
+          </Button>
+        )}
       </CardContent>
     </Card>
   );

web-ui/src/components/graph/graph-view.tsx

@@ -66,6 +66,7 @@ export function GraphView() {
     showPracticeAreas: true,
     showHalachot: false,
     showGaps: false,
+    showDigests: false,
   });
   const facets = useGraphFacets().data;
   const [selectedNode, setSelectedNode] = useState<GraphNode | null>(null);
@@ -80,12 +81,14 @@ export function GraphView() {
     if (controls.showPracticeAreas) t.push("practice_area");
     if (controls.showHalachot) t.push("halacha");
     if (controls.showGaps) t.push("gap");
+    if (controls.showDigests) t.push("digest");
     return t.join(",");
   }, [
     controls.showTopics,
     controls.showPracticeAreas,
     controls.showHalachot,
     controls.showGaps,
+    controls.showDigests,
   ]);
 
   // Metrics are needed when colouring by cluster or sizing by a centrality.

web-ui/src/lib/api/graph.ts

@@ -19,7 +19,8 @@ export type GraphNodeType =
   | "halacha"
   | "topic"
   | "practice_area"
-  | "gap";
+  | "gap"
+  | "digest";
 
 export type GraphEdgeType =
   | "cites"
@@ -27,7 +28,8 @@ export type GraphEdgeType =
   | "tagged"
   | "in_area"
   | "corroborates"
-  | "equivalent";
+  | "equivalent"
+  | "covers";
 
 export type GraphNode = {
   id: string;
@@ -45,6 +47,8 @@ export type GraphNode = {
   community: number | null; // dense cluster id, 0 = largest
   gap_status: string | null; // gap nodes only — open|uploaded|closed|irrelevant
   missing_precedent_id: string | null; // gap nodes only
+  note: string | null; // digest nodes only — the holding line
+  digest_id: string | null; // digest nodes only
 };
 
 export type GraphFacets = {

web/graph_api.py

@@ -38,7 +38,7 @@ from pydantic import BaseModel
 from web import graph_metrics
 
 # ── Node-type vocabulary ─────────────────────────────────────────────
-VALID_NODE_TYPES = {"precedent", "halacha", "topic", "practice_area", "gap"}
+VALID_NODE_TYPES = {"precedent", "halacha", "topic", "practice_area", "gap", "digest"}
 DEFAULT_NODE_TYPES = ("precedent", "topic", "practice_area")
 NODE_CAP_DEFAULT = 400
 NODE_CAP_MAX = 1500
@@ -72,6 +72,9 @@ class GraphNode(BaseModel):
     # Gap nodes only — research-gap status from missing_precedents (best-effort).
     gap_status: str | None = None  # open | uploaded | closed | irrelevant
     missing_precedent_id: str | None = None
+    # Digest nodes only — the holding line from the daily יומון.
+    note: str | None = None
+    digest_id: str | None = None  # for deep-link to /digests
 
 
 class GraphFacets(BaseModel):
@@ -306,6 +309,97 @@ async def _gap_nodes_and_edges(
     return nodes, edges
 
 
+async def _digest_nodes_and_edges(
+    conn: asyncpg.Connection,
+    prec_ids: list,
+) -> tuple[list[GraphNode], list[GraphEdge], list[GraphNode]]:
+    """Daily-digest (יומון) discovery layer. Each digest ``covers`` the ruling
+    it analyses: a corpus precedent (``linked_case_law_id``) when we have it, or
+    a ``gap`` node synthesized from ``underlying_citation`` when we don't — so
+    the digest doubles as a research signal ("the feed flagged this ruling").
+
+    Returns (digest_nodes, covers_edges, gap_target_nodes). The caller dedups
+    gap nodes against the gap layer (real in-degree there wins over size=1)."""
+    digest_nodes: list[GraphNode] = []
+    edges: list[GraphEdge] = []
+    gap_nodes: list[GraphNode] = []
+    if not prec_ids:
+        return digest_nodes, edges, gap_nodes
+    prec_set = {str(x) for x in prec_ids}
+
+    rows = await conn.fetch(
+        """
+        SELECT id, yomon_number, concept_tag, headline_holding,
+               underlying_citation, underlying_court, underlying_date,
+               digest_date, practice_area, linked_case_law_id,
+               regexp_replace(btrim(underlying_citation), '\\s+', ' ', 'g') AS u_num
+        FROM digests
+        WHERE extraction_status = 'completed'
+          AND (linked_case_law_id = ANY($1::uuid[])
+               OR (linked_case_law_id IS NULL AND btrim(underlying_citation) <> ''))
+        ORDER BY digest_date DESC NULLS LAST
+        LIMIT 400
+        """,
+        prec_ids,
+    )
+    seen_gap: set[str] = set()
+    for r in rows:
+        did = f"dig:{r['id']}"
+        linked = r["linked_case_law_id"]
+        if linked is not None and str(linked) in prec_set:
+            target = f"cl:{linked}"
+        elif r["u_num"]:
+            target = f"gap:{r['u_num']}"
+            if r["u_num"] not in seen_gap:
+                seen_gap.add(r["u_num"])
+                gap_nodes.append(
+                    GraphNode(
+                        id=target,
+                        type="gap",
+                        label=(r["underlying_citation"] or "").strip() or r["u_num"],
+                        size=1,
+                    )
+                )
+        else:
+            continue
+        label = (r["concept_tag"] or "").strip() or (
+            f"יומון {r['yomon_number']}" if r["yomon_number"] else "יומון"
+        )
+        d = r["underlying_date"] or r["digest_date"]
+        digest_nodes.append(
+            GraphNode(
+                id=did,
+                type="digest",
+                label=label[:48],
+                note=((r["headline_holding"] or "").strip()[:160] or None),
+                court=(r["underlying_court"] or None),
+                date=(d.isoformat() if d else None),
+                practice_area=(r["practice_area"] or None),
+                digest_id=str(r["id"]),
+            )
+        )
+        edges.append(GraphEdge(source=did, target=target, type="covers"))
+    return digest_nodes, edges, gap_nodes
+
+
+async def _add_digests(
+    conn: asyncpg.Connection,
+    prec_ids: list,
+    nodes: list[GraphNode],
+    edges: list[GraphEdge],
+) -> None:
+    """Append the digest layer in place, adding digest-target gap nodes only if
+    they aren't already present (the gap layer's real in-degree wins)."""
+    dig_nodes, dig_edges, gap_targets = await _digest_nodes_and_edges(conn, prec_ids)
+    existing = {n.id for n in nodes}
+    for g in gap_targets:
+        if g.id not in existing:
+            nodes.append(g)
+            existing.add(g.id)
+    nodes.extend(dig_nodes)
+    edges.extend(dig_edges)
+
+
 # ── Endpoints' core logic ────────────────────────────────────────────
 async def build_corpus_graph(
     pool: asyncpg.Pool,
@@ -379,12 +473,15 @@ async def build_corpus_graph(
 
         total_available = int(prec_rows[0]["total_available"]) if prec_rows else 0
         nodes = [_precedent_node(r) for r in prec_rows]
+        prec_id_list = [r["id"] for r in prec_rows]
         hub_nodes, edges = await _edges_and_hubs(conn, prec_rows, types)
         nodes.extend(hub_nodes)
         if "gap" in types:
-            gap_nodes, gap_edges = await _gap_nodes_and_edges(conn, [r["id"] for r in prec_rows])
+            gap_nodes, gap_edges = await _gap_nodes_and_edges(conn, prec_id_list)
             nodes.extend(gap_nodes)
             edges.extend(gap_edges)
+        if "digest" in types:
+            await _add_digests(conn, prec_id_list, nodes, edges)
 
     if metrics:
         _stamp_metrics(nodes, edges)
@@ -516,12 +613,15 @@ async def build_node_neighborhood(
             ids,
         )
         nodes = [_precedent_node(r) for r in prec_rows]
+        prec_id_list = [r["id"] for r in prec_rows]
         hub_nodes, edges = await _edges_and_hubs(conn, prec_rows, forced_types)
         nodes.extend(hub_nodes)
         if "gap" in forced_types:
-            gap_nodes, gap_edges = await _gap_nodes_and_edges(conn, [r["id"] for r in prec_rows])
+            gap_nodes, gap_edges = await _gap_nodes_and_edges(conn, prec_id_list)
             nodes.extend(gap_nodes)
             edges.extend(gap_edges)
+        if "digest" in forced_types:
+            await _add_digests(conn, prec_id_list, nodes, edges)
 
     return CorpusGraph(
         nodes=nodes,