graph context: a separate marker message before the first user turn

The map picks no longer glue into the opening prompt as seed text
(owner, 2026-10-04 late). POST /api/chats accepts graphContext
{propositions}; the route resolves the picks against the live graph,
derives the reasoning chains among them (chainsForSelection →
formatChainLine), and writes a graph-context custom marker as
message[0] — before the learner's first user message, in either mode.

- Core: newGraphContextMessage (model-facing content = the
  contextualization framing + proposition lines + chain lines;
  details = the structured pick); toLlmMessages flattens it to a user
  message like every marker, so the model reads it for free.
- View: projects to a user-side data-graph-context part.
- UI: GraphContextCard — minimal, muted, dashed, collapsed by default
  (counts only); expand reveals name — statement rows and the chain
  lines. Same compact-expandable pattern as the practice cards.
- Home: sends graphContext with the creation whenever picks exist;
  the prompt param carries the learner's own words only.
This commit is contained in:
amosblomqvist
2026-10-04 23:07:13 +03:00
parent 87f8e1e6f4
commit 90893ae236
8 changed files with 327 additions and 13 deletions
+8
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@@ -38,6 +38,7 @@ import type { PlanBlockData } from "@/src/core";
import { QuestionDock } from "@/components/question-dock";
import { PracticeDock } from "@/components/practice-dock";
import { ThinkingCard, type PracticeThinkingData } from "@/components/practice-cards";
import { GraphContextCard, type GraphContextData } from "@/components/graph-context-card";
import { TopBar } from "@/components/top-bar";
import type { ArtifactPartProps, JobRecord, Phase3, QuestionAnswerData, TurnUsage } from "@/src/core";
import type { LhViewMessage } from "@/src/core";
@@ -1258,6 +1259,13 @@ export function Chat({
);
case "step-start":
return pi > 0 ? <Separator key={pi} className="my-3" /> : null;
case "data-graph-context":
// The session's map pick (2026-10-04): a minimal
// collapsible card — scaffolding above the first
// user message, never a bubble.
return (
<GraphContextCard key={pi} data={part.data as GraphContextData} />
);
case "data-practice-thinking":
// The learner's practice submission (2026-10-04):
// user-side — the register (thinking trace /
+63
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@@ -0,0 +1,63 @@
"use client";
import { useState } from "react";
import { ChevronRightIcon } from "lucide-react";
import { cn } from "@/lib/utils";
/**
* The graph-context card (owner, 2026-10-04): the session's map pick —
* message[0] of a session started with propositions picked from the
* graph. Scaffolding, not a turn: minimal, muted, collapsed by default;
* expand reveals the picked propositions (name — statement) and the
* reasoning chains among them (premises → conclusion lines). The model
* reads the same content through the marker's own text (toLlmMessages);
* this card is the learner's face of it.
*/
/** The graph-context marker's details (native-messages.ts). */
export interface GraphContextData {
propositions: { id: string; name: string; statement: string }[];
chains: string[];
}
export function GraphContextCard({ data }: { data: GraphContextData }) {
const [open, setOpen] = useState(false);
const { propositions = [], chains = [] } = data ?? {};
const noun = (n: number, one: string, many: string) => `${n} ${n === 1 ? one : many}`;
return (
<div data-testid="graph-context-card" className="my-1">
<button
type="button"
data-testid="graph-context-toggle"
onClick={() => setOpen((v) => !v)}
className="flex w-full cursor-pointer items-center gap-2 rounded-lg border border-dashed border-border/70 px-3 py-2 text-left text-xs text-muted-foreground transition-colors hover:text-foreground"
>
<ChevronRightIcon aria-hidden="true" className={cn("size-3.5 shrink-0 transition-transform", open && "rotate-90")} />
<span className="font-medium">Graph context</span>
<span className="min-w-0 flex-1 truncate">
{noun(propositions.length, "proposition", "propositions")}
{chains.length > 0 ? ` · ${noun(chains.length, "chain", "chains")}` : ""}
</span>
</button>
{open && (
<div data-testid="graph-context-body" className="mt-1 space-y-1 rounded-lg border border-dashed border-border/70 px-4 py-3 text-xs">
{propositions.map((p) => (
<div key={p.id} data-testid={`graph-context-prop-${p.id}`} className="leading-relaxed">
<span className="font-medium text-foreground/80">{p.name}</span>
<span className="text-muted-foreground"> — {p.statement}</span>
</div>
))}
{chains.length > 0 && (
<div className="pt-1">
{chains.map((c, i) => (
<div key={i} className="font-mono text-[11px] text-muted-foreground">
{c}
</div>
))}
</div>
)}
</div>
)}
</div>
);
}
+11 -12
View File
@@ -112,26 +112,25 @@ export function Home({ initialConfigured }: { initialConfigured: boolean }) {
}
setBusy(true);
try {
// The practice seed: the picks ride the OPENING PROMPT (never
// the title — the title stays the learner's own words).
const seed =
mode === "practice" && practiceProps.length > 0
? `\n\nPropositions from the map:\n${practiceProps
.map((p) => `- ${p.name}: ${p.statement}`)
.join("\n")}`
: "";
// The map context (owner, 2026-10-04): picks in EITHER mode ride
// the CREATION as graphContext — the server writes a
// graph-context marker as message[0] (a separate custom message
// before the learner's first user message, propositions + the
// chains among them); the prompt stays the learner's own words.
const res = await fetch("/api/chats", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify(
mode === "practice" ? { title: t, kind: "practice" } : { title: t },
),
body: JSON.stringify({
title: t,
...(mode === "practice" ? { kind: "practice" } : {}),
...(practiceProps.length > 0 ? { graphContext: { propositions: practiceProps } } : {}),
}),
});
const { id } = (await res.json()) as { id: string };
// No settings PUT on create (per-session models, owner
// 2026-09-28): the SERVER stamps the newborn from the strong
// slot — the same default this surface's model control edits.
router.push(`/chat/${id}?prompt=${encodeURIComponent(t + seed)}`);
router.push(`/chat/${id}?prompt=${encodeURIComponent(t)}`);
} catch {
setBusy(false);
}