feat: graph context injection — the session's prior knowledge, steered in at session start (vision-context-injection.md)
One shot per chat, fired at the first turn's onFinish: the session's topic (its only typed message) is embedded as an EmbeddingGemma retrieval query; the semantically closest graph propositions are selected under the session's token budget (pure budget, no similarity threshold — the decided doctrine) and delivered as a marker-only steer through the wake pipeline, queuing behind pending questions like every sub-agent result. - contracts: ChatSettings.graphContextTokens (default 1024, max 4096, step 128, 0 = off); GraphContextData + graphContextText; the graph-context JobKind + buildGraphContextSteer (id steer_ctx_<chatId>) - core/graph-context.ts: brute-force cosine top-K, greedy chars/4 fill under budget, most-recent UnderstandingLevel fold, count cap 64, parse-don't-cast at the marker seam - server: embedQuery (role-asymmetric query format, same warm singleton — vector-space parity by construction); the runner (startGraphContext- Injection one-shot gates; runGraphContextJob validates ledger parity); wake branches (chatIdOf/jobIdOf, finalizeJob done, recoverStaleJobs re-deliver or contextRespawn); abortJob kills context jobs SILENTLY (nothing was promised in the lesson); turn-service trigger seam - adapter: data-graph-context flattens to the canonical block (malformed parts have no model face) - UI: the budget slider (home dock + /chat/new draft, the session-data strip); the quiet SystemLine "~537 · 10 propositions"; dock kind "Knowledge context"; model-picker PUT now spreads settings (a model pick can no longer clear the sibling override) Live-smoked end to end on the real embedder + real GLM: seeded ledger (10 propositions), session on "modal logic: possible worlds and the necessity box" — job in the dock, queued behind the prober's question, delivered on the answer, SystemLine in the transcript, wake turn reads the block and continues the probe. Gates: tsc, lint, 459/459, build.
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@@ -21,6 +21,9 @@ const KIND_LABEL: Record<JobKind, string> = {
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research: "Research agent",
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demo: "Demo agent",
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visual: "Figure agent",
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// The injection is server-initiated — it has no tool part, so never a
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// dispatch card. The entry exists only for the exhaustive record.
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"graph-context": "Knowledge context",
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};
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export function DispatchCard({ toolCallId, kind }: { toolCallId: string; kind: JobKind }) {
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