Extraction pipeline: extractor → auditor → merger — the sole graph writer (stage 5)

The knowledge graph's write channel is now the pivot's target
architecture (vision §1 construction):

- src/agent/subagents/extraction.ts — the pipeline factory
  (createExtractionPipeline({ chatStore, graphStore, extractor?,
  auditor? }); models env LH_EXTRACT_MODEL ?? LH_MODEL):
  * transcriptView(): the compact view both LLM stages see — final plan
    tree with node ids, conversation verbatim, QUIZ lines with outcomes,
    mark_done lines; job tool parts are one-liners, plan ops fold into
    the tree line.
  * Extractor: transcript → SessionFindings (propositions incl.
    misconceptions and prose-only supports edges, attribution for
    UNTAGGED probes, all with verbatim evidence) via one zod-validated
    submit_findings call.
  * Auditor: transcript + findings → the verified subset + drops (the
    faithfulness net) via submit_review.
- src/core/graph.ts — emitChat/foldStaleChats/replayFinalTree retire;
  mergeFindings() replaces them as the pipeline's deterministic apply
  stage: exact/alias identity resolution (one mapping line per (chat,
  graph node)), edge dedupe, and event rebuild FROM THE TRANSCRIPT's tool
  parts — kinds/timestamps/refs/notes deterministic, the LLM's only event
  say being WHICH proposition an untagged probe tested (retroactive —
  the vision's open question #3, resolved structurally: tagged events
  resolve deterministically; attribution rescues untagged and
  tagged-but-unmapped ones; unattributable land null + question text).
  pendingQuizAnswers() is the trigger helper.
- Trigger (turn-service.ts triggerExtraction, replacing the old
  foldTurnIntoGraph body): once a chat accumulates
  EXTRACTION.everyNQuizAnswers (LH_EXTRACT_N, default 3) new answered
  quizzes, fire the pipeline async — single-flight per chat, failure
  checkpoints nothing and re-runs on the next trigger. Deliberately a v1
  placeholder isolated in ONE seam, trigger-agnostic pipeline.
- GET /api/graph is now a pure read (foldStaleChats gone).
- NodeMapping.treeNodeId → sourceId (the mapping key is now the writer's
  local proposition id — tree node when tree-derived); store strict-read
  schema updated. Local ledger data regenerates through the pipeline.
- Tests: graph.test.ts rewritten around mergeFindings (identity,
  attribution paths incl. ghost-rescue, idempotency, cross-session
  provenance, trigger counting), graph-context.test.ts merge section
  converted to findings-driven, NEW extraction.test.ts — transcriptView
  units + the full pipeline with mock models (audit drops, failure
  checkpoints nothing, single-flight). 195/195, tsc/eslint/build clean.

Probe attribution (vision open question): probes attach retroactively by
the extractor against the whole transcript; a pre-tree probe maps to a
proposition the tree only articulates later. Fuzzy/embedding merge
adjudication stays deferred (conservative exact/alias only).

src/server/chat-handler.ts

@@ -1,9 +1,10 @@
 import { createAgentUIStreamResponse, type UIMessage } from "ai";
 import { createTeacherAgent, type TeacherAgent } from "../agent/teacher-agent.ts";
 import { createJobRunner } from "../agent/subagents/runner.ts";
+import { createExtractionPipeline } from "../agent/subagents/extraction.ts";
 import { createTeacherTools } from "../agent/tools.ts";
 import { stores } from "./stores.ts";
-import { buildTeacherContext, foldTurnIntoGraph, persistTurn, spawnTurnJobs } from "./turn-service.ts";
+import { buildTeacherContext, persistTurn, spawnTurnJobs, triggerExtraction } from "./turn-service.ts";
 
 /**
  * One chat turn: run the teacher agent over the client's message list and
@@ -18,6 +19,7 @@ import { buildTeacherContext, foldTurnIntoGraph, persistTurn, spawnTurnJobs } fr
  */
 
 const jobRunner = createJobRunner(stores);
+const extraction = createExtractionPipeline(stores);
 
 export async function handleChatRequest(req: Request, agent?: TeacherAgent): Promise<Response> {
 	let body: { chatId?: unknown; messages?: unknown };
@@ -46,7 +48,7 @@ export async function handleChatRequest(req: Request, agent?: TeacherAgent): Pro
 		onFinish: ({ messages, isAborted }) => {
 			persistTurn(stores.chatStore, chatId, messages as UIMessage[], isAborted);
 			spawnTurnJobs(jobRunner, chatId, messages as UIMessage[]);
-			foldTurnIntoGraph(stores, chatId);
+			triggerExtraction(stores, extraction, chatId);
 		},
 	});
 }