Five refinements to the hand-rolled renderer, all user-directed: 1. Settings are SERVER-persisted (data/render-settings.json via new GET/PUT /api/graph/render-settings) - one source of truth for every browser, replacing localStorage. The client loads once after mount, saves debounced on user changes, and never lets a slow GET clobber a faster user (or mounting PUT defaults over the server copy). The shape/defaults/sanitizer moved to src/core/render-settings.ts - pure, shared by client, server store, and tests; every disk/network value passes through sanitizeRenderSettings. 2. New "Label size" control (default 12px - the previous hardcoded size). Font, wrap width, and line height all scale; verified live: +76k px with the label gate open. 3. "Labels until zoom" slider reworked: log-scaled over 0.0625-4 so the useful band (0.25-0.5 camera-ratio units) sits at 33%/50% of the track instead of crammed at the far left of the old linear 0.25-4 slider. Display units are normalized: the default 0.5 reads as "1x", 0.25 as "0.5x". The underlying labelZoom semantics are unchanged, so existing values survive. 4. Smooth wheel zoom: d3-zoom instant per-notch jumps (x1.2, bang) are replaced by an eased glide - wheel events accumulate a cursor-anchored target scale and each tick eases the camera toward it (exponential, 120ms constant, frame-rate independent). Pan/pinch stay d3-owned; a pan cancels a glide in progress. Verified live: 8-frame glide. 5. Resize blanking fixed (graph vanished for the duration of a window drag, reappearing ~300ms after). Cause: every resize event reallocated the canvas backing store - which CLEARS it - and the redraw was deferred to rAF, which live resizes starve via relayout, so the canvas sat wiped for the whole drag. Fix: the ResizeObserver callback now redraws SYNCHRONOUSLY after reallocating (verified via a probe RO firing in the same delivery batch: canvas fully painted). kFit (the label gate 1x reference) is also recomputed on resize from the now-cached world bbox - the camera itself still persists. tests/render-settings.test.ts: 10 tests pinning the sanitizer (garbage/ partial/clamps, legacy no-labelSize records) and the slider mapping (default dead-center at 500, monotonic, exact round-trips, display units). 402/402 green; typecheck, lint, build pass.
93 lines
4.3 KiB
TypeScript
93 lines
4.3 KiB
TypeScript
import path from "node:path";
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import { fileURLToPath } from "node:url";
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/** Repository root (this file is at <root>/config.ts). */
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export const ROOT = path.dirname(fileURLToPath(import.meta.url));
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export const PATHS = {
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root: ROOT,
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/** Teacher system prompt — the agent's instructions (src/agent/). */
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teacherPrompt: path.join(ROOT, "src", "agent", "system-prompt.md"),
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data: path.join(ROOT, "data"),
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/** Chat sessions (AI SDK UIMessage transcripts, one JSON file per chat). */
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chats: path.join(ROOT, "data", "chats"),
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graph: path.join(ROOT, "data", "graph"),
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} as const;
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// ─── Models ────────────────────────────────────────────────────────────────
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// THE single place every LLM is chosen and tuned. .env stays for secrets
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// (API keys) only — model choice and thinking budget are product tuning,
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// not deployment environment, and this section is the one place they grow.
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// `effort` is pi's thinking-level scale (off|minimal|low|medium|high|xhigh
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// |max): the per-model truth lives in pi-ai's catalog (thinkingLevelMap) —
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// getSupportedThinkingLevels(model) lists what a model actually accepts,
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// and streamSimple clamps any other value to the nearest supported one
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// (e.g. GLM-5.3-flash supports exactly low|high|max).
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export type ThinkingLevel = "off" | "minimal" | "low" | "medium" | "high" | "xhigh" | "max";
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export interface ModelSpec {
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/** OpenRouter model id (e.g. "z-ai/glm-5.3-flash") — must exist in pi-ai's catalog. */
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model: string;
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/** Thinking budget — what the model may spend on reasoning tokens. */
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effort: ThinkingLevel;
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}
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export const MODELS = {
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/** The prober (agent A) — edge-bracketing questions; keep it lively and adaptive. */
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prober: { model: "z-ai/glm-5.3-flash", effort: "low" },
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/** The teacher (agent B) — planning + streaming, lesson-facing: smart, but keep it lively. */
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teacher: { model: "z-ai/glm-5.3-flash", effort: "low" },
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/** Background sub-agents: fast and cheap beats deep thought. */
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researcher: { model: "z-ai/glm-5.3-flash", effort: "low" },
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demoBuilder: { model: "z-ai/glm-5.3-flash", effort: "low" },
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/** Must be vision-capable: it looks at rendered SVGs. */
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visualMaker: { model: "qwen/qwen3.8-flash", effort: "low" },
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/** Extraction is judgment over given evidence — light thinking suffices. */
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extractor: { model: "z-ai/glm-5.3-flash", effort: "low" },
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/** The auditor verifies evidence exists; keep it cheap. */
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auditor: { model: "z-ai/glm-5.3-flash", effort: "low" },
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/** Names detected communities — one singular call, given member names
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* + statements. Purely a labeling flourish; keep it cheap. */
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labeler: { model: "z-ai/glm-5.3-flash", effort: "low" },
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} satisfies Record<string, ModelSpec>;
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export type ModelRole = keyof typeof MODELS;
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/**
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* The extraction pipeline (vision §1 construction): the sole graph writer.
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* Triggered per chat once this many NEW quiz answers have landed since the
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* chat's last extraction checkpoint. The trigger mechanism is a v1
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* placeholder — deliberately isolated behind one seam
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* (server/turn-service.ts) so it can be swapped without touching the
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* pipeline.
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*/
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export const EXTRACTION = { everyNQuizAnswers: 3 } as const;
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/**
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* The LIVE graph store (src/store/graph.ts) — owned by the app's extraction
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* pipeline. Line shapes: src/core/contracts.ts.
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*/
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export const LEDGER_FILES = {
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nodes: path.join(PATHS.graph, "nodes.jsonl"),
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edges: path.join(PATHS.graph, "edges.jsonl"),
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events: path.join(PATHS.graph, "events.jsonl"),
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mappings: path.join(PATHS.graph, "mappings.jsonl"),
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sessions: path.join(PATHS.graph, "sessions.jsonl"),
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/** LLM-named community records (contracts/graph.ts ClusterLabeling). */
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clusterLabels: path.join(PATHS.graph, "cluster-labels.jsonl"),
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} as const;
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/**
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* Notes-import bookkeeping (NOT a ledger): one JSON map, src-id → NotesSource
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* record (contracts/graph.ts) — the file path + import time + the run's usage
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* log. Read-modify-write like a chat file, not append-only like the ledgers.
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*/
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export const SOURCES_FILE = path.join(PATHS.graph, "sources.json");
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/**
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* Graph render settings (the settings-panel controls): one small JSON blob,
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* read-modify-write. Shared shape/sanitizer: src/core/render-settings.ts.
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*/
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export const RENDER_SETTINGS_FILE = path.join(PATHS.graph, "render-settings.json");
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