amosblomqvist
543cf33789
The same extractor→auditor→merger pipeline now runs over raw personal
notes in arbitrary formats (vision §1, DECIDED 2026-09-13):
- NotesSource records (data/graph/sources.json, deterministic id from
path hash → idempotent re-imports) play the chatId role in mappings,
checkpoints, and observation events; usage lands on the source record
(appendSourceUsage, idempotent per startedAt, kept across upserts).
- mergeFindings is chat-store-free: callers pass MergeSource
{messages, foldedAt} — sessions pass the chat record, notes pass
messages:null (no quiz-event rebuild; a deterministic rebuild needs
structured quiz tool parts).
- Second extractor prompt (NOTES_EXTRACTOR_INSTRUCTIONS) for general-
purpose extraction; understanding judges the AUTHOR's grasp. Auditor
wording input-agnostic. extract/audit share one generic runSubmitAgent.
- graphSnapshot.fileSources (srcId→filePath); notes sources render as
static path entries in the detail card (FileTextIcon, never a link).
- One shared pipeline instance (exported from chat-handler): same
single-flight registry, live status chips (label = file path), usage
accounting, and true abort for both front doors.
- Transport: POST /api/graph/import (multipart, 3-wide worker pool) +
Import notes… button in the graph view; scripts/import-notes.ts for
batch runs (concurrency 4).
- real-data-extraction/ gitignored (raw import sources never committed).
355/355 tests; typecheck, lint, build green.
82 lines
3.8 KiB
TypeScript
82 lines
3.8 KiB
TypeScript
import path from "node:path";
|
|
import { fileURLToPath } from "node:url";
|
|
|
|
/** Repository root (this file is at <root>/config.ts). */
|
|
export const ROOT = path.dirname(fileURLToPath(import.meta.url));
|
|
|
|
export const PATHS = {
|
|
root: ROOT,
|
|
/** Teacher system prompt — the agent's instructions (src/agent/). */
|
|
teacherPrompt: path.join(ROOT, "src", "agent", "system-prompt.md"),
|
|
data: path.join(ROOT, "data"),
|
|
/** Chat sessions (AI SDK UIMessage transcripts, one JSON file per chat). */
|
|
chats: path.join(ROOT, "data", "chats"),
|
|
graph: path.join(ROOT, "data", "graph"),
|
|
} as const;
|
|
|
|
// ─── Models ────────────────────────────────────────────────────────────────
|
|
// THE single place every LLM is chosen and tuned. .env stays for secrets
|
|
// (API keys) only — model choice and thinking budget are product tuning,
|
|
// not deployment environment, and this section is the one place they grow.
|
|
// `effort` is pi's thinking-level scale (off|minimal|low|medium|high|xhigh
|
|
// |max): the per-model truth lives in pi-ai's catalog (thinkingLevelMap) —
|
|
// getSupportedThinkingLevels(model) lists what a model actually accepts,
|
|
// and streamSimple clamps any other value to the nearest supported one
|
|
// (e.g. GLM-5.3-flash supports exactly low|high|max).
|
|
|
|
export type ThinkingLevel = "off" | "minimal" | "low" | "medium" | "high" | "xhigh" | "max";
|
|
|
|
export interface ModelSpec {
|
|
/** OpenRouter model id (e.g. "z-ai/glm-5.3-flash") — must exist in pi-ai's catalog. */
|
|
model: string;
|
|
/** Thinking budget — what the model may spend on reasoning tokens. */
|
|
effort: ThinkingLevel;
|
|
}
|
|
|
|
export const MODELS = {
|
|
/** The prober (agent A) — edge-bracketing questions; keep it lively and adaptive. */
|
|
prober: { model: "z-ai/glm-5.3-flash", effort: "low" },
|
|
/** The teacher (agent B) — planning + streaming, lesson-facing: smart, but keep it lively. */
|
|
teacher: { model: "z-ai/glm-5.3-flash", effort: "low" },
|
|
/** Background sub-agents: fast and cheap beats deep thought. */
|
|
researcher: { model: "z-ai/glm-5.3-flash", effort: "low" },
|
|
demoBuilder: { model: "z-ai/glm-5.3-flash", effort: "low" },
|
|
/** Must be vision-capable: it looks at rendered SVGs. */
|
|
visualMaker: { model: "qwen/qwen3.8-flash", effort: "low" },
|
|
/** Extraction is judgment over given evidence — light thinking suffices. */
|
|
extractor: { model: "z-ai/glm-5.3-flash", effort: "low" },
|
|
/** The auditor verifies evidence exists; keep it cheap. */
|
|
auditor: { model: "z-ai/glm-5.3-flash", effort: "low" },
|
|
} satisfies Record<string, ModelSpec>;
|
|
|
|
export type ModelRole = keyof typeof MODELS;
|
|
|
|
/**
|
|
* The extraction pipeline (vision §1 construction): the sole graph writer.
|
|
* Triggered per chat once this many NEW quiz answers have landed since the
|
|
* chat's last extraction checkpoint. The trigger mechanism is a v1
|
|
* placeholder — deliberately isolated behind one seam
|
|
* (server/turn-service.ts) so it can be swapped without touching the
|
|
* pipeline.
|
|
*/
|
|
export const EXTRACTION = { everyNQuizAnswers: 3 } as const;
|
|
|
|
/**
|
|
* The LIVE graph store (src/store/graph.ts) — owned by the app's extraction
|
|
* pipeline. Line shapes: src/core/contracts.ts.
|
|
*/
|
|
export const LEDGER_FILES = {
|
|
nodes: path.join(PATHS.graph, "nodes.jsonl"),
|
|
edges: path.join(PATHS.graph, "edges.jsonl"),
|
|
events: path.join(PATHS.graph, "events.jsonl"),
|
|
mappings: path.join(PATHS.graph, "mappings.jsonl"),
|
|
sessions: path.join(PATHS.graph, "sessions.jsonl"),
|
|
} as const;
|
|
|
|
/**
|
|
* Notes-import bookkeeping (NOT a ledger): one JSON map, src-id → NotesSource
|
|
* record (contracts/graph.ts) — the file path + import time + the run's usage
|
|
* log. Read-modify-write like a chat file, not append-only like the ledgers.
|
|
*/
|
|
export const SOURCES_FILE = path.join(PATHS.graph, "sources.json");
|