refactor: Business logic and dependencies updates

- 核心服务代码更新 (db, server, auth, proxy)
- Agent 相关模块更新 (mindspace, experience)
- 前端组件和 hooks 更新
- 数据库 schema 更新
- 依赖版本更新
This commit is contained in:
john
2026-06-27 08:25:02 +08:00
parent f1220a7905
commit 25f8223253
20 changed files with 1458 additions and 116 deletions
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import crypto from 'node:crypto';
/**
* Shared experience store (etat C of the goose scale plan).
*
* All goosed Worker instances read/write the same learned experience so that
* capability is not siloed per instance. This first implementation is backed by
* MySQL (`h5_experience`) with a keyword + recency ranking. The retrieval scoring
* is deliberately isolated in `rankRows` so that swapping to PostgreSQL + pgvector
* later only replaces the query/scoring layer, not the calling contract
* (record / search / reflect).
*
* @param {import('mysql2/promise').Pool} pool
* @param {object} [options]
* @param {() => number} [options.now] - injectable clock for tests
*/
export function createExperienceService(pool, options = {}) {
const now = options.now ?? (() => Date.now());
// Recency half-life: a record this old contributes half its keyword score.
const halfLifeMs = Math.max(
60_000,
Number(options.recencyHalfLifeMs ?? 30 * 24 * 60 * 60 * 1000),
);
function normalizeTags(tags) {
if (!Array.isArray(tags)) return [];
return [...new Set(tags.map((t) => String(t).trim()).filter(Boolean))];
}
function rowToExperience(row) {
return {
id: row.id,
scope: row.scope,
kind: row.kind,
title: row.title,
body: row.body,
tags: row.tags_json ? safeJsonArray(row.tags_json) : [],
sourceSessionId: row.source_session_id ?? null,
sourceUserId: row.source_user_id ?? null,
useCount: Number(row.use_count ?? 0),
createdAt: Number(row.created_at),
updatedAt: Number(row.updated_at),
};
}
function safeJsonArray(value) {
if (Array.isArray(value)) return value;
try {
const parsed = JSON.parse(value);
return Array.isArray(parsed) ? parsed : [];
} catch {
return [];
}
}
// Keyword overlap × recency decay. Kept separate so the pgvector backend can
// replace this with cosine similarity without touching search()'s shape.
function rankRows(rows, queryTerms, nowMs) {
const terms = queryTerms;
return rows
.map((row) => {
const haystack = `${row.title}\n${row.body}`.toLowerCase();
let keywordScore = 0;
for (const term of terms) {
if (haystack.includes(term)) keywordScore += 1;
}
const ageMs = Math.max(0, nowMs - Number(row.updated_at));
const recency = Math.pow(0.5, ageMs / halfLifeMs);
const score = keywordScore * recency;
return { row, score };
})
.filter((entry) => entry.score > 0)
.sort((a, b) => b.score - a.score);
}
function tokenize(query) {
return [
...new Set(
String(query ?? '')
.toLowerCase()
.split(/[^\p{L}\p{N}]+/u)
.map((t) => t.trim())
.filter((t) => t.length >= 2),
),
];
}
/**
* Persist a piece of experience. Returns the stored record.
*/
async function record(input) {
const title = String(input?.title ?? '').trim();
const body = String(input?.body ?? '').trim();
if (!title) throw experienceError('经验标题不能为空', 'invalid_experience_input');
if (!body) throw experienceError('经验内容不能为空', 'invalid_experience_input');
const id = crypto.randomUUID();
const ts = now();
const scope = String(input?.scope ?? 'global').trim() || 'global';
const kind = String(input?.kind ?? 'lesson').trim() || 'lesson';
const tags = normalizeTags(input?.tags);
await pool.query(
`INSERT INTO h5_experience
(id, scope, kind, title, body, tags_json, source_session_id, source_user_id,
use_count, created_at, updated_at)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, 0, ?, ?)`,
[
id,
scope,
kind,
title,
body,
JSON.stringify(tags),
input?.sourceSessionId ?? null,
input?.sourceUserId ?? null,
ts,
ts,
],
);
return rowToExperience({
id,
scope,
kind,
title,
body,
tags_json: tags,
source_session_id: input?.sourceSessionId ?? null,
source_user_id: input?.sourceUserId ?? null,
use_count: 0,
created_at: ts,
updated_at: ts,
});
}
/**
* Retrieve the most relevant experience for a query within a scope.
* @returns {Promise<Array>} ranked experiences (best first), max `limit`.
*/
async function search(query, { scope = 'global', limit = 5 } = {}) {
const terms = tokenize(query);
if (terms.length === 0) return [];
// Pull a bounded candidate set by scope+recency, then rank in JS. The
// candidate cap keeps this cheap on MySQL; pgvector would push ranking into SQL.
const [rows] = await pool.query(
`SELECT id, scope, kind, title, body, tags_json, source_session_id,
source_user_id, use_count, created_at, updated_at
FROM h5_experience
WHERE scope = ?
ORDER BY updated_at DESC
LIMIT 500`,
[scope],
);
const ranked = rankRows(rows, terms, now()).slice(0, Math.max(1, limit));
if (ranked.length > 0) {
// Best-effort usage bump so popular experience can be surfaced/weighted later.
const ids = ranked.map((entry) => entry.row.id);
const placeholders = ids.map(() => '?').join(',');
await pool
.query(
`UPDATE h5_experience SET use_count = use_count + 1 WHERE id IN (${placeholders})`,
ids,
)
.catch(() => {});
}
return ranked.map((entry) => rowToExperience(entry.row));
}
/**
* Placeholder for the reflection pass that distills raw session traces into
* durable lessons. Wired later once the record() trigger points are defined;
* kept here so the calling contract is stable.
*/
async function reflect() {
return { ok: false, reason: 'not_implemented' };
}
return { record, search, reflect };
}
function experienceError(message, code) {
return Object.assign(new Error(message), { code });
}