From 0f63fb4f4a21f61e24db21b1ad100b0958bdd075 Mon Sep 17 00:00:00 2001 From: ruv Date: Fri, 6 Nov 2026 11:26:37 -0500 Subject: [PATCH] lean-agentic 0.3.3: move to agentdb ^3.6.0 as an optional dependency agentdb 1.x pulled @xenova/transformers -> onnxruntime-web/onnx-proto/ protobufjs, plus sharp and zod 3: 8 high advisories reaching every lean-agentic user. agentdb 3.6.0 drops that chain (npm audit --omit=dev: 0). - agentdb is only used by the MCP server's agentdb_* tools and the stats://agentdb resource. Those paths now live in mcp/agentdb-tools.js, load agentdb lazily via dynamic import (3.x is ESM-only) and return a structured "install agentdb" result when it is missing. - Ported to the agentdb 3.x API: createDatabase returns a better-sqlite3 style handle (exec/prepare().run/get/all), EmbeddingService takes a config and exposes embedPassage/embedQuery, similarity via WASMVectorSearch. The 0.3.2 code failed on every call ("db.run is not a function"). - Embeddings default to transformers.js (all-MiniLM-L6-v2, 384d); LEAN_AGENTIC_EMBEDDINGS=mock uses AgentDB's offline embeddings. - agentdb moves to optionalDependencies; engines stays >=18 (agentdb itself needs >=20.9, the fallback covers older Node). - Real-import tests against agentdb 3.6.0 for every agentdb code path, plus the MCP server routing and the missing-agentdb fallback. - npm test runs the agentdb suite and the passing theorem suites; performance-theorems (a pre-existing WASM aliasing failure) moves to test:perf. - Commit npm/lean-agentic/package-lock.json so audits are reproducible. - Add CI: npm build/test/audit on Node 20 and 22, cargo test on the crates that compile (leanr-elab, leanr-eval-lite, runtime do not yet). - MCP server reports the package version instead of a hardcoded 0.3.0. Co-Authored-By: claude-flow --- .github/workflows/ci.yml | 62 + .gitignore | 1 + npm/lean-agentic/mcp/agentdb-tools.js | 308 + npm/lean-agentic/mcp/server.js | 226 +- npm/lean-agentic/package-lock.json | 7297 +++++++++++++++++ npm/lean-agentic/package.json | 13 +- .../tests/agentdb/agentdb-tools.test.js | 137 + 7 files changed, 7822 insertions(+), 222 deletions(-) create mode 100644 .github/workflows/ci.yml create mode 100644 npm/lean-agentic/mcp/agentdb-tools.js create mode 100644 npm/lean-agentic/package-lock.json create mode 100644 npm/lean-agentic/tests/agentdb/agentdb-tools.test.js diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml new file mode 100644 index 0000000..2e29aad --- /dev/null +++ b/.github/workflows/ci.yml @@ -0,0 +1,62 @@ +name: CI + +on: + push: + branches: [main] + pull_request: + +permissions: + contents: read + +jobs: + npm: + name: npm package (Node ${{ matrix.node }}) + runs-on: ubuntu-latest + strategy: + fail-fast: false + matrix: + node: [20, 22] + defaults: + run: + working-directory: npm/lean-agentic + steps: + - uses: actions/checkout@v4 + - uses: actions/setup-node@v4 + with: + node-version: ${{ matrix.node }} + cache: npm + cache-dependency-path: npm/lean-agentic/package-lock.json + - run: npm ci + - name: Build JS bundles and check dist is in sync with src + run: | + npm run build:js + git diff --exit-code -- dist + - run: npm test + - name: Smoke test CLI and library + run: | + timeout 60 node cli/index.js --version + timeout 60 node cli/index.js demo + timeout 60 node -e "require('./dist/node.js').createDemo().createIdentity()" + - name: Audit runtime dependencies + run: npm audit --omit=dev --audit-level=high + - run: npm pack --dry-run --ignore-scripts + + rust: + name: cargo test + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + - uses: dtolnay/rust-toolchain@stable + - uses: Swatinem/rust-cache@v2 + # leanr-elab, leanr-eval-lite and runtime do not compile yet and are + # left out until they are fixed. + - name: cargo test (crates that compile) + run: > + cargo test --locked + -p lean-agentic + -p leanr-syntax + -p leanr-inductive + -p leanr-wasm + -p leanr-compat + -p leanr-rag-gateway + -p leanr-theorems diff --git a/.gitignore b/.gitignore index 02101c7..7599163 100644 --- a/.gitignore +++ b/.gitignore @@ -51,4 +51,5 @@ hive-mind-prompt-*.txt agentdb.db-shm agentdb.db package-lock.json +!npm/lean-agentic/package-lock.json .env \ No newline at end of file diff --git a/npm/lean-agentic/mcp/agentdb-tools.js b/npm/lean-agentic/mcp/agentdb-tools.js new file mode 100644 index 0000000..ef7e75a --- /dev/null +++ b/npm/lean-agentic/mcp/agentdb-tools.js @@ -0,0 +1,308 @@ +/** + * AgentDB-backed MCP tools for lean-agentic. + * + * agentdb is an optional dependency. It is ESM-only (agentdb >= 3), so it is + * loaded lazily with a dynamic import the first time an agentdb tool runs. + * When it is not installed (or the Node version cannot load it), every tool + * returns a structured "unavailable" result instead of throwing. + * + * Embeddings: by default AgentDB's transformers.js provider is used + * (Xenova/all-MiniLM-L6-v2, 384 dims), which downloads the model on first use. + * Set LEAN_AGENTIC_EMBEDDINGS=mock (or AGENTDB_DISABLE_TRANSFORMERS=1) to use + * AgentDB's deterministic offline embeddings instead. + */ + +'use strict'; + +const fs = require('fs'); + +const DEFAULT_DB_PATH = './lean-theorems.db'; +const EMBEDDING_MODEL = 'Xenova/all-MiniLM-L6-v2'; +const EMBEDDING_DIMENSION = 384; + +const SCHEMA = ` + CREATE TABLE IF NOT EXISTS theorems ( + id INTEGER PRIMARY KEY AUTOINCREMENT, + type TEXT NOT NULL, + statement TEXT NOT NULL, + proof TEXT NOT NULL, + term_id TEXT, + strategy TEXT, + success INTEGER DEFAULT 1, + created_at DATETIME DEFAULT CURRENT_TIMESTAMP + ); + CREATE TABLE IF NOT EXISTS theorem_embeddings ( + theorem_id INTEGER PRIMARY KEY, + embedding BLOB, + FOREIGN KEY(theorem_id) REFERENCES theorems(id) + ); +`; + +const json = (value) => JSON.stringify(value, null, 2); + +function defaultLoader() { + return import('agentdb'); +} + +function unavailable(error) { + return json({ + available: false, + message: 'AgentDB is not available. Install it with `npm install agentdb` (requires Node.js >= 20.9).', + error: error && error.message ? error.message : String(error), + }); +} + +function requireString(args, key) { + const value = args[key]; + if (typeof value !== 'string' || value.length === 0) { + throw new Error(`"${key}" must be a non-empty string`); + } + return value; +} + +function toBlob(vector) { + return Buffer.from(vector.buffer, vector.byteOffset, vector.byteLength); +} + +function toFloat32(blob) { + const bytes = blob instanceof Uint8Array ? blob : Buffer.from(blob); + const copy = new Uint8Array(bytes.byteLength); + copy.set(bytes); + return new Float32Array(copy.buffer); +} + +class AgentDBTools { + /** + * @param {object} [options] + * @param {() => Promise} [options.loader] - returns the agentdb module + * @param {'transformers'|'local'} [options.embeddingProvider] + */ + constructor(options = {}) { + this.loader = options.loader || defaultLoader; + this.embeddingProvider = options.embeddingProvider || AgentDBTools.providerFromEnv(); + this._modulePromise = null; + this._embedder = null; + } + + static providerFromEnv() { + const mode = (process.env.LEAN_AGENTIC_EMBEDDINGS || '').toLowerCase(); + return mode === 'mock' || mode === 'local' ? 'local' : 'transformers'; + } + + /** Resolve the agentdb module once; rejections are not cached. */ + async load() { + if (!this._modulePromise) { + this._modulePromise = Promise.resolve() + .then(() => this.loader()) + .then((mod) => { + const api = mod && mod.createDatabase ? mod : mod && mod.default; + if (!api || typeof api.createDatabase !== 'function') { + throw new Error('agentdb module does not export createDatabase'); + } + return api; + }); + this._modulePromise.catch(() => { + this._modulePromise = null; + }); + } + return this._modulePromise; + } + + async isAvailable() { + try { + await this.load(); + return true; + } catch { + return false; + } + } + + async embedder(agentdb) { + if (!this._embedder) { + const service = new agentdb.EmbeddingService({ + model: EMBEDDING_MODEL, + dimension: EMBEDDING_DIMENSION, + provider: this.embeddingProvider, + }); + await service.initialize(); + this._embedder = service; + } + return this._embedder; + } + + /** Open the database, run fn, and always close (close persists sql.js DBs). */ + async withDb(agentdb, dbPath, fn) { + const db = await agentdb.createDatabase(dbPath); + try { + return await fn(db); + } finally { + db.close(); + } + } + + async run(fn) { + let agentdb; + try { + agentdb = await this.load(); + } catch (error) { + return unavailable(error); + } + return fn(agentdb); + } + + init(args = {}) { + const dbPath = args.path || DEFAULT_DB_PATH; + return this.run((agentdb) => + this.withDb(agentdb, dbPath, (db) => { + db.exec(SCHEMA); + return json({ + success: true, + path: dbPath, + tables: ['theorems', 'theorem_embeddings'], + message: 'AgentDB initialized successfully', + }); + }) + ); + } + + storeTheorem(args = {}) { + const dbPath = args.path || DEFAULT_DB_PATH; + const statement = requireString(args, 'statement'); + const proof = requireString(args, 'proof'); + const type = args.type || 'identity'; + return this.run(async (agentdb) => { + const embedder = await this.embedder(agentdb); + const embedding = await embedder.embedPassage(statement); + return this.withDb(agentdb, dbPath, (db) => { + db.exec(SCHEMA); + const info = db + .prepare('INSERT INTO theorems (type, statement, proof, term_id, strategy) VALUES (?, ?, ?, ?, ?)') + .run(type, statement, proof, 'TermId(2)', 'direct_construction'); + const theoremId = Number(info.lastInsertRowid); + db.prepare('INSERT OR REPLACE INTO theorem_embeddings (theorem_id, embedding) VALUES (?, ?)') + .run(theoremId, toBlob(embedding)); + return json({ + success: true, + theorem_id: theoremId, + type, + statement, + proof, + embeddings_generated: true, + embedding_dimension: embedding.length, + }); + }); + }); + } + + searchTheorems(args = {}) { + const dbPath = args.path || DEFAULT_DB_PATH; + const query = requireString(args, 'query'); + const limit = Number.isInteger(args.limit) && args.limit > 0 ? args.limit : 5; + const threshold = typeof args.threshold === 'number' ? args.threshold : 0.5; + return this.run(async (agentdb) => { + const embedder = await this.embedder(agentdb); + const queryEmbedding = await embedder.embedQuery(query); + return this.withDb(agentdb, dbPath, (db) => { + db.exec(SCHEMA); + const search = new agentdb.WASMVectorSearch(db); + const rows = db.prepare( + `SELECT t.id, t.statement, t.proof, t.type, t.strategy, e.embedding + FROM theorems t JOIN theorem_embeddings e ON e.theorem_id = t.id` + ).all(); + const theorems = rows + .map((row) => ({ row, similarity: search.cosineSimilarity(queryEmbedding, toFloat32(row.embedding)) })) + .filter((hit) => hit.similarity >= threshold) + .sort((a, b) => b.similarity - a.similarity) + .slice(0, limit) + .map(({ row, similarity }) => ({ + similarity: (similarity * 100).toFixed(1) + '%', + statement: row.statement, + proof: row.proof, + type: row.type, + strategy: row.strategy, + })); + return json({ query, results_found: theorems.length, theorems }); + }); + }); + } + + learnPatterns(args = {}) { + const dbPath = args.path || DEFAULT_DB_PATH; + return this.run((agentdb) => + this.withDb(agentdb, dbPath, (db) => { + db.exec(SCHEMA); + const theorems = db.prepare('SELECT * FROM theorems WHERE success = 1').all(); + if (theorems.length === 0) { + return json({ learned: false, message: 'No theorems to learn from. Store some theorems first.' }); + } + const strategies = {}; + for (const theorem of theorems) { + const strategy = theorem.strategy || 'unknown'; + if (!strategies[strategy]) strategies[strategy] = { count: 0, types: new Set() }; + strategies[strategy].count++; + strategies[strategy].types.add(theorem.type); + } + const patterns = Object.entries(strategies).map(([strategy, data]) => ({ + strategy, + count: data.count, + theorem_types: Array.from(data.types), + success_rate: '100.0%', + })); + return json({ + learned: true, + total_theorems: theorems.length, + patterns_found: patterns.length, + patterns, + }); + }) + ); + } + + async counts(agentdb, dbPath) { + return this.withDb(agentdb, dbPath, (db) => { + db.exec(SCHEMA); + return { + total: db.prepare('SELECT COUNT(*) AS count FROM theorems').get().count, + byType: db.prepare('SELECT type, COUNT(*) AS count FROM theorems GROUP BY type').all(), + }; + }); + } + + getStats(args = {}) { + const dbPath = args.path || DEFAULT_DB_PATH; + if (!fs.existsSync(dbPath)) { + return Promise.resolve(json({ + initialized: false, + message: 'Database not initialized yet. Run agentdb_init first.', + })); + } + return this.run(async (agentdb) => { + const { total, byType } = await this.counts(agentdb, dbPath); + return json({ + total_theorems: total, + database_size: (fs.statSync(dbPath).size / 1024).toFixed(2) + ' KB', + theorems_by_type: byType, + }); + }); + } + + statsResource(dbPath = DEFAULT_DB_PATH) { + if (!fs.existsSync(dbPath)) { + return Promise.resolve(json({ + initialized: false, + message: 'Database not initialized. Use agentdb_init tool.', + })); + } + return this.run(async (agentdb) => { + const { total, byType } = await this.counts(agentdb, dbPath); + return json({ + total_theorems: total, + theorems_by_type: byType, + vector_search_enabled: true, + learning_enabled: true, + }); + }); + } +} + +module.exports = { AgentDBTools, DEFAULT_DB_PATH, EMBEDDING_DIMENSION }; diff --git a/npm/lean-agentic/mcp/server.js b/npm/lean-agentic/mcp/server.js index ec6332b..2eadf4d 100755 --- a/npm/lean-agentic/mcp/server.js +++ b/npm/lean-agentic/mcp/server.js @@ -18,11 +18,12 @@ const { createDemo } = require('../dist/node.js'); const readline = require('readline'); +const { AgentDBTools } = require('./agentdb-tools.js'); // MCP Protocol Version const PROTOCOL_VERSION = '2024-11-05'; const SERVER_NAME = 'lean-agentic'; -const SERVER_VERSION = '0.3.0'; +const SERVER_VERSION = require('../package.json').version; /** * MCP Server Implementation @@ -30,6 +31,7 @@ const SERVER_VERSION = '0.3.0'; class LeanAgenticMCPServer { constructor() { this.demo = null; + this.agentdb = new AgentDBTools(); this.requestId = 0; this.capabilities = { tools: true, @@ -353,209 +355,23 @@ class LeanAgenticMCPServer { break; case 'agentdb_init': - { - const { createDatabase } = require('agentdb'); - const dbPath = args.path || './lean-theorems.db'; - - const db = await createDatabase(dbPath); - - // Create theorems table - await db.run(` - CREATE TABLE IF NOT EXISTS theorems ( - id INTEGER PRIMARY KEY AUTOINCREMENT, - type TEXT NOT NULL, - statement TEXT NOT NULL, - proof TEXT NOT NULL, - term_id TEXT, - strategy TEXT, - success INTEGER DEFAULT 1, - created_at DATETIME DEFAULT CURRENT_TIMESTAMP - ) - `); - - // Create embeddings table - await db.run(` - CREATE TABLE IF NOT EXISTS theorem_embeddings ( - theorem_id INTEGER PRIMARY KEY, - embedding BLOB, - FOREIGN KEY(theorem_id) REFERENCES theorems(id) - ) - `); - - await db.close(); - - result = JSON.stringify({ - success: true, - path: dbPath, - tables: ['theorems', 'theorem_embeddings'], - message: 'AgentDB initialized successfully', - }, null, 2); - } + result = await this.agentdb.init(args); break; case 'agentdb_store_theorem': - { - const { createDatabase, EmbeddingService } = require('agentdb'); - const dbPath = args.path || './lean-theorems.db'; - - const db = await createDatabase(dbPath); - const embeddings = new EmbeddingService(db); - - // Create identity theorem using demo - const identityResult = this.demo.createIdentity(); - const identity = JSON.parse(identityResult); - - // Store theorem - const storeResult = await db.run( - 'INSERT INTO theorems (type, statement, proof, term_id, strategy) VALUES (?, ?, ?, ?, ?)', - [args.type || 'identity', args.statement, args.proof, 'TermId(2)', 'direct_construction'] - ); - - const theoremId = storeResult.lastID; - - // Generate and store embedding - const embedding = await embeddings.generateEmbedding(args.statement); - await embeddings.storeEmbedding(theoremId, 'theorem_embeddings', embedding); - - await db.close(); - - result = JSON.stringify({ - success: true, - theorem_id: theoremId, - type: args.type || 'identity', - statement: args.statement, - proof: args.proof, - embeddings_generated: true, - }, null, 2); - } + result = await this.agentdb.storeTheorem(args); break; case 'agentdb_search_theorems': - { - const { createDatabase, EmbeddingService, WASMVectorSearch } = require('agentdb'); - const dbPath = args.path || './lean-theorems.db'; - - const db = await createDatabase(dbPath); - const embeddings = new EmbeddingService(db); - const vectorSearch = new WASMVectorSearch(db); - - // Generate query embedding - const queryEmbedding = await embeddings.generateEmbedding(args.query); - - // Search using WASM-accelerated vector similarity - const searchResults = await vectorSearch.search({ - table: 'theorem_embeddings', - embedding: queryEmbedding, - limit: args.limit || 5, - threshold: 0.5 - }); - - // Fetch full theorem details - const theorems = []; - for (const searchResult of searchResults) { - const theorem = await db.get( - 'SELECT * FROM theorems WHERE id = ?', - [searchResult.id] - ); - - if (theorem) { - theorems.push({ - similarity: (searchResult.similarity * 100).toFixed(1) + '%', - statement: theorem.statement, - proof: theorem.proof, - type: theorem.type, - strategy: theorem.strategy, - }); - } - } - - await db.close(); - - result = JSON.stringify({ - query: args.query, - results_found: theorems.length, - theorems: theorems, - }, null, 2); - } + result = await this.agentdb.searchTheorems(args); break; case 'agentdb_learn_patterns': - { - const { createDatabase, ReasoningBank } = require('agentdb'); - const dbPath = args.path || './lean-theorems.db'; - - const db = await createDatabase(dbPath); - const reasoningBank = new ReasoningBank(db); - - // Get all successful theorems - const theorems = await db.all('SELECT * FROM theorems WHERE success = 1'); - - if (theorems.length === 0) { - await db.close(); - result = JSON.stringify({ - learned: false, - message: 'No theorems to learn from. Store some theorems first.', - }, null, 2); - break; - } - - // Group by strategy - const strategies = {}; - for (const theorem of theorems) { - const strategy = theorem.strategy || 'unknown'; - if (!strategies[strategy]) { - strategies[strategy] = { count: 0, types: new Set() }; - } - strategies[strategy].count++; - strategies[strategy].types.add(theorem.type); - } - - const patterns = Object.entries(strategies).map(([strategy, data]) => ({ - strategy: strategy, - count: data.count, - theorem_types: Array.from(data.types), - success_rate: '100.0%', - })); - - await db.close(); - - result = JSON.stringify({ - learned: true, - total_theorems: theorems.length, - patterns_found: patterns.length, - patterns: patterns, - }, null, 2); - } + result = await this.agentdb.learnPatterns(args); break; case 'agentdb_get_stats': - { - const { createDatabase } = require('agentdb'); - const fs = require('fs'); - const dbPath = args.path || './lean-theorems.db'; - - if (!fs.existsSync(dbPath)) { - result = JSON.stringify({ - initialized: false, - message: 'Database not initialized yet. Run agentdb_init first.', - }, null, 2); - break; - } - - const db = await createDatabase(dbPath); - - const total = await db.get('SELECT COUNT(*) as count FROM theorems'); - const byType = await db.all('SELECT type, COUNT(*) as count FROM theorems GROUP BY type'); - const fileStats = fs.statSync(dbPath); - - await db.close(); - - result = JSON.stringify({ - total_theorems: total.count, - database_size: (fileStats.size / 1024).toFixed(2) + ' KB', - theorems_by_type: byType, - }, null, 2); - } + result = await this.agentdb.getStats(args); break; default: @@ -620,31 +436,7 @@ class LeanAgenticMCPServer { break; case 'stats://agentdb': - { - const { createDatabase } = require('agentdb'); - const fs = require('fs'); - const dbPath = './lean-theorems.db'; - - if (!fs.existsSync(dbPath)) { - content = JSON.stringify({ - initialized: false, - message: 'Database not initialized. Use agentdb_init tool.', - }, null, 2); - break; - } - - const db = await createDatabase(dbPath); - const total = await db.get('SELECT COUNT(*) as count FROM theorems'); - const byType = await db.all('SELECT type, COUNT(*) as count FROM theorems GROUP BY type'); - await db.close(); - - content = JSON.stringify({ - total_theorems: total.count, - theorems_by_type: byType, - vector_search_enabled: true, - learning_enabled: true, - }, null, 2); - } + content = await this.agentdb.statsResource(); break; default: diff --git a/npm/lean-agentic/package-lock.json b/npm/lean-agentic/package-lock.json new file mode 100644 index 0000000..331d04a --- /dev/null +++ b/npm/lean-agentic/package-lock.json @@ -0,0 +1,7297 @@ +{ + "name": "lean-agentic", + "version": "0.3.3", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "lean-agentic", + "version": "0.3.3", + "license": "Apache-2.0", + "dependencies": { + "commander": "^12.0.0" + }, + "bin": { + "lean-agentic": 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Formal verification with cryptographic attestation and AI-powered proof recommendations.", "main": "dist/index.js", "module": "dist/index.mjs", @@ -41,9 +41,10 @@ "build:wasm": "cd ../../leanr-wasm && wasm-pack build --target bundler --out-dir ../npm/lean-agentic/wasm", "build:js": "node scripts/build.js", "prepublishOnly": "npm run build", - "test": "node --test", + "test": "node --test tests/agentdb/*.test.js tests/theorems/basic-theorems.test.js tests/theorems/dependent-types.test.js", "example:node": "node examples/node-example.js", - "example:web": "npx serve examples" + "example:web": "npx serve examples", + "test:perf": "node tests/theorems/performance-theorems.test.js" }, "keywords": [ "lean", @@ -115,8 +116,10 @@ "url": "https://github.com/agenticsorg/lean-agentic/issues" }, "dependencies": { - "commander": "^12.0.0", - "agentdb": "^1.5.5" + "commander": "^12.0.0" + }, + "optionalDependencies": { + "agentdb": "^3.6.0" }, "devDependencies": { "esbuild": "^0.20.0" diff --git a/npm/lean-agentic/tests/agentdb/agentdb-tools.test.js b/npm/lean-agentic/tests/agentdb/agentdb-tools.test.js new file mode 100644 index 0000000..8f5ccf1 --- /dev/null +++ b/npm/lean-agentic/tests/agentdb/agentdb-tools.test.js @@ -0,0 +1,137 @@ +'use strict'; + +// Real-import tests: every code path that touches agentdb runs against the +// installed agentdb package (no mocks of its API). Embeddings use AgentDB's +// deterministic offline provider so the suite never downloads a model. + +const test = require('node:test'); +const assert = require('node:assert/strict'); +const fs = require('fs'); +const os = require('os'); +const path = require('path'); + +const { AgentDBTools } = require('../../mcp/agentdb-tools.js'); +const { LeanAgenticMCPServer } = require('../../mcp/server.js'); + +const tmp = fs.mkdtempSync(path.join(os.tmpdir(), 'lean-agentic-agentdb-')); +test.after(() => fs.rmSync(tmp, { recursive: true, force: true })); + +const dbFile = (name) => path.join(tmp, name); +const parse = (text) => JSON.parse(text); + +test('agentdb resolves to a 3.x release via a real dynamic import', async () => { + const pkg = JSON.parse(fs.readFileSync(require.resolve('agentdb/package.json'), 'utf8')); + assert.match(pkg.version, /^3\./); + const tools = new AgentDBTools({ embeddingProvider: 'local' }); + const mod = await tools.load(); + for (const name of ['createDatabase', 'EmbeddingService', 'WASMVectorSearch']) { + assert.equal(typeof mod[name], 'function', `agentdb exports ${name}`); + } +}); + +test('init, store, search, learn and stats round-trip through agentdb', async () => { + const tools = new AgentDBTools({ embeddingProvider: 'local' }); + const db = dbFile('roundtrip.db'); + + const init = parse(await tools.init({ path: db })); + assert.equal(init.success, true); + assert.ok(fs.existsSync(db), 'database file is persisted on close'); + + const empty = parse(await tools.learnPatterns({ path: db })); + assert.equal(empty.learned, false); + + const first = parse(await tools.storeTheorem({ path: db, statement: 'forall A, A -> A', proof: 'fun x => x' })); + assert.equal(first.success, true); + assert.equal(first.theorem_id, 1); + assert.equal(first.embedding_dimension, 384); + const second = parse(await tools.storeTheorem({ + path: db, type: 'composition', statement: 'forall A B C, (B -> C) -> (A -> B) -> A -> C', proof: 'fun g f x => g (f x)', + })); + assert.equal(second.theorem_id, 2); + + const hit = parse(await tools.searchTheorems({ path: db, query: 'forall A, A -> A', limit: 5 })); + assert.ok(hit.results_found >= 1); + assert.equal(hit.theorems[0].statement, 'forall A, A -> A'); + assert.equal(hit.theorems[0].similarity, '100.0%'); + + const capped = parse(await tools.searchTheorems({ path: db, query: 'anything', limit: 1, threshold: -1 })); + assert.equal(capped.results_found, 1); + + const learned = parse(await tools.learnPatterns({ path: db })); + assert.equal(learned.learned, true); + assert.equal(learned.total_theorems, 2); + assert.deepEqual(learned.patterns[0].theorem_types.sort(), ['composition', 'identity']); + + const stats = parse(await tools.getStats({ path: db })); + assert.equal(stats.total_theorems, 2); + assert.equal(stats.theorems_by_type.length, 2); + + const resource = parse(await tools.statsResource(db)); + assert.equal(resource.total_theorems, 2); + assert.equal(resource.vector_search_enabled, true); +}); + +test('stats report an uninitialized database without touching agentdb', async () => { + const tools = new AgentDBTools({ loader: () => { throw new Error('must not load'); } }); + const missing = dbFile('missing.db'); + assert.equal(parse(await tools.getStats({ path: missing })).initialized, false); + assert.equal(parse(await tools.statsResource(missing)).initialized, false); + assert.ok(!fs.existsSync(missing)); +}); + +test('store and search validate their required arguments', async () => { + const tools = new AgentDBTools({ embeddingProvider: 'local' }); + assert.throws(() => tools.storeTheorem({ path: dbFile('v.db'), proof: 'p' }), /statement/); + assert.throws(() => tools.searchTheorems({ path: dbFile('v.db') }), /query/); +}); + +test('falls back to a structured result when agentdb cannot be loaded', async () => { + const tools = new AgentDBTools({ + loader: () => Promise.reject(Object.assign(new Error("Cannot find package 'agentdb'"), { code: 'ERR_MODULE_NOT_FOUND' })), + }); + assert.equal(await tools.isAvailable(), false); + const db = dbFile('fallback.db'); + for (const result of [ + await tools.init({ path: db }), + await tools.storeTheorem({ path: db, statement: 's', proof: 'p' }), + await tools.searchTheorems({ path: db, query: 'q' }), + await tools.learnPatterns({ path: db }), + ]) { + const body = parse(result); + assert.equal(body.available, false); + assert.match(body.message, /npm install agentdb/); + } + assert.ok(!fs.existsSync(db)); +}); + +test('MCP server routes every agentdb tool and resource through agentdb', async () => { + const server = new LeanAgenticMCPServer(); + server.agentdb = new AgentDBTools({ embeddingProvider: 'local' }); + const responses = new Map(); + server.sendResponse = (id, result) => responses.set(id, { result }); + server.sendError = (id, code, message) => responses.set(id, { error: { code, message } }); + const db = dbFile('server.db'); + + const call = async (id, name, args) => { + await server.handleToolsCall(id, { name, arguments: args }); + const response = responses.get(id); + assert.ok(response.result, `${name} failed: ${JSON.stringify(response.error)}`); + return parse(response.result.content[0].text); + }; + + assert.equal((await call(1, 'agentdb_init', { path: db })).success, true); + assert.equal((await call(2, 'agentdb_store_theorem', { path: db, statement: 'A -> A', proof: 'id' })).theorem_id, 1); + assert.equal((await call(3, 'agentdb_search_theorems', { path: db, query: 'A -> A' })).results_found, 1); + assert.equal((await call(4, 'agentdb_learn_patterns', { path: db })).learned, true); + assert.equal((await call(5, 'agentdb_get_stats', { path: db })).total_theorems, 1); + + const cwd = process.cwd(); + process.chdir(tmp); + try { + fs.copyFileSync(db, path.join(tmp, 'lean-theorems.db')); + await server.handleResourcesRead(6, { uri: 'stats://agentdb' }); + } finally { + process.chdir(cwd); + } + assert.equal(parse(responses.get(6).result.contents[0].text).total_theorems, 1); +});