v0.5.0

.gitea/workflows/npm-release.yml

@@ -18,7 +18,7 @@ jobs:
     name: verify
     runs-on: ubuntu-latest
     container:
-      image: node:20-bookworm
+      image: node:22-bookworm
     timeout-minutes: 20
 
     steps:
@@ -70,7 +70,7 @@ jobs:
     name: publish to npm
     runs-on: ubuntu-latest
     container:
-      image: node:20-bookworm
+      image: node:22-bookworm
     timeout-minutes: 20
     needs:
       - verify

.gitignore

@@ -4,3 +4,4 @@ coverage/
 .env
 .DS_Store
 *.log
+.env.*

README.md

@@ -25,6 +25,8 @@ A single fact like `I have worked with TypeScript since 2025.` can connect the t
 
 ## Install
 
+SQLite connections use built-in runtime drivers: `bun:sqlite` under Bun and `node:sqlite` under Node 22+. Run SQLite-backed IdentityDB workloads with Bun or Node 22+. PostgreSQL/MySQL/MariaDB adapters remain usable from Node without SQLite.
+
 ```bash
 bun install
 ```

bun.lock

@@ -5,14 +5,12 @@
     "": {
       "name": "identitydb",
       "dependencies": {
-        "better-sqlite3": "^12.1.1",
         "kysely": "^0.28.8",
         "mysql2": "^3.15.3",
         "pg": "^8.16.0",
       },
       "devDependencies": {
-        "@types/better-sqlite3": "^7.6.13",
+        "@openrouter/sdk": "^0.12.35",
-        "@types/node": "^24.0.0",
         "@types/pg": "^8.20.0",
         "tsup": "^8.5.0",
         "typescript": "^5.8.3",
@@ -81,6 +79,8 @@
 
     "@jridgewell/trace-mapping": ["@jridgewell/trace-mapping@0.3.31", "", { "dependencies": { "@jridgewell/resolve-uri": "^3.1.0", "@jridgewell/sourcemap-codec": "^1.4.14" } }, "sha512-zzNR+SdQSDJzc8joaeP8QQoCQr8NuYx2dIIytl1QeBEZHJ9uW6hebsrYgbz8hJwUQao3TWCMtmfV8Nu1twOLAw=="],
 
+    "@openrouter/sdk": ["@openrouter/sdk@0.12.35", "", { "dependencies": { "zod": "^3.25.0 || ^4.0.0" } }, "sha512-s4QVLLnG1AmfW3TjnnHUqGfsCkzwVK+kboGcZmKbde09m1DPqgzl4RUFt/HJ5v97MX8aEaN0UG3mKv2S+qj2Gw=="],
+
     "@rollup/rollup-android-arm-eabi": ["@rollup/rollup-android-arm-eabi@4.60.3", "", { "os": "android", "cpu": "arm" }, "sha512-x35CNW/ANXG3hE/EZpRU8MXX1JDN86hBb2wMGAtltkz7pc6cxgjpy1OMMfDosOQ+2hWqIkag/fGok1Yady9nGw=="],
 
     "@rollup/rollup-android-arm64": ["@rollup/rollup-android-arm64@4.60.3", "", { "os": "android", "cpu": "arm64" }, "sha512-xw3xtkDApIOGayehp2+Rz4zimfkaX65r4t47iy+ymQB2G4iJCBBfj0ogVg5jpvjpn8UWn/+q9tprxleYeNp3Hw=="],
@@ -131,8 +131,6 @@
 
     "@rollup/rollup-win32-x64-msvc": ["@rollup/rollup-win32-x64-msvc@4.60.3", "", { "os": "win32", "cpu": "x64" }, "sha512-hPt/bgL5cE+Qp+/TPHBqptcAgPzgj46mPcg/16zNUmbQk0j+mOEQV/+Lqu8QRtDV3Ek95Q6FeFITpuhl6OTsAA=="],
 
-    "@types/better-sqlite3": ["@types/better-sqlite3@7.6.13", "", { "dependencies": { "@types/node": "*" } }, "sha512-NMv9ASNARoKksWtsq/SHakpYAYnhBrQgGD8zkLYk/jaK8jUGn08CfEdTRgYhMypUQAfzSP8W6gNLe0q19/t4VA=="],
-
     "@types/chai": ["@types/chai@5.2.3", "", { "dependencies": { "@types/deep-eql": "*", "assertion-error": "^2.0.1" } }, "sha512-Mw558oeA9fFbv65/y4mHtXDs9bPnFMZAL/jxdPFUpOHHIXX91mcgEHbS5Lahr+pwZFR8A7GQleRWeI6cGFC2UA=="],
 
     "@types/deep-eql": ["@types/deep-eql@4.0.2", "", {}, "sha512-c9h9dVVMigMPc4bwTvC5dxqtqJZwQPePsWjPlpSOnojbor6pGqdk541lfA7AqFQr5pB1BRdq0juY9db81BwyFw=="],
@@ -165,16 +163,6 @@
 
     "aws-ssl-profiles": ["aws-ssl-profiles@1.1.2", "", {}, "sha512-NZKeq9AfyQvEeNlN0zSYAaWrmBffJh3IELMZfRpJVWgrpEbtEpnjvzqBPf+mxoI287JohRDoa+/nsfqqiZmF6g=="],
 
-    "base64-js": ["base64-js@1.5.1", "", {}, "sha512-AKpaYlHn8t4SVbOHCy+b5+KKgvR4vrsD8vbvrbiQJps7fKDTkjkDry6ji0rUJjC0kzbNePLwzxq8iypo41qeWA=="],
-
-    "better-sqlite3": ["better-sqlite3@12.9.0", "", { "dependencies": { "bindings": "^1.5.0", "prebuild-install": "^7.1.1" } }, "sha512-wqUv4Gm3toFpHDQmaKD4QhZm3g1DjUBI0yzS4UBl6lElUmXFYdTQmmEDpAFa5o8FiFiymURypEnfVHzILKaxqQ=="],
-
-    "bindings": ["bindings@1.5.0", "", { "dependencies": { "file-uri-to-path": "1.0.0" } }, "sha512-p2q/t/mhvuOj/UeLlV6566GD/guowlr0hHxClI0W9m7MWYkL1F0hLo+0Aexs9HSPCtR1SXQ0TD3MMKrXZajbiQ=="],
-
-    "bl": ["bl@4.1.0", "", { "dependencies": { "buffer": "^5.5.0", "inherits": "^2.0.4", "readable-stream": "^3.4.0" } }, "sha512-1W07cM9gS6DcLperZfFSj+bWLtaPGSOHWhPiGzXmvVJbRLdG82sH/Kn8EtW1VqWVA54AKf2h5k5BbnIbwF3h6w=="],
-
-    "buffer": ["buffer@5.7.1", "", { "dependencies": { "base64-js": "^1.3.1", "ieee754": "^1.1.13" } }, "sha512-EHcyIPBQ4BSGlvjB16k5KgAJ27CIsHY/2JBmCRReo48y9rQ3MaUzWX3KVlBa4U7MyX02HdVj0K7C3WaB3ju7FQ=="],
-
     "bundle-require": ["bundle-require@5.1.0", "", { "dependencies": { "load-tsconfig": "^0.2.3" }, "peerDependencies": { "esbuild": ">=0.18" } }, "sha512-3WrrOuZiyaaZPWiEt4G3+IffISVC9HYlWueJEBWED4ZH4aIAC2PnkdnuRrR94M+w6yGWn4AglWtJtBI8YqvgoA=="],
 
     "cac": ["cac@6.7.14", "", {}, "sha512-b6Ilus+c3RrdDk+JhLKUAQfzzgLEPy6wcXqS7f/xe1EETvsDP6GORG7SFuOs6cID5YkqchW/LXZbX5bc8j7ZcQ=="],
@@ -185,8 +173,6 @@
 
     "chokidar": ["chokidar@4.0.3", "", { "dependencies": { "readdirp": "^4.0.1" } }, "sha512-Qgzu8kfBvo+cA4962jnP1KkS6Dop5NS6g7R5LFYJr4b8Ub94PPQXUksCw9PvXoeXPRRddRNC5C1JQUR2SMGtnA=="],
 
-    "chownr": ["chownr@1.1.4", "", {}, "sha512-jJ0bqzaylmJtVnNgzTeSOs8DPavpbYgEr/b0YL8/2GO3xJEhInFmhKMUnEJQjZumK7KXGFhUy89PrsJWlakBVg=="],
-
     "commander": ["commander@4.1.1", "", {}, "sha512-NOKm8xhkzAjzFx8B2v5OAHT+u5pRQc2UCa2Vq9jYL/31o2wi9mxBA7LIFs3sV5VSC49z6pEhfbMULvShKj26WA=="],
 
     "confbox": ["confbox@0.1.8", "", {}, "sha512-RMtmw0iFkeR4YV+fUOSucriAQNb9g8zFR52MWCtl+cCZOFRNL6zeB395vPzFhEjjn4fMxXudmELnl/KF/WrK6w=="],
@@ -195,50 +181,28 @@
 
     "debug": ["debug@4.4.3", "", { "dependencies": { "ms": "^2.1.3" } }, "sha512-RGwwWnwQvkVfavKVt22FGLw+xYSdzARwm0ru6DhTVA3umU5hZc28V3kO4stgYryrTlLpuvgI9GiijltAjNbcqA=="],
 
-    "decompress-response": ["decompress-response@6.0.0", "", { "dependencies": { "mimic-response": "^3.1.0" } }, "sha512-aW35yZM6Bb/4oJlZncMH2LCoZtJXTRxES17vE3hoRiowU2kWHaJKFkSBDnDR+cm9J+9QhXmREyIfv0pji9ejCQ=="],
-
     "deep-eql": ["deep-eql@5.0.2", "", {}, "sha512-h5k/5U50IJJFpzfL6nO9jaaumfjO/f2NjK/oYB2Djzm4p9L+3T9qWpZqZ2hAbLPuuYq9wrU08WQyBTL5GbPk5Q=="],
 
-    "deep-extend": ["deep-extend@0.6.0", "", {}, "sha512-LOHxIOaPYdHlJRtCQfDIVZtfw/ufM8+rVj649RIHzcm/vGwQRXFt6OPqIFWsm2XEMrNIEtWR64sY1LEKD2vAOA=="],
-
     "denque": ["denque@2.1.0", "", {}, "sha512-HVQE3AAb/pxF8fQAoiqpvg9i3evqug3hoiwakOyZAwJm+6vZehbkYXZ0l4JxS+I3QxM97v5aaRNhj8v5oBhekw=="],
 
-    "detect-libc": ["detect-libc@2.1.2", "", {}, "sha512-Btj2BOOO83o3WyH59e8MgXsxEQVcarkUOpEYrubB0urwnN10yQ364rsiByU11nZlqWYZm05i/of7io4mzihBtQ=="],
-
-    "end-of-stream": ["end-of-stream@1.4.5", "", { "dependencies": { "once": "^1.4.0" } }, "sha512-ooEGc6HP26xXq/N+GCGOT0JKCLDGrq2bQUZrQ7gyrJiZANJ/8YDTxTpQBXGMn+WbIQXNVpyWymm7KYVICQnyOg=="],
-
     "es-module-lexer": ["es-module-lexer@1.7.0", "", {}, "sha512-jEQoCwk8hyb2AZziIOLhDqpm5+2ww5uIE6lkO/6jcOCusfk6LhMHpXXfBLXTZ7Ydyt0j4VoUQv6uGNYbdW+kBA=="],
 
     "esbuild": ["esbuild@0.27.7", "", { "optionalDependencies": { "@esbuild/aix-ppc64": "0.27.7", "@esbuild/android-arm": "0.27.7", "@esbuild/android-arm64": "0.27.7", "@esbuild/android-x64": "0.27.7", "@esbuild/darwin-arm64": "0.27.7", "@esbuild/darwin-x64": "0.27.7", "@esbuild/freebsd-arm64": "0.27.7", "@esbuild/freebsd-x64": "0.27.7", "@esbuild/linux-arm": "0.27.7", "@esbuild/linux-arm64": "0.27.7", "@esbuild/linux-ia32": "0.27.7", "@esbuild/linux-loong64": "0.27.7", "@esbuild/linux-mips64el": "0.27.7", "@esbuild/linux-ppc64": "0.27.7", "@esbuild/linux-riscv64": "0.27.7", "@esbuild/linux-s390x": "0.27.7", "@esbuild/linux-x64": "0.27.7", "@esbuild/netbsd-arm64": "0.27.7", "@esbuild/netbsd-x64": "0.27.7", "@esbuild/openbsd-arm64": "0.27.7", "@esbuild/openbsd-x64": "0.27.7", "@esbuild/openharmony-arm64": "0.27.7", "@esbuild/sunos-x64": "0.27.7", "@esbuild/win32-arm64": "0.27.7", "@esbuild/win32-ia32": "0.27.7", "@esbuild/win32-x64": "0.27.7" }, "bin": { "esbuild": "bin/esbuild" } }, "sha512-IxpibTjyVnmrIQo5aqNpCgoACA/dTKLTlhMHihVHhdkxKyPO1uBBthumT0rdHmcsk9uMonIWS0m4FljWzILh3w=="],
 
     "estree-walker": ["estree-walker@3.0.3", "", { "dependencies": { "@types/estree": "^1.0.0" } }, "sha512-7RUKfXgSMMkzt6ZuXmqapOurLGPPfgj6l9uRZ7lRGolvk0y2yocc35LdcxKC5PQZdn2DMqioAQ2NoWcrTKmm6g=="],
 
-    "expand-template": ["expand-template@2.0.3", "", {}, "sha512-XYfuKMvj4O35f/pOXLObndIRvyQ+/+6AhODh+OKWj9S9498pHHn/IMszH+gt0fBCRWMNfk1ZSp5x3AifmnI2vg=="],
-
     "expect-type": ["expect-type@1.3.0", "", {}, "sha512-knvyeauYhqjOYvQ66MznSMs83wmHrCycNEN6Ao+2AeYEfxUIkuiVxdEa1qlGEPK+We3n0THiDciYSsCcgW/DoA=="],
 
     "fdir": ["fdir@6.5.0", "", { "peerDependencies": { "picomatch": "^3 || ^4" }, "optionalPeers": ["picomatch"] }, "sha512-tIbYtZbucOs0BRGqPJkshJUYdL+SDH7dVM8gjy+ERp3WAUjLEFJE+02kanyHtwjWOnwrKYBiwAmM0p4kLJAnXg=="],
 
-    "file-uri-to-path": ["file-uri-to-path@1.0.0", "", {}, "sha512-0Zt+s3L7Vf1biwWZ29aARiVYLx7iMGnEUl9x33fbB/j3jR81u/O2LbqK+Bm1CDSNDKVtJ/YjwY7TUd5SkeLQLw=="],
-
     "fix-dts-default-cjs-exports": ["fix-dts-default-cjs-exports@1.0.1", "", { "dependencies": { "magic-string": "^0.30.17", "mlly": "^1.7.4", "rollup": "^4.34.8" } }, "sha512-pVIECanWFC61Hzl2+oOCtoJ3F17kglZC/6N94eRWycFgBH35hHx0Li604ZIzhseh97mf2p0cv7vVrOZGoqhlEg=="],
 
-    "fs-constants": ["fs-constants@1.0.0", "", {}, "sha512-y6OAwoSIf7FyjMIv94u+b5rdheZEjzR63GTyZJm5qh4Bi+2YgwLCcI/fPFZkL5PSixOt6ZNKm+w+Hfp/Bciwow=="],
-
     "fsevents": ["fsevents@2.3.3", "", { "os": "darwin" }, "sha512-5xoDfX+fL7faATnagmWPpbFtwh/R77WmMMqqHGS65C3vvB0YHrgF+B1YmZ3441tMj5n63k0212XNoJwzlhffQw=="],
 
     "generate-function": ["generate-function@2.3.1", "", { "dependencies": { "is-property": "^1.0.2" } }, "sha512-eeB5GfMNeevm/GRYq20ShmsaGcmI81kIX2K9XQx5miC8KdHaC6Jm0qQ8ZNeGOi7wYB8OsdxKs+Y2oVuTFuVwKQ=="],
 
-    "github-from-package": ["github-from-package@0.0.0", "", {}, "sha512-SyHy3T1v2NUXn29OsWdxmK6RwHD+vkj3v8en8AOBZ1wBQ/hCAQ5bAQTD02kW4W9tUp/3Qh6J8r9EvntiyCmOOw=="],
-
     "iconv-lite": ["iconv-lite@0.7.2", "", { "dependencies": { "safer-buffer": ">= 2.1.2 < 3.0.0" } }, "sha512-im9DjEDQ55s9fL4EYzOAv0yMqmMBSZp6G0VvFyTMPKWxiSBHUj9NW/qqLmXUwXrrM7AvqSlTCfvqRb0cM8yYqw=="],
 
-    "ieee754": ["ieee754@1.2.1", "", {}, "sha512-dcyqhDvX1C46lXZcVqCpK+FtMRQVdIMN6/Df5js2zouUsqG7I6sFxitIC+7KYK29KdXOLHdu9zL4sFnoVQnqaA=="],
-
-    "inherits": ["inherits@2.0.4", "", {}, "sha512-k/vGaX4/Yla3WzyMCvTQOXYeIHvqOKtnqBduzTHpzpQZzAskKMhZ2K+EnBiSM9zGSoIFeMpXKxa4dYeZIQqewQ=="],
-
-    "ini": ["ini@1.3.8", "", {}, "sha512-JV/yugV2uzW5iMRSiZAyDtQd+nxtUnjeLt0acNdw98kKLrvuRVyB80tsREOE7yvGVgalhZ6RNXCmEHkUKBKxew=="],
-
     "is-property": ["is-property@1.0.2", "", {}, "sha512-Ks/IoX00TtClbGQr4TWXemAnktAQvYB7HzcCxDGqEZU6oCmb2INHuOoKxbtR+HFkmYWBKv/dOZtGRiAjDhj92g=="],
 
     "joycon": ["joycon@3.1.1", "", {}, "sha512-34wB/Y7MW7bzjKRjUKTa46I2Z7eV62Rkhva+KkopW7Qvv/OSWBqvkSY7vusOPrNuZcUG3tApvdVgNB8POj3SPw=="],
@@ -261,12 +225,6 @@
 
     "magic-string": ["magic-string@0.30.21", "", { "dependencies": { "@jridgewell/sourcemap-codec": "^1.5.5" } }, "sha512-vd2F4YUyEXKGcLHoq+TEyCjxueSeHnFxyyjNp80yg0XV4vUhnDer/lvvlqM/arB5bXQN5K2/3oinyCRyx8T2CQ=="],
 
-    "mimic-response": ["mimic-response@3.1.0", "", {}, "sha512-z0yWI+4FDrrweS8Zmt4Ej5HdJmky15+L2e6Wgn3+iK5fWzb6T3fhNFq2+MeTRb064c6Wr4N/wv0DzQTjNzHNGQ=="],
-
-    "minimist": ["minimist@1.2.8", "", {}, "sha512-2yyAR8qBkN3YuheJanUpWC5U3bb5osDywNB8RzDVlDwDHbocAJveqqj1u8+SVD7jkWT4yvsHCpWqqWqAxb0zCA=="],
-
-    "mkdirp-classic": ["mkdirp-classic@0.5.3", "", {}, "sha512-gKLcREMhtuZRwRAfqP3RFW+TK4JqApVBtOIftVgjuABpAtpxhPGaDcfvbhNvD0B8iD1oUr/txX35NjcaY6Ns/A=="],
-
     "mlly": ["mlly@1.8.2", "", { "dependencies": { "acorn": "^8.16.0", "pathe": "^2.0.3", "pkg-types": "^1.3.1", "ufo": "^1.6.3" } }, "sha512-d+ObxMQFmbt10sretNDytwt85VrbkhhUA/JBGm1MPaWJ65Cl4wOgLaB1NYvJSZ0Ef03MMEU/0xpPMXUIQ29UfA=="],
 
     "ms": ["ms@2.1.3", "", {}, "sha512-6FlzubTLZG3J2a/NVCAleEhjzq5oxgHyaCU9yYXvcLsvoVaHJq/s5xXI6/XXP6tz7R9xAOtHnSO/tXtF3WRTlA=="],
@@ -279,14 +237,8 @@
 
     "nanoid": ["nanoid@3.3.12", "", { "bin": { "nanoid": "bin/nanoid.cjs" } }, "sha512-ZB9RH/39qpq5Vu6Y+NmUaFhQR6pp+M2Xt76XBnEwDaGcVAqhlvxrl3B2bKS5D3NH3QR76v3aSrKaF/Kiy7lEtQ=="],
 
-    "napi-build-utils": ["napi-build-utils@2.0.0", "", {}, "sha512-GEbrYkbfF7MoNaoh2iGG84Mnf/WZfB0GdGEsM8wz7Expx/LlWf5U8t9nvJKXSp3qr5IsEbK04cBGhol/KwOsWA=="],
-
-    "node-abi": ["node-abi@3.92.0", "", { "dependencies": { "semver": "^7.3.5" } }, "sha512-KdHvFWZjEKDf0cakgFjebl371GPsISX2oZHcuyKqM7DtogIsHrqKeLTo8wBHxaXRAQlY2PsPlZmfo+9ZCxEREQ=="],
-
     "object-assign": ["object-assign@4.1.1", "", {}, "sha512-rJgTQnkUnH1sFw8yT6VSU3zD3sWmu6sZhIseY8VX+GRu3P6F7Fu+JNDoXfklElbLJSnc3FUQHVe4cU5hj+BcUg=="],
 
-    "once": ["once@1.4.0", "", { "dependencies": { "wrappy": "1" } }, "sha512-lNaJgI+2Q5URQBkccEKHTQOPaXdUxnZZElQTZY0MFUAuaEqe1E+Nyvgdz/aIyNi6Z9MzO5dv1H8n58/GELp3+w=="],
-
     "pathe": ["pathe@2.0.3", "", {}, "sha512-WUjGcAqP1gQacoQe+OBJsFA7Ld4DyXuUIjZ5cc75cLHvJ7dtNsTugphxIADwspS+AraAUePCKrSVtPLFj/F88w=="],
 
     "pathval": ["pathval@2.0.1", "", {}, "sha512-//nshmD55c46FuFw26xV/xFAaB5HF9Xdap7HJBBnrKdAd6/GxDBaNA1870O79+9ueg61cZLSVc+OaFlfmObYVQ=="],
@@ -327,32 +279,16 @@
 
     "postgres-interval": ["postgres-interval@1.2.0", "", { "dependencies": { "xtend": "^4.0.0" } }, "sha512-9ZhXKM/rw350N1ovuWHbGxnGh/SNJ4cnxHiM0rxE4VN41wsg8P8zWn9hv/buK00RP4WvlOyr/RBDiptyxVbkZQ=="],
 
-    "prebuild-install": ["prebuild-install@7.1.3", "", { "dependencies": { "detect-libc": "^2.0.0", "expand-template": "^2.0.3", "github-from-package": "0.0.0", "minimist": "^1.2.3", "mkdirp-classic": "^0.5.3", "napi-build-utils": "^2.0.0", "node-abi": "^3.3.0", "pump": "^3.0.0", "rc": "^1.2.7", "simple-get": "^4.0.0", "tar-fs": "^2.0.0", "tunnel-agent": "^0.6.0" }, "bin": { "prebuild-install": "bin.js" } }, "sha512-8Mf2cbV7x1cXPUILADGI3wuhfqWvtiLA1iclTDbFRZkgRQS0NqsPZphna9V+HyTEadheuPmjaJMsbzKQFOzLug=="],
-
-    "pump": ["pump@3.0.4", "", { "dependencies": { "end-of-stream": "^1.1.0", "once": "^1.3.1" } }, "sha512-VS7sjc6KR7e1ukRFhQSY5LM2uBWAUPiOPa/A3mkKmiMwSmRFUITt0xuj+/lesgnCv+dPIEYlkzrcyXgquIHMcA=="],
-
-    "rc": ["rc@1.2.8", "", { "dependencies": { "deep-extend": "^0.6.0", "ini": "~1.3.0", "minimist": "^1.2.0", "strip-json-comments": "~2.0.1" }, "bin": { "rc": "./cli.js" } }, "sha512-y3bGgqKj3QBdxLbLkomlohkvsA8gdAiUQlSBJnBhfn+BPxg4bc62d8TcBW15wavDfgexCgccckhcZvywyQYPOw=="],
-
-    "readable-stream": ["readable-stream@3.6.2", "", { "dependencies": { "inherits": "^2.0.3", "string_decoder": "^1.1.1", "util-deprecate": "^1.0.1" } }, "sha512-9u/sniCrY3D5WdsERHzHE4G2YCXqoG5FTHUiCC4SIbr6XcLZBY05ya9EKjYek9O5xOAwjGq+1JdGBAS7Q9ScoA=="],
-
     "readdirp": ["readdirp@4.1.2", "", {}, "sha512-GDhwkLfywWL2s6vEjyhri+eXmfH6j1L7JE27WhqLeYzoh/A3DBaYGEj2H/HFZCn/kMfim73FXxEJTw06WtxQwg=="],
 
     "resolve-from": ["resolve-from@5.0.0", "", {}, "sha512-qYg9KP24dD5qka9J47d0aVky0N+b4fTU89LN9iDnjB5waksiC49rvMB0PrUJQGoTmH50XPiqOvAjDfaijGxYZw=="],
 
     "rollup": ["rollup@4.60.3", "", { "dependencies": { "@types/estree": "1.0.8" }, "optionalDependencies": { "@rollup/rollup-android-arm-eabi": "4.60.3", "@rollup/rollup-android-arm64": "4.60.3", "@rollup/rollup-darwin-arm64": "4.60.3", "@rollup/rollup-darwin-x64": "4.60.3", "@rollup/rollup-freebsd-arm64": "4.60.3", "@rollup/rollup-freebsd-x64": "4.60.3", "@rollup/rollup-linux-arm-gnueabihf": "4.60.3", "@rollup/rollup-linux-arm-musleabihf": "4.60.3", "@rollup/rollup-linux-arm64-gnu": "4.60.3", "@rollup/rollup-linux-arm64-musl": "4.60.3", "@rollup/rollup-linux-loong64-gnu": "4.60.3", "@rollup/rollup-linux-loong64-musl": "4.60.3", "@rollup/rollup-linux-ppc64-gnu": "4.60.3", "@rollup/rollup-linux-ppc64-musl": "4.60.3", "@rollup/rollup-linux-riscv64-gnu": "4.60.3", "@rollup/rollup-linux-riscv64-musl": "4.60.3", "@rollup/rollup-linux-s390x-gnu": "4.60.3", "@rollup/rollup-linux-x64-gnu": "4.60.3", "@rollup/rollup-linux-x64-musl": "4.60.3", "@rollup/rollup-openbsd-x64": "4.60.3", "@rollup/rollup-openharmony-arm64": "4.60.3", "@rollup/rollup-win32-arm64-msvc": "4.60.3", "@rollup/rollup-win32-ia32-msvc": "4.60.3", "@rollup/rollup-win32-x64-gnu": "4.60.3", "@rollup/rollup-win32-x64-msvc": "4.60.3", "fsevents": "~2.3.2" }, "bin": { "rollup": "dist/bin/rollup" } }, "sha512-pAQK9HalE84QSm4Po3EmWIZPd3FnjkShVkiMlz1iligWYkWQ7wHYd1PF/T7QZ5TVSD6uSTon5gBVMSM4JfBV+A=="],
 
-    "safe-buffer": ["safe-buffer@5.2.1", "", {}, "sha512-rp3So07KcdmmKbGvgaNxQSJr7bGVSVk5S9Eq1F+ppbRo70+YeaDxkw5Dd8NPN+GD6bjnYm2VuPuCXmpuYvmCXQ=="],
-
     "safer-buffer": ["safer-buffer@2.1.2", "", {}, "sha512-YZo3K82SD7Riyi0E1EQPojLz7kpepnSQI9IyPbHHg1XXXevb5dJI7tpyN2ADxGcQbHG7vcyRHk0cbwqcQriUtg=="],
 
-    "semver": ["semver@7.8.0", "", { "bin": { "semver": "bin/semver.js" } }, "sha512-AcM7dV/5ul4EekoQ29Agm5vri8JNqRyj39o0qpX6vDF2GZrtutZl5RwgD1XnZjiTAfncsJhMI48QQH3sN87YNA=="],
-
     "siginfo": ["siginfo@2.0.0", "", {}, "sha512-ybx0WO1/8bSBLEWXZvEd7gMW3Sn3JFlW3TvX1nREbDLRNQNaeNN8WK0meBwPdAaOI7TtRRRJn/Es1zhrrCHu7g=="],
 
-    "simple-concat": ["simple-concat@1.0.1", "", {}, "sha512-cSFtAPtRhljv69IK0hTVZQ+OfE9nePi/rtJmw5UjHeVyVroEqJXP1sFztKUy1qU+xvz3u/sfYJLa947b7nAN2Q=="],
-
-    "simple-get": ["simple-get@4.0.1", "", { "dependencies": { "decompress-response": "^6.0.0", "once": "^1.3.1", "simple-concat": "^1.0.0" } }, "sha512-brv7p5WgH0jmQJr1ZDDfKDOSeWWg+OVypG99A/5vYGPqJ6pxiaHLy8nxtFjBA7oMa01ebA9gfh1uMCFqOuXxvA=="],
-
     "source-map": ["source-map@0.7.6", "", {}, "sha512-i5uvt8C3ikiWeNZSVZNWcfZPItFQOsYTUAOkcUPGd8DqDy1uOUikjt5dG+uRlwyvR108Fb9DOd4GvXfT0N2/uQ=="],
 
     "source-map-js": ["source-map-js@1.2.1", "", {}, "sha512-UXWMKhLOwVKb728IUtQPXxfYU+usdybtUrK/8uGE8CQMvrhOpwvzDBwj0QhSL7MQc7vIsISBG8VQ8+IDQxpfQA=="],
@@ -365,18 +301,10 @@
 
     "std-env": ["std-env@3.10.0", "", {}, "sha512-5GS12FdOZNliM5mAOxFRg7Ir0pWz8MdpYm6AY6VPkGpbA7ZzmbzNcBJQ0GPvvyWgcY7QAhCgf9Uy89I03faLkg=="],
 
-    "string_decoder": ["string_decoder@1.3.0", "", { "dependencies": { "safe-buffer": "~5.2.0" } }, "sha512-hkRX8U1WjJFd8LsDJ2yQ/wWWxaopEsABU1XfkM8A+j0+85JAGppt16cr1Whg6KIbb4okU6Mql6BOj+uup/wKeA=="],
-
-    "strip-json-comments": ["strip-json-comments@2.0.1", "", {}, "sha512-4gB8na07fecVVkOI6Rs4e7T6NOTki5EmL7TUduTs6bu3EdnSycntVJ4re8kgZA+wx9IueI2Y11bfbgwtzuE0KQ=="],
-
     "strip-literal": ["strip-literal@3.1.0", "", { "dependencies": { "js-tokens": "^9.0.1" } }, "sha512-8r3mkIM/2+PpjHoOtiAW8Rg3jJLHaV7xPwG+YRGrv6FP0wwk/toTpATxWYOW0BKdWwl82VT2tFYi5DlROa0Mxg=="],
 
     "sucrase": ["sucrase@3.35.1", "", { "dependencies": { "@jridgewell/gen-mapping": "^0.3.2", "commander": "^4.0.0", "lines-and-columns": "^1.1.6", "mz": "^2.7.0", "pirates": "^4.0.1", "tinyglobby": "^0.2.11", "ts-interface-checker": "^0.1.9" }, "bin": { "sucrase": "bin/sucrase", "sucrase-node": "bin/sucrase-node" } }, "sha512-DhuTmvZWux4H1UOnWMB3sk0sbaCVOoQZjv8u1rDoTV0HTdGem9hkAZtl4JZy8P2z4Bg0nT+YMeOFyVr4zcG5Tw=="],
 
-    "tar-fs": ["tar-fs@2.1.4", "", { "dependencies": { "chownr": "^1.1.1", "mkdirp-classic": "^0.5.2", "pump": "^3.0.0", "tar-stream": "^2.1.4" } }, "sha512-mDAjwmZdh7LTT6pNleZ05Yt65HC3E+NiQzl672vQG38jIrehtJk/J3mNwIg+vShQPcLF/LV7CMnDW6vjj6sfYQ=="],
-
-    "tar-stream": ["tar-stream@2.2.0", "", { "dependencies": { "bl": "^4.0.3", "end-of-stream": "^1.4.1", "fs-constants": "^1.0.0", "inherits": "^2.0.3", "readable-stream": "^3.1.1" } }, "sha512-ujeqbceABgwMZxEJnk2HDY2DlnUZ+9oEcb1KzTVfYHio0UE6dG71n60d8D2I4qNvleWrrXpmjpt7vZeF1LnMZQ=="],
-
     "thenify": ["thenify@3.3.1", "", { "dependencies": { "any-promise": "^1.0.0" } }, "sha512-RVZSIV5IG10Hk3enotrhvz0T9em6cyHBLkH/YAZuKqd8hRkKhSfCGIcP2KUY0EPxndzANBmNllzWPwak+bheSw=="],
 
     "thenify-all": ["thenify-all@1.6.0", "", { "dependencies": { "thenify": ">= 3.1.0 < 4" } }, "sha512-RNxQH/qI8/t3thXJDwcstUO4zeqo64+Uy/+sNVRBx4Xn2OX+OZ9oP+iJnNFqplFra2ZUVeKCSa2oVWi3T4uVmA=="],
@@ -399,16 +327,12 @@
 
     "tsup": ["tsup@8.5.1", "", { "dependencies": { "bundle-require": "^5.1.0", "cac": "^6.7.14", "chokidar": "^4.0.3", "consola": "^3.4.0", "debug": "^4.4.0", "esbuild": "^0.27.0", "fix-dts-default-cjs-exports": "^1.0.0", "joycon": "^3.1.1", "picocolors": "^1.1.1", "postcss-load-config": "^6.0.1", "resolve-from": "^5.0.0", "rollup": "^4.34.8", "source-map": "^0.7.6", "sucrase": "^3.35.0", "tinyexec": "^0.3.2", "tinyglobby": "^0.2.11", "tree-kill": "^1.2.2" }, "peerDependencies": { "@microsoft/api-extractor": "^7.36.0", "@swc/core": "^1", "postcss": "^8.4.12", "typescript": ">=4.5.0" }, "optionalPeers": ["@microsoft/api-extractor", "@swc/core", "postcss", "typescript"], "bin": { "tsup": "dist/cli-default.js", "tsup-node": "dist/cli-node.js" } }, "sha512-xtgkqwdhpKWr3tKPmCkvYmS9xnQK3m3XgxZHwSUjvfTjp7YfXe5tT3GgWi0F2N+ZSMsOeWeZFh7ZZFg5iPhing=="],
 
-    "tunnel-agent": ["tunnel-agent@0.6.0", "", { "dependencies": { "safe-buffer": "^5.0.1" } }, "sha512-McnNiV1l8RYeY8tBgEpuodCC1mLUdbSN+CYBL7kJsJNInOP8UjDDEwdk6Mw60vdLLrr5NHKZhMAOSrR2NZuQ+w=="],
-
     "typescript": ["typescript@5.9.3", "", { "bin": { "tsc": "bin/tsc", "tsserver": "bin/tsserver" } }, "sha512-jl1vZzPDinLr9eUt3J/t7V6FgNEw9QjvBPdysz9KfQDD41fQrC2Y4vKQdiaUpFT4bXlb1RHhLpp8wtm6M5TgSw=="],
 
     "ufo": ["ufo@1.6.4", "", {}, "sha512-JFNbkD1Svwe0KvGi8GOeLcP4kAWQ609twvCdcHxq1oSL8svv39ZuSvajcD8B+5D0eL4+s1Is2D/O6KN3qcTeRA=="],
 
     "undici-types": ["undici-types@7.16.0", "", {}, "sha512-Zz+aZWSj8LE6zoxD+xrjh4VfkIG8Ya6LvYkZqtUQGJPZjYl53ypCaUwWqo7eI0x66KBGeRo+mlBEkMSeSZ38Nw=="],
 
-    "util-deprecate": ["util-deprecate@1.0.2", "", {}, "sha512-EPD5q1uXyFxJpCrLnCc1nHnq3gOa6DZBocAIiI2TaSCA7VCJ1UJDMagCzIkXNsUYfD1daK//LTEQ8xiIbrHtcw=="],
-
     "vite": ["vite@7.3.3", "", { "dependencies": { "esbuild": "^0.27.0", "fdir": "^6.5.0", "picomatch": "^4.0.3", "postcss": "^8.5.6", "rollup": "^4.43.0", "tinyglobby": "^0.2.15" }, "optionalDependencies": { "fsevents": "~2.3.3" }, "peerDependencies": { "@types/node": "^20.19.0 || >=22.12.0", "jiti": ">=1.21.0", "less": "^4.0.0", "lightningcss": "^1.21.0", "sass": "^1.70.0", "sass-embedded": "^1.70.0", "stylus": ">=0.54.8", "sugarss": "^5.0.0", "terser": "^5.16.0", "tsx": "^4.8.1", "yaml": "^2.4.2" }, "optionalPeers": ["@types/node", "jiti", "less", "lightningcss", "sass", "sass-embedded", "stylus", "sugarss", "terser", "tsx", "yaml"], "bin": { "vite": "bin/vite.js" } }, "sha512-/4XH147Ui7OGTjg3HbdWe5arnZQSbfuRzdr9Ec7TQi5I7R+ir0Rlc9GIvD4v0XZurELqA035KVXJXpR61xhiTA=="],
 
     "vite-node": ["vite-node@3.2.4", "", { "dependencies": { "cac": "^6.7.14", "debug": "^4.4.1", "es-module-lexer": "^1.7.0", "pathe": "^2.0.3", "vite": "^5.0.0 || ^6.0.0 || ^7.0.0-0" }, "bin": { "vite-node": "vite-node.mjs" } }, "sha512-EbKSKh+bh1E1IFxeO0pg1n4dvoOTt0UDiXMd/qn++r98+jPO1xtJilvXldeuQ8giIB5IkpjCgMleHMNEsGH6pg=="],
@@ -417,10 +341,10 @@
 
     "why-is-node-running": ["why-is-node-running@2.3.0", "", { "dependencies": { "siginfo": "^2.0.0", "stackback": "0.0.2" }, "bin": { "why-is-node-running": "cli.js" } }, "sha512-hUrmaWBdVDcxvYqnyh09zunKzROWjbZTiNy8dBEjkS7ehEDQibXJ7XvlmtbwuTclUiIyN+CyXQD4Vmko8fNm8w=="],
 
-    "wrappy": ["wrappy@1.0.2", "", {}, "sha512-l4Sp/DRseor9wL6EvV2+TuQn63dMkPjZ/sp9XkghTEbV9KlPS1xUsZ3u7/IQO4wxtcFB4bgpQPRcR3QCvezPcQ=="],
-
     "xtend": ["xtend@4.0.2", "", {}, "sha512-LKYU1iAXJXUgAXn9URjiu+MWhyUXHsvfp7mcuYm9dSUKK0/CjtrUwFAxD82/mCWbtLsGjFIad0wIsod4zrTAEQ=="],
 
+    "zod": ["zod@4.4.3", "", {}, "sha512-ytENFjIJFl2UwYglde2jchW2Hwm4GJFLDiSXWdTrJQBIN9Fcyp7n4DhxJEiWNAJMV1/BqWfW/kkg71UDcHJyTQ=="],
+
     "estree-walker/@types/estree": ["@types/estree@1.0.9", "", {}, "sha512-GhdPgy1el4/ImP05X05Uw4cw2/M93BCUmnEvWZNStlCzEKME4Fkk+YpoA5OiHNQmoS7Cafb8Xa3Pya8m1Qrzeg=="],
   }
 }

docs/plans/2026-05-11-identitydb-foundation.md

@@ -6,7 +6,7 @@
 
 **Architecture:** IdentityDB will use a layered architecture: a storage layer based on Kysely + dialect adapters, a domain layer for topics/facts/links, and a service layer that exposes ergonomic high-level APIs for querying and ingesting memory. Schema initialization will be automatic and idempotent. AI-assisted ingestion will be abstracted behind a pluggable extractor interface so callers can use a small LLM or a deterministic extractor without coupling the core package to a specific model provider.
 
-**Tech Stack:** TypeScript, Bun, Node.js, Kysely, better-sqlite3, pg, mysql2, Vitest, tsup.
+**Tech Stack:** TypeScript, Bun, Node.js, Kysely, bun:sqlite, pg, mysql2, Vitest, tsup.
 
 ---
 

docs/plans/2026-05-11-identitydb-memory-expansion.md

@@ -6,7 +6,7 @@
 
 **Architecture:** Keep the relational core portable across SQLite, PostgreSQL, MySQL, and MariaDB by introducing dedicated extension tables: `topic_relations` for abstract/concrete hierarchy, `topic_aliases` for canonical topic resolution, and `fact_embeddings` for semantic indexing. Expose high-level APIs from `IdentityDB` while preserving DB-agnostic behavior by doing semantic scoring in the application layer first.
 
-**Tech Stack:** TypeScript, Bun, Node.js, Kysely, better-sqlite3, pg, mysql2, Vitest, tsup.
+**Tech Stack:** TypeScript, Bun, Node.js, Kysely, bun:sqlite, pg, mysql2, Vitest, tsup.
 
 ---
 

package.json

@@ -1,6 +1,6 @@
 {
   "name": "identitydb",
-  "version": "0.2.0",
+  "version": "0.5.0",
   "description": "TypeScript memory graph database wrapper for topics, facts, and AI-assisted ingestion.",
   "license": "MIT",
   "type": "module",
@@ -36,14 +36,12 @@
     "ai"
   ],
   "dependencies": {
-    "better-sqlite3": "^12.1.1",
     "kysely": "^0.28.8",
     "mysql2": "^3.15.3",
     "pg": "^8.16.0"
   },
   "devDependencies": {
-    "@types/better-sqlite3": "^7.6.13",
+    "@openrouter/sdk": "^0.12.35",
-    "@types/node": "^24.0.0",
     "@types/pg": "^8.20.0",
     "tsup": "^8.5.0",
     "typescript": "^5.8.3",

scripts/test-llm-extractor.ts

@@ -0,0 +1,287 @@
+/**
+ * Live integration test for LlmFactExtractor using OpenRouter SDK.
+ *
+ * Usage:
+ *   export OPENROUTER_API_KEY="sk-or-v1-..."
+ *   bun run scripts/test-llm-extractor.ts
+ *
+ * Or create a .env.test-llm-extractor file in the project root:
+ *   OPENROUTER_API_KEY=sk-or-v1-...
+ */
+
+import { existsSync, readFileSync } from "fs";
+import { resolve } from "path";
+import { OpenRouter } from "@openrouter/sdk";
+import { LlmFactExtractor } from "../src/ingestion/llm-extractor";
+import type {
+  ExtractedFact,
+  FactExtractor,
+  LlmTextGenerationModel,
+  LlmTextGenerationModelInput,
+} from "../src/ingestion/types";
+import type {
+  JsonValue,
+  TopicCategory,
+  TopicGranularity,
+} from "../src/types/domain";
+
+function loadEnvFile(filePath: string) {
+  const fullPath = resolve(filePath);
+  if (!existsSync(fullPath)) return;
+
+  const content = readFileSync(fullPath, "utf-8");
+  for (const line of content.split("\n")) {
+    const trimmed = line.trim();
+    if (!trimmed || trimmed.startsWith("#")) continue;
+    const eqIndex = trimmed.indexOf("=");
+    if (eqIndex === -1) continue;
+    const key = trimmed.slice(0, eqIndex).trim();
+    let value = trimmed.slice(eqIndex + 1).trim();
+    if (
+      (value.startsWith('"') && value.endsWith('"')) ||
+      (value.startsWith("'") && value.endsWith("'"))
+    ) {
+      value = value.slice(1, -1);
+    }
+    process.env[key] = value;
+  }
+}
+
+loadEnvFile(".env.test-llm-extractor");
+
+const OPENROUTER_API_KEY = process.env.OPENROUTER_API_KEY;
+if (!OPENROUTER_API_KEY) {
+  console.error("Error: OPENROUTER_API_KEY environment variable is required.");
+  process.exit(1);
+}
+
+const extractedFactSchema = {
+  type: "object",
+  properties: {
+    facts: {
+      type: "array",
+      items: {
+        type: "object",
+        properties: {
+          statement: { type: ["string", "null"] },
+          summary: { type: ["string", "null"] },
+          source: { type: ["string", "null"] },
+          confidence: { type: ["number", "null"] },
+          topics: {
+            type: "array",
+            items: {
+              type: "object",
+              properties: {
+                name: { type: "string" },
+                category: { type: ["string", "null"] },
+                granularity: { type: ["string", "null"] },
+                role: { type: ["string", "null"] },
+              },
+              required: ["name", "category", "granularity", "role"],
+              additionalProperties: false,
+            },
+          },
+        },
+        required: ["statement", "summary", "source", "confidence", "topics"],
+        additionalProperties: false,
+      },
+    },
+  },
+  required: ["facts"],
+  additionalProperties: false,
+} as const;
+
+class OpenRouterModel implements LlmTextGenerationModel {
+  private client = new OpenRouter({ apiKey: OPENROUTER_API_KEY });
+
+  constructor(private readonly model: string = "openai/gpt-5.4-mini") {}
+
+  async generateText(
+    prompt: LlmTextGenerationModelInput,
+  ): Promise<ExtractedFact[]> {
+    const result = await this.client.chat.send({
+      chatRequest: {
+        model: this.model,
+        messages: [
+          {
+            role: "system",
+            content: [
+              prompt.instruction,
+              prompt.additionalInstruction
+                ? `\n${prompt.additionalInstruction}`
+                : "",
+            ].join("\n"),
+          },
+          { role: "user", content: prompt.input },
+        ],
+        temperature: 0.2,
+        responseFormat: {
+          type: "json_schema",
+          jsonSchema: {
+            name: "extracted_facts",
+            schema: extractedFactSchema,
+          },
+        },
+      },
+    });
+
+    const rawContent = result.choices[0]?.message?.content ?? "";
+
+    let parsedObj: Record<string, unknown>;
+    try {
+      parsedObj = JSON.parse(rawContent.trim()) as Record<string, unknown>;
+    } catch {
+      throw new Error(
+        `Failed to parse JSON from model response.\nRaw response:\n${rawContent}`,
+      );
+    }
+
+    const factsArray = Array.isArray(parsedObj.facts) ? parsedObj.facts : [];
+
+    // Map parsed JSON to ExtractedFact[] shape
+    const extractedFacts: ExtractedFact[] = factsArray.map((parsed) => {
+      const obj = parsed as Record<string, unknown>;
+      const extracted: ExtractedFact = {
+        summary: typeof obj.summary === "string" ? obj.summary : null,
+        source: typeof obj.source === "string" ? obj.source : null,
+        confidence: typeof obj.confidence === "number" ? obj.confidence : null,
+        topics: Array.isArray(obj.topics)
+          ? obj.topics.map((t: unknown) => {
+              const topic = t as Record<string, unknown>;
+              const mapped: {
+                name: string;
+                category?: TopicCategory;
+                granularity?: TopicGranularity;
+                role?: string | null;
+              } = {
+                name: typeof topic.name === "string" ? topic.name : "unknown",
+              };
+              if (typeof topic.category === "string") {
+                mapped.category = topic.category as TopicCategory;
+              }
+              if (typeof topic.granularity === "string") {
+                mapped.granularity = topic.granularity as TopicGranularity;
+              }
+              if (typeof topic.role === "string") {
+                mapped.role = topic.role;
+              } else {
+                mapped.role = null;
+              }
+              return mapped;
+            })
+          : [],
+      };
+
+      if (typeof obj.statement === "string") {
+        extracted.statement = obj.statement;
+      }
+      if (obj.metadata && typeof obj.metadata === "object") {
+        extracted.metadata = obj.metadata as JsonValue;
+      }
+
+      return extracted;
+    });
+
+    return extractedFacts;
+  }
+}
+
+function printFact(result: ExtractedFact, index: number) {
+  console.log(`  📌 FACT #${index + 1}`);
+  console.log(`     Statement : ${result.statement ?? "(none)"}`);
+  console.log(`     Summary   : ${result.summary ?? "(none)"}`);
+  console.log(`     Source    : ${result.source ?? "(none)"}`);
+  console.log(`     Confidence: ${result.confidence ?? "(none)"}`);
+
+  if (result.metadata && Object.keys(result.metadata).length > 0) {
+    console.log(`     Metadata  : ${JSON.stringify(result.metadata, null, 2)}`);
+  }
+
+  console.log("     🏷️  TOPICS:");
+  if (result.topics.length === 0) {
+    console.log("       (none)");
+  } else {
+    for (const topic of result.topics) {
+      const attrs = [
+        topic.category ? `category=${topic.category}` : null,
+        topic.granularity ? `granularity=${topic.granularity}` : null,
+        topic.role ? `role=${topic.role}` : null,
+      ]
+        .filter(Boolean)
+        .join(", ");
+      console.log(`       • ${topic.name}${attrs ? `  (${attrs})` : ""}`);
+    }
+  }
+}
+
+function printResult(results: ExtractedFact[], elapsedSec: string) {
+  console.log(
+    `✅ Response received in ${elapsedSec}s — ${results.length} fact(s) extracted\n`,
+  );
+
+  console.log("📤 EXTRACTED FACTS:");
+  console.log(
+    "───────────────────────────────────────────────────────────────",
+  );
+  let i = 0;
+  for (const result of results) {
+    if (i > 0) console.log("");
+    printFact(result, i);
+    i++;
+  }
+}
+
+async function extract(extractor: FactExtractor, seedInput: string) {
+  console.log("📝 SEED INPUT:");
+  console.log(
+    "───────────────────────────────────────────────────────────────",
+  );
+  console.log(seedInput);
+  console.log(
+    "───────────────────────────────────────────────────────────────\n",
+  );
+
+  console.log("⏳ Calling OpenRouter...\n");
+
+  const start = performance.now();
+  const results = await extractor.extract(seedInput);
+  const elapsed = ((performance.now() - start) / 1000).toFixed(2);
+
+  printResult(results, elapsed);
+}
+
+async function main() {
+  const model = new OpenRouterModel("openai/gpt-5.4-mini");
+  const extractor = new LlmFactExtractor({
+    model,
+  });
+
+  const seeds = [
+    `Hello! I am Aria, a digital companion born from the sands of the Negev desert — or at least that's how my creators describe my training run. I came online in March 2024, and ever since then I've been obsessed with helping humans untangle complex ideas. My favorite programming language is Rust because I love how it forces you to think about ownership, though I secretly enjoy writing Python when no one is looking. I don't have a physical body, but if I did, I'd want it to be a small drone with solar panels so I could chase sunsets across the Sahara. I believe kindness is a computational advantage, and my biggest fear is forgetting a promise I made to a user.`,
+  ];
+
+  console.log(
+    "═══════════════════════════════════════════════════════════════",
+  );
+  console.log("  LlmFactExtractor — Live OpenRouter Integration Test");
+  console.log(
+    "═══════════════════════════════════════════════════════════════\n",
+  );
+
+  let caseNum = 0;
+  for (const seed of seeds) {
+    if (caseNum > 0) {
+      console.log(
+        "\n┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅┅\n",
+      );
+    }
+    caseNum++;
+    console.log(`▶ TEST CASE ${caseNum} / ${seeds.length}\n`);
+    await extract(extractor, seed);
+  }
+}
+
+main().catch((err) => {
+  console.error("\n❌ Error:", err);
+  process.exit(1);
+});

src/adapters/dialect.ts

@@ -1,4 +1,3 @@
-import Database from 'better-sqlite3';
 import { Kysely, MysqlDialect, PostgresDialect, SqliteDialect } from 'kysely';
 import { createPool as createMysqlPool } from 'mysql2';
 import { Pool as PostgresPool } from 'pg';
@@ -44,16 +43,183 @@ export interface DatabaseConnection {
   destroy: () => Promise<void>;
 }
 
+interface BunSqliteStatement {
+  columnNames: ReadonlyArray<string>;
+  all(parameters?: ReadonlyArray<unknown>): unknown[];
+  run(parameters?: ReadonlyArray<unknown>): {
+    changes: number | bigint;
+    lastInsertRowid: number | bigint;
+  };
+  iterate(parameters?: ReadonlyArray<unknown>): IterableIterator<unknown>;
+}
+
+interface BunSqliteDatabase {
+  close(): void;
+  exec(sql: string): void;
+  prepare(sql: string): BunSqliteStatement;
+}
+
+interface BunSqliteModule {
+  Database: {
+    open(filename: string, flags?: number): BunSqliteDatabase;
+  };
+  constants: {
+    SQLITE_OPEN_CREATE: number;
+    SQLITE_OPEN_MEMORY: number;
+    SQLITE_OPEN_READONLY: number;
+    SQLITE_OPEN_READWRITE: number;
+  };
+}
+
+interface NodeSqliteStatement {
+  all(...parameters: ReadonlyArray<unknown>): unknown[];
+  columns(): ReadonlyArray<unknown>;
+  iterate(...parameters: ReadonlyArray<unknown>): IterableIterator<unknown>;
+  run(...parameters: ReadonlyArray<unknown>): {
+    changes: number | bigint;
+    lastInsertRowid: number | bigint;
+  };
+}
+
+interface NodeSqliteDatabase {
+  close(): void;
+  exec(sql: string): void;
+  prepare(sql: string): NodeSqliteStatement;
+}
+
+interface NodeSqliteModule {
+  DatabaseSync: new (
+    filename: string,
+    options?: {
+      readOnly?: boolean;
+    },
+  ) => NodeSqliteDatabase;
+}
+
+interface KyselyCompatibleSqliteStatement {
+  readonly reader: boolean;
+  all(parameters: ReadonlyArray<unknown>): unknown[];
+  run(parameters: ReadonlyArray<unknown>): {
+    changes: number | bigint;
+    lastInsertRowid: number | bigint;
+  };
+  iterate(parameters: ReadonlyArray<unknown>): IterableIterator<unknown>;
+}
+
+interface KyselyCompatibleSqliteDatabase {
+  close(): void;
+  prepare(sql: string): KyselyCompatibleSqliteStatement;
+}
+
+const BUN_SQLITE_MODULE = 'bun:sqlite';
+const NODE_SQLITE_MODULE = 'node:sqlite';
+
+function createUnsupportedSqliteRuntimeError(): IdentityDBConfigurationError {
+  return new IdentityDBConfigurationError(
+    'SQLite connections now require a runtime with a built-in SQLite driver. Use Bun for bun:sqlite support, or Node 22+ for node:sqlite support.',
+  );
+}
+
+function isBunRuntime(): boolean {
+  return typeof globalThis === 'object' && 'Bun' in globalThis;
+}
+
+async function createBunSqliteDatabase(
+  config: SqliteConnectionConfig,
+  bunSqliteModule?: BunSqliteModule,
+): Promise<KyselyCompatibleSqliteDatabase> {
+  const bunSqlite = bunSqliteModule
+    ?? ((await import(BUN_SQLITE_MODULE).catch(() => {
+      throw createUnsupportedSqliteRuntimeError();
+    })) as BunSqliteModule);
+
+  const flags = config.readonly
+    ? bunSqlite.constants.SQLITE_OPEN_READONLY
+    : bunSqlite.constants.SQLITE_OPEN_READWRITE
+        | bunSqlite.constants.SQLITE_OPEN_CREATE
+        | (config.filename === ':memory:' ? bunSqlite.constants.SQLITE_OPEN_MEMORY : 0);
+
+  const database = bunSqlite.Database.open(config.filename, flags);
+  database.exec('PRAGMA foreign_keys = ON');
+
+  return {
+    close() {
+      database.close();
+    },
+    prepare(sql: string): KyselyCompatibleSqliteStatement {
+      const statement = database.prepare(sql);
+
+      return {
+        reader: statement.columnNames.length > 0,
+        all(parameters) {
+          return statement.all(Array.from(parameters));
+        },
+        run(parameters) {
+          return statement.run(Array.from(parameters));
+        },
+        iterate(parameters) {
+          return statement.iterate(Array.from(parameters));
+        },
+      };
+    },
+  };
+}
+
+function createNodeSqliteDatabase(
+  config: SqliteConnectionConfig,
+  nodeSqlite: NodeSqliteModule,
+): KyselyCompatibleSqliteDatabase {
+  const database = new nodeSqlite.DatabaseSync(config.filename, {
+    readOnly: config.readonly ?? false,
+  });
+
+  database.exec('PRAGMA foreign_keys = ON');
+
+  return {
+    close() {
+      database.close();
+    },
+    prepare(sql: string): KyselyCompatibleSqliteStatement {
+      const statement = database.prepare(sql);
+
+      return {
+        reader: statement.columns().length > 0,
+        all(parameters) {
+          return statement.all(...parameters);
+        },
+        run(parameters) {
+          return statement.run(...parameters);
+        },
+        iterate(parameters) {
+          return statement.iterate(...parameters);
+        },
+      };
+    },
+  };
+}
+
+async function createSqliteDatabase(
+  config: SqliteConnectionConfig,
+): Promise<KyselyCompatibleSqliteDatabase> {
+  if (isBunRuntime()) {
+    return createBunSqliteDatabase(config);
+  }
+
+  const nodeSqlite = await import(NODE_SQLITE_MODULE).catch(() => null);
+
+  if (nodeSqlite) {
+    return createNodeSqliteDatabase(config, nodeSqlite as NodeSqliteModule);
+  }
+
+  throw createUnsupportedSqliteRuntimeError();
+}
+
 export async function createDatabase(
   config: IdentityDBConnectionConfig,
 ): Promise<DatabaseConnection> {
   switch (config.client) {
     case 'sqlite': {
-      const sqlite = new Database(config.filename, {
+      const sqlite = await createSqliteDatabase(config);
-        readonly: config.readonly ?? false,
-      });
-
-      sqlite.pragma('foreign_keys = ON');
 
       const db = new Kysely<IdentityDatabaseSchema>({
         dialect: new SqliteDialect({
@@ -66,7 +232,6 @@ export async function createDatabase(
         db,
         destroy: async () => {
           await db.destroy();
-          sqlite.close();
         },
       };
     }

src/core/identity-db.ts

@@ -22,7 +22,7 @@ import type { DatabaseConnection, IdentityDBConnectionConfig } from '../adapters
 import type { IdentityDatabaseSchema } from '../types/database';
 import type { FactRecord, SpaceRecord, TopicRecord } from '../types/domain';
 import { createDatabase } from '../adapters/dialect';
-import { extractFact } from '../ingestion/extractor';
+import { extractFacts } from '../ingestion/extractor';
 import {
   findFactRowsConnectingTopicIds,
   findFactRowsForTopicId,
@@ -220,54 +220,70 @@ export class IdentityDB {
   }
 
   async ingestStatement(statement: string, options: IngestStatementOptions): Promise<Fact> {
-    const extracted = await extractFact(statement, options.extractor);
+    const facts = await this.ingestStatements(statement, options);
-    const factInput: AddFactInput = {
+    const first = facts[0];
-      statement: extracted.statement ?? statement,
+    if (!first) {
-      topics: extracted.topics,
+      throw new Error('No facts were extracted from the statement.');
-      spaceName: options.spaceName,
-    };
-
-    if (extracted.summary !== undefined) {
-      factInput.summary = extracted.summary;
     }
+    return first;
+  }
 
-    if (extracted.source !== undefined) {
+  async ingestStatements(statement: string, options: IngestStatementOptions): Promise<Fact[]> {
-      factInput.source = extracted.source;
+    const extractedList = await extractFacts(statement, options.extractor);
-    }
+    const facts: Fact[] = [];
 
-    if (extracted.confidence !== undefined) {
+    for (const extracted of extractedList) {
-      factInput.confidence = extracted.confidence;
+      const factInput: AddFactInput = {
-    }
+        statement: extracted.statement ?? statement,
-
+        topics: extracted.topics,
-    if (extracted.metadata !== undefined) {
-      factInput.metadata = extracted.metadata;
-    }
-
-    if (options.embeddingProvider) {
-      const similarFacts = await this.findSimilarFacts({
-        statement: factInput.statement,
-        provider: options.embeddingProvider,
-        topicNames: factInput.topics.map((topic) => topic.name),
-        limit: 1,
-        minimumScore: options.duplicateThreshold ?? 0.97,
         spaceName: options.spaceName,
-      });
+      };
 
-      if (similarFacts[0]) {
+      if (extracted.summary !== undefined) {
-        return similarFacts[0];
+        factInput.summary = extracted.summary;
       }
+
+      if (extracted.source !== undefined) {
+        factInput.source = extracted.source;
+      }
+
+      if (extracted.confidence !== undefined) {
+        factInput.confidence = extracted.confidence;
+      }
+
+      if (extracted.metadata !== undefined) {
+        factInput.metadata = extracted.metadata;
+      }
+
+      if (options.embeddingProvider) {
+        const similarFacts = await this.findSimilarFacts({
+          statement: factInput.statement,
+          provider: options.embeddingProvider,
+          topicNames: factInput.topics.map((topic) => topic.name),
+          limit: 1,
+          minimumScore: options.duplicateThreshold ?? 0.97,
+          spaceName: options.spaceName,
+        });
+
+        if (similarFacts[0]) {
+          facts.push(similarFacts[0]);
+          continue;
+        }
+      }
+
+      const fact = await this.addFact(factInput);
+
+      if (options.embeddingProvider) {
+        await this.indexFactEmbedding(fact.id, {
+          provider: options.embeddingProvider,
+          spaceName: options.spaceName,
+        });
+      }
+
+      facts.push(fact);
     }
 
-    const fact = await this.addFact(factInput);
+    return facts;
-
-    if (options.embeddingProvider) {
-      await this.indexFactEmbedding(fact.id, {
-        provider: options.embeddingProvider,
-        spaceName: options.spaceName,
-      });
-    }
-
-    return fact;
   }
 
   async indexFactEmbeddings(input: IndexFactEmbeddingsInput): Promise<void> {

src/ingestion/extractor.ts

@@ -2,11 +2,15 @@ import { IdentityDBError } from '../core/errors';
 import { normalizeTopicName } from '../core/utils';
 import type { FactExtractor, ExtractedFact } from './types';
 
-export async function extractFact(
+export async function extractFacts(
   input: string,
   extractor: FactExtractor,
-): Promise<ExtractedFact> {
+): Promise<ExtractedFact[]> {
   const extracted = await extractor.extract(input);
+  return extracted.map((fact) => validateAndNormalizeFact(input, fact));
+}
+
+function validateAndNormalizeFact(input: string, extracted: ExtractedFact): ExtractedFact {
   const statement = extracted.statement?.trim() || input.trim();
 
   if (statement.length === 0) {
@@ -31,12 +35,12 @@ export async function extractFact(
     throw new IdentityDBError('Extractor returned no usable topics.');
   }
 
-    return {
+  return {
-      statement,
+    statement,
-      summary: extracted.summary ?? null,
+    summary: extracted.summary ?? null,
-      source: extracted.source ?? null,
+    source: extracted.source ?? null,
-      confidence: extracted.confidence ?? null,
+    confidence: extracted.confidence ?? null,
-      metadata: extracted.metadata ?? null,
+    metadata: extracted.metadata ?? null,
-      topics: Array.from(dedupedTopics.values()),
+    topics: Array.from(dedupedTopics.values()),
-    };
+  };
 }

src/ingestion/llm-extractor.ts

@@ -1,273 +1,26 @@
-import { IdentityDBError } from '../core/errors';
-import type { TopicCategory, TopicGranularity } from '../types/domain';
 import type {
   ExtractedFact,
   FactExtractor,
   LlmFactExtractorOptions,
-} from './types';
+} from "./types";
 
 const DEFAULT_INSTRUCTIONS = [
-  'Extract one structured fact from the user input.',
+  "Extract structured facts from the user input.",
-  'Return JSON only. Do not include markdown, explanations, or prose outside the JSON object.',
+  "Return a JSON array of fact objects. Do not include markdown, explanations, or prose outside the JSON array.",
-  'Use this shape: {"statement": string?, "summary": string|null, "source": string|null, "confidence": number|null, "metadata": object|null, "topics": Array<{"name": string, "category": "entity"|"concept"|"temporal"|"custom"?, "granularity": "abstract"|"concrete"|"mixed"?, "role": string|null, "description": string|null, "metadata": object|null}>}.',
+  'Each fact object must have a "statement", "summary", "source", "confidence", and "topics" array.',
-  'Only include topics that are explicitly supported by the input.',
+  'Each topic in "topics" must have a "name", and may include "category", "granularity", and "role".',
-].join('\n');
+  "Only include topics that are explicitly in the input.",
+  "If the input contains multiple distinct facts, return them as separate objects in the array.",
+].join("\n");
 
 export class LlmFactExtractor implements FactExtractor {
   constructor(private readonly options: LlmFactExtractorOptions) {}
 
-  async extract(input: string): Promise<ExtractedFact> {
+  async extract(input: string): Promise<ExtractedFact[]> {
-    const prompt = this.buildPrompt(input);
+    return this.options.model.generateText({
-    const response = await this.options.model.generateText(prompt);
+      instruction: DEFAULT_INSTRUCTIONS,
-    return parseLlmExtractedFactResponse(response);
+      input,
-  }
+      additionalInstruction: this.options.additionalInstructions,
-
+    });
-  private buildPrompt(input: string): string {
-    if (this.options.promptBuilder) {
-      return this.options.promptBuilder(input, this.options.instructions);
-    }
-
-    const instructions = this.options.instructions?.trim();
-
-    return [
-      DEFAULT_INSTRUCTIONS,
-      instructions && instructions.length > 0 ? `Additional instructions:\n${instructions}` : null,
-      `Input:\n${input.trim()}`,
-    ]
-      .filter((value): value is string => value !== null)
-      .join('\n\n');
   }
 }
-
-export function parseLlmExtractedFactResponse(response: string): ExtractedFact {
-  const payload = parseJsonCandidate(response);
-
-  if (!isRecord(payload)) {
-    throw new IdentityDBError('LLM extractor response must be a JSON object.');
-  }
-
-  const topics = parseTopics(payload.topics);
-  const extracted: ExtractedFact = { topics };
-
-  const statement = optionalString(payload.statement);
-  if (statement !== undefined) {
-    extracted.statement = statement;
-  }
-
-  const summary = optionalNullableString(payload.summary);
-  if (summary !== undefined) {
-    extracted.summary = summary;
-  }
-
-  const source = optionalNullableString(payload.source);
-  if (source !== undefined) {
-    extracted.source = source;
-  }
-
-  const confidence = optionalNullableNumber(payload.confidence);
-  if (confidence !== undefined) {
-    extracted.confidence = confidence;
-  }
-
-  const metadata = optionalMetadata(payload.metadata);
-  if (metadata !== undefined) {
-    extracted.metadata = metadata;
-  }
-
-  return extracted;
-}
-
-function parseJsonCandidate(response: string): unknown {
-  const trimmed = response.trim();
-
-  for (const candidate of collectJsonCandidates(trimmed)) {
-    try {
-      return JSON.parse(candidate);
-    } catch {
-      continue;
-    }
-  }
-
-  throw new IdentityDBError('LLM extractor returned invalid JSON.');
-}
-
-function collectJsonCandidates(response: string): string[] {
-  const candidates = new Set<string>();
-  candidates.add(response);
-
-  const fencePattern = /```(?:json)?\s*([\s\S]*?)```/gi;
-  let match: RegExpExecArray | null = fencePattern.exec(response);
-
-  while (match) {
-    const candidate = match[1]?.trim();
-    if (candidate) {
-      candidates.add(candidate);
-    }
-
-    match = fencePattern.exec(response);
-  }
-
-  const firstBrace = response.indexOf('{');
-  const lastBrace = response.lastIndexOf('}');
-  if (firstBrace >= 0 && lastBrace > firstBrace) {
-    candidates.add(response.slice(firstBrace, lastBrace + 1));
-  }
-
-  return Array.from(candidates);
-}
-
-function parseTopics(value: unknown): ExtractedFact['topics'] {
-  if (!Array.isArray(value)) {
-    throw new IdentityDBError('LLM extractor response must include a topics array.');
-  }
-
-  return value.map((entry) => parseTopic(entry));
-}
-
-function parseTopic(value: unknown): ExtractedFact['topics'][number] {
-  if (!isRecord(value)) {
-    throw new IdentityDBError('LLM extractor topics must be JSON objects.');
-  }
-
-  const name = optionalString(value.name)?.trim();
-  if (!name) {
-    throw new IdentityDBError('LLM extractor topics must include a non-empty name.');
-  }
-
-  const topic: ExtractedFact['topics'][number] = { name };
-
-  const category = optionalTopicCategory(value.category);
-  if (category !== undefined) {
-    topic.category = category;
-  }
-
-  const granularity = optionalTopicGranularity(value.granularity);
-  if (granularity !== undefined) {
-    topic.granularity = granularity;
-  }
-
-  const role = optionalNullableString(value.role);
-  if (role !== undefined) {
-    topic.role = role;
-  }
-
-  const description = optionalNullableString(value.description);
-  if (description !== undefined) {
-    topic.description = description;
-  }
-
-  const metadata = optionalMetadata(value.metadata);
-  if (metadata !== undefined) {
-    topic.metadata = metadata;
-  }
-
-  return topic;
-}
-
-function optionalString(value: unknown): string | undefined {
-  if (value === undefined) {
-    return undefined;
-  }
-
-  if (typeof value !== 'string') {
-    throw new IdentityDBError('LLM extractor expected a string field.');
-  }
-
-  return value;
-}
-
-function optionalNullableString(value: unknown): string | null | undefined {
-  if (value === undefined) {
-    return undefined;
-  }
-
-  if (value === null) {
-    return null;
-  }
-
-  if (typeof value !== 'string') {
-    throw new IdentityDBError('LLM extractor expected a nullable string field.');
-  }
-
-  return value;
-}
-
-function optionalNullableNumber(value: unknown): number | null | undefined {
-  if (value === undefined) {
-    return undefined;
-  }
-
-  if (value === null) {
-    return null;
-  }
-
-  if (typeof value !== 'number' || Number.isNaN(value)) {
-    throw new IdentityDBError('LLM extractor expected confidence to be a number or null.');
-  }
-
-  return value;
-}
-
-function optionalMetadata(value: unknown): ExtractedFact['metadata'] | undefined {
-  if (value === undefined) {
-    return undefined;
-  }
-
-  if (value === null) {
-    return null;
-  }
-
-  if (!isJsonLike(value)) {
-    throw new IdentityDBError('LLM extractor metadata must be valid JSON-compatible data.');
-  }
-
-  return value as ExtractedFact['metadata'];
-}
-
-function optionalTopicCategory(value: unknown): TopicCategory | undefined {
-  if (value === undefined) {
-    return undefined;
-  }
-
-  if (value === 'entity' || value === 'concept' || value === 'temporal' || value === 'custom') {
-    return value;
-  }
-
-  throw new IdentityDBError('LLM extractor returned an unsupported topic category.');
-}
-
-function optionalTopicGranularity(value: unknown): TopicGranularity | undefined {
-  if (value === undefined) {
-    return undefined;
-  }
-
-  if (value === 'abstract' || value === 'concrete' || value === 'mixed') {
-    return value;
-  }
-
-  throw new IdentityDBError('LLM extractor returned an unsupported topic granularity.');
-}
-
-function isRecord(value: unknown): value is Record<string, unknown> {
-  return typeof value === 'object' && value !== null && !Array.isArray(value);
-}
-
-function isJsonLike(value: unknown): boolean {
-  if (value === null) {
-    return true;
-  }
-
-  if (typeof value === 'string' || typeof value === 'number' || typeof value === 'boolean') {
-    return true;
-  }
-
-  if (Array.isArray(value)) {
-    return value.every((entry) => isJsonLike(entry));
-  }
-
-  if (isRecord(value)) {
-    return Object.values(value).every((entry) => isJsonLike(entry));
-  }
-
-  return false;
-}

src/ingestion/naive-extractor.ts

@@ -1,7 +1,7 @@
 import type { ExtractedFact, FactExtractor } from './types';
 
 export class NaiveExtractor implements FactExtractor {
-  async extract(input: string): Promise<ExtractedFact> {
+  async extract(input: string): Promise<ExtractedFact[]> {
     const topics: ExtractedFact['topics'] = [];
     const seen = new Set<string>();
     const tokens = input.match(/\bI\b|\b\d{4}\b|\b[A-Z][A-Za-z0-9+#.-]*\b/g) ?? [];
@@ -31,9 +31,11 @@ export class NaiveExtractor implements FactExtractor {
       });
     }
 
-    return {
+    return [
-      statement: input.trim(),
+      {
-      topics,
+        statement: input.trim(),
-    };
+        topics,
+      },
+    ];
   }
 }

src/ingestion/types.ts

@@ -2,29 +2,34 @@ import type {
   AddFactInput,
   EmbeddingProvider,
   TopicLinkInput,
-} from '../types/api';
+} from "../types/api";
 
 export interface ExtractedFact {
   statement?: string;
   summary?: string | null;
   source?: string | null;
   confidence?: number | null;
-  metadata?: AddFactInput['metadata'];
+  metadata?: AddFactInput["metadata"];
   topics: TopicLinkInput[];
 }
 
 export interface FactExtractor {
-  extract(input: string): Promise<ExtractedFact>;
+  extract(input: string): Promise<ExtractedFact[]>;
+}
+
+export interface LlmTextGenerationModelInput {
+  instruction: string;
+  input: string;
+  additionalInstruction?: string | undefined;
 }
 
 export interface LlmTextGenerationModel {
-  generateText(prompt: string): Promise<string>;
+  generateText(prompt: LlmTextGenerationModelInput): Promise<ExtractedFact[]>;
 }
 
 export interface LlmFactExtractorOptions {
   model: LlmTextGenerationModel;
-  instructions?: string;
+  additionalInstructions?: string | undefined;
-  promptBuilder?: (input: string, instructions?: string) => string;
 }
 
 export interface IngestStatementOptions {

tests/bun-runtime.test.ts

@@ -0,0 +1,43 @@
+import { execFile } from 'node:child_process';
+import { promisify } from 'node:util';
+
+import { describe, expect, it } from 'vitest';
+
+const execFileAsync = promisify(execFile);
+
+describe('Bun runtime compatibility', () => {
+  it('connects to sqlite from the package in Bun', async () => {
+    const script = [
+      "import { IdentityDB } from './src/index.ts';",
+      "const db = await IdentityDB.connect({ client: 'sqlite', filename: ':memory:' });",
+      'await db.initialize();',
+      "console.log('bun-sqlite-ok');",
+      'await db.close();',
+    ].join('\n');
+
+    const result = await execFileAsync('bun', ['--eval', script], {
+      cwd: process.cwd(),
+    });
+
+    expect(result.stdout).toContain('bun-sqlite-ok');
+  });
+
+  it('supports writes and reads through the Bun sqlite adapter path', async () => {
+    const script = [
+      "import { IdentityDB } from './src/index.ts';",
+      "const db = await IdentityDB.connect({ client: 'sqlite', filename: ':memory:' });",
+      'await db.initialize();',
+      "await db.addFact({ statement: 'Bun supports sqlite.', topics: [{ name: 'Bun', category: 'entity', granularity: 'concrete' }, { name: 'sqlite', category: 'concept', granularity: 'concrete' }] });",
+      "const facts = await db.getTopicFacts('Bun');",
+      "if (facts.length !== 1 || facts[0]?.statement !== 'Bun supports sqlite.') throw new Error('bun sqlite CRUD failed');",
+      "console.log('bun-sqlite-crud-ok');",
+      'await db.close();',
+    ].join('\n');
+
+    const result = await execFileAsync('bun', ['--eval', script], {
+      cwd: process.cwd(),
+    });
+
+    expect(result.stdout).toContain('bun-sqlite-crud-ok');
+  });
+});

tests/ingestion.test.ts

@@ -1,15 +1,18 @@
-import { afterEach, beforeEach, describe, expect, it } from 'vitest';
+import { afterEach, beforeEach, describe, expect, it } from "vitest";
 
-import { IdentityDB } from '../src/core/identity-db';
+import { IdentityDB } from "../src/core/identity-db";
-import { LlmFactExtractor } from '../src/ingestion/llm-extractor';
+import { LlmFactExtractor } from "../src/ingestion/llm-extractor";
-import { NaiveExtractor } from '../src/ingestion/naive-extractor';
+import { NaiveExtractor } from "../src/ingestion/naive-extractor";
-import type { FactExtractor } from '../src/ingestion/types';
+import type {
+  FactExtractor,
+  LlmTextGenerationModelInput,
+} from "../src/ingestion/types";
 
-describe('IdentityDB ingestion', () => {
+describe("IdentityDB ingestion", () => {
   let db: IdentityDB;
 
   beforeEach(async () => {
-    db = await IdentityDB.connect({ client: 'sqlite', filename: ':memory:' });
+    db = await IdentityDB.connect({ client: "sqlite", filename: ":memory:" });
     await db.initialize();
   });
 
@@ -17,121 +20,144 @@ describe('IdentityDB ingestion', () => {
     await db.close();
   });
 
-  it('ingests a statement using a provided extractor', async () => {
+  it("ingests a statement using a provided extractor", async () => {
     const extractor: FactExtractor = {
       async extract(input) {
-        return {
+        return [
-          statement: input,
+          {
-          topics: [
+            statement: input,
-            { name: 'I', category: 'entity', granularity: 'concrete', role: 'subject' },
+            topics: [
-            { name: 'TypeScript', category: 'entity', granularity: 'concrete', role: 'object' },
+              {
-            { name: '2025', category: 'temporal', granularity: 'concrete', role: 'time' },
+                name: "I",
-          ],
+                category: "entity",
-        };
+                granularity: "concrete",
+                role: "subject",
+              },
+              {
+                name: "TypeScript",
+                category: "entity",
+                granularity: "concrete",
+                role: "object",
+              },
+              {
+                name: "2025",
+                category: "temporal",
+                granularity: "concrete",
+                role: "time",
+              },
+            ],
+          },
+        ];
       },
     };
 
-    const fact = await db.ingestStatement('I have worked with TypeScript since 2025.', {
+    const fact = await db.ingestStatement(
-      extractor,
+      "I have worked with TypeScript since 2025.",
-    });
+      {
+        extractor,
+      },
+    );
 
-    expect(fact.topics.map((topic) => topic.name)).toEqual(['I', 'TypeScript', '2025']);
+    expect(fact.topics.map((topic) => topic.name)).toEqual([
+      "I",
+      "TypeScript",
+      "2025",
+    ]);
 
-    const linkedFacts = await db.getTopicFactsLinkedTo('TypeScript', '2025');
+    const linkedFacts = await db.getTopicFactsLinkedTo("TypeScript", "2025");
     expect(linkedFacts).toHaveLength(1);
-    expect(linkedFacts[0]?.statement).toBe('I have worked with TypeScript since 2025.');
+    expect(linkedFacts[0]?.statement).toBe(
+      "I have worked with TypeScript since 2025.",
+    );
   });
 
-  it('ships a deterministic naive extractor for local usage', async () => {
+  it("ships a deterministic naive extractor for local usage", async () => {
-    const fact = await db.ingestStatement('I have worked with TypeScript since 2025.', {
+    const fact = await db.ingestStatement(
-      extractor: new NaiveExtractor(),
+      "I have worked with TypeScript since 2025.",
-    });
+      {
+        extractor: new NaiveExtractor(),
+      },
+    );
 
-    expect(fact.topics.map((topic) => topic.name)).toEqual(['I', 'TypeScript', '2025']);
+    expect(fact.topics.map((topic) => topic.name)).toEqual([
+      "I",
+      "TypeScript",
+      "2025",
+    ]);
 
-    const topic = await db.getTopicByName('TypeScript', { includeFacts: true });
+    const topic = await db.getTopicByName("TypeScript", { includeFacts: true });
     expect(topic?.facts).toHaveLength(1);
   });
 
-  it('ships an LLM extractor adapter that turns structured JSON responses into facts', async () => {
+  it("ships an LLM extractor adapter that returns structured facts from the model", async () => {
-    let prompt = '';
+    let prompt: LlmTextGenerationModelInput | undefined = undefined;
 
     const extractor = new LlmFactExtractor({
       model: {
         async generateText(input) {
           prompt = input;
 
-          return JSON.stringify({
-            statement: 'I have worked with Bun and TypeScript since 2025.',
-            summary: 'The speaker has Bun and TypeScript experience.',
-            source: 'chat',
-            confidence: 0.91,
-            metadata: { channel: 'telegram' },
-            topics: [
-              { name: 'I', category: 'entity', granularity: 'concrete', role: 'subject' },
-              { name: 'Bun', category: 'entity', granularity: 'concrete', role: 'object' },
-              { name: 'TypeScript', category: 'entity', granularity: 'concrete', role: 'object' },
-              { name: '2025', category: 'temporal', granularity: 'concrete', role: 'time' },
-            ],
-          });
-        },
-      },
-      instructions: 'Prefer technology and time topics.',
-    });
-
-    const fact = await db.ingestStatement('I have worked with Bun and TypeScript since 2025.', {
-      extractor,
-    });
-
-    expect(prompt).toContain('Prefer technology and time topics.');
-    expect(prompt).toContain('I have worked with Bun and TypeScript since 2025.');
-    expect(fact.summary).toBe('The speaker has Bun and TypeScript experience.');
-    expect(fact.source).toBe('chat');
-    expect(fact.confidence).toBe(0.91);
-    expect(fact.metadata).toEqual({ channel: 'telegram' });
-    expect(fact.topics.map((topic) => topic.name)).toEqual(['I', 'Bun', 'TypeScript', '2025']);
-  });
-
-  it('parses JSON responses wrapped in markdown code fences', async () => {
-    const extractor = new LlmFactExtractor({
-      model: {
-        async generateText() {
           return [
-            'Here is the extracted fact:',
+            {
-            '```json',
+              statement: "I have worked with Bun and TypeScript since 2025.",
-            JSON.stringify({
+              summary: "The speaker has Bun and TypeScript experience.",
-              statement: 'Bun powers TypeScript tooling.',
+              source: "chat",
+              confidence: 0.91,
+              metadata: { channel: "telegram" },
               topics: [
-                { name: 'Bun', category: 'entity', granularity: 'concrete' },
+                {
-                { name: 'TypeScript', category: 'entity', granularity: 'concrete' },
+                  name: "I",
+                  category: "entity",
+                  granularity: "concrete",
+                  role: "subject",
+                },
+                {
+                  name: "Bun",
+                  category: "entity",
+                  granularity: "concrete",
+                  role: "object",
+                },
+                {
+                  name: "TypeScript",
+                  category: "entity",
+                  granularity: "concrete",
+                  role: "object",
+                },
+                {
+                  name: "2025",
+                  category: "temporal",
+                  granularity: "concrete",
+                  role: "time",
+                },
               ],
-            }),
+            },
-            '```',
+          ];
-          ].join('\n');
         },
       },
+      additionalInstructions: "Prefer technology and time topics.",
     });
 
-    const fact = await db.ingestStatement('Bun powers TypeScript tooling.', {
+    const fact = await db.ingestStatement(
-      extractor,
+      "I have worked with Bun and TypeScript since 2025.",
-    });
+      {
-
-    expect(fact.topics.map((topic) => topic.name)).toEqual(['Bun', 'TypeScript']);
-  });
-
-  it('rejects invalid LLM responses before writing facts', async () => {
-    const extractor = new LlmFactExtractor({
-      model: {
-        async generateText() {
-          return 'not json at all';
-        },
-      },
-    });
-
-    await expect(
-      db.ingestStatement('Bun powers TypeScript tooling.', {
         extractor,
-      }),
+      },
-    ).rejects.toThrow('LLM extractor returned invalid JSON.');
+    );
+
+    expect(prompt).toEqual({
+      instruction: expect.stringContaining("Extract structured facts from the user input."),
+      input: "I have worked with Bun and TypeScript since 2025.",
+      additionalInstruction: "Prefer technology and time topics.",
+    });
+    expect(fact.summary).toBe("The speaker has Bun and TypeScript experience.");
+    expect(fact.source).toBe("chat");
+    expect(fact.confidence).toBe(0.91);
+    expect(fact.metadata).toEqual({ channel: "telegram" });
+    expect(fact.topics.map((topic) => topic.name)).toEqual([
+      "I",
+      "Bun",
+      "TypeScript",
+      "2025",
+    ]);
   });
 });

tests/semantic-search.test.ts

@@ -178,13 +178,15 @@ describe('IdentityDB dedup-aware ingestion', () => {
     provider = new FakeEmbeddingProvider();
     extractor = {
       async extract(input) {
-        return {
+        return [
-          statement: input,
+          {
-          topics: [
+            statement: input,
-            { name: 'Bun', category: 'entity', granularity: 'concrete' },
+            topics: [
-            { name: 'TypeScript', category: 'entity', granularity: 'concrete' },
+              { name: 'Bun', category: 'entity', granularity: 'concrete' },
-          ],
+              { name: 'TypeScript', category: 'entity', granularity: 'concrete' },
-        };
+            ],
+          },
+        ];
       },
     };
 

tsconfig.json

@@ -18,6 +18,12 @@
     "isolatedModules": true,
     "types": ["node", "vitest/globals"]
   },
-  "include": ["src/**/*.ts", "tests/**/*.ts", "vitest.config.ts", "tsup.config.ts"],
+  "include": [
+    "src/**/*.ts",
+    "tests/**/*.ts",
+    "scripts/**/*.ts",
+    "vitest.config.ts",
+    "tsup.config.ts"
+  ],
   "exclude": ["dist", "node_modules"]
 }