diff --git a/docs/next.config.mjs b/docs/next.config.mjs
index b73b4e6..798fa4a 100644
--- a/docs/next.config.mjs
+++ b/docs/next.config.mjs
@@ -1,14 +1,30 @@
 /** @type {import('next').NextConfig} */
 // import MillionLint from "@million/lint";
+import path from 'path';
+import { fileURLToPath } from 'url';
+
+const __dirname = path.dirname(fileURLToPath(import.meta.url));
 
 const nextConfig = {
     webpack: (config) => {
       config.module.rules.push({
         test: /\.json$/,
         type: 'json',
-      })
+      });
+      
+      config.resolve.alias = {
+        ...config.resolve.alias,
+        "sharp$": false,
+        "onnxruntime-node$": false,
+      }
+
+      config.resolve.alias['@huggingface/transformers'] = path.resolve(__dirname, 'node_modules/@huggingface/transformers');
+
       return config
     },
+    experimental: {
+      esmExternals: true // Enable ES modules
+    },
     // i18n: {
     //   locales: ['en', 'es', 'fr', 'de'],
     //   defaultLocale: 'en',
diff --git a/docs/package-lock.json b/docs/package-lock.json
index f48f35a..3c80bc7 100644
--- a/docs/package-lock.json
+++ b/docs/package-lock.json
@@ -1,12 +1,12 @@
 {
   "name": "akiradocs",
-  "version": "1.0.1",
+  "version": "1.0.52",
   "lockfileVersion": 3,
   "requires": true,
   "packages": {
     "": {
       "name": "akiradocs",
-      "version": "1.0.1",
+      "version": "1.0.52",
       "dependencies": {
         "@ai-sdk/anthropic": "^1.0.1",
         "@dnd-kit/core": "^6.1.0",
@@ -14,6 +14,7 @@
         "@dnd-kit/utilities": "^3.2.2",
         "@google/generative-ai": "^0.2.1",
         "@heroicons/react": "^2.1.5",
+        "@huggingface/transformers": "^3.2.3",
         "@mdx-js/loader": "^3.1.0",
         "@mdx-js/react": "^3.1.0",
         "@million/lint": "^1.0.12",
@@ -36,7 +37,9 @@
         "@radix-ui/react-toggle": "^1.1.0",
         "@radix-ui/react-toggle-group": "^1.1.0",
         "@radix-ui/react-tooltip": "^1.1.3",
+        "@xenova/transformers": "^2.17.2",
         "ai": "^4.0.2",
+        "better-sqlite3": "^11.7.0",
         "class-variance-authority": "^0.7.0",
         "clsx": "^2.1.1",
         "cross-spawn": "^7.0.6",
@@ -56,7 +59,11 @@
         "react-error-boundary": "^4.1.2",
         "react-markdown": "^9.0.1",
         "react-syntax-highlighter": "^15.6.1",
+        "remark-gfm": "^4.0.0",
+        "sharp": "^0.33.5",
         "sonner": "^1.7.0",
+        "sql.js-httpvfs": "^0.8.12",
+        "sqlite-vss": "^0.1.2",
         "styled-components": "^6.1.13",
         "tailwind-merge": "^2.5.4",
         "tailwindcss-animate": "^1.0.7"
@@ -529,7 +536,6 @@
     },
     "node_modules/@clack/prompts/node_modules/is-unicode-supported": {
       "version": "1.3.0",
-      "extraneous": true,
       "inBundle": true,
       "license": "MIT",
       "engines": {
@@ -610,6 +616,16 @@
         "react": ">=16.8.0"
       }
     },
+    "node_modules/@emnapi/runtime": {
+      "version": "1.3.1",
+      "resolved": "https://registry.npmjs.org/@emnapi/runtime/-/runtime-1.3.1.tgz",
+      "integrity": "sha512-kEBmG8KyqtxJZv+ygbEim+KCGtIq1fC22Ms3S4ziXmYKm8uyoLX0MHONVKwp+9opg390VaKRNt4a7A9NwmpNhw==",
+      "license": "MIT",
+      "optional": true,
+      "dependencies": {
+        "tslib": "^2.4.0"
+      }
+    },
     "node_modules/@emotion/is-prop-valid": {
       "version": "1.2.2",
       "resolved": "https://registry.npmjs.org/@emotion/is-prop-valid/-/is-prop-valid-1.2.2.tgz",
@@ -1118,6 +1134,108 @@
         "hono": "^4"
       }
     },
+    "node_modules/@huggingface/jinja": {
+      "version": "0.2.2",
+      "resolved": "https://registry.npmjs.org/@huggingface/jinja/-/jinja-0.2.2.tgz",
+      "integrity": "sha512-/KPde26khDUIPkTGU82jdtTW9UAuvUTumCAbFs/7giR0SxsvZC4hru51PBvpijH6BVkHcROcvZM/lpy5h1jRRA==",
+      "license": "MIT",
+      "engines": {
+        "node": ">=18"
+      }
+    },
+    "node_modules/@huggingface/transformers": {
+      "version": "3.2.3",
+      "resolved": "https://registry.npmjs.org/@huggingface/transformers/-/transformers-3.2.3.tgz",
+      "integrity": "sha512-o7QZphrCH3a3m0kF/MaSNv3DMDZCpTifdZ9k4Lwl2n9QhY8JIGOOtZDVa+Wv2cqKU6iJm1SiCqDdZpo8H20c8g==",
+      "license": "Apache-2.0",
+      "dependencies": {
+        "@huggingface/jinja": "^0.3.2",
+        "onnxruntime-node": "1.20.1",
+        "onnxruntime-web": "1.21.0-dev.20241205-d27fecd3d3",
+        "sharp": "^0.33.5"
+      }
+    },
+    "node_modules/@huggingface/transformers/node_modules/@huggingface/jinja": {
+      "version": "0.3.2",
+      "resolved": "https://registry.npmjs.org/@huggingface/jinja/-/jinja-0.3.2.tgz",
+      "integrity": "sha512-F2FvuIc+w1blGsaqJI/OErRbWH6bVJDCBI8Rm5D86yZ2wlwrGERsfIaru7XUv9eYC3DMP3ixDRRtF0h6d8AZcQ==",
+      "license": "MIT",
+      "engines": {
+        "node": ">=18"
+      }
+    },
+    "node_modules/@huggingface/transformers/node_modules/long": {
+      "version": "5.2.3",
+      "resolved": "https://registry.npmjs.org/long/-/long-5.2.3.tgz",
+      "integrity": "sha512-lcHwpNoggQTObv5apGNCTdJrO69eHOZMi4BNC+rTLER8iHAqGrUVeLh/irVIM7zTw2bOXA8T6uNPeujwOLg/2Q==",
+      "license": "Apache-2.0"
+    },
+    "node_modules/@huggingface/transformers/node_modules/onnxruntime-common": {
+      "version": "1.20.1",
+      "resolved": "https://registry.npmjs.org/onnxruntime-common/-/onnxruntime-common-1.20.1.tgz",
+      "integrity": "sha512-YiU0s0IzYYC+gWvqD1HzLc46Du1sXpSiwzKb63PACIJr6LfL27VsXSXQvt68EzD3V0D5Bc0vyJTjmMxp0ylQiw==",
+      "license": "MIT"
+    },
+    "node_modules/@huggingface/transformers/node_modules/onnxruntime-node": {
+      "version": "1.20.1",
+      "resolved": "https://registry.npmjs.org/onnxruntime-node/-/onnxruntime-node-1.20.1.tgz",
+      "integrity": "sha512-di/I4HDXRw+FLgq+TyHmQEDd3cEp9iFFZm0r4uJ1Wd7b/WE1VXtKWo8yemex347c6GNF/3Pv86ZfPhIWxORr0w==",
+      "hasInstallScript": true,
+      "license": "MIT",
+      "os": [
+        "win32",
+        "darwin",
+        "linux"
+      ],
+      "dependencies": {
+        "onnxruntime-common": "1.20.1",
+        "tar": "^7.0.1"
+      }
+    },
+    "node_modules/@huggingface/transformers/node_modules/onnxruntime-web": {
+      "version": "1.21.0-dev.20241205-d27fecd3d3",
+      "resolved": "https://registry.npmjs.org/onnxruntime-web/-/onnxruntime-web-1.21.0-dev.20241205-d27fecd3d3.tgz",
+      "integrity": "sha512-neeC9mv1sFWjUFrTaDl7enufNxbtSSTwR5V2i35ga4yXWS6r1MbpUwWwD1X+VKANujbSG8M5pk/ohRAOm2QhMQ==",
+      "license": "MIT",
+      "dependencies": {
+        "flatbuffers": "^1.12.0",
+        "guid-typescript": "^1.0.9",
+        "long": "^5.2.3",
+        "onnxruntime-common": "1.21.0-dev.20241205-6ed77cc374",
+        "platform": "^1.3.6",
+        "protobufjs": "^7.2.4"
+      }
+    },
+    "node_modules/@huggingface/transformers/node_modules/onnxruntime-web/node_modules/onnxruntime-common": {
+      "version": "1.21.0-dev.20241205-6ed77cc374",
+      "resolved": "https://registry.npmjs.org/onnxruntime-common/-/onnxruntime-common-1.21.0-dev.20241205-6ed77cc374.tgz",
+      "integrity": "sha512-U4DGq/dZiboIEK0Zv1KUuWJesJ/txUALpWSXwI8kqOCSxe8GrI65xfRFeMbqYFhPVGAWZPsBpT1zo1s4ksrlrg==",
+      "license": "MIT"
+    },
+    "node_modules/@huggingface/transformers/node_modules/protobufjs": {
+      "version": "7.4.0",
+      "resolved": "https://registry.npmjs.org/protobufjs/-/protobufjs-7.4.0.tgz",
+      "integrity": "sha512-mRUWCc3KUU4w1jU8sGxICXH/gNS94DvI1gxqDvBzhj1JpcsimQkYiOJfwsPUykUI5ZaspFbSgmBLER8IrQ3tqw==",
+      "hasInstallScript": true,
+      "license": "BSD-3-Clause",
+      "dependencies": {
+        "@protobufjs/aspromise": "^1.1.2",
+        "@protobufjs/base64": "^1.1.2",
+        "@protobufjs/codegen": "^2.0.4",
+        "@protobufjs/eventemitter": "^1.1.0",
+        "@protobufjs/fetch": "^1.1.0",
+        "@protobufjs/float": "^1.0.2",
+        "@protobufjs/inquire": "^1.1.0",
+        "@protobufjs/path": "^1.1.2",
+        "@protobufjs/pool": "^1.1.0",
+        "@protobufjs/utf8": "^1.1.0",
+        "@types/node": ">=13.7.0",
+        "long": "^5.0.0"
+      },
+      "engines": {
+        "node": ">=12.0.0"
+      }
+    },
     "node_modules/@humanwhocodes/config-array": {
       "version": "0.13.0",
       "resolved": "https://registry.npmjs.org/@humanwhocodes/config-array/-/config-array-0.13.0.tgz",
@@ -1174,6 +1292,28 @@
         "@img/sharp-libvips-darwin-arm64": "1.0.4"
       }
     },
+    "node_modules/@img/sharp-darwin-x64": {
+      "version": "0.33.5",
+      "resolved": "https://registry.npmjs.org/@img/sharp-darwin-x64/-/sharp-darwin-x64-0.33.5.tgz",
+      "integrity": "sha512-fyHac4jIc1ANYGRDxtiqelIbdWkIuQaI84Mv45KvGRRxSAa7o7d1ZKAOBaYbnepLC1WqxfpimdeWfvqqSGwR2Q==",
+      "cpu": [
+        "x64"
+      ],
+      "license": "Apache-2.0",
+      "optional": true,
+      "os": [
+        "darwin"
+      ],
+      "engines": {
+        "node": "^18.17.0 || ^20.3.0 || >=21.0.0"
+      },
+      "funding": {
+        "url": "https://opencollective.com/libvips"
+      },
+      "optionalDependencies": {
+        "@img/sharp-libvips-darwin-x64": "1.0.4"
+      }
+    },
     "node_modules/@img/sharp-libvips-darwin-arm64": {
       "version": "1.0.4",
       "resolved": "https://registry.npmjs.org/@img/sharp-libvips-darwin-arm64/-/sharp-libvips-darwin-arm64-1.0.4.tgz",
@@ -1189,118 +1329,431 @@
         "url": "https://opencollective.com/libvips"
       }
     },
-    "node_modules/@isaacs/cliui": {
-      "version": "8.0.2",
-      "resolved": "https://registry.npmjs.org/@isaacs/cliui/-/cliui-8.0.2.tgz",
-      "integrity": "sha512-O8jcjabXaleOG9DQ0+ARXWZBTfnP4WNAqzuiJK7ll44AmxGKv/J2M4TPjxjY3znBCfvBXFzucm1twdyFybFqEA==",
-      "dependencies": {
-        "string-width": "^5.1.2",
-        "string-width-cjs": "npm:string-width@^4.2.0",
-        "strip-ansi": "^7.0.1",
-        "strip-ansi-cjs": "npm:strip-ansi@^6.0.1",
-        "wrap-ansi": "^8.1.0",
-        "wrap-ansi-cjs": "npm:wrap-ansi@^7.0.0"
-      },
-      "engines": {
-        "node": ">=12"
+    "node_modules/@img/sharp-libvips-darwin-x64": {
+      "version": "1.0.4",
+      "resolved": "https://registry.npmjs.org/@img/sharp-libvips-darwin-x64/-/sharp-libvips-darwin-x64-1.0.4.tgz",
+      "integrity": "sha512-xnGR8YuZYfJGmWPvmlunFaWJsb9T/AO2ykoP3Fz/0X5XV2aoYBPkX6xqCQvUTKKiLddarLaxpzNe+b1hjeWHAQ==",
+      "cpu": [
+        "x64"
+      ],
+      "license": "LGPL-3.0-or-later",
+      "optional": true,
+      "os": [
+        "darwin"
+      ],
+      "funding": {
+        "url": "https://opencollective.com/libvips"
       }
     },
-    "node_modules/@isaacs/cliui/node_modules/ansi-regex": {
-      "version": "6.1.0",
-      "resolved": "https://registry.npmjs.org/ansi-regex/-/ansi-regex-6.1.0.tgz",
-      "integrity": "sha512-7HSX4QQb4CspciLpVFwyRe79O3xsIZDDLER21kERQ71oaPodF8jL725AgJMFAYbooIqolJoRLuM81SpeUkpkvA==",
-      "engines": {
-        "node": ">=12"
-      },
+    "node_modules/@img/sharp-libvips-linux-arm": {
+      "version": "1.0.5",
+      "resolved": "https://registry.npmjs.org/@img/sharp-libvips-linux-arm/-/sharp-libvips-linux-arm-1.0.5.tgz",
+      "integrity": "sha512-gvcC4ACAOPRNATg/ov8/MnbxFDJqf/pDePbBnuBDcjsI8PssmjoKMAz4LtLaVi+OnSb5FK/yIOamqDwGmXW32g==",
+      "cpu": [
+        "arm"
+      ],
+      "license": "LGPL-3.0-or-later",
+      "optional": true,
+      "os": [
+        "linux"
+      ],
       "funding": {
-        "url": "https://github.com/chalk/ansi-regex?sponsor=1"
+        "url": "https://opencollective.com/libvips"
       }
     },
-    "node_modules/@isaacs/cliui/node_modules/strip-ansi": {
-      "version": "7.1.0",
-      "resolved": "https://registry.npmjs.org/strip-ansi/-/strip-ansi-7.1.0.tgz",
-      "integrity": "sha512-iq6eVVI64nQQTRYq2KtEg2d2uU7LElhTJwsH4YzIHZshxlgZms/wIc4VoDQTlG/IvVIrBKG06CrZnp0qv7hkcQ==",
-      "dependencies": {
-        "ansi-regex": "^6.0.1"
-      },
-      "engines": {
-        "node": ">=12"
-      },
+    "node_modules/@img/sharp-libvips-linux-arm64": {
+      "version": "1.0.4",
+      "resolved": "https://registry.npmjs.org/@img/sharp-libvips-linux-arm64/-/sharp-libvips-linux-arm64-1.0.4.tgz",
+      "integrity": "sha512-9B+taZ8DlyyqzZQnoeIvDVR/2F4EbMepXMc/NdVbkzsJbzkUjhXv/70GQJ7tdLA4YJgNP25zukcxpX2/SueNrA==",
+      "cpu": [
+        "arm64"
+      ],
+      "license": "LGPL-3.0-or-later",
+      "optional": true,
+      "os": [
+        "linux"
+      ],
       "funding": {
-        "url": "https://github.com/chalk/strip-ansi?sponsor=1"
+        "url": "https://opencollective.com/libvips"
       }
     },
-    "node_modules/@jridgewell/gen-mapping": {
-      "version": "0.3.5",
-      "resolved": "https://registry.npmjs.org/@jridgewell/gen-mapping/-/gen-mapping-0.3.5.tgz",
-      "integrity": "sha512-IzL8ZoEDIBRWEzlCcRhOaCupYyN5gdIK+Q6fbFdPDg6HqX6jpkItn7DFIpW9LQzXG6Df9sA7+OKnq0qlz/GaQg==",
-      "dependencies": {
-        "@jridgewell/set-array": "^1.2.1",
-        "@jridgewell/sourcemap-codec": "^1.4.10",
-        "@jridgewell/trace-mapping": "^0.3.24"
-      },
-      "engines": {
-        "node": ">=6.0.0"
+    "node_modules/@img/sharp-libvips-linux-s390x": {
+      "version": "1.0.4",
+      "resolved": "https://registry.npmjs.org/@img/sharp-libvips-linux-s390x/-/sharp-libvips-linux-s390x-1.0.4.tgz",
+      "integrity": "sha512-u7Wz6ntiSSgGSGcjZ55im6uvTrOxSIS8/dgoVMoiGE9I6JAfU50yH5BoDlYA1tcuGS7g/QNtetJnxA6QEsCVTA==",
+      "cpu": [
+        "s390x"
+      ],
+      "license": "LGPL-3.0-or-later",
+      "optional": true,
+      "os": [
+        "linux"
+      ],
+      "funding": {
+        "url": "https://opencollective.com/libvips"
       }
     },
-    "node_modules/@jridgewell/resolve-uri": {
-      "version": "3.1.2",
-      "resolved": "https://registry.npmjs.org/@jridgewell/resolve-uri/-/resolve-uri-3.1.2.tgz",
-      "integrity": "sha512-bRISgCIjP20/tbWSPWMEi54QVPRZExkuD9lJL+UIxUKtwVJA8wW1Trb1jMs1RFXo1CBTNZ/5hpC9QvmKWdopKw==",
-      "engines": {
-        "node": ">=6.0.0"
+    "node_modules/@img/sharp-libvips-linux-x64": {
+      "version": "1.0.4",
+      "resolved": "https://registry.npmjs.org/@img/sharp-libvips-linux-x64/-/sharp-libvips-linux-x64-1.0.4.tgz",
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+      "cpu": [
+        "x64"
+      ],
+      "license": "LGPL-3.0-or-later",
+      "optional": true,
+      "os": [
+        "linux"
+      ],
+      "funding": {
+        "url": "https://opencollective.com/libvips"
       }
     },
-    "node_modules/@jridgewell/set-array": {
-      "version": "1.2.1",
-      "resolved": "https://registry.npmjs.org/@jridgewell/set-array/-/set-array-1.2.1.tgz",
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-      "engines": {
-        "node": ">=6.0.0"
+    "node_modules/@img/sharp-libvips-linuxmusl-arm64": {
+      "version": "1.0.4",
+      "resolved": "https://registry.npmjs.org/@img/sharp-libvips-linuxmusl-arm64/-/sharp-libvips-linuxmusl-arm64-1.0.4.tgz",
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+      "cpu": [
+        "arm64"
+      ],
+      "license": "LGPL-3.0-or-later",
+      "optional": true,
+      "os": [
+        "linux"
+      ],
+      "funding": {
+        "url": "https://opencollective.com/libvips"
       }
     },
-    "node_modules/@jridgewell/sourcemap-codec": {
-      "version": "1.5.0",
-      "resolved": "https://registry.npmjs.org/@jridgewell/sourcemap-codec/-/sourcemap-codec-1.5.0.tgz",
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-      "resolved": "https://registry.npmjs.org/@jridgewell/trace-mapping/-/trace-mapping-0.3.25.tgz",
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-      "dependencies": {
-        "@jridgewell/resolve-uri": "^3.1.0",
-        "@jridgewell/sourcemap-codec": "^1.4.14"
+    "node_modules/@img/sharp-libvips-linuxmusl-x64": {
+      "version": "1.0.4",
+      "resolved": "https://registry.npmjs.org/@img/sharp-libvips-linuxmusl-x64/-/sharp-libvips-linuxmusl-x64-1.0.4.tgz",
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+      "cpu": [
+        "x64"
+      ],
+      "license": "LGPL-3.0-or-later",
+      "optional": true,
+      "os": [
+        "linux"
+      ],
+      "funding": {
+        "url": "https://opencollective.com/libvips"
       }
     },
-    "node_modules/@mdx-js/loader": {
-      "version": "3.1.0",
-      "resolved": "https://registry.npmjs.org/@mdx-js/loader/-/loader-3.1.0.tgz",
-      "integrity": "sha512-xU/lwKdOyfXtQGqn3VnJjlDrmKXEvMi1mgYxVmukEUtVycIz1nh7oQ40bKTd4cA7rLStqu0740pnhGYxGoqsCg==",
-      "dependencies": {
-        "@mdx-js/mdx": "^3.0.0",
-        "source-map": "^0.7.0"
+    "node_modules/@img/sharp-linux-arm": {
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@@ -10752,6 +12323,78 @@
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+      "license": "ISC",
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+        "chownr": "^3.0.0",
+        "minipass": "^7.1.2",
+        "minizlib": "^3.0.1",
+        "mkdirp": "^3.0.1",
+        "yallist": "^5.0.0"
+      },
+      "engines": {
+        "node": ">=18"
+      }
+    },
+    "node_modules/tar-fs": {
+      "version": "2.1.1",
+      "resolved": "https://registry.npmjs.org/tar-fs/-/tar-fs-2.1.1.tgz",
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+      "license": "MIT",
+      "dependencies": {
+        "chownr": "^1.1.1",
+        "mkdirp-classic": "^0.5.2",
+        "pump": "^3.0.0",
+        "tar-stream": "^2.1.4"
+      }
+    },
+    "node_modules/tar-stream": {
+      "version": "2.2.0",
+      "resolved": "https://registry.npmjs.org/tar-stream/-/tar-stream-2.2.0.tgz",
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+      "license": "MIT",
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+        "fs-constants": "^1.0.0",
+        "inherits": "^2.0.3",
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+    },
+    "node_modules/tar/node_modules/chownr": {
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+      "license": "BlueOak-1.0.0",
+      "engines": {
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+      "license": "BlueOak-1.0.0",
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-      "dev": true
+      "integrity": "sha512-l4Sp/DRseor9wL6EvV2+TuQn63dMkPjZ/sp9XkghTEbV9KlPS1xUsZ3u7/IQO4wxtcFB4bgpQPRcR3QCvezPcQ=="
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+      "license": "MIT",
       "engines": {
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diff --git a/docs/package.json b/docs/package.json
index 0287ffb..6908e7e 100644
--- a/docs/package.json
+++ b/docs/package.json
@@ -1,6 +1,6 @@
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-  "version": "1.0.52",
+  "version": "1.0.53",
   "private": true,
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     "@google/generative-ai": "^0.2.1",
     "@heroicons/react": "^2.1.5",
+    "@huggingface/transformers": "^3.2.3",
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     "@mdx-js/react": "^3.1.0",
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     "@radix-ui/react-toggle-group": "^1.1.0",
     "@radix-ui/react-tooltip": "^1.1.3",
+    "@xenova/transformers": "^2.17.2",
     "ai": "^4.0.2",
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     "clsx": "^2.1.1",
     "cross-spawn": "^7.0.6",
@@ -62,7 +65,11 @@
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     "react-markdown": "^9.0.1",
     "react-syntax-highlighter": "^15.6.1",
+    "remark-gfm": "^4.0.0",
+    "sharp": "^0.33.5",
     "sonner": "^1.7.0",
+    "sql.js-httpvfs": "^0.8.12",
+    "sqlite-vss": "^0.1.2",
     "styled-components": "^6.1.13",
     "tailwind-merge": "^2.5.4",
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new file mode 100644
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diff --git a/docs/scripts/extract-docs-context.js b/docs/scripts/extract-docs-context.js
index 2bd7f4d..cdc252f 100644
--- a/docs/scripts/extract-docs-context.js
+++ b/docs/scripts/extract-docs-context.js
@@ -1,6 +1,33 @@
 const fs = require('fs/promises');
 const path = require('path');
 const { glob } = require('glob');
+const sqlite3 = require('better-sqlite3');
+
+class EmbeddingPipeline {
+  static task = 'feature-extraction';
+  static model = 'sauravpanda/gte-small-onnx';
+  static instance = null;
+
+  static async getInstance(progress_callback = null) {
+    if (this.instance === null) {
+      // Optionally set cache directory
+      const { pipeline, env } = await import('@xenova/transformers');
+      this.instance = await pipeline(this.task, this.model, { progress_callback });
+    }
+    return this.instance;
+  }
+}
+
+async function generateEmbedding(text) {
+  try {
+    const extractor = await EmbeddingPipeline.getInstance();
+    const output = await extractor(text, { pooling: 'mean', normalize: true });
+    return Array.from(output.data);
+  } catch (error) {
+    console.error('Error generating embedding:', error);
+    return null;
+  }
+}
 
 async function extractTextFromBlocks(blocks) {
   if (!Array.isArray(blocks)) {
@@ -67,26 +94,47 @@ async function main() {
     const contextDir = path.join(process.cwd(), 'public', 'context');
     await fs.mkdir(contextDir, { recursive: true });
     
+    const dbPath = path.join(contextDir, 'docs.db');
+    const db = sqlite3(dbPath);
+    
+    db.exec(`
+      CREATE TABLE IF NOT EXISTS documents (
+        id INTEGER PRIMARY KEY AUTOINCREMENT,
+        path TEXT NOT NULL,
+        content TEXT NOT NULL,
+        embedding BLOB,
+        created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
+      )
+    `);
+    
+    // Initialize the embedding model once
+    console.log('Initializing embedding model...');
+    // const extractor = await pipeline('feature-extraction', 'sauravpanda/gte-small-onnx');
+    
     const enDocsDir = path.join(process.cwd(), 'compiled', 'en');
     const docFiles = await glob('**/*.json', { 
       cwd: enDocsDir,
       ignore: '**/_meta.json'
     });
     
-    let combinedContent = [];
+    db.prepare('DELETE FROM documents').run();
+    const insert = db.prepare('INSERT INTO documents (path, content, embedding) VALUES (?, ?, ?)');
+    
+    console.log('Processing documents and generating embeddings...');
     
     for (const file of docFiles) {
       const fullPath = path.join(enDocsDir, file);
       const content = await processDocFile(fullPath);
       if (content) {
-        combinedContent.push(`[Document: ${file}]\n${content}\n-------------`);
+        const embedding = await generateEmbedding(content);
+        insert.run(file, content, embedding ? JSON.stringify(embedding) : null);
+        console.log(`Processed: ${file}`);
       }
     }
     
-    const outputPath = path.join(contextDir, 'en_docs.txt');
-    await fs.writeFile(outputPath, combinedContent.join('\n'));
-    
-    console.log('Documentation context has been extracted successfully!');
+    db.exec(`CREATE INDEX IF NOT EXISTS idx_embedding ON documents(embedding)`);
+    console.log('Documentation context and embeddings have been stored in SQLite database!');
+    db.close();
   } catch (error) {
     console.error('Error processing documentation:', error);
     process.exit(1);
diff --git a/docs/src/app/aiSearch/page.tsx b/docs/src/app/aiSearch/page.tsx
index 5e849e3..0239b37 100644
--- a/docs/src/app/aiSearch/page.tsx
+++ b/docs/src/app/aiSearch/page.tsx
@@ -1,6 +1,6 @@
 "use client"
 
-import { useState } from 'react'
+import { useState, useCallback } from 'react'
 import { SearchHeader } from '@/components/aiSearch/SearchHeader'
 import { SearchBar } from '@/components/aiSearch/SearchBar'
 import { LegacyDocsToggle } from '@/components/aiSearch/LegacyDocsToggle'
@@ -17,196 +17,294 @@ import { Source } from '@/types/Source'
 import AILoader from '@/components/aiSearch/AILoader'
 import { getHeaderConfig } from '@/lib/headerConfig'
 import { Header } from '@/components/layout/Header'
+import { generateEmbedding } from '@/lib/aisearch/embeddings'
+import { getDbWorker } from '@/lib/aisearch/dbWorker'
+
+function cosineSimilarity(a: number[], b: number[]): number {
+    if (a.some(isNaN) || b.some(isNaN)) {
+        console.error("NaN values detected in vectors:");
+        console.error("Vector A NaN indices:", a.map((val, i) => isNaN(val) ? i : null).filter(x => x !== null));
+        console.error("Vector B NaN indices:", b.map((val, i) => isNaN(val) ? i : null).filter(x => x !== null));
+        throw new Error("Invalid vectors containing NaN values");
+    }
+    
+    const dotProduct = a.reduce((sum, val, i) => sum + val * b[i], 0);
+    const magnitudeA = Math.sqrt(a.reduce((sum, val) => sum + val * val, 0));
+    const magnitudeB = Math.sqrt(b.reduce((sum, val) => sum + val * val, 0));
+    return dotProduct / (magnitudeA * magnitudeB);
+}
 
 export default function Home() {
-  const [query, setQuery] = useState('')
-  const [aiResponse, setAiResponse] = useState('')
-  const [isLoading, setIsLoading] = useState(false)
-  const [error, setError] = useState<string | null>(null)
-  const recommendedArticles = getRecommendedArticles()
-  const searchConfig = getSearchConfig()
-  const headerConfig = getHeaderConfig()
-  const config = getAkiradocsConfig()
-  const [sources, setSources] = useState<Source[]>([])
-
-  // If AI Search is disabled, show the disabled message
-  if (!config.navigation.header.items.find((item: any) => item.href === '/aiSearch')?.show) {
-    return (
-      <div className="min-h-screen flex flex-col items-center justify-center p-4">
-        <div className="text-center space-y-4 max-w-md">
-          <h1 className="text-3xl font-bold">AI Search is Disabled</h1>
-          <p className="text-muted-foreground">
-            AI Search is currently disabled. To enable this feature, set &quot;aiSearch&quot;: true in your configuration file.
-          </p>
-          <Button asChild>
-            <Link href="/">Go to Home</Link>
-          </Button>
-        </div>
-      </div>
-    )
-  }
+    const [query, setQuery] = useState('')
+    const [aiResponse, setAiResponse] = useState('')
+    const [loaderText, setLoaderText] = useState('Loading database ...')
+    const [isLoading, setIsLoading] = useState(false)
+    const [error, setError] = useState<string | null>(null)
+    const recommendedArticles = getRecommendedArticles()
+    const searchConfig = getSearchConfig()
+    const headerConfig = getHeaderConfig()
+    const config = getAkiradocsConfig()
+    const [sources, setSources] = useState<Source[]>([])
+    const handleGenerateEmbedding = useCallback(async (text: string) => {
+        try {
+            setIsLoading(true);
+            // console.log("Loading model for embedding");
+            const embedding = await generateEmbedding(text, (progress) => {});
+            return embedding;
+        } catch (error) {
+            console.error('Error generating embedding:', error);
+            throw error;
+        }
+        finally {
+          setLoaderText('Searching database for relevant information ...')
+        }
+    }, []);
 
-  const extractSources = (response: string): { cleanResponse: string, sources: Source[] } => {
-    // Split the response into parts
-    const parts = response.split('Sources:');
-    if (parts.length < 2) {
-      return { cleanResponse: response, sources: [] };
+    // If AI Search is disabled, show the disabled message
+    if (!config.navigation.header.items.find((item: any) => item.href === '/aiSearch')?.show) {
+        return (
+            <div className="min-h-screen flex flex-col items-center justify-center p-4">
+                <div className="text-center space-y-4 max-w-md">
+                    <h1 className="text-3xl font-bold">AI Search is Disabled</h1>
+                    <p className="text-muted-foreground">
+                        AI Search is currently disabled. To enable this feature, set &quot;aiSearch&quot;: true in your configuration file.
+                    </p>
+                    <Button asChild>
+                        <Link href="/">Go to Home</Link>
+                    </Button>
+                </div>
+            </div>
+        )
     }
 
-    const cleanResponse = parts[0].trim();
-    const sourcesText = parts[1].trim();
-
-    // Extract sources from the text
-    const sources: Source[] = sourcesText
-      .split('\n')
-      .filter(line => line.trim().length > 0 && line.includes('.json')) // Only process non-empty lines containing .json
-      .map(line => ({
-        title: line.trim().split('/').pop()?.replace('.json', '') || '', // Get the filename without extension
-        url: line.trim()
-      }));
-
-    return { cleanResponse, sources };
-  };
-
-  const handleSearch = async (e: React.FormEvent) => {
-    e.preventDefault()
-    setIsLoading(true)
-    setError(null)
-    setSources([])
-    
-    try {
-      const contextResponse = await fetch('/context/en_docs.txt');
-      if (!contextResponse.ok) {
-        throw new Error(`Failed to fetch context: ${contextResponse.status}`);
-      }
-      const contextData = await contextResponse.text();
-      const docsContext = contextData;
-
-      const engine = await CreateMLCEngine(
-        "Llama-3.2-1B-Instruct-q4f16_1-MLC",
-        { initProgressCallback: (progress: any) => console.log(progress)
-        },
-        {
-          context_window_size: 100000,
+    const extractSources = (response: string): { cleanResponse: string, sources: Source[] } => {
+        // Split the response into parts
+        const parts = response.split('Sources:');
+        if (parts.length < 2) {
+            return { cleanResponse: response, sources: [] };
         }
-      );
-
-      const messages = [
-        { 
-          role: "system", 
-          content: `You are a technical documentation assistant specialized in providing accurate, concise answers based on the official documentation. 
-          Your responses should be:
-          1. Direct and to the point
-          2. Based strictly on the provided documentation context
-          3. Include relevant code examples when available
-          4. Written in a technical but clear style
-
-          Documentation context: ${docsContext}`
-        },
-        { 
-          role: "user", 
-          content: `Answer the following question using only the provided documentation context. 
+
+        const cleanResponse = parts[0].trim();
+        const sourcesText = parts[1].trim();
+
+        // Extract sources from the text
+        const sources: Source[] = sourcesText
+            .split('\n')
+            .filter(line => line.trim().length > 0 && line.includes('.json')) // Only process non-empty lines containing .json
+            .map(line => ({
+                title: line.trim().split('/').pop()?.replace('.json', '') || '', // Get the filename without extension
+                url: line.trim()
+            }));
+
+        return { cleanResponse, sources };
+    };
+
+    const handleSearch = async (e: React.FormEvent) => {
+        e.preventDefault()
+        setIsLoading(true)
+        setError(null)
+        setSources([])
+        
+        const startTime = performance.now()
+        
+        try {
+            // Generate embedding for the query
+            const queryEmbedding = await handleGenerateEmbedding(query);
+            // console.log("Query embedding:", queryEmbedding)
+            // Get database worker
+            const worker = await getDbWorker();
+
+            // Get all documents
+            const allDocs = await worker.db.query(`
+                SELECT path, content, embedding
+                FROM documents
+                WHERE embedding IS NOT NULL
+            `);
+
+            // Calculate similarity scores and filter results
+            const similarityThreshold = 0.5;
+            const scoredDocs = allDocs
+                .map((doc: any) => {
+                    // Clean the embedding string and parse it
+                    const cleanEmbeddingStr = doc.embedding.replace(/[\[\]]/g, ''); // Remove square brackets
+                    const embeddingArray = cleanEmbeddingStr
+                        .split(',')
+                        .map((val: string) => {
+                            const parsed = parseFloat(val.trim());
+                            if (isNaN(parsed)) {
+                                console.error(`Invalid embedding value found: "${val}"`);
+                            }
+                            return parsed;
+                        });
+                    
+                    return {
+                        ...doc,
+                        similarity_score: cosineSimilarity(queryEmbedding, embeddingArray)
+                    };
+                })
+                .filter((doc: any) => doc.similarity_score > similarityThreshold)
+                .sort((a: any, b: any) => b.similarity_score - a.similarity_score)
+                .slice(0, 5);
+
+            console.log("RAG top 5 results:", scoredDocs);
+
+            // If no relevant documents found, return early
+            if (scoredDocs.length === 0) {
+                setAiResponse("I cannot answer this question from the given documentation. The available content doesn't seem relevant enough to provide a accurate answer.");
+                setIsLoading(false);
+                return;
+            }
+
+            setLoaderText('Loading the AI model ...')
+
+            // Combine relevant documents into context
+            const docsContext = scoredDocs
+                .map((doc: any) => `
+                    Source: ${doc.path}
+                    --- Content ---
+                    ${doc.content}
+                    --- End of Content ---
+                `)
+                .join('\n');
+
+            const engine = await CreateMLCEngine(
+                "Llama-3.2-1B-Instruct-q4f16_1-MLC",
+                { initProgressCallback: (progress: any) => {
+                    console.log(progress)
+                    setLoaderText(`Loading the AI model ${Math.round(progress.progress * 100)}% ...`)
+                } },
+                {
+                    context_window_size: 20000,
+                }
+            );
+
+
+
+            const engineLoadTime = performance.now() // Track engine load time
+            console.log(`Time taken for engine initialization: ${(engineLoadTime - startTime) / 1000}s`)
+            setLoaderText('Processing information and generating AI response ...')
+            const messages = [
+              {
+                  role: "system",
+                  content: `You are a technical documentation assistant for AkiraDocs. Your purpose is to:
+1. Provide accurate, helpful answers using ONLY the provided documentation
+2. Stay positive and factual based on the documentation provided.`
+              },
+              {
+                  role: "user",
+                  content: `
+                  Please provide a helpful answer which is short and concise to the following question using only the provided documentation.
+
           Question: ${query}
+          
+          Answer the question using only the provided documentation. 
+                    
+          Do not make assumptions or add information not in the documentation.
+          
+          If relevant, include short code snippets. Only add code snippets if it is helpful to the question.
+
+          Dont add any notes or comments to the answer.
 
-          Requirements for your response:
-          1. If the answer isn't clearly supported by the documentation, say "I don't have enough information to answer this question accurately."
-          2. Don't make assumptions or provide information not found in the documentation
-          3. If relevant, include short code snippets to illustrate your answer.
-          4. Only answer questions related to the Documentaion Context.
-          5. Try to be concise and to the point.
+          Make sure the question is answered properly avoiding unnecessary information.
+
+          Ensure the final output is in markdown format. Make sure it pretty and clean.
+          
+          Sources (if used):
+          - <title> (<path>)
           
-          After your answer, if you used any sources from the documentation, list them in this format:
-          -------------
-          Sources:
-          - <title> (<path>)` 
+          Here is the documentation, only answer based on this information: 
+          ${docsContext}
+          `
+              }
+          ];
+
+            // console.log("Messages:", messages)
+
+            const chunks = await engine.chat.completions.create({ 
+                messages: messages as ChatCompletionMessageParam[],
+                stream: true,
+                stream_options: { include_usage: true },
+                max_tokens: 300,
+                temperature: 0.3,
+                top_p: 0.95,
+                frequency_penalty: 0.5,
+                presence_penalty: 0.5,
+            });
+
+            let aiContent = "";
+            for await (const chunk of chunks) {
+                const newContent = chunk.choices[0]?.delta.content || "";
+                aiContent += newContent;
+                
+                // Process partial content for streaming
+                const { cleanResponse } = extractSources(aiContent);
+                setAiResponse(cleanResponse);
+            }
+
+            // Only extract and set sources after streaming is complete
+            const { sources } = extractSources(aiContent);
+            setSources(sources);
+
+            const endTime = performance.now() // Track total time
+            console.log(`Total time taken for AI search: ${(endTime - startTime) / 1000}s`)
+
+        } catch (error) {
+            console.error('Search error:', error);
+            setError(error instanceof Error ? error.message : 'An error occurred');
+        } finally {
+            setIsLoading(false);
         }
-      ];
-
-      console.log("messages", messages)
-
-      const chunks = await engine.chat.completions.create({ 
-        messages: messages as ChatCompletionMessageParam[],
-        stream: true,
-        stream_options: { include_usage: true }
-      });
-
-      let aiContent = "";
-      for await (const chunk of chunks) {
-        const newContent = chunk.choices[0]?.delta.content || "";
-        aiContent += newContent;
-        // Update the response in real-time
-        setAiResponse(aiContent);
-      }
-      
-      // Extract sources after the full response is received
-      const { cleanResponse, sources } = extractSources(aiContent);
-      setAiResponse(cleanResponse);
-      setSources(sources);
-      
-    } catch (error) {
-      console.error('Error during AI search:', error);
-      
-      // Check for WebGPU error
-      if (error instanceof Error && error.name === 'WebGPUNotAvailableError') {
-        setError('WebGPU is not yet supported on this browser. Please try using another browser.');
-      } else {
-        setError('Sorry, there was an error processing your request.');
-      }
-      setAiResponse('');
-    } finally {
-      setIsLoading(false)
     }
-  }
-
-  const handleBack = () => {
-    setAiResponse('')
-  }
-
-  return (
-    <div className="flex flex-col min-h-screen">
-      <Header {...headerConfig} currentLocale={`en`} currentType={`aiSearch`}/>
-    <div className="min-h-screen py-12 px-4 sm:px-6 lg:px-8">
-      
-      <div className="max-w-4xl mx-auto">
-        <SearchHeader 
-          logo={searchConfig.logo}
-          title={searchConfig.title}
-          description={searchConfig.description}
-        />
-        <div className="flex flex-col sm:flex-row space-y-4 sm:space-y-0 sm:space-x-4 justify-center items-center mb-12">
-          <SearchBar
-            query={query}
-            onQueryChange={setQuery}
-            onSubmit={handleSearch}
-          />
-          <LegacyDocsToggle/>
-        </div>
 
-        <AnimatePresence>
-          {isLoading ? (
-            <div className="flex flex-col justify-center items-center space-y-4 py-12">
-              <AILoader />
-              <p className="text-muted-foreground text-sm animate-pulse">
-                Loading AI response...
-              </p>
-            </div>
-          ) : error ? (
-            <div className="text-center p-4 rounded-lg bg-red-50 text-red-800">
-              <p className="text-lg font-medium mb-2">Error</p>
-              <p>{error}</p>
+    const handleBack = () => {
+        setAiResponse('')
+    }
+
+    return (
+        <div className="flex flex-col min-h-screen">
+            <Header {...headerConfig} currentLocale={`en`} currentType={`aiSearch`}/>
+            <div className="min-h-screen py-12 px-4 sm:px-6 lg:px-8">
+                
+                <div className="max-w-4xl mx-auto">
+                    <SearchHeader 
+                        logo={searchConfig.logo}
+                        title={searchConfig.title}
+                        description={searchConfig.description}
+                    />
+                    <div className="flex flex-col sm:flex-row space-y-4 sm:space-y-0 sm:space-x-4 justify-center items-center mb-12">
+                        <SearchBar
+                            query={query}
+                            onQueryChange={setQuery}
+                            onSubmit={handleSearch}
+                        />
+                        <LegacyDocsToggle/>
+                    </div>
+
+                    <AnimatePresence>
+                        {isLoading ? (
+                            <div className="flex flex-col justify-center items-center space-y-4 py-12">
+                                <AILoader />
+                                <p className="text-muted-foreground text-sm animate-pulse">
+                                    {loaderText}
+                                </p>
+                            </div>
+                        ) : error ? (
+                            <div className="text-center p-4 rounded-lg bg-red-50 text-red-800">
+                                <p className="text-lg font-medium mb-2">Error</p>
+                                <p>{error}</p>
+                            </div>
+                        ) : aiResponse ? (
+                            <AIResponse
+                                response={aiResponse}
+                                sources={sources}
+                                onBack={handleBack}
+                            />
+                        ) : recommendedArticles && (
+                            <RecommendedArticles articles={recommendedArticles} />
+                        )}
+                    </AnimatePresence>
+                </div>
             </div>
-          ) : aiResponse ? (
-            <AIResponse
-              response={aiResponse}
-              sources={sources}
-              onBack={handleBack}
-            />
-          ) : recommendedArticles && (
-            <RecommendedArticles articles={recommendedArticles} />
-          )}
-        </AnimatePresence>
-      </div>
-    </div>
-    </div>
-  )
+        </div>
+    )
 }
diff --git a/docs/src/components/aiSearch/AIResponse.tsx b/docs/src/components/aiSearch/AIResponse.tsx
index ca46310..e78f31f 100644
--- a/docs/src/components/aiSearch/AIResponse.tsx
+++ b/docs/src/components/aiSearch/AIResponse.tsx
@@ -8,6 +8,7 @@ import { AIResponseActions } from "./AIResponseActions"
 import { AIResponseSources } from "./AIResponseSources"
 import ReactMarkdown from 'react-markdown'
 import { Source } from "@/types/Source"
+import { memo } from 'react'
 
 interface AIResponseProps {
   response: string
@@ -15,6 +16,20 @@ interface AIResponseProps {
   onBack: () => void
 }
 
+// Memoize the markdown component to prevent unnecessary re-renders
+const MemoizedMarkdown = memo(({ content }: { content: string }) => (
+  <ReactMarkdown
+    components={{
+      pre({ children }) {
+        return <div className="not-prose">{children}</div>
+      }
+    }}
+  >
+    {content}
+  </ReactMarkdown>
+))
+MemoizedMarkdown.displayName = 'MemoizedMarkdown'
+
 export function AIResponse({ response, sources, onBack }: AIResponseProps) {
   return (
     <motion.div
@@ -35,8 +50,21 @@ export function AIResponse({ response, sources, onBack }: AIResponseProps) {
           </Button>
         </CardHeader>
         <CardContent className="pt-6">
-        <div className="prose dark:prose-invert max-w-none">
-            <ReactMarkdown>{response}</ReactMarkdown>
+          <div className="prose dark:prose-invert max-w-none
+            prose-headings:font-semibold
+            prose-h1:text-xl prose-h1:mt-8 prose-h1:mb-4
+            prose-h2:text-lg prose-h2:mt-6 prose-h2:mb-3
+            prose-p:my-4 prose-p:leading-relaxed
+            prose-ul:space-y-2 prose-ul:list-disc prose-ul:pl-6
+            prose-ol:space-y-2 prose-ol:list-decimal prose-ol:pl-6
+            prose-li:pl-2
+            [&_pre]:bg-secondary [&_pre]:p-4 [&_pre]:rounded-lg [&_pre]:my-4
+            [&_code:not(pre_code)]:bg-secondary [&_code:not(pre_code)]:px-1.5 [&_code:not(pre_code)]:py-0.5 [&_code:not(pre_code)]:rounded-sm
+            [&_pre_code]:bg-transparent [&_pre_code]:p-0 [&_pre_code]:rounded-none
+            [&>*:first-child]:mt-0
+            [&>p>strong]:block [&>p>strong]:mt-8 [&>p>strong]:mb-4 [&>p>strong]:text-lg
+            [&>p:has(>strong:only-child)]:m-0">
+            <MemoizedMarkdown content={response} />
           </div>
         </CardContent>
         <CardFooter className="flex flex-col items-start space-y-4">
diff --git a/docs/src/components/aiSearch/AIResponseSources.tsx b/docs/src/components/aiSearch/AIResponseSources.tsx
index 5b160ed..d146d15 100644
--- a/docs/src/components/aiSearch/AIResponseSources.tsx
+++ b/docs/src/components/aiSearch/AIResponseSources.tsx
@@ -12,7 +12,7 @@ export function AIResponseSources({ sources }: AIResponseSourcesProps) {
                 {sources.map((source, index) => (
                     <li key={index}>
                         <a
-                            href={source.url}
+                            href={`${window.location.origin}/en/${source.url.replace('%20', '')}?utm_source=akiradocs`}
                             target="_blank"
                             rel="noopener noreferrer"
                             className="text-sm text-indigo-600 dark:text-indigo-400 hover:underline"
diff --git a/docs/src/lib/aisearch/dbWorker.ts b/docs/src/lib/aisearch/dbWorker.ts
new file mode 100644
index 0000000..9e6a3b2
--- /dev/null
+++ b/docs/src/lib/aisearch/dbWorker.ts
@@ -0,0 +1,35 @@
+import { createDbWorker } from "sql.js-httpvfs";
+import { SplitFileConfig } from "sql.js-httpvfs/dist/sqlite.worker";
+
+let dbInstance: any = null;
+
+export async function getDbWorker() {
+    if (dbInstance) return dbInstance;
+
+    const workerUrl = new URL(
+        "sql.js-httpvfs/dist/sqlite.worker.js",
+        import.meta.url
+    );
+    const wasmUrl = new URL(
+        "sql.js-httpvfs/dist/sql-wasm.wasm",
+        import.meta.url
+    );
+
+    const config: SplitFileConfig = {
+        from: "inline" as const,
+        config: {
+            serverMode: "full",
+            requestChunkSize: 4096,
+            url: "/context/docs.db"
+        }
+    };
+
+    const worker = await createDbWorker(
+        [config],
+        workerUrl.toString(),
+        wasmUrl.toString()
+    );
+
+    dbInstance = worker;
+    return dbInstance;
+}
\ No newline at end of file
diff --git a/docs/src/lib/aisearch/embeddings.ts b/docs/src/lib/aisearch/embeddings.ts
new file mode 100644
index 0000000..f93f006
--- /dev/null
+++ b/docs/src/lib/aisearch/embeddings.ts
@@ -0,0 +1,34 @@
+export interface ProgressCallback {
+    file: string;
+    progress: number;
+    loaded: number;
+    total: number;
+}
+
+export async function generateEmbedding(
+    text: string,
+    onProgress?: (progress: ProgressCallback) => void
+): Promise<number[]> {
+    return new Promise((resolve, reject) => {
+        const worker = new Worker(
+            new URL('./embeddings.worker.ts', import.meta.url),
+            { type: 'module' }
+        );
+
+        worker.addEventListener('message', (event) => {
+            if (event.data.status === 'progress' && onProgress) {
+                onProgress(event.data.progress);
+            } else if (event.data.status === 'complete') {
+                resolve(event.data.output);
+                worker.terminate();
+            }
+        });
+
+        worker.addEventListener('error', (error) => {
+            reject(error);
+            worker.terminate();
+        });
+
+        worker.postMessage({ text });
+    });
+} 
\ No newline at end of file
diff --git a/docs/src/lib/aisearch/embeddings.worker.ts b/docs/src/lib/aisearch/embeddings.worker.ts
new file mode 100644
index 0000000..52b26d6
--- /dev/null
+++ b/docs/src/lib/aisearch/embeddings.worker.ts
@@ -0,0 +1,30 @@
+import { pipeline, ProgressCallback, type PipelineType } from "@huggingface/transformers";
+
+class EmbeddingPipelineSingleton {
+    static task: PipelineType = 'feature-extraction';
+    static model = 'sauravpanda/gte-small-onnx';
+    static instance: Promise<any> | null = null;
+
+    static async getInstance(progress_callback: ProgressCallback | null = null) {
+        this.instance ??= pipeline(this.task, this.model, { 
+            progress_callback: progress_callback ?? undefined
+        });
+        return this.instance;
+    }
+}
+
+self.addEventListener('message', async (event) => {
+    const embedder = await EmbeddingPipelineSingleton.getInstance(x => {
+        self.postMessage({ status: 'progress', progress: x });
+    });
+
+    const output = await embedder(event.data.text, {
+        pooling: 'mean',
+        normalize: true
+    });
+
+    self.postMessage({
+        status: 'complete',
+        output: Array.from(output.data),
+    });
+}); 
\ No newline at end of file
diff --git a/packages/akiradocs/compiled/manifest.json b/packages/akiradocs/compiled/manifest.json
index 9b82fb7..d96ba5d 100644
--- a/packages/akiradocs/compiled/manifest.json
+++ b/packages/akiradocs/compiled/manifest.json
@@ -37,6 +37,7 @@
     "fr/articles/welcome.json",
     "fr/docs/_meta.json",
     "fr/docs/getting-started/quickstart.json",
-    "fr/docs/introduction.json"
+    "fr/docs/introduction.json",
+    "manifest.json"
   ]
 }
\ No newline at end of file
diff --git a/packages/akiradocs/next.config.mjs b/packages/akiradocs/next.config.mjs
index b73b4e6..798fa4a 100644
--- a/packages/akiradocs/next.config.mjs
+++ b/packages/akiradocs/next.config.mjs
@@ -1,14 +1,30 @@
 /** @type {import('next').NextConfig} */
 // import MillionLint from "@million/lint";
+import path from 'path';
+import { fileURLToPath } from 'url';
+
+const __dirname = path.dirname(fileURLToPath(import.meta.url));
 
 const nextConfig = {
     webpack: (config) => {
       config.module.rules.push({
         test: /\.json$/,
         type: 'json',
-      })
+      });
+      
+      config.resolve.alias = {
+        ...config.resolve.alias,
+        "sharp$": false,
+        "onnxruntime-node$": false,
+      }
+
+      config.resolve.alias['@huggingface/transformers'] = path.resolve(__dirname, 'node_modules/@huggingface/transformers');
+
       return config
     },
+    experimental: {
+      esmExternals: true // Enable ES modules
+    },
     // i18n: {
     //   locales: ['en', 'es', 'fr', 'de'],
     //   defaultLocale: 'en',
diff --git a/packages/akiradocs/package-lock.json b/packages/akiradocs/package-lock.json
index f48f35a..cd20ac1 100644
--- a/packages/akiradocs/package-lock.json
+++ b/packages/akiradocs/package-lock.json
@@ -14,6 +14,7 @@
         "@dnd-kit/utilities": "^3.2.2",
         "@google/generative-ai": "^0.2.1",
         "@heroicons/react": "^2.1.5",
+        "@huggingface/transformers": "^3.2.3",
         "@mdx-js/loader": "^3.1.0",
         "@mdx-js/react": "^3.1.0",
         "@million/lint": "^1.0.12",
@@ -36,7 +37,9 @@
         "@radix-ui/react-toggle": "^1.1.0",
         "@radix-ui/react-toggle-group": "^1.1.0",
         "@radix-ui/react-tooltip": "^1.1.3",
+        "@xenova/transformers": "^2.17.2",
         "ai": "^4.0.2",
+        "better-sqlite3": "^11.7.0",
         "class-variance-authority": "^0.7.0",
         "clsx": "^2.1.1",
         "cross-spawn": "^7.0.6",
@@ -56,7 +59,9 @@
         "react-error-boundary": "^4.1.2",
         "react-markdown": "^9.0.1",
         "react-syntax-highlighter": "^15.6.1",
+        "sharp": "^0.33.5",
         "sonner": "^1.7.0",
+        "sql.js-httpvfs": "^0.8.12",
         "styled-components": "^6.1.13",
         "tailwind-merge": "^2.5.4",
         "tailwindcss-animate": "^1.0.7"
@@ -529,7 +534,6 @@
     },
     "node_modules/@clack/prompts/node_modules/is-unicode-supported": {
       "version": "1.3.0",
-      "extraneous": true,
       "inBundle": true,
       "license": "MIT",
       "engines": {
@@ -610,6 +614,16 @@
         "react": ">=16.8.0"
       }
     },
+    "node_modules/@emnapi/runtime": {
+      "version": "1.3.1",
+      "resolved": "https://registry.npmjs.org/@emnapi/runtime/-/runtime-1.3.1.tgz",
+      "integrity": "sha512-kEBmG8KyqtxJZv+ygbEim+KCGtIq1fC22Ms3S4ziXmYKm8uyoLX0MHONVKwp+9opg390VaKRNt4a7A9NwmpNhw==",
+      "license": "MIT",
+      "optional": true,
+      "dependencies": {
+        "tslib": "^2.4.0"
+      }
+    },
     "node_modules/@emotion/is-prop-valid": {
       "version": "1.2.2",
       "resolved": "https://registry.npmjs.org/@emotion/is-prop-valid/-/is-prop-valid-1.2.2.tgz",
@@ -1118,6 +1132,27 @@
         "hono": "^4"
       }
     },
+    "node_modules/@huggingface/jinja": {
+      "version": "0.3.2",
+      "resolved": "https://registry.npmjs.org/@huggingface/jinja/-/jinja-0.3.2.tgz",
+      "integrity": "sha512-F2FvuIc+w1blGsaqJI/OErRbWH6bVJDCBI8Rm5D86yZ2wlwrGERsfIaru7XUv9eYC3DMP3ixDRRtF0h6d8AZcQ==",
+      "license": "MIT",
+      "engines": {
+        "node": ">=18"
+      }
+    },
+    "node_modules/@huggingface/transformers": {
+      "version": "3.2.3",
+      "resolved": "https://registry.npmjs.org/@huggingface/transformers/-/transformers-3.2.3.tgz",
+      "integrity": "sha512-o7QZphrCH3a3m0kF/MaSNv3DMDZCpTifdZ9k4Lwl2n9QhY8JIGOOtZDVa+Wv2cqKU6iJm1SiCqDdZpo8H20c8g==",
+      "license": "Apache-2.0",
+      "dependencies": {
+        "@huggingface/jinja": "^0.3.2",
+        "onnxruntime-node": "1.20.1",
+        "onnxruntime-web": "1.21.0-dev.20241205-d27fecd3d3",
+        "sharp": "^0.33.5"
+      }
+    },
     "node_modules/@humanwhocodes/config-array": {
       "version": "0.13.0",
       "resolved": "https://registry.npmjs.org/@humanwhocodes/config-array/-/config-array-0.13.0.tgz",
@@ -1174,6 +1209,28 @@
         "@img/sharp-libvips-darwin-arm64": "1.0.4"
       }
     },
+    "node_modules/@img/sharp-darwin-x64": {
+      "version": "0.33.5",
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@@ -10145,11 +11292,55 @@
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@@ -10235,6 +11435,29 @@
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@@ -10752,6 +11975,66 @@
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diff --git a/packages/akiradocs/package.json b/packages/akiradocs/package.json
index a391fc2..6907677 100644
--- a/packages/akiradocs/package.json
+++ b/packages/akiradocs/package.json
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new file mode 100644
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+++ b/packages/akiradocs/public/sql.js-httpvfs/sqlite.worker.js
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t?function(e,t){return q.fill(0,e,e+t),e}(t,e):0}var ef,ed={ops_table:null,mount:function(e){return ed.createNode(null,"/",16895,0)},createNode:function(e,t,r,n){if(eh.isBlkdev(r)||eh.isFIFO(r))throw new eh.ErrnoError(63);ed.ops_table||(ed.ops_table={dir:{node:{getattr:ed.node_ops.getattr,setattr:ed.node_ops.setattr,lookup:ed.node_ops.lookup,mknod:ed.node_ops.mknod,rename:ed.node_ops.rename,unlink:ed.node_ops.unlink,rmdir:ed.node_ops.rmdir,readdir:ed.node_ops.readdir,symlink:ed.node_ops.symlink},stream:{llseek:ed.stream_ops.llseek}},file:{node:{getattr:ed.node_ops.getattr,setattr:ed.node_ops.setattr},stream:{llseek:ed.stream_ops.llseek,read:ed.stream_ops.read,write:ed.stream_ops.write,allocate:ed.stream_ops.allocate,mmap:ed.stream_ops.mmap,msync:ed.stream_ops.msync}},link:{node:{getattr:ed.node_ops.getattr,setattr:ed.node_ops.setattr,readlink:ed.node_ops.readlink},stream:{}},chrdev:{node:{getattr:ed.node_ops.getattr,setattr:ed.node_ops.setattr},stream:eh.chrdev_stream_ops}});var o=eh.createNode(e,t,r,n);return eh.isDir(o.mode)?(o.node_ops=ed.ops_table.dir.node,o.stream_ops=ed.ops_table.dir.stream,o.contents={}):eh.isFile(o.mode)?(o.node_ops=ed.ops_table.file.node,o.stream_ops=ed.ops_table.file.stream,o.usedBytes=0,o.contents=null):eh.isLink(o.mode)?(o.node_ops=ed.ops_table.link.node,o.stream_ops=ed.ops_table.link.stream):eh.isChrdev(o.mode)&&(o.node_ops=ed.ops_table.chrdev.node,o.stream_ops=ed.ops_table.chrdev.stream),o.timestamp=Date.now(),e&&(e.contents[t]=o,e.timestamp=o.timestamp),o},getFileDataAsTypedArray:function(e){return e.contents?e.contents.subarray?e.contents.subarray(0,e.usedBytes):new Uint8Array(e.contents):new Uint8Array(0)},expandFileStorage:function(e,t){var r=e.contents?e.contents.length:0;if(!(r>=t)){t=Math.max(t,r*(r<1048576?2:1.125)>>>0),0!=r&&(t=Math.max(t,256));var n=e.contents;e.contents=new 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n;try{n=eh.lookupNode(t,r)}catch(e){}if(n)for(var o in n.contents)throw new eh.ErrnoError(55)}delete e.parent.contents[e.name],e.parent.timestamp=Date.now(),e.name=r,t.contents[r]=e,t.timestamp=e.parent.timestamp,e.parent=t},unlink:function(e,t){delete e.contents[t],e.timestamp=Date.now()},rmdir:function(e,t){var r=eh.lookupNode(e,t);for(var n in r.contents)throw new eh.ErrnoError(55);delete e.contents[t],e.timestamp=Date.now()},readdir:function(e){var t=[".",".."];for(var r in e.contents)e.contents.hasOwnProperty(r)&&t.push(r);return t},symlink:function(e,t,r){var n=ed.createNode(e,t,41471,0);return n.link=r,n},readlink:function(e){if(!eh.isLink(e.mode))throw new eh.ErrnoError(28);return e.link}},stream_ops:{read:function(e,t,r,n,o){var i=e.node.contents;if(o>=e.node.usedBytes)return 0;var s=Math.min(e.node.usedBytes-o,n);if(s>8&&i.subarray)t.set(i.subarray(o,o+s),r);else for(var a=0;a<s;a++)t[r+a]=i[o+a];return s},write:function(e,t,r,n,o,i){if(t.buffer===x.buffer&&(i=!1),!n)return 0;var s=e.node;if(s.timestamp=Date.now(),t.subarray&&(!s.contents||s.contents.subarray)){if(i)return s.contents=t.subarray(r,r+n),s.usedBytes=n,n;if(0===s.usedBytes&&0===o)return s.contents=t.slice(r,r+n),s.usedBytes=n,n;if(o+n<=s.usedBytes)return s.contents.set(t.subarray(r,r+n),o),n}if(ed.expandFileStorage(s,o+n),s.contents.subarray&&t.subarray)s.contents.set(t.subarray(r,r+n),o);else for(var a=0;a<n;a++)s.contents[o+a]=t[r+a];return s.usedBytes=Math.max(s.usedBytes,o+n),n},llseek:function(e,t,r){var n=t;if(1===r?n+=e.position:2===r&&eh.isFile(e.node.mode)&&(n+=e.node.usedBytes),n<0)throw new eh.ErrnoError(28);return n},allocate:function(e,t,r){ed.expandFileStorage(e.node,t+r),e.node.usedBytes=Math.max(e.node.usedBytes,t+r)},mmap:function(e,t,r,n,o){if(!eh.isFile(e.node.mode))throw new eh.ErrnoError(43);var i,s,a=e.node.contents;if(2&o||a.buffer!==S){if((r>0||r+t<a.length)&&(a=a.subarray?a.subarray(r,r+t):Array.prototype.slice.call(a,r,r+t)),s=!0,!(i=ec(t)))throw new eh.ErrnoError(48);x.set(a,i)}else s=!1,i=a.byteOffset;return{ptr:i,allocated:s}},msync:function(e,t,r,n,o){if(!eh.isFile(e.node.mode))throw new eh.ErrnoError(43);return 2&o||ed.stream_ops.write(e,t,0,n,r,!1),0}}},eh={root:null,mounts:[],devices:{},streams:[],nextInode:1,nameTable:null,currentPath:"/",initialized:!1,ignorePermissions:!0,ErrnoError:null,genericErrors:{},filesystems:null,syncFSRequests:0,lookupPath:(e,t={})=>{if(!(e=ea.resolve(eh.cwd(),e)))return{path:"",node:null};if((t=Object.assign({follow_mount:!0,recurse_count:0},t)).recurse_count>8)throw new eh.ErrnoError(32);for(var r=es.normalizeArray(e.split("/").filter(e=>!!e),!1),n=eh.root,o="/",i=0;i<r.length;i++){var s=i===r.length-1;if(s&&t.parent)break;if(n=eh.lookupNode(n,r[i]),o=es.join2(o,r[i]),eh.isMountpoint(n)&&(!s||s&&t.follow_mount)&&(n=n.mounted.root),!s||t.follow)for(var a=0;eh.isLink(n.mode);){var u=eh.readlink(o);if(o=ea.resolve(es.dirname(o),u),n=eh.lookupPath(o,{recurse_count:t.recurse_count+1}).node,a++>40)throw new eh.ErrnoError(32)}}return{path:o,node:n}},getPath:e=>{for(var t;;){if(eh.isRoot(e)){var r=e.mount.mountpoint;return t?"/"!==r[r.length-1]?r+"/"+t:r+t:r}t=t?e.name+"/"+t:e.name,e=e.parent}},hashName:(e,t)=>{for(var r=0,n=0;n<t.length;n++)r=(r<<5)-r+t.charCodeAt(n)|0;return(e+r>>>0)%eh.nameTable.length},hashAddNode:e=>{var t=eh.hashName(e.parent.id,e.name);e.name_next=eh.nameTable[t],eh.nameTable[t]=e},hashRemoveNode:e=>{var t=eh.hashName(e.parent.id,e.name);if(eh.nameTable[t]===e)eh.nameTable[t]=e.name_next;else for(var r=eh.nameTable[t];r;){if(r.name_next===e){r.name_next=e.name_next;break}r=r.name_next}},lookupNode:(e,t)=>{var r=eh.mayLookup(e);if(r)throw new eh.ErrnoError(r,e);for(var n=eh.hashName(e.id,t),o=eh.nameTable[n];o;o=o.name_next){var i=o.name;if(o.parent.id===e.id&&i===t)return o}return eh.lookup(e,t)},createNode:(e,t,r,n)=>{var o=new eh.FSNode(e,t,r,n);return eh.hashAddNode(o),o},destroyNode:e=>{eh.hashRemoveNode(e)},isRoot:e=>e===e.parent,isMountpoint:e=>!!e.mounted,isFile:e=>32768==(61440&e),isDir:e=>16384==(61440&e),isLink:e=>40960==(61440&e),isChrdev:e=>8192==(61440&e),isBlkdev:e=>24576==(61440&e),isFIFO:e=>4096==(61440&e),isSocket:e=>49152==(49152&e),flagModes:{r:0,"r+":2,w:577,"w+":578,a:1089,"a+":1090},modeStringToFlags:e=>{var t=eh.flagModes[e];if(void 0===t)throw Error("Unknown file open mode: "+e);return t},flagsToPermissionString:e=>{var t=["r","w","rw"][3&e];return 512&e&&(t+="w"),t},nodePermissions:(e,t)=>eh.ignorePermissions||(!t.includes("r")||292&e.mode)&&(!t.includes("w")||146&e.mode)&&(!t.includes("x")||73&e.mode)?0:2,mayLookup:e=>eh.nodePermissions(e,"x")||(e.node_ops.lookup?0:2),mayCreate:(e,t)=>{try{return eh.lookupNode(e,t),20}catch(e){}return eh.nodePermissions(e,"wx")},mayDelete:(e,t,r)=>{try{n=eh.lookupNode(e,t)}catch(e){return e.errno}var n,o=eh.nodePermissions(e,"wx");if(o)return o;if(r){if(!eh.isDir(n.mode))return 54;if(eh.isRoot(n)||eh.getPath(n)===eh.cwd())return 10}else if(eh.isDir(n.mode))return 31;return 0},mayOpen:(e,t)=>e?eh.isLink(e.mode)?32:eh.isDir(e.mode)&&("r"!==eh.flagsToPermissionString(t)||512&t)?31:eh.nodePermissions(e,eh.flagsToPermissionString(t)):44,MAX_OPEN_FDS:4096,nextfd:(e=0,t=eh.MAX_OPEN_FDS)=>{for(var r=e;r<=t;r++)if(!eh.streams[r])return r;throw new eh.ErrnoError(33)},getStream:e=>eh.streams[e],createStream:(e,t,r)=>{eh.FSStream||(eh.FSStream=function(){this.shared={}},eh.FSStream.prototype={},Object.defineProperties(eh.FSStream.prototype,{object:{get:function(){return this.node},set:function(e){this.node=e}},isRead:{get:function(){return 1!=(2097155&this.flags)}},isWrite:{get:function(){return 0!=(2097155&this.flags)}},isAppend:{get:function(){return 1024&this.flags}},flags:{get:function(){return this.shared.flags},set:function(e){this.shared.flags=e}},position:{get:function(){return this.shared.position},set:function(e){this.shared.position=e}}})),e=Object.assign(new eh.FSStream,e);var n=eh.nextfd(t,r);return e.fd=n,eh.streams[n]=e,e},closeStream:e=>{eh.streams[e]=null},chrdev_stream_ops:{open:e=>{var t=eh.getDevice(e.node.rdev);e.stream_ops=t.stream_ops,e.stream_ops.open&&e.stream_ops.open(e)},llseek:()=>{throw new eh.ErrnoError(70)}},major:e=>e>>8,minor:e=>255&e,makedev:(e,t)=>e<<8|t,registerDevice:(e,t)=>{eh.devices[e]={stream_ops:t}},getDevice:e=>eh.devices[e],getMounts:e=>{for(var t=[],r=[e];r.length;){var n=r.pop();t.push(n),r.push.apply(r,n.mounts)}return t},syncfs:(e,t)=>{"function"==typeof e&&(t=e,e=!1),eh.syncFSRequests++,eh.syncFSRequests>1&&E("warning: "+eh.syncFSRequests+" FS.syncfs operations in flight at once, probably just doing extra work");var r=eh.getMounts(eh.root.mount),n=0;function o(e){return eh.syncFSRequests--,t(e)}function i(e){if(e)return i.errored?void 0:(i.errored=!0,o(e));++n>=r.length&&o(null)}r.forEach(t=>{if(!t.type.syncfs)return i(null);t.type.syncfs(t,e,i)})},mount:(e,t,r)=>{var n,o="/"===r,i=!r;if(o&&eh.root)throw new eh.ErrnoError(10);if(!o&&!i){var s=eh.lookupPath(r,{follow_mount:!1});if(r=s.path,n=s.node,eh.isMountpoint(n))throw new eh.ErrnoError(10);if(!eh.isDir(n.mode))throw new eh.ErrnoError(54)}var a={type:e,opts:t,mountpoint:r,mounts:[]},u=e.mount(a);return u.mount=a,a.root=u,o?eh.root=u:n&&(n.mounted=a,n.mount&&n.mount.mounts.push(a)),u},unmount:e=>{var t=eh.lookupPath(e,{follow_mount:!1});if(!eh.isMountpoint(t.node))throw new eh.ErrnoError(28);var r=t.node,n=r.mounted,o=eh.getMounts(n);Object.keys(eh.nameTable).forEach(e=>{for(var t=eh.nameTable[e];t;){var r=t.name_next;o.includes(t.mount)&&eh.destroyNode(t),t=r}}),r.mounted=null;var i=r.mount.mounts.indexOf(n);r.mount.mounts.splice(i,1)},lookup:(e,t)=>e.node_ops.lookup(e,t),mknod:(e,t,r)=>{var n=eh.lookupPath(e,{parent:!0}).node,o=es.basename(e);if(!o||"."===o||".."===o)throw new eh.ErrnoError(28);var i=eh.mayCreate(n,o);if(i)throw new eh.ErrnoError(i);if(!n.node_ops.mknod)throw new eh.ErrnoError(63);return n.node_ops.mknod(n,o,t,r)},create:(e,t)=>(t=(void 0!==t?t:438)&4095|32768,eh.mknod(e,t,0)),mkdir:(e,t)=>(t=(void 0!==t?t:511)&1023|16384,eh.mknod(e,t,0)),mkdirTree:(e,t)=>{for(var r=e.split("/"),n="",o=0;o<r.length;++o)if(r[o]){n+="/"+r[o];try{eh.mkdir(n,t)}catch(e){if(20!=e.errno)throw e}}},mkdev:(e,t,r)=>(void 0===r&&(r=t,t=438),t|=8192,eh.mknod(e,t,r)),symlink:(e,t)=>{if(!ea.resolve(e))throw new eh.ErrnoError(44);var r=eh.lookupPath(t,{parent:!0}).node;if(!r)throw new eh.ErrnoError(44);var n=es.basename(t),o=eh.mayCreate(r,n);if(o)throw new eh.ErrnoError(o);if(!r.node_ops.symlink)throw new eh.ErrnoError(63);return r.node_ops.symlink(r,n,e)},rename:(e,t)=>{var r,n,o=es.dirname(e),i=es.dirname(t),s=es.basename(e),a=es.basename(t);if(r=eh.lookupPath(e,{parent:!0}).node,n=eh.lookupPath(t,{parent:!0}).node,!r||!n)throw new eh.ErrnoError(44);if(r.mount!==n.mount)throw new eh.ErrnoError(75);var u,l=eh.lookupNode(r,s),c=ea.relative(e,i);if("."!==c.charAt(0))throw new eh.ErrnoError(28);if("."!==(c=ea.relative(t,o)).charAt(0))throw new eh.ErrnoError(55);try{u=eh.lookupNode(n,a)}catch(e){}if(l!==u){var f=eh.isDir(l.mode),d=eh.mayDelete(r,s,f);if(d||(d=u?eh.mayDelete(n,a,f):eh.mayCreate(n,a)))throw new eh.ErrnoError(d);if(!r.node_ops.rename)throw new eh.ErrnoError(63);if(eh.isMountpoint(l)||u&&eh.isMountpoint(u))throw new eh.ErrnoError(10);if(n!==r&&(d=eh.nodePermissions(r,"w")))throw new eh.ErrnoError(d);eh.hashRemoveNode(l);try{r.node_ops.rename(l,n,a)}catch(e){throw e}finally{eh.hashAddNode(l)}}},rmdir:e=>{var t=eh.lookupPath(e,{parent:!0}).node,r=es.basename(e),n=eh.lookupNode(t,r),o=eh.mayDelete(t,r,!0);if(o)throw new eh.ErrnoError(o);if(!t.node_ops.rmdir)throw new eh.ErrnoError(63);if(eh.isMountpoint(n))throw new eh.ErrnoError(10);t.node_ops.rmdir(t,r),eh.destroyNode(n)},readdir:e=>{var t=eh.lookupPath(e,{follow:!0}).node;if(!t.node_ops.readdir)throw new eh.ErrnoError(54);return t.node_ops.readdir(t)},unlink:e=>{var t=eh.lookupPath(e,{parent:!0}).node;if(!t)throw new eh.ErrnoError(44);var r=es.basename(e),n=eh.lookupNode(t,r),o=eh.mayDelete(t,r,!1);if(o)throw new eh.ErrnoError(o);if(!t.node_ops.unlink)throw new eh.ErrnoError(63);if(eh.isMountpoint(n))throw new eh.ErrnoError(10);t.node_ops.unlink(t,r),eh.destroyNode(n)},readlink:e=>{var t=eh.lookupPath(e).node;if(!t)throw new eh.ErrnoError(44);if(!t.node_ops.readlink)throw new eh.ErrnoError(28);return ea.resolve(eh.getPath(t.parent),t.node_ops.readlink(t))},stat:(e,t)=>{var r=eh.lookupPath(e,{follow:!t}).node;if(!r)throw new eh.ErrnoError(44);if(!r.node_ops.getattr)throw new eh.ErrnoError(63);return r.node_ops.getattr(r)},lstat:e=>eh.stat(e,!0),chmod:(e,t,r)=>{var n;if(!(n="string"==typeof e?eh.lookupPath(e,{follow:!r}).node:e).node_ops.setattr)throw new 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Symbol&&Symbol.toStringTag&&Object.defineProperty(e,Symbol.toStringTag,{value:"Module"}),Object.defineProperty(e,"__esModule",{value:!0})},__webpack_require__.nmd=e=>(e.paths=[],e.children||(e.children=[]),e),__webpack_require__.p="";var __webpack_exports__=__webpack_require__(630);return __webpack_exports__})()});
\ No newline at end of file
diff --git a/packages/akiradocs/scripts/extract-docs-context.js b/packages/akiradocs/scripts/extract-docs-context.js
index 2bd7f4d..cdc252f 100644
--- a/packages/akiradocs/scripts/extract-docs-context.js
+++ b/packages/akiradocs/scripts/extract-docs-context.js
@@ -1,6 +1,33 @@
 const fs = require('fs/promises');
 const path = require('path');
 const { glob } = require('glob');
+const sqlite3 = require('better-sqlite3');
+
+class EmbeddingPipeline {
+  static task = 'feature-extraction';
+  static model = 'sauravpanda/gte-small-onnx';
+  static instance = null;
+
+  static async getInstance(progress_callback = null) {
+    if (this.instance === null) {
+      // Optionally set cache directory
+      const { pipeline, env } = await import('@xenova/transformers');
+      this.instance = await pipeline(this.task, this.model, { progress_callback });
+    }
+    return this.instance;
+  }
+}
+
+async function generateEmbedding(text) {
+  try {
+    const extractor = await EmbeddingPipeline.getInstance();
+    const output = await extractor(text, { pooling: 'mean', normalize: true });
+    return Array.from(output.data);
+  } catch (error) {
+    console.error('Error generating embedding:', error);
+    return null;
+  }
+}
 
 async function extractTextFromBlocks(blocks) {
   if (!Array.isArray(blocks)) {
@@ -67,26 +94,47 @@ async function main() {
     const contextDir = path.join(process.cwd(), 'public', 'context');
     await fs.mkdir(contextDir, { recursive: true });
     
+    const dbPath = path.join(contextDir, 'docs.db');
+    const db = sqlite3(dbPath);
+    
+    db.exec(`
+      CREATE TABLE IF NOT EXISTS documents (
+        id INTEGER PRIMARY KEY AUTOINCREMENT,
+        path TEXT NOT NULL,
+        content TEXT NOT NULL,
+        embedding BLOB,
+        created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
+      )
+    `);
+    
+    // Initialize the embedding model once
+    console.log('Initializing embedding model...');
+    // const extractor = await pipeline('feature-extraction', 'sauravpanda/gte-small-onnx');
+    
     const enDocsDir = path.join(process.cwd(), 'compiled', 'en');
     const docFiles = await glob('**/*.json', { 
       cwd: enDocsDir,
       ignore: '**/_meta.json'
     });
     
-    let combinedContent = [];
+    db.prepare('DELETE FROM documents').run();
+    const insert = db.prepare('INSERT INTO documents (path, content, embedding) VALUES (?, ?, ?)');
+    
+    console.log('Processing documents and generating embeddings...');
     
     for (const file of docFiles) {
       const fullPath = path.join(enDocsDir, file);
       const content = await processDocFile(fullPath);
       if (content) {
-        combinedContent.push(`[Document: ${file}]\n${content}\n-------------`);
+        const embedding = await generateEmbedding(content);
+        insert.run(file, content, embedding ? JSON.stringify(embedding) : null);
+        console.log(`Processed: ${file}`);
       }
     }
     
-    const outputPath = path.join(contextDir, 'en_docs.txt');
-    await fs.writeFile(outputPath, combinedContent.join('\n'));
-    
-    console.log('Documentation context has been extracted successfully!');
+    db.exec(`CREATE INDEX IF NOT EXISTS idx_embedding ON documents(embedding)`);
+    console.log('Documentation context and embeddings have been stored in SQLite database!');
+    db.close();
   } catch (error) {
     console.error('Error processing documentation:', error);
     process.exit(1);
diff --git a/packages/akiradocs/src/app/aiSearch/page.tsx b/packages/akiradocs/src/app/aiSearch/page.tsx
index 5e849e3..4261df2 100644
--- a/packages/akiradocs/src/app/aiSearch/page.tsx
+++ b/packages/akiradocs/src/app/aiSearch/page.tsx
@@ -1,6 +1,6 @@
 "use client"
 
-import { useState } from 'react'
+import { useState, useCallback } from 'react'
 import { SearchHeader } from '@/components/aiSearch/SearchHeader'
 import { SearchBar } from '@/components/aiSearch/SearchBar'
 import { LegacyDocsToggle } from '@/components/aiSearch/LegacyDocsToggle'
@@ -17,10 +17,27 @@ import { Source } from '@/types/Source'
 import AILoader from '@/components/aiSearch/AILoader'
 import { getHeaderConfig } from '@/lib/headerConfig'
 import { Header } from '@/components/layout/Header'
+import { generateEmbedding } from '@/lib/aisearch/embeddings'
+import { getDbWorker } from '@/lib/aisearch/dbWorker'
+
+function cosineSimilarity(a: number[], b: number[]): number {
+    if (a.some(isNaN) || b.some(isNaN)) {
+        console.error("NaN values detected in vectors:");
+        console.error("Vector A NaN indices:", a.map((val, i) => isNaN(val) ? i : null).filter(x => x !== null));
+        console.error("Vector B NaN indices:", b.map((val, i) => isNaN(val) ? i : null).filter(x => x !== null));
+        throw new Error("Invalid vectors containing NaN values");
+    }
+    
+    const dotProduct = a.reduce((sum, val, i) => sum + val * b[i], 0);
+    const magnitudeA = Math.sqrt(a.reduce((sum, val) => sum + val * val, 0));
+    const magnitudeB = Math.sqrt(b.reduce((sum, val) => sum + val * val, 0));
+    return dotProduct / (magnitudeA * magnitudeB);
+}
 
 export default function Home() {
   const [query, setQuery] = useState('')
   const [aiResponse, setAiResponse] = useState('')
+    const [loaderText, setLoaderText] = useState('Loading database ...')
   const [isLoading, setIsLoading] = useState(false)
   const [error, setError] = useState<string | null>(null)
   const recommendedArticles = getRecommendedArticles()
@@ -28,6 +45,20 @@ export default function Home() {
   const headerConfig = getHeaderConfig()
   const config = getAkiradocsConfig()
   const [sources, setSources] = useState<Source[]>([])
+    const handleGenerateEmbedding = useCallback(async (text: string) => {
+        try {
+            setIsLoading(true);
+            // console.log("Loading model for embedding");
+            const embedding = await generateEmbedding(text, (progress) => {});
+            return embedding;
+        } catch (error) {
+            console.error('Error generating embedding:', error);
+            throw error;
+        }
+        finally {
+          setLoaderText('Searching database for relevant information ...')
+        }
+    }, []);
 
   // If AI Search is disabled, show the disabled message
   if (!config.navigation.header.items.find((item: any) => item.href === '/aiSearch')?.show) {
@@ -74,87 +105,157 @@ export default function Home() {
     setError(null)
     setSources([])
     
-    try {
-      const contextResponse = await fetch('/context/en_docs.txt');
-      if (!contextResponse.ok) {
-        throw new Error(`Failed to fetch context: ${contextResponse.status}`);
-      }
-      const contextData = await contextResponse.text();
-      const docsContext = contextData;
+        const startTime = performance.now()
+        
+        try {
+            // Generate embedding for the query
+            const queryEmbedding = await handleGenerateEmbedding(query);
+            // console.log("Query embedding:", queryEmbedding)
+            // Get database worker
+            const worker = await getDbWorker();
+
+            // Get all documents
+            const allDocs = await worker.db.query(`
+                SELECT path, content, embedding
+                FROM documents
+                WHERE embedding IS NOT NULL
+            `);
+
+            // Calculate similarity scores and filter results
+            const similarityThreshold = 0.5;
+            const scoredDocs = allDocs
+                .map((doc: any) => {
+                    // Clean the embedding string and parse it
+                    const cleanEmbeddingStr = doc.embedding.replace(/[\[\]]/g, ''); // Remove square brackets
+                    const embeddingArray = cleanEmbeddingStr
+                        .split(',')
+                        .map((val: string) => {
+                            const parsed = parseFloat(val.trim());
+                            if (isNaN(parsed)) {
+                                console.error(`Invalid embedding value found: "${val}"`);
+                            }
+                            return parsed;
+                        });
+                    
+                    return {
+                        ...doc,
+                        similarity_score: cosineSimilarity(queryEmbedding, embeddingArray)
+                    };
+                })
+                .filter((doc: any) => doc.similarity_score > similarityThreshold)
+                .sort((a: any, b: any) => b.similarity_score - a.similarity_score)
+                .slice(0, 5);
+
+            console.log("RAG top 5 results:", scoredDocs);
+
+            // If no relevant documents found, return early
+            if (scoredDocs.length === 0) {
+                setAiResponse("I cannot answer this question from the given documentation. The available content doesn't seem relevant enough to provide a accurate answer.");
+                setIsLoading(false);
+                return;
+            }
+
+            setLoaderText('Loading the AI model ...')
+
+            // Combine relevant documents into context
+            const docsContext = scoredDocs
+                .map((doc: any) => `
+                    Source: ${doc.path}
+                    --- Content ---
+                    ${doc.content}
+                    --- End of Content ---
+                `)
+                .join('\n');
 
       const engine = await CreateMLCEngine(
         "Llama-3.2-1B-Instruct-q4f16_1-MLC",
-        { initProgressCallback: (progress: any) => console.log(progress)
-        },
+                { initProgressCallback: (progress: any) => {
+                    console.log(progress)
+                    setLoaderText(`Loading the AI model ${Math.round(progress.progress * 100)}% ...`)
+                } },
         {
-          context_window_size: 100000,
+                    context_window_size: 20000,
         }
       );
 
+
+
+            const engineLoadTime = performance.now() // Track engine load time
+            console.log(`Time taken for engine initialization: ${(engineLoadTime - startTime) / 1000}s`)
+            setLoaderText('Processing information and generating AI response ...')
       const messages = [
         { 
           role: "system", 
-          content: `You are a technical documentation assistant specialized in providing accurate, concise answers based on the official documentation. 
-          Your responses should be:
-          1. Direct and to the point
-          2. Based strictly on the provided documentation context
-          3. Include relevant code examples when available
-          4. Written in a technical but clear style
-
-          Documentation context: ${docsContext}`
+                  content: `You are a technical documentation assistant for AkiraDocs. Your purpose is to:
+1. Provide accurate, helpful answers using ONLY the provided documentation
+2. Stay positive and factual based on the documentation provided.
+3. Make sure the markdown answer is pretty, clean and easy to read.`
         },
         { 
           role: "user", 
-          content: `Answer the following question using only the provided documentation context. 
+                  content: `
+                  Please provide a helpful answer which is short and concise to the following question using only the provided documentation.
+
           Question: ${query}
 
-          Requirements for your response:
-          1. If the answer isn't clearly supported by the documentation, say "I don't have enough information to answer this question accurately."
-          2. Don't make assumptions or provide information not found in the documentation
-          3. If relevant, include short code snippets to illustrate your answer.
-          4. Only answer questions related to the Documentaion Context.
-          5. Try to be concise and to the point.
+          Answer the question using only the provided documentation. 
+                    
+          Do not make assumptions or add information not in the documentation.
+          
+          If relevant, include short code snippets. Only add code snippets if it is helpful to the question.
+
+          Dont add any notes or comments to the answer.
+
+          Make sure the question is answered properly avoiding unnecessary information.
+
+          Ensure the final output is in markdown format. Make sure it pretty and clean.
           
-          After your answer, if you used any sources from the documentation, list them in this format:
+          End of the answer, if you used any sources from the documentation, list them in this format:
           -------------
           Sources:
-          - <title> (<path>)` 
+          - <title> (<path>)
+          
+          Here is the documentation, only answer based on this information: 
+          ${docsContext}
+          `
         }
       ];
 
-      console.log("messages", messages)
+            // console.log("Messages:", messages)
 
       const chunks = await engine.chat.completions.create({ 
         messages: messages as ChatCompletionMessageParam[],
         stream: true,
-        stream_options: { include_usage: true }
+                stream_options: { include_usage: true },
+                max_tokens: 500,
+                temperature: 0.7,
+                top_p: 0.95,
+                frequency_penalty: 0.5,
+                presence_penalty: 0.5,
       });
 
       let aiContent = "";
       for await (const chunk of chunks) {
         const newContent = chunk.choices[0]?.delta.content || "";
         aiContent += newContent;
-        // Update the response in real-time
-        setAiResponse(aiContent);
-      }
-      
-      // Extract sources after the full response is received
-      const { cleanResponse, sources } = extractSources(aiContent);
+                
+                // Process partial content for streaming
+                const { cleanResponse } = extractSources(aiContent);
       setAiResponse(cleanResponse);
+            }
+
+            // Only extract and set sources after streaming is complete
+            const { sources } = extractSources(aiContent);
       setSources(sources);
       
-    } catch (error) {
-      console.error('Error during AI search:', error);
-      
-      // Check for WebGPU error
-      if (error instanceof Error && error.name === 'WebGPUNotAvailableError') {
-        setError('WebGPU is not yet supported on this browser. Please try using another browser.');
-      } else {
-        setError('Sorry, there was an error processing your request.');
-      }
-      setAiResponse('');
+            const endTime = performance.now() // Track total time
+            console.log(`Total time taken for AI search: ${(endTime - startTime) / 1000}s`)
+
+        } catch (error) {
+            console.error('Search error:', error);
+            setError(error instanceof Error ? error.message : 'An error occurred');
     } finally {
-      setIsLoading(false)
+            setIsLoading(false);
     }
   }
 
@@ -187,7 +288,7 @@ export default function Home() {
             <div className="flex flex-col justify-center items-center space-y-4 py-12">
               <AILoader />
               <p className="text-muted-foreground text-sm animate-pulse">
-                Loading AI response...
+                                    {loaderText}
               </p>
             </div>
           ) : error ? (
diff --git a/packages/akiradocs/src/components/aiSearch/AIResponse.tsx b/packages/akiradocs/src/components/aiSearch/AIResponse.tsx
index ca46310..e78f31f 100644
--- a/packages/akiradocs/src/components/aiSearch/AIResponse.tsx
+++ b/packages/akiradocs/src/components/aiSearch/AIResponse.tsx
@@ -8,6 +8,7 @@ import { AIResponseActions } from "./AIResponseActions"
 import { AIResponseSources } from "./AIResponseSources"
 import ReactMarkdown from 'react-markdown'
 import { Source } from "@/types/Source"
+import { memo } from 'react'
 
 interface AIResponseProps {
   response: string
@@ -15,6 +16,20 @@ interface AIResponseProps {
   onBack: () => void
 }
 
+// Memoize the markdown component to prevent unnecessary re-renders
+const MemoizedMarkdown = memo(({ content }: { content: string }) => (
+  <ReactMarkdown
+    components={{
+      pre({ children }) {
+        return <div className="not-prose">{children}</div>
+      }
+    }}
+  >
+    {content}
+  </ReactMarkdown>
+))
+MemoizedMarkdown.displayName = 'MemoizedMarkdown'
+
 export function AIResponse({ response, sources, onBack }: AIResponseProps) {
   return (
     <motion.div
@@ -35,8 +50,21 @@ export function AIResponse({ response, sources, onBack }: AIResponseProps) {
           </Button>
         </CardHeader>
         <CardContent className="pt-6">
-        <div className="prose dark:prose-invert max-w-none">
-            <ReactMarkdown>{response}</ReactMarkdown>
+          <div className="prose dark:prose-invert max-w-none
+            prose-headings:font-semibold
+            prose-h1:text-xl prose-h1:mt-8 prose-h1:mb-4
+            prose-h2:text-lg prose-h2:mt-6 prose-h2:mb-3
+            prose-p:my-4 prose-p:leading-relaxed
+            prose-ul:space-y-2 prose-ul:list-disc prose-ul:pl-6
+            prose-ol:space-y-2 prose-ol:list-decimal prose-ol:pl-6
+            prose-li:pl-2
+            [&_pre]:bg-secondary [&_pre]:p-4 [&_pre]:rounded-lg [&_pre]:my-4
+            [&_code:not(pre_code)]:bg-secondary [&_code:not(pre_code)]:px-1.5 [&_code:not(pre_code)]:py-0.5 [&_code:not(pre_code)]:rounded-sm
+            [&_pre_code]:bg-transparent [&_pre_code]:p-0 [&_pre_code]:rounded-none
+            [&>*:first-child]:mt-0
+            [&>p>strong]:block [&>p>strong]:mt-8 [&>p>strong]:mb-4 [&>p>strong]:text-lg
+            [&>p:has(>strong:only-child)]:m-0">
+            <MemoizedMarkdown content={response} />
           </div>
         </CardContent>
         <CardFooter className="flex flex-col items-start space-y-4">
diff --git a/packages/akiradocs/src/components/aiSearch/AIResponseSources.tsx b/packages/akiradocs/src/components/aiSearch/AIResponseSources.tsx
index 5b160ed..d146d15 100644
--- a/packages/akiradocs/src/components/aiSearch/AIResponseSources.tsx
+++ b/packages/akiradocs/src/components/aiSearch/AIResponseSources.tsx
@@ -12,7 +12,7 @@ export function AIResponseSources({ sources }: AIResponseSourcesProps) {
                 {sources.map((source, index) => (
                     <li key={index}>
                         <a
-                            href={source.url}
+                            href={`${window.location.origin}/en/${source.url.replace('%20', '')}?utm_source=akiradocs`}
                             target="_blank"
                             rel="noopener noreferrer"
                             className="text-sm text-indigo-600 dark:text-indigo-400 hover:underline"
diff --git a/packages/akiradocs/src/lib/aisearch/dbWorker.ts b/packages/akiradocs/src/lib/aisearch/dbWorker.ts
new file mode 100644
index 0000000..9e6a3b2
--- /dev/null
+++ b/packages/akiradocs/src/lib/aisearch/dbWorker.ts
@@ -0,0 +1,35 @@
+import { createDbWorker } from "sql.js-httpvfs";
+import { SplitFileConfig } from "sql.js-httpvfs/dist/sqlite.worker";
+
+let dbInstance: any = null;
+
+export async function getDbWorker() {
+    if (dbInstance) return dbInstance;
+
+    const workerUrl = new URL(
+        "sql.js-httpvfs/dist/sqlite.worker.js",
+        import.meta.url
+    );
+    const wasmUrl = new URL(
+        "sql.js-httpvfs/dist/sql-wasm.wasm",
+        import.meta.url
+    );
+
+    const config: SplitFileConfig = {
+        from: "inline" as const,
+        config: {
+            serverMode: "full",
+            requestChunkSize: 4096,
+            url: "/context/docs.db"
+        }
+    };
+
+    const worker = await createDbWorker(
+        [config],
+        workerUrl.toString(),
+        wasmUrl.toString()
+    );
+
+    dbInstance = worker;
+    return dbInstance;
+}
\ No newline at end of file
diff --git a/packages/akiradocs/src/lib/aisearch/embeddings.ts b/packages/akiradocs/src/lib/aisearch/embeddings.ts
new file mode 100644
index 0000000..f93f006
--- /dev/null
+++ b/packages/akiradocs/src/lib/aisearch/embeddings.ts
@@ -0,0 +1,34 @@
+export interface ProgressCallback {
+    file: string;
+    progress: number;
+    loaded: number;
+    total: number;
+}
+
+export async function generateEmbedding(
+    text: string,
+    onProgress?: (progress: ProgressCallback) => void
+): Promise<number[]> {
+    return new Promise((resolve, reject) => {
+        const worker = new Worker(
+            new URL('./embeddings.worker.ts', import.meta.url),
+            { type: 'module' }
+        );
+
+        worker.addEventListener('message', (event) => {
+            if (event.data.status === 'progress' && onProgress) {
+                onProgress(event.data.progress);
+            } else if (event.data.status === 'complete') {
+                resolve(event.data.output);
+                worker.terminate();
+            }
+        });
+
+        worker.addEventListener('error', (error) => {
+            reject(error);
+            worker.terminate();
+        });
+
+        worker.postMessage({ text });
+    });
+} 
\ No newline at end of file
diff --git a/packages/akiradocs/src/lib/aisearch/embeddings.worker.ts b/packages/akiradocs/src/lib/aisearch/embeddings.worker.ts
new file mode 100644
index 0000000..52b26d6
--- /dev/null
+++ b/packages/akiradocs/src/lib/aisearch/embeddings.worker.ts
@@ -0,0 +1,30 @@
+import { pipeline, ProgressCallback, type PipelineType } from "@huggingface/transformers";
+
+class EmbeddingPipelineSingleton {
+    static task: PipelineType = 'feature-extraction';
+    static model = 'sauravpanda/gte-small-onnx';
+    static instance: Promise<any> | null = null;
+
+    static async getInstance(progress_callback: ProgressCallback | null = null) {
+        this.instance ??= pipeline(this.task, this.model, { 
+            progress_callback: progress_callback ?? undefined
+        });
+        return this.instance;
+    }
+}
+
+self.addEventListener('message', async (event) => {
+    const embedder = await EmbeddingPipelineSingleton.getInstance(x => {
+        self.postMessage({ status: 'progress', progress: x });
+    });
+
+    const output = await embedder(event.data.text, {
+        pooling: 'mean',
+        normalize: true
+    });
+
+    self.postMessage({
+        status: 'complete',
+        output: Array.from(output.data),
+    });
+}); 
\ No newline at end of file
diff --git a/packages/create-app/package.json b/packages/create-app/package.json
index f6c40d3..9f8a964 100644
--- a/packages/create-app/package.json
+++ b/packages/create-app/package.json
@@ -1,6 +1,6 @@
 {
   "name": "create-akiradocs",
-  "version": "1.0.52",
+  "version": "1.0.53",
   "description": "Create Akira Docs documentation sites with one command",
   "main": "./dist/index.js",
   "type": "module",