feat(db): migration and database setup

packages/db/src/utils/computed.ts

@@ -0,0 +1,57 @@
+import { TiktokenEncoding, get_encoding } from "tiktoken";
+
+import { TokenStatistics } from "@/schema";
+
+/**
+ * Count the number of tokens in the given text using the specified encoding.
+ * @param text - The input text
+ * @param encoding - The token encoding (default: "cl100k_base")
+ */
+export const computeTokenCount = (
+  text: string,
+  encoding: TiktokenEncoding = "cl100k_base",
+): number => {
+  try {
+    const encoder = get_encoding(encoding);
+    const tokens = encoder.encode(text);
+    encoder.free();
+    return tokens.length;
+  } catch {
+    return text.length;
+  }
+};
+
+/**
+ * Create token statistics for the given data.
+ * @param data  - The input data containing title, body, and categories
+ * @returns TokenStatistics object
+ */
+export const computeTokenStatistics = (data: {
+  title: string;
+  body: string;
+  categories: string[];
+}): TokenStatistics => {
+  const title = computeTokenCount(data.title);
+  const body = computeTokenCount(data.body);
+  const categories = computeTokenCount(data.categories.join(","));
+  const excerpt = computeTokenCount(data.body.substring(0, 200));
+
+  return {
+    body,
+    categories,
+    excerpt,
+    title,
+    total: title + body + categories + excerpt,
+  };
+};
+
+/**
+ * Compute the estimated reading time for the given text.
+ * @param text - The input text
+ * @param wordsPerMinute - The reading speed in words per minute (default: 200)
+ * @returns The estimated reading time in minutes
+ */
+export const computeReadingTime = (text: string, wordsPerMinute = 200): number => {
+  const words = text.trim().split(/\s+/).length;
+  return Math.ceil(words / wordsPerMinute);
+};