Commit Roast My Website

examples/roastmywebsite/src/lib/LLM/llm.ts

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+import OpenAI from "openai";
+import { encoding_for_model } from "@dqbd/tiktoken";
+
+/**
+ * Function to generate a roast for a website based on its screenshot and markdown content.
+ * @param roastPrompt - Initial prompt text for the roast.
+ * @param screenshotUrl - URL of the screenshot of the website.
+ * @param content - Raw markdown content of the website.
+ */
+export async function roastPrompt(roastPrompt: string, screenshotUrl: string, content: string) {
+    try {
+        // Initialize OpenAI with the API key from environment variables
+        const openai = new OpenAI({
+            apiKey: process.env.OPEN_AI_KEY
+        });
+
+    
+        let contentTruncated = await truncateContentToFit(content, 30000);
+
+        const response = await openai.chat.completions.create({
+            model: "gpt-4o",
+            messages: [
+                {
+                    role: "user",
+                    content: [
+                        { type: "text", text: roastPrompt },
+                        { type: "image_url", image_url: { url: screenshotUrl, detail: "low" } },
+                        { type: "text", text: contentTruncated }
+                    ],
+                },
+            ],
+        });
+        // Return the first choice's message instead of logging it
+        return response.choices[0].message.content;
+    } catch (error) {
+        console.error("Error generating roast:", error);
+        // Assert error as an instance of Error to access message property
+        return `Error generating roast: ${(error as Error).message}`;
+    }
+}
+
+
+
+export function numTokensFromString(message: string, model: string): number {
+    const encoder = encoding_for_model(model as any);
+
+    // Encode the message into tokens
+    const tokens = encoder.encode(message);
+
+    // Free the encoder resources after use
+    encoder.free();
+
+    // Return the number of tokens
+    return tokens.length;
+}
+
+
+
+async function truncateContentToFit(content: string, maxTokens: number): Promise<string> {
+    const modifier = 4;
+
+    let contentTotruncate = content;
+    const numTokens = numTokensFromString(contentTotruncate, "gpt-4");
+
+    if (numTokens > maxTokens) {
+        // trim the document to the maximum number of tokens, tokens != characters
+        contentTotruncate = content.slice(0, (maxTokens * modifier));
+
+    }
+    return contentTotruncate
+}
+
+
+
+

examples/roastmywebsite/src/lib/utils.ts

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+import { type ClassValue, clsx } from "clsx"
+import { twMerge } from "tailwind-merge"
+
+export function cn(...inputs: ClassValue[]) {
+  return twMerge(clsx(inputs))
+}