ImgJoc - AI Image Analysis

\n\n

\n${\n [\"dashboard\", \"new-analysis\", \"history\", \"settings\", \"image-detail\", \"analysis-detail\"].map(v =>\n `

`\n ).join(\"\")\n }\n

\n\n\n`;\n}\n\nexport default async function(req: Request) {\n const { OpenAI } = await import(\"https://esm.town/v/std/openai\");\n // The 'Buffer' class is specific to Node.js. In other environments like Deno or Cloudflare Workers,\n // this might not be available. The client-side logic correctly uses FileReader, which is standard.\n // The server-side logic has been updated to expect a data URL directly.\n const { Buffer } = await import(\"node:buffer\");\n\n const CORS_HEADERS = {\n \"Access-Control-Allow-Origin\": \"*\",\n \"Access-Control-Allow-Methods\": \"POST, GET, OPTIONS\",\n \"Access-Control-Allow-Headers\": \"Content-Type, Accept\",\n };\n if (req.method === \"OPTIONS\") return new Response(null, { status: 204, headers: CORS_HEADERS });\n\n const url = new URL(req.url);\n const format = url.searchParams.get(\"format\");\n const action = url.searchParams.get(\"action\");\n const sourceUrl = import.meta.url.replace(\"esm.town\", \"val.town\");\n const openai = new OpenAI();\n\n async function fileToDataURL(file: File): Promise {\n const arrayBuffer = await file.arrayBuffer();\n // Using Buffer here assumes a Node.js-compatible environment.\n const base64 = Buffer.from(arrayBuffer).toString(\"base64\");\n return `data:${file.type};base64,${base64}`;\n }\n\n async function callAI(\n systemPrompt: string,\n userMessage: any, // Can be string or vision payload\n log: LogEntry[],\n agentName: string,\n ): Promise