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🎨 Wallpaper History

\n ${history.map(item => `\n

\n \n $\"Wallpaper\"$ \n \n

${item.prompt}

${new Date(item.timestamp).toLocaleString()}

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

\n \n \n `;\n \n return c.html(html);\n } catch (error) {\n return c.text(`Error: ${error.message}`, 500);\n }\n});\n\nexport default app.fetch;\n","import { Hono } from \"npm:hono@4\";\nimport OpenAI from \"npm:openai@4\";\nimport { blob } from \"https://esm.town/v/std/blob?v=11\";\n\nconst app = new Hono();\n\n// Generate and return the image directly using DALL-E\napp.get(\"/\", async (c) => {\n const openai = new OpenAI();\n \n try {\n // First, have the LLM generate a creative prompt\n const chatResponse = await openai.chat.completions.create({\n model: \"gpt-4o-mini\",\n messages: [\n {\n role: \"system\",\n content: \"You are a creative prompt generator for laptop wallpapers. Generate beautiful, minimalist, calming image prompts perfect for desktop backgrounds. Keep them simple, aesthetically pleasing, and not too busy.\"\n },\n {\n role: \"user\",\n content: \"Generate a creative prompt for a laptop wallpaper. It should be minimalist, beautiful, and calming. Include simple subjects, soft colors, and clean composition.\"\n }\n ],\n temperature: 1.2,\n });\n \n const generatedPrompt = chatResponse.choices[0].message.content;\n \n // Now generate the image using the LLM-generated prompt\n const response = await openai.images.generate({\n model: \"dall-e-3\",\n prompt: generatedPrompt,\n n: 1,\n size: \"1792x1024\",\n });\n \n const imageUrl = response.data[0].url;\n \n // Fetch the image and return it directly\n const imageResponse = await fetch(imageUrl);\n const imageBlob = await imageResponse.blob();\n \n // Store in blob storage with timestamp\n const timestamp = Date.now();\n const key = `wallpapers/${timestamp}.png`;\n await blob.setJSON(`metadata/${timestamp}`, {\n prompt: generatedPrompt,\n timestamp,\n imageUrl,\n });\n \n // Store the actual image\n const arrayBuffer = await imageBlob.arrayBuffer();\n await blob.set(key, new Uint8Array(arrayBuffer));\n \n return new Response(imageBlob, {\n headers: {\n \"Content-Type\": imageResponse.headers.get(\"Content-Type\") || \"image/png\",\n },\n });\n } catch (error) {\n return c.text(`Error: ${error.message}`, 500);\n }\n});\n\n// History endpoint returning JSON array\napp.get(\"/history\", async (c) => {\n try {\n // List all metadata files\n const blobs = await blob.list(\"metadata/\");\n \n // Get all metadata\n const history = await Promise.all(\n blobs.map(async (b) => {\n const metadata = await blob.getJSON(b.key);\n return metadata;\n })\n );\n \n // Sort by timestamp, newest first\n history.sort((a, b) => b.timestamp - 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Diff · v18