We all Jiankui

[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8,"_9":10},"actionData","errors","root",{"_152":153,"_154":155},"routes/_app.x.$handle.$name",{"_11":12,"_13":14,"_15":16,"_18":19,"_17":-7,"_115":-5,"_20":116,"_22":117,"_118":119,"_120":121,"_25":122,"_24":-5,"_123":-5,"_124":-5,"_125":53,"_126":127,"_128":44,"_129":-5,"_130":-5,"_131":132},"routes/_app.x.$handle.$name.branch.$branch.code.$",{"_11":12,"_13":14,"_15":16,"_17":-7,"_18":19,"_20":21,"_22":23,"_24":-7,"_25":26,"_27":-5,"_28":-5,"_29":-5,"_30":-5,"_31":-5},"handle","yawnxyz","name","wecrispr","branchName","main","version","path","","project",{"_33":61,"_13":14,"_45":62,"_63":-5,"_64":44,"_65":66,"_67":66,"_68":-5,"_69":-5,"_70":71,"_72":37,"_73":44,"_74":-5,"_75":-5,"_76":77,"_78":79,"_80":-5,"_81":-5,"_82":-5,"_83":-5,"_84":85,"_86":85,"_87":88,"_89":88,"_90":88,"_91":85,"_92":85,"_93":94,"_95":96,"_97":98,"_99":53},"tree",[56],"file","contents",[32],"upstream","pull","ahead","behind","envVars",{"_33":34,"_13":35,"_36":37,"_38":-5,"_39":40,"_41":42,"_43":44,"_45":46,"_17":47,"_48":49,"_50":51,"_52":53,"_54":-5,"_18":55},"id","6188128e-2793-11f0-9d52-569c3dd06744","main.tsx","fileId","6161ace8-2793-11f0-9d52-569c3dd06744","parentId","branchId","615e6b00-2793-11f0-9d52-569c3dd06744","branchVersion",8,"latest",true,"createdAt",["D",1742196762877],7,"fileType","http","content","import { Hono } from \"https://deno.land/x/hono@v3.11.7/mod.ts\";\nimport \"jsr:@std/dotenv/load\"; // needed for deno run; not req for smallweb or valtown\n\n\nconst app = new Hono();\n\n\n\nimport { GoogleGenerativeAI } from \"npm:@google/generative-ai\";\nimport \"jsr:@std/dotenv/load\"; // needed for deno run; not req for smallweb or valtown\nimport { encode as base64Encode } from \"https://deno.land/std@0.177.0/encoding/base64.ts\";\n\n// Function to fetch and encode an external image\nasync function fetchAndEncodeImage(url) {\n try {\n const response = await fetch(url);\n if (!response.ok) {\n throw new Error(`Failed to fetch image: ${response.status} ${response.statusText}`);\n }\n const arrayBuffer = await response.arrayBuffer();\n const uint8Array = new Uint8Array(arrayBuffer);\n return base64Encode(uint8Array);\n } catch (error) {\n console.error(\"Error fetching external image:\", error);\n throw error;\n }\n}\n\nexport const imageEditHandler = async (c) => {\n try {\n const formData = await c.req.formData();\n const imageFile = formData.get(\"image\");\n const userPrompt = formData.get(\"prompt\") || \"swap my face with the scientist\";\n\n if (!imageFile) {\n return c.json({ error: \"No image provided\" }, 400);\n }\n\n // Get API key from environment variable\n const apiKey = Deno.env.get(\"GOOGLE_API_KEY\");\n if (!apiKey) {\n return c.json({ error: \"API key not configured\" }, 500);\n }\n\n // Convert the uploaded file to base64\n const arrayBuffer = await imageFile.arrayBuffer();\n const uint8Array = new Uint8Array(arrayBuffer);\n const userImageBase64 = base64Encode(uint8Array);\n\n // Fetch and encode the scientist image\n const scientistImageUrl = \"https://pbs.twimg.com/media/GdMjZhubYAAM1Yf?format=jpg&name=4096x4096\";\n const scientistImageBase64 = await fetchAndEncodeImage(scientistImageUrl);\n\n console.log(\"Processing images with Gemini 2.0 Flash Experimental...\");\n console.log(\"User image type:\", imageFile.type);\n\n // Initialize the Google Generative AI\n const genAI = new GoogleGenerativeAI(apiKey);\n\n // Use the Gemini 2.0 Flash Experimental model with image generation capability\n const model = genAI.getGenerativeModel({\n model: \"gemini-2.0-flash-exp-image-generation\",\n generationConfig: {\n temperature: 1,\n responseModalities: [\"Text\", \"Image\"]\n }\n });\n\n // Create a very specific prompt for face swapping\n const faceSwapPrompt = `\n I need to create a face swap where the user's face is placed onto the scientist's body.\n \n Image 1: The SOURCE face (source face)\n Image 2: The scientist in the lab photo (target body)\n \n IMPORTANT INSTRUCTIONS:\n - REPLACE the scientist's face with the SOURCE face EXACTLY as it appears in Image 2\n - DO NOT change the user's face or make up another face\n - KEEP the scientist's exact pose, lab coat, and entire lab setting unchanged\n - PLACE the user's head PRECISELY where the scientist's head is\n - Make sure the lighting on the face matches the lab environment lighting\n - Ensure the head is realistically connected to the neck area\n - The head must be correctly sized and proportioned to look natural on the body\n - The final result should look like the user is actually in the lab photo\n - Place the user's face in the center of the lab photo, on top of the scientist!!\n \n This is for ${userPrompt}\n `;\n\n try {\n console.log(\"Sending request to Gemini API...\");\n\n // First approach: Try with the scientist image first, then the user image\n const contents = [\n faceSwapPrompt,\n {\n inlineData: {\n data: userImageBase64,\n mimeType: imageFile.type\n }\n },\n {\n inlineData: {\n data: scientistImageBase64,\n mimeType: \"image/jpeg\"\n }\n },\n ];\n\n const result = await model.generateContent(contents);\n console.log(\"Response received from Gemini API\");\n\n const response = result.response;\n\n // Process the response\n if (response && response.candidates &&\n response.candidates[0] &&\n response.candidates[0].content &&\n response.candidates[0].content.parts) {\n\n const parts = response.candidates[0].content.parts;\n let textResponse = \"\";\n let imageData = null;\n\n // Extract text and image data from parts\n for (const part of parts) {\n if (part.text) {\n textResponse += part.text;\n } else if (part.inlineData && part.inlineData.data) {\n imageData = part.inlineData.data;\n }\n }\n\n // Return both text and image if available\n if (imageData) {\n return c.json({\n text: textResponse || \"Face swap completed successfully!\",\n images: [{ data: imageData }]\n });\n } else {\n throw new Error(\"No image was generated\");\n }\n } else {\n throw new Error(\"Invalid response structure\");\n }\n } catch (error) {\n console.error(\"Image processing error:\", error);\n\n // Fall back to text response\n try {\n const textModel = genAI.getGenerativeModel({\n model: \"gemini-pro-vision\",\n generationConfig: {\n temperature: 1\n }\n });\n\n const textContents = [\n \"I was trying to swap this person's face onto a scientist image but it failed. Can you describe what this person looks like?\",\n {\n inlineData: {\n data: userImageBase64,\n mimeType: imageFile.type\n }\n }\n ];\n\n const textResult = await textModel.generateContent(textContents);\n const textResponse = textResult.response.text();\n\n return c.json({\n text: \"I couldn't generate the face swap image. \" + textResponse,\n note: \"Please try again with a different image that has a clear face.\",\n images: []\n });\n } catch (textError) {\n console.error(\"Text fallback error:\", textError);\n return c.json({\n error: \"Failed to process image and generate face swap\"\n }, 500);\n }\n }\n } catch (error) {\n console.error(\"Image editing error:\", error);\n return c.json({\n error: error.message || \"Error processing image\"\n }, 500);\n }\n};\n\nexport const getTailwindConfig = () => ({\n theme: {\n extend: {\n colors: {\n 'background': '#F5F4F4',\n 'page-bg': '#F5F4F4',\n 'app-bg': '#FDFBF7',\n 'app-bg-alt': '#FFFFFF',\n 'app-accent': '#E2DFDF',\n 'primary': 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Jiankui\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n

You CRISPR,
I CRISPR,
We all CRISPR...

Ever want to be a scientist? With the help of CRISPR and modern AI, you too can become a powerful CRISPR scientist!

\n\n

\n \n

\n \n \n Click to browse or drop image here\n \n

\n \n \n

Your Image

\n $\"Your$ \n

\n \n \n

\n \n

\n \n \n

\n If it doesn't look good, just re-CRISPR!\n

\n \n

\n $\"Edited$ \n

\n Code on val.town. Uses Gemini 2.0 flash-experimental image generation.\n

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You CRISPR, I CRISPR, We all CRISPR...

Your Image

You CRISPR,
I CRISPR,
We all CRISPR...