Parallax Studio Pro+

Loading Vision Engine...

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\n Stage View\n

Container Width

Zoom

\n Parallax & Tilt\n

Max Tilt (deg)

Perspective

Scale

Parallax Scale

\n Layer Generation\n

Generation Mode

Depth Source

Layer Count

Distribution

Base Depth

Spacing Multiplier

Invert Depth Order

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\n Extraction Pipeline\n

Mode

Hue Min/Max

Sat Min

Val Min

Invert Key

Block Size

Threshold Inv

Softness (Feather)

Morphology

Kernel

Iterations

Invert Alpha

\n Post-Processing (Selected Layer)\n

Brightness

Contrast

Gamma

Unsharp Amt

Blur

\n \n \n\n`;\n}\n\n// --- VAL TOWN SERVER LOGIC ---\nexport default async function (req: Request) {\n const url = new URL(req.url);\n\n // Handle the AI Assist POST request\n if (req.method === \"POST\") {\n try {\n const openai = new OpenAI();\n const { image } = await req.json();\n\n if (!image || !image.startsWith(\"data:image/\")) {\n throw new Error(\"A valid base64 image string is required.\");\n }\n\n const completion = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [\n {\n role: \"system\",\n content: AI_ASSIST_PROMPT,\n },\n {\n role: \"user\",\n content: [\n {\n type: \"text\",\n text:\n \"Analyze this image and provide the optimal extraction pipeline configuration.\",\n },\n {\n type: \"image_url\",\n image_url: {\n url: image,\n detail: \"low\",\n },\n },\n ],\n },\n ],\n temperature: 0.2,\n response_format: { type: \"json_object\" },\n });\n\n const content = completion.choices[0].message.content;\n\n // Sanitize AI response: ensure it's valid JSON and nothing else.\n let parsedContent: AIPipelineResponse;\n try {\n parsedContent = JSON.parse(content);\n } catch (e) {\n throw new Error(\"AI returned malformed JSON.\");\n }\n\n if (!parsedContent.pipeline || !parsedContent.reason) {\n throw new Error(\n \"AI response was missing required 'pipeline' or 'reason' keys.\",\n );\n }\n\n // Re-serialize the parsed object to strip any potential malicious code\n // or extraneous properties not defined in our expected structure.\n const sanitizedResponse = JSON.stringify({\n pipeline: parsedContent.pipeline,\n reason: parsedContent.reason,\n });\n\n return new Response(sanitizedResponse, {\n headers: { \"Content-Type\": \"application/json\" },\n });\n } catch (error) {\n console.error(\"AI Assist Error:\", error);\n return new Response(\n JSON.stringify({\n error: error.message || \"An unknown server error occurred.\",\n }),\n {\n status: 500,\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n }\n }\n\n // Serve the HTML for GET requests\n const sourceUrl = `https://${url.hostname}${url.pathname}`;\n return new Response(generateHtml(sourceUrl), {\n headers: { \"Content-Type\": \"text/html\" },\n });\n}","deleted","label",[98],"permalink","https://www.val.town/x/know/imagen/code/main.tsx","extension","actionData","errors"]