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Figma creds: env FIGMA_READ_TOKEN.\n//\n// Returns: frame_image_url, frame_box, scale, slices[] (box + image_url + nodes[]),\n// and slices_json (stringified slices, for the Make Create-JSON → planner step).\n// Coordinates are ABSOLUTE Figma coords (same space V1 used) so upload_image's\n// (region.x - frame_box.x) * scale crop math is unchanged.\nexport default async function (req: Request): Promise {\n const fail = (stage: string, status: number, detail: unknown) =>\n new Response(JSON.stringify({ ok: false, stage, detail }), {\n status,\n headers: { \"content-type\": \"application/json\" },\n });\n\n if (req.headers.get(\"x-auth\") !== Deno.env.get(\"AUTH_TOKEN\")) {\n return fail(\"auth\", 401, \"Invalid or missing x-auth header\");\n }\n\n let inp: any;\n try {\n inp = await req.json();\n } catch (e) {\n return fail(\"parse_input\", 400, \"Body not valid JSON: \" + String(e));\n }\n\n const fileKey = inp.file_key;\n let nodeId = inp.frame_node_id || inp.node_id;\n const scale = Number(inp.scale) || 0.6;\n const visionW = Number(inp.vision_width) || 700; // px cap for the planner's vision image\n if (!fileKey || !nodeId) {\n return fail(\"validate_input\", 400, \"need file_key and frame_node_id\");\n }\n nodeId = String(nodeId).replace(/-/g, \":\");\n\n const token = Deno.env.get(\"FIGMA_READ_TOKEN\");\n if (!token) return fail(\"config\", 500, \"FIGMA_READ_TOKEN not set\");\n const FH = { \"X-Figma-Token\": token };\n\n // ---- 1. render the frame PNG + 2. fetch the node tree (in parallel) -------\n let frameImageUrl = \"\";\n let doc: any;\n try {\n const [imgR, nodesR] = await Promise.all([\n fetch(\n `https://api.figma.com/v1/images/${fileKey}?ids=${\n encodeURIComponent(nodeId)\n }&format=png&scale=${scale}`,\n { headers: FH },\n ),\n fetch(\n `https://api.figma.com/v1/files/${fileKey}/nodes?ids=${\n encodeURIComponent(nodeId)\n }`,\n { headers: FH },\n ),\n ]);\n const imgT = await imgR.text();\n if (!imgR.ok) return fail(\"figma_render\", imgR.status, imgT.slice(0, 400));\n frameImageUrl = JSON.parse(imgT)?.images?.[nodeId] || \"\";\n if (!frameImageUrl) {\n return fail(\"figma_render\", 502, \"no image url returned for node\");\n }\n\n const nodesT = await nodesR.text();\n if (!nodesR.ok) {\n return fail(\"figma_get\", nodesR.status, nodesT.slice(0, 400));\n }\n doc = JSON.parse(nodesT)?.nodes?.[nodeId]?.document;\n if (!doc) return fail(\"figma_get\", 404, \"node not found: \" + nodeId);\n } catch (e) {\n return fail(\"figma_fetch\", 502, \"Figma fetch threw: \" + String(e));\n }\n\n const frameBox = doc.absoluteBoundingBox\n ? {\n x: Math.round(doc.absoluteBoundingBox.x),\n y: Math.round(doc.absoluteBoundingBox.y),\n w: Math.round(doc.absoluteBoundingBox.width),\n h: Math.round(doc.absoluteBoundingBox.height),\n }\n : null;\n if (!frameBox) return fail(\"figma_get\", 500, \"frame has no bounding box\");\n\n // ---- 3. walk the tree, classify content nodes + collect slices ------------\n const visible = (arr: any): any[] =>\n Array.isArray(arr) ? arr.filter((p) => p && p.visible !== false) : [];\n const box = (n: any) =>\n n.absoluteBoundingBox\n ? {\n x: Math.round(n.absoluteBoundingBox.x),\n y: Math.round(n.absoluteBoundingBox.y),\n w: Math.round(n.absoluteBoundingBox.width),\n h: Math.round(n.absoluteBoundingBox.height),\n }\n : null;\n\n const slices: any[] = [];\n const nodes: any[] = []; // flat list of classified content nodes\n const seenGroupBox = new Set(); // dedupe nested identical-box groups\n\n const walk = (n: any) => {\n const b = box(n);\n\n if (n.type === \"SLICE\") {\n if (b && b.w > 0 && b.h > 0) {\n slices.push({ id: n.id, name: n.name, box: b });\n }\n return; // slices have no content children we care about\n }\n\n if (b && b.w > 0 && b.h > 0) {\n const fills = visible(n.fills).map((p: any) => p.type);\n const strokes = visible(n.strokes).map((p: any) => p.type);\n const hasImage = fills.includes(\"IMAGE\");\n const hasPaint = fills.some((t: string) =>\n t === \"SOLID\" || t.startsWith(\"GRADIENT\")\n );\n const hasStroke = strokes.length > 0;\n const isContainer = n.type === \"GROUP\" || n.type === \"FRAME\" ||\n n.type === \"INSTANCE\";\n\n let kind = \"\";\n if (n.type === \"TEXT\") kind = \"text\";\n else if (hasImage) kind = \"image\";\n else if (isContainer) kind = \"group\";\n else if (hasPaint || hasStroke) kind = \"shape\"; // buttons, cards, dividers\n // VECTOR / STAR / BOOLEAN etc. (icons, decoration) are skipped for cutting\n\n if (kind) {\n // dedupe nested groups that share the same box (Earth Runners chains):\n // keep the shallowest (first seen in DFS).\n const key = `${b.x},${b.y},${b.w},${b.h}`;\n const dup = kind === \"group\" && seenGroupBox.has(key);\n if (kind === \"group\") seenGroupBox.add(key);\n if (!dup) {\n const rec: any = { id: n.id, type: n.type, kind, box: b };\n if (kind === \"text\") {\n rec.text = String(n.characters || \"\");\n rec.font_size = n.style?.fontSize ?? null;\n }\n if (hasImage) rec.image = true;\n if (hasPaint) rec.fill = true;\n if (hasStroke) rec.stroke = true;\n nodes.push(rec);\n }\n }\n }\n for (const c of (n.children || [])) walk(c);\n };\n walk(doc);\n\n if (slices.length === 0) {\n return fail(\"validate\", 422, \"no SLICE markers found in frame\");\n }\n\n // ---- 4. assign nodes to slices (by center) + build per-slice vision crop --\n const centerIn = (nb: any, sb: any) => {\n const cx = nb.x + nb.w / 2, cy = nb.y + nb.h / 2;\n return cx >= sb.x && cx <= sb.x + sb.w && cy >= sb.y && cy <= sb.y + sb.h;\n };\n\n // wsrv crop of the slice region from the rendered frame, downscaled to visionW.\n const cropUrl = (sb: any) => {\n const cx = Math.round((sb.x - frameBox.x) * scale);\n const cy = Math.round((sb.y - frameBox.y) * scale);\n const cw = Math.round(sb.w * scale);\n const ch = Math.round(sb.h * scale);\n const w = Math.min(cw, visionW);\n return `https://wsrv.nl/?url=${encodeURIComponent(frameImageUrl)}` +\n `&precrop=true&cx=${cx}&cy=${cy}&cw=${cw}&ch=${ch}&w=${w}&output=jpg&q=80`;\n };\n\n // top-to-bottom slice order\n slices.sort((a, b) => a.box.y - b.box.y);\n for (const s of slices) {\n s.image_url = cropUrl(s.box);\n s.nodes = nodes.filter((nd) => centerIn(nd.box, s.box));\n }\n\n return new Response(\n JSON.stringify({\n ok: true,\n stage: \"done\",\n frame_image_url: frameImageUrl,\n frame_box: frameBox,\n scale,\n slices,\n slices_json: JSON.stringify(slices),\n }),\n { headers: { \"content-type\": \"application/json\" } },\n );\n}","// figma_prep-v2 — the deterministic backbone for V2.\n//\n// Difference from V1: V1 captured ONLY slice markers + TEXT + image-fill rects,\n// so button/card boxes were invisible and row cuts had to be guessed (the BIAS).\n// V2 captures EVERY visible content node — text, images, filled/stroked shapes\n// (buttons, cards, dividers) and group/tile boxes — so planner-v2 can cut at the\n// true gutters with no guessing.\n//\n// POST { \"file_key\": \"...\", \"frame_node_id\": \"120:1829\", \"scale\": 0.6 }\n// Header: x-auth: . Figma creds: env FIGMA_READ_TOKEN.\n//\n// Returns: frame_image_url, frame_box, scale, slices[] (box + image_url + nodes[]),\n// and slices_json (stringified slices, for the Make Create-JSON → planner step).\n// Coordinates are ABSOLUTE Figma coords (same space V1 used) so upload_image's\n// (region.x - frame_box.x) * scale crop math is unchanged.\nexport default async function (req: Request): Promise {\n const fail = (stage: string, status: number, detail: unknown) =>\n new Response(JSON.stringify({ ok: false, stage, detail }), {\n status,\n headers: { \"content-type\": \"application/json\" },\n });\n\n if (req.headers.get(\"x-auth\") !== Deno.env.get(\"AUTH_TOKEN\")) {\n return fail(\"auth\", 401, \"Invalid or missing x-auth header\");\n }\n\n let inp: any;\n try {\n inp = await req.json();\n } catch (e) {\n return fail(\"parse_input\", 400, \"Body not valid JSON: \" + String(e));\n }\n\n const fileKey = inp.file_key;\n let nodeId = inp.frame_node_id || inp.node_id;\n const scale = Number(inp.scale) || 0.6;\n const visionW = Number(inp.vision_width) || 700; // px cap for the planner's vision image\n if (!fileKey || !nodeId) {\n return fail(\"validate_input\", 400, \"need file_key and frame_node_id\");\n }\n nodeId = String(nodeId).replace(/-/g, \":\");\n\n const token = Deno.env.get(\"FIGMA_READ_TOKEN\");\n if (!token) return fail(\"config\", 500, \"FIGMA_READ_TOKEN not set\");\n const FH = { \"X-Figma-Token\": token };\n\n // ---- 1. render the frame PNG + 2. fetch the node tree (in parallel) -------\n let frameImageUrl = \"\";\n let doc: any;\n try {\n const [imgR, nodesR] = await Promise.all([\n fetch(\n `https://api.figma.com/v1/images/${fileKey}?ids=${\n encodeURIComponent(nodeId)\n }&format=png&scale=${scale}`,\n { headers: FH },\n ),\n fetch(\n `https://api.figma.com/v1/files/${fileKey}/nodes?ids=${\n encodeURIComponent(nodeId)\n }`,\n { headers: FH },\n ),\n ]);\n const imgT = await imgR.text();\n if (!imgR.ok) return fail(\"figma_render\", imgR.status, imgT.slice(0, 400));\n frameImageUrl = JSON.parse(imgT)?.images?.[nodeId] || \"\";\n if (!frameImageUrl) {\n return fail(\"figma_render\", 502, \"no image url returned for node\");\n }\n\n const nodesT = await nodesR.text();\n if (!nodesR.ok) {\n return fail(\"figma_get\", nodesR.status, nodesT.slice(0, 400));\n }\n doc = JSON.parse(nodesT)?.nodes?.[nodeId]?.document;\n if (!doc) return fail(\"figma_get\", 404, \"node not found: \" + nodeId);\n } catch (e) {\n return fail(\"figma_fetch\", 502, \"Figma fetch threw: \" + String(e));\n }\n\n const frameBox = doc.absoluteBoundingBox\n ? {\n x: Math.round(doc.absoluteBoundingBox.x),\n y: Math.round(doc.absoluteBoundingBox.y),\n w: Math.round(doc.absoluteBoundingBox.width),\n h: Math.round(doc.absoluteBoundingBox.height),\n }\n : null;\n if (!frameBox) return fail(\"figma_get\", 500, \"frame has no bounding box\");\n\n // ---- 3. walk the tree, classify content nodes + collect slices ------------\n const visible = (arr: any): any[] =>\n Array.isArray(arr) ? arr.filter((p) => p && p.visible !== false) : [];\n const box = (n: any) =>\n n.absoluteBoundingBox\n ? {\n x: Math.round(n.absoluteBoundingBox.x),\n y: Math.round(n.absoluteBoundingBox.y),\n w: Math.round(n.absoluteBoundingBox.width),\n h: Math.round(n.absoluteBoundingBox.height),\n }\n : null;\n\n const slices: any[] = [];\n const nodes: any[] = []; // flat list of classified content nodes\n const seenGroupBox = new Set(); // dedupe nested identical-box groups\n\n const walk = (n: any, depth: number) => {\n const b = box(n);\n\n if (n.type === \"SLICE\") {\n if (b && b.w > 0 && b.h > 0) {\n slices.push({ id: n.id, name: n.name, box: b });\n }\n return; // slices have no content children we care about\n }\n\n // depth 0 is the frame we rendered — never a content node (its center would\n // otherwise leak into whichever slice sits at the frame's vertical middle).\n if (depth > 0 && b && b.w > 0 && b.h > 0) {\n const fills = visible(n.fills).map((p: any) => p.type);\n const strokes = visible(n.strokes).map((p: any) => p.type);\n const hasImage = fills.includes(\"IMAGE\");\n const hasPaint = fills.some((t: string) =>\n t === \"SOLID\" || t.startsWith(\"GRADIENT\")\n );\n const hasStroke = strokes.length > 0;\n const isContainer = n.type === \"GROUP\" || n.type === \"FRAME\" ||\n n.type === \"INSTANCE\";\n\n let kind = \"\";\n if (n.type === \"TEXT\") kind = \"text\";\n else if (hasImage) kind = \"image\";\n else if (isContainer) kind = \"group\";\n else if (hasPaint || hasStroke) kind = \"shape\"; // buttons, cards, dividers\n // VECTOR / STAR / BOOLEAN etc. (icons, decoration) are skipped for cutting\n\n if (kind) {\n // dedupe nested groups that share the same box (Earth Runners chains):\n // keep the shallowest (first seen in DFS).\n const key = `${b.x},${b.y},${b.w},${b.h}`;\n const dup = kind === \"group\" && seenGroupBox.has(key);\n if (kind === \"group\") seenGroupBox.add(key);\n if (!dup) {\n const rec: any = { id: n.id, type: n.type, kind, box: b };\n if (kind === \"text\") {\n rec.text = String(n.characters || \"\");\n rec.font_size = n.style?.fontSize ?? null;\n }\n if (hasImage) rec.image = true;\n if (hasPaint) rec.fill = true;\n if (hasStroke) rec.stroke = true;\n nodes.push(rec);\n }\n }\n }\n for (const c of (n.children || [])) walk(c, depth + 1);\n };\n walk(doc, 0);\n\n if (slices.length === 0) {\n return fail(\"validate\", 422, \"no SLICE markers found in frame\");\n }\n\n // ---- 4. assign nodes to slices (by center) + build per-slice vision crop --\n const centerIn = (nb: any, sb: any) => {\n const cx = nb.x + nb.w / 2, cy = nb.y + nb.h / 2;\n return cx >= sb.x && cx <= sb.x + sb.w && cy >= sb.y && cy <= sb.y + sb.h;\n };\n\n // wsrv crop of the slice region from the rendered frame, downscaled to visionW.\n const cropUrl = (sb: any) => {\n const cx = Math.round((sb.x - frameBox.x) * scale);\n const cy = Math.round((sb.y - frameBox.y) * scale);\n const cw = Math.round(sb.w * scale);\n const ch = Math.round(sb.h * scale);\n const w = Math.min(cw, visionW);\n return `https://wsrv.nl/?url=${encodeURIComponent(frameImageUrl)}` +\n `&precrop=true&cx=${cx}&cy=${cy}&cw=${cw}&ch=${ch}&w=${w}&output=jpg&q=80`;\n };\n\n // top-to-bottom slice order\n slices.sort((a, b) => a.box.y - b.box.y);\n for (const s of slices) {\n s.image_url = cropUrl(s.box);\n s.nodes = nodes.filter((nd) => centerIn(nd.box, s.box));\n }\n\n return new Response(\n JSON.stringify({\n ok: true,\n stage: \"done\",\n frame_image_url: frameImageUrl,\n frame_box: frameBox,\n scale,\n slices,\n slices_json: JSON.stringify(slices),\n }),\n { headers: { \"content-type\": \"application/json\" } },\n 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default async function (req: Request): Promise {\n const fail = (stage: string, status: number, detail: unknown) =>\n new Response(JSON.stringify({ ok: false, stage, detail }), {\n status,\n headers: { \"content-type\": \"application/json\" },\n });\n\n if (req.headers.get(\"x-auth\") !== Deno.env.get(\"AUTH_TOKEN\")) {\n return fail(\"auth\", 401, \"Invalid or missing x-auth header\");\n }\n\n let inp: any;\n try {\n inp = await req.json();\n } catch (e) {\n return fail(\"parse_input\", 400, \"Body not valid JSON: \" + String(e));\n }\n if (!inp.file_key || !inp.frame_node_id) {\n return fail(\"validate_input\", 400, \"file_key and frame_node_id required\");\n }\n\n const frameId = String(inp.frame_node_id).replaceAll(\"-\", \":\");\n const scale = Number(inp.scale) || 0.6;\n const out = inp.output || \"jpg\";\n const q = inp.q || 85;\n const token = Deno.env.get(\"FIGMA_READ_TOKEN\");\n if (!token) return fail(\"config\", 500, \"FIGMA_READ_TOKEN env var not set\");\n const H = { \"X-Figma-Token\": token };\n\n // 1) nodes (geometry + text)\n let frame: any;\n try {\n const r = await fetch(\n `https://api.figma.com/v1/files/${inp.file_key}/nodes?ids=${frameId}`,\n { headers: H },\n );\n const t = await r.text();\n if (!r.ok) return fail(\"get_nodes\", r.status, t);\n let parsed: any;\n try {\n parsed = JSON.parse(t);\n } catch (e) {\n return fail(\"parse_nodes\", 502, \"Non-JSON: \" + t.slice(0, 500));\n }\n frame = parsed?.nodes?.[frameId]?.document;\n if (!frame?.absoluteBoundingBox) {\n return fail(\n \"get_nodes\",\n 404,\n `frame '${frameId}' not found or has no bounds`,\n );\n }\n } catch (e) {\n return fail(\"get_nodes\", 502, \"GET nodes threw: \" + String(e));\n }\n\n // 2) render full frame\n let frameUrl: string | null = null;\n try {\n const r = await fetch(\n `https://api.figma.com/v1/images/${inp.file_key}?ids=${frameId}&format=png&scale=${scale}`,\n { headers: H },\n );\n const t = await r.text();\n if (!r.ok) return fail(\"render_frame\", r.status, t);\n frameUrl = JSON.parse(t)?.images?.[frameId] ?? null;\n if (!frameUrl) {\n return fail(\n \"render_frame\",\n 502,\n \"Figma returned null image (frame too complex/large at this scale, or render failed)\",\n );\n }\n } catch (e) {\n return fail(\"render_frame\", 502, \"Render threw: \" + String(e));\n }\n\n // 3) collect slices + text, compute crop + alt\n try {\n const fb = frame.absoluteBoundingBox;\n const slices: any[] = [], texts: any[] = [];\n const walk = (n: any) => {\n if (!n) return;\n const bb = n.absoluteBoundingBox;\n if (n.type === \"SLICE\" && bb) slices.push({ id: n.id, name: n.name, bb });\n if (n.type === \"TEXT\" && bb && n.characters) {\n texts.push({ chars: n.characters, size: n.style?.fontSize || 0, bb });\n }\n (n.children || []).forEach(walk);\n };\n walk(frame);\n\n // top-to-bottom order\n slices.sort((a, b) => (a.bb.y - b.bb.y) || (a.bb.x - b.bb.x));\n\n const centerIn = (t: any, s: any) => {\n const cx = t.bb.x + t.bb.width / 2, cy = t.bb.y + t.bb.height / 2;\n return cx >= s.bb.x && cx <= s.bb.x + s.bb.width && cy >= s.bb.y &&\n cy <= s.bb.y + s.bb.height;\n };\n\n const result = slices.map((s, i) => {\n const cx = Math.round((s.bb.x - fb.x) * scale);\n const cy = Math.round((s.bb.y - fb.y) * scale);\n const cw = Math.round(s.bb.width * scale);\n const ch = Math.round(s.bb.height * scale);\n const within = texts.filter((t) => centerIn(t, s)).sort((a, b) =>\n b.size - a.size\n );\n const alt = within.length\n ? within[0].chars.trim().replace(/\\s+/g, \" \")\n : \"\";\n const wsrv_url = `https://wsrv.nl/?url=${\n encodeURIComponent(frameUrl!)\n }&cx=${cx}&cy=${cy}&cw=${cw}&ch=${ch}&output=${out}&q=${q}`;\n return { id: s.id, order: i + 1, alt, cx, cy, cw, ch, wsrv_url };\n });\n\n return new Response(\n JSON.stringify({\n ok: true,\n stage: \"done\",\n frame_image_url: frameUrl,\n scale,\n slice_count: result.length,\n slices: result,\n }),\n { headers: { \"content-type\": \"application/json\" } },\n );\n } catch (e) {\n return fail(\"compute\", 500, \"Compute failed: \" + String(e));\n }\n}","label",[131],"6e8d6f14-4a30-42da-af90-3e13ef715a3e",["D",1781118522498],4,[28],"e0e41a1f-968d-4e1a-80ec-7ece71096654","figma_prep.ts","19bf851e-6346-11f1-903c-1607ee4eb77e",18,["D",1780980289387],9,"export default async function (req: Request): Promise {\n const fail = (stage: string, status: number, detail: unknown) =>\n new Response(JSON.stringify({ ok: false, stage, detail }), {\n status,\n headers: { \"content-type\": \"application/json\" },\n });\n\n if (req.headers.get(\"x-auth\") !== Deno.env.get(\"AUTH_TOKEN\")) {\n return fail(\"auth\", 401, \"Invalid or missing x-auth header\");\n }\n\n let inp: any;\n try {\n inp = await req.json();\n } catch (e) {\n return fail(\"parse_input\", 400, \"Body not valid JSON: \" + String(e));\n }\n if (!inp.file_key || !inp.frame_node_id) {\n return fail(\"validate_input\", 400, \"file_key and frame_node_id required\");\n }\n\n const frameId = String(inp.frame_node_id).replaceAll(\"-\", \":\");\n const scale = Math.min(4, Math.max(0.01, Number(inp.scale) || 0.6));\n const token = Deno.env.get(\"FIGMA_READ_TOKEN\");\n if (!token) return fail(\"config\", 500, \"FIGMA_READ_TOKEN not set\");\n const H = { \"X-Figma-Token\": token };\n const rb = (bb: any) => ({\n x: Math.round(bb.x),\n y: Math.round(bb.y),\n w: Math.round(bb.width),\n h: Math.round(bb.height),\n });\n\n // 1) nodes\n let frame: any;\n try {\n const r = await fetch(\n `https://api.figma.com/v1/files/${inp.file_key}/nodes?ids=${frameId}`,\n { headers: H },\n );\n const t = await r.text();\n if (!r.ok) return fail(\"get_nodes\", r.status, t);\n let parsed: any;\n try {\n parsed = JSON.parse(t);\n } catch (e) {\n return fail(\"parse_nodes\", 502, \"Non-JSON: \" + t.slice(0, 500));\n }\n frame = parsed?.nodes?.[frameId]?.document;\n if (!frame?.absoluteBoundingBox) {\n return fail(\"get_nodes\", 404, `frame '${frameId}' not found / no bounds`);\n }\n } catch (e) {\n return fail(\"get_nodes\", 502, \"GET nodes threw: \" + String(e));\n }\n\n // 2) render frame\n let frameUrl: string | null = null;\n try {\n const r = await fetch(\n `https://api.figma.com/v1/images/${inp.file_key}?ids=${frameId}&format=png&scale=${scale}`,\n { headers: H },\n );\n const t = await r.text();\n if (!r.ok) return fail(\"render_frame\", r.status, t);\n frameUrl = JSON.parse(t)?.images?.[frameId] ?? null;\n if (!frameUrl) {\n return fail(\n \"render_frame\",\n 502,\n \"Figma returned null image (frame too complex/large at this scale)\",\n );\n }\n } catch (e) {\n return fail(\"render_frame\", 502, \"Render threw: \" + String(e));\n }\n\n // 3) collect SLICES + content; assign by geometry; add per-slice crop image for vision\n try {\n const fb = frame.absoluteBoundingBox;\n const slices: any[] = [];\n const content: any[] = [];\n const hasImg = (n: any) =>\n Array.isArray(n.fills) &&\n n.fills.some((f: any) => f.type === \"IMAGE\" && f.visible !== false);\n\n const walk = (n: any) => {\n if (!n) return;\n const bb = n.absoluteBoundingBox;\n if (bb) {\n if (n.type === \"SLICE\") {\n slices.push({ id: n.id, name: n.name, box: rb(bb), elements: [] });\n } else {\n const isText = n.type === \"TEXT\" && n.characters;\n const img = hasImg(n);\n if (isText || img) {\n const el: any = { id: n.id, type: n.type, box: rb(bb) };\n if (isText) {\n el.text = n.characters.trim().replace(/\\s+/g, \" \");\n el.font_size = n.style?.fontSize || 0;\n }\n if (img) el.has_image = true;\n content.push(el);\n }\n }\n }\n (n.children || []).forEach(walk);\n };\n walk(frame);\n\n const centerIn = (el: any, s: any) => {\n const cx = el.box.x + el.box.w / 2, cy = el.box.y + el.box.h / 2;\n return cx >= s.box.x && cx <= s.box.x + s.box.w && cy >= s.box.y &&\n cy <= s.box.y + s.box.h;\n };\n for (const s of slices) {\n s.elements = content.filter((el) => centerIn(el, s));\n }\n slices.sort((a, b) => (a.box.y - b.box.y) || (a.box.x - b.box.x));\n\n // per-slice crop image (vision input for the planner)\n const sliceCropUrl = (box: any) => {\n const cx = Math.round((box.x - fb.x) * scale);\n const cy = Math.round((box.y - fb.y) * scale);\n const cw = Math.round(box.w * scale);\n const ch = Math.round(box.h * scale);\n return `https://wsrv.nl/?url=${\n encodeURIComponent(frameUrl!)\n }&cx=${cx}&cy=${cy}&cw=${cw}&ch=${ch}&output=jpg&q=85`;\n };\n for (const s of slices) s.image_url = sliceCropUrl(s.box);\n\n return new Response(\n JSON.stringify({\n ok: true,\n stage: \"done\",\n frame_image_url: frameUrl,\n scale,\n frame_box: rb(fb),\n slice_count: slices.length,\n slices,\n slices_json: JSON.stringify(slices),\n }),\n { headers: { \"content-type\": \"application/json\" } },\n );\n } catch (e) {\n return fail(\"collect\", 500, \"Collect failed: \" + String(e));\n }\n}",[146],"d5454654-2d22-4763-98b9-1e619be5c85c","figma_inspect.ts","a880c65a-64f9-11f1-a655-1607ee4eb77e",22,["D",1781115930223],3,"// figma_inspect — V2 foundation / diagnostic.\n// Dumps the Figma node tree for a frame so we can see exactly what\n// figma_prep-v2 must capture: node TYPE, auto-layout MODE, FILLS/STROKES\n// (→ button & card boxes), and absolute BOUNDING BOX (→ tile boxes via groups).\n//\n// POST { \"file_key\": \"...\", \"frame_node_id\": \"123:456\" } (accepts 123-456 too)\n// Header: x-auth: \n// Reuses the same Figma credential as figma_prep: env FIGMA_READ_TOKEN.\nexport default async function (req: Request): Promise {\n const fail = (stage: string, status: number, detail: unknown) =>\n new Response(JSON.stringify({ ok: false, stage, detail }), {\n status,\n headers: { \"content-type\": \"application/json\" },\n });\n\n if (req.headers.get(\"x-auth\") !== Deno.env.get(\"AUTH_TOKEN\")) {\n return fail(\"auth\", 401, \"Invalid or missing x-auth header\");\n }\n\n let inp: any;\n try {\n inp = await req.json();\n } catch (e) {\n return fail(\"parse_input\", 400, \"Body not valid JSON: \" + String(e));\n }\n\n const fileKey = inp.file_key;\n let nodeId = inp.frame_node_id || inp.node_id;\n if (!fileKey || !nodeId) {\n return fail(\"validate_input\", 400, \"need file_key and frame_node_id\");\n }\n nodeId = String(nodeId).replace(/-/g, \":\"); // accept 123-456 or 123:456\n\n const token = Deno.env.get(\"FIGMA_READ_TOKEN\");\n if (!token) return fail(\"config\", 500, \"FIGMA_READ_TOKEN not set\");\n\n // ---- fetch the node subtree -------------------------------------------\n let doc: any;\n try {\n const r = await fetch(\n `https://api.figma.com/v1/files/${fileKey}/nodes?ids=${\n encodeURIComponent(nodeId)\n }`,\n { headers: { \"X-Figma-Token\": token } },\n );\n const t = await r.text();\n if (!r.ok) return fail(\"figma_get\", r.status, t.slice(0, 500));\n const j = JSON.parse(t);\n doc = j?.nodes?.[nodeId]?.document;\n if (!doc) {\n return fail(\n \"figma_get\",\n 404,\n `node ${nodeId} not found (returned keys: ${\n Object.keys(j?.nodes || {}).join(\",\")\n })`,\n );\n }\n } catch (e) {\n return fail(\"figma_get\", 502, \"Figma GET threw: \" + String(e));\n }\n\n // ---- walk the tree -----------------------------------------------------\n // visible solid/gradient/image paint types on a node\n const paint = (arr: any): string[] =>\n Array.isArray(arr)\n ? arr.filter((p) => p && p.visible !== false).map((p) => p.type)\n : [];\n const box = (n: any) =>\n n.absoluteBoundingBox\n ? {\n x: Math.round(n.absoluteBoundingBox.x),\n y: Math.round(n.absoluteBoundingBox.y),\n w: Math.round(n.absoluteBoundingBox.width),\n h: Math.round(n.absoluteBoundingBox.height),\n }\n : null;\n\n const flat: any[] = [];\n const lines: string[] = [];\n\n const walk = (n: any, depth: number) => {\n const fills = paint(n.fills);\n const strokes = paint(n.strokes);\n const b = box(n);\n flat.push({\n depth,\n id: n.id,\n type: n.type,\n name: n.name,\n layoutMode: n.layoutMode ?? null, // FRAME only: NONE / HORIZONTAL / VERTICAL\n fills,\n strokes,\n text: n.type === \"TEXT\"\n ? String(n.characters || \"\").slice(0, 60)\n : undefined,\n box: b,\n });\n\n const tags = [\n n.type,\n n.layoutMode && n.layoutMode !== \"NONE\"\n ? `AUTOLAYOUT:${n.layoutMode}`\n : null,\n fills.length ? `fill:${fills.join(\"/\")}` : null,\n strokes.length ? `stroke:${strokes.join(\"/\")}` : null,\n b ? `[${b.w}x${b.h} @${b.x},${b.y}]` : null,\n ].filter(Boolean).join(\" \");\n lines.push(`${\" \".repeat(depth)}${n.name} — ${tags}`);\n\n for (const c of (n.children || [])) walk(c, depth + 1);\n };\n walk(doc, 0);\n\n // ---- verdicts on the two V2 questions ---------------------------------\n const anyAutoLayout = flat.some((r) =>\n r.layoutMode && r.layoutMode !== \"NONE\"\n );\n const filledRects = flat.filter(\n (r) => (r.type === \"RECTANGLE\" || r.type === \"FRAME\") && r.fills.length,\n );\n const groups = flat.filter((r) => r.type === \"GROUP\");\n\n const summary = {\n root: doc.name,\n node_count: flat.length,\n uses_auto_layout: anyAutoLayout, // false here = plain groups, expected\n filled_box_candidates: filledRects.length, // → button/card boxes (the V1 blind spot)\n group_count: groups.length, // → tile boxes come from these\n type_counts: flat.reduce(\n (m: any, r) => ((m[r.type] = (m[r.type] || 0) + 1), m),\n {},\n ),\n };\n\n return new Response(\n JSON.stringify({ ok: true, summary, tree: lines, nodes: flat }, null, 2),\n { headers: { \"content-type\": \"application/json\" } },\n );\n}",[154],"pulls","branches",1,"forks","envVars",{"_169":171,"_172":61},"connections",{"_169":61,"_170":61},"count","unfilledCount",2,"emptyCount",{"_43":153,"_32":154,"_30":155,"_133":-5,"_41":42,"_40":156,"_135":121,"_38":187,"_13":158,"_33":34,"_35":159,"_24":25,"_139":-5,"_178":188,"_27":189},{"_43":145,"_32":146,"_30":147,"_133":-5,"_41":42,"_40":148,"_135":121,"_38":184,"_13":150,"_33":34,"_35":151,"_24":25,"_139":-5,"_178":185,"_27":186},{"_43":141,"_32":28,"_30":31,"_133":-5,"_41":42,"_40":14,"_135":25,"_38":181,"_13":143,"_33":34,"_35":37,"_24":25,"_139":-5,"_178":182,"_27":183},{"_43":130,"_32":131,"_30":132,"_133":-5,"_41":42,"_40":134,"_135":121,"_38":177,"_13":137,"_33":34,"_35":138,"_24":25,"_139":-5,"_178":179,"_27":180},["D",1780928419595],"children",[],[131],["D",1781118522498],[],[28],["D",1780980289387],[],[146],["D",1781115930223],[],[154],["D",1780906587974],{"_95":94,"_103":99},{"_95":94,"_96":97,"_98":99,"_18":55,"_100":101,"_102":25},{"_13":84,"_32":85,"_43":42,"_86":44,"_87":-5,"_88":-5,"_89":-5,"_90":-5,"_91":-5,"_92":45,"_93":94},"ctx",{"_77":-5,"_123":227,"_228":229,"_230":231,"_232":25,"_233":25,"_234":25,"_235":121,"_236":-5,"_237":-7,"_238":-7,"_239":61,"_240":25,"_241":25,"_242":-5,"_243":25,"_244":25,"_245":25,"_246":-5},"ENV",{"_198":199,"_200":201,"_202":85,"_203":204,"_205":206,"_207":208,"_209":210,"_211":212,"_213":214,"_215":216,"_217":218,"_219":220,"_221":222,"_223":224,"_225":226},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","RENDER_GIT_COMMIT","e87eb04e707cf64e7e532c8e8ec395f209e17f15","RENDER_GIT_BRANCH","POSTHOG_API_TOKEN","phc_nmoyuAkStEZuUp69rYlg1DZgrIt19Gx0Y4Hwf8tGgJP","POSTHOG_API_HOST","https://wart.val.town","WEB_API_TEMPLATE","https://{val}.web.val.run","APP_URL","https://www.val.town","MODULE_URL","https://esm.town","VANITY_WEB_API_TEMPLATE","https://{label}.val.run/","DENOLS_URL","https://lsp.val.town","NODE_ENV","production","CLOUDFLARE_TURNSTILE_SITE_KEY","0x4AAAAAACtaIZJH7s9rBMZ6","GOOGLE_CLIENT_ID","875989696899-jtsqkhlbdv5jrlsk8631p7ipjg3c6o62.apps.googleusercontent.com","STRIPE_PUBLISHABLE_KEY","pk_live_51N2zvWEpZTTLipIkVEwXrUG9AT0yeOOEYxszarZT1jpsZV58Ly6wlg3SltZpHN26CUalOBmUSY7adQRQiSkCZz2500qSXNkf8Y","API_URL","https://api.val.town",[],"preferencesKeybindings","default","preferencesTheme","light","preferencesFixers","preferencesCopilot","preferencesSelectionAi","preferencesCloseBrackets","preferencesChatPanelState","preferencesDprint","preferencesDenofmt","notificationCount","flagDenols","isBusinessOrgMember","businessOrgHandle","isBusinessOrgAdmin","isHigherTownieTier","navCollapsed","currentOrgId"]

Diff · v27