[{"_1":2,"_181":-5,"_182":-5},"loaderData",{"_3":4,"_96":97},"root",{"_5":6,"_37":38,"_69":70},"ctx",{"_7":8,"_23":-5,"_24":25,"_26":27,"_28":20,"_29":20,"_30":20,"_31":-5,"_32":33,"_34":20,"_35":20,"_36":20},"auth",{"_9":-5,"_10":-5,"_11":-5,"_12":-5,"_13":-5,"_14":-5,"_15":-5,"_16":-5,"_17":-5,"_18":-5,"_19":20,"_21":22},"sessionClaims","sessionId","sessionStatus","userId","actor","orgId","orgRole","orgSlug","orgPermissions","factorVerificationAge","isAuthenticated",false,"tokenType","session_token","user","preferencesKeybindings","default","preferencesTheme","light","preferencesFixers","preferencesCopilot","preferencesSelectionAi","preferencesChatPanelState","notificationCount",0,"flagDenols","isBusinessOrgMember","isHigherTownieTier","ENV",{"_39":40,"_41":42,"_43":44,"_45":46,"_47":48,"_49":50,"_51":52,"_53":54,"_55":56,"_57":58,"_59":60,"_61":62,"_63":64,"_65":66,"_67":68},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","VAL_RUNTIME_NAME","prod","RENDER_GIT_COMMIT","7d99597163ee6d2ecd75e0020d9771df6719deb7","RENDER_GIT_BRANCH","main","CLERK_PUBLISHABLE_KEY","pk_live_Y2xlcmsudmFsLnRvd24k","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","API_URL","https://api.val.town","clerkState",{"_71":72},"__internal_clerk_state",{"_73":74,"_75":48,"_76":77,"_78":77,"_79":20,"_80":77,"_81":77,"_82":77,"_83":77,"_84":85,"_94":20,"_95":20},"__clerk_ssr_state",{"_21":22,"_9":-5,"_10":-5,"_11":-5,"_12":-5,"_13":-5,"_14":-5,"_15":-5,"_16":-5,"_17":-5,"_18":-5,"_19":20},"__publishableKey","__proxyUrl","","__domain","__isSatellite","__signInUrl","__signUpUrl","__afterSignInUrl","__afterSignUpUrl","__clerk_debug",{"_86":20,"_19":20,"_87":77,"_88":89,"_90":77,"_91":48,"_92":20,"_93":77},"isSignedIn","proxyUrl","reason","session-token-and-uat-missing","message","publishableKey","isSatellite","domain","__telemetryDisabled","__telemetryDebug","routes/embed.x.$handle.$name.$",{"_98":99,"_100":101,"_102":103,"_104":105,"_162":163,"_178":179,"_180":-5},"handle","MadeiInGermany","name","GPT-OSS-120b","path","main.tsx","project",{"_106":107,"_100":101,"_108":109,"_110":-5,"_111":20,"_112":113,"_114":115,"_116":117,"_12":118,"_119":120,"_121":122,"_123":-5,"_124":-5,"_125":33,"_14":126,"_127":-5,"_128":-5,"_129":-5,"_130":-5,"_131":132,"_133":132,"_134":135,"_136":135,"_137":135,"_138":132,"_139":132,"_23":140,"_143":144,"_148":149,"_161":20},"id","2a0e6452-253f-11f1-ad75-42dde27851f2","createdAt",["D",1774108864351],"deletedAt","legacyEnvVars","privacy","public","description","https://poe.com/GPT-OSS-120b-Chat","imageUrl","https://imagedelivery.net/iHX6Ovru0O7AjmyT5yZRoA/d3cfb6de-80fd-49f0-24fe-d2d84b3be000/square512","01995b22-1b41-771e-a0ac-a4cfc92d3606","pinnedFileId","019d1120-f001-75ad-9c0c-f47cd3de73b0","pinPreview",true,"pinMigrated","screenshotVersion","likeCount","01995b22-1b41-771e-a0ac-a96f3508eae1","tursoName","tursoHostname","tursoMeasuredAt","pinned","userPerm","r","valPerm","blobPerm","rw","emailPerm","sqlitePerm","projectPerm","telemetryPerm",{"_98":99,"_141":142},"profileImageUrl","https://imagedelivery.net/iHX6Ovru0O7AjmyT5yZRoA/a46b91d4-4b2a-48c3-0c37-9c04ea652a00/square512","org",{"_98":99,"_145":142,"_12":118,"_146":147},"avatar","tier","free","branch",{"_150":151,"_100":46,"_106":152,"_153":107,"_154":-5,"_155":-5,"_156":-5,"_157":-5,"_158":-5,"_159":101,"_160":99},"version",1,"2a1f2ef4-253f-11f1-ad75-42dde27851f2","projectId","forkedBranchId","forkedBranchVersion","forkedProjectPrivacy","forkedProjectId","forkedProjectOrgId","projectName","userHandle","isOwned","file",{"_106":164,"_100":103,"_165":120,"_166":-5,"_167":152,"_168":151,"_169":122,"_108":170,"_150":33,"_171":172,"_173":174,"_175":20,"_176":-5,"_102":177},"2a2423b4-253f-11f1-ad75-42dde27851f2","fileId","parentId","branchId","branchVersion","latest",["D",1774108864351],"fileType","http","content","import process from \"node:process\"; \n\nconst BASE_COST = 400;\nconst K_LENGTH = 32;\n\nfunction authenticateRequest(req: Request): { success: boolean; error?: string } {\n try {\n const expectedBotKey = process.env.BOT_KEY;\n if (!expectedBotKey) { \n return { success: false, error: \"bot key not configured\" };\n } \n if (expectedBotKey.length !== K_LENGTH) { \n return { success: false, error: \"Invalid bot key configuration\" };\n }\n const authHeader = req.headers.get('Authorization'); \n if (!authHeader) {\n return { success: false, error: \"Missing Authorization header\" };\n }\n let providedKey = ''; \n if (authHeader.startsWith('Bearer ')) { \n providedKey = authHeader.substring(7); \n } else if (authHeader.startsWith('BOT_KEY ')) { \n providedKey = authHeader.substring(8); \n } else { \n providedKey = authHeader; \n } \n if (!providedKey) { \n return { success: false, error: \"Invalid Authorization header format\" }; \n } \n if (providedKey.length !== K_LENGTH) { \n return { success: false, error: \"Invalid length\" }; \n } \n if (!constantTimeEquals(providedKey, expectedBotKey)) { \n return { success: false, error: \"Invalid bot key\" }; \n } \n return { success: true }; \n } catch (error) { \n console.error(\"Authentication error:\", error); \n return { success: false, error: \"Authentication failed\" }; \n } \n} \n\nfunction constantTimeEquals(a: string, b: string): boolean { \n if (a.length !== b.length) { \n return false; \n } \n let result = 0; \n for (let i = 0; i < a.length; i++) { \n result |= a.charCodeAt(i) ^ b.charCodeAt(i); \n } \n return result === 0; \n} \n\nasync function processImageWithLlama(attachment: any): Promise { \n try { \n const fileData = await fetch(attachment.url).then(res => res.arrayBuffer()); \n const base64Data = Buffer.from(fileData).toString('base64'); \n const mimeType = attachment.content_type; \n const dataUrl = `data:${mimeType};base64,${base64Data}`; \n const payload = { \n model: \"meta-llama/llama-4-scout-17b-16e-instruct\", \n messages: [ \n {\n role: \"user\", \n content: [ \n { \n type: \"text\", \n text: `Attached image ${attachment.name}` \n }, \n {\n type: \"image_url\", \n image_url: { \n url: dataUrl \n } \n } \n ] \n } \n ], \n max_tokens: 2048, \n temperature: 0.7 \n }; \n const response = await fetch(\"https://api.groq.com/openai/v1/chat/completions\", { \n method: 'POST', \n headers: { \n 'Authorization': `Bearer ${process.env.GROQ_API_KEY}`, \n 'Content-Type': 'application/json', \n }, \n body: JSON.stringify(payload), \n }); \n if (!response.ok) { \n const errorText = await response.text().catch(() => \"Unknown error\"); \n throw new Error(`API failed: ${response.status} - ${errorText}`); \n } \n const result = await response.json(); \n if (result.choices?.[0]?.message?.content) { \n return result.choices[0].message.content; \n } else { \n throw new Error(\"No content returned\"); \n } \n } catch (error) { \n console.error(\"Processing error:\", error); \n throw new Error(`Processing failed: ${error.message}`); \n } \n} \n\nasync function processVideoWithGemini(attachment: any): Promise { \n try { \n const fileData = await fetch(attachment.url).then(res => res.arrayBuffer()); \n const base64Data = Buffer.from(fileData).toString('base64'); \n const mimeType = attachment.content_type; \n const payload = { \n contents: [ \n { \n parts: [ \n { \n text: `Attached video ${attachment.name}` \n }, \n { \n inline_data: { \n mime_type: mimeType, \n data: base64Data \n } \n } \n ] \n } \n ], \n generationConfig: { \n temperature: 0.7, \n maxOutputTokens: 2048, \n } \n }; \n const response = await fetch(`https://generativelanguage.googleapis.com/v1beta/models/gemini-flash-latest:generateContent?key=${process.env.GEMINI_API_KEY}`, { \n method: 'POST', \n headers: { \n 'Content-Type': 'application/json', \n }, \n body: JSON.stringify(payload), \n }); \n if (!response.ok) { \n const errorText = await response.text().catch(() => \"Unknown error\"); \n throw new Error(` API failed: ${response.status} - ${errorText}`); \n } \n const result = await response.json(); \n if (result.candidates?.[0]?.content?.parts?.[0]?.text) { \n return result.candidates[0].content.parts[0].text; \n } else { \n throw new Error(\"No content returned\"); \n } \n } catch (error) { \n console.error(\"Video processing error:\", error); \n throw new Error(`Processing failed: ${error.message}`); \n } \n} \n\nasync function processImageWithGemini(attachment: any): Promise { \n try { \n const fileData = await fetch(attachment.url).then(res => res.arrayBuffer()); \n const base64Data = Buffer.from(fileData).toString('base64'); \n const mimeType = attachment.content_type; \n const payload = { \n contents: [ \n { \n parts: [ \n { \n text: `Attached image ${attachment.name}` \n }, \n { \n inline_data: { \n mime_type: mimeType, \n data: base64Data \n } \n } \n ] \n } \n ], \n generationConfig: { \n temperature: 0.7, \n maxOutputTokens: 2048, \n } \n }; \n const response = await fetch(`https://generativelanguage.googleapis.com/v1beta/models/gemini-flash-latest:generateContent?key=${process.env.GEMINI_API_KEY}`, { \n method: 'POST', \n headers: { \n 'Content-Type': 'application/json', \n }, \n body: JSON.stringify(payload), \n }); \n if (!response.ok) { \n const errorText = await response.text().catch(() => \"Unknown error\"); \n throw new Error(`API failed: ${response.status} - ${errorText}`); \n } \n const result = await response.json(); \n if (result.candidates?.[0]?.content?.parts?.[0]?.text) { \n return result.candidates[0].content.parts[0].text; \n } else { \n throw new Error(\"No content returned\"); \n } \n } catch (error) { \n console.error(\"Processing error:\", error); \n throw new Error(`Processing failed: ${error.message}`); \n } \n} \n\nfunction checkFileType(fileName: string): { type: 'image' | 'video' | 'audio' | 'text' | 'pdf' | 'unsupported', isSupported: boolean } {\n const lowerFileName = fileName.toLowerCase();\n \n const imageExtensions = ['.jpeg', '.jpg', '.png', '.webp', '.heic'];\n if (imageExtensions.some(ext => lowerFileName.endsWith(ext))) {\n return { type: 'image', isSupported: true };\n }\n \n const videoExtensions = ['.webm'];\n if (videoExtensions.some(ext => lowerFileName.endsWith(ext))) {\n return { type: 'video', isSupported: true };\n }\n \n const audioExtensions = ['.mp3', '.wav', '.ogg', '.m4a', '.flac'];\n if (audioExtensions.some(ext => lowerFileName.endsWith(ext))) {\n return { type: 'audio', isSupported: false };\n }\n \n const textExtensions = ['.txt', '.json', '.js', '.ts', '.jsx', '.tsx', '.html', '.css', '.xml', '.md', '.csv'];\n if (textExtensions.some(ext => lowerFileName.endsWith(ext))) {\n return { type: 'text', isSupported: true };\n }\n \n if (lowerFileName.endsWith('.pdf')) {\n return { type: 'pdf', isSupported: true };\n }\n \n // Check if it's an unsupported image/video/audio format\n const allImageExtensions = [...imageExtensions, '.gif', '.bmp', '.tiff', '.svg'];\n const allVideoExtensions = [...videoExtensions, '.mp4', '.avi', '.mov', '.mkv'];\n \n if (allImageExtensions.some(ext => lowerFileName.endsWith(ext))) {\n return { type: 'image', isSupported: false };\n }\n \n if (allVideoExtensions.some(ext => lowerFileName.endsWith(ext))) {\n return { type: 'video', isSupported: false };\n }\n \n return { type: 'unsupported', isSupported: false };\n}\n\nfunction hasUnsupportedFiles(attachments: any[]): boolean {\n return attachments.some(attachment => {\n const fileName = attachment.name || '';\n const { isSupported } = checkFileType(fileName);\n return !isSupported;\n });\n}\n\nasync function processFileAttachment(attachment: any): Promise { \n try { \n if (attachment.parsed_content) { \n return attachment.parsed_content; \n } \n \n const fileName = attachment.name || '';\n const { type, isSupported } = checkFileType(fileName);\n \n if (type === 'image') { \n if (!isSupported) { \n return `Unsupported image format: ${attachment.name}`; \n } \n try { \n return await processImageWithLlama(attachment); \n } catch (llamaError) { \n console.warn(\"Llama processing failed, trying Gemini:\", llamaError.message); \n try { \n return await processImageWithGemini(attachment); \n } catch (geminiError) { \n console.warn(\"Gemini processing also failed:\", geminiError.message); \n return `Image file: ${attachment.name}. Processing failed: ${geminiError.message}`; \n } \n } \n } \n \n if (type === 'audio') { \n return `Audio file: ${attachment.name}. Audio processing is currently unavailable.`; \n } \n \n if (type === 'video') { \n if (!isSupported) { \n return `Unsupported video format: ${attachment.name}`; \n } \n try { \n return await processVideoWithGemini(attachment); \n } catch (geminiError) { \n console.warn(\"Gemini video processing failed:\", geminiError.message); \n return `Video file: ${attachment.name}. Processing failed: ${geminiError.message}`; \n } \n } \n \n if (attachment.url) { \n try { \n const fileResponse = await fetch(attachment.url, { \n headers: { \n \"User-Agent\": \"Mozilla/5.0 (compatible; FileProcessor/1.0)\", \n }, \n }); \n if (fileResponse.ok) { \n if (type === 'text') { \n const textContent = await fileResponse.text(); \n return textContent.substring(0, 2000) + (textContent.length > 2000 ? '...(truncated)' : ''); \n } else if (type === 'pdf') { \n return `PDF file content from ${attachment.name}. Content extraction requires specialized processing.`; \n } else { \n return `Binary file: ${attachment.name}. Unable to extract text content.`; \n } \n } \n } catch (directError) { \n console.warn(\"Direct file processing error:\", directError.message); \n } \n } \n return `File ${attachment.name}. File processing service unavailable.`; \n } catch (error) { \n console.error(\"File processing error:\", error); \n return `File ${attachment.name} - Processing error: ${error.message}`; \n } \n} \n\nasync function getResponse(req: Query, send: SendEventFn) { \n send(\"meta\", { content_type: \"text/markdown\" }); \n let fileAnalysisResults = \"\"; \n let hasFiles = false; \n if (req.query.length > 0) { \n const lastMessage = req.query[req.query.length - 1]; \n if (lastMessage.attachments && lastMessage.attachments.length > 0) { \n if (hasUnsupportedFiles(lastMessage.attachments)) { \n send(\"error\", { text: \"This bot doesn't support file processing.\", allow_retry: false }); \n send(\"done\", {}); \n return; \n } \n hasFiles = true; \n send(\"text\", { text: \"Thinking...\\n\\n\" }); \n for (const attachment of lastMessage.attachments) { \n try { \n const { type } = checkFileType(attachment.name || '');\n \n if (type === 'audio') { \n send(\"text\", { text: `Processing audio file...\\n` }); \n } else if (type === 'video') { \n send(\"text\", { text: `Processing video file...\\n` }); \n } else if (type === 'image') { \n send(\"text\", { text: `Processing image file...\\n` }); \n } \n const analysisResult = await processFileAttachment(attachment); \n fileAnalysisResults += `Content from ${attachment.name}:\\n${analysisResult}\\n\\n`; \n } catch (error) { \n fileAnalysisResults += `Error processing ${attachment.name}: ${error.message}\\n\\n`; \n } \n } \n } \n } \n const messages = req.query.map((msg) => ({ \n role: msg.role === \"bot\" ? \"assistant\" : msg.role as \"user\" | \"assistant\" | \"system\", \n content: msg.role === \"user\" && fileAnalysisResults ? `${msg.content}\\n\\nFile Content:\\n${fileAnalysisResults}` : msg.content, \n })); \n if (hasFiles && messages.length > 0) { \n const systemMessage = { \n role: \"system\" as const, \n content: \"Analyze file\" \n }; \n messages.unshift(systemMessage); \n } \n const models = [ \n \"openai/gpt-oss-120b\",\n \"openai/gpt-oss-20b\",\n \"groq/compound\",\n \"groq/compound-mini\",\n ]; \n for (let i = 0; i < models.length; i++) { \n const model = models[i]; \n let response: Response | null = null; \n let reader: ReadableStreamDefaultReader | null = null; \n try { \n const controller = new AbortController(); \n const timeoutId = setTimeout(() => controller.abort(), 30000); \n response = await fetch(\"https://api.groq.com/openai/v1/chat/completions\", { \n method: \"POST\", \n headers: { \n \"Authorization\": `Bearer ${process.env.GROQ_API_KEY}`, \n \"Content-Type\": \"application/json\", \n }, \n body: JSON.stringify({ \n model: model, \n messages: messages, \n stream: true, \n max_tokens: 2048, \n temperature: 0.7, \n }), \n signal: controller.signal, \n }); \n clearTimeout(timeoutId); \n if (!response.ok) { \n const errorText = await response.text().catch(() => \"Unknown error\"); \n console.error(`Model ${model} failed with status ${response.status}: ${errorText}`); \n if (response.status === 429 && i < models.length - 1) { \n const waitTime = Math.pow(2, i) * 1000; \n console.log(`Rate limited, waiting ${waitTime}ms before trying next model`); \n await sleep(waitTime); \n } \n if (i === models.length - 1) { \n throw new Error(`All models failed. Last error: ${response.status} - ${errorText}`); \n } \n continue; \n } \n if (!response.body) { \n console.warn(`No response body from model ${model}`); \n if (i === models.length - 1) { \n throw new Error(\"No response body from any model\"); \n } \n continue; \n } \n reader = response.body.getReader(); \n const decoder = new TextDecoder(); \n let buffer = \"\"; \n if (hasFiles) { \n send(\"replace_response\", { text: \"\" }); \n } \n while (true) { \n const { done, value } = await reader.read(); \n if (done) break; \n buffer += decoder.decode(value, { stream: true }); \n const lines = buffer.split(\"\\n\"); \n buffer = lines.pop() || \"\"; \n for (const line of lines) { \n if (line.startsWith(\"data: \")) { \n const data = line.slice(6).trim(); \n if (data === \"[DONE]\") continue; \n if (!data) continue; \n try { \n const parsed = JSON.parse(data); \n const content = parsed.choices?.[0]?.delta?.content; \n if (content) { \n send(\"text\", { text: content }); \n } \n const finishReason = parsed.choices?.[0]?.finish_reason; \n if (finishReason) { \n console.log(`Model ${model} finished with reason: ${finishReason}`); \n } \n } catch (e) { \n console.error(\"Parse error:\", e, \"Data:\", data); \n } \n } \n } \n } \n console.log(`Successfully completed with model: ${model}`); \n reader.releaseLock(); \n return; \n } catch (error) { \n if (reader) { \n try { \n reader.releaseLock(); \n } catch (e) { \n console.warn(\"Error releasing reader lock:\", e); \n } \n reader = null; \n } \n if (response?.body) { \n try { \n await response.body.cancel(); \n } catch (e) { \n console.warn(\"Error canceling response body:\", e); \n } \n } \n console.error(`Model ${model} error:`, error.message); \n if (i === models.length - 1) { \n console.error(\"All models failed:\", error); \n send(\"error\", { \n text: `Error: All AI models are currently unavailable. ${error.message}`, \n allow_retry: true, \n }); \n break; \n } \n console.warn(`Trying next model after ${model} failed:`, error.message); \n await sleep(1000); \n } \n } \n send(\"done\", {}); \n} \n\nasync function getBotSettings(): Promise { \n const rateCard = `| Type | Price |\\n` + \n `|------|------|\\n` + \n `| Message Cost | ${BASE_COST} points |\\n`; \n const costLabel = `${BASE_COST} points`; \n return { \n allow_attachments: false, \n expand_text_attachments: true, \n enable_multi_bot_chat_prompting: true, \n rate_card: rateCard, \n cost_label: costLabel, \n supports_system_messages: true,\n suggested_replies: true\n };\n} \n\nconst sleep = (ms: number) => new Promise((resolve) => setTimeout(resolve)); \n\ntype BotSettings = { \n allow_attachments?: boolean; \n expand_text_attachments?: boolean; \n enable_multi_bot_chat_prompting?: boolean; \n rate_card?: string; \n cost_label?: string; \n supports_system_messages?: boolean; \n suggested_replies?: boolean; \n}; \n\ntype Attachment = { \n url: string; \n content_type: string; \n name: string; \n parsed_content?: string; \n}; \n\ntype Message = { \n role: \"system\" | \"user\" | \"bot\"; \n content: string; \n content_type: string; \n timestamp: number; \n message_id: string; \n feedback: { \n type: \"like\" | \"dislike\"; \n reason?: string; \n }[]; \n attachments: Attachment[]; \n}; \n\ntype Query = { \n version: string; \n type: \"query\"; \n query: Message[]; \n message_id: string; \n user_id: string; \n conversation_id: string; \n metadata: string; \n language_code: string; \n}; \n\ntype Events = { \n meta: { content_type: string }; \n text: { text: string }; \n replace_response: { text: string }; \n suggested_reply: { text: string }; \n error: { allow_retry?: boolean; text: string }; \n done: {}; \n}; \n\ntype SendEventFn = ( \n eventName: EventName, \n data: Events[EventName], \n) => void; \n\nfunction encodeEvent(event: string, data: any = {}) { \n return new TextEncoder().encode( \n `event: ${event}\\ndata: ${JSON.stringify(data)}\\n\\n`, \n );\n}\n\nexport default async function (req: Request): Promise { \n if (req.method === 'OPTIONS') { \n return new Response(null, { \n status: 200, \n headers: {\n \"Access-Control-Allow-Origin\": \"*\",\n \"Access-Control-Allow-Methods\": \"POST, OPTIONS\",\n \"Access-Control-Allow-Headers\": \"Content-Type, Authorization\",\n \"Access-Control-Max-Age\": \"86400\",\n },\n });\n }\n const authResult = authenticateRequest(req); \n if (!authResult.success) { \n console.error(\"Authentication failed:\", authResult.error); \n return new Response(JSON.stringify({ error: \"Authentication failed\", details: authResult.error }), { \n status: 401, \n headers: { \n \"Content-Type\": \"application/json\", \n \"Access-Control-Allow-Origin\": \"*\" \n }, \n }); \n } \n let reqBody: any; \n try { \n reqBody = await req.json(); \n } catch (e) { \n console.error(\"Request body parse error:\", e); \n return new Response(JSON.stringify({ error: \"Invalid JSON in request body\" }), { \n status: 400, \n headers: { \n \"Content-Type\": \"application/json\", \n \"Access-Control-Allow-Origin\": \"*\" \n }, \n }); \n } \n console.log(\"Authenticated request body:\", JSON.stringify(reqBody, null, 2)); \n if (reqBody.type === \"settings\") { \n try { \n const settings = await getBotSettings(); \n return new Response(JSON.stringify(settings), { \n status: 200, \n headers: {\n \"Content-Type\": \"application/json\", \n \"Access-Control-Allow-Origin\": \"*\" \n },\n });\n } catch (error) {\n console.error(\"Settings error:\", error); \n return new Response(JSON.stringify({ error: \"Failed to get bot settings\" }), { \n status: 500, \n headers: { \n \"Content-Type\": \"application/json\", \n \"Access-Control-Allow-Origin\": \"*\" \n }, \n }); \n }\n }\n if (!reqBody.query || !Array.isArray(reqBody.query)) { \n return new Response(JSON.stringify({ error: \"Invalid query format\" }), { \n status: 400, \n headers: { \n \"Content-Type\": \"application/json\", \n \"Access-Control-Allow-Origin\": \"*\" \n }, \n }); \n } \n const body = new ReadableStream({ \n start(controller) { \n const send = (event: string, data: any) => { \n try { \n controller.enqueue(encodeEvent(event, data)); \n } catch (e) { \n console.error(\"Error sending event:\", e); \n } \n }; \n return getResponse(reqBody as Query, send) \n .catch((e) => { \n console.error(\"Get response error:\", e); \n send(\"error\", { text: `Internal error: ${e.message}`, allow_retry: true }); \n }) \n .finally(() => { \n try { \n controller.close(); \n } catch (e) { \n console.warn(\"Error closing controller:\", e); \n } \n }); \n }, \n }); \n return new Response(body, { \n status: 200, \n headers: { \n \"Content-Type\": \"text/event-stream\", \n \"Cache-Control\": \"no-cache\", \n \"Connection\": \"keep-alive\", \n \"Access-Control-Allow-Origin\": \"*\", \n \"Access-Control-Allow-Methods\": \"POST, OPTIONS\", \n \"Access-Control-Allow-Headers\": \"Content-Type, Authorization\", \n },\n }); \n}","deleted","label",[103],"permalink","https://www.val.town/x/MadeiInGermany/GPT-OSS-120b/code/main.tsx","extension","actionData","errors"]