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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\nfunction calculateInputCost(messages: any[]): number {\n const totalInputChars = messages.reduce((total, msg) => {\n return total + (msg.content?.length || 0);\n }, 0);\n return Math.ceil(totalInputChars * INPUT_COST_PER_CHAR);\n}\n\nfunction calculateOutputCost(outputText: string): number {\n return Math.ceil(outputText.length * OUTPUT_COST_PER_CHAR);\n}\n\nasync function authorizeCost(send: SendEventFn, amount: number, description: string): Promise {\n send(\"authorize_cost\", {\n amount_usd_milli_cents: amount,\n description: description\n });\n}\n\nasync function captureCost(send: SendEventFn, amount: number, description: string): Promise {\n send(\"capture_cost\", {\n amount_usd_milli_cents: amount,\n description: description\n });\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\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: `Analyze 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\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\n if (!response.ok) {\n const errorText = await response.text().catch(() => \"Unknown error\");\n throw new Error(`API failed: ${response.status} - ${errorText}`);\n }\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\n const payload = {\n contents: [\n {\n parts: [\n {\n text: `Analyze video ${attachment.name}`\n },\n {\n inline_data: {\n mime_type: mimeType,\n data: base64Data\n }\n }\n ]\n }\n ],\n generationConfig: {\n temperature: 0.7,\n maxOutputTokens: 2048,\n }\n };\n\n const response = await fetch(`https://generativelanguage.googleapis.com/v1beta/models/gemini-flash-latest:generateContent?key=${process.env.GEMINI_API_KEY}`, {\n method: 'POST',\n headers: {\n 'Content-Type': 'application/json',\n },\n body: JSON.stringify(payload),\n });\n\n if (!response.ok) {\n const errorText = await response.text().catch(() => \"Unknown error\");\n throw new Error(`API failed: ${response.status} - ${errorText}`);\n }\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\n const payload = {\n contents: [\n {\n parts: [\n {\n text: `Analyze image detailed ${attachment.name}. What can you see?`\n },\n {\n inline_data: {\n mime_type: mimeType,\n data: base64Data\n }\n }\n ]\n }\n ],\n generationConfig: {\n temperature: 0.7,\n maxOutputTokens: 2048,\n }\n };\n\n const response = await fetch(`https://generativelanguage.googleapis.com/v1beta/models/gemini-flash-latest:generateContent?key=${process.env.GEMINI_API_KEY}`, {\n method: 'POST',\n headers: {\n 'Content-Type': 'application/json',\n },\n body: JSON.stringify(payload),\n });\n\n if (!response.ok) {\n const errorText = await response.text().catch(() => \"Unknown error\");\n throw new Error(`API failed: ${response.status} - ${errorText}`);\n }\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 const imageExtensions = ['.jpeg', '.jpg', '.png', '.webp', '.heic'];\n if (imageExtensions.some(ext => lowerFileName.endsWith(ext))) {\n return { type: 'image', isSupported: true };\n }\n const videoExtensions = ['.webm'];\n if (videoExtensions.some(ext => lowerFileName.endsWith(ext))) {\n return { type: 'video', isSupported: true };\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 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 if (lowerFileName.endsWith('.pdf')) {\n return { type: 'pdf', isSupported: true };\n }\n const allImageExtensions = [...imageExtensions, '.gif', '.bmp', '.tiff', '.svg'];\n const allVideoExtensions = [...videoExtensions, '.mp4', '.avi', '.mov', '.mkv'];\n if (allImageExtensions.some(ext => lowerFileName.endsWith(ext))) {\n return { type: 'image', isSupported: false };\n }\n if (allVideoExtensions.some(ext => lowerFileName.endsWith(ext))) {\n return { type: 'video', isSupported: false };\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\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\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\n let fileAnalysisResults = \"\";\n let hasFiles = false;\n let processedFileCount = 0;\n\n // Calculate estimated costs\n const inputCost = calculateInputCost(req.query);\n let estimatedFileCost = 0;\n let estimatedTotalCost = BASE_COST + inputCost;\n\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\", {\n text: \"Sorry, I can only process supported file formats like JPEG, PNG, WebP, PDF and other text files.\",\n allow_retry: false\n });\n send(\"done\", {});\n return;\n }\n\n hasFiles = true;\n processedFileCount = lastMessage.attachments.length;\n estimatedFileCost = processedFileCount * FILE_PROCESSING_COST;\n estimatedTotalCost += estimatedFileCost;\n\n // Authorize estimated cost before processing\n try {\n await authorizeCost(send, estimatedTotalCost, \"Bot message with file processing\");\n } catch (error) {\n send(\"error\", {\n text: \"Insufficient funds to process this request. Please add more points to your account.\",\n allow_retry: false\n });\n send(\"done\", {});\n return;\n }\n\n send(\"text\", { text: \"Thinking...\\n\\n\" });\n\n for (const attachment of lastMessage.attachments) {\n try {\n const { type } = checkFileType(attachment.name || '');\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}: ${error.message}\\n\\n`;\n }\n }\n }\n }\n\n // If no files, still authorize the base cost\n if (!hasFiles) {\n try {\n await authorizeCost(send, estimatedTotalCost, \"Bot message\");\n } catch (error) {\n send(\"error\", {\n text: \"Insufficient funds to process this request. Please add more points to your account.\",\n allow_retry: false\n });\n send(\"done\", {});\n return;\n }\n }\n\n const messages = req.query.map((msg) => ({\n role: msg.role === \"bot\" ? \"assistant\" : msg.role as \"user\" | \"assistant\" | \"system\",\n content: msg.role === \"user\" && fileAnalysisResults ? `${msg.content}\\n\\nFile Content:\\n${fileAnalysisResults}` : msg.content,\n }));\n\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\n const models = [\n \"moonshotai/kimi-k2-instruct-0905\",\n \"moonshotai/kimi-k2-instruct\",\n \"groq/compound-mini\",\n \"groq/compound\",\n ];\n\n let outputText = \"\";\n let streamingCompleted = false;\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\n try {\n const controller = new AbortController();\n const timeoutId = setTimeout(() => controller.abort(), 30000);\n\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\n clearTimeout(timeoutId);\n\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 \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\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\n reader = response.body.getReader();\n const decoder = new TextDecoder();\n let buffer = \"\";\n\n if (hasFiles) {\n send(\"replace_response\", { text: \"\" });\n }\n\n while (true) {\n const { done, value } = await reader.read();\n if (done) break;\n\n buffer += decoder.decode(value, { stream: true });\n const lines = buffer.split(\"\\n\");\n buffer = lines.pop() || \"\";\n\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\n try {\n const parsed = JSON.parse(data);\n const content = parsed.choices?.[0]?.delta?.content;\n if (content) {\n outputText += 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 streamingCompleted = true;\n }\n } catch (e) {\n console.error(\"Parse error:\", e, \"Data:\", data);\n }\n }\n }\n }\n\n console.log(`Successfully completed with model: ${model}`);\n reader.releaseLock();\n streamingCompleted = true;\n break;\n\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\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\n console.error(`Model ${model} error:`, error.message);\n\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 send(\"done\", {});\n return;\n }\n\n console.warn(`Trying next model after ${model} failed:`, error.message);\n await sleep(1000);\n }\n }\n\n // Capture actual costs after successful completion\n if (outputText) {\n const outputCost = calculateOutputCost(outputText);\n const actualTotalCost = BASE_COST + inputCost + estimatedFileCost + outputCost;\n \n try {\n await captureCost(send, actualTotalCost, \"Bot message completion\");\n } catch (error) {\n console.error(\"Error capturing cost:\", error);\n }\n } else {\n // Capture base costs even if no output\n try {\n await captureCost(send, estimatedTotalCost, \"Bot message attempt\");\n } catch (error) {\n console.error(\"Error capturing cost:\", error);\n }\n }\n\n send(\"done\", {});\n}\n\nasync function getBotSettings(): Promise {\n const rateCard = `Cost overview:\n\n| Type | Rate |\n|------|------|\n| Base Cost | ${BASE_COST} points |\n| Input (file) | ${FILE_PROCESSING_COST} points |\n| Input (text) | ${INPUT_COST_PER_CHAR} points |\n| Output (text) | ${OUTPUT_COST_PER_CHAR} points |`;\n\n const costLabel = `${BASE_COST}+ points`;\n\n return {\n allow_attachments: true,\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, ms));\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 authorize_cost: { amount_usd_milli_cents: number; description: string };\n capture_cost: { amount_usd_milli_cents: number; description: 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\n const authResult = authenticateRequest(req);\n if (!authResult.success) {\n console.error(\"Authentication failed:\", authResult.error);\n return new Response(JSON.stringify({\n error: \"Authentication failed\",\n details: authResult.error\n }), {\n status: 401,\n headers: {\n \"Content-Type\": \"application/json\",\n \"Access-Control-Allow-Origin\": \"*\"\n },\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({\n error: \"Invalid JSON in request body\"\n }), {\n status: 400,\n headers: {\n \"Content-Type\": \"application/json\",\n \"Access-Control-Allow-Origin\": \"*\"\n },\n });\n }\n\n console.log(\"Authenticated request body:\", JSON.stringify(reqBody, null, 2));\n\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({\n error: \"Failed to get bot settings\"\n }), {\n status: 500,\n headers: {\n \"Content-Type\": \"application/json\",\n \"Access-Control-Allow-Origin\": \"*\"\n },\n });\n }\n }\n\n if (!reqBody.query || !Array.isArray(reqBody.query)) {\n return new Response(JSON.stringify({\n error: \"Invalid query format\"\n }), {\n status: 400,\n headers: {\n \"Content-Type\": \"application/json\",\n \"Access-Control-Allow-Origin\": \"*\"\n },\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\n return getResponse(reqBody as Query, send)\n .catch((e) => {\n console.error(\"Get response error:\", e);\n send(\"error\", {\n text: `Internal error: ${e.message}`,\n allow_retry: true\n });\n })\n .finally(() => {\n try {\n controller.close();\n } catch (e) {\n console.warn(\"Error closing controller:\", e);\n }\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/Kimi-K2-0905-Vers-02/code/main.tsx","extension","actionData","errors"]