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\n\nconst BASE_COST = 2500;\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: `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 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 `Attached audio: ${attachment.name}`; \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: \"The uploaded file is not supported. This bot can only process formats like JPEG, PNG, WebP, PDF and other text files.\", 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 \"llama-4-scout-17b-16e-instruct\",\n \"Llama-3.3-70B-Vers\",\n \"llama-3.1-8b-instant\",\n \"groq/compound-mini\",\n \"groq/compound\",\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(`Success 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: 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)); \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); 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