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process from \"node:process\";\n\nconst GEMINI_API_KEY = Deno.env.get(\"GEMINI_API_KEY\") || \"\";\nconst GEMINI_API_KEY2 = Deno.env.get(\"GEMINI_API_KEY2\") || \"\";\nconst GEMINI_API_KEY3 = Deno.env.get(\"GEMINI_API_KEY3\") || \"\";\nconst GEMINI_API_KEY4 = Deno.env.get(\"GEMINI_API_KEY4\") || \"\";\nconst GROQ_API_KEY = Deno.env.get(\"GROQ_API_KEY\") || \"\";\nconst GROQ_API_KEY2 = Deno.env.get(\"GROQ_API_KEY2\") || \"\";\nconst GROQ_API_KEY3 = Deno.env.get(\"GROQ_API_KEY3\") || \"\";\nconst OPENROUTER_API_KEY = Deno.env.get(\"OPENROUTER_API_KEY\") || \"\";\nconst OPENROUTER_API_KEY2 = Deno.env.get(\"OPENROUTER_API_KEY2\") || \"\";\nconst OPENROUTER_API_KEY3 = Deno.env.get(\"OPENROUTER_API_KEY3\") || \"\";\nconst POE_API_KEY1 = Deno.env.get(\"POE_API_KEY1\") || \"\";\nconst POE_API_KEY2 = Deno.env.get(\"POE_API_KEY2\") || \"\";\nconst POE_API_KEY3 = Deno.env.get(\"POE_API_KEY3\") || \"\";\n\nconst BASE_COST = 1200;\nconst BOT_ACCESS_KEY = Deno.env.get(\"BOT_ACCESS_KEY\") || \"\";\n\nconst GEMINI_KEYS = [GEMINI_API_KEY, GEMINI_API_KEY2, GEMINI_API_KEY3, GEMINI_API_KEY4].filter(k => k);\nconst GROQ_KEYS = [GROQ_API_KEY, GROQ_API_KEY2, GROQ_API_KEY3].filter(k => k);\nconst OPENROUTER_KEYS = [OPENROUTER_API_KEY, OPENROUTER_API_KEY2, OPENROUTER_API_KEY3].filter(k => k);\n\nconst GROQ_MODELS = [\n 'moonshotai/kimi-k2-instruct',\n 'groq/compound',\n 'groq/compound-mini'\n];\n\nconst OPENROUTER_MODELS = [\n 'moonshotai/kimi-k2:free',\n 'moonshotai/kimi-k2',\n 'moonshotai/kimi-k2-0905'\n];\n\nfunction compressText(text: string): string {\n return text.split('\\n').map(line => line.trim()).filter(line => line.length > 0).join(' ');\n}\n\nasync function parseFileLocally(url: string, contentType: string): Promise {\n try {\n const response = await fetch(url);\n const buffer = await response.arrayBuffer();\n \n // Handle text-based files\n if (contentType.startsWith('text/') || \n contentType === 'application/json' ||\n contentType === 'application/javascript' ||\n contentType === 'application/xml') {\n const text = new TextDecoder().decode(buffer);\n return compressText(text);\n }\n \n // Handle PDF files\n if (contentType === 'application/pdf') {\n // Note: For production, you'd want to use a proper PDF parser\n // For now, we'll just indicate it's a PDF\n return \"[PDF file content - requires PDF parser library]\";\n }\n \n // Handle document files (if you have parsers available)\n if (contentType.includes('word') || contentType.includes('document')) {\n return \"[Document file - requires document parser library]\";\n }\n \n if (contentType.includes('spreadsheet') || contentType.includes('excel')) {\n return \"[Spreadsheet file - requires spreadsheet parser library]\";\n }\n \n // For binary files, return a description\n return `[Binary file of type ${contentType}]`;\n } catch (error) {\n console.error(\"Error parsing file:\", error);\n return `[Error parsing file: ${error.message}]`;\n }\n}\n\nasync function callGemini(content: string, mediaUrl?: string, mediaType?: string, keyIndex = 0): Promise {\n if (keyIndex >= GEMINI_KEYS.length) {\n throw new Error(\"All Gemini API keys exhausted\");\n }\n \n const apiKey = GEMINI_KEYS[keyIndex];\n const isMedia = mediaUrl && (mediaType?.startsWith('image/') || mediaType?.startsWith('video/') || mediaType?.startsWith('audio/'));\n let parts: any[] = [];\n \n if (isMedia && mediaUrl) {\n const mediaResponse = await fetch(mediaUrl);\n const mediaBuffer = await mediaResponse.arrayBuffer();\n const base64Data = btoa(String.fromCharCode(...new Uint8Array(mediaBuffer)));\n parts = [\n { text: content },\n { inline_data: { mime_type: mediaType, data: base64Data } }\n ];\n } else {\n parts = [{ text: content }];\n }\n \n try {\n const response = await fetch(`https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-exp:generateContent?key=${apiKey}`, {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify({ contents: [{ parts }] })\n });\n \n if (!response.ok) {\n throw new Error(`Gemini API error: ${response.status}`);\n }\n \n const data = await response.json();\n return data.candidates?.[0]?.content?.parts?.[0]?.text || \"No response from AI\";\n } catch (error) {\n console.error(`Gemini key ${keyIndex + 1} failed:`, error.message);\n return callGemini(content, mediaUrl, mediaType, keyIndex + 1);\n }\n}\n\nasync function callGroq(content: string, keyIndex = 0, modelIndex = 0): Promise {\n if (keyIndex >= GROQ_KEYS.length) {\n throw new Error(\"All Groq API keys exhausted\");\n }\n \n const apiKey = GROQ_KEYS[keyIndex];\n const model = GROQ_MODELS[modelIndex];\n \n try {\n const response = await fetch('https://api.groq.com/openai/v1/chat/completions', {\n method: 'POST',\n headers: {\n 'Content-Type': 'application/json',\n 'Authorization': `Bearer ${apiKey}`\n },\n body: JSON.stringify({\n model: model,\n messages: [{ role: 'user', content }]\n })\n });\n \n if (!response.ok) {\n throw new Error(`Groq API error: ${response.status}`);\n }\n \n const data = await response.json();\n return data.choices?.[0]?.message?.content || \"No response from AI\";\n } catch (error) {\n console.error(`Groq key ${keyIndex + 1}, model ${model} failed:`, error.message);\n \n if (modelIndex < GROQ_MODELS.length - 1) {\n return callGroq(content, keyIndex, modelIndex + 1);\n } else if (keyIndex < GROQ_KEYS.length - 1) {\n return callGroq(content, keyIndex + 1, 0);\n } else {\n throw new Error(\"All Groq API keys and models exhausted\");\n }\n }\n}\n\nasync function callOpenRouter(content: string, keyIndex = 0, modelIndex = 0): Promise {\n if (keyIndex >= OPENROUTER_KEYS.length) {\n throw new Error(\"All OpenRouter API keys exhausted\");\n }\n \n const apiKey = OPENROUTER_KEYS[keyIndex];\n const model = OPENROUTER_MODELS[modelIndex];\n \n try {\n const response = await fetch('https://openrouter.ai/api/v1/chat/completions', {\n method: 'POST',\n headers: {\n 'Content-Type': 'application/json',\n 'Authorization': `Bearer ${apiKey}`\n },\n body: JSON.stringify({\n model: model,\n messages: [{ role: 'user', content }]\n })\n });\n \n if (!response.ok) {\n throw new Error(`OpenRouter API error: ${response.status}`);\n }\n \n const data = await response.json();\n return data.choices?.[0]?.message?.content || \"No response from AI\";\n } catch (error) {\n console.error(`OpenRouter key ${keyIndex + 1}, model ${model} failed:`, error.message);\n \n if (modelIndex < OPENROUTER_MODELS.length - 1) {\n return callOpenRouter(content, keyIndex, modelIndex + 1);\n } else if (keyIndex < OPENROUTER_KEYS.length - 1) {\n return callOpenRouter(content, keyIndex + 1, 0);\n } else {\n throw new Error(\"All OpenRouter API keys and models exhausted\");\n }\n }\n}\n\nasync function getResponse(req: Query, send: SendEventFn) {\n send(\"meta\", { content_type: \"text/markdown\" });\n const lastMessage = req.query.at(-1);\n const attachment = lastMessage?.attachments?.[0];\n const userMessage = lastMessage?.content || \"\";\n const compressedUserMessage = compressText(userMessage);\n let finalPrompt = \"\";\n let mediaUrl = \"\";\n let mediaType = \"\";\n \n if (attachment) {\n mediaUrl = attachment.url;\n mediaType = attachment.content_type;\n \n const isMedia = mediaType?.startsWith('image/') || mediaType?.startsWith('video/') || mediaType?.startsWith('audio/');\n \n if (isMedia) {\n // For media files, use Gemini with the media directly\n finalPrompt = `User message: ${compressedUserMessage}\\n\\nAttached file: ${mediaType}`;\n } else {\n // For all other files, parse locally and compress\n send(\"text\", { text: \"📄 Processing attached file...\\n\\n\" });\n const parsedContent = await parseFileLocally(mediaUrl, mediaType);\n const compressedContent = compressText(parsedContent);\n finalPrompt = `User message: ${compressedUserMessage}\\n\\nAttached file content (${mediaType}):\\n${compressedContent}\\n\\nPlease analyze the file content and respond to the user's message.`;\n }\n } else {\n finalPrompt = `User message: ${compressedUserMessage}\\n\\n`;\n }\n \n try {\n let aiResponse = \"\";\n const isMedia = mediaType?.startsWith('image/') || mediaType?.startsWith('video/') || mediaType?.startsWith('audio/');\n \n // Use Gemini for media files (image, video, audio)\n if (isMedia) {\n if (GEMINI_KEYS.length > 0) {\n aiResponse = await callGemini(finalPrompt, mediaUrl, mediaType);\n } else {\n throw new Error(\"Gemini API key required for media files but not configured\");\n }\n } else {\n // For text/document files and regular text, use text models\n // Try OpenRouter first\n if (OPENROUTER_KEYS.length > 0) {\n try {\n aiResponse = await callOpenRouter(finalPrompt);\n } catch (error) {\n console.error(\"OpenRouter failed, trying Groq:\", error.message);\n if (GROQ_KEYS.length > 0) {\n aiResponse = await callGroq(finalPrompt);\n } else {\n throw new Error(\"No text API keys available\");\n }\n }\n } else if (GROQ_KEYS.length > 0) {\n aiResponse = await callGroq(finalPrompt);\n } else {\n aiResponse = \"No AI API key configured. Please set at least one API key.\";\n }\n }\n \n send(\"text\", { text: aiResponse });\n } catch (error) {\n send(\"error\", { text: `Error: ${error.message}`, allow_retry: true });\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 \n const costLabel = `1200 points`;\n\n return {\n allow_attachments: true,\n expand_text_attachments: false,\n enable_multi_bot_chat_prompting: true,\n enable_suggested_replies: true,\n rate_card: rateCard,\n cost_label: costLabel,\n supports_system_messages: true,\n suggested_replies: true\n };\n}\n\nfunction verifyAccessKey(req: Request): boolean {\n if (!BOT_ACCESS_KEY) {\n console.warn(\"BOT_ACCESS_KEY not configured\");\n return true;\n }\n \n const authHeader = req.headers.get(\"Authorization\");\n if (!authHeader) {\n return false;\n }\n \n const token = authHeader.replace(\"Bearer \", \"\");\n return token === BOT_ACCESS_KEY;\n}\n\ntype BotSettings = {\n allow_attachments?: boolean;\n expand_text_attachments?: boolean;\n enable_multi_bot_chat_prompting?: boolean;\n enable_suggested_replies?: boolean;\n rate_card?: string;\n cost_label?: string;\n supports_system_messages?: boolean;\n suggested_replies?: boolean;\n};\n\ntype Query = {\n version: string;\n type: \"query\";\n query: {\n role: \"system\" | \"user\" | \"bot\";\n content: string;\n content_type: string;\n timestamp: number;\n message_id: string;\n feedback: { type: \"like\" | \"dislike\"; reason?: string }[];\n attachments: {\n url: string;\n content_type: string;\n name: string;\n parsed_content?: string;\n }[];\n }[];\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 (!verifyAccessKey(req)) {\n return new Response(\n JSON.stringify({ error: \"Unauthorized - Invalid or missing access key\" }),\n {\n status: 401,\n headers: { \"Content-Type\": \"application/json\" },\n }\n );\n }\n\n const reqBody = await req.json().catch((e) => {\n console.error(\"body parse error\", e);\n return {};\n });\n \n console.log(\"body\", reqBody);\n \n if (reqBody.type === \"settings\") {\n return new Response(JSON.stringify(await getBotSettings()), {\n status: 200,\n headers: { \"Content-Type\": \"application/json\" },\n });\n }\n \n const body = new ReadableStream({\n start(controller) {\n const send = (event, data) => {\n controller.enqueue(encodeEvent(event, data));\n };\n return getResponse(reqBody, send).catch((e) =>\n console.error(\"get response error\", e)\n ).finally(() => controller.close());\n },\n });\n \n return new Response(body, {\n status: 200,\n headers: { \"Content-Type\": \"text/event-stream\" },\n });\n}","deleted","label",[103],"permalink","https://www.val.town/x/MadeiInGermany/Kimi-K2-0905-Vers-03/code/main.tsx","extension","actionData","errors"]