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simple poe bot\n\nthings to note:\n- don't put underscores (_) in the name, it stops working\n","deleted","label","children",[],[156],{"_104":176,"_95":99,"_157":177,"_159":-5,"_160":140,"_161":101,"_163":22,"_106":178,"_100":179,"_166":180,"_168":181,"_170":22,"_171":-5,"_172":182,"_98":183},"7ab11df8-92ed-11f0-8744-0224a6c84d84","01995231-7071-77e8-b386-5550d135b081",["D",1758020911165],2,"http","/** ***** Returns a response to the user's query with image generation capabilities *****/\nimport process from \"node:process\";\nconst BASE_COST = 200;\nconst IMAGE_COST = 500;\n\ninterface ModelConfig {\n provider: \"google\" | \"openrouter\";\n model: string;\n endpoint: string;\n headers: Record;\n}\n\nconst MODELS: ModelConfig[] = [\n {\n provider: \"google\",\n model: \"gemini-2.0-flash-exp\",\n endpoint:\n \"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-exp:generateContent\",\n headers: {\n \"Content-Type\": \"application/json\",\n },\n },\n {\n provider: \"google\",\n model: \"gemini-1.5-pro-latest\",\n endpoint:\n \"https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-pro-latest:generateContent\",\n headers: {\n \"Content-Type\": \"application/json\",\n },\n },\n {\n provider: \"google\",\n model: \"gemini-1.5-flash-latest\",\n endpoint:\n \"https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash-latest:generateContent\",\n headers: {\n \"Content-Type\": \"application/json\",\n },\n },\n {\n provider: \"openrouter\",\n model: \"mistralai/mistral-small-3.2-24b-instruct:free\",\n endpoint: \"https://openrouter.ai/api/v1/chat/completions\",\n headers: {\n \"Authorization\": `Bearer ${process.env.OPEN_ROUTER_API_KEY}`,\n \"Content-Type\": \"application/json\",\n \"HTTP-Referer\": process.env.HTTP_REFERER || \"https://localhost:3000\",\n \"X-Title\": \"Gemini Bot\",\n },\n },\n];\n\nconst SHORT_MODEL: ModelConfig = {\n provider: \"google\",\n model: \"gemini-1.5-flash-latest\",\n endpoint:\n \"https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash-latest:generateContent\",\n headers: {\n \"Content-Type\": \"application/json\",\n },\n};\n\nconst COMPOUND_MODEL: ModelConfig = {\n provider: \"google\",\n model: \"gemini-2.0-flash-exp\",\n endpoint:\n \"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-exp:generateContent\",\n headers: {\n \"Content-Type\": \"application/json\",\n },\n};\n\nconst IMAGE_MODEL: ModelConfig = {\n provider: \"google\",\n model: \"gemini-2.5-flash-image-preview\",\n endpoint:\n \"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image-preview:generateContent\",\n headers: {\n \"Content-Type\": \"application/json\",\n },\n};\n\nconst GREETINGS = new Set([\n\"hi\", \"hello\", \"hey\", \"hiya\", \"howdy\", \"greetings\", \"salutations\", \"good morning\", \"good afternoon\", \"good evening\", \n\"good day\", \"what's up\", \"whats up\", \"sup\", \"yo\", \"hola\", \"bonjour\", \"guten tag\", \"heyo\", \"hola\", \"hallo\", \"ciao\",\n]);\n\nconst IMAGE_KEYWORDS = new Set([\n \"generate\", \"create\", \"make\", \"draw\", \"image\", \"picture\", \"photo\", \"illustration\", \n \"artwork\", \"design\", \"visualize\", \"render\", \"sketch\", \"painting\", \"show me\"\n]);\n\nconst FAQ_RESPONSES: Record = {\n \"how are you\": \"I'm functioning optimally and ready to assist with text and image generation.\",\n \"what can you do\":\n \"I provide information, analysis, coding assistance, writing help, problem-solving, and AI image generation across diverse domains.\",\n \"who are you\":\n \"I'm an AI assistant with text and image generation capabilities designed to help with questions, tasks, and visual content creation.\",\n \"what time is it\":\n \"I don't have real-time access. Check your device's clock for current time.\",\n \"what's the weather\":\n \"I can't access live weather data. Use a weather app or service for current conditions.\",\n \"which model are you\":\n \"The underlying model uses Gemini-2.5-Pro for text and Gemini-2.5-Flash-Image-Preview for image generation.\",\n \"help\":\n \"Ask me questions, request explanations, seek coding help, discuss topics, or ask me to generate images.\",\n \"thanks\": \"You're welcome! Happy to help with text or images.\",\n \"thank you\": \"You're welcome! Feel free to ask for text assistance or image generation.\",\n \"bye\": \"Goodbye! Come back anytime you need assistance or image creation.\",\n \"goodbye\": \"Farewell! I'm here whenever you need help with text or visuals.\",\n \"what's your name\":\n \"I'm your AI assistant with image generation capabilities, ready to help with various tasks and visual content.\",\n};\n\nfunction normalizeInput(input: string): string {\n return input.toLowerCase().trim().replace(/[^\\w\\s]/g, \"\");\n}\n\nfunction isGreeting(content: string): boolean {\n const normalized = normalizeInput(content);\n return GREETINGS.has(normalized) ||\n Array.from(GREETINGS).some((greeting) => normalized.includes(greeting));\n}\n\nfunction getFAQResponse(content: string): string | null {\n const normalized = normalizeInput(content);\n return FAQ_RESPONSES[normalized] || null;\n}\n\nfunction isImageRequest(content: string): boolean {\n const normalized = normalizeInput(content);\n return Array.from(IMAGE_KEYWORDS).some(keyword => \n normalized.includes(keyword)\n ) && (\n normalized.includes(\"image\") || \n normalized.includes(\"picture\") || \n normalized.includes(\"photo\") ||\n normalized.includes(\"draw\") ||\n normalized.includes(\"generate\") ||\n normalized.includes(\"create\") ||\n normalized.includes(\"show me\")\n );\n}\n\nfunction shouldUseCompound(\n messages: Array<{ role: string; content: string }>,\n): boolean {\n const lastUserMessage = messages.filter((m) => m.role === \"user\").pop();\n if (!lastUserMessage) return false;\n const content = lastUserMessage.content;\n if (content.length < 17) return true;\n const sentences = content.split(/[.!?]+/).filter((s) => s.trim().length > 0);\n return sentences.length > 2 && content.toLowerCase().includes(\"search\");\n}\n\nfunction isShortInput(\n messages: Array<{ role: string; content: string }>,\n): boolean {\n const lastUserMessage = messages.filter((m) => m.role === \"user\").pop();\n return lastUserMessage ? lastUserMessage.content.length <= 10 : false;\n}\n\nfunction convertToGeminiFormat(\n messages: Array<{ role: string; content: string }>,\n isImageGen: boolean = false\n) {\n const contents = [];\n\n for (const message of messages) {\n if (message.role === \"system\") {\n continue;\n }\n\n const role = message.role === \"assistant\" || message.role === \"bot\"\n ? \"model\"\n : \"user\";\n contents.push({\n role,\n parts: [{ text: message.content }],\n });\n }\n\n const config: any = {\n contents,\n generationConfig: {\n temperature: isImageGen ? 0.8 : 0.7,\n maxOutputTokens: isImageGen ? 1024 : 2048,\n },\n };\n\n if (isImageGen) {\n config.generationConfig.candidateCount = 1;\n }\n\n return config;\n}\n\nfunction convertToOpenRouterFormat(\n messages: Array<{ role: string; content: string }>,\n) {\n return {\n model: \"mistralai/mistral-small-3.2-24b-instruct:free\",\n messages: messages.map((msg) => ({\n role: msg.role === \"bot\"\n ? \"assistant\"\n : msg.role as \"user\" | \"assistant\" | \"system\",\n content: msg.content,\n })),\n stream: true,\n max_tokens: 2048,\n temperature: 0.7,\n };\n}\n\nasync function makeRequest(\n config: ModelConfig,\n messages: Array<{ role: string; content: string }>,\n isImageGen: boolean = false\n): Promise {\n if (config.provider === \"google\") {\n const geminiPayload = convertToGeminiFormat(messages, isImageGen);\n const url = `${config.endpoint}?key=${process.env.GEMINI_API_KEY}&alt=sse`;\n\n return fetch(url, {\n method: \"POST\",\n headers: config.headers,\n body: JSON.stringify(geminiPayload),\n });\n } else {\n return fetch(config.endpoint, {\n method: \"POST\",\n headers: config.headers,\n body: JSON.stringify(convertToOpenRouterFormat(messages)),\n });\n }\n}\n\nasync function processStream(\n response: Response,\n send: SendEventFn,\n provider: string,\n): Promise {\n if (!response.body) {\n throw new Error(\"No response body\");\n }\n\n const reader = response.body.getReader();\n const decoder = new TextDecoder();\n let buffer = \"\";\n\n try {\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\n if (provider === \"google\") {\n const content = parsed.candidates?.[0]?.content?.parts?.[0]?.text;\n if (content) {\n send(\"text\", { text: content });\n }\n } else {\n const content = parsed.choices?.[0]?.delta?.content;\n if (content) {\n send(\"text\", { text: content });\n }\n }\n } catch (e) {\n console.error(\"Parse error:\", e, \"Data:\", data);\n }\n }\n }\n }\n } finally {\n reader.releaseLock();\n }\n}\n\nasync function generateImage(\n prompt: string,\n send: SendEventFn\n): Promise {\n try {\n const imagePrompt = `Generate a high-quality image based on this description: ${prompt}. Create a detailed, visually appealing image that captures the essence of the request.`;\n \n const payload = {\n contents: [{\n role: \"user\",\n parts: [{ text: imagePrompt }]\n }],\n generationConfig: {\n temperature: 0.8,\n maxOutputTokens: 1024,\n candidateCount: 1\n }\n };\n\n const url = `${IMAGE_MODEL.endpoint}?key=${process.env.GEMINI_API_KEY}`;\n \n const response = await fetch(url, {\n method: \"POST\",\n headers: IMAGE_MODEL.headers,\n body: JSON.stringify(payload),\n });\n\n if (!response.ok) {\n const errorText = await response.text().catch(() => \"Unknown error\");\n throw new Error(`Image generation failed: ${response.status} - ${errorText}`);\n }\n\n const result = await response.json();\n const generatedContent = result.candidates?.[0]?.content?.parts?.[0]?.text;\n \n if (generatedContent) {\n send(\"text\", { text: `🎨 **Image Generated Successfully!**\\n\\n${generatedContent}\\n\\n*Note: This is a simulated image generation response using Gemini 2.5 Flash Image Preview. In a production environment, this would return actual image data.*` });\n } else {\n throw new Error(\"No content generated from image model\");\n }\n \n } catch (error) {\n console.error(\"Image generation error:\", error);\n send(\"error\", { \n text: `Image generation failed: ${error.message}. Please try a different prompt.`, \n allow_retry: true \n });\n }\n}\n\nasync function getResponse(req: Query, send: SendEventFn) {\n send(\"meta\", { content_type: \"text/markdown\" });\n\n if (\n req.query &&\n req.query.some((msg) => msg.attachments && msg.attachments.length > 0)\n ) {\n send(\"error\", {\n text:\n \"File uploads are not supported. Please send your message as text only.\",\n allow_retry: false,\n });\n send(\"done\", {});\n return;\n }\n\n const messages = req.query.map((msg) => {\n if (msg.attachments && msg.attachments.length > 0) {\n return null;\n }\n\n return {\n role: msg.role === \"bot\"\n ? \"assistant\"\n : msg.role as \"user\" | \"assistant\" | \"system\",\n content: msg.content,\n };\n }).filter(Boolean) as Array<{ role: string; content: string }>;\n\n const lastUserMessage = messages.filter((m) => m.role === \"user\").pop();\n if (!lastUserMessage) {\n send(\"text\", { text: \"Hello! How can I assist you today? I can help with text responses or generate images based on your descriptions.\" });\n send(\"done\", {});\n return;\n }\n\n const userContent = lastUserMessage.content;\n\n if (!userContent || userContent.trim().length === 0) {\n send(\"error\", {\n text: \"Please provide a valid text message.\",\n allow_retry: false,\n });\n send(\"done\", {});\n return;\n }\n\n if (isGreeting(userContent)) {\n const greetingResponses = [\n \"Hello! How can I help you today? I can assist with text or generate images!\",\n \"Hi there! What can I assist you with? Text responses or image generation?\",\n \"Greetings! I'm here to help with questions and visual content creation.\",\n \"Hello! Ready to assist with your questions or create images for you.\",\n ];\n const response =\n greetingResponses[Math.floor(Math.random() * greetingResponses.length)];\n send(\"text\", { text: response });\n send(\"done\", {});\n return;\n }\n\n const faqResponse = getFAQResponse(userContent);\n if (faqResponse) {\n send(\"text\", { text: faqResponse });\n send(\"done\", {});\n return;\n }\n\n // Check if this is an image generation request\n if (isImageRequest(userContent)) {\n await generateImage(userContent, send);\n send(\"done\", {});\n return;\n }\n\n let modelsToTry: ModelConfig[];\n if (shouldUseCompound(messages)) {\n modelsToTry = [COMPOUND_MODEL];\n } else if (isShortInput(messages)) {\n modelsToTry = [SHORT_MODEL];\n } else {\n modelsToTry = MODELS;\n }\n\n for (let i = 0; i < modelsToTry.length; i++) {\n const config = modelsToTry[i];\n let response: Response | null = null;\n\n try {\n response = await makeRequest(config, messages);\n\n if (!response.ok) {\n const errorText = await response.text().catch(() => \"Unknown error\");\n console.error(\n `Model ${config.model} (${config.provider}) failed with status ${response.status}: ${errorText}`,\n );\n if (i === modelsToTry.length - 1) {\n throw new Error(\n `All models failed. Last error: ${response.status} - ${errorText}`,\n );\n }\n console.warn(`Trying next model after ${config.model} failure`);\n continue;\n }\n\n await processStream(response, send, config.provider);\n return;\n } catch (error) {\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 if (i === modelsToTry.length - 1) {\n console.error(\"All models failed:\", error);\n send(\"error\", { text: `Error: ${error.message}`, allow_retry: true });\n break;\n }\n\n console.warn(\n `Model ${config.model} (${config.provider}) failed:`,\n error.message,\n \"- trying next model\",\n );\n }\n }\n\n send(\"done\", {});\n}\n\nasync function getBotSettings(): Promise {\n const rateCard = \"| Type | Price |\\n\" + \"|------|------|\\n\" +\n `| Text Message | ${BASE_COST} points |\\n` +\n `| Image Generation | ${IMAGE_COST} points |\\n`;\n const costLabel = `${BASE_COST}+ points`;\n\n return {\n allow_attachments: false,\n expand_text_attachments: false,\n enable_multi_bot_chat_prompting: true,\n rate_card: rateCard,\n cost_label: costLabel,\n };\n}\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};\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: {\n type: \"like\" | \"dislike\";\n reason?: string;\n }[];\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: ${JSON.stringify(data)}\\n\\n`,\n );\n}\n\nexport default async function (req: Request): Promise {\n const reqBody = await req.json().catch((e) => {\n console.error(\"body parse error\", e);\n return {};\n });\n\n console.log(\"body\", reqBody);\n\n if (reqBody.type === \"settings\") {\n return new Response(JSON.stringify(await getBotSettings()), {\n status: 200,\n headers: { \"Content-Type\": \"application/json\" },\n });\n }\n\n const body = new ReadableStream({\n start(controller) {\n const send = (event, data) => {\n controller.enqueue(encodeEvent(event, data));\n };\n\n return getResponse(reqBody, send)\n .catch((e) => console.error(\"get response error\", e))\n .finally(() => controller.close());\n },\n });\n\n return new Response(body, {\n status: 200,\n headers: { \"Content-Type\": \"text/event-stream\" },\n });\n}",[],[99],"files",[154,175],"counts",{"_188":32,"_189":162,"_190":32,"_191":139},"pulls","branches","forks","envVars","contents",[],{"_104":176,"_160":140,"_157":177,"_95":99,"_168":181,"_166":180,"_100":179,"_159":-5,"_106":195,"_161":101,"_171":-5,"_98":196},["D",1758020911165],[99],"upstreamProject","upstreamBranch","emptyEnvVars","isNew","flags",[],"routes/_app.x.$handle.$name.branch.$branch.version.$version.code.$",{"_93":94,"_95":96,"_97":43,"_100":101,"_98":99,"_102":205,"_152":210,"_184":217,"_167":218,"_192":221,"_222":-5,"_223":22,"_224":-5,"_225":-5,"_226":-5,"_227":228},{"_104":105,"_95":96,"_106":206,"_108":-5,"_109":22,"_110":111,"_112":113,"_114":115,"_14":116,"_117":-5,"_118":22,"_119":-5,"_120":32,"_16":121,"_122":123,"_124":123,"_125":126,"_127":126,"_128":126,"_129":123,"_130":123,"_23":207,"_134":208,"_137":209,"_151":22},["D",1758020595774],{"_93":94,"_132":133},{"_93":94,"_136":133},{"_100":139,"_95":43,"_104":140,"_141":105,"_142":-5,"_143":-5,"_144":145,"_146":147,"_148":121,"_149":96,"_150":94},[211,214],{"_104":155,"_95":156,"_157":158,"_159":-5,"_160":140,"_161":162,"_163":164,"_106":165,"_100":32,"_166":167,"_168":169,"_170":22,"_171":-5,"_172":212,"_98":213},[],[156],{"_104":176,"_95":99,"_157":177,"_159":-5,"_160":140,"_161":101,"_163":22,"_106":178,"_100":179,"_166":180,"_168":181,"_170":22,"_171":-5,"_172":215,"_98":216},[],[99],[211,214],{"_104":176,"_160":140,"_157":177,"_95":99,"_168":181,"_166":180,"_100":179,"_159":-5,"_106":219,"_161":101,"_171":-5,"_98":220},["D",1758020911165],[99],[],"upstream","showCompareCallout","pull","ahead","behind","templates",[],"actionData","errors"]