Create aiEngine.js

aiEngine.js

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+import OpenAI from "openai";
+
+const openRouterAI = new OpenAI({
+  apiKey: process.env.OPENROUTER_API_KEY,
+  baseURL: "https://openrouter.ai/api/v1",
+  defaultHeaders: {
+    "HTTP-Referer": process.env.YOUR_SITE_URL || "https://everydaycats.web.app",
+    "X-Title": process.env.YOUR_SITE_NAME || "Aura Scanner",
+  }
+});
+
+// --- MODEL ROUTER ---
+const getModelId = (modelName) => {
+  switch (modelName?.toLowerCase()) {
+    case "llama": case "maverick":   return "meta-llama/llama-4-maverick:floor";
+    case "llama-3.2-11b":            return "meta-llama/llama-3.2-11b-vision-instruct:free";
+    case "qwen-2-vl-7b":             return "qwen/qwen-2-vl-7b-instruct:free";
+    case "nemotron-12b":             return "nvidia/nemotron-nano-12b-v2-vl:free";
+    case "gpt": case "gpt-5.4-nano": return "openai/gpt-5.4-nano";
+    case "qwen-non":                 return "qwen/qwen3-vl-30b-a3b-instruct";
+    case "qwen": default:            return "qwen/qwen3-vl-30b-a3b-thinking:floor";
+  }
+};
+
+// --- IMAGE MODEL ROUTER ---
+const getImageModelId = (tier) => {
+  switch (tier) {
+    case "premium": return "bytedance-seed/seedream-4.5";          // $0.04/img
+    case "quick":   return "sourceful/riverflow-v2-fast";          // $0.002/img
+    default:        return "sourceful/riverflow-v2-fast";
+  }
+};
+
+// --- ERROR LOGGER ---
+const logOpenRouterError = (error, context) => {
+  const status = error.status || error.response?.status;
+  if      (status === 402) console.error(`💸 [402] ${context}: Insufficient credits.`);
+  else if (status === 429) console.error(`🚨 [429] ${context}: Rate limit exceeded.`);
+  else if (status === 401) console.error(`🛑 [401] ${context}: Invalid API Key.`);
+  else if (status === 400) console.error(`⚠️  [400] ${context}: Bad request / invalid payload.`);
+  else if (status >= 500)  console.error(`🔥 [${status}] ${context}: Provider backend down.`);
+  else if (error.code === 'ECONNRESET' || error.code === 'ETIMEDOUT')
+                           console.error(`⏳ [TIMEOUT] ${context}: Connection dropped.`);
+  else                     console.error(`❌ [ERROR] ${context}:`, error.message || error);
+};
+
+// --- TEXT COMPLETION ---
+export const generateCompletion = async ({ model, prompt, system_prompt, images }) => {
+  try {
+    const targetModel = getModelId(model);
+    let messagesPayload = [
+      { role: "system", content: system_prompt || "You are an elite AI assistant." }
+    ];
+
+    if (images?.length > 0) {
+      let userContent = [{ type: "text", text: prompt }];
+      images.forEach((imgStr) => {
+        if (imgStr.length > 7000000) throw new Error("Image too large. Max ~4MB.");
+        const formattedImg = imgStr.startsWith('data:image')
+          ? imgStr : `data:image/jpeg;base64,${imgStr}`;
+        userContent.push({ type: "image_url", image_url: { url: formattedImg } });
+      });
+      messagesPayload.push({ role: "user", content: userContent });
+    } else {
+      messagesPayload.push({ role: "user", content: prompt });
+    }
+
+    const response = await openRouterAI.chat.completions.create({
+      model: targetModel,
+      messages: messagesPayload,
+      response_format: { type: "json_object" },
+      max_tokens: 1200,
+    });
+
+    return {
+      success: true,
+      data: response.choices[0].message.content,
+      usage: response.usage,
+      model_used: targetModel
+    };
+  } catch (error) {
+    logOpenRouterError(error, "generateCompletion");
+    return { success: false, error: error.message, status: error.status || 500 };
+  }
+};
+
+// --- STREAMING TEXT COMPLETION ---
+export const streamCompletion = async ({ model, prompt, system_prompt, images, res }) => {
+  try {
+    const targetModel = getModelId(model);
+    let messagesPayload = [
+      { role: "system", content: system_prompt || "You are an elite AI assistant." }
+    ];
+
+    if (images?.length > 0) {
+      let userContent = [{ type: "text", text: prompt }];
+      images.forEach((imgStr) => {
+        if (imgStr.length > 7000000) throw new Error("Image too large. Max ~4MB.");
+        const formattedImg = imgStr.startsWith('data:image')
+          ? imgStr : `data:image/jpeg;base64,${imgStr}`;
+        userContent.push({ type: "image_url", image_url: { url: formattedImg } });
+      });
+      messagesPayload.push({ role: "user", content: userContent });
+    } else {
+      messagesPayload.push({ role: "user", content: prompt });
+    }
+
+    const stream = await openRouterAI.chat.completions.create({
+      model: targetModel,
+      messages: messagesPayload,
+      stream: true,
+      stream_options: { include_usage: true },
+      max_tokens: 2000,
+    });
+
+    let totalTokenCount = 0;
+    for await (const chunk of stream) {
+      const delta = chunk.choices[0]?.delta;
+      if (delta?.reasoning_content) res.write(`__THINK__${delta.reasoning_content}`);
+      else if (delta?.content)      res.write(delta.content);
+      if (chunk.usage) totalTokenCount = chunk.usage.total_tokens;
+    }
+
+    res.write(`__USAGE__${JSON.stringify({ totalTokenCount })}`);
+    res.end();
+  } catch (error) {
+    logOpenRouterError(error, "streamCompletion");
+    res.write(`\n\n[ERROR]: ${error.message}`);
+    res.end();
+  }
+};
+
+// --- IMAGE GENERATION ---
+// Uses OpenRouter's image generation endpoint directly (not chat completions)
+export const generateImage = async ({ prompt, tier = "quick" }) => {
+  try {
+    const model = getImageModelId(tier);
+
+    const response = await fetch("https://openrouter.ai/api/v1/images/generations", {
+      method: "POST",
+      headers: {
+        "Authorization": `Bearer ${process.env.OPENROUTER_API_KEY}`,
+        "Content-Type": "application/json",
+        "HTTP-Referer": process.env.YOUR_SITE_URL || "https://everydaycats.web.app",
+        "X-Title": process.env.YOUR_SITE_NAME || "lightnovel.ai",
+      },
+      body: JSON.stringify({
+        model,
+        prompt,
+        n: 1,
+        size: "1024x1024",
+      })
+    });
+
+    if (!response.ok) {
+      const err = await response.json();
+      throw Object.assign(new Error(err?.error?.message || "Image gen failed"), { status: response.status });
+    }
+
+    const data = await response.json();
+    const imageUrl = data?.data?.[0]?.url;
+    if (!imageUrl) throw new Error("No image URL returned.");
+
+    return { success: true, url: imageUrl, model_used: model };
+  } catch (error) {
+    logOpenRouterError(error, "generateImage");
+    return { success: false, error: error.message, status: error.status || 500 };
+  }
+};