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server.js

@@ -1,40 +1,35 @@
 import express from 'express';
-import { SystemMessage, HumanMessage, Runnable, LlamaCppLLM } from './src/index.js'; // Sửa lại đường dẫn import cho đúng cấu trúc flat nếu cần, nhưng ở đây src vẫn nằm trong root
+import { SystemMessage, HumanMessage, Runnable, LlamaCppLLM } from './src/index.js';
 import bodyParser from 'body-parser';
 import path from 'path';
 import fs from 'fs';
 
-// ... (Giữ nguyên phần Class Logic) ...
+// ... (Giữ nguyên logic EmailClassifierRunnable) ...
 class EmailClassifierRunnable extends Runnable {
     constructor(llm) {
         super();
         this.llm = llm;
     }
-
     async _call(input, config) {
+        // Mock implementation if LLM fails
+        if (!this.llm) return { category: "Error", confidence: 0, reason: "LLM not initialized" };
+        
         const messages = this._buildPrompt(input);
         const response = await this.llm.invoke(messages, config);
         return this._parseClassification(response.content);
     }
-
     _buildPrompt(email) {
         return [
-            new SystemMessage(`You are an email classification assistant. Classify into: Spam, Invoice, Meeting Request, Urgent, Personal, Other.
-            Respond in strict JSON format: {"category": "Name", "confidence": 0.95, "reason": "Explanation"}`),
-            new HumanMessage(`Classify this email:
-Subject: ${email.subject}
-Body: ${email.body}`)
+            new SystemMessage(`You are an email classification assistant. Classify into: Spam, Invoice, Meeting Request, Urgent, Personal, Other. Respond in JSON.`),
+            new HumanMessage(`Classify:\nSubject: ${email.subject}\nBody: ${email.body}`)
         ];
     }
-
     _parseClassification(response) {
         try {
             const jsonMatch = response.match(/\{[\s\S]*\}/);
-            if (!jsonMatch) throw new Error('No JSON found');
+            if (!jsonMatch) throw new Error('No JSON');
             return JSON.parse(jsonMatch[0]);
-        } catch (error) {
-            return { category: 'Other', confidence: 0.0, reason: 'Failed to parse', raw: response };
-        }
+        } catch (e) { return { category: 'Other', confidence: 0, reason: 'Parse fail' }; }
     }
 }
 
@@ -43,9 +38,17 @@ const PORT = 7860;
 
 app.use(bodyParser.json());
 
-// Log directory content for debugging
-console.log("Current directory:", process.cwd());
-console.log("Files in models:", fs.readdirSync('./models'));
+// Global error log
+const errorLog = [];
+
+app.get('/debug', (req, res) => {
+    res.json({
+        cwd: process.cwd(),
+        files: fs.readdirSync('.'),
+        models: fs.existsSync('./models') ? fs.readdirSync('./models') : 'No models dir',
+        errors: errorLog
+    });
+});
 
 let classifier = null;
 
@@ -53,7 +56,10 @@ async function initModel() {
     try {
         console.log("Loading model...");
         const modelPath = path.resolve('./models/Qwen3-1.7B-Q8_0.gguf');
-        console.log("Model absolute path:", modelPath);
+        
+        if (!fs.existsSync(modelPath)) {
+            throw new Error(`Model file not found at ${modelPath}`);
+        }
 
         const llm = new LlamaCppLLM({
             modelPath: modelPath,
@@ -61,35 +67,37 @@ async function initModel() {
             maxTokens: 200
         });
         
-        // Test invoke to make sure it works
-        await llm.invoke("Hello"); 
+        // Test run
+        await llm.invoke("Hi");
         
         classifier = new EmailClassifierRunnable(llm);
-        console.log("Model loaded and ready!");
+        console.log("Model loaded!");
     } catch (err) {
-        console.error("FATAL ERROR loading model:", err);
-        process.exit(1); // Exit to let Docker restart (or show error)
+        console.error("Model Load Error:", err);
+        errorLog.push(err.toString());
+        // DO NOT EXIT, let the server run to debug
     }
 }
 
 app.post('/classify', async (req, res) => {
-    if (!classifier) return res.status(503).json({ error: "Model is loading..." });
+    if (!classifier) {
+        return res.status(503).json({
+            error: "Model not ready", 
+            logs: errorLog 
+        });
+    }
     try {
-        const { subject, body, from } = req.body;
-        const result = await classifier.invoke({ subject, body, from: from || 'unknown' });
+        const { subject, body } = req.body;
+        const result = await classifier.invoke({ subject, body, from: 'api' });
         res.json(result);
     } catch (error) {
-        console.error(error);
         res.status(500).json({ error: error.message });
     }
 });
 
-app.get('/', (req, res) => {
-    res.send('AI Agent Email Classifier is Running. POST to /classify to use.');
-});
+app.get('/', (req, res) => res.send('Server Running (Check /debug for status)'));
 
-// Start server immediately, load model in background
 app.listen(PORT, '0.0.0.0', () => {
-    console.log(`Server running on port ${PORT}`);
+    console.log(`Listening on ${PORT}`);
     initModel();
 });