Update index.html

index.html

@@ -232,63 +232,55 @@
             animationId = setTimeout(updateVisualizer, 50);
         }
 
-        async function initializePipelines() {
-            try {
-                addLog('System: Initializing pipelines...');
-                [sttPipeline, ttsPipeline] = await Promise.all([
-                    pipeline('automatic-speech-recognition', 'Xenova/whisper-tiny.en', { quantized: true }),
-                    pipeline('text-to-speech', 'Xenova/mms-tts-eng', { quantized: true })
-                ]);
-
-                const initProgressCallback = (report) => {
-                    addLog(`System: ${report.text}`);
-                };
-                const selectedModel = "TinyLlama-1.1B-Chat-v0.4-q4f16_1-1k";
-                llmEngine = await webllm.CreateEngine(
-                    selectedModel,
-                    {
-                        initProgressCallback: initProgressCallback
-                    }
-                );
-              
-                addLog('System: Digital Human Voice Chat initialized with WebLLM. Click "Begin Call" to start.');
-                startButton.disabled = false;
-                loadingDiv.style.display = 'none';
-            } catch (error) {
-                console.error('Error initializing pipelines:', error);
-                addLog(`System: Error initializing pipelines: ${error.message}`);
-                loadingDiv.style.display = 'none';
-            }
-        }
 
-        async function processSpeech(audio) {
-            try {
-                if (!sttPipeline || !ttsPipeline || !llmEngine) {
-                    throw new Error('Pipelines not initialized');
-                }
-
-                const transcription = await sttPipeline(audio);
-                addLog(`User: ${transcription.text}`);
-                
-                const reply = await llmEngine.chat.completions.create({
-                    messages: [
-                        { role: 'system', content: 'You are a helpful assistant.' },
-                        { role: 'user', content: transcription.text }
-                    ]
-                });
-
-                const botResponse = reply.choices[0].message.content;
-                addLog(`Bot: ${botResponse}`);
+      async function initializePipelines() {
+        try {
+            addLog('System: Initializing pipelines...');
+            [sttPipeline, ttsPipeline] = await Promise.all([
+                pipeline('automatic-speech-recognition', 'Xenova/whisper-tiny.en', { quantized: true }),
+                pipeline('text-to-speech', 'Xenova/mms-tts-eng', { quantized: true })
+            ]);
+
+            addLog('System: Initializing WebLLM...');
+            llmChat = new webllm.ChatModule({
+                model: "TinyLlama-1.1B-Chat-v0.4-q4f16_1-1k"
+            });
+            await llmChat.reload();
+            addLog('System: WebLLM initialized successfully.');
+          
+            addLog('System: Digital Human Voice Chat initialized. Click "Begin Call" to start.');
+            startButton.disabled = false;
+            loadingDiv.style.display = 'none';
+        } catch (error) {
+            console.error('Error initializing pipelines:', error);
+            addLog(`System: Error initializing pipelines: ${error.message}`);
+            loadingDiv.style.display = 'none';
+        }
+    }
 
-                isSpeaking = true;
-                const speechOutput = await ttsPipeline(botResponse);
-                await playAudio(speechOutput.audio);
-                isSpeaking = false;
-            } catch (error) {
-                console.error('Error processing speech:', error);
-                addLog(`System: Error processing speech: ${error.message}`);
+    async function processSpeech(audio) {
+        try {
+            if (!sttPipeline || !ttsPipeline || !llmChat) {
+                throw new Error('Pipelines not initialized');
             }
+
+            const transcription = await sttPipeline(audio);
+            addLog(`User: ${transcription.text}`);
+            
+            const reply = await llmChat.generate(transcription.text);
+
+            const botResponse = reply.trim();
+            addLog(`Bot: ${botResponse}`);
+
+            isSpeaking = true;
+            const speechOutput = await ttsPipeline(botResponse);
+            await playAudio(speechOutput.audio);
+            isSpeaking = false;
+        } catch (error) {
+            console.error('Error processing speech:', error);
+            addLog(`System: Error processing speech: ${error.message}`);
         }
+    }
 
         function addLog(message) {
             const now = new Date();