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"Here's some wisdom: Keep doing your duty without expecting results. That's the essence of Karma Yoga!"
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}
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}
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// GREETINGS
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if (lower.matches(".*(hello|hi|hey|greetings|sup|yo).*".toRegex())) {
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returnlistOf(
@@ -447,7 +474,7 @@ class ChatManager(private val context: Context) {
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// CAPABILITIES
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if (lower.contains("what can you do") || lower.contains("help") || lower.contains("capabilities")) {
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return"I can:\n• Get news headlines (India)\n• Control device (WiFi, Bluetooth, flashlight, volume)\n• Get real weather data (500+ Indian cities)\n• Make calls & send messages\n• Check time & date\n• Answer questions\n• Set reminders\n• Open apps\n• And much more! Just ask!"
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return"I can:\n• Get news headlines (India)\n• Control device (WiFi, Bluetooth, flashlight, volume)\n• Get real weather data (500+ Indian cities)\n• Make calls & send messages\n• Check time & date\n• Give motivational quotes (Bhagavad Gita)\n• Answer questions\n• Set reminders\n• Open apps\n• And much more! Just ask!"
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}
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// TIME & DATE
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// DEFAULT
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returnwhen {
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input.endsWith("?") ->"That's a great question! I can help with news, weather, device control, and more. What do you need?"
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input.endsWith("?") ->"That's a great question! I can help with news, weather, device control, motivational quotes, and more. What do you need?"
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input.length <3->"I'm listening. What would you like me to do?"
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else->"I understand you're asking about that. Try asking me about news, weather, time, or device control!"
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else->"I understand you're asking about that. Try asking me about news, weather, time, Gita quotes, or device control!"
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}
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}
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@@ -575,14 +602,16 @@ class ChatManager(private val context: Context) {
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append("\n✅ Weather API: Available")
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append("\n✅ Web Search: Available")
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append("\n✅ Device Control: Available")
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append("\n✅ Bhagavad Gita: 700+ verses")
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}
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}
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fungetModelInfo(): Map<String, String> =mapOf(
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"gguf_ready" to llamaCppEngine.isReady().toString(),
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"model_ready" to isModelReady().toString(),
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"model_name" to (llmModelPath?.name ?:"none"),
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"model_size_mb" to "${(llmModelPath?.length() ?:0) / (1024*1024)}"
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"model_size_mb" to "${(llmModelPath?.length() ?:0) / (1024*1024)}",
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