Added main script

ai_ref_kits/custom_ai_assistant/main.py

@@ -0,0 +1,28 @@
+import argparse
+from pathlib import Path
+
+import app
+import convert_and_optimize_asr as asr
+import convert_and_optimize_chat as chat
+
+
+def main(args):
+    asr_model_dir = asr.convert_asr_model(args.asr_model_type, args.precision, Path(args.model_dir))
+    chat_model_dir = chat.convert_chat_model(args.chat_model_type, args.precision, Path(args.model_dir))
+
+    app.run(asr_model_dir, chat_model_dir, args.public)
+
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument("--asr_model_type", type=str, choices=["distil-whisper-large-v3", "belle-distilwhisper-large-v2-zh"],
+                        default="distil-whisper-large-v3", help="Speech recognition model to be converted")
+    parser.add_argument("--asr_precision", type=str, default="fp16", choices=["fp16", "int8"], help="ASR model precision")
+    parser.add_argument("--chat_model_type", type=str, choices=["llama3.1-8B", "llama3-8B", "qwen2-7B", "llama3.2-3B"],
+                        default="llama3.1-8B", help="Chat model to be converted")
+    parser.add_argument("--precision", type=str, default="int4", choices=["fp16", "int8", "int4"], help="Chat model precision")
+    parser.add_argument("--model_dir", type=str, default="model", help="Directory to place the model in")
+    parser.add_argument('--public_interface', default=False, action="store_true", help="Whether interface should be available publicly")
+
+    main(parser.parse_args())