refactor example Python class to accept a single prompt and exit

tests/llm/phi3_interface.py

@@ -1 +0,0 @@
-# TODO: business logic for REST API interaction w/ LLM via prompt input

tests/llm/phi3_language_model.py

@@ -0,0 +1,57 @@
+# TODO: business logic for REST API interaction w/ LLM via prompt input
+
+import onnxruntime_genai as og
+import argparse
+
+
+class Phi3LanguageModel:
+
+    def __init__(self, model_path):
+        # configure the ONNX runtime
+        config = og.Config(model_path)
+        config.clear_providers()
+        self.model = og.Model(config)
+        self.tokenizer = og.Tokenizer(model)
+        self.tokenizer_stream = self.tokenizer.create_stream()    
+    
+
+    def get_response(self, args):
+
+        search_options = { 'max_length': 2048 }
+        params = og.GeneratorParams(model)
+        params.set_search_options(**search_options)
+        generator = og.Generator(model, params)
+
+        # process prompt input and generate tokens
+        prompt_input = args.prompt
+        chat_template = '<|user|>\n{input} <|end|>\n<|assistant|>'
+        prompt = f'{chat_template.format(input=prompt_input)}'
+        input_tokens = self.tokenizer.encode(prompt)
+        generator.append_tokens(input_tokens)
+
+        print("Output: ", end='', flush=True)
+
+        try:
+            while not generator.is_done():
+                generator.generate_next_token()
+                new_token = generator.get_next_tokens()[0]
+                print(self.tokenizer_stream.decode(new_token), end='', flush=True)
+        except Exception as e:
+            print(f'{e}')
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(argument_default=argparse.SUPPRESS, description="End-to-end AI Question/Answer example for gen-ai")
+    parser.add_argument('-m', '--model_path', type=str, required=True, help='Onnx model folder path (must contain genai_config.json and model.onnx)')
+    parser.add_argument('-p', '--prompt', type=str, required=True, help='Prompt input')
+    parser.add_argument('-i', '--min_length', type=int, help='Min number of tokens to generate including the prompt')
+    parser.add_argument('-l', '--max_length', type=int, help='Max number of tokens to generate including the prompt')
+    parser.add_argument('-ds', '--do_sample', action='store_true', default=False, help='Do random sampling. When false, greedy or beam search are used to generate the output. Defaults to false')
+    parser.add_argument('--top_p', type=float, help='Top p probability to sample with')
+    parser.add_argument('--top_k', type=int, help='Top k tokens to sample from')
+    parser.add_argument('--temperature', type=float, help='Temperature to sample with')
+    parser.add_argument('--repetition_penalty', type=float, help='Repetition penalty to sample with')
+    args = parser.parse_args()
+
+    model = Phi3LanguageModel(args.model_path)
+    model.get_response()