From bd4e98af69d517474dfefb1197caeb7ad0f5bcf0 Mon Sep 17 00:00:00 2001
From: groupuser <groupuser@aifrica.co.kr>
Date: Mon, 14 Apr 2025 04:22:25 +0000
Subject: [PATCH] create by CHEETAH

---
 1/model.py | 84 ++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 84 insertions(+)
 create mode 100644 1/model.py

diff --git a/1/model.py b/1/model.py
new file mode 100644
index 0000000..7449b7d
--- /dev/null
+++ b/1/model.py
@@ -0,0 +1,84 @@
+import triton_python_backend_utils as pb_utils
+from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
+import numpy as np
+import json
+
+class TritonPythonModel:
+    def initialize(self, args):
+        """모델 초기화. Triton이 서버 시작 시 실행."""
+        self.logger = pb_utils.Logger
+
+        model_repository = args["model_repository"]
+        model_name = args["model_name"]
+        model_path = f"{model_repository}/{model_name}"
+
+        self.model_config = json.loads(args["model_config"])
+
+        self.tokenizer = AutoTokenizer.from_pretrained(model_path)
+
+        self.model = AutoModelForCausalLM.from_pretrained(
+            model_path,
+            local_files_only=True,
+            device_map="auto"
+        )
+
+        self.logger.log_info(f"\n### {model_name} 모델 초기화 완료")
+
+
+    def execute(self, requests):
+        """Triton이 호출하는 Inference 실행 함수."""
+        responses = []
+
+        input_name = self.model_config.get("input")[0]['name']
+        output_name = self.model_config.get("output")[0]['name']
+
+        for request in requests:
+            # Triton 입력 파싱
+            input_tensor = pb_utils.get_input_tensor_by_name(request, input_name).as_numpy()[0]
+            input_text = input_tensor.decode('utf-8')
+            self.logger.log_info(f"### INPUT_TEXT: {input_text}")
+
+            # 토크나이징
+            inputs = self.tokenizer(
+                f"### 질문: {input_text}\n\n### 답변:",
+                return_tensors="pt").to(device=self.model.device)
+
+            input_ids = inputs["input_ids"].to(device=self.model.device)
+            attention_mask = inputs["attention_mask"].to(device=self.model.device)
+
+            generation_config = GenerationConfig(
+                max_new_tokens=256,
+            )
+
+            # 모델 추론
+            gened = self.model.generate(
+                generation_config=generation_config,
+                input_ids=input_ids,
+                attention_mask=attention_mask,
+                pad_token_id=2,
+                repetition_penalty=1.1,
+            )
+
+            # 생성된 텍스트 디코딩
+            answer = self.tokenizer.decode(gened[0])
+            self.logger.log_info(f"### MODEL ANSWER:\n{answer}")
+
+            # 답변 내용 후처리
+            output = self.post_process(answer)
+            self.logger.log_info(f"### OUTPUT_TEXT: {output}")
+
+            # Triton에 텐서로 반환
+            output_tensor = pb_utils.Tensor(output_name, np.array(output.encode('utf-8'), dtype=np.bytes_))
+            responses.append(pb_utils.InferenceResponse(output_tensors=[output_tensor]))
+
+        return responses
+
+    def post_process(self, text):
+        try:
+            return str(text.split("### 답변:")[1].split("### 질문:")[0].strip())
+        except IndexError:
+            return text
+
+    def finalize(self):
+        """서버 종료 시 정리 (옵션)."""
+        pass
\ No newline at end of file