初始化项目，由ModelHub XC社区提供模型

Model: dennny123/cybersec-qwen2.5-coder-7b
Source: Original Platform

handler.py

@@ -0,0 +1,46 @@
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+class EndpointHandler:
+    def __init__(self, path=""):
+        self.tokenizer = AutoTokenizer.from_pretrained(path, trust_remote_code=True)
+        self.model = AutoModelForCausalLM.from_pretrained(
+            path,
+            torch_dtype=torch.float16,
+            device_map="auto",
+            trust_remote_code=True
+        )
+        self.model.eval()
+
+    def __call__(self, data):
+        inputs = data.pop("inputs", "")
+        parameters = data.pop("parameters", {})
+        
+        # Build chat format
+        messages = [
+            {"role": "system", "content": "You are a cybersecurity expert assistant."},
+            {"role": "user", "content": inputs}
+        ]
+        
+        text = self.tokenizer.apply_chat_template(
+            messages, tokenize=False, add_generation_prompt=True
+        )
+        
+        model_inputs = self.tokenizer(text, return_tensors="pt").to(self.model.device)
+        
+        with torch.no_grad():
+            outputs = self.model.generate(
+                **model_inputs,
+                max_new_tokens=parameters.get("max_new_tokens", 512),
+                temperature=parameters.get("temperature", 0.7),
+                top_p=parameters.get("top_p", 0.9),
+                do_sample=True,
+                pad_token_id=self.tokenizer.eos_token_id
+            )
+        
+        response = self.tokenizer.decode(
+            outputs[0][model_inputs['input_ids'].shape[1]:], 
+            skip_special_tokens=True
+        )
+        
+        return {"generated_text": response}