Create handler.py

handler.py

@@ -0,0 +1,32 @@
+# handler.py
+from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
+import torch
+
+class EndpointHandler:
+    def __init__(self, path=""):
+        self.tokenizer = AutoTokenizer.from_pretrained(path)
+        self.model = AutoModelForCausalLM.from_pretrained(
+            path,
+            torch_dtype=torch.float16,
+            device_map="auto",
+            load_in_4bit=True,
+        )
+        self.pipeline = pipeline(
+            "text-generation",
+            model=self.model,
+            tokenizer=self.tokenizer,
+        )
+
+    def __call__(self, data):
+        messages = data.get("inputs", {}).get("messages", [])
+        prompt = self.tokenizer.apply_chat_template(
+            messages, tokenize=False, add_generation_prompt=True
+        )
+        result = self.pipeline(
+            prompt,
+            max_new_tokens=data.get("parameters", {}).get("max_tokens", 500),
+            temperature=data.get("parameters", {}).get("temperature", 0.45),
+            do_sample=True,
+        )
+        text = result[0]["generated_text"][len(prompt):]
+        return {"choices": [{"message": {"role": "assistant", "content": text}}]}