Upload handler.py

This is the handler.py file

handler.py

@@ -0,0 +1,72 @@
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+class ModelHandler:
+    def __init__(self):
+        self.initialized = False
+
+    def initialize(self, model_dir: str):
+        self.tokenizer = AutoTokenizer.from_pretrained(model_dir)
+        self.model = AutoModelForCausalLM.from_pretrained(model_dir, torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32)
+        self.model.eval()
+        if torch.cuda.is_available():
+            self.model.to("cuda")
+        self.initialized = True
+
+    def predict(self, inputs: dict):
+        if not self.initialized:
+            raise RuntimeError("Model not initialized")
+
+        messages = inputs.get("messages", [])
+        max_tokens = inputs.get("max_tokens", 512)
+        temperature = inputs.get("temperature", 0.7)
+
+        # Convert OpenAI-style messages into a single prompt
+        prompt = self._build_prompt(messages)
+
+        # Tokenize
+        input_ids = self.tokenizer(prompt, return_tensors="pt").input_ids
+        if torch.cuda.is_available():
+            input_ids = input_ids.to("cuda")
+
+        # Generate
+        output_ids = self.model.generate(
+            input_ids,
+            max_new_tokens=max_tokens,
+            temperature=temperature,
+            do_sample=True,
+            pad_token_id=self.tokenizer.eos_token_id,
+        )
+
+        response = self.tokenizer.decode(output_ids[0], skip_special_tokens=True)
+
+        # Return just the newly generated portion
+        generated_text = response[len(prompt):].strip()
+
+        return {
+            "id": "chatcmpl-fakeid",
+            "object": "chat.completion",
+            "choices": [
+                {
+                    "index": 0,
+                    "message": {
+                        "role": "assistant",
+                        "content": generated_text
+                    },
+                    "finish_reason": "stop"
+                }
+            ],
+            "model": "your-model-id",
+        }
+
+    def _build_prompt(self, messages):
+        prompt = ""
+        for msg in messages:
+            role = msg["role"]
+            content = msg["content"]
+            if role == "user":
+                prompt += f"User: {content}\n"
+            elif role == "assistant":
+                prompt += f"Assistant: {content}\n"
+        prompt += "Assistant:"
+        return prompt