初始化项目，由ModelHub XC社区提供模型

Model: mistral-hackaton-2026/ecotopia-citizens-8b-merged
Source: Original Platform

handler.py

@@ -0,0 +1,46 @@
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
+from typing import Dict, Any
+
+class EndpointHandler:
+    def __init__(self, path=""):
+        quantization_config = BitsAndBytesConfig(
+            load_in_4bit=True,
+            bnb_4bit_compute_dtype=torch.float16,
+            bnb_4bit_quant_type="nf4",
+        )
+        self.tokenizer = AutoTokenizer.from_pretrained(path)
+        self.model = AutoModelForCausalLM.from_pretrained(
+            path,
+            quantization_config=quantization_config,
+            device_map="auto",
+            torch_dtype=torch.float16,
+        )
+
+    def __call__(self, data: Dict[str, Any]) -> Dict[str, Any]:
+        inputs = data.get("inputs", "")
+        parameters = data.get("parameters", {})
+
+        if isinstance(inputs, list):
+            text = self.tokenizer.apply_chat_template(inputs, tokenize=False, add_generation_prompt=True)
+        else:
+            text = inputs
+
+        encoded = self.tokenizer(text, return_tensors="pt").to(self.model.device)
+        # Remove token_type_ids - not used by Mistral models
+        encoded.pop("token_type_ids", None)
+        
+        max_new_tokens = parameters.get("max_new_tokens", 512)
+        temperature = parameters.get("temperature", 0.7)
+
+        with torch.no_grad():
+            outputs = self.model.generate(
+                **encoded,
+                max_new_tokens=max_new_tokens,
+                temperature=max(temperature, 0.01),
+                do_sample=temperature > 0,
+            )
+
+        new_tokens = outputs[0][encoded["input_ids"].shape[1]:]
+        response = self.tokenizer.decode(new_tokens, skip_special_tokens=True)
+        return [{"generated_text": response}]