feat: 完成 issue #8 ⑥ K8s/Helm 部署底座 + 昇腾适配层

core/inference-backend/gpu_backend.py

@@ -0,0 +1,74 @@
+# -*- coding: utf-8 -*-
+"""NVIDIA GPU 推理后端实现（5090，Triton/ONNX）。
+
+对应 PRD 5.6：5090 实现（Triton/ONNX）——通过 OpenAI 兼容接口
+（vLLM / Triton Inference Server）对外提供推理，业务侧统一走
+`InferenceBackend` 接口，不感知硬件。
+"""
+from inference_backend.base import InferenceBackend, InferRequest, InferResult
+
+
+class NvidiaGpuBackend(InferenceBackend):
+    """NVIDIA GPU 后端：面向 5090 服务器（Triton/ONNX，OpenAI 兼容）。"""
+
+    backend_name = "gpu"
+
+    def __init__(self, endpoint: str = "", model: str = "iaop-default",
+                 timeout_seconds: float = 10.0, runtime: str = "vllm",
+                 device: str = "nvidia-5090", **kwargs):
+        super().__init__(endpoint, model, timeout_seconds)
+        self.runtime = runtime          # vllm | triton
+        self.device = device            # 硬件型号（默认 5090）
+        self._loaded = False
+
+    def load_model(self, model_name: str | None = None) -> dict:
+        """加载模型到 GPU。无 endpoint 时仅维护本地状态（适配层就绪）。"""
+        model_name = model_name or self.model
+        if not self.endpoint:
+            self._loaded = True
+            return {"status": "ok", "backend": self.backend_name,
+                    "model": model_name, "device": self.device,
+                    "reason": "dry-run（未配置 endpoint）"}
+        body = self._post_json("/v1/models/load",
+                               {"model": model_name, "device": self.device})
+        self._loaded = body.get("status") in ("ok", "loaded", "ready")
+        return body
+
+    def infer(self, request: InferRequest) -> InferResult:
+        """OpenAI 兼容生成（/v1/chat/completions）。"""
+        started = __import__("time").monotonic()
+        payload = request.to_payload()
+        payload["model"] = payload["model"] or self.model
+        body = self._post_json("/v1/chat/completions", payload)
+        latency_ms = round((__import__("time").monotonic() - started) * 1000, 2)
+        try:
+            text = body["choices"][0]["message"]["content"]
+        except (KeyError, IndexError, TypeError):
+            text = str(body)
+        return InferResult(
+            text=text,
+            backend=self.backend_name,
+            latency_ms=latency_ms,
+            meta={"runtime": self.runtime, "device": self.device,
+                  "model": self.model, "raw": body},
+        )
+
+    def health(self) -> dict:
+        """健康巡检：探测 /health，返回后端/设备/运行时信息。"""
+        base = self._healthz()
+        base.update({
+            "backend": self.backend_name,
+            "runtime": self.runtime,
+            "device": self.device,
+            "model": self.model,
+            "loaded": self._loaded,
+        })
+        return base
+
+    def unload(self) -> dict:
+        """卸载模型、释放显存。"""
+        self._loaded = False
+        if not self.endpoint:
+            return {"status": "ok", "backend": self.backend_name,
+                    "reason": "dry-run（未配置 endpoint）"}
+        return self._post_json("/v1/models/unload", {"model": self.model})