feat: 模型评测端到端闭环 — EvalRunner引擎 + 算力节点Job执行 + 结果回写

算力节点 (compute):
- 新建 eval_runner.py: 评测执行引擎，作为subprocess运行
  - 加载模型 + JSONL数据集 + 逐样本推理
  - BLEU/ROUGE/Cosine基础指标计算
  - LLM Judge评分(OpenAI兼容API调用)
  - 结果写入eval_results.json
- adapter.py: build_command新增engine=eval分支
- main.py: 新增/json模块导入，新增/compute/files/read端点，eval job校验

后端:
- platform.py: 重写startEval提交eval job到算力节点
  - 支持models表和trained_models表查找
  - 已合并模型不传adapter路径
- platform_store.py: 新增update_eval_task/running_eval_tasks/apply_eval_job_result
- sync.py: poller新增eval job同步，异步读取eval_results.json回写结果

前端:
- EvalCreateView/DimensionCreateView: eval模型过滤扩展(API类型+api_url)
- EvalCreateView: GPU过滤在线节点空闲GPU
- EvalTaskSetupStep: GPU value从数组index改为gpu.id
- BasicMetricSetupStep: ROUGE方法名修正(rouge_1→rouge1)
- EvalView: 新增5秒轮询刷新

Co-Authored-By: Claude <noreply@anthropic.com>

compute/api/main.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import json
 import os
 import math
 import hashlib
@@ -449,6 +450,29 @@ def create_app() -> FastAPI:
                 accelerator_errors, accelerator_warnings, accelerator = _validate_training_accelerator(payload)
                 errors.extend(accelerator_errors)
                 warnings.extend(accelerator_warnings)
+        elif engine == "eval":
+            # Eval engine: validate model path and dataset path
+            if not payload.get("model_name_or_path"):
+                errors.append("model_name_or_path is required for eval")
+            else:
+                path_checks.append(_check_path_item({
+                    "name": "model_name_or_path",
+                    "path": payload.get("model_name_or_path", ""),
+                    "type": "any",
+                    "required": True,
+                }))
+            if payload.get("dataset_path"):
+                path_checks.append(_check_path_item({
+                    "name": "dataset_path",
+                    "path": payload.get("dataset_path", ""),
+                    "type": "file",
+                    "required": True,
+                }))
+            else:
+                errors.append("dataset_path is required for eval")
+            if shutil.which("python") is None:
+                errors.append("python runtime not found")
+
         elif engine == "smoke":
             warnings.append("smoke engine skips model and dataset path checks")
 
@@ -811,6 +835,22 @@ def create_app() -> FastAPI:
             "checksum_sha256": checksum,
         }
 
+    @app.get(f"{route_prefix}/compute/files/read")
+    async def read_file(path: str = Query(...)) -> JSONResponse:
+        """Read a text file from within YG_FT_DATA_ROOT.  Used by the backend
+        to fetch eval results and other job outputs."""
+        data_root = Path(os.getenv("YG_FT_DATA_ROOT", "/data/yg-ft"))
+        target = (data_root / path.lstrip("/\\")).resolve()
+        if not _path_inside(data_root, target):
+            raise HTTPException(status_code=400, detail="path must stay inside YG_FT_DATA_ROOT")
+        if not target.is_file():
+            raise HTTPException(status_code=404, detail="file not found")
+        try:
+            content = target.read_text(encoding="utf-8")
+            return JSONResponse(json.loads(content) if content.strip().startswith("{") else {"content": content})
+        except Exception as exc:
+            raise HTTPException(status_code=500, detail=str(exc))
+
     @app.get(f"{route_prefix}/compute/files/{{file_id}}/download")
     async def download_file(file_id: str) -> FileResponse:
         upload_root = Path(os.getenv("YG_FT_DATA_ROOT", "/data/yg-ft")) / "uploads"