refactor: move k3_report_test.py to bash/case and make repo-root detection robust

bash/case/api_case.sh

@@ -0,0 +1,25 @@
+
+curl -X POST https://api.vectron.meta-stone.com/v1/chat/completions \
+  -H "Authorization: Bearer sk-xxx" \
+  -H "Content-Type: application/json" \
+  -d '{
+  "model": "ZhipuAi/GLM-5.2",
+  "messages": [
+    {
+      "role": "user",
+      "content": "Say hello in one sentence."
+    }
+  ],
+    "thinking": {
+        "type": "disabled",
+        "type": "string",
+        "budget_tokens": 0
+    },
+    "extra_body": {
+    "thinking": {
+        "type": "disabled",
+        "type": "string",
+        "budget_tokens": 10
+    }
+    }
+}'

bash/case/k3_report_test.py

@@ -31,7 +31,18 @@ import subprocess
 import sys
 from pathlib import Path
 
-ROOT = Path(__file__).resolve().parent
+def _find_repo_root() -> Path:
+    """向上查找，直到目录下存在 bash/run.py。"""
+    p = Path(__file__).resolve().parent
+    while p != p.parent:
+        if (p / "bash" / "run.py").exists():
+            return p
+        p = p.parent
+    # 兜底：脚本所在目录的上级（兼容放在 bash/case/ 的情况）
+    return Path(__file__).resolve().parent.parent
+
+
+ROOT = _find_repo_root()
 
 # ---------------------------------------------------------------------------
 # Kimi K3 report -> evalscope dataset 映射
@@ -192,8 +203,8 @@ def build_run_command(
         sys.executable,
         str(ROOT / "bash" / "run.py"),
         "--datasets", dataset,
-        "--model", model,
-        "--api-url", api_url,
+        # "--model", model,
+        # "--api-url", api_url,
         "--output-dir", output_dir,
         "--folder-name", folder_name,
         "--config", config,