Initial commit: MLflow dashboard project

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

schemas.py

@@ -0,0 +1,48 @@
+from pydantic import BaseModel
+from typing import Dict, Optional
+
+
+class ExperimentSummary(BaseModel):
+    experiment_id: str
+    name: str
+    lifecycle_stage: str
+    run_count: int
+
+
+class RunSummary(BaseModel):
+    run_id: str
+    run_name: Optional[str] = None
+    experiment_id: str
+    status: str
+    start_time: Optional[int] = None
+    end_time: Optional[int] = None
+
+
+class RunDetail(BaseModel):
+    run_id: str
+    run_name: Optional[str] = None
+    experiment_id: str
+    status: str
+    start_time: Optional[int] = None
+    end_time: Optional[int] = None
+    params: Dict[str, str] = {}
+    metrics: Dict[str, float] = {}
+    tags: Dict[str, str] = {}
+
+
+class MLflowLink(BaseModel):
+    url: str
+
+
+class ServeRequest(BaseModel):
+    tracking_uri: Optional[str] = None
+    model_uri: str  # e.g. "models:/model_name/1"
+    port: int = 5001
+
+
+class ServeStatus(BaseModel):
+    id: str
+    model_uri: str
+    port: int
+    pid: int
+    status: str  # "running" or "stopped"