feat: add LLMProfile pydantic models

tests/webapp/test_profile_manager.py

@@ -0,0 +1,28 @@
+import pytest
+from webapp.models import LLMProfile, ProfileApplyRequest, ProfileApplyResponse
+
+def test_llm_profile_defaults():
+    p = LLMProfile(
+        profile_id="abc",
+        name="Test",
+        model="gpt-4",
+        base_url="http://localhost/v1",
+        api_key="sk-test",
+    )
+    assert p.timeout_seconds == 30
+    assert p.created_at != ""
+    assert p.updated_at != ""
+
+def test_profile_apply_request_fields():
+    req = ProfileApplyRequest(
+        scenario_path="scenarios/offline/sample.yaml",
+        judge_profile_id="id1",
+        answer_profile_id="id2",
+        dataset_profile_id=None,
+    )
+    assert req.judge_profile_id == "id1"
+    assert req.dataset_profile_id is None
+
+def test_profile_apply_response():
+    resp = ProfileApplyResponse(scenario_path="scenarios/offline/sample.yaml", patched_fields=["judge_model"])
+    assert "judge_model" in resp.patched_fields

webapp/models.py

@@ -2,11 +2,16 @@
 
 from __future__ import annotations
 
+from datetime import datetime, timezone
 from typing import Any
 
 from pydantic import BaseModel, Field
 
 
+def _utcnow_iso() -> str:
+    return datetime.now(timezone.utc).isoformat()
+
+
 class RunSummary(BaseModel):
     """Compact description of a single evaluation run for list views."""
 
@@ -114,6 +119,45 @@ class TriggerEvaluationResponse(BaseModel):
     task_id: str
 
 
+class LLMProfile(BaseModel):
+    """A named LLM connection configuration that can be reused across tasks."""
+
+    profile_id: str
+    name: str
+    model: str
+    base_url: str
+    api_key: str
+    timeout_seconds: int = 30
+    created_at: str = Field(default_factory=_utcnow_iso)
+    updated_at: str = Field(default_factory=_utcnow_iso)
+
+
+class CreateProfileRequest(BaseModel):
+    """Request body for creating or updating an LLM profile."""
+
+    name: str
+    model: str
+    base_url: str
+    api_key: str
+    timeout_seconds: int = 30
+
+
+class ProfileApplyRequest(BaseModel):
+    """Request body to patch LLM profile selections into a scenario YAML."""
+
+    scenario_path: str
+    judge_profile_id: str | None = None
+    answer_profile_id: str | None = None
+    dataset_profile_id: str | None = None
+
+
+class ProfileApplyResponse(BaseModel):
+    """Response after patching a scenario YAML with profile settings."""
+
+    scenario_path: str
+    patched_fields: list[str] = Field(default_factory=list)
+
+
 def jsonable(value: Any) -> Any:
     """Convert NaN/inf floats into None so the payload stays valid JSON."""
     import math