first-update

backend/app/api/v1/eval/__init__.py

@@ -0,0 +1,100 @@
+"""
+Evaluation API Router
+"""
+from typing import List, Optional
+from uuid import UUID
+from pydantic import BaseModel
+from fastapi import APIRouter, Depends, HTTPException
+from sqlalchemy.ext.asyncio import AsyncSession
+from sqlalchemy import select
+from app.core.database import get_db
+from app.models.models import EvalDataset, Task
+from app.schemas.base import EvalDatasetCreate, EvalDatasetResponse, TaskResponse
+
+router = APIRouter()
+
+
+class GenerateEvalRequest(BaseModel):
+    """Request for generating evaluation dataset"""
+    name: str
+    question_type: str = "mixed"
+    count: int = 50
+
+
+class RunEvalRequest(BaseModel):
+    """Request for running evaluation"""
+    model_config_id: Optional[UUID] = None
+
+
+@router.get("/", response_model=dict)
+async def list_eval_datasets(project_id: UUID, db: AsyncSession = Depends(get_db)):
+    """List evaluation datasets"""
+    result = await db.execute(
+        select(EvalDataset).where(EvalDataset.project_id == project_id).order_by(EvalDataset.created_at.desc())
+    )
+    datasets = result.scalars().all()
+
+    return {"datasets": [EvalDatasetResponse.model_validate(d) for d in datasets]}
+
+
+@router.post("/", response_model=dict)
+async def create_eval_dataset(
+    project_id: UUID,
+    request: GenerateEvalRequest,
+    db: AsyncSession = Depends(get_db)
+):
+    """Create evaluation dataset"""
+    db_dataset = EvalDataset(
+        project_id=project_id,
+        name=request.name,
+        question_type=request.question_type
+    )
+    db.add(db_dataset)
+    await db.commit()
+    await db.refresh(db_dataset)
+
+    return {"id": str(db_dataset.id)}
+
+
+@router.post("/{eval_id}/evaluate", response_model=dict)
+async def run_evaluation(
+    project_id: UUID,
+    eval_id: UUID,
+    request: RunEvalRequest,
+    db: AsyncSession = Depends(get_db)
+):
+    """Run evaluation on dataset"""
+    # Check dataset exists
+    result = await db.execute(
+        select(EvalDataset).where(EvalDataset.id == eval_id, EvalDataset.project_id == project_id)
+    )
+    dataset = result.scalar_one_or_none()
+    if not dataset:
+        raise HTTPException(status_code=404, detail="Evaluation dataset not found")
+
+    # Create evaluation task
+    task = Task(
+        project_id=project_id,
+        task_type="eval",
+        status="pending"
+    )
+    db.add(task)
+    await db.commit()
+    await db.refresh(task)
+
+    # TODO: Start evaluation in background
+
+    return {"task_id": str(task.id), "message": "Evaluation task started"}
+
+
+@router.get("/results", response_model=dict)
+async def get_eval_results(project_id: UUID, task_id: UUID, db: AsyncSession = Depends(get_db)):
+    """Get evaluation results"""
+    result = await db.execute(
+        select(Task).where(Task.id == task_id, Task.project_id == project_id)
+    )
+    task = result.scalar_one_or_none()
+    if not task:
+        raise HTTPException(status_code=404, detail="Task not found")
+
+    return TaskResponse.model_validate(task)