feat: complete production-quality Model Router AI traffic control platform

backend/app/experiments/service.py

@@ -0,0 +1,85 @@
+import uuid
+import datetime
+from typing import Dict, Any, List
+from sqlalchemy import select, func
+from sqlalchemy.ext.asyncio import AsyncSession
+from app.storage.models import ExperimentRecord, ExperimentRunRecord
+
+
+async def log_experiment_run(
+    session: AsyncSession,
+    experiment_id: str,
+    request_id: str,
+    policy: str,
+    model: str,
+    cost: float,
+    latency_ms: float,
+):
+    run = ExperimentRunRecord(
+        id=str(uuid.uuid4()),
+        experiment_id=experiment_id,
+        request_id=request_id,
+        assigned_policy=policy,
+        selected_model=model,
+        cost=cost,
+        latency_ms=latency_ms,
+    )
+    session.add(run)
+    
+    # Increment sample count
+    res = await session.execute(select(ExperimentRecord).filter_by(id=experiment_id))
+    exp = res.scalar_one_or_none()
+    if exp:
+        exp.sample_count += 1
+    await session.commit()
+
+
+async def get_experiment_summary(
+    session: AsyncSession,
+    experiment_id: str,
+) -> Dict[str, Any]:
+    res = await session.execute(select(ExperimentRecord).filter_by(id=experiment_id))
+    exp = res.scalar_one_or_none()
+    if not exp:
+        return {}
+
+    # Calculate metrics for Policy A vs Policy B
+    runs_a = await session.execute(
+        select(
+            func.count(ExperimentRunRecord.id),
+            func.avg(ExperimentRunRecord.cost),
+            func.avg(ExperimentRunRecord.latency_ms),
+        ).filter_by(experiment_id=experiment_id, assigned_policy=exp.policy_a)
+    )
+    count_a, cost_a, lat_a = runs_a.one()
+
+    runs_b = await session.execute(
+        select(
+            func.count(ExperimentRunRecord.id),
+            func.avg(ExperimentRunRecord.cost),
+            func.avg(ExperimentRunRecord.latency_ms),
+        ).filter_by(experiment_id=experiment_id, assigned_policy=exp.policy_b)
+    )
+    count_b, cost_b, lat_b = runs_b.one()
+
+    return {
+        "id": exp.id,
+        "name": exp.name,
+        "description": exp.description,
+        "policy_a": exp.policy_a,
+        "policy_b": exp.policy_b,
+        "status": exp.status,
+        "total_samples": exp.sample_count,
+        "results": {
+            exp.policy_a: {
+                "sample_count": count_a or 0,
+                "avg_cost_usd": round(cost_a or 0.0, 6),
+                "avg_latency_ms": round(lat_a or 0.0, 1),
+            },
+            exp.policy_b: {
+                "sample_count": count_b or 0,
+                "avg_cost_usd": round(cost_b or 0.0, 6),
+                "avg_latency_ms": round(lat_b or 0.0, 1),
+            },
+        },
+    }