feat: persist user comments per video with author and source filters

Extends /predict to accept video_id, author and a persist flag, so a manual post lands in Supabase under source=user_comment with the team-member name attached. /predictions now wraps the rows under a predictions key and supports filtering by source. The list_predictions helper and SQL schema gain the author column and a matching source filter.

src/api/routes/predict.py

@@ -21,13 +21,16 @@ router = APIRouter(tags=["Prediction"])
 @router.post("/predict", response_model=PredictResponse)
 async def predict(request: PredictRequest):
     response = predict_single(request.text, request.threshold)
-    save_prediction(
-        text=request.text,
-        result=response,
-        source="api_direct",
-        threshold=request.threshold,
-        latency_ms=response.latency_ms,
-    )
+    if request.persist:
+        save_prediction(
+            text=request.text,
+            result=response,
+            source="user_comment" if request.author else "api_direct",
+            video_id=request.video_id,
+            author=request.author,
+            threshold=request.threshold,
+            latency_ms=response.latency_ms,
+        )
     return response
 
 
@@ -110,7 +113,8 @@ async def predict_video(request: VideoRequest):
 @router.get("/predictions")
 async def get_predictions(
     video_id: str | None = Query(default=None),
+    source: str | None = Query(default=None),
     limit: int = Query(default=50, ge=1, le=200),
 ):
-    rows = list_predictions(video_id=video_id, limit=limit)
-    return rows
+    rows = list_predictions(video_id=video_id, source=source, limit=limit)
+    return {"predictions": rows, "total": len(rows)}

src/api/schemas.py

@@ -8,6 +8,9 @@ from pydantic import BaseModel, Field, field_validator
 class PredictRequest(BaseModel):
     text: str = Field(..., min_length=1, max_length=5000)
     threshold: float = Field(0.5, ge=0.0, le=1.0)
+    video_id: Optional[str] = None
+    author: Optional[str] = None
+    persist: bool = True
 
     @field_validator("text")
     @classmethod

src/db/supabase_client.py

@@ -51,6 +51,7 @@ def save_prediction(
     video_url: str | None = None,
     threshold: float | None = None,
     latency_ms: float | None = None,
+    author: str | None = None,
 ) -> None:
     """Persist a single prediction, silently no-op when DB is not configured.
 
@@ -87,6 +88,7 @@ def save_prediction(
             "threshold": threshold,
             "latency_ms": latency_ms if latency_ms is not None else data.get("latency_ms"),
             "source": source,
+            "author": author,
         }
         client.table(_TABLE).insert(row).execute()
     except Exception as exc:
@@ -96,6 +98,7 @@ def save_prediction(
 def list_predictions(
     video_id: str | None = None,
     limit: int = 50,
+    source: str | None = None,
 ) -> list[dict]:
     """Return latest predictions ordered by ``created_at`` desc.
 
@@ -109,6 +112,8 @@ def list_predictions(
         query = client.table(_TABLE).select("*").order("created_at", desc=True)
         if video_id:
             query = query.eq("video_id", video_id)
+        if source:
+            query = query.eq("source", source)
         query = query.limit(max(1, min(limit, 200)))
         response = query.execute()
         return list(getattr(response, "data", []) or [])

supabase/predictions_setup.sql

@@ -17,9 +17,13 @@ create table if not exists public.predictions (
     model_used  text,
     threshold   double precision,
     latency_ms  double precision,
-    source      text          -- "api_direct" | "video_fetch" | "user_comment"
+    source      text,         -- "api_direct" | "video_fetch" | "user_comment"
+    author      text
 );
 
+-- Migration: add author column on existing installs
+alter table public.predictions add column if not exists author text;
+
 -- 2. Indexes for the queries the API will run
 create index if not exists predictions_created_at_idx
     on public.predictions (created_at desc);