Add stored-vector point search path

qdrant/main.py

@@ -169,6 +169,16 @@ class SearchVectorRequest(BaseModel):
     exact: bool = False
     indexed_only: bool = False
 
+class SearchPointRequest(BaseModel):
+    id: int = Field(ge=1)
+    limit: int = Field(default=5, ge=1, le=100)
+    score_threshold: Optional[float] = Field(default=None, ge=0.0, le=1.0)
+    collection: Optional[str] = None
+    filter_metadata: Dict[str, Any] = Field(default_factory=dict)
+    hnsw_ef: Optional[int] = Field(default=None, ge=1, le=512)
+    exact: bool = False
+    indexed_only: bool = False
+
 
 class DeleteRequest(BaseModel):
     ids: List[str]
@@ -271,6 +281,22 @@ def _id_filter(original_id: str) -> Filter:
     return Filter(must=[FieldCondition(key="_original_id", match=MatchValue(value=original_id))])
 
 
+def _lookup_point_id(raw: str):
+    """Parse an existing Qdrant point id without generating a new id."""
+    try:
+        value = int(raw)
+        if value < 0:
+            raise ValueError
+        return value
+    except (TypeError, ValueError):
+        pass
+
+    try:
+        return str(uuid.UUID(raw))
+    except (TypeError, ValueError, AttributeError):
+        raise HTTPException(400, "Invalid point ID. Expected an unsigned integer or UUID.")
+
+
 def _point_id(raw: Optional[str]) -> str:
     """Return a Qdrant-compatible point id.
 
@@ -592,6 +618,43 @@ async def search_file(
     vector = await _embed_bytes(data)
     return _do_search(vector, int(limit), score_threshold, collection, filter_metadata, hnsw_ef, exact, indexed_only)
 
+@app.post("/search/point")
+def search_point(req: SearchPointRequest):
+    """
+    Search using an already-indexed Qdrant point.
+
+    This avoids re-downloading and re-embedding the source artwork through CLIP.
+    """
+    col = _col(req.collection)
+
+    try:
+        points = client.retrieve(
+            collection_name=col,
+            ids=[req.id],
+            with_vectors=True,
+            with_payload=False,
+        )
+    except Exception as e:
+        raise HTTPException(500, f"Qdrant point lookup failed: {e}")
+
+    if not points:
+        raise HTTPException(404, f"Point '{req.id}' not found")
+
+    vector = points[0].vector
+
+    if not isinstance(vector, list) or not vector:
+        raise HTTPException(500, f"Point '{req.id}' has no usable vector")
+
+    return _do_search(
+        vector,
+        req.limit,
+        req.score_threshold,
+        req.collection,
+        req.filter_metadata,
+        req.hnsw_ef,
+        req.exact,
+        req.indexed_only,
+    )
 
 @app.post("/search/vector")
 def search_vector(req: SearchVectorRequest):
@@ -655,7 +718,8 @@ def delete_points(req: DeleteRequest):
 def get_point(point_id: str, collection: Optional[str] = None):
     col = _col(collection)
     try:
-        points = client.retrieve(collection_name=col, ids=[point_id], with_vectors=True)
+        pid = _lookup_point_id(point_id)
+        points = client.retrieve(collection_name=col, ids=[pid], with_vectors=True)
         if not points:
             raise HTTPException(404, f"Point '{point_id}' not found")
         p = points[0]