diff --git a/vision_agent/tools/tools.py b/vision_agent/tools/tools.py
index 71646c45..ed48fafe 100644
--- a/vision_agent/tools/tools.py
+++ b/vision_agent/tools/tools.py
@@ -473,7 +473,11 @@ def florence2_sam2_image(
 
 
 def florence2_sam2_video_tracking(
-    prompt: str, frames: List[np.ndarray], chunk_length: Optional[int] = None
+    prompt: str,
+    frames: List[np.ndarray],
+    chunk_length: Optional[int] = None,
+    iou_threshold: Optional[float] = None,
+    nms_threshold: Optional[float] = None,
 ) -> List[List[Dict[str, Any]]]:
     """'florence2_sam2_video_tracking' is a tool that can segment and track multiple
     entities in a video given a text prompt such as category names or referring
@@ -486,6 +490,10 @@ def florence2_sam2_video_tracking(
         frames (List[np.ndarray]): The list of frames to ground the prompt to.
         chunk_length (Optional[int]): The number of frames to re-run florence2 to find
             new objects.
+        iou_threshold (Optional[float]): Value between 0.1 and 1.0.
+            The IoU threshold value used to compare last_predictions and new_predictions objects.
+        nms_threshold (Optional[float]): Value between 0.1 and 1.0.
+            The non-maximum suppression threshold value used to filter the Florencev2 predictions.
 
     Returns:
         List[List[Dict[str, Any]]]: A list of list of dictionaries containing the label
@@ -520,6 +528,10 @@ def florence2_sam2_video_tracking(
     }
     if chunk_length is not None:
         payload["chunk_length"] = chunk_length  # type: ignore
+    if iou_threshold is not None:
+        payload["iou_threshold"] = iou_threshold  # type: ignore
+    if nms_threshold is not None:
+        payload["nms_threshold"] = nms_threshold  # type: ignore
     data: Dict[str, Any] = send_inference_request(
         payload, "florence2-sam2", files=files, v2=True
     )