uipath v2 (#413)

* submission v2

* small updates

mm_agents/uipath/grounder_client.py

@@ -4,21 +4,20 @@ import os
 
 class GrounderClient(object):
     def __init__(self):
-        # Proxy for hosting UI-TARS + UiElementPredictor
-        # Could be replaced with a VLLM server and grounder (UI-TARS) specific processing
-        # Or any other grounder 
+        # Proxy for hosting finetuned Qwen3VL + UiElementPredictor
+        # Could be replaced with a VLLM server and grounder specific processing
         self.url = ""
 
     async def predict(
-        self, image_base64: str, action_description: str, action: str | None = None
+        self, image_base64: str, action_description: str, action: str, element_description: str | None = None,
     ) -> utils.GroundingOutput:
         request = utils.GroundingRequest(
             description=action_description,
             image_base64=image_base64,
             action_type=action,
+            element_description=element_description
         )
         api_key = os.getenv("SERVICE_KEY")
-
         async with httpx.AsyncClient() as client:
             response = await client.post(
                 self.url,
@@ -26,6 +25,7 @@ class GrounderClient(object):
                     "image_base64": request.image_base64,
                     "action_description": request.description,
                     "action": request.action_type,
+                    "element_description": request.element_description,
                 },
                 headers={
                     "X-API-KEY": api_key
@@ -37,6 +37,8 @@ class GrounderClient(object):
             raise ValueError(f"Prediction failed: {response.text}")
 
         data = response.json()
+        if tuple(data["position"]) == (-1, -1):
+            raise utils.GroundingOutputValidationException(f"Element {request.description} not found in image", request.description)
         return utils.GroundingOutput(
             description=data["description"],
             position=tuple(data["position"]),