fix and log inputs

handler.py

@@ -7,7 +7,7 @@ import requests
 
 
 class EndpointHandler:
-    def __init__(self, path=""):
+    def __init__(self):
         self.processor = LlavaNextProcessor.from_pretrained("llava-hf/llava-v1.6-mistral-7b-hf")
 
     
@@ -26,23 +26,32 @@ class EndpointHandler:
     def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
         """
         data args:
-            text (:obj: `str`)
-            files (:obj: `list`) - List of URLs to images
+            inputs (:obj: `dict`)
         Return:
             A :obj:`list` | `dict`: will be serialized and returned
         """
         # get inputs
         inputs = data.pop("inputs", data)
+
+        if not inputs:
+            return f"Inputs not in payload got {data.keys()}"
+        
         # get additional date field0
         prompt = inputs.pop("prompt", None)
         image_url = inputs.pop("image", None)
 
-        print(image_url)
-        print(prompt)
-
         if image_url is None:
             return "You need to upload an image URL for LLaVA to work."
 
+        if prompt is None:
+            prompt = "Can you describe this picture focusing on specifics visual artifacts and ambiance (objects, colors, person, athmosphere..). Please stay concise only output keywords and concepts detected."
+        
+        if not self.model:
+            return "Model was not initialized"
+        
+        if not self.processor:
+            return "Processor was not initialized"
+        
         # Create a temporary directory
         with TemporaryDirectory() as tmpdirname:
             # Download the image

test_inference_endpoint.py

@@ -1,4 +1,5 @@
 import os
+import json
 import requests
 from dotenv import load_dotenv
 
@@ -18,8 +19,9 @@ def call(payload):
     response = requests.post(
         URL,
         headers=headers,
-        json=payload
+        json=json.dumps(payload)
     )
+    print(response)
     return response.json()
 
 def test_local(payload):