Enable text-only embedding request

handler.py

@@ -47,6 +47,14 @@ def get_image_embedding(image_base64, model, transformer):
         image_feature = image_feature / image_feature.norm(dim=-1, keepdim=True)
     return image_feature.cpu().numpy().tolist()
 
+def get_text_embedding(text, model):
+    """Convert text query to tensor."""
+    text_tensor = preprocess_text(text)
+    with torch.no_grad():
+        text_feature = model.encode_text(text_tensor)
+        text_feature = text_feature / text_feature.norm(dim=-1, keepdim=True)
+    return text_feature.cpu().numpy().tolist()
+
 class EndpointHandler:
     def __init__(self, path: str = ""):
         """
@@ -80,9 +88,10 @@ class EndpointHandler:
         Returns:
             dict: {"embedding": [float, float, ...]}
         """
-        # Parse inputs
+        
         inputs = data.pop("inputs", data)
-        if "sketch" in inputs:
+        # text-sketch embedding
+        if len(inputs) == 2 and "sketch" in inputs and "text" in inputs:
             sketch_base64 = inputs.get("sketch", "")
             text_query = inputs.get("text", "")
             if not sketch_base64 or not text_query:
@@ -91,11 +100,19 @@ class EndpointHandler:
             # Generate Fused Embedding
             fused_embedding = get_fused_embedding(sketch_base64, text_query, self.model, self.transform)
             return {"embedding": fused_embedding}
-        elif "image" in inputs:
+        # image-only embedding
+        elif len(inputs) == 1 and "image" in inputs:
             image_base64 = inputs.get("image", "")
             if not image_base64:
                 return {"error": "Image 'image' (base64) is required input."}
             embedding = get_image_embedding(image_base64, self.model, self.transform)
             return {"embedding": embedding}
+        # text-only embedding
+        elif len(inputs) == 1 and "text" in inputs:
+            text_query = inputs.get("text", "")
+            if not text_query:
+                return {"error": "Text 'text' is required input."}
+            embedding = get_text_embedding(text_query, self.model)
+            return {"embedding": embedding}
         else:
-            return {"error": "Input 'sketch' or 'image' is required."}
+            return {"error": "Invalid request."}