Update app.py

app.py

@@ -26,24 +26,30 @@ captioning_client = Client(CAPTION_SPACE)
 llm_client = Client(LLM_SPACE)
 
 def generate_compliment(image):
+    caption_text = ""
+    compliment_text = ""
+    
+    # Convert PIL image to bytes
+    buffered = io.BytesIO()
+    image.save(buffered, format="JPEG")
+    image_bytes = buffered.getvalue()
+    
+    # Connect to the captioning model on Hugging Face Spaces
     try:
-        # Convert PIL image to bytes
-        buffered = io.BytesIO()
-        image.save(buffered, format="JPEG")
-        image_bytes = buffered.getvalue()
-
-        # Get caption for the image using Gradio client
-        caption_response = captioning_client.predict("/create_captions_rich", { "image": file(image_bytes) })
+        captioning_space = Client("gokaygokay/SD3-Long-Captioner")
+        caption_response = captioning_space.predict("/create_captions_rich", {"image": file(image_bytes)})
         caption_text = caption_response.data[0]
-
-        # Generate compliment based on the caption using language model
-        llm_response = llm_client.predict(SYSTEM_PROMPT, f"Caption: {caption_text}\nCompliment: ")
+    except Exception as e:
+        return "Error", f"Failed to get caption. Exception: {str(e)}"
+    
+    # Connect to the LLM model on Hugging Face Spaces
+    try:
+        llm_space = Client("hysts/zephyr-7b")
+        llm_response = llm_space.predict({"system_prompt": "...", "message": f"Caption: {caption_text}\nCompliment: "})
         compliment_text = llm_response.data[0]
-
     except Exception as e:
-        caption_text = f"Error: Failed to get caption. Exception: {str(e)}"
-        compliment_text = "Error: Failed to generate compliment."
-
+        return "Error", f"Failed to generate compliment. Exception: {str(e)}"
+    
     return caption_text, compliment_text
 
 # Gradio interface