Update app.py

app.py

@@ -1,9 +1,12 @@
 import gradio as gr
+import os 
+hf_token = os.environ.get('HF_TOKEN')
 
 lpmc_client = gr.load("seungheondoh/LP-Music-Caps-demo", src="spaces")
+
 from gradio_client import Client
 
-client = Client("https://ysharma-explore-llamav2-with-tgi.hf.space/")
+client = Client("https://fffiloni-test-llama-api.hf.space/", api_key=hf_token)
 
 from diffusers import DiffusionPipeline
 import torch
@@ -59,20 +62,23 @@ def infer(audio_file):
     #print(f"SUMMARY: {summary_result}")
 
     llama_q = f"""
-
+    [INST] <<SYS>>\n
+    
     I'll give you music description, then i want you to provide an illustrative image description that would fit well with the music.
     
     Answer with only one image description. Never do lists. Do not processs each segment, but provide a summary for the whole instead.
 
     Here's the music description :
 
+    \n<</SYS>>\n\n{} [/INST]
+
     {cap_result}
     
     """
 
     result = client.predict(
     				llama_q,	# str in 'Message' Textbox component
-    				api_name="/chat_1"
+    				api_name="/predict"
     )