Update app.py

app.py

@@ -6,7 +6,7 @@ lpmc_client = gr.load("seungheondoh/LP-Music-Caps-demo", src="spaces")
 
 from gradio_client import Client
 
-client = Client("https://fffiloni-test-llama-api.hf.space/", hf_token=hf_token)
+client = Client("https://fffiloni-test-llama-api-debug.hf.space/", hf_token=hf_token)
 lyrics_client = Client("https://fffiloni-music-to-lyrics.hf.space/")
 visualizer_client = Client("https://fffiloni-animated-audio-visualizer.hf.space/")
 
@@ -139,6 +139,7 @@ def infer(audio_file, has_lyrics):
     gr.Info("Calling Llama2 ...")
     result = client.predict(
     				llama_q,	# str in 'Message' Textbox component
+                    "M2I",
     				api_name="/predict"
     )    
     
@@ -146,25 +147,25 @@ def infer(audio_file, has_lyrics):
 
     print(f"Llama2 result: {result}")
 
-    gr.Info("Prompt Optimization ...")
-    get_shorter_prompt = f"""
-    From this image description, please provide a short but efficient summary for a good Stable Diffusion prompt:
-    '{result}'
-    """
+    #gr.Info("Prompt Optimization ...")
+    #get_shorter_prompt = f"""
+    #From this image description, please provide a short but efficient summary for a good Stable Diffusion prompt:
+    #'{result}'
+    #"""
 
-    shorten = client.predict(
-    				get_shorter_prompt,	# str in 'Message' Textbox component
-    				api_name="/predict"
-    )  
+    #shorten = client.predict(
+    #				get_shorter_prompt,	# str in 'Message' Textbox component
+    #				api_name="/predict"
+    #)  
 
-    print(f'SHORTEN PROMPT: {shorten}')
+    #print(f'SHORTEN PROMPT: {shorten}')
 
     # ———
     print("""———
     Calling SD-XL ...
     """)
     gr.Info('Calling SD-XL ...')
-    prompt = shorten
+    prompt = result
     conditioning, pooled = compel(prompt)
     images = pipe(prompt_embeds=conditioning, pooled_prompt_embeds=pooled).images[0]