Update app.py

app.py

@@ -4,11 +4,11 @@ from huggingface_hub import InferenceClient
 from sentence_transformers import SentenceTransformer
 import torch
 
-#theme = gr.themes.Base(
-    #primary_hue=gr.themes.Color(c100="#dbeafe", c200="#bfdbfe", c300="#93c5fd", c400="#60a5fa", c50="#eff6ff", c500="rgba(59.925932017543865, 128.98921451355668, 241.82500000000002, 1)", c600="#2563eb", c700="#1d4ed8", c800="#1e40af", c900="#1e3a8a", c950="#1d3660"),
-    #secondary_hue="green",
-#)
-#with gr.Blocks(theme=theme) as demo:
+theme = gr.themes.Base(
+    primary_hue=gr.themes.Color(c100="#dbeafe", c200="#bfdbfe", c300="#93c5fd", c400="#60a5fa", c50="#eff6ff", c500="rgba(59.925932017543865, 128.98921451355668, 241.82500000000002, 1)", c600="#2563eb", c700="#1d4ed8", c800="#1e40af", c900="#1e3a8a", c950="#1d3660"),
+    secondary_hue="green",
+)
+
     
 # SEMANTIC SEARCH STEP 2
 with open("songs_knowledge_base_2.txt", "r", encoding="utf-8") as file:
@@ -102,11 +102,6 @@ def get_top_chunks(query, chunk_embeddings, text_chunks):
   # Return the list of most relevant chunks
   return top_chunks
 
-
-
-    
-
-
 client = InferenceClient('Qwen/Qwen2.5-7B-Instruct-1M')
 def respond(message, history):
     info = get_top_chunks(message, chunk_embeddings, cleaned_chunks)
@@ -126,5 +121,8 @@ def echo(message, history):
 def yes_no(message, history):
     responses = ["Yes", "No"]
     return random.choice(responses)
-chatbot = gr.ChatInterface(respond, type="messages", title = "AuxAI", description = "Hi! I’m AuxAI, your friendly music recommendation assistant. Tell me your mood, genre, or style and I’ll suggest some songs!")
-chatbot.launch()
+with gr.Blocks(theme=theme) as chatbot:
+    with gr.Row():
+        gr.ChatInterface(respond, type="messages", title = "AuxAI", description = "Hi! I’m AuxAI, your friendly music recommendation assistant. Tell me your mood, genre, or style and I’ll suggest some songs!")
+
+chatbot.launch()