Update app.py

app.py

@@ -19,45 +19,25 @@ print("DEBUG ", encoder_text_path)
 os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
 os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
 
-
 python_path = hf_hub_download(repo_id="PierreHanna/TextRetrieval", repo_type="space", filename="models.py",
                             use_auth_token=os.environ['TOKEN'])
-
 print(python_path)
 os.system('ls -la')
-#from models import *
-
 sys.path.append(os.environ['PRIVATE_DIR'])
 from models import *
-
 preprocess_model, model = get_models()
-
 index_path = hf_hub_download(repo_id="PierreHanna/TextRetrieval", repo_type="space", filename=os.environ['INDEX'],
                             use_auth_token=os.environ['TOKEN'])
 indexnames_path = hf_hub_download(repo_id="PierreHanna/TextRetrieval", repo_type="space", filename=os.environ['INDEX_NAMES'],
                             use_auth_token=os.environ['TOKEN'])
 catalog_path = hf_hub_download(repo_id="PierreHanna/TextRetrieval", repo_type="space", filename=os.environ['CATALOG'],
                             use_auth_token=os.environ['TOKEN'])
-
-#url
-url_dict={}
-with open(catalog_path) as csv_file:
-    csv_reader = csv.reader(csv_file, delimiter=';')
-    for row in csv_reader:
-      f = row[2].split('/')[-1]
-      url_dict[f.split('/')[-1][:-4]] = row[2]
-
-# names index
+url_dict=get_durl(catalog_path)
 audio_names = joblib.load(open(indexnames_path, 'rb'))
-
-# load embed audio catalog
 index = faiss.read_index(index_path)
-
 encoder_text = tf.keras.models.load_model(encoder_text_path)
 
-
 def process(prompt, lang):
-
     now = datetime.datetime.now()
     print()
     print('*************')
@@ -110,7 +90,6 @@ poc_examples = [#[["I love learning machine learning"],["autre"]]
           ["90 eurodance beat","en"],
 ]
 
-
 outputs = [gr.Audio(label="Track 1"), gr.Audio(label="Track 2"), gr.Audio(label="Track 3"), gr.Audio(label="Track 4"), gr.Audio(label="Track 5")]
 demo1 = gr.Interface(fn=process, inputs=inputs, outputs=outputs, examples=poc_examples, cache_examples=False)