Update app.py

app.py

@@ -20,7 +20,7 @@ speaker_embeddings = {
 }
 
 def getNews(search_key):
-    return requests.get ("https://newsapi.org/v2/everything?q=" +search_key+ "&pagesize=3&apiKey=3bca07c913ec4703a23f6ba03e15b30b").content.decode("utf-8")
+    return requests.get ("https://newsapi.org/v2/everything?pagesize=3&apiKey=3bca07c913ec4703a23f6ba03e15b30b&q="+search_key).content.decode("utf-8")
 
 def getHeadlines():
     return requests.get ("https://newsapi.org/v2/top-headlines?country=us&apiKey=3bca07c913ec4703a23f6ba03e15b30b").content.decode("utf-8")
@@ -32,14 +32,14 @@ def predict(text, preset):
 
     # text = getNews ()
     # inputs = processor(text=text, return_tensors="pt")
-    inputs = processor(text=getNews(text), return_tensors="pt")
+    inputs = processor(text=textwrap.shorten(getNews(text), width=250), return_tensors="pt")
 
     # limit input length
     input_ids = inputs["input_ids"]
     input_ids = input_ids[..., :model.config.max_text_positions]
 
     # cmu_us_awb_arctic-wav-arctic_a0002.npy
-    speaker_embedding = np.load('spkemb/cmu_us_clb_arctic-wav-arctic_a0144.npy')
+    speaker_embedding = np.load('spkemb/cmu_us_bdl_arctic-wav-arctic_a0009.npy')
     speaker_embedding = torch.tensor(speaker_embedding).unsqueeze(0)
     speech = model.generate_speech(input_ids, speaker_embedding, vocoder=vocoder)