Update app.py

app.py

@@ -11,13 +11,15 @@ def classify(text):
 
 def predict_sentiment(text, model):
     if model == "finiteautomata/bertweet-base-sentiment-analysis":
-        pipe = pipeline("text-classification", model="finiteautomata/bertweet-base-sentiment-analysis")
-        out = pipe(text, return_all_scores=True)
-        return {pred["label"]: pred["score"] for pred in out[0]}
+        # pipe = pipeline("text-classification", model="finiteautomata/bertweet-base-sentiment-analysis")
+        # out = pipe(text, return_all_scores=True)
+        # return {pred["label"]: pred["score"] for pred in out[0]}
+        return {"cathf": 0.3, "doghf": 0.7}
     elif model == "vader":
-        nltk.download('vader_lexicon')
-        sia = SentimentIntensityAnalyzer()
-        return sia.polarity_scores(text)
+        # nltk.download('vader_lexicon')
+        # sia = SentimentIntensityAnalyzer()
+        # return sia.polarity_scores(text)
+        return {"catv": 0.3, "dogv": 0.7}