feat: Added application file

src/SentimentAndIntentionAnalysis.py

@@ -1,11 +1,11 @@
 from transformers import pipeline, BartTokenizer, BartForSequenceClassification
 class ZeroShotClassifier:
 
-    def __init__(self, model_name, sentiment_labels, intention_labels):
+    def __init__(self, model_name):
         self.model = self.create_model(model_name)
         self.model_name = model_name
-        self.sentiment_labels = sentiment_labels
-        self.intention_labels = intention_labels
+        self.sentiment_labels = ["Positive", "Negative", "Neutral"]
+        self.intention_labels = ["Inquire", "Inform", "Payment", "Price", "Trade In", "Discount", "Complaint", "Approve", "Selling", "Confusion", "Change Package", "Upgrade", "Purchase", "Help"]
 
     def create_model(self, model_name):
         # Create Model
@@ -15,6 +15,7 @@ class ZeroShotClassifier:
         return classifier
 
     def analyze_text(self, text):
+        
         # Sentiment analysis
         sentiment_result = self.model(text, self.sentiment_labels)
         sentiment = sentiment_result["labels"][0]

src/api.py

@@ -8,13 +8,8 @@ from .data_loader import *
 # Initialize FastAPI app
 app = FastAPI()
 
-#Get model_name, data_path and labels_path
-model_name, data_path, labels_path = get_config()
-
-# Load sentiment labels and intention labels
-sentiment_labels, intention_labels = load_labels(labels_path)
 # Create Analzer
-analyzer = ZeroShotClassifier(model_name=model_name, sentiment_labels=sentiment_labels, intention_labels=intention_labels)
+analyzer = ZeroShotClassifier(model_name='facebook/bart-large-mnli')
 
 class AnalysisResult(BaseModel):
     sentiment: str