Update app.py

app.py

@@ -37,7 +37,7 @@ class CustomEmbeddingFunction:
         embeddings = outputs.last_hidden_state.mean(dim=1).squeeze().numpy()
         return embeddings
 
-# Initialize components
+
 sentiment_pipeline = pipeline("sentiment-analysis")
 chroma_client = Client(Settings(persist_directory="chromadb_storage"))
 embedding_fn = CustomEmbeddingFunction()
@@ -83,10 +83,12 @@ def update_google_sheet(transcribed_text, sentiment,objection, recommendations,o
         st.error(f"Failed to update Google Sheets: {e}")
 
 load_dotenv()
-huggingface_api_key= os.getenv("HUGGINGFACE_TOKEN")
-if not huggingface_api_key:
-    st.error("Hugging Face API key not found. Please set the HUGGINGFACE_TOKEN environment variable.")
-    st.stop()
+hf_token= os.getenv("huggingface_api_key")
+# login(token=huggingface_api_key)
+if not hf_token:
+    raise ValueError("Hugging Face API key not found! Please set the HUGGINGFACE_TOKEN variable.")
+print(f"API Key Loaded: {hf_token[:5]}****")
+
 model_name = "tabularisai/multilingual-sentiment-analysis"
 model = AutoModelForSequenceClassification.from_pretrained(model_name)
 tokenizer = AutoTokenizer.from_pretrained(model_name)
@@ -104,7 +106,7 @@ def analyze_sentiment(text):
         
         print(f"Sentiment Analysis Result: {result}")
         
-        # Map raw labels to sentiments
+        
         sentiment_map = {
             'Very Negative': "NEGATIVE",
             'Negative': "NEGATIVE",