Update app.py

app.py

@@ -21,16 +21,10 @@ SPREADSHEET_ID = "1CsBub3Jlwyo7WHMQty6SDnBShIZMjl5XTVSoOKrxZhc"
 RANGE_NAME = 'Sheet1!A1:E'
 SERVICE_ACCOUNT_FILE = r"C:\Users\bhagy\AI\credentials.json"
 
+
 csv_file_path = r"C:\Users\bhagy\OneDrive\Desktop\INFOSYS PROJECT\900_products_dataset.csv"
 
-persist_dir = r"C:\Users\bhagy\OneDrive\Desktop\INFOSYS PROJECT\chromadb_storage"
-os.makedirs(persist_dir, exist_ok=True)  # Ensure the directory exists
-print(f"Persistence directory: {persist_dir}")
 
-chroma_client = Client(Settings(
-    persist_directory=persist_dir,  # Use /tmp/ for Hugging Face Spaces
-    allow_reset=True  # Enable reset to prevent database issues
-))
 class CustomEmbeddingFunction:
     def __init__(self, model_name="sentence-transformers/all-MiniLM-L6-v2"):
         self.tokenizer = AutoTokenizer.from_pretrained(model_name)
@@ -43,12 +37,9 @@ class CustomEmbeddingFunction:
         embeddings = outputs.last_hidden_state.mean(dim=1).squeeze().numpy()
         return embeddings
 
-sentiment_pipeline = pipeline("sentiment-analysis")
-# chroma_client = Client(Settings(
-#     persist_directory="/tmp/chromadb_storage",  # Directory to store ChromaDB data
-#     allow_reset=True  # Enable reset to prevent database issues
-# ))
 
+sentiment_pipeline = pipeline("sentiment-analysis")
+chroma_client = Client(Settings(persist_directory="chromadb_storage"))
 embedding_fn = CustomEmbeddingFunction()
 collection_name = "crm_data"
 
@@ -57,20 +48,6 @@ try:
 except Exception:
     collection = chroma_client.create_collection(collection_name)
 
-# chroma_client = Client(Settings(persist_directory="chromadb_storage"))
-# chroma_client = Client(Settings(
-#     persist_directory="/home/user/app/chromadb_storage",
-#     tenant="default_tenant", 
-#     database="default_db"     
-# ))
-# embedding_fn = CustomEmbeddingFunction()
-# collection_name = "crm_data"
-
-# try:
-#     collection = chroma_client.get_collection(collection_name)
-# except Exception:
-#     collection = chroma_client.create_collection(collection_name)
-
 def get_google_sheets_service():
     creds = Credentials.from_service_account_file(
         SERVICE_ACCOUNT_FILE,
@@ -107,7 +84,7 @@ def update_google_sheet(transcribed_text, sentiment,objection, recommendations,o
 
 load_dotenv()
 hf_token= os.getenv("HUGGINGFACE_TOKEN")
-# login(token=huggingface_api_key)
+login(token=hf_token)
 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]}****")
@@ -202,6 +179,7 @@ def query_crm_data_with_context(prompt, top_k=3):
         return ["Error in querying recommendations."]
 
 
+
 sentence_model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')
 faiss_index = faiss.IndexFlatL2(384)