Update app.py

app.py

@@ -11,18 +11,12 @@ from langchain.prompts import PromptTemplate
 from sentence_transformers import SentenceTransformer
 import torch
 from transformers import AutoModelForSequenceClassification, AutoTokenizer
-import logging
 
 # Set up environment, Pinecone is a database
-st.write(
-	"Has environment variables been set:",
-	os.environ["API_TOKEN"] == st.secrets["HUGGINGFACEHUB_API_TOKEN"] and
-    os.environ["PINECONE_API_KEY"] == st.secrets["PINECONE_API_KEY"] and
-    os.environ["Index_Name"] == st.secrets["Index_Name"])
-cache_dir = os.getenv("CACHE_DIR")  # Directory for cache
-Huggingface_token = os.getenv("API_TOKEN")  # Huggingface API key
-pc = Pinecone(api_key=os.getenv("PINECONE_API_KEY"))  # Database API key
-index = pc.Index(os.getenv("Index_Name"))  # Database index name
+cache_dir = None  # Directory for cache
+Huggingface_token = st.secrets["HUGGINGFACEHUB_API_TOKEN"]  # Huggingface API key
+pc = Pinecone(api_key=st.secrets["PINECONE_API_KEY"]  # Database API key
+index = pc.Index(st.secrets["Index_Name"])  # Database index name
 
 # Initialize embedding model (LLM will be saved to cache_dir if assigned)
 embedding_model = "all-mpnet-base-v2"  # See link https://www.sbert.net/docs/pretrained_models.html