updated the app.py

app.py

@@ -3,6 +3,7 @@ import requests
 from bs4 import BeautifulSoup
 import difflib
 from langchain.document_loaders import GutenbergLoader
+import os
 
 
 import langchain
@@ -117,14 +118,16 @@ def create_book_embeddings(book_content):
     
     
     vectordb = None
+    print("Creating book embeddings...")
     try:
-        vectordb = Chroma.load(persist_directory = Configuration.Persist_directory,
+        vectordb = Chroma.load(persist_directory = '.',
                                collection_name = 'book')
     except:
         vectordb = Chroma.from_documents(documents = texts,
                                          embedding = instructor_embeddings,
-                                         persist_directory = Configuration.Persist_directory,
+                                         persist_directory = '.',
                                          collection_name = 'book')
+    print("Book embeddings created.")
         
     vectordb.add_documents(documents=texts, embedding=instructor_embeddings)
     vectordb.persist()
@@ -192,6 +195,8 @@ def generate_answer_from_embeddings(query, book_embeddings):
 
 
 app = FastAPI()
+REPLICATE_API_TOKEN="r8_KWM7ZPHF27SufFBDWyTQdAHvU07aUHm2aUjQh"
+os.environ["REPLICATE_API_TOKEN"] = REPLICATE_API_TOKEN
 llm = Replicate(
     model=  "replicate/llama-2-70b-chat:2796ee9483c3fd7aa2e171d38f4ca12251a30609463dcfd4cd76703f22e96cdf",
     input={"temperature": 0.75, "max_length": 500, "top_p": 1},