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longevity.py

@@ -5,15 +5,14 @@ import sys
 import os
 import openai
 from ratelimit import limits, sleep_and_retry
-import streamlit
 
 # fixing bugs
-# 1. open ai key: https://stackoverflow.com/questions/76425556/tenacity-retryerror-retryerrorfuture-at-0x7f89bc35eb90-state-finished-raised 
+# 1. open ai key: https://stackoverflow.com/questions/76425556/tenacity-retryerror-retryerrorfuture-at-0x7f89bc35eb90-state-finished-raised
 # 2. rate limit error in lang_chain default version - install langchain==0.0.188. https://github.com/jerryjliu/llama_index/issues/924
-# 3. added true Config variable in langchain: https://github.com/pydantic/pydantic/issues/3320 
+# 3. added true Config variable in langchain: https://github.com/pydantic/pydantic/issues/3320
 
 
-os.environ["OPENAI_API_KEY"] = streamlit.secrets["openai_key"]
+os.environ["OPENAI_API_KEY"] = os.environ.get("openai_key")
 openai.api_key = os.environ["OPENAI_API_KEY"]
 
 # Define the rate limit for API calls (requests per second)
@@ -48,7 +47,7 @@ def data_ingestion_indexing(directory_path):
 
     #loads data from the specified directory path
     documents = SimpleDirectoryReader(directory_path).load_data()
-    
+
     #when first building the index
     index = GPTVectorStoreIndex.from_documents(
         documents, service_context=create_service_context()
@@ -66,10 +65,10 @@ def data_querying(input_text):
 
     #loads index from storage
     index = load_index_from_storage(storage_context, service_context=create_service_context())
-    
+
     #queries the index with the input text
     response = index.as_query_engine().query(input_text)
-    
+
     return response.response
 
 iface = gr.Interface(fn=data_querying,