Moved keys and hidden variables into streamlit secrets

.gitignore

@@ -2,3 +2,5 @@ venv/
 data/
 .DS_Store
 config.json
+.streamlit/
+secrets.toml

app.py

@@ -1,25 +1,23 @@
-import json
+import os
 
 import streamlit as st
 
 from chatbot.utils import download_test_data
 from chatbot.utils import load_data
 
+# add OpenAI API key to environemntal variables
+os.environ["OPENAI_API_KEY"] = st.secrets["OPENAI_API_KEY"]
+
 # Initialize message history
 st.header("Chat with André's research 💬 📚")
 
 if "messages" not in st.session_state.keys():  # Initialize the chat message history
     st.session_state.messages = [{"role": "assistant", "content": "Ask me a question about André's research!"}]
 
-# Load config values
-with open(r"config.json") as config_file:
-    config_details = json.load(config_file)
-
-
 def main():
     # setup dataset
     download_test_data()
-    index = load_data(config_details)
+    index = load_data()
     chat_engine = index.as_chat_engine(chat_mode="condense_question", verbose=True)
 
     if prompt := st.chat_input("Your question"):  # Prompt for user input and save to chat history

chatbot/utils.py

@@ -14,22 +14,21 @@ from llama_index.llms import AzureOpenAI
 def download_test_data():
     # url = f"https://drive.google.com/drive/folders/uc?export=download&confirm=pbef&id={file_id}"
     url = "https://drive.google.com/drive/folders/1uDSAWtLvp1YPzfXUsK_v6DeWta16pq6y"
-    with st.spinner(text="Downloading test data. Might take a few seconds."):
+    with st.spinner(text="Downloading test data. This might take a minute."):
         download_folder(url=url, quiet=False, use_cookies=False, output="./data/")
 
-
 @st.cache_resource(show_spinner=False)
-def load_data(config_details):
+def load_data():
     with st.spinner(text="Loading and indexing the provided dataset – hang tight! This may take a few seconds."):
         documents = SimpleDirectoryReader(input_dir="./data", recursive=True).load_data()
         llm = AzureOpenAI(
             model="gpt-3.5-turbo",
-            engine=config_details["ENGINE"],
+            engine=st.secrets["ENGINE"],
             temperature=0.5,
-            api_key=os.getenv("OPENAI_API_KEY"),
-            api_base=config_details["OPENAI_API_BASE"],
+            api_key=os.environ["OPENAI_API_KEY"],
+            api_base=st.secrets["OPENAI_API_BASE"],
             api_type="azure",
-            api_version=config_details["OPENAI_API_VERSION"],
+            api_version=st.secrets["OPENAI_API_VERSION"],
             system_prompt="You are an expert on André's research and your job is to answer"
             "technical questions. Assume that all questions are related to"
             "André's research. Keep your answers technical and based on facts"
@@ -38,11 +37,11 @@ def load_data(config_details):
         # You need to deploy your own embedding model as well as your own chat completion model
         embed_model = OpenAIEmbedding(
             model="text-embedding-ada-002",
-            deployment_name=config_details["ENGINE_EMBEDDING"],
-            api_key=os.getenv("OPENAI_API_KEY"),
-            api_base=config_details["OPENAI_API_BASE"],
+            deployment_name=st.secrets["ENGINE_EMBEDDING"],
+            api_key=os.environ["OPENAI_API_KEY"],
+            api_base=st.secrets["OPENAI_API_BASE"],
             api_type="azure",
-            api_version=config_details["OPENAI_API_VERSION"],
+            api_version=st.secrets["OPENAI_API_VERSION"],
         )
         service_context = ServiceContext.from_defaults(llm=llm, embed_model=embed_model)
         set_global_service_context(service_context)