Load secrets as environmental variables for HF support

app.py

@@ -5,8 +5,14 @@ import streamlit as st
 from chatbot.data import download_test_data
 from chatbot.data import load_data
 
-# add OpenAI API key to environemntal variables
-os.environ["OPENAI_API_KEY"] = st.secrets["OPENAI_API_KEY"]
+# add all secrets into environmental variables
+try:
+    for key, value in st.secrets.items():
+        os.environ[key] = value
+except FileNotFoundError as e:
+    print(e)
+    print("./streamlit/secrets.toml not found. Assuming secrets are already available"
+          "as environmental variables...")
 
 # Initialize message history
 st.header("Chat with André's research 💬 📚")
@@ -14,7 +20,6 @@ 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!"}]
 
-
 def main():
     # setup logger sidebar
     # st.sidebar.text("Standard output log:")

chatbot/data.py

@@ -28,12 +28,12 @@ def load_data():
     with st.spinner(text="Setting up Azure OpenAI..."):
         llm = AzureOpenAI(
             model="gpt-3.5-turbo",
-            engine=st.secrets["ENGINE"],
+            engine=os.environ["ENGINE"],
             temperature=0.5,
             api_key=os.environ["OPENAI_API_KEY"],
-            api_base=st.secrets["OPENAI_API_BASE"],
+            api_base=os.environ["OPENAI_API_BASE"],
             api_type="azure",
-            api_version=st.secrets["OPENAI_API_VERSION"],
+            api_version=os.environ["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;"
@@ -44,11 +44,11 @@ def load_data():
         # 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=st.secrets["ENGINE_EMBEDDING"],
+            deployment_name=os.environ["ENGINE_EMBEDDING"],
             api_key=os.environ["OPENAI_API_KEY"],
-            api_base=st.secrets["OPENAI_API_BASE"],
+            api_base=os.environ["OPENAI_API_BASE"],
             api_type="azure",
-            api_version=st.secrets["OPENAI_API_VERSION"],
+            api_version=os.environ["OPENAI_API_VERSION"],
             embed_batch_size=10,  # set to low value to reduce rate limit -> may degrade response runtime
         )