Update app.py

app.py

@@ -13,8 +13,10 @@ import tempfile
 
 # Streamlit specific setup
 st.title("Uber Quarterly Report QA")
-user_llama_key = st.text_input("Enter your LLAMA Cloud API key:")
-user_groq_key = st.text_input("Enter your GROQ API key:")
+
+# Access API keys from secrets
+llama_cloud_api_key = st.secrets["llama_cloud_api_key"]
+groq_api_key = st.secrets["groq_api_key"]
 
 # Function to load or parse data from uploaded PDF file
 def load_or_parse_data(uploaded_file):
@@ -25,7 +27,7 @@ def load_or_parse_data(uploaded_file):
     parsing_instruction = """The provided document is a quarterly report filed by Uber Technologies,
     Inc. with the Securities and Exchange Commission (SEC)...
     """
-    parser = LlamaParse(api_key=user_llama_key, result_type="markdown", parsing_instruction=parsing_instruction, max_timeout=5000)
+    parser = LlamaParse(api_key=llama_cloud_api_key, result_type="markdown", parsing_instruction=parsing_instruction, max_timeout=5000)
     llama_parse_documents = parser.load_data(temp_file_path)
     os.remove(temp_file_path)
     return llama_parse_documents
@@ -64,7 +66,7 @@ if uploaded_file is not None:
     chat_model = ChatGroq(
         temperature=0,
         model_name="mixtral-8x7b-32768",
-        api_key=user_groq_key
+        api_key=groq_api_key
     )
 
     # Convert retrieved documents into QA format