restructured

app.py

@@ -4,55 +4,55 @@ from streamlit_pdf_viewer import pdf_viewer
 
 st.set_page_config(layout="wide")
 
-def main():
-    with st.sidebar:
-        st.title('Document Summarization and QA System')
-        # st.markdown('''
-        # ## About this application
-        # Upload a pdf to ask questions about it. This retrieval-augmented generation (RAG) workflow uses:
-        # - [Streamlit](https://streamlit.io/)
-        # - [LlamaIndex](https://docs.llamaindex.ai/en/stable/)
-        # - [OpenAI](https://platform.openai.com/docs/models)
-        # ''')
-
-        # st.write('Made by ***Nate Mahynski***')
-        # st.write('nathan.mahynski@nist.gov')
-
-        # Select Provider
-        provider = st.selectbox(
-            label="Select LLM Provider",
-            options=['openai', 'huggingface'],
-            index=0
-        )
-
-        # Select LLM
-        if provider == 'openai':
-            llm_list = ['gpt-3.5-turbo', 'gpt-4', 'gpt-4-turbo', 'gpt-4o']
-        else:
-            llm_list = []
-
-        llm = st.selectbox(
-            label="Select LLM Model",
-            options=llm_list,
-            index=0
-        )
-
-        # Enter Token
-        token = st.text_input(
-            "Enter your token",
-            value=None
-        )
-
-        uploaded_file = st.file_uploader(
-            "Choose a PDF file to upload", 
-            type=['pdf'], 
-            accept_multiple_files=False
-        )
-
-        if uploaded_file is not None:
-            # Parse the file
-            pass
-
+with st.sidebar:
+    st.title('Document Summarization and QA System')
+    # st.markdown('''
+    # ## About this application
+    # Upload a pdf to ask questions about it. This retrieval-augmented generation (RAG) workflow uses:
+    # - [Streamlit](https://streamlit.io/)
+    # - [LlamaIndex](https://docs.llamaindex.ai/en/stable/)
+    # - [OpenAI](https://platform.openai.com/docs/models)
+    # ''')
+
+    # st.write('Made by ***Nate Mahynski***')
+    # st.write('nathan.mahynski@nist.gov')
+
+    # Select Provider
+    provider = st.selectbox(
+        label="Select LLM Provider",
+        options=['openai', 'huggingface'],
+        index=0
+    )
+
+    # Select LLM
+    if provider == 'openai':
+        llm_list = ['gpt-3.5-turbo', 'gpt-4', 'gpt-4-turbo', 'gpt-4o']
+    else:
+        llm_list = []
+
+    llm = st.selectbox(
+        label="Select LLM Model",
+        options=llm_list,
+        index=0
+    )
+
+    # Enter Token
+    token = st.text_input(
+        "Enter your token",
+        value=None
+    )
+
+    uploaded_file = st.file_uploader(
+        "Choose a PDF file to upload", 
+        type=['pdf'], 
+        accept_multiple_files=False
+    )
+
+    if uploaded_file is not None:
+        # Parse the file
+        pass
+
+def main()
     col1, col2 = st.columns(2)
 
     with col2: