Update app.py

app.py

@@ -1,4 +1,3 @@
-
 import streamlit as st
 from llama_index.core import StorageContext, load_index_from_storage, VectorStoreIndex, SimpleDirectoryReader, ChatPromptTemplate
 from llama_index.llms.huggingface import HuggingFaceInferenceAPI
@@ -59,9 +58,7 @@ def handle_query(query):
              If a question does not match the provided context or is outside the scope of the document, kindly advise the user to ask questions within the context
              of the document
               
-             
             
-
             Context:
             {context_str}
             Question:
@@ -85,14 +82,14 @@ def handle_query(query):
 st.set_page_config(page_title="PDF Information and Inference", page_icon=":book:", layout="wide")
 
 st.title("📚 PDF Information and Inference")
-st.markdown("Welcome to the Retrieval-Augmented Generation tool! Upload a PDF and ask questions about its content.")
+st.markdown("Welcome to the Retrieval-Augmented Generation tool! You can either upload a PDF or chat with the language model directly.")
 
 # Sidebar for PDF upload and processing
 with st.sidebar:
     st.title("Menu")
     st.subheader("Upload and Process PDF")
     uploaded_file = st.file_uploader("Upload your PDF file here:", type="pdf")
-    if st.button("Submit & Process"):
+    if st.button("Submit & Process PDF"):
         if uploaded_file is not None:
             with st.spinner("Processing..."):
                 filepath = os.path.join(DATA_DIR, "saved_pdf.pdf")
@@ -106,10 +103,21 @@ with st.sidebar:
             st.sidebar.error("Please upload a PDF file first.")
 
 # Main section for user interaction
-st.header("Chat with the PDF")
-user_prompt = st.text_input("Ask me anything about the content of the PDF:")
+st.header("Chat with the PDF or the LLM")
+
+if uploaded_file:
+    st.write("You can now ask questions about the uploaded PDF.")
+else:
+    st.write("No PDF uploaded. You can still chat with the LLM.")
+
+user_prompt = st.text_input("Ask me anything:")
 
 if user_prompt:
     with st.spinner("Fetching answer..."):
-        response = handle_query(user_prompt)
-        st.write(response)
+        if uploaded_file:
+            # Handle query with PDF context
+            response = handle_query(user_prompt)
+        else:
+            # Handle query without PDF, just using the LLM
+            response = Settings.llm.generate([user_prompt])
+        st.write(response[0]["generated_text"] if isinstance(response, list) else response)