Update app.py

app.py

@@ -91,7 +91,7 @@ def load_sample_pdf():
     for file in sample_filenames:
         loader = PyPDFLoader(file)
         documents.extend(loader.load())
-        print(f"{file} is processed!")
+        # print(f"{file} is processed!")
 
     # Split the documents into chunks
     text_splitter = RecursiveCharacterTextSplitter(chunk_size=1024, chunk_overlap=64)
@@ -133,7 +133,7 @@ def generate_response(query, history, model, temperature, max_tokens, top_p, see
 
     response = rag_chain.invoke(query)
    
-    return response
+    return response, relevant_info
 
 additional_inputs = [
     gr.Dropdown(choices=["llama-3.3-70b-versatile", "llama-3.1-8b-instant", "llama3-70b-8192", "llama3-8b-8192", "mixtral-8x7b-32768", "gemma2-9b-it"], value="gemma2-9b-it", label="Model"),
@@ -143,6 +143,10 @@ additional_inputs = [
     gr.Number(precision=0, value=0, label="Seed", info="A starting point to initiate generation, use 0 for random")
 ]
 
+additional_outputs = [
+    gr.Textbox(label="Retrieved Information", interactive=False, lines=10)
+]
+
 # Create the Gradio interface
 with gr.Blocks(theme=gr.themes.Default()) as demo:
     with gr.Tab("Indexing"):
@@ -164,7 +168,7 @@ with gr.Blocks(theme=gr.themes.Default()) as demo:
                     chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"),
                     examples=examples_questions,
                     additional_inputs=additional_inputs,
-                    # additional_outputs=[relevant_info],
+                    additional_outputs=additional_outputs,
                     cache_examples=False,
                 )
             # with gr.Column():