changes to app.py

app.py

@@ -63,7 +63,7 @@ def process_documents(files, save_location=None):
         chat_state.document_retrieval.init_retriever(vectorstore)
         chat_state.conversation = chat_state.document_retrieval.get_qa_retrieval_chain()
         chat_state.input_disabled = False
-        return "Documents processed successfully. You can now ask questions."
+        return "Complete! You can now ask questions."
     except Exception as e:
         return f"An error occurred while processing: {str(e)}"
 
@@ -90,31 +90,33 @@ caution_text = """⚠️ Note: depending on the size of your document, this coul
 
 with gr.Blocks() as demo:
     #gr.Markdown("# SambaNova Analyst Assistant") # title
-    gr.Markdown("# 🟠 SambaNova Analyst Assistant", 
+    gr.Markdown("# Enterprise Knowledge Retriever", 
             elem_id="title")
     
-    gr.Markdown("Powered by SambaNova Cloud. Get your API key [here](https://cloud.sambanova.ai/apis).")
+    gr.Markdown("Powered by LLama3.1-8B-Instruct on SambaNova Cloud. Get your API key [here](https://cloud.sambanova.ai/apis).")
 
     api_key = gr.Textbox(label="API Key", type="password", placeholder="(Optional) Enter your API key here for more availability")
 
     # Step 1: Add PDF file   
-    gr.Markdown("## 1️⃣ Pick a datasource")
-    docs = gr.File(label="Add PDF file", file_types=["pdf"], file_count="single")
+    gr.Markdown("## 1️⃣ Upload PDF")
+    docs = gr.File(label="Add PDF file (single)", file_types=["pdf"], file_count="single")
         
     # Step 2: Process PDF file
-    gr.Markdown(("## 2️⃣ Process your documents and create vector store"))
+    gr.Markdown(("## 2️⃣ Process document and create vector store"))
+    db_btn = gr.Radio(["ChromaDB"], label="Vector store type", value = "ChromaDB", type="index", info="Choose your vector store")
+    setup_output = gr.Textbox(label="Processing status", visible=True, value="None") 
     process_btn = gr.Button("🔄 Process")
     gr.Markdown(caution_text)
-    setup_output = gr.Textbox(label="Setup Output", visible=True)   
+      
 
     process_btn.click(process_documents, inputs=[docs], outputs=setup_output, concurrency_limit=10)
         #process_save_btn.click(process_documents, inputs=[file_upload, save_location], outputs=setup_output)
         #load_db_btn.click(load_existing_db, inputs=[db_path], outputs=setup_output)
     
     # Step 3: Chat with your data
-    gr.Markdown("## 3️⃣ Chat")
+    gr.Markdown("## 3️⃣ Chat with your document")
     chatbot = gr.Chatbot(label="Chatbot", show_label=True, show_share_button=False, show_copy_button=True, likeable=True)
-    msg = gr.Textbox(label="Ask questions about your data", placeholder="Enter your message...")
+    msg = gr.Textbox(label="Ask questions about your data", show_label=True, placeholder="Enter your message...")
     clear = gr.Button("Clear chat")
     #show_sources = gr.Checkbox(label="Show sources", value=True)
     sources_output = gr.Textbox(label="Sources", visible=False)