Update app.py

app.py

@@ -14,7 +14,8 @@ load_dotenv()
 llm = HuggingFaceInferenceAPI(
     # model_name="meta-llama/Meta-Llama-3-8B-Instruct",
     model_name="mistralai/Mixtral-8x7B-Instruct-v0.1",
-    token=os.getenv("TOKEN")
+    token=os.getenv("TOKEN"),
+    model_config={'protected_namespaces': ()}
 )
 
 parser = LlamaParse(api_key=os.getenv("LLAMA_INDEX_API"), result_type='markdown')
@@ -46,7 +47,7 @@ def respond(message, history):
         # for chr in bot_message:
         #     output += chr
         #     yield output
-        print(f"\n{datetime.now()}::message --> {str(bot_message)}\n")
+        print(f"\n{datetime.now()}:: {message} --> {str(bot_message)}\n")
         return str(bot_message)
     except Exception as e:
         if e == "'NoneType' object has no attribute 'as_query_engine'":
@@ -62,10 +63,10 @@ with gr.Blocks() as demo:
                 clear = gr.ClearButton()
                 btn = gr.Button("Submit", variant='primary')
             output = gr.Text(label='Vector Index')
-        with gr.Column(scale=2):
+        with gr.Column(scale=3):
              gr.ChatInterface(fn=respond,
                               chatbot=gr.Chatbot(height=500),
-                              textbox=gr.Textbox(placeholder="Ask me a yes or no question", container=False, scale=7),
+                              textbox=gr.Textbox(placeholder="Ask me questions on given document!", container=False, scale=7),
                               # examples=["summarize the document"]
                              )
 
@@ -76,4 +77,4 @@ with gr.Blocks() as demo:
 
 # Launch the demo with public link option
 if __name__ == "__main__":
-    demo.launch(share=True)
+    demo.launch()