Update app.py

app.py

@@ -12,7 +12,8 @@ load_dotenv()
 
 # Initialize the LLM and parser
 llm = HuggingFaceInferenceAPI(
-    model_name="meta-llama/Meta-Llama-3-8B-Instruct",
+    # model_name="meta-llama/Meta-Llama-3-8B-Instruct",
+    model_name="mistralai/Mixtral-8x7B-Instruct-v0.1",
     token=os.getenv("TOKEN")
 )
 
@@ -45,7 +46,7 @@ def respond(message, history):
         # for chr in bot_message:
         #     output += chr
         #     yield output
-        print(f"{datetime.now()}::message=>{str(bot_message)}")
+        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'":
@@ -57,7 +58,7 @@ with gr.Blocks() as demo:
     with gr.Row():
         with gr.Column(scale=1):
             file_input = gr.File(file_count="single", type='filepath')
-            with gr.Column():
+            with gr.Row():
                 clear = gr.ClearButton()
                 btn = gr.Button("Submit", variant='primary')
             output = gr.Text(label='Vector Index')
@@ -65,7 +66,7 @@ with gr.Blocks() as demo:
              gr.ChatInterface(fn=respond,
                               chatbot=gr.Chatbot(height=500),
                               textbox=gr.Textbox(placeholder="Ask me a yes or no question", container=False, scale=7),
-                              examples=["summarize the document"]
+                              # examples=["summarize the document"]
                              )
 
     # Action on button click to process file and load into index