Update app.py

app.py

@@ -1,6 +1,5 @@
-from transformers import MllamaForConditionalGeneration, AutoProcessor, AutoTokenizer, TextIteratorStreamer
+from transformers import MllamaForConditionalGeneration, AutoProcessor, TextIteratorStreamer
 from PIL import Image
-import os
 import requests
 import torch
 from threading import Thread
@@ -8,16 +7,15 @@ import gradio as gr
 from gradio import FileData
 import time
 import spaces
-from src.search import perform_search
 
 hf_token = os.environ.get("HF_KEY")
 
 ckpt = "meta-llama/Llama-3.2-11B-Vision-Instruct"
 
 model = MllamaForConditionalGeneration.from_pretrained(ckpt,
-    torch_dtype=torch.bfloat16).to("cuda")
-processor = AutoProcessor.from_pretrained(ckpt)
-tokenizer = AutoTokenizer.from_pretrained( "meta-llama/Llama-3.2-11B-Vision-Instruct", token=hf_token )
+    torch_dtype=torch.bfloat16,
+    token=hf_token).to("cuda")
+processor = AutoProcessor.from_pretrained(ckpt, token=hf_token)
 
 
 @spaces.GPU
@@ -80,9 +78,7 @@ def bot_streaming(message, history, max_new_tokens=250):
 demo = gr.ChatInterface(fn=bot_streaming, title="Multimodal Llama", examples=[
     [{"text": "Which era does this piece belong to? Give details about the era.", "files":["./examples/rococo.jpg"]},
     200],
-        [{"text": "How long does it take from invoice date to due date? Be short and concise.", "files":["./examples/invoice.png"]},
-    250],
-    [{"text": "Where to find this monument? Can you give me other recommendations around the area?", "files":["./examples/wat_arun.jpg"]}, 
+    [{"text": "Where do the droughts happen according to this diagram?", "files":["./examples/weather_events.png"]},
     250],
     ],
       textbox=gr.MultimodalTextbox(),