upload all the files

app.py

@@ -1,22 +1,25 @@
 import gradio as gr
-from transformers import AutoModelForCausalLM, AutoProcessor
-from PIL import Image
+from transformers import AutoModelForCausalLM, AutoProcessor, AutoConfig
 import torch
+from PIL import Image
+
+# Custom configuration class
+class Florence2Config(AutoConfig):
+    def to_dict(self):
+        config_dict = super().to_dict()
+        return config_dict
 
 # Load model and processor with trust_remote_code=True
-try:
-    model = AutoModelForCausalLM.from_pretrained(
-        "mynkchaudhry/Florence-2-FT-DocVQA",
-        force_download=True,
-        trust_remote_code=True
-    )
-    processor = AutoProcessor.from_pretrained(
-        "mynkchaudhry/Florence-2-FT-DocVQA",
-        force_download=True,
-        trust_remote_code=True
-    )
-except Exception as e:
-    raise RuntimeError(f"Error loading model or processor: {e}")
+model = AutoModelForCausalLM.from_pretrained(
+    "mynkchaudhry/Florence-2-FT-DocVQA",
+    force_download=True,
+    trust_remote_code=True
+)
+processor = AutoProcessor.from_pretrained(
+    "mynkchaudhry/Florence-2-FT-DocVQA",
+    force_download=True,
+    trust_remote_code=True
+)
 
 def generate_response(image, question):
     try:
@@ -42,11 +45,11 @@ def generate_response(image, question):
     except Exception as e:
         return f"Error processing image: {e}"
 
-# Example images for demonstration (ensure paths are correct and files are accessible)
+# Example images for demonstration (update paths as needed)
 examples = [
-    [Image.open("demo.png"), "what is the address in the page?"],
-    [Image.open("demo2.jpg"), "what is the date in the page?"],
-    [Image.open("demo.png"), "what is the name in the page?"]
+    ["demo.png", "what is the address in the page?"],
+    ["demo2.jpg", "what is the date in the page?"],
+    ["demo.png", "what is the name in the page?"]
 ]
 
 # Gradio interface