Add application file

app.py

@@ -1,10 +1,6 @@
-from __future__ import annotations
-from typing import Iterable
 import gradio as gr
-from gradio.themes.base import Base
-from gradio.themes.utils import colors, fonts, sizes
+from gradio import themes
 from transformers import AutoModelForCausalLM, AutoTokenizer
-from PIL import Image
 import numpy as np
 
 # Load the model and tokenizer
@@ -16,46 +12,35 @@ model = AutoModelForCausalLM.from_pretrained(
 tokenizer = AutoTokenizer.from_pretrained(model_id, revision=revision)
 
 def analyze_image_direct(image, question):
-    # This is a placeholder; modify based on the actual capabilities of your model.
-    # Here we assume that the model has methods `encode_image` and `answer_question` which might not exist.
-    # You need to replace them with the actual methods your model uses to process images and generate answers.
-    
     # Convert PIL Image to the format expected by the model
-    # Example transformation (actual code will depend on model's requirements):
-    enc_image = np.array(image)  # Placeholder transformation; adjust as needed
+    # This is a placeholder transformation; adjust as needed
+    enc_image = np.array(image)
     
-    # Hypothetical method calls (replace with actual methods):
-    inputs = tokenizer.encode(question, return_tensors='pt')
-    outputs = model.generate(inputs, max_length=50)
+    # Example of processing text input with the model
+    inputs = tokenizer(question, return_tensors='pt')
+    outputs = model.generate(**inputs, max_length=50)
     answer = tokenizer.decode(outputs[0], skip_special_tokens=True)
     
     return answer
 
 # Define a custom theme with purple color scheme
-class PurpleTheme(Base):
-    def __init__(self):
-        super().__init__()
-        self.primary_hue = colors.purple
-        self.secondary_hue = colors.purple
-        self.neutral_hue = colors.gray
-        self.text_size = sizes.text_lg
-        self.text_color = colors.white
-        self.background_color = colors.purple_900
-        self.primary_text_color = colors.white
-        self.secondary_background_color = colors.purple_700
-        self.secondary_text_color = colors.white
-        self.font = fonts.GoogleFont("Arial")
-
-# Create a custom theme instance
-purple_theme = PurpleTheme()
+class PurpleTheme(themes.Theme):
+    base = "light"
+    font = "Arial"
+    colors = {
+        "primary": "#9b59b6",
+        "text": "#FFFFFF",
+        "background": "#5B2C6F",
+        "secondary_background": "#7D3C98",
+    }
 
 # Create Gradio interface with the custom theme
 iface = gr.Interface(fn=analyze_image_direct,
-                     theme=purple_theme,
+                     theme=PurpleTheme(),
                      inputs=[gr.Image(type="pil"), gr.Textbox(lines=2, placeholder="Enter your question here...")],
                      outputs='text',
                      title="Direct Image Question Answering",
                      description="Upload an image and ask a question about it directly using the model.")
 
 # Launch the interface
-iface.launch()
+iface.launch()