Update app.py

app.py

@@ -2,17 +2,23 @@ import gradio as gr
 from transformers import VisionEncoderDecoderModel, AutoTokenizer
 from PIL import Image
 import io
+import torch
 
-# Load model
-model = LLaVAForVisionTextGeneration.from_pretrained("liuhaotian/LLaVA-1.5-7b")
-tokenizer = LLaVATokenizer.from_pretrained("liuhaotian/LLaVA-1.5-7b")
+# Load model and tokenizer
+model = VisionEncoderDecoderModel.from_pretrained("liuhaotian/LLaVA-1.5-7b")
+tokenizer = AutoTokenizer.from_pretrained("liuhaotian/LLaVA-1.5-7b")
 
 # Function to analyze the image
 def analyze_image(image_blob):
     image = Image.open(io.BytesIO(image_blob))
+    pixel_values = torch.tensor(image).unsqueeze(0)  # Add batch dimension
     inputs = tokenizer("Analyze the emotions in this image", return_tensors="pt")
-    outputs = model.generate(**inputs, images=image)
-    return tokenizer.decode(outputs[0])
+    
+    # Run the model
+    outputs = model.generate(**inputs, pixel_values=pixel_values)
+    result = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    
+    return result
 
 # Set up the Gradio interface
 iface = gr.Interface(fn=analyze_image, inputs="file", outputs="text")