Create app.py

app.py

@@ -0,0 +1,41 @@
+import torch
+from safetensors.torch import save_file
+import gradio as gr
+import os
+
+def convert_embedding(sd15_embedding):
+    # Temporary file paths
+    input_path = "temp_input.pt"
+    output_path = "temp_output.safetensors"
+    
+    # Save uploaded file to disk to be processed
+    with open(input_path, "wb") as f:
+        f.write(sd15_embedding.read())
+
+    # Your existing conversion logic
+    sd15_embedding = torch.load(input_path, map_location=torch.device('cpu'))
+    sd15_tensor = sd15_embedding['string_to_param']['*']
+    num_vectors = sd15_tensor.shape[0]
+    clip_g_shape = (num_vectors, 1280)
+    clip_l_shape = (num_vectors, 768)
+    clip_g = torch.zeros(clip_g_shape, dtype=torch.float16)
+    clip_l = torch.zeros(clip_l_shape, dtype=torch.float16)
+    clip_l[:sd15_tensor.shape[0], :sd15_tensor.shape[1]] = sd15_tensor.to(dtype=torch.float16)
+    save_file({"clip_g": clip_g, "clip_l": clip_l}, output_path)
+
+    # Remove the temporary input file
+    os.remove(input_path)
+
+    # Return the path to the converted file for download
+    return output_path
+
+iface = gr.Interface(
+    fn=convert_embedding,
+    inputs=gr.inputs.File(label="Upload SD1.5 Embedding"),
+    outputs=gr.outputs.File(label="Download Converted SDXL Embedding"),
+    title="SD1.5 to SDXL Embedding Converter",
+    description="Upload an SD1.5 embedding file to convert it to SDXL format."
+)
+
+if __name__ == "__main__":
+    iface.launch()