Create app.py

app.py

@@ -0,0 +1,84 @@
+import gradio as gr
+import requests
+import os
+from huggingface_hub import hf_hub_download
+from handwriting_api import InputData
+from typing import List
+
+# Download model from Hugging Face Hub
+def download_model():
+    REPO_ID = os.getenv("HF_REPO_ID", "your_username/your_model")
+    FILENAMES = [
+        "checkpoints/model-17900.data-00000-of-00001",
+        "checkpoints/model-17900.index",
+        "checkpoints/model-17900.meta"
+    ]
+    
+    os.makedirs("checkpoints", exist_ok=True)
+    
+    for filename in FILENAMES:
+        hf_hub_download(
+            repo_id=REPO_ID,
+            filename=filename,
+            local_dir=".",
+            token=os.getenv("HF_TOKEN")
+        )
+
+# Download model on startup        
+try:
+    download_model()
+except Exception as e:
+    raise RuntimeError(f"Model download failed: {str(e)}") from e
+
+# Hugging Face Spaces requires app to run on port 7860
+GRADIO_PORT = int(os.getenv("GRADIO_SERVER_PORT", "7860"))
+def generate_handwriting_interface(text: str, style: int) -> str:
+    data = InputData(
+        text=text,
+        style=style,
+        bias=0.75,
+        stroke_colors=["#000000"],
+        stroke_widths=[2]
+    )
+    
+    response = requests.post(
+        "http://localhost:8000/synthesize",
+        json=data.dict()
+    )
+    
+    if response.status_code == 200:
+        return open("img/output.svg").read()
+    else:
+        return f"Error: {response.json()['detail']}"
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Handwriting Synthesis")
+    with gr.Row():
+        text_input = gr.Textbox(label="Input Text", lines=3, placeholder="Enter text to convert to handwriting...")
+        style_select = gr.Slider(minimum=0, maximum=12, step=1, label="Style", value=0)
+    
+    output_svg = gr.HTML(label="Generated Handwriting")
+    download_button = gr.Button("Download SVG")
+    
+    inputs = [text_input, style_select]
+    outputs = [output_svg]
+    
+    generate_button = gr.Button("Generate")
+    generate_button.click(
+        fn=generate_handwriting_interface,
+        inputs=inputs,
+        outputs=outputs
+    )
+    
+    download_button.click(
+        fn=lambda svg: svg,
+        inputs=output_svg,
+        outputs=gr.File(label="Download SVG")
+    )
+
+demo.launch(
+    server_name="0.0.0.0",
+    server_port=GRADIO_PORT,
+    share=False,
+    show_error=True
+)