| import gradio as gr |
| import requests |
|
|
| BASE_URL = "https://citegraph-1099254244451.us-east1.run.app/" |
| HEADERS = {"Content-Type": "application/json"} |
|
|
|
|
| def load_documents(file_path): |
| print(file_path) |
| url = f"{BASE_URL}/api/predict" |
| if file_path is not None: |
| with open(file_path.name, "rb") as f: |
| file = {"file": f} |
| response = requests.post(url, files=file) |
| f.close() |
|
|
| output = response.json() |
| print(output) |
| return f"## <div align='center'>Output: </div>\n# <div align='center'>{output['predicted_label']}</div>" |
|
|
|
|
| def createUI(): |
| css = """ |
| h1 { |
| text-align: center; |
| display:block; |
| } |
| """ |
| with gr.Blocks(css=css) as demo: |
| with gr.Row(): |
| with gr.Column(scale=1): |
| |
| |
| |
| upload_btn = gr.File(label="Upload a PDF", file_types=[".pdf"]) |
|
|
| with gr.Row(): |
| class_label = gr.Markdown("## Output: ") |
|
|
| upload_btn.upload( |
| fn=load_documents, |
| inputs=[upload_btn], |
| outputs=[class_label], |
| ) |
| return demo |
|
|
|
|
| if __name__ == "__main__": |
| demo = createUI() |
| demo.launch(pwa=True, share=False) |
|
|
