#import os # temp_dir = './temp/' # os.environ["CUDA_VISIBLE_DEVICES"] = "0" # os.environ['TMPDIR'] = temp_dir # import shutil import gradio as gr from summagery_pipline import Summagery # if os.path.exists(temp_dir): # try: # shutil.rmtree(temp_dir) # print(f"The directory at {temp_dir} has been removed successfully along with its contents.") # except OSError as e: # print(f"Error: {temp_dir} - {e}") # os.makedirs(temp_dir, exist_ok=True) def generate(text, batch_size, model_type, abstractness): model = Summagery(model_type,batch_size=int(batch_size),abstractness=abstractness) images=model.ignite(text) return images with gr.Blocks(theme=gr.themes.Soft(),) as demo: gr.Markdown( """

Welcome to Summagery: Document Summarization through Images

Summarize long and short documents on any topic as images

1. Document: Enter the text of the document you want to summarize. It could be just a single word, a sentence, or an entire book.

2. Batch Size: Adjust the batch size for processing very long documents (e.g., 500 pages)

3. T5_Model_Checkpoint: Choose the model checkpoint (e.g., "t5-large", "t5-base", "t5-small"). Smaller models require less memory.

4. Abstractness: Slide to select the level of abstractness of your document, vary this attribute to explore different images.

Source Code: Github

""") inputs = [ gr.Textbox(label="Document", lines=10,interactive=True), gr.Number(label="Batch Size", value=5), gr.Dropdown(label="T5_Model_Checkpoint", choices=["t5-large", "t5-base", "t5-small"], value='t5-large'), gr.Slider(label="Abstractness", minimum=0, maximum=1, value=.2) ] outputs = gr.Gallery( label="Generated images", show_label=False, elem_id="gallery" , columns=[2], rows=[2], object_fit="contain", height="auto") clear = gr.ClearButton([inputs[0]]) greet_btn = gr.Button("Submit") greet_btn.click(fn=generate, inputs=inputs, outputs=outputs, api_name="Summagery") demo.launch()