astro21 commited on
Commit
de6eaa0
1 Parent(s): 8dfca02

Update app.py

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Files changed (1) hide show
  1. app.py +16 -33
app.py CHANGED
@@ -1,18 +1,18 @@
1
  import gradio as gr
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  from transformers import pipeline
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- import os
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  import pandas as pd
 
5
 
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  # Load the text summarization pipeline
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  summarizer = pipeline("summarization", model="astro21/bart-cls_n")
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  chunk_counter = 0
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-
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  def summarize_text(input_text):
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  global chunk_counter
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- chunk_counter = 0
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  max_chunk_size = 1024
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  chunks = [input_text[i:i + max_chunk_size] for i in range(0, len(input_text), max_chunk_size)]
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@@ -25,7 +25,6 @@ def summarize_text(input_text):
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  summarized_chunk = summarizer(chunk, max_length=128, min_length=64, do_sample=False)[0]['summary_text']
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  summarized_chunks.append(f"Chunk {chunk_counter}:\n{summarized_chunk}")
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  summarized_chunks_only.append(summarized_chunk)
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-
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  chunk_lengths.append(len(chunk))
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  summarized_text = "\n".join(summarized_chunks)
@@ -35,35 +34,19 @@ def summarize_text(input_text):
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  with open("summarized.txt", "w") as output_file:
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  output_file.write(summarized_text_only)
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- chunk_df = pd.DataFrame({'Chunk Number': range(1, chunk_counter + 1), 'Chunk Length': chunk_lengths})
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-
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- return summarized_text
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-
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-
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- # def read_file(file):
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- # print(file[0].name)
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- # with open(file[0].name, 'r') as file_:
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- # content = file_.read()
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- # return content
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-
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-
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- # def summarize_text_file(file):
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- # if file is not None:
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- # content = read_file(file)
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- # return summarize_text(content)
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-
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-
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- # input_type = gr.inputs.Textbox(label = "textbox" )
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-
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- # Name the outputs using the label parameter and provide a download option
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- demo = gr.Interface(fn=summarize_text, inputs=[gr.Textbox(label="Enter Text",placeholder="Ask me anything.",lines=3)],
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- outputs=[gr.Textbox(label="Summarized Text")],
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- title = "Text Summarization",
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- description = "Summarize text using BART",
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- theme = "huggingface",
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- allow_flagging="never",
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- live=True)
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- demo.launch(share=True,debug=True)
 
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1
  import gradio as gr
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  from transformers import pipeline
 
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  import pandas as pd
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+ import time # Import time to measure duration
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  # Load the text summarization pipeline
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  summarizer = pipeline("summarization", model="astro21/bart-cls_n")
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  chunk_counter = 0
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  def summarize_text(input_text):
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  global chunk_counter
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+ start_time = time.time() # Start timer
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+ chunk_counter = 0
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  max_chunk_size = 1024
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  chunks = [input_text[i:i + max_chunk_size] for i in range(0, len(input_text), max_chunk_size)]
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  summarized_chunk = summarizer(chunk, max_length=128, min_length=64, do_sample=False)[0]['summary_text']
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  summarized_chunks.append(f"Chunk {chunk_counter}:\n{summarized_chunk}")
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  summarized_chunks_only.append(summarized_chunk)
 
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  chunk_lengths.append(len(chunk))
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  summarized_text = "\n".join(summarized_chunks)
 
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  with open("summarized.txt", "w") as output_file:
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  output_file.write(summarized_text_only)
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+ end_time = time.time() # End timer
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+ duration = end_time - start_time
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ result = f"Summarized in {duration:.2f} seconds:\n{summarized_text}"
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+ return result
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+ # Define the Gradio interface
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+ demo = gr.Interface(fn=summarize_text,
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+ inputs=gr.Textbox(label="Enter Text", placeholder="Paste your text here.", lines=10),
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+ outputs=gr.Textbox(label="Summarized Text"),
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+ title="Text Summarization",
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+ description="Paste text and click 'Summarize' to see a summarized version using BART.",
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+ theme="huggingface",
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+ allow_flagging="never")
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+ demo.launch(share=True, debug=True)