hideosnes commited on
Commit
d3959f2
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1 Parent(s): 2224978

Update app.py

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no more prompt in the summary

Files changed (1) hide show
  1. app.py +11 -5
app.py CHANGED
@@ -63,9 +63,9 @@ def summarize(file, text, style, length):
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  # System prompt based on language and style
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  prompt_map = {
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  "en": {
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- "Precise": "In English, distill the following text into a concise summary, utilizing formal and academic language to convey the essential information:",
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- "Sloppy": "In English, provide a brief and informal summary of the following text, using straightforward language to facilitate easy comprehension:",
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- "Keywords": "In English, condense the following text into a list of keywords, highlighting key points and main ideas in a clear and objective manner:",
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  }#, <-- don't forget the comma!!!!!
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  #"foo": { "precise": "another language or prompt map could go here"}
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  }
@@ -96,6 +96,12 @@ def summarize(file, text, style, length):
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  no_repeat_ngram_size=3
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  )
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  summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
 
 
 
 
 
 
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  # These lines calculate and store the word count of the original text,
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  # the word count of the summary, and the percentage reduction in length after summarization.
@@ -131,7 +137,7 @@ with gr.Blocks() as demo:
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  with gr.Row(): # for inline horizontal layout
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  style = gr.Dropdown(["Precise", "Sloppy", "Keywords"], label="Style")
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- length = gr.Radio(["Short", "Middle", "Long"], label="Length")
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  token_info = gr.Text(label="Max. Tokens:", value="1024 tokens ~ 750–800 words", interactive=False)
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  btn = gr.Button("Transform")
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@@ -149,4 +155,4 @@ with gr.Blocks() as demo:
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  outputs=[summary, keywords, original_len, summary_len, reduction, plot]
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  )
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- demo.launch()
 
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  # System prompt based on language and style
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  prompt_map = {
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  "en": {
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+ "Precise": "Summarize concisely in a dry, scientific and academic style:",
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+ "Sloppy": "Summarize comprehensively for a child:",
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+ "Keywords": "Write only a list of important keywords of main ideas separated by a comma:",
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  }#, <-- don't forget the comma!!!!!
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  #"foo": { "precise": "another language or prompt map could go here"}
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  }
 
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  no_repeat_ngram_size=3
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  )
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  summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
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+ # removing the prompt text from the summary
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+ prompt_text = prompt_map.get(lang_code, prompt_map["en"])[style]
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+ if summary.startswith(prompt_text):
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+ summary = summary[len(prompt_text):].strip()
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+ if text_input in summary:
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+ summary = summary.replace(text_input, "").strip()
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  # These lines calculate and store the word count of the original text,
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  # the word count of the summary, and the percentage reduction in length after summarization.
 
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  with gr.Row(): # for inline horizontal layout
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  style = gr.Dropdown(["Precise", "Sloppy", "Keywords"], label="Style")
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+ length = gr.Dropdown(["Short", "Middle", "Long"], label="Length")
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  token_info = gr.Text(label="Max. Tokens:", value="1024 tokens ~ 750–800 words", interactive=False)
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  btn = gr.Button("Transform")
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  outputs=[summary, keywords, original_len, summary_len, reduction, plot]
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  )
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+ demo.launch(share=True)