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import gradio as gr |
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from PyPDF2 import PdfReader |
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from transformers import pipeline |
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from gtts import gTTS |
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import tempfile |
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import os |
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def extract_abstract_from_pdf(file): |
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reader = PdfReader(file.name) |
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first_page = reader.pages[0] |
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text = first_page.extract_text() |
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return text |
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def summarize_text(text, model_name='sshleifer/distilbart-cnn-12-6'): |
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summarizer = pipeline("summarization", model=model_name) |
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summary = summarizer(text, max_length=75, min_length=20, do_sample=False) |
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first_sentence = summary[0]['summary_text'].split('.')[0] + '.' |
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return first_sentence |
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def process_pdf_to_speech(file): |
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abstract = extract_abstract_from_pdf(file) |
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summary = summarize_text(abstract) |
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tts = gTTS(text=summary, lang='en') |
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with tempfile.NamedTemporaryFile(delete=False, suffix='.mp3') as fp: |
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tts.save(fp.name) |
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return fp.name |
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iface = gr.Interface( |
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fn=process_pdf_to_speech, |
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inputs=gr.File(label="Upload PDF"), |
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outputs=gr.Audio(label="Play Summary"), |
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title="PDF Abstract to Speech", |
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description="This app summarizes the abstract from a PDF and converts it to speech. Please upload a PDF with an abstract." |
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) |
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iface.launch() |
