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Update app.py
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app.py
CHANGED
@@ -3,17 +3,14 @@
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# The code receives a PDF but doesnt' appear to process it.
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# I still need to add the gradio interface output to show the summarized text and play the sound file
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import gradio as gr
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def process_input(pdf_file):
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print("Received PDF File:", pdf_file.name)
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# Read the content of the uploaded PDF file
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pdf_content = pdf_file.read()
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# Save the received PDF content locally
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with open("received_pdf.pdf", "wb") as output_file:
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output_file.write(pdf_content)
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# Return the content of the processed PDF file
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return pdf_content
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iface = gr.Interface(
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fn=process_input,
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inputs=[
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@@ -22,8 +19,33 @@ iface = gr.Interface(
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label="Hello. This app is called Abstract Summariser and gives a one sentence summary of the input PDF in both written and spoken form. Please upload a PDF file that contains an abstract.",
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),
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],
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outputs=
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)
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iface.launch(share=True)
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#iface.launch()
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#python app.py
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@@ -336,3 +358,9 @@ with torch.no_grad():
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speech = model.generate_speech(inputs["input_ids"], speaker_embeddings, vocoder=vocoder)
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Audio(speech, rate=16000)
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# The code receives a PDF but doesnt' appear to process it.
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# I still need to add the gradio interface output to show the summarized text and play the sound file
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import gradio as gr
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# Interface for displaying the summarized text
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summarized_textbox = gr.Textbox(type="text", label="Summarized Text")
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# Interface for playing the speech
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speech_audio = gr.Audio(type="file", label="Text-to-Speech Audio", element_id="audio_element")
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# Interface to process input and display results
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iface = gr.Interface(
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fn=process_input,
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inputs=[
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label="Hello. This app is called Abstract Summariser and gives a one sentence summary of the input PDF in both written and spoken form. Please upload a PDF file that contains an abstract.",
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),
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],
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outputs=[summarized_textbox, speech_audio], # Display the summarized text and audio
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)
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def process_input(pdf_file):
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print("Received PDF File:", pdf_file.name)
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# Read the content of the uploaded PDF file
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pdf_content = pdf_file.read()
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# Save the received PDF content locally
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with open("received_pdf.pdf", "wb") as output_file:
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output_file.write(pdf_content)
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# Return the content of the processed PDF file
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return pdf_content
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###commented out latest version
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#iface = gr.Interface(
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# fn=process_input,
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# inputs=[
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# gr.File(
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# type="binary",
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# label="Hello. This app is called Abstract Summariser and gives a one sentence summary of the input PDF in both written and spoken form. Please upload a PDF file that contains an abstract.",
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# ),
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# ],
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# outputs=None,
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#)
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iface.launch(share=True)
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#iface.launch()
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#python app.py
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speech = model.generate_speech(inputs["input_ids"], speaker_embeddings, vocoder=vocoder)
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Audio(speech, rate=16000)
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#new code
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summarized_text = summarize_abstract(abstract_from_pdf)
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# Set the value of the summarized_textbox
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summarized_textbox.value = summarized_text
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speech_audio.file = audio_path
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