Update app.py

app.py

@@ -1,43 +1,12 @@
-import gradio as gr
-import PyPDF2
-from pdfminer.high_level import extract_text
-import pdfplumber
-from pdf2image import convert_from_path
-from PIL import Image
-import pytesseract
-from transformers import pipeline
-
-def read_pdf(pdf_path):
-    pdfFileObj = open(pdf_path, 'rb')
-    pdfReader = PyPDF2.PdfFileReader(pdfFileObj)
-
-    text_per_page = {}
-    for pagenum, page in enumerate(extract_text(pdf_path).split('\x0c')):
-        print("Elaborating Page_" + str(pagenum))
-        page_text = []
-        # other variables...
-
-        text_per_page[f'Page_{pagenum}'] = [page_text]  # You can add other lists as needed
-
-    pdfFileObj.close()
-    return text_per_page
-
-def summarize_text(text):
-    summarizer = pipeline("summarization", model="ainize/bart-base-cnn")
-    return summarizer(text)
-
-def text_to_speech(text):
-    # Add the text-to-speech code here using the provided code
-
-# Define Gradio interface
+# Gradio interface
 iface = gr.Interface(
-    fn=read_pdf,
-    inputs=gr.File(),
-    outputs=gr.Textbox(),
+    fn=summarize_and_speak,
+    inputs=gr.File(label="Upload PDF", type="file"),
+    outputs="text",
     live=True,
-    interpretation="pdf",
-    title="PDF Reader"
+    title="PDF Abstract Summarizer",
+    description="Please upload a PDF that contains an abstract. I will provide a one-sentence summary of the abstract and will say the summary out loud."
 )
 
-# Launch the Gradio app
-iface.launch()
+# Launch the interface
+iface.launch()