Create app.py

app.py

@@ -0,0 +1,34 @@
+import subprocess
+
+subprocess.run(["pip", "install", "PyPDF2", "transformers", "bark", "gradio"])
+
+import PyPDF2
+from transformers import pipeline
+from bark import SAMPLE_RATE, generate_audio, preload_models
+import gradio as gr
+
+def summarize_and_convert_to_audio(pdf_path, abstract_page):
+    with open(pdf_path, 'rb') as file:
+        pdf_reader = PyPDF2.PdfReader(file)
+        
+        # Get the abstract page text
+        abstract_page_text = pdf_reader.pages[abstract_page - 1].extract_text()
+
+    summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+    summary = summarizer(abstract_page_text, max_length=20, min_length=20)
+
+    preload_models()
+
+    text = summary[0]['summary_text']
+    audio_array = generate_audio(text)
+
+    return Audio(audio_array, rate=SAMPLE_RATE)
+
+iface = gr.Interface(
+    fn=summarize_and_convert_to_audio,
+    inputs=["file", "number"],
+    outputs="audio",
+    live=True
+)
+
+iface.launch()