Update app.py

app.py

@@ -1,37 +1,27 @@
 import gradio as gr
 from PyPDF2 import PdfReader
 from transformers import pipeline
-from bark import SAMPLE_RATE, generate_audio, preload_models
-from IPython.display import Audio
 
-# Preload Bark models
-preload_models()
-
-def summarize_generate_audio(files):
-    summarizer = pipeline("summarization", model="stevhliu/my_awesome_billsum_model")
+def summarize_and_extract_text(files):
+    summarizer = pipeline("summarization")
     summaries = []
-    audios = []
-
+    extracted_texts = []
     for file in files:
         with open(file.name, "rb") as pdf_file:
             pdf_reader = PdfReader(pdf_file)
             text = ""
             for page in pdf_reader.pages:
                 text += page.extract_text() + "\n"
+            extracted_texts.append(text)
             summary = summarizer(text, max_length=50, min_length=10, do_sample=False)[0]['summary_text']
             summaries.append(summary)
-            audio_array = generate_audio(summary)
-            audios.append(audio_array)
-    return summaries, audios
+    return summaries, extracted_texts
 
 iface = gr.Interface(
-    fn=summarize_generate_audio,
+    fn=summarize_and_extract_text,
     inputs=gr.UploadButton("Click to Upload a PDF", file_types=["pdf"], file_count="multiple"),
-    outputs=[
-        gr.Textbox(label="Summarized Text"),
-        gr.Audio(label="Generated Audio")
-    ],
-    title="PDF Summarizer & Audio Generator"
+    outputs=[gr.Textbox(label="Summarized Text"), gr.Textbox(label="Extracted Text")],
+    title="PDF Summarizer & Extracted Text"
 )
 
 iface.launch()