Create app.py

app.py

@@ -0,0 +1,37 @@
+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")
+    summaries = []
+    audios = []
+
+    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"
+            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
+
+iface = gr.Interface(
+    fn=summarize_generate_audio,
+    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"
+)
+
+iface.launch()