Create app.py

app.py

@@ -0,0 +1,38 @@
+import PyPDF2
+from transformers import pipeline
+import gradio as gr
+
+# Function to extract text from PDF
+def extract_text_from_pdf(pdf_file):
+    reader = PyPDF2.PdfReader(pdf_file)
+    text = ""
+    for page in reader.pages:
+        if page and page.extract_text():
+            text += page.extract_text()
+    return text
+
+# Load text-to-speech pipeline from Hugging Face
+tts = pipeline("text-to-speech", model="facebook/fastspeech2-en-ljspeech")
+
+# Function to convert PDF to audio with no text limit
+def pdf_to_audio(pdf_file):
+    text = extract_text_from_pdf(pdf_file)
+    if not text.strip():
+        return "", "No text found in PDF"
+
+    audio = tts(text)
+    audio_path = "output_audio.wav"
+    with open(audio_path, "wb") as f:
+        f.write(audio["audio"])  # Hugging Face TTS returns audio data
+
+    return audio_path, "Audio generated successfully"
+
+# Gradio interface
+interface = gr.Interface(
+    fn=pdf_to_audio,
+    inputs=gr.File(type="file"),
+    outputs=[gr.Audio(type="filepath"), gr.Text()]
+)
+
+if __name__ == "__main__":
+    interface.launch()