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import gradio as gr
from utils import generate_script, generate_audio, truncate_text, extract_text_from_url
from prompts import SYSTEM_PROMPT
from pydub import AudioSegment
import pypdf
import os
import tempfile
def generate_podcast(file, url, tone, length):
try:
if file and url:
return None, "Please provide either a PDF file or a URL, not both."
if file:
if not file.name.lower().endswith('.pdf'):
return None, "Please upload a PDF file."
pdf_reader = pypdf.PdfReader(file.name)
text = ""
for page in pdf_reader.pages:
text += page.extract_text()
elif url:
text = extract_text_from_url(url)
else:
return None, "Please provide either a PDF file or a URL."
truncated_text = truncate_text(text)
if len(truncated_text) < len(text):
print("Warning: The input text was truncated to fit within 2048 tokens.")
script = generate_script(SYSTEM_PROMPT, truncated_text, tone, length)
audio_segments = []
transcript = ""
try:
for item in script.dialogue:
audio_file = generate_audio(item.text, item.speaker)
audio_segment = AudioSegment.from_mp3(audio_file)
audio_segments.append(audio_segment)
transcript += f"**{item.speaker}**: {item.text}\n\n"
os.remove(audio_file) # Clean up temporary audio file
except Exception as e:
raise gr.Error(f"Error generating audio: {str(e)}")
combined_audio = sum(audio_segments)
with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as temp_audio:
combined_audio.export(temp_audio.name, format="mp3")
temp_audio_path = temp_audio.name
return temp_audio_path, transcript
except Exception as e:
return None, f"An error occurred: {str(e)}"
instructions = """
# Podify Studio
Welcome to the Podcast Generator ! This tool creates custom podcast episodes using AI-generated content.
"""
iface = gr.Interface(
fn=generate_podcast,
inputs=[
gr.File(label="Upload PDF file (optional)", file_types=[".pdf"]),
gr.Textbox(label="OR Enter URL"),
gr.Radio(["humorous", "casual", "formal"], label="Select podcast tone", value="casual"),
gr.Radio(["Short (1-2 min)", "Medium (3-5 min)"], label="Podcast length", value="Medium (3-5 min)")
],
outputs=[
gr.Audio(label="Generated Podcast"),
gr.Markdown(label="Transcript")
],
title="🎙️ Amuthvani:AI Podcast !",
description=instructions,
allow_flagging="never",
theme=gr.themes.Soft()
)
if __name__ == "__main__":
iface.launch()
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