TTS / app.py
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Update app.py
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import gradio as gr
import numpy as np
import io
import base64
import requests
import re
from scipy.io import wavfile
from murf import Murf
# Global variable to track the number of tries.
attempt_count = 0
# Initialize the Murf client with your initial API key.
client = Murf(api_key="ap2_94209101-077d-4962-9f4b-daeec8caeda2")
def extract_voice_id(selection):
"""
Extracts the voice ID from the dropdown selection.
Expects a string in the format "Label (voice_id)".
"""
match = re.search(r'\((.*?)\)', selection)
if match:
return match.group(1)
return selection
def generate_voice_murf(text, voice_selection):
global attempt_count, client
# Check if the try limit is reached.
if attempt_count >= 5:
raise gr.Error("Limit of 5 tries reached. Please update your API key. To fetch your new API key, visit https://murf.ai/api/dashboard.")
attempt_count += 1
# Extract the voice_id from the dropdown selection.
voice_id = extract_voice_id(voice_selection)
try:
# Limit text to 250 characters.
text = text[:250]
# Call the Murf API to generate speech.
response = client.text_to_speech.generate(
text=text,
voice_id=voice_id,
format="WAV"
)
# Try to access the audio data.
if hasattr(response, "encoded_audio") and response.encoded_audio:
audio_bytes = base64.b64decode(response.encoded_audio)
elif hasattr(response, "audio_file") and response.audio_file:
audio_url = response.audio_file
r = requests.get(audio_url)
if r.status_code != 200:
raise Exception("Error downloading audio file.")
audio_bytes = r.content
else:
raise Exception("No audio returned by the API.")
# Convert the audio bytes to a NumPy array for Gradio.
audio_file = io.BytesIO(audio_bytes)
sample_rate, audio_data = wavfile.read(audio_file)
return (sample_rate, audio_data)
except Exception as e:
raise gr.Error(str(e))
def update_api_key(new_key):
global client, attempt_count
if new_key.strip() == "":
raise gr.Error("Please provide a valid API key.")
client = Murf(api_key=new_key)
attempt_count = 0 # Reset try counter
return "API key updated successfully. You can now try again."
# Define sample voice options as friendly strings.
voice_options = [
"Natalie (en-US-natalie)",
"Matt (en-UK-matt)"
]
with gr.Blocks() as demo:
gr.Markdown("# Murf TTS Demo")
gr.Markdown("A demo using the Murf API to generate speech from text. Enter some text (max 250 characters) and choose a voice.")
input_text = gr.Textbox(
label="Input Text (250 characters max)",
lines=2,
value="Hello, welcome to the Murf TTS demo!",
elem_id="input_text"
)
voice_dropdown = gr.Dropdown(
label="Voice",
choices=voice_options,
value=voice_options[0],
elem_id="voice_dropdown"
)
generate_button = gr.Button("Generate Voice", elem_id="generate_button")
out_audio = gr.Audio(label="Generated Voice", type="numpy", elem_id="out_audio")
generate_button.click(
fn=generate_voice_murf,
inputs=[input_text, voice_dropdown],
outputs=out_audio,
queue=True
)
# Update API Key section – only needed after a "Limit of 5 tries reached" error.
gr.Markdown("### Update API Key (Only update after receiving a 'Limit of 5 tries reached' error)")
gr.Markdown("To fetch your new API key, visit [Murf Dashboard](https://murf.ai/api/dashboard).")
new_api_key = gr.Textbox(
label="New API Key",
placeholder="Enter new API key here...",
elem_id="new_api_key"
)
update_button = gr.Button("Update API Key", elem_id="update_button")
api_key_status = gr.Textbox(label="Status", interactive=False, elem_id="api_key_status")
update_button.click(
fn=update_api_key,
inputs=new_api_key,
outputs=api_key_status,
queue=True
)
demo.launch()