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import os
import tempfile
import io
import gradio as gr
from openai import OpenAI
# Read API key from Space secret
client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
SYSTEM_PROMPT = "You are a friendly, concise voice assistant. Keep replies short when spoken (~2-3 sentences)."
def ensure_bytesio(obj):
if isinstance(obj, (bytes, bytearray)):
return io.BytesIO(obj)
return obj
def chat_fn(history, mic_audio, text_input, voice="alloy", model=None, temperature=0.6):
messages = [{"role": "system", "content": SYSTEM_PROMPT}]
# Convert history (list of [user, assistant]) -> messages
for pair in history or []:
if pair[0]:
messages.append({"role": "user", "content": pair[0]})
if len(pair) > 1 and pair[1]:
messages.append({"role": "assistant", "content": pair[1]})
user_text = (text_input or "").strip()
# If user provided audio, transcribe it
transcript_text = None
if mic_audio:
# mic_audio is a file path (type='filepath')
with open(mic_audio, "rb") as f:
tr = client.audio.transcriptions.create(
model="whisper-1",
file=f,
response_format="text"
)
transcript_text = tr if isinstance(tr, str) else getattr(tr, "text", None)
if transcript_text:
user_text = (user_text + " " + transcript_text).strip() if user_text else transcript_text
if not user_text:
return history, None, "Please speak or type something."
messages.append({"role": "user", "content": user_text})
chosen_model = model or os.getenv("OPENAI_MODEL", "gpt-4o-mini")
comp = client.chat.completions.create(
model=chosen_model,
messages=messages,
temperature=float(temperature)
)
reply = comp.choices[0].message.content.strip()
# TTS
speech = client.audio.speech.create(
model="gpt-4o-mini-tts",
voice=voice,
input=reply
)
# Save to a temp mp3
with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp:
tmp.write(speech.read())
tts_path = tmp.name
new_hist = (history or []) + [[user_text, reply]]
return new_hist, tts_path, transcript_text or ""
with gr.Blocks(theme=gr.themes.Soft(), fill_height=True) as demo:
gr.Markdown("# 🎙️ Voice Chat (Hugging Face Space)
Talk to the AI and it talks back.")
with gr.Row():
chatbot = gr.Chatbot(height=340, type="messages")
with gr.Row():
audio_in = gr.Audio(sources=["microphone"], type="filepath", label="Mic (press to record)")
with gr.Row():
text_in = gr.Textbox(placeholder="...or type here and press Enter", scale=2)
voice = gr.Dropdown(choices=["alloy","verse","amber","aria","bright","sage","sol","luna","coral","spark","horizon"], value="alloy", label="Voice", scale=1)
with gr.Row():
model = gr.Textbox(value="", placeholder="Model (leave blank for gpt-4o-mini)", label="Model override", scale=1)
temp = gr.Slider(0.0, 1.5, value=0.6, step=0.1, label="Creativity")
with gr.Row():
audio_out = gr.Audio(label="AI Voice Reply", autoplay=True)
transcript = gr.Textbox(label="Last transcription", interactive=False)
state = gr.State([])
def _chat(state_hist, audio, text, voice, model, temp):
return chat_fn(state_hist, audio, text, voice, model, temp)
go = gr.Button("Send / Speak")
clear = gr.Button("Clear")
go.click(_chat, inputs=[state, audio_in, text_in, voice, model, temp], outputs=[state, audio_out, transcript])
text_in.submit(_chat, inputs=[state, audio_in, text_in, voice, model, temp], outputs=[state, audio_out, transcript])
clear.click(fn=lambda: ([], None, ""), outputs=[state, audio_out, transcript])
if __name__ == "__main__":
demo.launch()
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