Create app.py

app.py

@@ -0,0 +1,101 @@
+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()
+