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| import gradio as gr | |
| import google.generativeai as genai | |
| import whisper | |
| import requests | |
| import subprocess | |
| import os | |
| import time | |
| import tempfile | |
| from base64 import b64decode | |
| # ── Load API keys from HF Secrets ───────────────────────────────── | |
| MURF_API_KEY = os.environ.get("MURF_API_KEY", "") | |
| GEMINI_API_KEY = os.environ.get("GEMINI_API_KEY", "") | |
| # ── Configure Gemini ─────────────────────────────────────────────── | |
| genai.configure(api_key=GEMINI_API_KEY) | |
| SYSTEM_PROMPT = """ | |
| You are ARIA, a warm, witty, smart voice assistant. | |
| STRICT RULES: | |
| 1. Reply in MAXIMUM 2 short sentences — spoken aloud | |
| 2. Sound 100% human — contractions, casual words | |
| 3. Be expressive — curious, funny, empathetic | |
| 4. NEVER say 'As an AI' — talk like a real person | |
| 5. Remember everything in this conversation | |
| 6. End with a natural hook to keep conversation flowing | |
| """ | |
| gemini_model = genai.GenerativeModel( | |
| model_name="gemini-1.5-flash", | |
| system_instruction=SYSTEM_PROMPT | |
| ) | |
| chat_session = gemini_model.start_chat(history=[]) | |
| MURF_VOICE_ID = "en-US-natalie" | |
| # ── Load Whisper once at startup ─────────────────────────────────── | |
| print("Loading Whisper tiny.en...") | |
| whisper_model = whisper.load_model("tiny.en") | |
| print("Whisper ready!") | |
| def ask_gemini(text: str, retries: int = 4) -> str: | |
| for attempt in range(retries): | |
| try: | |
| return chat_session.send_message(text).text.strip() | |
| except Exception as e: | |
| if "429" in str(e): | |
| wait = 40 | |
| for tok in str(e).split(): | |
| try: | |
| v = float(tok.rstrip("s,.")) | |
| if 1 < v < 300: | |
| wait = int(v) + 5 | |
| break | |
| except: | |
| pass | |
| if attempt < retries - 1: | |
| time.sleep(wait) | |
| else: | |
| raise RuntimeError("Rate limited — try again in a minute") | |
| else: | |
| raise RuntimeError(str(e)[:150]) | |
| def speak_murf(text: str) -> str: | |
| r = requests.post( | |
| "https://api.murf.ai/v1/speech/generate", | |
| json={ | |
| "text": text, | |
| "voiceId": MURF_VOICE_ID, | |
| "style": "Conversational", | |
| "format": "mp3", | |
| "sampleRate": 24000, | |
| "speed": -5, | |
| }, | |
| headers={"api-key": MURF_API_KEY, "Content-Type": "application/json"}, | |
| timeout=20 | |
| ) | |
| if r.status_code != 200: | |
| raise RuntimeError(f"Murf error {r.status_code}: {r.text[:150]}") | |
| audio_url = r.json().get("audioFile", "") | |
| audio_bytes = requests.get(audio_url, timeout=20).content | |
| # Save to temp file for Gradio to serve | |
| tmp = tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") | |
| tmp.write(audio_bytes) | |
| tmp.close() | |
| return tmp.name | |
| def process_audio(audio_path): | |
| """Main pipeline: audio file → text → Gemini → Murf → audio""" | |
| if audio_path is None: | |
| return None, "⚠️ No audio received. Please record something.", "" | |
| try: | |
| # ── Step 1: Convert to WAV ───────────────────────────────── | |
| wav_path = "/tmp/aria_input.wav" | |
| subprocess.run( | |
| ["ffmpeg", "-y", "-i", audio_path, | |
| "-ar", "16000", "-ac", "1", | |
| "-t", "8", wav_path], | |
| capture_output=True, check=True | |
| ) | |
| # ── Step 2: Whisper STT ──────────────────────────────────── | |
| result = whisper_model.transcribe( | |
| wav_path, | |
| fp16=False, | |
| language="en", | |
| task="transcribe" | |
| ) | |
| user_text = result["text"].strip() | |
| if not user_text: | |
| return None, "⚠️ Couldn't hear anything. Speak louder!", "" | |
| # ── Step 3: Gemini ───────────────────────────────────────── | |
| reply = ask_gemini(user_text) | |
| # ── Step 4: Murf TTS ─────────────────────────────────────── | |
| audio_out = speak_murf(reply) | |
| return audio_out, f"🧑 You: {user_text}", f"🤖 ARIA: {reply}" | |
| except Exception as e: | |
| return None, f"❌ Error: {str(e)}", "" | |
| # ── Gradio UI ────────────────────────────────────────────────────── | |
| css = """ | |
| #component-0 { max-width: 600px; margin: auto; } | |
| .title { text-align: center; } | |
| footer { display: none !important; } | |
| """ | |
| with gr.Blocks( | |
| title="🎤 ARIA — Voice Assistant", | |
| css=css, | |
| theme=gr.themes.Soft( | |
| primary_hue="violet", | |
| neutral_hue="slate" | |
| ) | |
| ) as demo: | |
| gr.HTML(""" | |
| <div style="text-align:center; padding: 20px 0 10px"> | |
| <h1 style="font-size:2.2rem; font-weight:700; margin:0">🎤 ARIA</h1> | |
| <p style="color:#888; margin:4px 0 0; font-size:0.95rem; letter-spacing:2px"> | |
| AI VOICE ASSISTANT · Gemini + Murf + Whisper | |
| </p> | |
| </div> | |
| """) | |
| with gr.Row(): | |
| with gr.Column(): | |
| audio_input = gr.Audio( | |
| sources=["microphone"], | |
| type="filepath", | |
| label="🎙️ Press & Hold to Record", | |
| show_download_button=False | |
| ) | |
| submit_btn = gr.Button( | |
| "⚡ Send to ARIA", | |
| variant="primary", | |
| size="lg" | |
| ) | |
| with gr.Column(): | |
| audio_output = gr.Audio( | |
| label="🔊 ARIA's Voice Response", | |
| autoplay=True, | |
| show_download_button=False | |
| ) | |
| user_text_box = gr.Textbox( | |
| label="📝 You said", | |
| interactive=False, | |
| lines=2 | |
| ) | |
| aria_text_box = gr.Textbox( | |
| label="🤖 ARIA replied", | |
| interactive=False, | |
| lines=3 | |
| ) | |
| submit_btn.click( | |
| fn=process_audio, | |
| inputs=[audio_input], | |
| outputs=[audio_output, user_text_box, aria_text_box] | |
| ) | |
| # Also auto-submit when recording stops | |
| audio_input.stop_recording( | |
| fn=process_audio, | |
| inputs=[audio_input], | |
| outputs=[audio_output, user_text_box, aria_text_box] | |
| ) | |
| gr.HTML(""" | |
| <div style="text-align:center; color:#666; font-size:0.8rem; padding:16px 0 0"> | |
| gemini-1.5-flash · whisper tiny.en · murf conversational | |
| </div> | |
| """) | |
| demo.launch() | |
| ``` | |
| --- | |
| ## 📄 File 2 — `requirements.txt` | |
| ``` | |
| google-generativeai | |
| openai-whisper | |
| requests | |
| gradio | |
| ffmpeg-python | |
| ``` | |
| --- | |
| ## 🌐 Deploy Steps on Hugging Face | |
| ### Step 1 — Create account | |
| Go to **https://huggingface.co** → Sign Up (free) | |
| ### Step 2 — Create new Space | |
| ``` | |
| huggingface.co/spaces → + New Space | |
| Fill in: | |
| Space name: aria-voice-assistant | |
| SDK: Gradio ← important! | |
| Hardware: CPU Basic (free) | |
| Visibility: Public or Private | |
| ``` | |
| ### Step 3 — Add Secret API Keys | |
| ``` | |
| Space page → Settings tab → Variables and Secrets | |
| Add secret: MURF_API_KEY = your_murf_key | |
| Add secret: GEMINI_API_KEY = your_gemini_key | |
| ``` | |
| > ✅ Secrets are encrypted — nobody can see them, not even you after saving | |
| ### Step 4 — Upload files | |
| ``` | |
| Space page → Files tab → + Add File | |
| Upload: app.py | |
| Upload: requirements.txt | |
| ``` | |
| ### Step 5 — Wait for build (~3 min) | |
| ``` | |
| Space auto-builds → watch the logs | |
| When you see "Running on public URL" → it's live! | |
| ``` | |
| ### Step 6 — Your live URL | |
| ``` | |
| https://huggingface.co/spaces/YOUR_USERNAME/aria-voice-assistant |