Create app.py

app.py

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+import gradio as gr
+from groq import Groq
+from gtts import gTTS
+import tempfile
+import os
+
+# ---------------- CONFIG ----------------
+# On Hugging Face Spaces, add your Groq API key under Settings → Secrets → GROQ_API_KEY
+client = Groq(api_key=os.getenv("GROQ_API_KEY", "YOUR_GROQ_API_KEY"))
+
+# Store last few messages for context
+memory = []
+
+# ---------------- LLM BOT ----------------
+def llm_bot(prompt):
+    # Use last few turns of context for continuity
+    chat_history = "\n".join([f"{r[0]}: {r[1]}" for r in memory[-6:]])
+
+    completion = client.chat.completions.create(
+        model="llama-3.1-8b-instant",
+        messages=[
+            {"role": "system", "content": "You are a friendly and helpful AI voice assistant."},
+            {"role": "user", "content": f"{chat_history}\nUser: {prompt}"}
+        ],
+    )
+    return completion.choices[0].message.content.strip()
+
+# ---------------- MAIN FUNCTION ----------------
+def speech_to_speech(audio):
+    if audio is None:
+        return "Please speak something!", None
+
+    # Step 1: Transcribe speech to text using Groq Whisper
+    with open(audio, "rb") as f:
+        transcription = client.audio.transcriptions.create(
+            file=("speech.wav", f.read()),
+            model="whisper-large-v3",
+        )
+    user_text = transcription.text.strip()
+
+    # Step 2: Generate LLM response
+    response = llm_bot(user_text)
+    memory.append(("User", user_text))
+    memory.append(("Bot", response))
+
+    # Step 3: Convert LLM response to speech
+    tts = gTTS(response)
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as temp_audio:
+        tts.save(temp_audio.name)
+        audio_out = temp_audio.name
+
+    # Step 4: Return text + audio
+    return f"🗣️ You said: {user_text}\n\n🤖 Bot: {response}", audio_out
+
+
+# ---------------- GRADIO INTERFACE ----------------
+with gr.Blocks(title="Groq Voice Chatbot 🎙️") as demo:
+    gr.Markdown("## 🎧 Groq-Powered Voice Assistant")
+    gr.Markdown("Speak naturally — it listens, thinks, and replies with speech using LLaMA-3.1 and Whisper on Groq!")
+
+    mic = gr.Audio(sources=["microphone"], type="filepath", label="🎙️ Speak Here")
+    output_text = gr.Textbox(label="🧠 Transcription + Bot Response")
+    output_audio = gr.Audio(label="🔊 Bot Voice Reply")
+
+    submit_btn = gr.Button("💬 Talk")
+
+    submit_btn.click(
+        fn=speech_to_speech,
+        inputs=[mic],
+        outputs=[output_text, output_audio]
+    )
+
+demo.launch()