Upload app.py

app.py

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+import streamlit as st
+import os
+import tempfile
+import speech_recognition as sr
+import torch
+from groq import Groq
+from TTS.api import TTS
+from pydub import AudioSegment
+
+client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
+
+st.set_page_config(page_title="Voice Q&A App", layout="centered")
+st.title("🎤 Voice Q&A with Groq + TTS")
+
+uploaded_audio = st.file_uploader("Upload your question (WAV or M4A format)", type=["wav", "m4a"], key="uploader")
+user_text = None
+
+if uploaded_audio:
+    with tempfile.NamedTemporaryFile(delete=False, suffix=f".{uploaded_audio.name.split('.')[-1]}") as f:
+        f.write(uploaded_audio.read())
+        audio_path = f.name
+
+    if uploaded_audio.name.endswith(".m4a"):
+        wav_path = audio_path.replace(".m4a", ".wav")
+        sound = AudioSegment.from_file(audio_path)
+        sound.export(wav_path, format="wav")
+        audio_path = wav_path
+
+    recognizer = sr.Recognizer()
+    with sr.AudioFile(audio_path) as source:
+        audio_data = recognizer.record(source)
+        try:
+            user_text = recognizer.recognize_whisper(audio_data, model="base")
+            st.success(f"Recognized Text: {user_text}")
+        except Exception as e:
+            st.error(f"Speech recognition failed: {e}")
+
+if user_text:
+    st.header("Response from Groq AI")
+    with st.spinner("Generating response..."):
+        try:
+            chat_completion = client.chat.completions.create(
+                messages=[{"role": "user", "content": user_text}],
+                model="llama-3-70b-8192"
+            )
+            answer = chat_completion.choices[0].message.content
+            st.success("Answer:")
+            st.write(answer)
+
+            st.header("Listen to the Answer")
+
+            @st.cache_resource
+            def load_tts():
+                return TTS(model_name="tts_models/en/ljspeech/tacotron2-DDC", progress_bar=False, gpu=torch.cuda.is_available())
+
+            tts = load_tts()
+            tts_file_path = tempfile.mktemp(suffix=".wav")
+            tts.tts_to_file(text=answer, file_path=tts_file_path)
+
+            with open(tts_file_path, "rb") as audio_file:
+                st.audio(audio_file.read(), format="audio/wav")
+        except Exception as e:
+            st.error(f"Groq API Error: {e}")