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# Required Libraries
import os
import tempfile
import whisper
from groq import Groq
from gtts import gTTS
import gradio as gr
from pydub import AudioSegment
# ---------------------------
# 🔑 API Key Configuration
# ---------------------------
os.environ['GROQ_API_KEY'] = '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'
# ---------------------------
# 📥 Load Whisper Model
# ---------------------------
try:
whisper_model = whisper.load_model("base")
print("[INFO] Whisper model loaded successfully.")
except AttributeError:
from whisper import Whisper
whisper_model = Whisper.load_model("base")
print("[INFO] Whisper model loaded using alternative syntax.")
# ---------------------------
# 🎙️ Audio Processing
# ---------------------------
def validate_audio_file(audio_file):
"""Validate if the audio file exists and is not empty."""
if not audio_file or not os.path.exists(audio_file) or os.path.getsize(audio_file) == 0:
print(f"[ERROR] Invalid or empty audio file: {audio_file}")
return False
return True
def convert_to_wav(audio_file):
"""Convert audio file to WAV format if needed."""
try:
audio = AudioSegment.from_file(audio_file)
wav_path = tempfile.NamedTemporaryFile(suffix=".wav", delete=False).name
audio.export(wav_path, format="wav")
print(f"[INFO] Audio converted to WAV: {wav_path}")
return wav_path
except Exception as e:
print(f"[ERROR] Audio Conversion Error: {e}")
return None
def transcribe_audio(audio_file):
"""Transcribe audio using Whisper."""
try:
print(f"[INFO] Transcribing audio file: {audio_file}")
if not validate_audio_file(audio_file):
raise FileNotFoundError("Audio file not found or invalid path.")
audio_file = convert_to_wav(audio_file)
if not audio_file:
raise Exception("Failed to convert audio to WAV format.")
result = whisper_model.transcribe(audio_file)
print(f"[INFO] Transcription result: {result['text']}")
return result['text']
except Exception as e:
print(f"[ERROR] Transcription Error: {e}")
return f"Transcription Error: {e}"
# ---------------------------
# 🤖 LLM Interaction
# ---------------------------
def get_groq_response(user_input):
"""Get chatbot response from Groq's API."""
try:
print(f"[INFO] Sending input to Groq: {user_input}")
client = Groq(api_key=os.environ['GROQ_API_KEY'])
chat_completion = client.chat.completions.create(
messages=[
{"role": "user", "content": user_input}
],
model="llama-3.3-70b-versatile",
stream=False,
)
response = chat_completion.choices[0].message.content
print(f"[INFO] Groq response: {response}")
return response
except Exception as e:
print(f"[ERROR] Groq API Error: {e}")
return f"Groq API Error: {e}"
# ---------------------------
# 🗣️ Text-to-Speech
# ---------------------------
def text_to_speech(text):
"""Convert text to speech using gTTS."""
try:
print(f"[INFO] Converting text to speech: {text}")
tts = gTTS(text)
audio_path = tempfile.NamedTemporaryFile(suffix=".mp3", delete=False).name
tts.save(audio_path)
print(f"[INFO] Audio file saved: {audio_path}")
return audio_path
except Exception as e:
print(f"[ERROR] TTS Error: {e}")
return f"TTS Error: {e}"
# ---------------------------
# 🛠️ Main Interaction Logic
# ---------------------------
def chatbot(audio_input):
"""Handle full chatbot interaction."""
try:
print(f"[INFO] Audio Input Path: {audio_input}")
# Validate Audio File
if not validate_audio_file(audio_input):
return "Error: Audio file not found or invalid path", None
# Step 1: Transcribe Audio
text_input = transcribe_audio(audio_input)
if "Error" in text_input:
return text_input, None
# Step 2: Get Response from Groq
llm_response = get_groq_response(text_input)
if "Error" in llm_response:
return llm_response, None
# Step 3: Convert Response to Audio
audio_output = text_to_speech(llm_response)
if "Error" in audio_output:
return audio_output, None
return llm_response, audio_output
except Exception as e:
print(f"[ERROR] General Error: {e}")
return f"General Error: {e}", None
# ---------------------------
# 🌐 Gradio Interface
# ---------------------------
interface = gr.Interface(
fn=chatbot,
inputs=gr.Audio(type="filepath"),
outputs=[
gr.Textbox(label="LLM Response"),
gr.Audio(label="Audio Response")
],
title="Real-Time Voice-to-Voice Chatbot",
description="Speak into the microphone, and the chatbot will respond with audio.",
live=True # Ensures real-time interaction
)
# Launch Gradio App
if __name__ == "__main__":
print("[INFO] Starting Gradio Interface...")
interface.launch(share=True)
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