Spaces:
Runtime error
Runtime error
File size: 4,824 Bytes
e228198 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 |
# Required Libraries
import whisper
from groq import Groq
from gtts import gTTS
import gradio as gr
import os
import tempfile
from pydub import AudioSegment
# ---------------------------
# 🔑 API Key Configuration
# ---------------------------
GROQ_API_KEY= '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'
client=Groq(api_key=GROQ_API_KEY)
# Initialize Whisper model
whisper_model = whisper.load_model("base")
# ---------------------------
# 🎙️ 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}")
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__":
interface.launch(share=True)
|