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import torch
from transformers import pipeline
import requests
import json
import soundfile as sf
import os
import google.generativeai as genai
def voice_to_text(audio_data, model_name="openai/whisper-small", device="cuda" if torch.cuda.is_available() else "cpu"):
try:
model = pipeline("automatic-speech-recognition", model=model_name, device=device, trust_remote_code=True)
text = model(audio_data)["text"]
return text
except Exception as e:
return f"Error during transcription"
def get_gemini_response(text):
genai.configure(api_key=os.environ['API_KEY'])
model = genai.GenerativeModel('gemini-1.5-flash')
prompt = f"You are a compassionate and supportive mental health assistant. Provide helpful advice, encouragement, and information to the user. Respond in a warm and understanding tone. User: {text}"
response = model.generate_content(prompt)
return response.text
def text_to_audio(text):
device = "cuda" if torch.cuda.is_available() else "cpu"
model = pipeline("text-to-speech", model="parler-tts/parler_tts_mini_v0.1", device=device, trust_remote_code=True)
audio_array = model(text)["audio"]
return audio_array