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from transformers import AutoModelForCausalLM, AutoTokenizer
from gtts import gTTS
import torch
import gradio as gr
device = "cuda" if torch.cuda.is_available() else "cpu"
language_model_name = "Qwen/Qwen2-1.5B-Instruct"
language_model = AutoModelForCausalLM.from_pretrained(
language_model_name,
torch_dtype="auto",
device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained(language_model_name)
def process_input(input_text, action):
if action == "Translate to English":
prompt = f"Please translate the following text into English: {input_text}"
lang = "en"
elif action == "Translate to Chinese":
prompt = f"Please translate the following text into Chinese: {input_text}"
lang = "zh-cn"
elif action == "Translate to Japanese":
prompt = f"Please translate the following text into Japanese: {input_text}"
lang = "ja"
elif action == "Translate to Russian":
prompt = f"Please translate the following text into Russian: {input_text}"
lang = "ru"
else:
prompt = input_text
lang = "en"
messages = [
{"role": "system", "content": "You are a helpful AI assistant."},
{"role": "user", "content": prompt}
]
text = tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True
)
model_inputs = tokenizer([text], return_tensors="pt").to(device)
generated_ids = language_model.generate(
model_inputs.input_ids,
max_new_tokens=512
)
generated_ids = [
output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
]
output_text = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
return output_text, lang
def text_to_speech(text, lang):
tts = gTTS(text=text, lang=lang)
filename = "output_audio.mp3"
tts.save(filename)
return filename
def handle_interaction(input_text, action):
output_text, lang = process_input(input_text, action)
audio_filename = text_to_speech(output_text, lang)
return output_text, audio_filename
action_options = ["Translate to English", "Translate to Chinese", "Translate to Russian", "Чат с ИИ"]
iface = gr.Interface(
fn=handle_interaction,
inputs=[
gr.Textbox(label="input text"),
gr.Dropdown(action_options, label="select action")
],
outputs=[
gr.Textbox(label="output text"),
gr.Audio(label="output audio")
],
title="Translation and Chat App using AI",
description="Translate input text or chat based on the selected action.",
theme= "gradio/soft"
)
if __name__ == "__main__":
iface.launch(share=True) |