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import os
import gradio as gr
from pydantic.v1 import BaseModel, Field
from langchain.prompts import HumanMessagePromptTemplate, ChatPromptTemplate
from langchain.output_parsers import PydanticOutputParser
from langchain_openai import ChatOpenAI
chat = ChatOpenAI()
# Define the Pydantic Model
class TextTranslator(BaseModel):
output: str = Field(description="Python string containing the output text translated in the desired language")
output_parser = PydanticOutputParser(pydantic_object=TextTranslator)
format_instructions = output_parser.get_format_instructions()
def text_translator(input_text : str, language : str) -> str:
human_template = """Enter the text that you want to translate:
{input_text}, and enter the language that you want it to translate to {language}. {format_instructions}"""
human_message_prompt = HumanMessagePromptTemplate.from_template(human_template)
chat_prompt = ChatPromptTemplate.from_messages([human_message_prompt])
prompt = chat_prompt.format_prompt(input_text = input_text, language = language, format_instructions = format_instructions)
messages = prompt.to_messages()
response = chat(messages = messages)
output = output_parser.parse(response.content)
output_text = output.output
return output_text
# Interface
def translator_interface():
with gr.Blocks() as demo:
gr.HTML("<h1 align = 'center'> Text Translator </h1>")
gr.HTML("<h4 align = 'center'> Translate to any language </h4>")
with gr.Row():
input_text = gr.Textbox(label="Enter the text that you want to translate")
language = gr.Textbox(label="Enter the language that you want it to translate to", placeholder="Example: Hindi, French, Bengali, etc.")
generate_btn = gr.Button(value='Generate')
output_text = gr.Textbox(label="Translated text")
generate_btn.click(fn=text_translator, inputs=[input_text, language], outputs=output_text)
return demo
# สำหรับแสดง Interface ใน app.py
def get_translator_tab():
return translator_interface()
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