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import os | |
import gradio as gr | |
from langchain_core.pydantic_v1 import BaseModel, Field | |
from langchain.prompts import HumanMessagePromptTemplate, ChatPromptTemplate | |
from langchain.output_parsers import PydanticOutputParser | |
from langchain_openai import ChatOpenAI | |
# with open('openai_api_key.txt') as f: | |
# api_key = f.read() | |
# os.environ['OPENAI_API_KEY'] = api_key | |
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 | |
with gr.Blocks() as demo: | |
gr.HTML("<h1 align = 'center'> Text Translator </h1>") | |
gr.HTML("<h4 align = 'center'> Translate to any language </h4>") | |
inputs = [gr.Textbox(label = "Enter the text that you want to translate"), 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') | |
outputs = [gr.Textbox(label = "Translated text")] | |
generate_btn.click(fn = text_translator, inputs= inputs, outputs = outputs) | |
if __name__ == '__main__': | |
demo.launch() |