Upload app.py

app.py

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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()
+
+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()