Update translator.py

translator.py

@@ -1,35 +1,49 @@
+import os
 import gradio as gr
-from pydantic import BaseModel, Field
+
+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
 
 chat = ChatOpenAI()
 
-# Define the Pydantic Model (updated for Pydantic v2)
+# Define the Pydantic Model
 class TextTranslator(BaseModel):
     output: str = Field(description="Python string containing the output text translated in the desired language")
-
-# Use PydanticOutputParser (no need for response_schemas)
+    
 output_parser = PydanticOutputParser(pydantic_object=TextTranslator)
+format_instructions = output_parser.get_format_instructions()
 
-def text_translator(input_text: str, language: str) -> str:
+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}."""
+                {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)
+    
+    prompt = chat_prompt.format_prompt(input_text = input_text, language = language, format_instructions = format_instructions)
+    
     messages = prompt.to_messages()
-    response = chat(messages=messages)
     
-    # Use output_parser to parse the response
+    response = chat(messages = messages)
+    
     output = output_parser.parse(response.content)
-    return output.output
+    
+    output_text = output.output
+    
+    return output_text
 
 def text_translator_ui():
-    gr.Markdown("### Text Translator\nTranslate text into any language using AI.")
-    input_text = gr.Textbox(label="Enter the text that you want to translate")
-    input_lang = gr.Textbox(label="Enter the language that you want it to translate to", placeholder="Example: Hindi, French, Bengali, etc.")
-    output_text = gr.Textbox(label="Translated text")
-    translate_button = gr.Button("Translate")
-    translate_button.click(fn=text_translator, inputs=[input_text, input_lang], outputs=output_text)
+    with gr.Column() as translator_ui:
+        gr.HTML("<h1 align='center'>Text Translator</h1>")
+        gr.HTML("<h4 align='center'>Translate to any language</h4>")
+
+        input_text = gr.Textbox(label="Enter the text that you want to translate")
+        target_lang = 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, target_lang], outputs=[output_text])
+        
+    return translator_ui