Text Translation

This example demonstrates how to use ControlFlow to create a task that translates text from one language to another. It showcases the use of custom types and context passing for language translation tasks.

​

Code

The following code creates a function that takes a text string and a target language, then returns a translation result:

import controlflow as cf
from pydantic import BaseModel

class TranslationResult(BaseModel):
    translated: str
    target_language: str

def translate_text(text: str, target_language: str) -> TranslationResult:
    return cf.run(
        f"Translate the given text to {target_language}",
        result_type=TranslationResult,
        context={"text": text, "target_language": target_language}
    )

Now we can use this function to translate text:

​

Key concepts

This implementation showcases several important ControlFlow features:

1. Pydantic models: We use a Pydantic model (TranslationResult) to define the structure of our translation result. This ensures that the translation task returns well-structured, consistent results.

   class TranslationResult(BaseModel):
       original: str
       translated: str
       target_language: str
   

2. Context passing: We pass both the original text and the target language as context to the task, providing all necessary information for the translation.

   context={"text": text, "target_language": target_language}
   

By leveraging these ControlFlow features, we create an efficient and flexible text translation tool. This example demonstrates how ControlFlow can be used to build AI-powered language processing workflows that can handle translation tasks with ease.