Welcome to the second lesson of our course, Laying the Foundations for Code Translation with Haystack! In our first lesson, you learned how to use Haystack to translate natural language text. Now, we're ready to tackle a more challenging and practical task: building a pipeline that translates code from one programming language to another.

Automated code translation is a powerful tool for developers. Whether you're porting a project, learning a new language, or collaborating with teams using different tech stacks, being able to translate code quickly and accurately can save hours of work. By the end of this lesson, you'll have a working code translation pipeline that you can use and extend for your own projects.

The heart of our pipeline is the prompt we give to the language model. A good prompt makes the model's job clear and helps ensure accurate translations. Let's see how to build a prompt template that's both flexible and effective:

Here, we're telling the model exactly what we want: a translation from one programming language to another. By using variables like {{source_lang}}, {{target_lang}}, and {{code}}, we make our prompt reusable for any language pair and any code snippet. This approach keeps our pipeline adaptable and easy to extend.

With our prompt in place, the next step is to set up the components that will power our translation pipeline. We'll use Haystack's modular design to keep things organized and maintainable.

This function creates a pipeline that takes in code and language specifications, builds a prompt, and sends it to the language model using the OpenAIGenerator. By wrapping this logic in a function, we make it easy to create pipelines for any language pair.

To make our pipeline easy to use, let's create a function that handles the translation process from start to finish. This function will take care of building the pipeline, preparing the input, and extracting the translated code:

This function abstracts away the pipeline details, so you can focus on what matters: providing code and getting a translation. The result extraction step is tailored to Haystack's output format, ensuring you always get the translated code in a straightforward way.

Let's see our translator in action with a practical example. Suppose you have a simple Python function and want to convert it to JavaScript:

When you run this, you'll see output similar to the following:

Notice how the output not only provides the translated JavaScript code, but also includes a brief explanation and uses idiomatic JavaScript syntax. This demonstrates the effectiveness of the pipeline in producing clear and context-aware translations.

Great work—your code translation pipeline is up and running! With just a few lines of code, you’ve unlocked the ability to convert programs between languages, making cross-language development faster and more accessible. This is a powerful foundation you can build on, whether you want to handle more complex code, add new features, or integrate translation into your own projects.

Now, it’s your turn to get hands-on. In the next section, you’ll dive into practice exercises designed to reinforce what you’ve learned and help you master each step of the pipeline. Happy coding!