Explore how to efficiently switch between different Large Language Models (LLMs) using R with the vitals package. To initiate a new chat instance, simply create a chat object with your chosen model, such as Google Gemini 3 Flash Preview. You can run tasks in three ways: clone an existing task and set the new chat as its solver, clone it for a new evaluation, or create a new task from scratch with a distinct name.
For data analysis, utilize the vitals_bind() function to combine results from multiple tasks into a cohesive R dataframe. Easily analyze outputs by flattening complex data structures with tidyr.
Gain insights by testing local models, like Ollama, making it ideal for sensitive data use cases. Use the generate_structured() function for precise data extraction from text. Evaluate different models effectively and make informed decisions on your LLM applications. For deeper knowledge, consider exploring the capabilities of the vitals R package.
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