[Feature]: Retrieval Augmented Generation for function calling

### Feature Request

As demonstrated in this video https://youtu.be/QMaWfbosR_E there is a potential to use Retrieval Augmented Generation to redirect LLM calls to our own functions for specific use cases, where LLM could fail to respond correctly (for example a web search, a hard math calculation or a fresh summary of URL contents)

How could we achieve this feature in the spirit of Rivet?

We could have a block for:
* text to train alternative RAG paths on LLM (with cached output) - input and output nodes are both LLM

routed into block for:
* calling text on new model with applied training (new exit nodes appear for distinct functions trained in previous block)

routed into multiple blocks for:
* function calls (these are tiny python code snippets to be executed when called)

### Code of Conduct

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