A software vendor's Foundry-hosted assistant must always respond in the company's specific documentation tone and format, and it must also quote the current price of each product, which changes weekly through automated updates in a product catalog. The team wants pricing to always stay current without retraining the model, while the tone and formatting stay consistent. Which combination of techniques should they use?
Select an answer to reveal the explanation.
Short Explanation
You want tone baked in once with fine-tuning, but prices fetched live with retrieval-augmented generation. That keeps the voice consistent and the numbers current without weekly retraining. You don't want to retrain every week just to keep prices fresh.
Full Explanation
The correct answer is the combination of fine-tuning the model on writing style examples for tone and connecting it to the live product catalog through retrieval-augmented generation for pricing. Fine-tuning is well suited to teaching a model a consistent tone and formatting pattern because those are stable, repeatable characteristics the model can internalize once, while retrieval-augmented generation is well suited to pricing because it pulls the latest values from the live product catalog at the moment of each request, so prices stay current without ever retraining the model. The approach that fine-tunes the model on both writing style examples and this week's prices, then repeats the job weekly, is incorrect because retraining every week to bake in that week's prices reintroduces the exact staleness problem the team wants to avoid between fine-tuning runs, and it adds unnecessary weekly cost and delay. The approach that uses retrieval-augmented generation for both tone and pricing is incorrect because writing tone and formatting are properties of how the model generates language, and retrieval only supplies source text for the model to draw facts from; retrieved passages do not reliably constrain the model's own phrasing or structure, so tone consistency would suffer. The approach that relies on a longer system message listing this week's prices directly in every request is incorrect because manually listing prices in the system message requires someone to update that message every time prices change, which is exactly the manual, retraining-like effort the team is trying to eliminate, and it also wastes context space and cost on every request.