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This tutorial shows a practical cost-reduction pattern for multimodal AI: a fast object detector screens every image, and a gate forwards only plausible candidates to a more expensive vision LLM like Gemini. The core trade-off is recall versus cost, so the useful question for readers is how many relevant images the cheap first stage drops, which the article proposes measuring on labeled examples. Teams processing large image libraries should validate that retention rate before relying on the approach.
How to Pre-Filter Images Before Sending Them to an LLM
Learn how to pre-filter images before sending them to an LLM. Build a two-stage cascade in Roboflow Workflows where RF-DETR annotates every image, a Continue If gate drops clear negatives, and Gemini checks only the candidates. Cut inference cost without losing the images that matter.
To pre-filter images before sending them to an LLM, run a fast RF-DETR detector on every image in Roboflow Workflows and add a Continue If gate, so only images that match your rule reach Gemini. Sending every image in a dataset to a multimodal LLM means spending time and tokens on images that may never meet your selection criteria. To pre-filter images before sending them to an LLM, run an object detection model first, apply a relevance rule, and send only the images that pass for deeper analysis. With Roboflow Workflows, you can connect these steps in one pipeline. An RF-DETR model detects objects, a Continue If block controls which images advance, and Google Gemini analyzes the remaining candidates and returns structured results. In this tutorial, you’ll build a workflow for finding sports-car photos in a larger image library. The detector identifies potential candidates, while Gemini checks whether the vehicle is a sports car, whether it is the main subject, and whether alcohol is visible. You’ll also learn how to tune the filter on labeled examples, measure how many relevant images it retains, and process a dataset with Python. The goal is to reduce unnecessary LLM calls while preserving the…
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