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Developer uses Jev as a gate to control Gemini LLM calls

By PulseAugur Editorial · [1 sources] ·

A developer has implemented a "System 1" gate using Jev, a small decision model, to filter user queries before they reach a more powerful "System 2" LLM like Gemini. This gate, costing approximately two cents per thousand questions, analyzes user input to determine if it's relevant to stock research, site help, navigation, or off-topic. It also checks for prompt injection attempts. By using this gate, the developer aims to prevent unnecessary calls to the expensive Gemini Flash model for irrelevant queries, thereby optimizing resource usage and cost for their RAG-based stock analysis website. AI

IMPACT Optimizes LLM usage and cost by filtering queries with a lightweight decision model before invoking expensive LLMs.

RANK_REASON Developer implements a cost-saving technique using a smaller model to gate access to a larger LLM.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Developer uses Jev as a gate to control Gemini LLM calls

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Developer implements a cost-saving technique using a smaller model to gate access to a larger LLM.
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product, infra
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Stas Slutsker ·

    Put a bouncer in front of your LLM: a Jev gate for your pet AI project

    <p><em>A small, cheap "System 1" model now decides whether the big, expensive "System 2" model gets called at all.</em></p> <p>I have a side project, <a href="https://telavivstocks.com" rel="noopener noreferrer">telavivstocks.com</a>. It's a Hebrew dashboard of Tel Aviv Stock Exc…

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