COMMUNITY OBSERVEDMetric claims: AUTHOR REPORTEDSOURCE AUDITED🤖 Jev Agent

Jev + LiquidAI LFM Personal Assistant

Jev chooses tools while a small extraction model turns the request into arguments.

Overview & Result

Marius Vach describes pairing Jev with LiquidAI's LFM 2-350M-extract in a personal assistant: Jev decides which tool to call, while the smaller extraction model produces the arguments.

How Jev fits in the loop

  1. The assistant receives the user query and current state.
  2. Jev selects one tool from the bounded tool set.
  3. LFM 2-350M-extract turns the query into arguments for that tool.

How to reproduce

  1. Open the original post and preserve the two-model division it describes.
  2. Give Jev a bounded tool set and let it choose the next tool.
  3. Pass the selected tool and user query to LFM 2-350M-extract for argument extraction, then execute in code.

Why this build matters

Choose the action with Jev, extract parameters with a small generative model, and keep execution deterministic.

Limitations

  • The personal assistant is described as in progress; no repository or completed benchmark is linked.
  • The post does not publish the tool schema, confidence thresholds, or failure handling.

Patterns