Jev Can Massively Speed Up Hermes Agents...

Summary

The video demonstrates how to speed up Hermes agents by adding a Jev decision model as a pre-LLM hook. Hermes stays connected to its normal reasoning model, while Jev handles quick, predefined classifications—such as identifying a request for disk usage—and runs the relevant command. The command output is then supplied as context.

The reasoning model still writes the final response, but can skip figuring out which simple command to run.

How the approach works

1. A user prompt is sent to Hermes and examined by the pre-LLM hook.
2. Jev classifies the request against configured categories.
3. For a recognized request, the hook runs a specified command and adds its output and an instruction to the prompt, such as “answer directly; do not use tools.”
4. Hermes’s reasoning model responds using that context.
5. Requests that do not match a configured use case proceed without added context.

This approach is most useful for frequent, predictable tasks where the command or action is already known. It does not replace the reasoning model; its usefulness depends on defining suitable categories and commands.

Tutorial highlights

The presenter walks through:

1. Setting up a Linux VPS, installing Hermes, configuring a model, and testing Hermes from the command line.
2. Storing a TypeSafe API key in Hermes’s environment file.
3. Writing a Python hook that sends the user message and classification questions to Jev’s API.
4. Registering the script as a pre-LLM hook in Hermes’s configuration and setting a timeout.
5. Testing a disk-usage example with df -h, then extending the approach to checks such as suspicious logs, system health, memory, site availability, and service status.

One troubleshooting step was adding a Python shebang to the hook script so Hermes could execute it directly. The presenter also notes that always-on agents are better suited to a server than a personal computer, and warns that running an agent on a personal system can be insecure without strong sandboxing.

Reported timing comparison

In the presenter’s tests:

• A disk-usage request took 4.68 seconds with the hook, compared with 8.4 seconds and 9.2 seconds in subsequent runs without it.
• A suspicious-logs request took 18.9 seconds with the hook, compared with 28 seconds without it.

These are examples from the video, not controlled guarantees; response times and results can vary.

Main speakers and sources

• Main speaker: NeuralNine presenter
• Technical components discussed: Hermes agent and the Jev decision model/API from TypeSafe
• Sponsor mentioned: Hostinger, for VPS hosting