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How to classify support messages with a decision model with PS5 LM

Send a message to the PS5 /v1/systemone API to get typed intent and yes-or-no answers.

Authorization notice. PS5 LM is dual-use. Only use it on software, sites and systems you own or have explicit permission to test.

Who it is forA support or operations person who wants fast, local intent and tone labels for incoming customer messages.

The problemSorting customer messages by intent and mood by hand is slow, and sending them to a cloud model may not be acceptable.

The outcomeThe decision model returns a typed choice for intent and a yes-or-no answer for anger, in a fraction of a second, from the PS5 on your network.

What you need first

  • A PS5 on firmware 7.00 to 13.60 that is jailbroken
  • The kstuff-lite, etaHEN and ShadowMountPlus payloads loaded on the console
  • The ps5lm-app zip from the latest GitHub release
  • A laptop or phone on the same network as the PS5, and an FTP client (ftpsrv on port 2121 is recommended)

Steps

  1. Load d1 Omni 600M from the Suggested list in Models on the PS5.
  2. Wait for Home to say Ready, then send the request below with your own state and questions, replacing http:// with the PS5 address and port 8081.
  3. Read the typed decision and probabilities in the response, and check that the intent matches the message.
  4. Send the same message to the TV's chat view to confirm the request was logged on the console.

Prompt for your agent

Using the cobanov/PS5LM repo, send a POST to http://<PS5-IP>:8081/v1/systemone with a customer message as state and an intent choice question. Expected output is a typed decision with probabilities, and verify that the chosen intent is one of the criteria you supplied.

Caveat. The decision endpoint is described in the README as matching Ollaya's API, and the README does not give accuracy figures for any model.

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