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Skill

update-model

update models on LiteLLM proxy

Published by LiteLLM Updated Jul 14
Covers Configuration LLM AI Infrastructure

Description

Update an existing model on a live LiteLLM proxy. Ask for the model_id and what to change (API key, base URL, etc.), then call POST /model/update.

SKILL.md

Update Model

Update an existing model's configuration on a live LiteLLM proxy.

Setup

LITELLM_BASE_URL  — e.g. https://my-proxy.example.com
LITELLM_API_KEY   — proxy admin key

Ask the user

  1. model_id (required) — if they don't have it, list models first:
    curl -s "$BASE/model/info" -H "Authorization: Bearer $KEY" | python3 -c "
    import sys,json
    for m in json.load(sys.stdin).get('data',[]):
      print(m['model_info']['id'], m['model_name'])
    "
    
  2. What to change — any combination of:
    • api_key (rotate the credential)
    • api_base (change endpoint)
    • api_version (Azure)
    • model (underlying model string, e.g. azure/new-deployment)

Run

curl -s -X POST "$BASE/model/update" \
  -H "Authorization: Bearer $KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model_info": {"id": "<model_id>"},
    "litellm_params": {
      "api_key": "<new_key>",
      "api_base": "<new_base>"
    }
  }'

Only include litellm_params fields being changed.

Output

Confirm the model was updated. Offer to run a test call to verify it still routes correctly.

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