add-model

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Add a new model to a live LiteLLM proxy. Walks the user through picking a provider, entering the deployment name and credentials, calls POST /model/new, then test-calls the model to confirm it routes correctly. Use when the user wants to add, register, deploy, or configure a new model on a LiteLLM proxy instance.

BerriAI By BerriAI schedule Updated 4/15/2026

name: add-model description: "Add a new model to a live LiteLLM proxy. Walks the user through picking a provider, entering the deployment name and credentials, calls POST /model/new, then test-calls the model to confirm it routes correctly. Use when the user wants to add, register, deploy, or configure a new model on a LiteLLM proxy instance." license: MIT compatibility: Requires curl. metadata: author: BerriAI version: "1.0" allowed-tools: Bash(curl:*)

Add Model

Add a new LLM to a live LiteLLM proxy.

Setup

Ask for these if not already known:

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

API reference: https://litellm.vercel.app/docs/proxy/model_management

Ask the user

  1. Public model name — what callers will send in "model": "..." (e.g. gpt-4o, my-claude, llama3)
  2. Provider — pick from the table below
  3. Credentials — whatever that provider needs

Provider table

Provider litellm_params.model Extra params
OpenAI openai/gpt-4o api_key
Azure OpenAI azure/<deployment-name> api_key, api_base, api_version
Anthropic anthropic/claude-3-5-sonnet-20241022 api_key
AWS Bedrock bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0 AWS creds via env
Google Vertex vertex_ai/gemini-1.5-pro vertex_project, vertex_location
Ollama ollama/llama3 api_base (e.g. http://localhost:11434)
Groq groq/llama-3.3-70b-versatile api_key
Together AI together_ai/meta-llama/Llama-3-70b api_key
Mistral mistral/mistral-large-latest api_key

Full list: https://docs.litellm.ai/docs/providers

Run

curl -s -X POST "$BASE/model/new" \
  -H "Authorization: Bearer $KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model_name": "<public-name>",
    "litellm_params": {
      "model": "<provider/deployment>",
      "api_key": "<key>",
      "api_base": "<base_if_needed>",
      "api_version": "<version_if_azure>"
    }
  }'

Test it

After adding, verify it routes:

curl -s -X POST "$BASE/chat/completions" \
  -H "Authorization: Bearer $KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "<public-name>",
    "messages": [{"role": "user", "content": "say hi"}],
    "max_tokens": 10
  }'

Output

Show model_id from the response — needed to update or delete the model later. Report pass/fail from the test call.

Install via CLI
npx skills add https://github.com/BerriAI/litellm-skills --skill add-model
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