Using Vision Models

Quick Start

Example passing images to a model

LiteLLMPython SDK

import os 
from litellm import completion

os.environ["OPENAI_API_KEY"] = "your-api-key"

# openai call
response = completion(
    model = "gpt-4-vision-preview", 
    messages=[
        {
            "role": "user",
            "content": [
                            {
                                "type": "text",
                                "text": "What’s in this image?"
                            },
                            {
                                "type": "image_url",
                                "image_url": {
                                "url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
                                }
                            }
                        ]
        }
    ],
)

LiteLLM Proxy Server

1. Define vision models on config.yaml

model_list:
  - model_name: gpt-4-vision-preview # OpenAI gpt-4-vision-preview
    litellm_params:
      model: openai/gpt-4-vision-preview
      api_key: os.environ/OPENAI_API_KEY
  - model_name: llava-hf          # Custom OpenAI compatible model
    litellm_params:
      model: openai/llava-hf/llava-v1.6-vicuna-7b-hf
      api_base: http://localhost:8000
      api_key: fake-key
    model_info:
      supports_vision: True        # set supports_vision to True so /model/info returns this attribute as True

2. Run proxy server

litellm --config config.yaml

3. Test it using the OpenAI Python SDK

import os 
from openai import OpenAI

client = OpenAI(
    api_key="sk-1234", # your litellm proxy api key
)

response = client.chat.completions.create(
    model = "gpt-4-vision-preview",  # use model="llava-hf" to test your custom OpenAI endpoint
    messages=[
        {
            "role": "user",
            "content": [
                            {
                                "type": "text",
                                "text": "What’s in this image?"
                            },
                            {
                                "type": "image_url",
                                "image_url": {
                                "url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
                                }
                            }
                        ]
        }
    ],
)

Checking if a model supports vision

LiteLLM Python SDK

Use litellm.supports_vision(model="") -> returns True if model supports vision and False if not

assert litellm.supports_vision(model="gpt-4-vision-preview") == True
assert litellm.supports_vision(model="gemini-1.0-pro-vision") == True
assert litellm.supports_vision(model="gpt-3.5-turbo") == False

LiteLLM Proxy Server

1. Define vision models on config.yaml

model_list:
  - model_name: gpt-4-vision-preview # OpenAI gpt-4-vision-preview
    litellm_params:
      model: openai/gpt-4-vision-preview
      api_key: os.environ/OPENAI_API_KEY
  - model_name: llava-hf          # Custom OpenAI compatible model
    litellm_params:
      model: openai/llava-hf/llava-v1.6-vicuna-7b-hf
      api_base: http://localhost:8000
      api_key: fake-key
    model_info:
      supports_vision: True        # set supports_vision to True so /model/info returns this attribute as True

2. Run proxy server

litellm --config config.yaml

3. Call /model_group/info to check if your model supports vision

curl -X 'GET' \
  'http://localhost:4000/model_group/info' \
  -H 'accept: application/json' \
  -H 'x-api-key: sk-1234'

Expected Response

{
  "data": [
    {
      "model_group": "gpt-4-vision-preview",
      "providers": ["openai"],
      "max_input_tokens": 128000,
      "max_output_tokens": 4096,
      "mode": "chat",
      "supports_vision": true, # 👈 supports_vision is true
      "supports_function_calling": false
    },
    {
      "model_group": "llava-hf",
      "providers": ["openai"],
      "max_input_tokens": null,
      "max_output_tokens": null,
      "mode": null,
      "supports_vision": true, # 👈 supports_vision is true
      "supports_function_calling": false
    }
  ]
}