gpt-vision.md

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LocalAI supports understanding images by using LLaVA, and implements the GPT Vision API from OpenAI.

Usage

OpenAI docs: https://platform.openai.com/docs/guides/vision

To let LocalAI understand and reply with what sees in the image, use the /v1/chat/completions endpoint, for example with curl:

curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
     "model": "llava",
     "messages": [{"role": "user", "content": [{"type":"text", "text": "What is in the 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" }}], "temperature": 0.9}]}'

Grammars and function tools can be used as well in conjunction with vision APIs:

 curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
     "model": "llava", "grammar": "root ::= (\"yes\" | \"no\")",
     "messages": [{"role": "user", "content": [{"type":"text", "text": "Is there some grass in the 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" }}], "temperature": 0.9}]}'

Setup

All-in-One images have already shipped the llava model as gpt-4-vision-preview, so no setup is needed in this case.

To setup the LLaVa models, follow the full example in the configuration examples.