Multimodal

Learn how to process images and audio with LLMs.

Vision

With the vision ability you can have your model take in images and answer questions about them. Within Xinference, this indicates that certain models are capable of processing image inputs when conducting dialogues via the Chat API.

Supported models

The vision ability is supported with the following models in Xinference:

• qwen-vl-chat

• deepseek-vl-chat

• yi-vl-chat

• omnilmm

• internvl-chat

• cogvlm2

• MiniCPM-Llama3-V 2.5

• GLM-4V

• MiniCPM-Llama3-V 2.6

• internvl2

• qwen2-vl-instruct

• llama-3.2-vision

• llama-3.2-vision-instruct

• glm-edge-v

Quickstart

Images are made available to the model in two main ways: by passing a link to the image or by passing the base64 encoded image directly in the request.

Example using OpenAI Client

import openai

client = openai.Client(
    api_key="cannot be empty",
    base_url=f"http://<XINFERENCE_HOST>:<XINFERENCE_PORT>/v1"
)
response = client.chat.completions.create(
    model="<MODEL_UID>",
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "What’s in this image?"},
                {
                    "type": "image_url",
                    "image_url": {
                        "url": "http://i.epochtimes.com/assets/uploads/2020/07/shutterstock_675595789-600x400.jpg",
                    },
                },
            ],
        }
    ],
)
print(response.choices[0])

Uploading base 64 encoded images

import openai
import base64

# Function to encode the image
def encode_image(image_path):
with open(image_path, "rb") as image_file:
    return base64.b64encode(image_file.read()).decode('utf-8')

# Path to your image
image_path = "path_to_your_image.jpg"

# Getting the base64 string
b64_img = encode_image(image_path)

client = openai.Client(
    api_key="cannot be empty",
    base_url=f"http://<XINFERENCE_HOST>:<XINFERENCE_PORT>/v1"
)
response = client.chat.completions.create(
    model="<MODEL_UID>",
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "What’s in this image?"},
                {
                    "type": "image_url",
                    "image_url": {
                        "url": f"data:image/jpeg;base64,{b64_img}",
                    },
                },
            ],
        }
    ],
)
print(response.choices[0])

You can find more examples of vision ability in the tutorial notebook:

Qwen VL Chat

Learn vision ability from a example using qwen-vl-chat

https://github.com/xorbitsai/inference/blob/main/examples/chat_vl.ipynb

Audio

With the audio ability you can have your model take in audio and performing audio analysis or direct textual responses with regard to speech instructions. Within Xinference, this indicates that certain models are capable of processing audio inputs when conducting dialogues via the Chat API.

Supported models

The audio ability is supported with the following models in Xinference:

• qwen2-audio-instruct

Quickstart

Audios are made available to the model in two main ways: by passing a link to the image or by passing the audio url directly in the request.

Chat with audio

from xinference.client import Client

client = Client("http://<XINFERENCE_HOST>:<XINFERENCE_PORT>")
model = client.get_model(<MODEL_UID>)

messages = [
    {"role": "system", "content": "You are a helpful assistant."},
    {
        "role": "user",
        "content": [
            {
                "type": "audio",
                "audio_url": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen2-Audio/audio/glass-breaking-151256.mp3",
            },
            {"type": "text", "text": "What's that sound?"},
        ],
    },
    {"role": "assistant", "content": "It is the sound of glass shattering."},
    {
        "role": "user",
        "content": [
            {"type": "text", "text": "What can you do when you hear that?"},
        ],
    },
    {
        "role": "assistant",
        "content": "Stay alert and cautious, and check if anyone is hurt or if there is any damage to property.",
    },
    {
        "role": "user",
        "content": [
            {
                "type": "audio",
                "audio_url": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen2-Audio/audio/1272-128104-0000.flac",
            },
            {"type": "text", "text": "What does the person say?"},
        ],
    },
]
print(model.chat(messages))