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[Misc][Doc] Add Example of using OpenAI Server with VLM (#5832)
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@ -130,6 +130,8 @@ To consume the server, you can use the OpenAI client like in the example below:
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)
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print("Chat response:", chat_response)
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A full code example can be found in `examples/openai_vision_api_client.py <https://github.com/vllm-project/vllm/blob/main/examples/openai_vision_api_client.py>`_.
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.. note::
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By default, the timeout for fetching images through http url is ``5`` seconds. You can override this by setting the environment variable:
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90
examples/openai_vision_api_client.py
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90
examples/openai_vision_api_client.py
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@ -0,0 +1,90 @@
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"""An example showing how to use vLLM to serve VLMs.
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Launch the vLLM server with the following command:
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python -m vllm.entrypoints.openai.api_server \
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--model llava-hf/llava-1.5-7b-hf \
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--image-input-type pixel_values \
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--image-token-id 32000 \
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--image-input-shape 1,3,336,336 \
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--image-feature-size 576 \
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--chat-template template_llava.jinja
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"""
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import base64
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import requests
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from openai import OpenAI
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# Modify OpenAI's API key and API base to use vLLM's API server.
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openai_api_key = "EMPTY"
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openai_api_base = "http://localhost:8000/v1"
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client = OpenAI(
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# defaults to os.environ.get("OPENAI_API_KEY")
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api_key=openai_api_key,
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base_url=openai_api_base,
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)
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models = client.models.list()
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model = models.data[0].id
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image_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"
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# Use image url in the payload
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chat_completion_from_url = client.chat.completions.create(
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messages=[{
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"role":
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"user",
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"content": [
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{
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"type": "text",
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"text": "What’s in this image?"
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},
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{
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"type": "image_url",
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"image_url": {
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"url": image_url
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},
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},
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],
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}],
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model=model,
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)
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result = chat_completion_from_url.choices[0].message.content
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print(f"Chat completion output:{result}")
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# Use base64 encoded image in the payload
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def encode_image_base64_from_url(image_url: str) -> str:
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"""Encode an image retrieved from a remote url to base64 format."""
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with requests.get(image_url) as response:
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response.raise_for_status()
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result = base64.b64encode(response.content).decode('utf-8')
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return result
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image_base64 = encode_image_base64_from_url(image_url=image_url)
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chat_completion_from_base64 = client.chat.completions.create(
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messages=[{
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"role":
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"user",
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"content": [
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{
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"type": "text",
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"text": "What’s in this image?"
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},
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{
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"type": "image_url",
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"image_url": {
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"url": f"data:image/jpeg;base64,{image_base64}"
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},
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},
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],
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}],
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model=model,
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)
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result = chat_completion_from_base64.choices[0].message.content
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print(f"Chat completion output:{result}")
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@ -1,6 +1,7 @@
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import base64
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from io import BytesIO
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from typing import Optional, Union
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from urllib.parse import urlparse
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import aiohttp
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from PIL import Image
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@ -28,6 +29,10 @@ class ImageFetchAiohttp:
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"""Load PIL image from a url or base64 encoded openai GPT4V format"""
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if image_url.startswith('http'):
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parsed_url = urlparse(image_url)
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if parsed_url.scheme not in ["http", "https"]:
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raise ValueError("Invalid 'image_url': A valid 'image_url' "
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"must have scheme 'http' or 'https'.")
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# Avoid circular import
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from vllm import __version__ as VLLM_VERSION
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@ -44,8 +49,9 @@ class ImageFetchAiohttp:
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image = load_image_from_base64(image_url.split(',', 1)[1])
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else:
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raise ValueError("Invalid image url: A valid image url must start "
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"with either 'data:image' or 'http'.")
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raise ValueError(
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"Invalid 'image_url': A valid 'image_url' must start "
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"with either 'data:image' or 'http'.")
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return image
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@ -56,7 +62,7 @@ async def async_get_and_parse_image(image_url: str) -> ImagePixelData:
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def encode_image_base64(image: Image.Image, format: str = 'JPEG') -> str:
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"""encode image to base64 format."""
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"""Encode a pillow image to base64 format."""
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buffered = BytesIO()
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if format == 'JPEG':
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