vllm/examples/openai_vision_api_client.py

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"""An example showing how to use vLLM to serve VLMs.
Launch the vLLM server with the following command:
vllm serve llava-hf/llava-1.5-7b-hf --chat-template template_llava.jinja
"""
import base64
import requests
from openai import OpenAI
# Modify OpenAI's API key and API base to use vLLM's API server.
openai_api_key = "EMPTY"
openai_api_base = "http://localhost:8000/v1"
client = OpenAI(
# defaults to os.environ.get("OPENAI_API_KEY")
api_key=openai_api_key,
base_url=openai_api_base,
)
models = client.models.list()
model = models.data[0].id
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"
# Use image url in the payload
chat_completion_from_url = client.chat.completions.create(
messages=[{
"role":
"user",
"content": [
{
"type": "text",
"text": "Whats in this image?"
},
{
"type": "image_url",
"image_url": {
"url": image_url
},
},
],
}],
model=model,
max_tokens=64,
)
result = chat_completion_from_url.choices[0].message.content
print(f"Chat completion output:{result}")
# Use base64 encoded image in the payload
def encode_image_base64_from_url(image_url: str) -> str:
"""Encode an image retrieved from a remote url to base64 format."""
with requests.get(image_url) as response:
response.raise_for_status()
result = base64.b64encode(response.content).decode('utf-8')
return result
image_base64 = encode_image_base64_from_url(image_url=image_url)
chat_completion_from_base64 = client.chat.completions.create(
messages=[{
"role":
"user",
"content": [
{
"type": "text",
"text": "Whats in this image?"
},
{
"type": "image_url",
"image_url": {
"url": f"data:image/jpeg;base64,{image_base64}"
},
},
],
}],
model=model,
max_tokens=64,
)
result = chat_completion_from_base64.choices[0].message.content
print(f"Chat completion output:{result}")