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Add multimodal input method in the documentation (#31601)

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Signed-off-by: xiaoming <1259730330@qq.com>
This commit is contained in:
labAxiaoming
2026-01-02 20:43:30 +08:00
committed by GitHub
parent cc410e8644
commit a01f2faedf
2 changed files with 96 additions and 0 deletions
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33
docs/features/multimodal_inputs.md
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@@ -506,6 +506,7 @@ Then, you can use the OpenAI client as follows:
??? code
```python
import os
from openai import OpenAI
openai_api_key = "EMPTY"
@@ -517,8 +518,11 @@ Then, you can use the OpenAI client as follows:
)
# Single-image input inference
# Public image URL for testing remote image processing
image_url = "https://vllm-public-assets.s3.us-west-2.amazonaws.com/vision_model_images/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
# Create chat completion with remote image
chat_response = client.chat.completions.create(
model="microsoft/Phi-3.5-vision-instruct",
messages=[
@@ -542,6 +546,35 @@ Then, you can use the OpenAI client as follows:
)
print("Chat completion output:", chat_response.choices[0].message.content)
# Local image file path (update this to point to your actual image file)
image_file = "/path/to/image.jpg"
# Create chat completion with local image file
# Launch the API server/engine with the --allowed-local-media-path argument.
if os.path.exists(image_file):
chat_completion_from_local_image_url = client.chat.completions.create(
model="microsoft/Phi-3.5-vision-instruct",
messages=[
{
"role": "user",
"content": [
{
"type": "text",
"text": "What’s in this image?",
},
{
"type": "image_url",
"image_url": {"url": f"file://{image_file}"},
},
],
}
],
)
result = chat_completion_from_local_image_url.choices[0].message.content
print("Chat completion output from local image file:\n", result)
else:
print(f"Local image file not found at {image_file}, skipping local file test.")
# Multi-image input inference
image_url_duck = "https://vllm-public-assets.s3.us-west-2.amazonaws.com/multimodal_asset/duck.jpg"
image_url_lion = "https://vllm-public-assets.s3.us-west-2.amazonaws.com/multimodal_asset/lion.jpg"

63
examples/online_serving/openai_chat_completion_client_for_multimodal.py
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@@ -21,6 +21,7 @@ python openai_chat_completion_client_for_multimodal.py --chat-type audio
"""
import base64
import os
import requests
from openai import OpenAI
@@ -51,6 +52,16 @@ def encode_base64_content_from_url(content_url: str) -> str:
return result
def encode_base64_content_from_file(file_path: str) -> str:
"""Encode a local file content to base64 format."""
with open(file_path, "rb") as file:
file_content = file.read()
result = base64.b64encode(file_content).decode("utf-8")
return result
# Text-only inference
def run_text_only(model: str, max_completion_tokens: int) -> None:
chat_completion = client.chat.completions.create(
@@ -67,6 +78,7 @@ def run_text_only(model: str, max_completion_tokens: int) -> None:
def run_single_image(model: str, max_completion_tokens: int) -> None:
## Use image url in the payload
image_url = "https://vllm-public-assets.s3.us-west-2.amazonaws.com/vision_model_images/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
image_file = "/path/to/image.jpg" # local file
chat_completion_from_url = client.chat.completions.create(
messages=[
{
@@ -87,6 +99,30 @@ def run_single_image(model: str, max_completion_tokens: int) -> None:
result = chat_completion_from_url.choices[0].message.content
print("Chat completion output from image url:\n", result)
## Use local image url in the payload
# Launch the API server/engine with the --allowed-local-media-path argument.
if os.path.exists(image_file):
chat_completion_from_local_image_url = client.chat.completions.create(
messages=[
{
"role": "user",
"content": [
{"type": "text", "text": "What's in this image?"},
{
"type": "image_url",
"image_url": {"url": f"file://{image_file}"},
},
],
}
],
model=model,
max_completion_tokens=max_completion_tokens,
)
result = chat_completion_from_local_image_url.choices[0].message.content
print("Chat completion output from local image file:\n", result)
else:
print(f"Local image file not found at {image_file}, skipping local file test.")
## Use base64 encoded image in the payload
image_base64 = encode_base64_content_from_url(image_url)
chat_completion_from_base64 = client.chat.completions.create(
@@ -109,6 +145,33 @@ def run_single_image(model: str, max_completion_tokens: int) -> None:
result = chat_completion_from_base64.choices[0].message.content
print("Chat completion output from base64 encoded image:", result)
## Use base64 encoded local image in the payload
if os.path.exists(image_file):
local_image_base64 = encode_base64_content_from_file(image_file)
chat_completion_from_local_image_base64 = client.chat.completions.create(
messages=[
{
"role": "user",
"content": [
{"type": "text", "text": "What's in this image?"},
{
"type": "image_url",
"image_url": {
"url": f"data:image/jpeg;base64,{local_image_base64}"
},
},
],
}
],
model=model,
max_completion_tokens=max_completion_tokens,
)
result = chat_completion_from_local_image_base64.choices[0].message.content
print("Chat completion output from base64 encoded local image:", result)
else:
print(f"Local image file not found at {image_file}, skipping local file test.")
# Multi-image input inference
def run_multi_image(model: str, max_completion_tokens: int) -> None: