简体中文
/chat/completions
detail
high
low
auto
{ "role": "user", "content": [ { "type": "image_url", "image_url": { "url": "https://example.com/image.png", "detail": "high" } }, { "type": "text", "text": "请描述图片中的场景。" } ] }
{ "role": "user", "content": [ { "type": "image_url", "image_url": { "url": "data:image/jpeg;base64,{base64_image}", "detail": "low" } }, { "type": "text", "text": "图片中有哪些文字内容?" } ] }
import base64 from PIL import Image import io def image_to_base64(image_path): with Image.open(image_path) as img: buffered = io.BytesIO() img.save(buffered, format="JPEG") return base64.b64encode(buffered.getvalue()).decode('utf-8') base64_image = image_to_base64("path/to/your/image.jpg")
{ "role": "user", "content": [ { "type": "image_url", "image_url": { "url": "https://example.com/image1.png" } }, { "type": "image_url", "image_url": { "url": "data:image/jpeg;base64,{base64_image}" } }, { "type": "text", "text": "比较这两张图片的共同特征。" } ] }
from openai import OpenAI client = OpenAI(api_key="YOUR_KEY", base_url="https://api.ppinfra.com/v3/openai") response = client.chat.completions.create( model="qwen/qwen2.5-vl-72b-instruct", messages=[ { "role": "user", "content": [ {"type": "image_url", "image_url": {"url": "https://example.com/cityscape.jpg"}}, {"type": "text", "text": "描述图片中的主要建筑物。"} ] } ], stream=True ) for chunk in response: print(chunk.choices[0].delta.content or "", end="", flush=True)
response = client.chat.completions.create( model="qwen/qwen2.5-vl-72b-instruct", messages=[ { "role": "user", "content": [ {"type": "image_url", "image_url": {"url": "https://example.com/product1.jpg"}}, {"type": "image_url", "image_url": {"url": "https://example.com/product2.jpg"}}, {"type": "text", "text": "请对比一下这两个产品的主要区别。"} ] } ], stream=True ) for chunk in response: print(chunk.choices[0].delta.content or "", end="", flush=True)