6.1 KiB
6.1 KiB
调用示例
基础与流式
Python
安装 SDK
# 安装最新版本
pip install zai-sdk
# 或指定版本
pip install zai-sdk==0.2.0
验证安装
import zai
print(zai.__version__)
基础调用
from zai import ZhipuAiClient
client = ZhipuAiClient(api_key="") # 填写您自己的 APIKey
response = client.chat.completions.create(
model="glm-4.6v-flash", # 填写需要调用的模型名称
messages=[
{
"content": [
{
"type": "image_url",
"image_url": {
"url": "https://cloudcovert-1305175928.cos.ap-guangzhou.myqcloud.com/%E5%9B%BE%E7%89%87grounding.PNG"
}
},
{
"type": "text",
"text": "Where is the second bottle of beer from the right on the table? Provide coordinates in [[xmin,ymin,xmax,ymax]] format"
}
],
"role": "user"
}
],
thinking={
"type": "enabled"
}
)
print(response.choices[0].message)
流式调用
from zai import ZhipuAiClient
client = ZhipuAiClient(api_key="") # 填写您自己的APIKey
response = client.chat.completions.create(
model="glm-4.6v-flash", # 填写需要调用的模型名称
messages=[
{
"content": [
{
"type": "image_url",
"image_url": {
"url": "https://cloudcovert-1305175928.cos.ap-guangzhou.myqcloud.com/%E5%9B%BE%E7%89%87grounding.PNG"
}
},
{
"type": "text",
"text": "Where is the second bottle of beer from the right on the table? Provide coordinates in [[xmin,ymin,xmax,ymax]] format"
}
],
"role": "user"
}
],
thinking={
"type": "enabled"
},
stream=True
)
for chunk in response:
if chunk.choices[0].delta.reasoning_content:
print(chunk.choices[0].delta.reasoning_content, end='', flush=True)
if chunk.choices[0].delta.content:
print(chunk.choices[0].delta.content, end='', flush=True)
多模态理解
不支持同时理解文件、视频和图像。
Python
安装 SDK
# 安装最新版本
pip install zai-sdk
# 或指定版本
pip install zai-sdk==0.2.0
验证安装
import zai
print(zai.__version__)
图片理解
from zai import ZhipuAiClient
client = ZhipuAiClient(api_key="your-api-key") # 填写您自己的APIKey
response = client.chat.completions.create(
model="glm-4.6v-flash",
messages=[
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": {
"url": "https://cdn.bigmodel.cn/static/logo/register.png"
}
},
{
"type": "image_url",
"image_url": {
"url": "https://cdn.bigmodel.cn/static/logo/api-key.png"
}
},
{
"type": "text",
"text": "What are the pics talk about?"
}
]
}
],
thinking={
"type": "enabled"
}
)
print(response.choices[0].message)
传入 Base64 图片
from zai import ZhipuAiClient
import base64
client = ZhipuAiClient(api_key="your-api-key") # 填写您自己的APIKey
img_path = "your/path/xxx.png"
with open(img_path, "rb") as img_file:
img_base = base64.b64encode(img_file.read()).decode("utf-8")
response = client.chat.completions.create(
model="glm-4.6v-flash",
messages=[
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": {
"url": img_base
}
},
{
"type": "text",
"text": "请描述这个图片"
}
]
}
],
thinking={
"type": "enabled"
}
)
print(response.choices[0].message)
视频理解
from zai import ZhipuAiClient
client = ZhipuAiClient(api_key="your-api-key") # 填写您自己的APIKey
response = client.chat.completions.create(
model="glm-4.6v-flash",
messages=[
{
"role": "user",
"content": [
{
"type": "video_url",
"video_url": {
"url": "https://cdn.bigmodel.cn/agent-demos/lark/113123.mov"
}
},
{
"type": "text",
"text": "What are the video show about?"
}
]
}
],
thinking={
"type": "enabled"
}
)
print(response.choices[0].message)
文件理解
from zai import ZhipuAiClient
client = ZhipuAiClient(api_key="your-api-key") # 填写您自己的APIKey
response = client.chat.completions.create(
model="glm-4.6v-flash",
messages=[
{
"role": "user",
"content": [
{
"type": "file_url",
"file_url": {
"url": "https://cdn.bigmodel.cn/static/demo/demo2.txt"
}
},
{
"type": "file_url",
"file_url": {
"url": "https://cdn.bigmodel.cn/static/demo/demo1.pdf"
}
},
{
"type": "text",
"text": "What are the files show about?"
}
]
}
],
thinking={
"type": "enabled"
}
)
print(response.choices[0].message)