智谱开放平台大模型接口 Python SDK（Big Model API SDK in Python），让开发者更便捷的调用智谱开放API
正式的 Python (3.8, 3.9, 3.10, 3.11, 3.12)
zhipuai 软件包及其依赖pip install zhipuai
sdk支持通过环境变量配置APIKey
ZHIPUAI_API_KEY: 您的APIKey
ZHIPUAI_BASE_URL: 您的API地址
from zhipuai import ZhipuAI
client = ZhipuAI(
api_key="", # 填写您的 APIKey
)
在core/_http_client.py中，可以配置网络链接的超时时间，重试次数，限制等参数
# 通过 `Timeout` 控制接口`connect` 和 `read` 超时时间，默认为`timeout=300.0, connect=8.0`
ZHIPUAI_DEFAULT_TIMEOUT = httpx.Timeout(timeout=300.0, connect=8.0)
# 通过 `retry` 参数控制重试次数，默认为3次
ZHIPUAI_DEFAULT_MAX_RETRIES = 3
# 通过 `Limits` 控制最大连接数和保持连接数，默认为`max_connections=50, max_keepalive_connections=10`
ZHIPUAI_DEFAULT_LIMITS = httpx.Limits(max_connections=50, max_keepalive_connections=10)
同样在ZhipuAI入参中可以配置
client = ZhipuAI(
timeout= httpx.Timeout(timeout=300.0, connect=8.0),
max_retries=3,
)
from zhipuai import ZhipuAI
client = ZhipuAI() # 填写您自己的APIKey
response = client.chat.completions.create(
model="glm-4", # 填写需要调用的模型名称
messages=[
{"role": "user", "content": "作为一名营销专家，请为我的产品创作一个吸引人的slogan"},
{"role": "assistant", "content": "当然，为了创作一个吸引人的slogan，请告诉我一些关于您产品的信息"},
{"role": "user", "content": "智谱AI开放平台"},
{"role": "assistant", "content": "智启未来，谱绘无限一智谱AI，让创新触手可及!"},
{"role": "user", "content": "创造一个更精准、吸引人的slogan"}
],
tools=[
{
"type": "web_search",
"web_search": {
"search_query": "帮我看看清华的升学率",
"search_result": True,
}
}
],
# 拓展参数
extra_body={"temperature": 0.5, "max_tokens": 50},
)
print(response)
from zhipuai import ZhipuAI
client = ZhipuAI(api_key="") # 请填写您自己的APIKey
response = client.chat.completions.create(
model="", # 填写需要调用的模型名称
messages=[
{"role": "system", "content": "你是一个人工智能助手，你叫叫chatGLM"},
{"role": "user", "content": "你好！你叫什么名字"},
],
stream=True,
)
for chunk in response:
print(chunk.choices[0].delta)
# Function to encode the image
def encode_image(image_path):
import base64
with open(image_path, "rb") as image_file:
return base64.b64encode(image_file.read()).decode('utf-8')
def test_completions_vis():
client = ZhipuAI() # 填写您自己的APIKey
base64_image = encode_image("img/MetaGLM.png")
response = client.chat.completions.create(
model="glm-4v", # 填写需要调用的模型名称
extra_body={"temperature": 0.5, "max_tokens": 50},
messages=[
{
"role": "user",
"content": [
{
"type": "text",
"text": "图里有什么"
},
# {
# "type": "image_url",
# "image_url": {
# "url": "https://img1.baidu.com/it/u=1369931113,3388870256&fm=253&app=138&size=w931&n=0&f=JPEG&fmt=auto?sec=1703696400&t=f3028c7a1dca43a080aeb8239f09cc2f"
# }
# },
{
"type": "image_url",
"image_url": {
"url": f"data:image/jpeg;base64,{base64_image}"
}
}
]
}
]
)
print(response)
test_completions_vis()
提供能力的模型名称，请从官网获取
def test_completions_charglm():
client = ZhipuAI() # 请填写您自己的APIKey
response = client.chat.completions.create(
model="charglm-3", # 填写需要调用的模型名称
messages=[
{
"role": "user",
"content": "请问你在做什么"
}
],
meta={
"user_info": "我是陆星辰，是一个男性，是一位知名导演，也是苏梦远的合作导演。我擅长拍摄音乐题材的电影。苏梦远对我的态度是尊敬的，并视我为良师益友。",
"bot_info": "苏梦远，本名苏远心，是一位当红的国内女歌手及演员。在参加选秀节目后，凭借独特的嗓音及出众的舞台魅力迅速成名，进入娱乐圈。她外表美丽动人，但真正的魅力在于她的才华和勤奋。苏梦远是音乐学院毕业的优秀生，善于创作，拥有多首热门原创歌曲。除了音乐方面的成就，她还热衷于慈善事业，积极参加公益活动，用实际行动传递正能量。在工作中，她对待工作非常敬业，拍戏时总是全身心投入角色，赢得了业内人士的赞誉和粉丝的喜爱。虽然在娱乐圈，但她始终保持低调、谦逊的态度，深得同行尊重。在表达时，苏梦远喜欢使用“我们”和“一起”，强调团队精神。",
"bot_name": "苏梦远",
"user_name": "陆星辰"
},
)
print(response)
test_completions_charglm()
def test_assistant() -> None:
client = ZhipuAI() # 填写您自己的APIKey
generate = client.assistant.conversation(
assistant_id="659e54b1b8006379b4b2abd6",
model="glm-4-assistant",
messages=[
{
"role": "user",
"content": [{
"type": "text",
"text": "帮我搜索下智谱的cogvideox发布时间"
}]
}
],
stream=True,
attachments=None,
metadata=None,
request_id="request_1790291013237211136",
user_id="12345678"
)
for assistant in generate:
print(assistant)
test_assistant()
def test_videos():
client = ZhipuAI() # 填写您自己的APIKey
try:
response = client.videos.generations(
model="cogvideo",
prompt="一个开船的人",
user_id="1212222"
)
print(response)
test_videos()
模块定义了一些统一的参数返回(例如:响应错误，网络超时错误)
业务定义了http错误的响应类 (在接口返回，40x或者50x), 会抛出 zhipuai.APIStatusError ,包含 status_code 和 response 属性. 它们都是继承 zhipuai.APIStatusError.
其它Exception，属于不可预知的错误
from zhipuai import ZhipuAI
import zhipuai
client = ZhipuAI() # 填写您自己的APIKey
try:
response = client.chat.completions.create(
model="glm-4", # 填写需要调用的模型名称
messages=[
{"role": "user", "content": "作为一名营销专家，请为我的产品创作一个吸引人的slogan"},
{"role": "assistant", "content": "当然，为了创作一个吸引人的slogan，请告诉我一些关于您产品的信息"},
{"role": "user", "content": "智谱AI开放平台"},
{"role": "assistant", "content": "智启未来，谱绘无限一智谱AI，让创新触手可及!"},
{"role": "user", "content": "创造一个更精准、吸引人的slogan"}
]
)
print(response)
except zhipuai.APIStatusError as err:
print(err)
except zhipuai.APITimeoutError as err:
print(err)
Error codes are as followed:
| Status Code | Error Type |
|---|---|
| 400 | APIRequestFailedError |
| 401 | APIAuthenticationError |
| 429 | APIReachLimitError |
| 500 | APIInternalError |
| 503 | APIServerFlowExceedError |
| N/A | APIStatusError |
2024-8-12
2024-7-25
2024-7-12
2024-5-20
python3.12 的依赖问题，2024-4-29
python3.7 的代码适配问题，retry 参数控制重试次数，默认为3次Timeout 控制接口connect 和 read 超时时间，默认为timeout=300.0, connect=8.0model="charglm-3", meta参数支持2024-4-23
pydantic<3,>=1.9.0 的代码，top_p:1,temperture:0(do_sample重写false，参数top_p temperture不生效)data:image/jpeg;base64兼容FAQs
A SDK library for accessing big model apis from ZhipuAI
We found that zhipuai demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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