Python SDK 与代码集成指南

pip install openai

key='sk-xxxx'


from openai import OpenAI

client = OpenAI(
    base_url="https://socialvision.tisyk.xyz/v1",
    api_key=key
)

response = client.chat.completions.create(
  model="gpt-4o",
  messages=[
    {"role": "user", "content": "你好?"},

  ],
  timeout=100,

)
print(response)

import openai
import time

# 打印openai的版本
print(openai.__version__)

client = openai.OpenAI(
    base_url="https://socialvision.tisyk.xyz/v1",
    api_key="sk-xxx"
)

messages = [
    {"role": "system", "content": "You are a helpful assistant."}
]

while True:
    user_input = input("You: ")
    messages.append({"role": "user", "content": user_input})

    response = client.chat.completions.create(
        model="gpt-4o",
        messages=messages,
        temperature=1
    )

    assistant_response = response.choices[0].message.content
    print(f"Assistant: {assistant_response}")

    messages.append({"role": "assistant", "content": assistant_response})
    time.sleep(1)

from llama_index.llms.openai import OpenAI

llm = OpenAI(
    model="gpt-3.5-turbo",
    api_key="sk-xxxxx",
    api_base="https://socialvision.tisyk.xyz/v1")
ret=llm.complete("Paul Graham is ")
print(ret)

from openai import OpenAI
client = OpenAI(
    base_url="https://socialvision.tisyk.xyz/v1",
    api_key=key
)

response = client.images.generate(
  model="dall-e-3",
  prompt="a white siamese cat",
  size="1024x1024",
  quality="standard",
  n=1,
)

image_url = response.data[0].url

from openai import OpenAI
client = OpenAI(
    base_url="https://socialvision.tisyk.xyz/v1",
    api_key=key
)

response = client.images.edit((
  model="dall-e-2",
  image=open("sunlit_lounge.png", "rb"),
  mask=open("mask.png", "rb"),
  prompt="A sunlit indoor lounge area with a pool containing a flamingo",
  n=1,
  size="1024x1024"
)
image_url = response.data[0].url

from openai import OpenAI
client = OpenAI(
    base_url="https://socialvision.tisyk.xyz/v1",
    api_key=key
)

response = client.images.create_variation(
  model="dall-e-2",
  image=open("corgi_and_cat_paw.png", "rb"),
  n=1,
  size="1024x1024"
)

image_url = response.data[0].url

I NEED to test how the tool works with extremely simple prompts. 
DO NOT add any detail, just use it AS-IS:

from openai import OpenAI
client = OpenAI(
    base_url="https://socialvision.tisyk.xyz/v1",
    api_key=key
)

response = client.embeddings.create(
    input="Your text string goes here",
    model="text-embedding-3-small"
)

print(response.data[0].embedding)

{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "index": 0,
      "embedding": [
        -0.006929283495992422,
        -0.005336422007530928,
        // ... 更多数值
      ],
    }
  ],
  "model": "text-embedding-3-small",
  "usage": {
    "prompt_tokens": 5,
    "total_tokens": 5
  }
}

from openai import OpenAI
client = OpenAI(
    base_url="https://socialvision.tisyk.xyz/v1",
    api_key=key
)

def get_embedding(text, model="text-embedding-3-small"):
   text = text.replace("\n", " ")
   return client.embeddings.create(input = [text], model=model).data[0].embedding

# 处理数据框
df['ada_embedding'] = df.combined.apply(lambda x: get_embedding(x, model='text-embedding-3-small'))
df.to_csv('output/embedded_1k_reviews.csv', index=False)

# 加载保存的嵌入
import pandas as pd
import numpy as np

df = pd.read_csv('output/embedded_1k_reviews.csv')
df['ada_embedding'] = df.ada_embedding.apply(eval).apply(np.array)

import openai

# 设置 API 基础地址和密钥
openai.api_base = "https://socialvision.tisyk.xyz/v1"
openai.api_key = "sk-xxxxxxxxx"

OPENAI_API_BASE=https://socialvision.tisyk.xyz/v1
OPENAI_API_KEY=sk-xxxxx

from openai import OpenAI

# 初始化客户端
client = OpenAI(
    base_url="https://socialvision.tisyk.xyz/v1",
    api_key='您的API KEY',
    timeout=120
)

# 创建聊天完成
response = client.chat.completions.create(
  model="gpt-4o",
  messages=[
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": "Who won the world series in 2020?"},
    {"role": "assistant", "content": "The Los Angeles Dodgers won the World Series in 2020."},
    {"role": "user", "content": "Where was it played?"}
  ]
)
print(response)

#response格式

response = client.responses.create(
    model="gpt-5",
    input="Write a one-sentence bedtime story about a unicorn."
)

print(response.output_text)

import requests
import json

url = "https://socialvision.tisyk.xyz/v1/chat/completions"

payload = json.dumps({
   "model": "o1-preview",
   "messages": [
      {
         "role": "user",
         "content": "写一个小情书"
      }
   ],
   "stream": True
})
headers = {
   'Accept': 'text/event-stream',
   'Authorization': 'Bearer 你的key',
   'Content-Type': 'application/json'
}

response = requests.request("POST", url, headers=headers, data=payload, stream=True)

for line in response.iter_lines():
    if line:
        # 跳过空行
        line = line.decode('utf-8')
        if line.startswith('data: '):
            if line == 'data: [DONE]':
                break
            # 解析JSON数据
            data = json.loads(line[6:])  # 去掉 "data: " 前缀
            if 'choices' in data and len(data['choices']) > 0:
                delta = data['choices'][0].get('delta', {})
                if 'content' in delta:
                    print(delta['content'], end='', flush=True)

pip install langchain_openai
pip install langchain

#新版本langchina
from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
    openai_api_base="https://socialvision.tisyk.xyz/v1",
    openai_api_key="sk-xxxxx"
)

res = llm.invoke("hello")
print(res.content)


#老版本langchina  通过设置环境变量的形式设置中转地址
$env:OPENAI_BASE_URL="https://socialvision.tisyk.xyz/v1"
$env:OPENAI_API_KEY="sk-xxxxx"