SDK 参考指南

OpenAI SDK 相容性

BazaarLink 与 OpenAI Python 和 Node.js SDK 完全相容。只需两项更改：

之前（直接使用 OpenAI）

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from openai import OpenAI

client = OpenAI(
    api_key="sk-..."
)

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

之后（使用 BazaarLink）

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from openai import OpenAI

client = OpenAI(
    base_url="https://bazaarlink.ai/api/v1",
    api_key="sk-bl-YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="openai/gpt-4o",  # add provider/
    messages=[...]
)

就是这样！

所有其他功能 — 串流、工具呼叫、结构化输出、非同步 — 完全相同。唯一的更改是 base_url、api_key，以及在模型 ID 前加上供应商前缀。

Python

安装

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pip install openai

同步

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from openai import OpenAI

client = OpenAI(
    base_url="https://bazaarlink.ai/api/v1",
    api_key="sk-bl-YOUR_API_KEY",
)

response = client.chat.completions.create(
    model="openai/gpt-4o",
    messages=[{"role": "user", "content": "Hello!"}],
)

print(response.choices[0].message.content)

非同步

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import asyncio
from openai import AsyncOpenAI

client = AsyncOpenAI(
    base_url="https://bazaarlink.ai/api/v1",
    api_key="sk-bl-YOUR_API_KEY",
)

async def main():
    response = await client.chat.completions.create(
        model="anthropic/claude-sonnet-4.6",
        messages=[{"role": "user", "content": "Hello async world!"}],
    )
    print(response.choices[0].message.content)

asyncio.run(main())

非同步串流

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async def stream_chat():
    stream = await client.chat.completions.create(
        model="deepseek/deepseek-chat",
        messages=[{"role": "user", "content": "Tell me a story"}],
        stream=True,
    )
    async for chunk in stream:
        content = chunk.choices[0].delta.content
        if content:
            print(content, end="", flush=True)

asyncio.run(stream_chat())

TypeScript / Node.js

安装

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npm install openai

基本用法

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import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://bazaarlink.ai/api/v1",
  apiKey: process.env.BAZAARLINK_API_KEY,
});

async function chat(message: string): Promise<string> {
  const response = await client.chat.completions.create({
    model: "openai/gpt-4o",
    messages: [{ role: "user", content: message }],
  });
  return response.choices[0].message.content ?? "";
}

串流

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const stream = await client.chat.completions.create({
  model: "openai/gpt-4o",
  messages: [{ role: "user", content: "Tell me a story" }],
  stream: true,
});

for await (const chunk of stream) {
  process.stdout.write(chunk.choices[0]?.delta?.content ?? "");
}

LangChain

透过设定 OpenAI 相容的 base URL，在 LangChain 中使用 BazaarLink。

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from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
    base_url="https://bazaarlink.ai/api/v1",
    api_key="sk-bl-YOUR_API_KEY",
    model="anthropic/claude-sonnet-4.6",
)

response = llm.invoke("Explain BazaarLink in one sentence.")
print(response.content)

LlamaIndex

在 LlamaIndex RAG 管线中使用 BazaarLink。LlamaIndex 支援 OpenAI 相容的 base URL，更改两个参数即可。

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from llama_index.llms.openai import OpenAI
from llama_index.core import Settings

Settings.llm = OpenAI(
    model="openai/gpt-4o",
    api_base="https://bazaarlink.ai/api/v1",
    api_key="sk-bl-YOUR_API_KEY",
)

# Now use LlamaIndex normally — it calls BazaarLink
from llama_index.core import VectorStoreIndex, SimpleDirectoryReader

documents = SimpleDirectoryReader("./docs").load_data()
index = VectorStoreIndex.from_documents(documents)
query_engine = index.as_query_engine()
response = query_engine.query("What is this documentation about?")
print(response)

Vercel AI SDK

在 Next.js 应用中将 Vercel AI SDK 与 BazaarLink 整合。支援串流、工具呼叫、结构化输出。

安装

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npm install ai @ai-sdk/openai

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import { createOpenAI } from "@ai-sdk/openai";
import { generateText } from "ai";

const bazaarlink = createOpenAI({
  baseURL: "https://bazaarlink.ai/api/v1",
  apiKey: "sk-bl-YOUR_API_KEY",
});

const { text } = await generateText({
  model: bazaarlink("openai/gpt-4o"),
  prompt: "Write a haiku about programming",
});

console.log(text);