Dokumentation API-Referenz SDK-Referenz Agentic-Nutzung KI-Skills

SDK-Referenz

OpenAI SDK-Kompatibilität

BazaarLink ist vollständig kompatibel mit den OpenAI Python- und Node.js-SDKs. Nur zwei Änderungen erforderlich:

Vorher (OpenAI direkt)

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from openai import OpenAI

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

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

Nachher (BazaarLink)

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from openai import OpenAI

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

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

Das war's!

Alle anderen Funktionen — Streaming, Tool Calling, Structured Output, Async — funktionieren genau gleich. Die einzige Änderung ist base_url, api_key und das Hinzufügen des Anbieter-Präfix zur Modell-ID.

Python

Installation

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pip install openai

Synchron

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from openai import OpenAI

client = OpenAI(
    base_url="https://api.bazaarlink.ai/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)

Asynchron

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import asyncio
from openai import AsyncOpenAI

client = AsyncOpenAI(
    base_url="https://api.bazaarlink.ai/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())

Streaming mit Async

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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

Installation

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npm install openai

Grundlegende Nutzung

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import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.bazaarlink.ai/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 ?? "";
}

Streaming

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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

Verwenden Sie BazaarLink mit LangChain, indem Sie die OpenAI-kompatible Base-URL konfigurieren.

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from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
    base_url="https://api.bazaarlink.ai/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

Verwenden Sie BazaarLink in LlamaIndex-RAG-Pipelines. LlamaIndex unterstützt jeden OpenAI-kompatiblen Endpunkt — ändern Sie einfach zwei Parameter.

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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://api.bazaarlink.ai/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

Integrieren Sie das Vercel AI SDK mit BazaarLink in Ihrer Next.js-App. Unterstützt Streaming, Tool Calling und Structured Output.

Installation

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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://api.bazaarlink.ai/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);