LangChain

pip install langchain-openai
export API_KEY="sk-at-…"

import os

from langchain_core.tools import tool
from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
    base_url="https://api.aitokens.ch/v1",
    api_key=os.environ["API_KEY"],
    model="qwen3.8-27b",
    max_tokens=2048,  # room for the reasoning of the models that reason
)

print(llm.invoke("Name the four national languages of Switzerland, comma-separated.").content)


@tool
def get_weather(city: str) -> str:
    """Current weather for a city."""
    return "14 °C, light rain"


msg = llm.bind_tools([get_weather]).invoke("What is the weather in Lugano?")
print(msg.tool_calls)

German, French, Italian, Romansh
[{'name': 'get_weather', 'args': {'city': 'Lugano'}, 'id': 'chatcmpl-tool-…', 'type': 'tool_call'}]

quick = ChatOpenAI(
    base_url="https://api.aitokens.ch/v1",
    api_key=os.environ["API_KEY"],
    model="qwen3.8-27b",
    max_tokens=2048,
    reasoning_effort="none",
)

from langchain_openai import OpenAIEmbeddings

emb = OpenAIEmbeddings(
    base_url="https://api.aitokens.ch/v1",
    api_key=os.environ["API_KEY"],
    model="bge-m3",
    check_embedding_ctx_length=False,  # send text, not token ids
    chunk_size=32,                     # at most 32 texts per request
)
vectors = emb.embed_documents(["Lugano is in Ticino.", "Chur is in Graubünden."])
print(len(vectors), len(vectors[0]))  # 2 1024