from langchain_openai import ChatOpenAI
from langchain_core.messages import HumanMessage
import os

llm = ChatOpenAI(
    model="clarke-1.0",
    openai_api_key=os.environ["RADIUM_API_KEY"],
    openai_api_base="https://api.radium.cloud/v1",
    temperature=0.7,
)

response = llm.invoke([HumanMessage(content="Explain Docker in one sentence.")])
print(response.content)

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

const openai = new OpenAI({
  apiKey: process.env.RADIUM_API_KEY,
  baseURL: "https://api.radium.cloud/v1",
});

const { text } = await generateText({
  model: openai("clarke-1.0"),
  prompt: "Write a haiku about cloud computing.",
});
console.log(text);

from pydantic_ai import Agent
import os

agent = Agent(
    "openai:clarke-1.0",
    api_key=os.environ["RADIUM_API_KEY"],
    base_url="https://api.radium.cloud/v1",
)

result = agent.run_sync("What is 2 + 2?")
print(result.data)

from anthropic import Anthropic
import os

client = Anthropic(
    api_key=os.environ["RADIUM_API_KEY"],
    base_url="https://api.radium.cloud",
)

response = client.messages.create(
    model="clarke-1.0",
    max_tokens=256,
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.content[-1].text)

import litellm
import os

response = litellm.completion(
    model="openai/clarke-1.0",
    messages=[{"role": "user", "content": "Hello!"}],
    api_key=os.environ["RADIUM_API_KEY"],
    api_base="https://api.radium.cloud/v1",
)
print(response.choices[0].message.content)