from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
    openai_api_key="YOUR_HYPERBOLIC_API_KEY",
    openai_api_base="https://api.hyperbolic.xyz/v1",
    model_name="meta-llama/Llama-3.3-70B-Instruct"
)

response = llm.invoke("What is the capital of France?")
print(response.content)

pip install langchain langchain-openai

from llama_index.llms.openai_like import OpenAILike

llm = OpenAILike(
    api_key="YOUR_HYPERBOLIC_API_KEY",
    api_base="https://api.hyperbolic.xyz/v1",
    model="meta-llama/Llama-3.3-70B-Instruct"
)

response = llm.complete("Explain quantum computing in simple terms")
print(response.text)

pip install llama-index llama-index-llms-openai-like

from huggingface_hub import InferenceClient

client = InferenceClient(
    provider="hyperbolic",
    api_key="YOUR_HYPERBOLIC_API_KEY"
)

response = client.chat.completions.create(
    model="deepseek-ai/DeepSeek-R1",
    messages=[
        {"role": "user", "content": "What is the capital of France?"}
    ],
    max_tokens=500
)

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

pip install huggingface_hub>=0.29.0

import gradio as gr
from openai import OpenAI

client = OpenAI(
    api_key="YOUR_HYPERBOLIC_API_KEY",
    base_url="https://api.hyperbolic.xyz/v1"
)

def chat(message, history):
    response = client.chat.completions.create(
        model="meta-llama/Llama-3.3-70B-Instruct",
        messages=[{"role": "user", "content": message}]
    )
    return response.choices[0].message.content

demo = gr.ChatInterface(chat)
demo.launch()

pip install gradio openai