Quickstart | Flow AI Docs

Flow AI serves models from many labs behind one OpenAI-compatible endpoint. Instead of signing up with OpenAI, Google, DeepSeek and the rest one by one, you integrate once and call any of them with one key.

Option	Best for
The API	Any language, no dependencies. Plain HTTP requests.
The OpenAI SDK	Python and TypeScript apps. Change the base URL and keep the rest of your code.
A framework	Apps built on the Vercel AI SDK, LangChain, PydanticAI and others.

Set up

Fund your account

Requests are paid in $THINK, 1 THINK =$ 1 of usage. Deposit some on Console → Funds.

Create an API key

Go to Console → API keys and choose Create key. Give it a name, and optionally limit the models it may call and how much it may spend.

The key starts with sk- and is shown only once. Copy it straight away; you can’t see it again later.

Keep it in an environment variable rather than in your code:

export HYPERFLOW_API_KEY="sk-..."

Using the API

Send a request to https://ai.hyperflow.fun/v1/chat/completions with your key as a bearer token. It works from any language or framework.

curl https://ai.hyperflow.fun/v1/chat/completions \
  -H "Authorization: Bearer $HYPERFLOW_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "openai/gpt-6-luna",
    "messages": [{ "role": "user", "content": "What is the meaning of life?" }]
  }'

The response follows OpenAI’s shape, with the answer in choices[0].message.content and the tokens it used in usage. Add "stream": true to get the answer as it’s written; see Streaming.

Choosing a model

Model ids look like lab/model, for example openai/gpt-6-luna. Copy one from the Models page, or list the ones your key can call:

curl https://ai.hyperflow.fun/v1/models \
  -H "Authorization: Bearer $HYPERFLOW_API_KEY"

See Models for what the list contains.

Using the OpenAI SDK

Flow AI speaks the OpenAI API, so the official SDK works as a drop-in replacement. Point it at the Flow AI base URL and keep the rest of your code:

import os
from openai import OpenAI
client = OpenAI(
    base_url="https://ai.hyperflow.fun/v1",
    api_key=os.environ["HYPERFLOW_API_KEY"],
)
response = client.chat.completions.create(
    model="openai/gpt-6-luna",
    messages=[{"role": "user", "content": "What is the meaning of life?"}],
)
print(response.choices[0].message.content)

Tools built on the OpenAI SDK often read OPENAI_BASE_URL and OPENAI_API_KEY from the environment. Set them to https://ai.hyperflow.fun/v1 and your Flow AI key to point those tools at Flow AI without changing their code.

Next steps

Streaming

Get the answer token by token as it’s written.

Integrations

Use Flow AI from your framework or coding tool.

Errors

What each error means and what to do.

Next: Streaming — get answers as the model writes them.