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Documentation Index

Fetch the complete documentation index at: https://docs.llm7.io/llms.txt

Use this file to discover all available pages before exploring further.

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Get started in two steps

Spin up the OpenAI SDK against the LLM7.io endpoint and make your first requests.

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Step 1: Set up

pip install openai

Configure the client

LLM7.io requires a token. Get one for free at token.llm7.io for higher rate limits.
import openai

client = openai.OpenAI(
    base_url="https://api.llm7.io/v1",
    api_key="unused",  # Required. Get it for free at https://token.llm7.io/ for higher rate limits.
)

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Step 2: Text generation

Chat completions (Python)

import openai

client = openai.OpenAI(
    base_url="https://api.llm7.io/v1",
    api_key="unused",  # Required. Get it for free at https://token.llm7.io/ for higher rate limits.
)

resp = client.chat.completions.create(
    model="default",
    messages=[
        {"role": "user", "content": "Tell me a short story about a brave squirrel."}
    ],
)

print(resp.choices[0].message.content)
The output will be a short story generated by the model, for example:
Once upon a time, in a lush green forest, there lived a brave squirrel named Sammy. Sammy was known for his adventurous spirit and his willingness to help others. One day, a fierce storm hit the forest, causing a massive tree to fall and block the entrance to the squirrel village. Without hesitation, Sammy gathered his friends and devised a plan to clear the path. With teamwork and determination, they managed to move the fallen tree and restore access to their home. The villagers celebrated Sammy's bravery, and he became a legend in the forest for his courageous act.

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Next steps

Function calling

Bind tool calls to your own functions reliably.

JSON mode

Get guaranteed JSON outputs for structured use-cases.

Streaming

Stream tokens for lower latency UIs.

Available models

See model options.
Need help? Check the API reference above or join the community.