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Llm7.Io

Llm7.Io is an API gateway that connects applications to large language models from multiple providers through one OpenAI-compatible interface. It also publishes a model catalogue and comparison assets generated from a public API snapshot.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Llm7.Io — OpenViST project profile in AI APIs & Platforms.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use Llm7.Io when you want a shared API interface for accessing models from multiple providers, especially when working with an OpenAI-compatible client.

Who it is for

  • Developers integrating language models into applications or existing OpenAI-compatible tools.
  • Readers comparing models represented in the public catalogue.

Documented uses

  • Route application requests to models through a shared API endpoint.
  • Use an OpenAI-compatible client pattern to make model requests.
  • Review models and comparisons in the public catalogue.
Before you choose

Requirements & limits

API calls require a token. The project describes free tokens and says higher rate limits are available through dash.llm7.io.

  • The API is described as OpenAI-compatible, and the README includes Python, Node.js and CLI examples.
  • Token access is required for API calls; the README points to the dashboard for free tokens and higher rate limits.
  • The public GitHub repository is licensed under AGPL-3.0 and contains TypeScript source for the landing page, not the service implementation.
  • Model catalogue and comparison assets are generated from a public API snapshot during the landing-page build.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Make an OpenAI-compatible chat request through LLM7.io

Send a chat-completions request using LLM7.io’s API with a token.

Before you start

  • An API token from dash.llm7.io.
  • The Python openai package.

Steps

  1. Create an OpenAI client with base_url="https://api.llm7.io/v1" and set api_key to your token.

  2. Call client.chat.completions.create with a model name and messages.

Expected outcome

The client submits a chat-completions request through LLM7.io’s API gateway.

Guide limitations

  • Access requires an API token.
  • The example names gpt-4 but does not specify model availability or validate a successful response.
Documentation 1 ↗
Source-based practical guide

Build and inspect the public model catalogue assets

Generate static catalogue-related assets from the public API snapshot and inspect the exported pages.

Before you start

  • A local checkout of the repository.
  • Node.js and npm dependencies installed.

Steps

  1. Run the command below in the repository.

    Documented command
    npm install

  2. Run the command below to generate model, comparison, sitemap, and Open Graph assets from the public API snapshot.

    Documented command
    npm run build

  3. Run the command below after the production build to inspect the exported out/ pages.

    Documented command
    npm run validate:seo

Expected outcome

A production build generates catalogue-related assets, and the SEO validation command inspects the exported pages.

Guide limitations

  • This procedure does not deploy the generated site.
  • Price-only changes are obtained live in the browser from the models API; API-side caching can delay updated rates. New model routes or changes to static capabilities or statistics require a build.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
8 October 2026
Original website title
chigwell/llm7.io · Official homepage title · retained in its source language
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