Building AI systems that can reason, use tools, execute workflows, and verify outcomes.

An open-source AI engineering project exploring autonomous agents, model orchestration, and developer-focused AI infrastructure.

Explore the Platform · Explore the Repository · Explore the Model Provider

AI should do more than generate text. A useful AI system should be able to understand a goal, plan the steps, select suitable tools, act on results, recover from errors, and verify whether the task was completed.

ZYRAXON AI is built around that engineering philosophy.

The project brings together autonomous-agent workflows, tool integrations, model orchestration, multimodal interactions, and developer-oriented infrastructure in an evolving ecosystem.

The ZYRAXON Model Provider presents ten branded model identities through a unified API interface. Developers can use familiar chat-completion patterns and consult the live provider catalogue for current model availability and supported capabilities.

Provider highlights

• Unified API interface for model discovery and chat completions.
• Ten branded model identities for different intended workloads.
• Streaming-oriented workflows where supported by the endpoint.
• Multimodal request formats for supported media and model combinations.
• Capability-aware routing and fallback behavior, as described by the provider documentation.

List available models

GET https://zyraxonai.lovable.app/api/public/zyraxon/v1/models

Create a chat completion

POST https://zyraxonai.lovable.app/api/public/zyraxon/v1/chat/completions

Context sizes and modality labels reflect the supplied provider specifications. Check the live catalogue for current availability, limits, and supported features.

Install the OpenAI JavaScript SDK:

npm install openai

Example client setup:

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://zyraxonai.lovable.app/api/public/zyraxon/v1",
  apiKey: process.env.ZYRAXON_API_KEY || "not-needed",
});

const response = await client.chat.completions.create({
  model: "zyraxon-apex",
  messages: [
    {
      role: "user",
      content: "Explain how an autonomous AI agent works.",
    },
  ],
});

console.log(response.choices[0].message.content);

Authentication: This example follows the supplied public quickstart pattern. Verify the endpoint's current authentication requirements, rate limits, and access policy in the official documentation before using it in production. Never expose a private API key in client-side code.

Provider links: Model Dashboard · Quickstart · Provider Documentation

const response = await client.chat.completions.create({
  model: "zyraxon-matrix",
  messages: [
    {
      role: "user",
      content: [
        { type: "text", text: "Describe the chart and its main trend." },
        {
          type: "image_url",
          image_url: {
            url: "data:image/png;base64,YOUR_IMAGE_BASE64",
          },
        },
      ],
    },
  ],
});

console.log(response.choices[0].message.content);

Replace YOUR_IMAGE_BASE64 with a valid image payload. Confirm supported formats, payload limits, and model compatibility in the provider documentation.

ZYRAXON AI focuses on the system surrounding the model: helping transform a user's goal into a workflow that can use tools, observe results, and validate outcomes.

• Goal-oriented execution — turn user intent into actionable steps.
• Tool integration — connect AI reasoning to external services and execution environments.
• Multi-agent orchestration — coordinate specialized agents for larger tasks.
• Execution and observation — use tool results to inform subsequent actions.
• Failure recovery — handle errors and revise or retry steps where appropriate.
• Verification — check results rather than assuming every generated answer means success.
• Developer extensibility — support an ecosystem that can evolve through integrations and contributions.

These principles describe the project's engineering direction; consult the source code and release notes to evaluate the implementation in a particular version.

Explore the source code →

Metrics are supplied by third-party services and may be affected by caching, availability, or API limits.

Ways to contribute:

• Code: improve features, fix bugs, and submit pull requests.
• Test: reproduce issues and report clear, actionable feedback.
• Documentation: improve setup guides, examples, and API instructions.
• Integrations: experiment with tools, models, and compatible workflows.
• Community: share demos, tutorials, ideas, and independent reviews.

Explore. Build. Contribute. Improve.

Autonomous Agents · Model Infrastructure · Open-Source Engineering

Think beyond the prompt. Build beyond the answer.

_{ZYRAXON AI INC. © 2026 · See the repository for the applicable license and terms.}