Zegeisa API Documentation

Build powerful AI solutions with our secure, scalable, and developer-friendly API.

Overview

Core Features

High-performance AI inference and training endpoints
Seamless integration with ML frameworks

Getting Started

1 Sign up and obtain an API key from Dashboard
2 Install required SDKs from Client Libraries

Authentication

API Key Authentication

Add your API key to the Authorization header:


Authorization: Bearer YOUR_API_KEY

Rate Limits

Free Tier 1000 requests/min
Paid Tier 500,000 requests/min

Requests exceeding limits will receive HTTP 429 Too Many Requests

Endpoints

POST /v1/predict

Request Body

{
  "model_id": "neuralflow-2.0",
  "input": {
    "prompt": "Generate a 300-word summary of recent AI research",
    "parameters": {
      "temperature": 0.7,
      "max_tokens": 300
    }
  }
}

Response Example

{
  "id": "pred-456789",
  "content": "Recent advances in AI ... [summary text] ... revolutionizing NLP tasks.",
  "completion_time": "0.45s"
}

POST /v1/train

Required Parameters

dataset_id - Identifier for training data
hyperparameters - JSON object with tuning parameters

Example Usage

curl -X POST "https://api.zegeisa.com/v1/train" 
     -H "Authorization: Bearer YOUR_API_KEY" 
     -d '{"dataset_id": "ds-001", 
         "hyperparameters": {"epochs": 10, "batch_size": 32}}'

Client Libraries

Python SDK

Install with:

pip install zegeisa

JavaScript SDK

Install with:

npm install @zegeisa/sdk

Other Languages

Community-maintained libraries available for:

• Java
• C#
• Go
• R

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