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MegaLLM
Getting Started

Quick Start

Get started with MegaLLM API in minutes

Quick Start

Get up and running with MegaLLM API in just a few minutes. This guide will walk you through the initial setup and your first API call.

Prerequisites: You'll need a MegaLLM API key to use our services.

Installation

Get Your API Key

First, you'll need to obtain your MegaLLM API key. This key will be used to authenticate all your API requests.

export MEGALLM_API_KEY="your-api-key"

See our Authentication Guide for detailed instructions on obtaining your API key.

Choose Your API Format

MegaLLM supports both OpenAI and Anthropic API formats. Choose the one that best fits your needs:

Set your base URL to use OpenAI-compatible endpoints:

export OPENAI_BASE_URL="https://ai.megallm.io/v1"
export OPENAI_API_KEY=$MEGALLM_API_KEY

Set your base URL to use Anthropic-compatible endpoints:

export ANTHROPIC_BASE_URL="https://ai.megallm.io"
export ANTHROPIC_API_KEY=$MEGALLM_API_KEY

Make Your First Request

Now you're ready to make your first API call!

curl https://ai.megallm.io/v1/chat/completions \
  -H "Authorization: Bearer $MEGALLM_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4",
    "messages": [
      {
        "role": "user",
        "content": "Hello! Can you introduce yourself?"
      }
    ],
    "max_tokens": 100
  }'
import requests
import os

response = requests.post(
    "https://ai.megallm.io/v1/chat/completions",
    headers={
        "Authorization": f"Bearer {os.getenv('MEGALLM_API_KEY')}",
        "Content-Type": "application/json"
    },
    json={
        "model": "gpt-4",
        "messages": [
            {
                "role": "user",
                "content": "Hello! Can you introduce yourself?"
            }
        ],
        "max_tokens": 100
    }
)

print(response.json())
const response = await fetch("https://ai.megallm.io/v1/chat/completions", {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${process.env.MEGALLM_API_KEY}`,
    "Content-Type": "application/json"
  },
  body: JSON.stringify({
    model: "gpt-4",
    messages: [
      {
        role: "user",
        content: "Hello! Can you introduce yourself?"
      }
    ],
    max_tokens: 100
  })
});

const data = await response.json();
console.log(data);
package main

import (
    "bytes"
    "encoding/json"
    "net/http"
    "os"
)

func main() {
    payload := map[string]interface{}{
        "model": "gpt-4",
        "messages": []map[string]string{
            {
                "role": "user",
                "content": "Hello! Can you introduce yourself?",
            },
        },
        "max_tokens": 100,
    }

    body, _ := json.Marshal(payload)

    req, _ := http.NewRequest("POST",
        "https://ai.megallm.io/v1/chat/completions",
        bytes.NewBuffer(body))

    req.Header.Set("Authorization", "Bearer " + os.Getenv("MEGALLM_API_KEY"))
    req.Header.Set("Content-Type", "application/json")

    client := &http.Client{}
    resp, _ := client.Do(req)
    defer resp.Body.Close()
}

Verify Your Setup

If everything is set up correctly, you should receive a response like this:

{
  "id": "chatcmpl-123",
  "object": "chat.completion",
  "created": 1677652288,
  "model": "gpt-4",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "Hello! I'm an AI assistant powered by MegaLLM..."
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 10,
    "completion_tokens": 25,
    "total_tokens": 35
  }
}

Next Steps

Common Issues

Rate Limiting: If you encounter rate limit errors, see our Rate Limiting Guide for handling strategies.

Authentication Failed: Make sure your API key is valid and has the necessary permissions. Check our Troubleshooting Guide for solutions.