跳转到主要内容
前提条件: 您需要一个 MegaLLM API 密钥才能使用我们的服务。

​
安装

1

获取您的 API 密钥

首先,您需要获取 MegaLLM API 密钥。此密钥将用于验证您的所有 API 请求。
export MEGALLM_API_KEY="your-api-key"
查看我们的身份验证指南以获取有关获取 API 密钥的详细说明。
2

选择您的 API 格式

MegaLLM 同时支持 OpenAI 和 Anthropic API 格式。选择最适合您需求的格式:
设置您的基础 URL 以使用与 OpenAI 兼容的端点:
export MEGALLM_BASE_URL="https://ai.megallm.io/v1"
# 使用您的 MegaLLM API 密钥
export MEGALLM_API_KEY="your-api-key"
3

发出您的第一个请求

现在您已准备好进行第一次 API 调用!
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()
}
4

验证您的设置

如果一切设置正确,您应该会收到如下响应:
{
  "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
  }
}

​
下一步

身份验证

了解身份验证方法和 API 密钥管理

OpenAI API

探索与 OpenAI 兼容的端点

Anthropic API

发现 Anthropic Claude API 功能

最佳实践

常见问题和最佳实践

​
常见问题

速率限制: 如果您遇到速率限制错误,请查看我们的常见问题获取指导。
身份验证失败: 确保您的 API 密钥有效并具有必要的权限。查看我们的身份验证指南以获取解决方案。