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。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。
export MEGALLM_API_KEY="your-api-key"
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:
- OpenAI Format
- Anthropic Format
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"
设置您的基础 URL 以使用与 Anthropic 兼容的端点:
export ANTHROPIC_BASE_URL="https://ai.megallm.io"
export ANTHROPIC_API_KEY=$MEGALLM_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。