代码示例
本页面提供了在各种编程语言和框架中使用 Feima API 的示例代码。
Python
Section titled “Python”基本聊天完成
Section titled “基本聊天完成”import httpx
async def chat_completion(api_key: str, prompt: str): """发送聊天完成请求。""" async with httpx.AsyncClient() as client: response = await client.post( "https://api.feimacode.cn/v1/chat/completions", headers={ "Authorization": f"Bearer {api_key}", "Content-Type": "application/json", }, json={ "model": "glm-5", "messages": [ {"role": "user", "content": prompt} ], "stream": False, } ) response.raise_for_status() return response.json()
# 使用import asyncio
result = asyncio.run(chat_completion( "feima_sk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx", "编写一个 Python 函数来计算阶乘。"))print(result["choices"][0]["message"]["content"])流式聊天完成
Section titled “流式聊天完成”import httpximport json
async def stream_chat_completion(api_key: str, prompt: str): """发送流式聊天完成请求。""" async with httpx.AsyncClient() as client: async with client.stream( "POST", "https://api.feimacode.cn/v1/chat/completions", headers={ "Authorization": f"Bearer {api_key}", "Content-Type": "application/json", }, json={ "model": "glm-5", "messages": [ {"role": "user", "content": prompt} ], "stream": True, } ) as response: response.raise_for_status() async for line in response.aiter_lines(): if line.startswith("data: "): data = line[6:] if data == "[DONE]": break chunk = json.loads(data) if chunk["choices"][0].get("delta", {}).get("content"): print(chunk["choices"][0]["delta"]["content"], end="", flush=True) print()
# 使用import asyncio
asyncio.run(stream_chat_completion( "feima_sk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx", "数到 10"))import httpximport json
async def chat_with_tools(api_key: str, prompt: str): """发送带工具调用的聊天完成请求。""" tools = [ { "type": "function", "function": { "name": "get_weather", "description": "获取位置的当前天气", "parameters": { "type": "object", "properties": { "location": {"type": "string"}, "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]} }, "required": ["location"] } } } ]
async with httpx.AsyncClient() as client: response = await client.post( "https://api.feimacode.cn/v1/chat/completions", headers={ "Authorization": f"Bearer {api_key}", "Content-Type": "application/json", }, json={ "model": "glm-5", "messages": [ {"role": "user", "content": prompt} ], "tools": tools, "tool_choice": "auto", } ) response.raise_for_status() return response.json()
# 使用import asyncio
result = asyncio.run(chat_with_tools( "feima_sk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx", "东京的天气怎么样？"))
# 检查模型是否想要调用工具if result["choices"][0]["finish_reason"] == "tool_calls": tool_call = result["choices"][0]["message"]["tool_calls"][0] print(f"调用的工具: {tool_call['function']['name']}") print(f"参数: {tool_call['function']['arguments']}")else: print(result["choices"][0]["message"]["content"])使用 OpenAI SDK
Section titled “使用 OpenAI SDK”from openai import OpenAI
# 配置 OpenAI SDK 使用 Feimaclient = OpenAI( api_key="feima_sk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx", base_url="https://api.feimacode.cn/v1")
# 基本完成response = client.chat.completions.create( model="glm-5", messages=[ {"role": "system", "content": "你是一个有用的助手。"}, {"role": "user", "content": "你好，Feima！"} ])print(response.choices[0].message.content)
# 流式完成stream = client.chat.completions.create( model="glm-5", messages=[{"role": "user", "content": "数到 10"}], stream=True)for chunk in stream: if chunk.choices[0].delta.content: print(chunk.choices[0].delta.content, end="", flush=True)print()
# 带工具tools = [ { "type": "function", "function": { "name": "get_weather", "description": "获取当前天气", "parameters": { "type": "object", "properties": { "location": {"type": "string"} }, "required": ["location"] } } }]
response = client.chat.completions.create( model="glm-5", messages=[{"role": "user", "content": "东京的天气怎么样？"}], tools=tools, tool_choice="auto")使用 Anthropic SDK
Section titled “使用 Anthropic SDK”from anthropic import Anthropic
# 配置 Anthropic SDK 使用 Feimaclient = Anthropic( api_key="feima_sk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx", base_url="https://api.feimacode.cn/v1")
# 基本完成message = client.messages.create( model="glm-5", max_tokens=1024, messages=[ {"role": "user", "content": "你好，Feima！"} ])print(message.content[0].text)
# 流式完成with client.messages.stream( model="glm-5", max_tokens=1024, messages=[{"role": "user", "content": "数到 10"}]) as stream: for text in stream.text_stream: print(text, end="", flush=True) print()
# 带工具tools = [ { "name": "get_weather", "description": "获取当前天气", "input_schema": { "type": "object", "properties": { "location": {"type": "string"} }, "required": ["location"] } }]
message = client.messages.create( model="glm-5", max_tokens=1024, messages=[{"role": "user", "content": "东京的天气怎么样？"}], tools=tools)JavaScript/TypeScript
Section titled “JavaScript/TypeScript”基本聊天完成
Section titled “基本聊天完成”async function chatCompletion(apiKey: string, prompt: string) { const response = await fetch('https://api.feimacode.cn/v1/chat/completions', { method: 'POST', headers: { 'Authorization': `Bearer ${apiKey}`, 'Content-Type': 'application/json', }, body: JSON.stringify({ model: 'glm-5', messages: [{ role: 'user', content: prompt }], stream: false, }), });
if (!response.ok) { throw new Error(`HTTP error! status: ${response.status}`); }
const data = await response.json(); return data.choices[0].message.content;}
// 使用const result = await chatCompletion( 'feima_sk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx', '编写一个 JavaScript 函数来计算阶乘。');console.log(result);流式聊天完成
Section titled “流式聊天完成”async function streamChatCompletion(apiKey: string, prompt: string) { const response = await fetch('https://api.feimacode.cn/v1/chat/completions', { method: 'POST', headers: { 'Authorization': `Bearer ${apiKey}`, 'Content-Type': 'application/json', }, body: JSON.stringify({ model: 'glm-5', messages: [{ role: 'user', content: prompt }], stream: true, }), });
if (!response.ok) { throw new Error(`HTTP error! status: ${response.status}`); }
const reader = response.body.getReader(); const decoder = new TextDecoder();
while (true) { const { done, value } = await reader.read(); if (done) break;
const chunk = decoder.decode(value); const lines = chunk.split('\n');
for (const line of lines) { if (line.startsWith('data: ')) { const data = line.slice(6); if (data === '[DONE]') break; try { const parsed = JSON.parse(data); const content = parsed.choices[0]?.delta?.content; if (content) { process.stdout.write(content); } } catch (e) { // 忽略不完整块的解析错误 } } } } console.log();}
// 使用await streamChatCompletion( 'feima_sk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx', '数到 10');使用 OpenAI SDK
Section titled “使用 OpenAI SDK”import OpenAI from 'openai';
const client = new OpenAI({ apiKey: 'feima_sk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx', baseURL: 'https://api.feimacode.cn/v1',});
// 基本完成const response = await client.chat.completions.create({ model: 'glm-5', messages: [ { role: 'system', content: '你是一个有用的助手。' }, { role: 'user', content: '你好，Feima！' }, ],});console.log(response.choices[0].message.content);
// 流式完成const stream = await client.chat.completions.create({ model: 'glm-5', messages: [{ role: 'user', content: '数到 10' }], stream: true,});
for await (const chunk of stream) { if (chunk.choices[0]?.delta?.content) { process.stdout.write(chunk.choices[0].delta.content); }}console.log();
// 带工具const tools = [ { type: 'function' as const, function: { name: 'get_weather', description: '获取当前天气', parameters: { type: 'object', properties: { location: { type: 'string' }, }, required: ['location'], }, }, },];
const responseWithTools = await client.chat.completions.create({ model: 'glm-5', messages: [{ role: 'user', content: '东京的天气怎么样？' }], tools, tool_choice: 'auto',});使用 Anthropic SDK
Section titled “使用 Anthropic SDK”import Anthropic from '@anthropic-ai/sdk';
const client = new Anthropic({ apiKey: 'feima_sk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx', baseURL: 'https://api.feimacode.cn/v1',});
// 基本完成const message = await client.messages.create({ model: 'glm-5', max_tokens: 1024, messages: [{ role: 'user', content: '你好，Feima！' }],});console.log(message.content[0].text);
// 流式完成const stream = await client.messages.create({ model: 'glm-5', max_tokens: 1024, messages: [{ role: 'user', content: '数到 10' }], stream: true,});
for await (const event of stream) { if (event.type === 'content_block_delta' && event.delta.type === 'text_delta') { process.stdout.write(event.delta.text); }}console.log();
// 带工具const tools = [ { name: 'get_weather', description: '获取当前天气', input_schema: { type: 'object', properties: { location: { type: 'string' }, }, required: ['location'], }, },];
const messageWithTools = await client.messages.create({ model: 'glm-5', max_tokens: 1024, messages: [{ role: 'user', content: '东京的天气怎么样？' }], tools,});curl https://api.feimacode.cn/v1/chat/completions \ -H "Authorization: Bearer feima_sk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" \ -H "Content-Type: application/json" \ -d '{ "model": "glm-5", "messages": [ {"role": "user", "content": "你好，Feima！"} ] }'curl https://api.feimacode.cn/v1/chat/completions \ -H "Authorization: Bearer feima_sk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" \ -H "Content-Type: application/json" \ -d '{ "model": "glm-5", "messages": [ {"role": "user", "content": "数到 10"} ], "stream": true }'curl https://api.feimacode.cn/v1/chat/completions \ -H "Authorization: Bearer feima_sk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" \ -H "Content-Type: application/json" \ -d '{ "model": "glm-5", "messages": [ {"role": "user", "content": "东京的天气怎么样？"} ], "tools": [ { "type": "function", "function": { "name": "get_weather", "description": "获取当前天气", "parameters": { "type": "object", "properties": { "location": {"type": "string"} }, "required": ["location"] } } } ], "tool_choice": "auto" }'基本聊天完成
Section titled “基本聊天完成”package main
import ( "bytes" "encoding/json" "fmt" "io" "net/http")
type ChatRequest struct { Model string `json:"model"` Messages []Message `json:"messages"` Stream bool `json:"stream"`}
type Message struct { Role string `json:"role"` Content string `json:"content"`}
type ChatResponse struct { Choices []Choice `json:"choices"`}
type Choice struct { Message Message `json:"message"`}
func chatCompletion(apiKey, prompt string) (string, error) { req := ChatRequest{ Model: "glm-5", Messages: []Message{ {Role: "user", Content: prompt}, }, Stream: false, }
reqBody, err := json.Marshal(req) if err != nil { return "", err }
httpReq, err := http.NewRequest("POST", "https://api.feimacode.cn/v1/chat/completions", bytes.NewBuffer(reqBody)) if err != nil { return "", err }
httpReq.Header.Set("Authorization", "Bearer "+apiKey) httpReq.Header.Set("Content-Type", "application/json")
client := &http.Client{} resp, err := client.Do(httpReq) if err != nil { return "", err } defer resp.Body.Close()
body, err := io.ReadAll(resp.Body) if err != nil { return "", err }
var chatResp ChatResponse if err := json.Unmarshal(body, &chatResp); err != nil { return "", err }
return chatResp.Choices[0].Message.Content, nil}
func main() { result, err := chatCompletion("feima_sk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx", "你好，Feima！") if err != nil { fmt.Printf("错误: %v\n", err) return } fmt.Println(result)}基本聊天完成
Section titled “基本聊天完成”import java.net.URI;import java.net.http.HttpClient;import java.net.http.HttpRequest;import java.net.http.HttpResponse;import java.net.http.HttpRequest.BodyPublishers;import java.net.http.HttpResponse.BodyHandlers;import com.fasterxml.jackson.databind.ObjectMapper;
public class FeimaClient { private static final String API_KEY = "feima_sk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"; private static final String BASE_URL = "https://api.feimacode.cn/v1";
private final HttpClient client; private final ObjectMapper mapper;
public FeimaClient() { this.client = HttpClient.newHttpClient(); this.mapper = new ObjectMapper(); }
public String chatCompletion(String prompt) throws Exception { String requestBody = String.format( "{\"model\":\"glm-5\",\"messages\":[{\"role\":\"user\",\"content\":\"%s\"}]}", prompt );
HttpRequest request = HttpRequest.newBuilder() .uri(URI.create(BASE_URL + "/chat/completions")) .header("Authorization", "Bearer " + API_KEY) .header("Content-Type", "application/json") .POST(BodyPublishers.ofString(requestBody)) .build();
HttpResponse<String> response = client.send(request, BodyHandlers.ofString());
if (response.statusCode() != 200) { throw new RuntimeException("请求失败: " + response.statusCode()); }
JsonNode root = mapper.readTree(response.body()); return root.path("choices").get(0).path("message").path("content").asText(); }
public static void main(String[] args) throws Exception { FeimaClient client = new FeimaClient(); String result = client.chatCompletion("你好，Feima！"); System.out.println(result); }}基本聊天完成
Section titled “基本聊天完成”use reqwest::{Client, header::AUTHORIZATION, header::CONTENT_TYPE};use serde::{Deserialize, Serialize};
#[derive(Serialize)]struct ChatRequest { model: String, messages: Vec<Message>, stream: bool,}
#[derive(Serialize)]struct Message { role: String, content: String,}
#[derive(Deserialize)]struct ChatResponse { choices: Vec<Choice>,}
#[derive(Deserialize)]struct Choice { message: MessageResponse,}
#[derive(Deserialize)]struct MessageResponse { content: String,}
#[tokio::main]async fn main() -> Result<(), Box<dyn std::error::Error>> { let client = Client::new(); let api_key = "feima_sk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx";
let request = ChatRequest { model: "glm-5".to_string(), messages: vec![Message { role: "user".to_string(), content: "你好，Feima！".to_string(), }], stream: false, };
let response = client .post("https://api.feimacode.cn/v1/chat/completions") .header(AUTHORIZATION, format!("Bearer {}", api_key)) .header(CONTENT_TYPE, "application/json") .json(&request) .send() .await?;
let chat_response: ChatResponse = response.json().await?; println!("{}", chat_response.choices[0].message.content);
Ok(())}基本聊天完成
Section titled “基本聊天完成”require 'net/http'require 'json'require 'uri'
def chat_completion(api_key, prompt) uri = URI('https://api.feimacode.cn/v1/chat/completions')
request = Net::HTTP::Post.new(uri) request['Authorization'] = "Bearer #{api_key}" request['Content-Type'] = 'application/json' request.body = { model: 'glm-5', messages: [{ role: 'user', content: prompt }], stream: false }.to_json
response = Net::HTTP.start(uri.hostname, uri.port, use_ssl: true) do |http| http.request(request) end
if response.code != '200' raise "请求失败: #{response.code} #{response.message}" end
data = JSON.parse(response.body) data['choices'][0]['message']['content']end
# 使用result = chat_completion('feima_sk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx', '你好，Feima！')puts result基本聊天完成
Section titled “基本聊天完成”<?php
function chatCompletion($apiKey, $prompt) { $url = 'https://api.feimacode.cn/v1/chat/completions';
$data = [ 'model' => 'glm-5', 'messages' => [ ['role' => 'user', 'content' => $prompt] ], 'stream' => false ];
$ch = curl_init($url); curl_setopt($ch, CURLOPT_RETURNTRANSFER, true); curl_setopt($ch, CURLOPT_POST, true); curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($data)); curl_setopt($ch, CURLOPT_HTTPHEADER, [ 'Authorization: Bearer ' . $apiKey, 'Content-Type: application/json' ]);
$response = curl_exec($ch); $httpCode = curl_getinfo($ch, CURLINFO_HTTP_CODE); curl_close($ch);
if ($httpCode !== 200) { throw new Exception("请求失败: HTTP $httpCode"); }
$result = json_decode($response, true); return $result['choices'][0]['message']['content'];}
// 使用try { $result = chatCompletion('feima_sk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx', '你好，Feima！'); echo $result;} catch (Exception $e) { echo "错误: " . $e->getMessage();}?>