概览
流式传输允许你在响应生成时接收部分内容,从而为聊天应用提供更好的用户体验。启用流式传输
在请求中设置stream: true:
复制
curl https://api.lemondata.cc/v1/chat/completions \
-H "Authorization: Bearer sk-your-api-key" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-4o",
"messages": [{"role": "user", "content": "Write a short poem"}],
"stream": true
}'
流式响应格式
流中的每个数据块(chunk)都遵循以下格式:复制
data: {"id":"chatcmpl-xxx","object":"chat.completion.chunk","created":1234567890,"model":"gpt-4o","choices":[{"index":0,"delta":{"content":"Hello"},"finish_reason":null}]}
data: {"id":"chatcmpl-xxx","object":"chat.completion.chunk","created":1234567890,"model":"gpt-4o","choices":[{"index":0,"delta":{"content":" world"},"finish_reason":null}]}
data: {"id":"chatcmpl-xxx","object":"chat.completion.chunk","created":1234567890,"model":"gpt-4o","choices":[{"index":0,"delta":{},"finish_reason":"stop"}]}
data: [DONE]
处理流结束
流以以下方式结束:finish_reason: "stop"- 正常完成finish_reason: "length"- 达到max_tokens限制finish_reason: "tool_calls"- 模型想要调用工具data: [DONE]- 最终消息
收集完整响应
在流式传输时收集完整响应:复制
full_response = ""
for chunk in stream:
if chunk.choices[0].delta.content:
content = chunk.choices[0].delta.content
full_response += content
print(content, end="", flush=True)
print(f"\n\nFull response: {full_response}")
异步流式传输
对于异步应用:复制
import asyncio
from openai import AsyncOpenAI
async def main():
client = AsyncOpenAI(
api_key="sk-your-api-key",
base_url="https://api.lemondata.cc/v1"
)
stream = await client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": "Hello!"}],
stream=True
)
async for chunk in stream:
if chunk.choices[0].delta.content:
print(chunk.choices[0].delta.content, end="")
asyncio.run(main())
Web 应用示例
对于 Web 聊天界面:复制
async function streamChat(message) {
const response = await fetch('https://api.lemondata.cc/v1/chat/completions', {
method: 'POST',
headers: {
'Authorization': 'Bearer sk-your-api-key',
'Content-Type': 'application/json'
},
body: JSON.stringify({
model: 'gpt-4o',
messages: [{ role: 'user', content: message }],
stream: true
})
});
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').filter(line => line.startsWith('data: '));
for (const line of lines) {
const data = line.slice(6);
if (data === '[DONE]') return;
const parsed = JSON.parse(data);
const content = parsed.choices[0]?.delta?.content;
if (content) {
// 添加到你的 UI
document.getElementById('output').textContent += content;
}
}
}
}