提交任务
POST http(s)://{{Host}}/v1/queue/put
示例
请求 (callback模式)
curl -X POST "https://${Host}/v1/queue/put" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${apikey}" \
-d '{
"queue": "test-queue",
"endpoint": "/v1/chat/completions",
"level": 1,
"data": {
"model": "deepseek-r1-20250401",
"messages": [
{
"role": "user",
"content": "你好"
}
],
"stream": false
},
"callback_url": "http://localhost:8081/test/callback",
}'
响应 (callback模式)
{
"code": 200,
"timestamp": 1762856201269,
"data": "TASK-X-X-X-XXXXXXXXXXXX-XXXX-XXXXXX"
}
请求 (blocking模式)
curl -X POST "https://${Host}/v1/queue/put" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${apikey}" \
-d '{
"queue": "test-queue",
"endpoint": "/v1/chat/completions",
"level": 0,
"response_mode": "blocking",
"data": {
"model": "deepseek-r1-20250401",
"messages": [
{
"role": "user",
"content": "你好"
}
],
"stream": false
}
}'
响应 (blocking模式)
{
"id": "chatcmpl-XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX",
"object": "chat.completion",
"created": 1762857979,
"model": "deepseek-r1-20250401",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "\n你好呀!👋 很高兴见到你~ \n我是你的AI助手,随时准备帮你解答问题、整理资料或陪你聊聊有趣的话题。有什么想聊的,或者需要帮忙的吗?比如: \n- 生活小烦恼? 📚 \n- 学习/工作上的疑问? 💡 \n- 想探索某个知识领域? 🌍 \n- 或者单纯想放松聊聊? 😄 \n\n等你开口啦~ ✨",
"tool_calls": [],
"reasoning_content": "\n嗯,用户发来一句简单的“你好”。看起来像是初次打招呼,可能刚打开聊天界面或者第一次使用这类AI助手。 \n\n用户没有提出具体问题,可能是在测试功能、想闲聊,或者还没想好要问什么。这时候需要既保持友好开放的态度,又避免过度热情显得机械。 \n\n考虑到中文语境,“你好”比“嗨”更正式一点,但也不是特别拘谨。回复时可以带点温度,比如加个表情符号平衡正式感,同时明确表达“我随时能帮忙”的立场。 \n\n要不要主动提供方向提示呢?新用户可能真的需要引导。列举几个常见方向(生活/学习/工作)比较稳妥,覆盖大部分场景,再加个“其他需求”的兜底选项,避免局限感。结尾用波浪号和emoji保持轻松感比较合适。 \n\n对了,最后那句“等你开口”是不是太文艺了?……不过配合前面的✨符号应该能传达出“耐心等待”的善意,保留吧。\n"
},
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 4,
"total_tokens": 307,
"completion_tokens": 303
}
}
请求 (streaming模式)
curl -X POST "https://${Host}/v1/queue/put" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${apikey}" \
-d '{
"queue": "test-queue",
"endpoint": "/v1/chat/completions",
"level": 0,
"response_mode": "streaming",
"data": {
"model": "deepseek-r1-20250401",
"messages": [
{
"role": "user",
"content": "你好"
}
],
"stream": true
}
}'
响应 (streaming模式)
Connected to http://{{Host}}/v1/queue/put
data: {"id":"chatcmpl-XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX","object":"chat.completion.chunk","created":1762858384,"model":"deepseek-r1-20250401","choices":[{"index":0,"delta":{"role":"assistant","content":""},"logprobs":null,"finish_reason":null}]}
data: {"id":"chatcmpl-XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX","object":"chat.completion.chunk","created":1762858384,"model":"deepseek-r1-20250401","choices":[{"index":0,"delta":{"reasoning_content":"\n"},"logprobs":null,"finish_reason":null}]}
data: {"id":"chatcmpl-XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX","object":"chat.completion.chunk","created":1762858384,"model":"deepseek-r1-20250401","choices":[{"index":0,"delta":{"reasoning_content":"嗯"},"logprobs":null,"finish_reason":null}]}
data: {"id":"chatcmpl-XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX","object":"chat.completion.chunk","created":1762858384,"model":"deepseek-r1-20250401","choices":[{"index":0,"delta":{"reasoning_content":","},"logprobs":null,"finish_reason":null}]}
...
data: [DONE]
Connection closed
Request Body Parameters
| 参数 | 类型 | 必需 | 说明 |
|---|---|---|---|
queue | string | Required | 队列名称 |
endpoint | string | Required | 处理任务的能力点 |
level | integer | Required | 队列级别:0(在线队列)、1(离线队列) |
data | object | Required | 任务数据载荷,参考openapi使用文档 |
response_mode | string | Optional | 响应模式:blocking(阻塞)、streaming(流式)、callback(回调),默认callback。callback支持在线和离线队列,blocking和streaming仅支持在线队列 |
callback_url | string | Optional | 回调URL(callback模式时使用) |
timeout | integer | Optional | 任务超时时间(秒),blocking/streaming模式默认300秒,callback模式默认24小时 |
Response Modes
blocking模式
- 同步等待任务完成并返回结果
- 适合实时交互场景
- 响应时间受任务处理时长影响
- 仅支持在线队列 (level=0)
streaming模式
- 返回Server-Sent Events流
- 适合需要实时流式输出的场景
- 客户端需支持SSE
- 仅支持在线队列 (level=0)
callback模式
- 异步处理,完成后回调指定URL
- 适合长时间处理任务
- 立即返回任务ID
- 支持在线队列 (level=0) 和离线队列 (level=1)
Returns
根据response_mode返回不同格式:
- blocking: 直接返回任务处理结果
- streaming: 返回SSE流对象
- callback: 返回包含任务ID的响应对象