importrequestsdeftest():url=r"http://127.0.0.1:8000/"headers={'Content-Type':'text/event-stream'}response=requests.get(url,headers=headers,stream=True)forchunkinresponse.iter_content(chunk_size=1024,decode_unicode=True):print(chunk)if__name__=='__main__':test() 这段代码中使用了response ...
import aiohttp import asyncio async def test(): headers = {'Content-Type': 'text/event-stream'} sseresp = aiohttp.request("GET", r"http://127.0.0.1:9000/api/sse", headers=headers) async with sseresp as r: async for chunk in r.content.iter_any(): print(chunk.decode()) if __nam...
g = event_generator(request)returnEventSourceResponse(g) SEE客户端测试脚本 importaiohttpimportasyncioasyncdeftest(): headers = {'Content-Type':'text/event-stream'} sseresp = aiohttp.request("GET",r"http://127.0.0.1:9000/api/sse", headers=headers)asyncwithsserespasr:asyncforchunkinr.content.i...
headers = {'Content-Type': 'text/event-stream'} sseresp = aiohttp.request("GET", r"http://127.0.0.1:9000/api/sse", headers=headers) async with sseresp as r: async for chunk in r.content.iter_any(): print(chunk.decode()) if __name__ == '__main__': loop = asyncio.get_eve...
上面的代码中,我们创建了一个GET路由/sse,将Content-Type设置为"text/event-stream",并在一个无限循环中向客户端发送"Hello, world!"消息。 步骤2:在前端创建一个用于接收SSE消息的EventSource对象 在前端HTML文件中,我们需要创建一个EventSource对象来接收服务器端发送的SSE消息。
():headers={'Content-Type':'text/event-stream'}sseresp=aiohttp.request("GET",r"http://127.0.0.1:9000/api/sse",headers=headers)asyncwithsserespasr:asyncforchunkinr.content.iter_any():print(chunk.decode())if__name__=='__main__':loop=asyncio.get_event_loop()loop.run_until_complete(...
根据需要向客户端推送数据。FastAPI (sse-starlette)、Flask (Flask-SSE) 和 Django (Django EventStream) 支持。 队列 ZeroMQ、Celery、Redis 和 RabbitMQ 等外部软件包支持作业队列、发布-订阅和其他网络模式。 WebSockets 由FastAPI(直接)、Django(Django Channels)和 Flask(第三方软件包)支持。
question)), media_type="text/event-stream") @app.get("/output/{conversation_id}") async def get_output(conversation_id: str): if conversation_id not in desk_instances: raise HTTPException(status_code=404, detail="Conversation not found") logging.info(f"Getting output for conversation ID: ...
(content=req_model.content)]returnStreamingResponse(generate_stream_response(callback,llm,messages),media_type="text/event-stream")asyncdefgenerate_stream_response(_callback,llm:ChatOpenAI,messages:list[BaseMessage]):"""流式响应"""task=asyncio.create_task(llm.apredict_messages(messages))asyncfor...
ask(req:dict):stream=awaitclient.chat.completions.create(messages=req["messages"],model="gpt-3.5-turbo",stream=True, )asyncdefgenerator():asyncforchunkinstream:yieldchunk.choices[0].delta.contentor""response_messages=generator()returnStreamingResponse(response_messages,media_type="text/event-stream"...