From 9cc1bd5136a1544b9171b1d276eb2ba362ab5e6c Mon Sep 17 00:00:00 2001 From: Yu Xin Date: Sun, 14 May 2023 23:19:08 +0800 Subject: [PATCH] =?UTF-8?q?api.py=E6=94=AF=E6=8C=81=E5=B9=B6=E5=8F=91?= =?UTF-8?q?=E6=9C=8D=E5=8A=A1.?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- api.py | 19 ++++++++++++++++--- 1 file changed, 16 insertions(+), 3 deletions(-) diff --git a/api.py b/api.py index 693c70a..3193d2d 100644 --- a/api.py +++ b/api.py @@ -2,6 +2,8 @@ from fastapi import FastAPI, Request from transformers import AutoTokenizer, AutoModel import uvicorn, json, datetime import torch +import threading +import asyncio DEVICE = "cuda" DEVICE_ID = "0" @@ -17,9 +19,12 @@ def torch_gc(): app = FastAPI() +import concurrent +from functools import partial +pool = concurrent.futures.ThreadPoolExecutor(10) @app.post("/") -async def create_item(request: Request): +async def _create_item(request: Request): global model, tokenizer json_post_raw = await request.json() json_post = json.dumps(json_post_raw) @@ -29,12 +34,13 @@ async def create_item(request: Request): max_length = json_post_list.get('max_length') top_p = json_post_list.get('top_p') temperature = json_post_list.get('temperature') - response, history = model.chat(tokenizer, + loop = asyncio.get_event_loop() + response, history = await loop.run_in_executor(pool,partial(model.chat,tokenizer, prompt, history=history, max_length=max_length if max_length else 2048, top_p=top_p if top_p else 0.7, - temperature=temperature if temperature else 0.95) + temperature=temperature if temperature else 0.95)) now = datetime.datetime.now() time = now.strftime("%Y-%m-%d %H:%M:%S") answer = { @@ -48,9 +54,16 @@ async def create_item(request: Request): torch_gc() return answer +async def create_item(request: Request): + loop = asyncio.get_event_loop() + with concurrent.futures.ThreadPoolExecutor() as pool: + result = await loop.run_in_executor(pool,_create_item, request) + print(result) + return result if __name__ == '__main__': tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True) model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).half().cuda() model.eval() uvicorn.run(app, host='0.0.0.0', port=8000, workers=1) +