mirror of https://github.com/THUDM/ChatGLM-6B
34 lines
1.1 KiB
Python
34 lines
1.1 KiB
Python
from typing import Optional
|
|
from fastapi import FastAPI, Request
|
|
from pydantic import BaseModel
|
|
from transformers import AutoTokenizer, AutoModel
|
|
import uvicorn, json, time, datetime, os, platform
|
|
|
|
app = FastAPI()
|
|
@app.post("/")
|
|
async def create_item(request: Request):
|
|
global history, model, tokenizer
|
|
jsonPostRaw = await request.json()
|
|
jsonPost = json.dumps(jsonPostRaw)
|
|
jsonPostList = json.loads(jsonPost)
|
|
prompt = jsonPostList.get('prompt')
|
|
response, history = model.chat(tokenizer, prompt, history=history)
|
|
now = datetime.datetime.now()
|
|
time = now.strftime("%Y-%m-%d %H:%M:%S")
|
|
answer = {
|
|
"response":response,
|
|
"status":200,
|
|
"time":time
|
|
}
|
|
log = "["+time+"] "+'device:"'+jsonPostList.get('device')+'", prompt:"'+prompt+'", response:"'+repr(response)+'"'
|
|
print(log)
|
|
return answer
|
|
|
|
if __name__ == '__main__':
|
|
uvicorn.run('API:app',host='0.0.0.0',port=8000,workers=1)
|
|
|
|
history = []
|
|
tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True)
|
|
model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).half().quantize(4).cuda()
|
|
model = model.eval()
|