基于FastAPI实现的ChatGLM2-6B流式返回API接口_chatglm2 api

# -*-coding:utf-8-*-
'''
File Name:chatglm2-6b-stream-api.py
Author:Luofan
Time:2023/6/26 13:33
'''

import os
import sys
import json
import torch
import uvicorn
import logging
import argparse
from fastapi import FastAPI
from transformers import AutoTokenizer, AutoModel
from fastapi.middleware.cors import CORSMiddleware
from sse_starlette.sse import ServerSentEvent, EventSourceResponse


def getLogger(name, file_name, use_formatter=True):
    logger = logging.getLogger(name)
    logger.setLevel(logging.INFO)
    console_handler = logging.StreamHandler(sys.stdout)
    formatter = logging.Formatter('%(asctime)s    %(message)s')
    console_handler.setFormatter(formatter)
    console_handler.setLevel(logging.INFO)
    logger.addHandler(console_handler)
    if file_name:
        handler = logging.FileHandler(file_name, encoding='utf8')
        handler.setLevel(logging.INFO)
        if use_formatter:
            formatter = logging.Formatter('%(asctime)s - %(name)s - %(message)s')
            handler.setFormatter(formatter)
        logger.addHandler(handler)
    return logger


logger = getLogger('ChatGLM', 'chatlog.log')

MAX_HISTORY = 3


class ChatGLM():
    def __init__(self) -> None:
        logger.info("Start initialize model...")
        self.tokenizer = AutoTokenizer.from_pretrained(
            "/home/luofan/chatglm2-6b/THUDM/chatglm2-6b", trust_remote_code=True)
        self.model = AutoModel.from_pretrained("/home/luofan/chatglm2-6b/THUDM/chatglm2-6b",
                                               trust_remote_code=True).quantize(8).cuda()
        self.model.eval()
        logger.info("Model initialization finished.")

    def clear(self) -> None:
        if torch.cuda.is_available():
            with torch.cuda.device(f"cuda:{args.device}"):
                torch.cuda.empty_cache()
                torch.cuda.ipc_collect()

    def answer(self, query: str, history):
        response, history = self.model.chat(self.tokenizer, query, history=history)
        history = [list(h) for h in history]
        return response, history

    def stream(self, query, history):
        if query is None or history is None:
            yield {"query": "", "response": "", "history": [], "finished": True}
        size = 0
        response = ""
        for response, history in self.model.stream_chat(self.tokenizer, query, history):
            this_response = response[size:]
            history = [list(h) for h in history]
            size = len(response)
            yield {"delta": this_response, "response": response, "finished": False}
        logger.info("Answer - {}".format(response))
        yield {"query": query, "delta": "[EOS]", "response": response, "history": history, "finished": True}


def start_server(http_address: str, port: int, gpu_id: str):
    os.environ['CUDA_DEVICE_ORDER'] = 'PCI_BUS_ID'
    os.environ['CUDA_VISIBLE_DEVICES'] = gpu_id

    bot = ChatGLM()

    app = FastAPI()
    app.add_middleware(CORSMiddleware,
                       allow_origins=["*"],
                       allow_credentials=True,
                       allow_methods=["*"],
                       allow_headers=["*"]
                       )

    @app.get("/")
    def index():
        return {'message': 'started', 'success': True}

    @app.post("/chat")
    async def answer_question(arg_dict: dict):
        result = {"query": "", "response": "", "success": False}
        try:
            text = arg_dict["query"]
            ori_history = arg_dict["history"]
            logger.info("Query - {}".format(text))
            if len(ori_history) > 0:
                logger.info("History - {}".format(ori_history))
            history = ori_history[-MAX_HISTORY:]
            history = [tuple(h) for h in history]
            response, history = bot.answer(text, history)
            logger.info("Answer - {}".format(response))
            ori_history.append((text, response))
            result = {"query": text, "response": response,
                      "history": ori_history, "success": True}
        except Exception as e:
            logger.error(f"error: {e}")
        return result

    @app.post("/stream")
    def answer_question_stream(arg_dict: dict):
        def decorate(generator):
            for item in generator:
                yield ServerSentEvent(json.dumps(item, ensure_ascii=False), event='delta')

        try:
            text = arg_dict["query"]
            ori_history = arg_dict["history"]
            logger.info("Query - {}".format(text))
            if len(ori_history) > 0:
                logger.info("History - {}".format(ori_history))
            history = ori_history[-MAX_HISTORY:]
            history = [tuple(h) for h in history]
            return EventSourceResponse(decorate(bot.stream(text, history)))
        except Exception as e:
            logger.error(f"error: {e}")
            return EventSourceResponse(decorate(bot.stream(None, None)))

    @app.get("/free_gc")
    def free_gpu_cache():
        try:
            bot.clear()
            return {"success": True}
        except Exception as e:
            logger.error(f"error: {e}")
            return {"success": False}

    logger.info("starting server...")
    uvicorn.run(app=app, host=http_address, port=port, workers=1)


if __name__ == '__main__':

    parser = argparse.ArgumentParser(description='Stream API Service for ChatGLM2-6B')
    parser.add_argument('--device', '-d', help='device，-1 means cpu, other means gpu ids', default='0')
    parser.add_argument('--host', '-H', help='host to listen', default='0.0.0.0')
    parser.add_argument('--port', '-P', help='port of this service', default=8000)
    args = parser.parse_args()
    start_server(args.host, int(args.port), args.device)

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157