# encoding:utf-8 import requests, json from bot.bot import Bot from bot.session_manager import SessionManager from bot.baidu.baidu_wenxin_session import BaiduWenxinSession from bridge.context import ContextType, Context from bridge.reply import Reply, ReplyType from common.log import logger from config import conf from common import const import time import _thread as thread import datetime from datetime import datetime from wsgiref.handlers import format_date_time from urllib.parse import urlencode import base64 import ssl import hashlib import hmac import json from time import mktime from urllib.parse import urlparse import websocket import queue import threading import random # 消息队列 map queue_map = dict() # 响应队列 map reply_map = dict() class XunFeiBot(Bot): def __init__(self): super().__init__() self.app_id = conf().get("xunfei_app_id") self.api_key = conf().get("xunfei_api_key") self.api_secret = conf().get("xunfei_api_secret") # 默认使用v2.0版本: "generalv2" # v1.5版本为 "general" # v3.0版本为: "generalv3" self.domain = "generalv3" # 默认使用v2.0版本: "ws://spark-api.xf-yun.com/v2.1/chat" # v1.5版本为: "ws://spark-api.xf-yun.com/v1.1/chat" # v3.0版本为: "ws://spark-api.xf-yun.com/v3.1/chat" self.spark_url = "ws://spark-api.xf-yun.com/v3.1/chat" self.host = urlparse(self.spark_url).netloc self.path = urlparse(self.spark_url).path # 和wenxin使用相同的session机制 self.sessions = SessionManager(BaiduWenxinSession, model=const.XUNFEI) def reply(self, query, context: Context = None) -> Reply: if context.type == ContextType.TEXT: logger.info("[XunFei] query={}".format(query)) session_id = context["session_id"] request_id = self.gen_request_id(session_id) reply_map[request_id] = "" session = self.sessions.session_query(query, session_id) threading.Thread(target=self.create_web_socket, args=(session.messages, request_id)).start() depth = 0 time.sleep(0.1) t1 = time.time() usage = {} while depth <= 300: try: data_queue = queue_map.get(request_id) if not data_queue: depth += 1 time.sleep(0.1) continue data_item = data_queue.get(block=True, timeout=0.1) if data_item.is_end: # 请求结束 del queue_map[request_id] if data_item.reply: reply_map[request_id] += data_item.reply usage = data_item.usage break reply_map[request_id] += data_item.reply depth += 1 except Exception as e: depth += 1 continue t2 = time.time() logger.info( f"[XunFei-API] response={reply_map[request_id]}, time={t2 - t1}s, usage={usage}" ) self.sessions.session_reply(reply_map[request_id], session_id, usage.get("total_tokens")) reply = Reply(ReplyType.TEXT, reply_map[request_id]) del reply_map[request_id] return reply else: reply = Reply(ReplyType.ERROR, "Bot不支持处理{}类型的消息".format(context.type)) return reply def create_web_socket(self, prompt, session_id, temperature=0.5): logger.info(f"[XunFei] start connect, prompt={prompt}") websocket.enableTrace(False) wsUrl = self.create_url() ws = websocket.WebSocketApp(wsUrl, on_message=on_message, on_error=on_error, on_close=on_close, on_open=on_open) data_queue = queue.Queue(1000) queue_map[session_id] = data_queue ws.appid = self.app_id ws.question = prompt ws.domain = self.domain ws.session_id = session_id ws.temperature = temperature ws.run_forever(sslopt={"cert_reqs": ssl.CERT_NONE}) def gen_request_id(self, session_id: str): return session_id + "_" + str(int(time.time())) + "" + str( random.randint(0, 100)) # 生成url def create_url(self): # 生成RFC1123格式的时间戳 now = datetime.now() date = format_date_time(mktime(now.timetuple())) # 拼接字符串 signature_origin = "host: " + self.host + "\n" signature_origin += "date: " + date + "\n" signature_origin += "GET " + self.path + " HTTP/1.1" # 进行hmac-sha256进行加密 signature_sha = hmac.new(self.api_secret.encode('utf-8'), signature_origin.encode('utf-8'), digestmod=hashlib.sha256).digest() signature_sha_base64 = base64.b64encode(signature_sha).decode( encoding='utf-8') authorization_origin = f'api_key="{self.api_key}", algorithm="hmac-sha256", headers="host date request-line", ' \ f'signature="{signature_sha_base64}"' authorization = base64.b64encode( authorization_origin.encode('utf-8')).decode(encoding='utf-8') # 将请求的鉴权参数组合为字典 v = {"authorization": authorization, "date": date, "host": self.host} # 拼接鉴权参数,生成url url = self.spark_url + '?' + urlencode(v) # 此处打印出建立连接时候的url,参考本demo的时候可取消上方打印的注释,比对相同参数时生成的url与自己代码生成的url是否一致 return url def gen_params(self, appid, domain, question): """ 通过appid和用户的提问来生成请参数 """ data = { "header": { "app_id": appid, "uid": "1234" }, "parameter": { "chat": { "domain": domain, "random_threshold": 0.5, "max_tokens": 2048, "auditing": "default" } }, "payload": { "message": { "text": question } } } return data class ReplyItem: def __init__(self, reply, usage=None, is_end=False): self.is_end = is_end self.reply = reply self.usage = usage # 收到websocket错误的处理 def on_error(ws, error): logger.error(f"[XunFei] error: {str(error)}") # 收到websocket关闭的处理 def on_close(ws, one, two): data_queue = queue_map.get(ws.session_id) data_queue.put("END") # 收到websocket连接建立的处理 def on_open(ws): logger.info(f"[XunFei] Start websocket, session_id={ws.session_id}") thread.start_new_thread(run, (ws, )) def run(ws, *args): data = json.dumps( gen_params(appid=ws.appid, domain=ws.domain, question=ws.question, temperature=ws.temperature)) ws.send(data) # Websocket 操作 # 收到websocket消息的处理 def on_message(ws, message): data = json.loads(message) code = data['header']['code'] if code != 0: logger.error(f'请求错误: {code}, {data}') ws.close() else: choices = data["payload"]["choices"] status = choices["status"] content = choices["text"][0]["content"] data_queue = queue_map.get(ws.session_id) if not data_queue: logger.error( f"[XunFei] can't find data queue, session_id={ws.session_id}") return reply_item = ReplyItem(content) if status == 2: usage = data["payload"].get("usage") reply_item = ReplyItem(content, usage) reply_item.is_end = True ws.close() data_queue.put(reply_item) def gen_params(appid, domain, question, temperature=0.5): """ 通过appid和用户的提问来生成请参数 """ data = { "header": { "app_id": appid, "uid": "1234" }, "parameter": { "chat": { "domain": domain, "temperature": temperature, "random_threshold": 0.5, "max_tokens": 2048, "auditing": "default" } }, "payload": { "message": { "text": question } } } return data