mirror of
https://github.com/zhayujie/chatgpt-on-wechat.git
synced 2026-07-20 13:47:15 +08:00
feat: add xunfei spark bot
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zhayujie
@@ -14,31 +14,29 @@ def create_bot(bot_type):
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# 替换Baidu Unit为Baidu文心千帆对话接口
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# from bot.baidu.baidu_unit_bot import BaiduUnitBot
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# return BaiduUnitBot()
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from bot.baidu.baidu_wenxin import BaiduWenxinBot
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return BaiduWenxinBot()
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elif bot_type == const.CHATGPT:
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# ChatGPT 网页端web接口
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from bot.chatgpt.chat_gpt_bot import ChatGPTBot
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return ChatGPTBot()
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elif bot_type == const.OPEN_AI:
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# OpenAI 官方对话模型API
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from bot.openai.open_ai_bot import OpenAIBot
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return OpenAIBot()
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elif bot_type == const.CHATGPTONAZURE:
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# Azure chatgpt service https://azure.microsoft.com/en-in/products/cognitive-services/openai-service/
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from bot.chatgpt.chat_gpt_bot import AzureChatGPTBot
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return AzureChatGPTBot()
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elif bot_type == const.XUNFEI:
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from bot.xunfei.xunfei_spark_bot import XunFeiBot
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return XunFeiBot()
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elif bot_type == const.LINKAI:
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from bot.linkai.link_ai_bot import LinkAIBot
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return LinkAIBot()
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raise RuntimeError
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@@ -55,11 +55,16 @@ class ChatGPTSession(Session):
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# refer to https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb
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def num_tokens_from_messages(messages, model):
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"""Returns the number of tokens used by a list of messages."""
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if model in ["wenxin", "xunfei"]:
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return num_tokens_by_character(messages)
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import tiktoken
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if model in ["gpt-3.5-turbo-0301", "gpt-35-turbo"]:
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return num_tokens_from_messages(messages, model="gpt-3.5-turbo")
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elif model in ["gpt-4-0314", "gpt-4-0613", "gpt-4-32k", "gpt-4-32k-0613", "gpt-3.5-turbo-0613", "gpt-3.5-turbo-16k", "gpt-3.5-turbo-16k-0613", "gpt-35-turbo-16k"]:
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elif model in ["gpt-4-0314", "gpt-4-0613", "gpt-4-32k", "gpt-4-32k-0613", "gpt-3.5-turbo-0613",
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"gpt-3.5-turbo-16k", "gpt-3.5-turbo-16k-0613", "gpt-35-turbo-16k"]:
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return num_tokens_from_messages(messages, model="gpt-4")
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try:
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@@ -85,3 +90,11 @@ def num_tokens_from_messages(messages, model):
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num_tokens += tokens_per_name
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num_tokens += 3 # every reply is primed with <|start|>assistant<|message|>
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return num_tokens
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def num_tokens_by_character(messages):
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"""Returns the number of tokens used by a list of messages."""
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tokens = 0
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for msg in messages:
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tokens += len(msg["content"])
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return tokens
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246
bot/xunfei/xunfei_spark_bot.py
Normal file
246
bot/xunfei/xunfei_spark_bot.py
Normal file
@@ -0,0 +1,246 @@
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# encoding:utf-8
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import requests, json
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from bot.bot import Bot
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from bot.session_manager import SessionManager
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from bot.baidu.baidu_wenxin_session import BaiduWenxinSession
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from bridge.context import ContextType, Context
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from bridge.reply import Reply, ReplyType
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from common.log import logger
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from config import conf
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from common import const
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import time
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import _thread as thread
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import datetime
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from datetime import datetime
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from wsgiref.handlers import format_date_time
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from urllib.parse import urlencode
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import base64
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import ssl
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import hashlib
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import hmac
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import json
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from time import mktime
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from urllib.parse import urlparse
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import websocket
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import queue
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import threading
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import random
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# 消息队列 map
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queue_map = dict()
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class XunFeiBot(Bot):
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def __init__(self):
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super().__init__()
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self.app_id = conf().get("xunfei_app_id")
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self.api_key = conf().get("xunfei_api_key")
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self.api_secret = conf().get("xunfei_api_secret")
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# 默认使用v2.0版本，1.5版本可设置为 general
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self.domain = "generalv2"
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# 默认使用v2.0版本，1.5版本可设置为 "ws://spark-api.xf-yun.com/v1.1/chat"
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self.spark_url = "ws://spark-api.xf-yun.com/v2.1/chat"
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self.host = urlparse(self.spark_url).netloc
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self.path = urlparse(self.spark_url).path
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self.answer = ""
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# 和wenxin使用相同的session机制
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self.sessions = SessionManager(BaiduWenxinSession, model=const.XUNFEI)
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def reply(self, query, context: Context = None) -> Reply:
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if context.type == ContextType.TEXT:
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logger.info("[XunFei] query={}".format(query))
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session_id = context["session_id"]
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request_id = self.gen_request_id(session_id)
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session = self.sessions.session_query(query, session_id)
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threading.Thread(target=self.create_web_socket, args=(session.messages, request_id)).start()
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depth = 0
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time.sleep(0.1)
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t1 = time.time()
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usage = {}
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while depth <= 300:
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try:
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data_queue = queue_map.get(request_id)
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if not data_queue:
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depth += 1
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time.sleep(0.1)
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continue
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data_item = data_queue.get(block=True, timeout=0.1)
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if data_item.is_end:
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# 请求结束
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del queue_map[request_id]
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if data_item.reply:
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self.answer += data_item.reply
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usage = data_item.usage
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break
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self.answer += data_item.reply
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depth += 1
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except Exception as e:
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depth += 1
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continue
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t2 = time.time()
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logger.info(f"[XunFei-API] response={self.answer}, time={t2 - t1}s, usage={usage}")
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self.sessions.session_reply(self.answer, session_id, usage.get("total_tokens"))
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reply = Reply(ReplyType.TEXT, self.answer)
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return reply
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else:
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reply = Reply(ReplyType.ERROR, "Bot不支持处理{}类型的消息".format(context.type))
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return reply
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def create_web_socket(self, prompt, session_id, temperature=0.5):
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logger.info(f"[XunFei] start connect, prompt={prompt}")
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websocket.enableTrace(False)
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wsUrl = self.create_url()
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ws = websocket.WebSocketApp(wsUrl, on_message=on_message, on_error=on_error, on_close=on_close,
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on_open=on_open)
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data_queue = queue.Queue(1000)
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queue_map[session_id] = data_queue
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ws.appid = self.app_id
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ws.question = prompt
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ws.domain = self.domain
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ws.session_id = session_id
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ws.temperature = temperature
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ws.run_forever(sslopt={"cert_reqs": ssl.CERT_NONE})
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def gen_request_id(self, session_id: str):
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return session_id + "_" + str(int(time.time())) + "" + str(random.randint(0, 100))
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# 生成url
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def create_url(self):
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# 生成RFC1123格式的时间戳
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now = datetime.now()
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date = format_date_time(mktime(now.timetuple()))
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# 拼接字符串
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signature_origin = "host: " + self.host + "\n"
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signature_origin += "date: " + date + "\n"
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signature_origin += "GET " + self.path + " HTTP/1.1"
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# 进行hmac-sha256进行加密
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signature_sha = hmac.new(self.api_secret.encode('utf-8'), signature_origin.encode('utf-8'),
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digestmod=hashlib.sha256).digest()
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signature_sha_base64 = base64.b64encode(signature_sha).decode(encoding='utf-8')
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authorization_origin = f'api_key="{self.api_key}", algorithm="hmac-sha256", headers="host date request-line", ' \
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f'signature="{signature_sha_base64}"'
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authorization = base64.b64encode(authorization_origin.encode('utf-8')).decode(encoding='utf-8')
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# 将请求的鉴权参数组合为字典
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v = {
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"authorization": authorization,
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"date": date,
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"host": self.host
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}
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# 拼接鉴权参数，生成url
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url = self.spark_url + '?' + urlencode(v)
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# 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
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return url
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def gen_params(self, appid, domain, question):
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"""
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通过appid和用户的提问来生成请参数
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"""
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data = {
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"header": {
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"app_id": appid,
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"uid": "1234"
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},
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"parameter": {
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"chat": {
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"domain": domain,
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"random_threshold": 0.5,
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"max_tokens": 2048,
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"auditing": "default"
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}
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},
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"payload": {
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"message": {
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"text": question
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}
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}
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}
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return data
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class ReplyItem:
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def __init__(self, reply, usage=None, is_end=False):
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self.is_end = is_end
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self.reply = reply
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self.usage = usage
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# 收到websocket错误的处理
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def on_error(ws, error):
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logger.error("[XunFei] error:", error)
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# 收到websocket关闭的处理
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def on_close(ws, one, two):
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data_queue = queue_map.get(ws.session_id)
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data_queue.put("END")
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# 收到websocket连接建立的处理
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def on_open(ws):
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logger.info(f"[XunFei] Start websocket, session_id={ws.session_id}")
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thread.start_new_thread(run, (ws,))
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def run(ws, *args):
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data = json.dumps(gen_params(appid=ws.appid, domain=ws.domain, question=ws.question, temperature=ws.temperature))
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ws.send(data)
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# Websocket 操作
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# 收到websocket消息的处理
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def on_message(ws, message):
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data = json.loads(message)
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code = data['header']['code']
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if code != 0:
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logger.error(f'请求错误: {code}, {data}')
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ws.close()
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else:
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choices = data["payload"]["choices"]
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status = choices["status"]
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content = choices["text"][0]["content"]
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data_queue = queue_map.get(ws.session_id)
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if not data_queue:
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logger.error(f"[XunFei] can't find data queue, session_id={ws.session_id}")
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return
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reply_item = ReplyItem(content)
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if status == 2:
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usage = data["payload"].get("usage")
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reply_item = ReplyItem(content, usage)
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reply_item.is_end = True
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ws.close()
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data_queue.put(reply_item)
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def gen_params(appid, domain, question, temperature=0.5):
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"""
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通过appid和用户的提问来生成请参数
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"""
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data = {
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"header": {
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"app_id": appid,
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"uid": "1234"
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},
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"parameter": {
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"chat": {
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"domain": domain,
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"temperature": temperature,
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"random_threshold": 0.5,
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"max_tokens": 2048,
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"auditing": "default"
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}
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},
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"payload": {
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"message": {
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"text": question
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}
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}
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}
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return data
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