Add support for ModelScope API

This commit is contained in:
yanrk123
2025-03-11 11:12:57 +08:00
parent 436c038a2f
commit 3e185dbbfe
8 changed files with 219 additions and 4 deletions

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@@ -0,0 +1,152 @@
# encoding:utf-8
import time
import json
import openai
import openai.error
from bot.bot import Bot
from bot.session_manager import SessionManager
from bridge.context import ContextType
from bridge.reply import Reply, ReplyType
from common.log import logger
from config import conf, load_config
from .modelscope_session import ModelScopeSession
import requests
# ModelScope对话模型API
class ModelScopeBot(Bot):
def __init__(self):
super().__init__()
self.sessions = SessionManager(ModelScopeSession, model=conf().get("model") or "Qwen/Qwen2.5-7B-Instruct")
model = conf().get("model") or "Qwen/Qwen2.5-7B-Instruct"
if model == "modelscope":
model = "Qwen/Qwen2.5-7B-Instruct"
self.args = {
"model": model, # 对话模型的名称
"temperature": conf().get("temperature", 0.3), # 如果设置,值域须为 [0, 1] 我们推荐 0.3,以达到较合适的效果。
"top_p": conf().get("top_p", 1.0), # 使用默认值
}
self.api_key = conf().get("modelscope_api_key")
self.base_url = conf().get("modelscope_base_url", "https://api-inference.modelscope.cn/v1/chat/completions")
"""
需要获取MOdelScope支持API-inference的模型名称列表请到魔搭社区官网模型中心查看 https://modelscope.cn/models?filter=inference_type&page=1。
或者使用命令 curl https://api-inference.modelscope.cn/v1/models 对模型列表和ID进行获取。
获取ModelScope的免费API Key请到魔搭社区官网用户中心查看获取方式 https://modelscope.cn/docs/model-service/API-Inference/intro。
"""
def reply(self, query, context=None):
# acquire reply content
if context.type == ContextType.TEXT:
logger.info("[MODELSCOPE_AI] query={}".format(query))
session_id = context["session_id"]
reply = None
clear_memory_commands = conf().get("clear_memory_commands", ["#清除记忆"])
if query in clear_memory_commands:
self.sessions.clear_session(session_id)
reply = Reply(ReplyType.INFO, "记忆已清除")
elif query == "#清除所有":
self.sessions.clear_all_session()
reply = Reply(ReplyType.INFO, "所有人记忆已清除")
elif query == "#更新配置":
load_config()
reply = Reply(ReplyType.INFO, "配置已更新")
if reply:
return reply
session = self.sessions.session_query(query, session_id)
logger.debug("[MODELSCOPE_AI] session query={}".format(session.messages))
model = context.get("modelscope_model")
new_args = self.args.copy()
if model:
new_args["model"] = model
# if context.get('stream'):
# # reply in stream
# return self.reply_text_stream(query, new_query, session_id)
reply_content = self.reply_text(session, args=new_args)
logger.debug(
"[MODELSCOPE_AI] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format(
session.messages,
session_id,
reply_content["content"],
reply_content["completion_tokens"],
)
)
if reply_content["completion_tokens"] == 0 and len(reply_content["content"]) > 0:
reply = Reply(ReplyType.ERROR, reply_content["content"])
elif reply_content["completion_tokens"] > 0:
self.sessions.session_reply(reply_content["content"], session_id, reply_content["total_tokens"])
reply = Reply(ReplyType.TEXT, reply_content["content"])
else:
reply = Reply(ReplyType.ERROR, reply_content["content"])
logger.debug("[MODELSCOPE_AI] reply {} used 0 tokens.".format(reply_content))
return reply
else:
reply = Reply(ReplyType.ERROR, "Bot不支持处理{}类型的消息".format(context.type))
return reply
def reply_text(self, session: ModelScopeSession, args=None, retry_count=0) -> dict:
"""
call openai's ChatCompletion to get the answer
:param session: a conversation session
:param session_id: session id
:param retry_count: retry count
:return: {}
"""
try:
headers = {
"Content-Type": "application/json",
"Authorization": "Bearer " + self.api_key
}
body = args
body["messages"] = session.messages
# logger.debug("[MODELSCOPE_AI] response={}".format(response))
# logger.info("[MODELSCOPE_AI] reply={}, total_tokens={}".format(response.choices[0]['message']['content'], response["usage"]["total_tokens"]))
res = requests.post(
self.base_url,
headers=headers,
data=json.dumps(body)
)
if res.status_code == 200:
response = res.json()
return {
"total_tokens": response["usage"]["total_tokens"],
"completion_tokens": response["usage"]["completion_tokens"],
"content": response["choices"][0]["message"]["content"]
}
else:
response = res.json()
error = response.get("error")
logger.error(f"[MODELSCOPE_AI] chat failed, status_code={res.status_code}, "
f"msg={error.get('message')}, type={error.get('type')}")
result = {"completion_tokens": 0, "content": "提问太快啦,请休息一下再问我吧"}
need_retry = False
if res.status_code >= 500:
# server error, need retry
logger.warn(f"[MODELSCOPE_AI] do retry, times={retry_count}")
need_retry = retry_count < 2
elif res.status_code == 401:
result["content"] = "授权失败请检查API Key是否正确"
elif res.status_code == 429:
result["content"] = "请求过于频繁,请稍后再试"
need_retry = retry_count < 2
else:
need_retry = False
if need_retry:
time.sleep(3)
return self.reply_text(session, args, retry_count + 1)
else:
return result
except Exception as e:
logger.exception(e)
need_retry = retry_count < 2
result = {"completion_tokens": 0, "content": "我现在有点累了,等会再来吧"}
if need_retry:
return self.reply_text(session, args, retry_count + 1)
else:
return result