145 lines
5.8 KiB
Python
145 lines
5.8 KiB
Python
from nonebot.typing import T_State
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from nonebot import on_command
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from nonebot.adapters import Message
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from nonebot.params import CommandArg
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from nonebot.permission import SUPERUSER
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#from .acgnapis import *
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from nonebot_plugin_alconna import on_alconna
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from nonebot_plugin_alconna.uniseg import UniMessage, UniMsg
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from arclet.alconna import Alconna, Args, AllParam
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from .util import *
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import traceback
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from azure.ai.inference.aio import ChatCompletionsClient
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from azure.ai.inference.models import UserMessage, AssistantMessage, TextContentItem, ImageContentItem, ImageUrl, CompletionsFinishReason
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from azure.core.credentials import AzureKeyCredential
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from .__init__ import __plugin_meta__
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from .config import config
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from .models import MarshoContext
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changemodel_cmd = on_command("changemodel",permission=SUPERUSER)
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resetmem_cmd = on_command("reset",permission=SUPERUSER)
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setprompt_cmd = on_command("prompt",permission=SUPERUSER)
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praises_cmd = on_command("praises",permission=SUPERUSER)
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add_usermsg_cmd = on_command("usermsg",permission=SUPERUSER)
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add_assistantmsg_cmd = on_command("assistantmsg",permission=SUPERUSER)
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contexts_cmd = on_command("contexts",permission=SUPERUSER)
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marsho_cmd = on_alconna(
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Alconna(
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"marsho",
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Args["text?",AllParam],
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)
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)
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model_name = config.marshoai_default_model
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context = MarshoContext()
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context_limit = 50
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@add_usermsg_cmd.handle()
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async def add_usermsg(arg: Message = CommandArg()):
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if msg := arg.extract_plain_text():
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context.append(UserMessage(content=msg))
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await UniMessage("已添加用户消息").send()
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@add_assistantmsg_cmd.handle()
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async def add_assistantmsg(arg: Message = CommandArg()):
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if msg := arg.extract_plain_text():
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context.append(AssistantMessage(content=msg))
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await UniMessage("已添加助手消息").send()
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@praises_cmd.handle()
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async def praises():
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await UniMessage(build_praises()).send()
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@contexts_cmd.handle()
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async def contexts():
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await UniMessage(str(context.build()[1:])).send()
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# @setprompt_cmd.handle() #用不了了
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# async def setprompt(arg: Message = CommandArg()):
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# global spell, context
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# if prompt := arg.extract_plain_text():
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# spell = SystemMessage(content=prompt)
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# await setprompt_cmd.finish("已设置提示词")
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# else:
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# spell = SystemMessage(content="")
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# context = []
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# await setprompt_cmd.finish("已清除提示词")
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@resetmem_cmd.handle()
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async def resetmem_cmd():
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context.reset()
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context.resetcount()
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await resetmem_cmd.finish("上下文已重置")
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@changemodel_cmd.handle()
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async def changemodel(arg : Message = CommandArg()):
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global model_name
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if model := arg.extract_plain_text():
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model_name = model
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await changemodel_cmd.finish("已切换")
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@marsho_cmd.handle()
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async def marsho(
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message: UniMsg,
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text = None
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):
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token = config.marshoai_token
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endpoint = config.marshoai_azure_endpoint
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#msg = await UniMessage.generate(message=message)
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client = ChatCompletionsClient(
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endpoint=endpoint,
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credential=AzureKeyCredential(token),
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)
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if not text:
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await UniMessage(
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__plugin_meta__.usage+"\n当前使用的模型："+model_name).send()
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return
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if context.count >= context_limit:
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await UniMessage("上下文数量达到阈值。已自动重置上下文。").send()
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context.reset()
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context.resetcount()
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# await UniMessage(str(text)).send()
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try:
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is_support_image_model = model_name.lower() in config.marshoai_support_image_models
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usermsg = [] if is_support_image_model else ""
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for i in message:
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if i.type == "image":
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if is_support_image_model:
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imgurl = i.data["url"]
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picmsg = ImageContentItem(
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image_url=ImageUrl(url=str(await get_image_b64(imgurl)))
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)
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usermsg.append(picmsg)
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else:
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await UniMessage("*此模型不支持图片处理。").send()
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elif i.type == "text":
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if is_support_image_model:
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usermsg.append(TextContentItem(text=i.data["text"]))
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else:
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usermsg += str(i.data["text"])
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response = await client.complete(
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messages=context.build()+[UserMessage(content=usermsg)],
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model=model_name
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)
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#await UniMessage(str(response)).send()
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choice = response.choices[0]
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if choice["finish_reason"] == CompletionsFinishReason.STOPPED:
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context.append(UserMessage(content=usermsg))
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context.append(choice.message)
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context.addcount()
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elif choice["finish_reason"] == CompletionsFinishReason.CONTENT_FILTERED:
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await UniMessage("*已被内容过滤器过滤。*").send()
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#await UniMessage(str(choice)).send()
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await UniMessage(str(choice.message.content)).send(reply_to=True)
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#requests_limit = response.headers.get('x-ratelimit-limit-requests')
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#request_id = response.headers.get('x-request-id')
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#remaining_requests = response.headers.get('x-ratelimit-remaining-requests')
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#remaining_tokens = response.headers.get('x-ratelimit-remaining-tokens')
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#await UniMessage(f""" 剩余token：{remaining_tokens}"""
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# ).send()
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except Exception as e:
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await UniMessage(str(e)+suggest_solution(str(e))).send()
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# await UniMessage(str(e.reason)).send()
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traceback.print_exc()
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return
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