mirror of
https://github.com/LiteyukiStudio/marshoai-melo.git
synced 2024-11-23 19:25:03 +08:00
127 lines
5.3 KiB
Python
127 lines
5.3 KiB
Python
import base64
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import mimetypes
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import os
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import json
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import httpx
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from datetime import datetime
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from zhDateTime import DateTime
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from pathlib import Path
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from azure.ai.inference.aio import ChatCompletionsClient
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from azure.ai.inference.models import SystemMessage, UserMessage
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from config import *
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async def get_image_b64(url):
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headers = {
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'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36'
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}
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async with httpx.AsyncClient() as client:
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response = await client.get(url, headers=headers)
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if response.status_code == 200:
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# 获取图片数据
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image_data = response.content
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content_type = response.headers.get('Content-Type')
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if not content_type:
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content_type = mimetypes.guess_type(url)[0]
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image_format = content_type.split('/')[1] if content_type else 'jpeg'
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base64_image = base64.b64encode(image_data).decode('utf-8')
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data_url = f"data:{content_type};base64,{base64_image}"
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return data_url
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else:
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return None
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async def make_chat(client: ChatCompletionsClient, msg, model_name: str):
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return await client.complete(
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messages=msg,
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model=model_name
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# temperature=config.marshoai_temperature,
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# max_tokens=config.marshoai_max_tokens,
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# top_p=config.marshoai_top_p
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)
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# def get_praises():
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# praises_file = store.get_plugin_data_file("praises.json") # 夸赞名单文件使用localstore存储
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# if not os.path.exists(praises_file):
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# init_data = {
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# "like": [
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# {"name":"Asankilp","advantages":"赋予了Marsho猫娘人格，使用vim与vscode为Marsho写了许多代码，使Marsho更加可爱"}
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# ]
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# }
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# with open(praises_file,"w",encoding="utf-8") as f:
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# json.dump(init_data,f,ensure_ascii=False,indent=4)
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# with open(praises_file,"r",encoding="utf-8") as f:
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# data = json.load(f)
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# return data
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# def build_praises():
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# praises = get_praises()
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# result = ["你喜欢以下几个人物，他们有各自的优点："]
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# for item in praises["like"]:
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# result.append(f"名字：{item['name']}，优点：{item['advantages']}")
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# return "\n".join(result)
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# async def save_context_to_json(name: str, context: str):
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# context_dir = store.get_plugin_data_dir() / "contexts"
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# os.makedirs(context_dir, exist_ok=True)
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# file_path = os.path.join(context_dir, f"{name}.json")
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# with open(file_path, 'w', encoding='utf-8') as json_file:
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# json.dump(context, json_file, ensure_ascii=False, indent=4)
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# async def load_context_from_json(name: str):
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# context_dir = store.get_plugin_data_dir() / "contexts"
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# os.makedirs(context_dir, exist_ok=True)
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# file_path = os.path.join(context_dir, f"{name}.json")
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# try:
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# with open(file_path, 'r', encoding='utf-8') as json_file:
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# return json.load(json_file)
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# except FileNotFoundError:
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# return []
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# async def set_nickname(user_id: str, name: str):
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# filename = store.get_plugin_data_file("nickname.json")
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# if not os.path.exists(filename):
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# data = {}
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# else:
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# with open(filename,'r') as f:
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# data = json.load(f)
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# data[user_id] = name
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# with open(filename, 'w') as f:
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# json.dump(data, f, ensure_ascii=False, indent=4)
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# async def get_nicknames():
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# filename = store.get_plugin_data_file("nickname.json")
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# try:
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# with open(filename, 'r', encoding='utf-8') as f:
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# return json.load(f)
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# except FileNotFoundError:
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# return {}
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def get_prompt():
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prompts = ""
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# prompts += config.marshoai_additional_prompt
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# if config.marshoai_enable_praises:
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# praises_prompt = build_praises()
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# prompts += praises_prompt
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# if config.marshoai_enable_time_prompt:
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# current_time = datetime.now().strftime('%Y.%m.%d %H:%M:%S')
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# current_lunar_date = DateTime.now().to_lunar().date_hanzify()[5:] #库更新之前使用切片
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# time_prompt = f"现在的时间是{current_time}，农历{current_lunar_date}。"
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# prompts += time_prompt
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marsho_prompt = marshoai_prompt
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spell = SystemMessage(content=marsho_prompt+prompts).as_dict()
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return spell
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def suggest_solution(errinfo: str) -> str:
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suggestions = {
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"content_filter": "消息已被内容过滤器过滤。请调整聊天内容后重试。",
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"RateLimitReached": "模型达到调用速率限制。请稍等一段时间或联系Bot管理员。",
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"tokens_limit_reached": "请求token达到上限。请重置上下文。",
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"content_length_limit": "请求体过大。请重置上下文。",
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"unauthorized": "Azure凭据无效。请联系Bot管理员。",
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"invalid type: parameter messages.content is of type array but should be of type string.": "聊天请求体包含此模型不支持的数据类型。请重置上下文。",
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"At most 1 image(s) may be provided in one request.": "此模型只能在上下文中包含1张图片。如果此前的聊天已经发送过图片，请重置上下文。"
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}
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for key, suggestion in suggestions.items():
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if key in errinfo:
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return f"\n{suggestion}"
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return ""
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