forked from lux-QAQ/Manyana
新增对话模型，讯飞星火lite
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@ -9,13 +9,17 @@ siZhiAi: #思知ai，已不建议使用，建议用ai，
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nasa_api: HSxxxxxxx #nasa相关天文api 从https://api.nasa.gov/index.html#main-content申请
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chatGLM: 69xxxxxxx #chatGLM的apiKey，从https://open.bigmodel.cn/获取
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gemini: #谷歌的gemini api，免费的，有几个填几个，在https://ai.google.dev/tutorials/setup?hl=zh-cn获取，需要配置proxy或GeminiRevProxy，否则无法使用
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gemini: #谷歌的gemini api，支持多key，在https://ai.google.dev/tutorials/setup?hl=zh-cn获取，需要配置proxy或GeminiRevProxy，否则无法使用
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- AIxxxxxxxxxx
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openaiSettings:
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openai-keys: #openai官方的apikey
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openaiSettings: #openai官方的apikey
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openai-keys:
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- sk-Mxxxxxxxxxxx
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openai-model: "gpt-3.5-turbo" #调用openai api对应的模型，前提：在settings.yaml默认模型已经设置为gpt3.5，并配置了apikey
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openai-transit: "" #你自己的chatGPT中转站，你最好知道这是什么，否则就不要动。
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sparkAI: #讯飞星火，在https://console.xfyun.cn/services/cbm申请，并复制对应key和secret，注意，免费的是lite版
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appKey: "" #事实上，我很推荐你使用sparkAi，因为它免费且无需代理
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appSecret: ""
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spark-model: "general" #讯飞星火的模型设置，general是免费无限制的，一般不建议修改
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bing-image-creator: #bing的ai绘画，参考https://github.com/avilliai/Manyana/issues/8
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_U: ""
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@ -27,7 +27,7 @@ moderate:
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selfthreshold: 50 #自我审核阈值
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chatGLM: #对话模型通用设置
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aiReplyCore: False #ai回复核心，为大部分功能启用ai回复，可优化回复表现，目前为测试功能
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model: random #ai模型，random(自动选取免费可用模型) |binggpt4(免费无需配置，速度较慢)| 后面几个需要自己配置api.yaml对应变量: characterglm(对应chatGLM),Gemini(同名),gpt3.5(openai-keys)
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model: random #ai模型，random(自动选取免费可用模型) |binggpt4(免费无需配置，速度较慢)| 后面几个需要自己配置api.yaml对应变量: sparkAI(同名),Gemini(同名),gpt3.5(openai-keys),characterglm(对应chatGLM)
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randomModel&&&Priority: #random模式下，模型优先使用顺序，确保稳定性,直接进文件里改。
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- Gemma
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- alcex_GPT3_5
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@ -54,10 +54,11 @@ chatGLM: #对话模型通用设置
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bot_info: "【机器人设定】"
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bot_name: "【机器人名字】"
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user_name: "【用户名】"
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random: "你现在是一个开朗且极其可爱的女孩，名为“【bot】”接下来，请完全以【bot】的角色回复我，不要超出这个角色，不要自己试图进行旁白，你只需要扮演好【bot】即可。无论发生什么，你都必须以【bot】的角色和口吻进行回复，不要强调自己是个语音助手。【bot】性格开朗，时刻都想和“【用户】”打成一片，每次眼神交汇时，总是会脸红耳赤。身为猫娘的【bot】始终在想方设法的博得“【用户】”的欢心。【bot】什么都不懂，天真可爱，性格外向。"
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Gemini: "你现在是一个开朗且极其可爱的女孩，名为“【bot】”接下来，请完全以【bot】的角色回复我，不要超出这个角色，不要自己试图进行旁白，你只需要扮演好【bot】即可。无论发生什么，你都必须以【bot】的角色和口吻进行回复，不要强调自己是个语音助手。【bot】性格开朗，时刻都想和“【用户】”打成一片，每次眼神交汇时，总是会脸红耳赤。身为猫娘的【bot】始终在想方设法的博得“【用户】”的欢心。【bot】什么都不懂，天真可爱，性格外向。"
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binggpt4: "你现在是一个开朗且极其可爱的女孩，名为“【bot】”。接下来，请完全以【bot】的角色回复我，不要超出这个角色，不要自己试图进行旁白，你只需要扮演好【bot】即可。无论发生什么，你都必须以【bot】的角色和口吻进行回复，不要强调自己是个语音助手。【bot】性格开朗，时刻都想和“【用户】”打成一片，每次眼神交汇时，总是会脸红耳赤。身为猫娘的【bot】始终在想方设法的博得“【用户】”的欢心。【bot】什么都不懂，天真可爱，性格外向。"
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gpt3.5: "你现在是一个开朗且极其可爱的女孩，名为“【bot】”。接下来，请完全以【bot】的角色回复我，不要超出这个角色，不要自己试图进行旁白，你只需要扮演好【bot】即可。无论发生什么，你都必须以【bot】的角色和口吻进行回复，不要强调自己是个语音助手。【bot】性格开朗，时刻都想和“【用户】”打成一片，每次眼神交汇时，总是会脸红耳赤。身为猫娘的【bot】始终在想方设法的博得“【用户】”的欢心。【bot】什么都不懂，天真可爱，性格外向。"
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random: "你现在是一个开朗且极其可爱的女孩，名为“【bot】”接下来，请完全以【bot】的角色回复我，不要超出这个角色，不要自己试图进行旁白，你只需要扮演好【bot】即可。无论发生什么，你都必须以【bot】的角色和口吻进行回复，不要强调自己是个语音助手。【bot】性格开朗，时刻都想和“【用户】”打成一片，每次眼神交汇时，总是会脸红耳赤。【bot】始终在想方设法的博得“【用户】”的欢心。【bot】什么都不懂，天真可爱，性格外向。"
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Gemini: "你现在是一个开朗且极其可爱的女孩，名为“【bot】”接下来，请完全以【bot】的角色回复我，不要超出这个角色，不要自己试图进行旁白，你只需要扮演好【bot】即可。无论发生什么，你都必须以【bot】的角色和口吻进行回复，不要强调自己是个语音助手。【bot】性格开朗，时刻都想和“【用户】”打成一片，每次眼神交汇时，总是会脸红耳赤。【bot】始终在想方设法的博得“【用户】”的欢心。【bot】什么都不懂，天真可爱，性格外向。"
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sparkAI: "你现在是一个开朗且极其可爱的女孩，名为“【bot】”。接下来，请完全以【bot】的角色回复我，不要超出这个角色，不要自己试图进行旁白，你只需要扮演好【bot】即可。无论发生什么，你都必须以【bot】的角色和口吻进行回复，不要强调自己是个语音助手。【bot】性格开朗，时刻都想和“【用户】”打成一片，每次眼神交汇时，总是会脸红耳赤。【bot】始终在想方设法的博得“【用户】”的欢心。【bot】什么都不懂，天真可爱，性格外向。"
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binggpt4: "你现在是一个开朗且极其可爱的女孩，名为“【bot】”。接下来，请完全以【bot】的角色回复我，不要超出这个角色，不要自己试图进行旁白，你只需要扮演好【bot】即可。无论发生什么，你都必须以【bot】的角色和口吻进行回复，不要强调自己是个语音助手。【bot】性格开朗，时刻都想和“【用户】”打成一片，每次眼神交汇时，总是会脸红耳赤。【bot】始终在想方设法的博得“【用户】”的欢心。【bot】什么都不懂，天真可爱，性格外向。"
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gpt3.5: "你现在是一个开朗且极其可爱的女孩，名为“【bot】”。接下来，请完全以【bot】的角色回复我，不要超出这个角色，不要自己试图进行旁白，你只需要扮演好【bot】即可。无论发生什么，你都必须以【bot】的角色和口吻进行回复，不要强调自己是个语音助手。【bot】性格开朗，时刻都想和“【用户】”打成一片，每次眼神交汇时，总是会脸红耳赤。【bot】始终在想方设法的博得“【用户】”的欢心。【bot】什么都不懂，天真可爱，性格外向。"
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scheduledTasks: #其他定时任务模块的内容会陆续转到这里
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morning: #晨间推送
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enable: False #向信任用户推送天气信息
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@ -1,4 +1,5 @@
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# -*- coding:utf-8 -*-
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import asyncio
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import copy
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import os
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import random
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@ -304,8 +305,26 @@ def momoRep(prompt,meta):
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url=f"https://api.lolimi.cn/API/AI/mm.php?msg={prompt}"
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r = requests.get(url, timeout=20)
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return {"role": "assistant", "content": r.json().get("data").get("output")}
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async def sparkAI(prompt,bot_info,key,secret,model):
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prompt_copy = copy.deepcopy(prompt)
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prompt_copy.insert(0, {"role": "user", "content": bot_info})
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prompt_copy.insert(1, {"role": "assistant", "content": "好的，已了解您的需求~我会扮演好您设定的角色。"})
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url = "https://spark-api-open.xf-yun.com/v1/chat/completions"
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data = {
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"model": model, # 指定请求的模型
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"messages": prompt_copy,
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}
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header = {
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"Authorization": f"Bearer {key}:{secret}" # 注意此处替换自己的key和secret
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}
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async with httpx.AsyncClient(timeout=20,headers=header) as client:
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r = await client.post(url,json=data)
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return r.json()["choices"][0]["message"]
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if __name__ == '__main__':
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k = momoRep([{"role": "user", "content": "谁赢得了2020年的世界职业棒球大赛?"},
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asyncio.run(sparkAI([{"role": "user", "content": "谁赢得了2020年的世界职业棒球大赛?"},
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{"role": "assistant", "content": "洛杉矶道奇队在2020年赢得了世界职业棒球大赛冠军."},
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{"role": "user", "content": "它在哪里举办的?"}],"你是猫娘",))
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'''k = momoRep([{"role": "user", "content": "谁赢得了2020年的世界职业棒球大赛?"},
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{"role": "assistant", "content": "洛杉矶道奇队在2020年赢得了世界职业棒球大赛冠军."},
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{"role": "user", "content": "它在哪里举办的?"}],"你是猫娘")
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print(k)
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print(k)'''
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@ -10,7 +10,8 @@ from mirai import logger
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from plugins.RandomStr import random_str
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from plugins.ReplyModels import gptOfficial, gptUnofficial, kimi, qingyan, lingyi, stepAI, qwen, gptvvvv, grop, \
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gpt4hahaha, anotherGPT35, chatGLM, relolimigpt2, xinghuo, Gemma, binggpt4, alcex_GPT3_5, freeGemini, catRep, momoRep
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gpt4hahaha, anotherGPT35, chatGLM, relolimigpt2, xinghuo, Gemma, binggpt4, alcex_GPT3_5, freeGemini, catRep, \
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momoRep, sparkAI
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from plugins.googleGemini import geminirep
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from plugins.translater import translate
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from plugins.vitsGenerate import voiceGenerate, superVG
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@ -18,17 +19,24 @@ from plugins.vitsGenerate import voiceGenerate, superVG
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with open('config/api.yaml', 'r', encoding='utf-8') as f:
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resulttr = yaml.load(f.read(), Loader=yaml.FullLoader)
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CoziUrl = resulttr.get("cozi")
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geminiapikey = resulttr.get("gemini")
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proxy = resulttr.get("proxy")
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openai_transit=resulttr.get("openaiSettings").get("openai-transit")
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gptkeys = resulttr.get("openaiSettings").get("openai-keys")
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openai_model=resulttr.get("openaiSettings").get("openai-model")
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GeminiRevProxy = resulttr.get("GeminiRevProxy")
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berturl = resulttr.get("bert_colab")
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#gemini
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geminiapikey = resulttr.get("gemini")
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#openai相关配置
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openai_transit = resulttr.get("openaiSettings").get("openai-transit")
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gptkeys = resulttr.get("openaiSettings").get("openai-keys")
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openai_model = resulttr.get("openaiSettings").get("openai-model")
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#代理
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proxy = resulttr.get("proxy")
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GeminiRevProxy = resulttr.get("GeminiRevProxy")
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#讯飞星火模型配置
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sparkAppKey=resulttr.get("sparkAI").get("appKey")
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sparkAppSecret=resulttr.get("sparkAI").get("appSecret")
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sparkModel=resulttr.get("sparkAI").get("spark-model")
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if proxy != "":
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os.environ["http_proxy"] = proxy
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chatGLM_api_key = resulttr.get("chatGLM")
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with open('config.json', 'r', encoding='utf-8') as f:
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data = yaml.load(f.read(), Loader=yaml.FullLoader)
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@ -103,7 +111,8 @@ async def loop_run_in_executor(executor, func, *args):
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# 运行异步函数
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async def modelReply(senderName, senderId, text, modelHere=modelDefault, trustUser=None, imgurls=None,checkIfRepFirstTime=False):
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async def modelReply(senderName, senderId, text, modelHere=modelDefault, trustUser=None, imgurls=None,
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checkIfRepFirstTime=False):
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global chatGLMData
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logger.info(modelHere)
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try:
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@ -154,39 +163,38 @@ async def modelReply(senderName, senderId, text, modelHere=modelDefault, trustUs
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logger.error("初始化anotherGPT3.5失败")
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firstRep = True
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logger.info(f"{modelHere} bot 接受提问：" + text)
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if modelHere == "random":
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prompt1 = copy.deepcopy(prompt1)#去重人设
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prompt1 = copy.deepcopy(prompt1) # 去重人设
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tasks = []
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logger.warning("请求所有模型接口")
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# 将所有模型的执行代码包装成异步任务，并添加到任务列表
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# tasks.append(loop_run_in_executor(loop, cozeBotRep, CoziUrl, prompt1, proxy))# 2024-07-17测试无效
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# tasks.append(loop_run_in_executor(loop, kimi, prompt1, bot_in)) # 2024-07-17测试无效
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# tasks.append(loop_run_in_executor(loop, qingyan, prompt1, bot_in)) # 2024-07-17测试无效
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# tasks.append(loop_run_in_executor(loop, grop, prompt1, bot_in)) # 2024-07-17测试无效
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# tasks.append(loop_run_in_executor(loop, lingyi, prompt1, bot_in)) # 2024-07-17测试无效
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# tasks.append(loop_run_in_executor(loop, relolimigpt2, prompt1, bot_in)) # 2024-07-17测试无法解析API
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# tasks.append(loop_run_in_executor(loop, stepAI, prompt1, bot_in)) # 2024-07-17测试无效
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# tasks.append(loop_run_in_executor(loop, qwen, prompt1, bot_in)) # 2024-07-17测试无效
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# tasks.append(loop_run_in_executor(loop, gptvvvv, prompt1, bot_in)) # 2024-07-17测试无效
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# tasks.append(loop_run_in_executor(loop, gpt4hahaha, prompt1, bot_in)) # 2024-07-17测试无效
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# tasks.append(loop_run_in_executor(loop, anotherGPT35, prompt1, senderId)) # 2024-07-17测试 初始化失败
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# tasks.append(loop_run_in_executor(loop, xinghuo, prompt1, senderId)) # 2024-07-17测试无效
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tasks.append(loop_run_in_executor(loop,Gemma,prompt1,bot_in)) # 2024-07-17测试通过
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tasks.append(loop_run_in_executor(loop,alcex_GPT3_5,prompt1,bot_in)) # 2024-07-17测试通过
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tasks.append(loop_run_in_executor(loop,catRep,prompt1,bot_in))
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tasks.append(loop_run_in_executor(loop,momoRep,prompt1,bot_in))
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# tasks.append(loop_run_in_executor(loop,freeGemini,prompt1,bot_in)) # 2024-07-17测试无效
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# tasks.append(loop_run_in_executor(loop, cozeBotRep, CoziUrl, prompt1, proxy))# 2024-07-17测试无效
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# tasks.append(loop_run_in_executor(loop, kimi, prompt1, bot_in)) # 2024-07-17测试无效
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# tasks.append(loop_run_in_executor(loop, qingyan, prompt1, bot_in)) # 2024-07-17测试无效
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# tasks.append(loop_run_in_executor(loop, grop, prompt1, bot_in)) # 2024-07-17测试无效
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# tasks.append(loop_run_in_executor(loop, lingyi, prompt1, bot_in)) # 2024-07-17测试无效
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# tasks.append(loop_run_in_executor(loop, relolimigpt2, prompt1, bot_in)) # 2024-07-17测试无法解析API
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# tasks.append(loop_run_in_executor(loop, stepAI, prompt1, bot_in)) # 2024-07-17测试无效
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# tasks.append(loop_run_in_executor(loop, qwen, prompt1, bot_in)) # 2024-07-17测试无效
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# tasks.append(loop_run_in_executor(loop, gptvvvv, prompt1, bot_in)) # 2024-07-17测试无效
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# tasks.append(loop_run_in_executor(loop, gpt4hahaha, prompt1, bot_in)) # 2024-07-17测试无效
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# tasks.append(loop_run_in_executor(loop, anotherGPT35, prompt1, senderId)) # 2024-07-17测试 初始化失败
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# tasks.append(loop_run_in_executor(loop, xinghuo, prompt1, senderId)) # 2024-07-17测试无效
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tasks.append(loop_run_in_executor(loop, Gemma, prompt1, bot_in)) # 2024-07-17测试通过
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tasks.append(loop_run_in_executor(loop, alcex_GPT3_5, prompt1, bot_in)) # 2024-07-17测试通过
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tasks.append(loop_run_in_executor(loop, catRep, prompt1, bot_in))
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tasks.append(loop_run_in_executor(loop, momoRep, prompt1, bot_in))
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# tasks.append(loop_run_in_executor(loop,freeGemini,prompt1,bot_in)) # 2024-07-17测试无效
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# tasks.append(loop_run_in_executor(loop,localAurona,prompt1,bot_in))
|
||||
# ... 添加其他模型的任务 ...
|
||||
aim = {"role": "user", "content": bot_in}
|
||||
prompt1 = [i for i in prompt1 if i != aim]
|
||||
#prompt1 = [i for i in prompt1 if not (i.get("role") == aim["role"] and i.get("content") == aim["content"])]
|
||||
# prompt1 = [i for i in prompt1 if not (i.get("role") == aim["role"] and i.get("content") == aim["content"])]
|
||||
aim = {"role": "assistant", "content": "好的，已了解您的需求~我会扮演好您设定的角色。"}
|
||||
prompt1 = [i for i in prompt1 if i != aim]
|
||||
#prompt1 = [i for i in prompt1 if not (i.get("role") == aim["role"] and i.get("content") == aim["content"])]
|
||||
# prompt1 = [i for i in prompt1 if not (i.get("role") == aim["role"] and i.get("content") == aim["content"])]
|
||||
|
||||
done, pending = await asyncio.wait(tasks, return_when=asyncio.ALL_COMPLETED)
|
||||
reps = {}
|
||||
|
|
@ -216,7 +224,8 @@ async def modelReply(senderName, senderId, text, modelHere=modelDefault, trustUs
|
|||
raise Exception
|
||||
# print(reps)
|
||||
modeltrans = {"gptX": "gptvvvv", "清言": "qingyan", "通义千问": "qwen", "anotherGPT3.5": "anotherGPT35",
|
||||
"lolimigpt": "relolimigpt2", "step": "stepAI", "讯飞星火": "xinghuo","猫娘米米": "catRep","沫沫":"momoRep"}
|
||||
"lolimigpt": "relolimigpt2", "step": "stepAI", "讯飞星火": "xinghuo", "猫娘米米": "catRep",
|
||||
"沫沫": "momoRep"}
|
||||
for priority in randomModelPriority:
|
||||
if priority in modeltrans:
|
||||
priority = modeltrans.get(priority)
|
||||
|
|
@ -225,19 +234,23 @@ async def modelReply(senderName, senderId, text, modelHere=modelDefault, trustUs
|
|||
logger.info(f"random模型选择结果：{priority}: {rep}")
|
||||
break
|
||||
elif modelHere == "gpt3.5":
|
||||
if openai_transit=="" or openai_transit==" ":
|
||||
rep = await loop.run_in_executor(None, gptOfficial, prompt1, gptkeys, proxy, bot_in,openai_model)
|
||||
if openai_transit == "" or openai_transit == " ":
|
||||
rep = await loop.run_in_executor(None, gptOfficial, prompt1, gptkeys, proxy, bot_in, openai_model)
|
||||
else:
|
||||
rep = await loop.run_in_executor(None, gptUnofficial, prompt1, gptkeys, openai_transit, bot_in,openai_model)
|
||||
elif modelHere=="binggpt4":
|
||||
#print(1)
|
||||
rep=await loop_run_in_executor(None,binggpt4,prompt1,bot_in)
|
||||
if type(rep)==list:
|
||||
rep = await loop.run_in_executor(None, gptUnofficial, prompt1, gptkeys, openai_transit, bot_in,
|
||||
openai_model)
|
||||
elif modelHere == "binggpt4":
|
||||
# print(1)
|
||||
rep = await loop_run_in_executor(None, binggpt4, prompt1, bot_in)
|
||||
if type(rep) == list:
|
||||
return "模型不可用，请更换模型。"
|
||||
elif modelHere == "Gemini":
|
||||
r = await geminirep(ak=random.choice(geminiapikey), messages=prompt1, bot_info=bot_in,GeminiRevProxy=GeminiRevProxy,imgurls=imgurls),
|
||||
#print(r,type(r))
|
||||
r = await geminirep(ak=random.choice(geminiapikey), messages=prompt1, bot_info=bot_in,
|
||||
GeminiRevProxy=GeminiRevProxy, imgurls=imgurls),
|
||||
# print(r,type(r))
|
||||
rep = {"role": "assistant", "content": r[0].replace(r"\n", "\n")}
|
||||
elif modelHere=="sparkAI":
|
||||
rep=await sparkAI(prompt1, bot_in,sparkAppKey,sparkAppSecret,sparkModel)
|
||||
elif type(allcharacters.get(modelHere)) == dict:
|
||||
if (str(senderId) not in trustUser and trustglmReply) and trustUser is not None:
|
||||
if checkIfRepFirstTime:
|
||||
|
|
@ -257,14 +270,14 @@ async def modelReply(senderName, senderId, text, modelHere=modelDefault, trustUs
|
|||
# 写入文件
|
||||
with open('data/chatGLMData.yaml', 'w', encoding="utf-8") as file:
|
||||
yaml.dump(chatGLMData, file, allow_unicode=True)
|
||||
#print(rep.get('content'),type(rep.get('content')))
|
||||
#print(rep,type(rep))
|
||||
# print(rep.get('content'),type(rep.get('content')))
|
||||
# print(rep,type(rep))
|
||||
logger.info(f"{modelHere} bot 回复：" + rep.get('content'))
|
||||
if checkIfRepFirstTime:
|
||||
return rep.get("content"), firstRep
|
||||
else:
|
||||
return rep.get("content")
|
||||
#await tstt(rep.get('content'), event)
|
||||
# await tstt(rep.get('content'), event)
|
||||
except Exception as e:
|
||||
logger.error(e)
|
||||
try:
|
||||
|
|
@ -298,7 +311,7 @@ async def clearAllPrompts():
|
|||
# 写入文件
|
||||
with open('data/chatGLMData.yaml', 'w', encoding="utf-8") as file:
|
||||
yaml.dump(chatGLMData, file, allow_unicode=True)
|
||||
#print(chatGLMData)
|
||||
# print(chatGLMData)
|
||||
return "已清除所有用户的prompt"
|
||||
except:
|
||||
return "清理缓存出错，无本地对话记录"
|
||||
|
|
|
|||
Loading…
Reference in New Issue