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koishi-plugin-chatluna-cohere-playground-adapter

v0.0.7

Published

Chatluna 的 Cohere 适配器,无甲,免费量大管饱,输出速度快,智商低,瑟瑟文笔逆天,适合纯瑟瑟母猪流用户。

Downloads

443

Readme

koishi-plugin-chatluna-cohere-playground-adapter

npm

🎐 介绍

Chatluna 的 Cohere 适配器,无甲,免费量大管饱,输出速度快,智商低,瑟瑟文笔逆天,适合纯瑟瑟母猪流用户。

🎉 安装

前往 Koishi 插件市场添加该插件即可。

🌈 使用

  1. 获取 API Key:
  • 访问 Cohere 注册并登录。
  • 登录后前往 Cohere API Key 页面,复制 Trial key
    • Trial key 形如 iD35z8XuYzI1KKGoQ9EdzOSoV0SKPWLCHrUv61OD
  1. 配置插件: 在本插件请求设置中添加获取到的 Trial key

  2. 开始使用! 现在您可以通过 Chatluna 与 Cohere AI 进行对话了。

  • 仅推荐使用 command-r-plus 模型,其他模型不予置评。
  • Cohere 每个账号每月有 1000 次免费请求,超出后将无法使用。
    • 小贴士:使用 Gmail 临时邮箱 注册 Cohere 账号,以获取更多免费请求次数。

⚙️ 配置项

请求设置

  • apiKeys - Cohere API Keys。

模型设置

  • k - k 参数。确保在每个步骤中只考虑最有可能的 k 个 tokens。默认 0,范围 0-500。
  • p - p 参数。确保在每一步生成时,只考虑总概率质量为 p 的可能性最大的 tokens。如果 k 和 p 都启用,则 p 在 k 之后执行。默认 0.75。范围 0.01-0.99。
  • max_tokens - 最大输出 tokens。默认 4000,范围 1-4000。
  • temperature - 回复温度,越高越随机。随机性可以通过增加 p 参数的值来进一步最大化。范围 0-1。
  • frequencyPenalty - 频率惩罚。用于减少生成的重复性。值越高,越随机,且跟 tokens 重复出现的次数成比例。默认 0,范围 0-1。
  • presencePenalty - 存在惩罚。用于减少生成的重复性。与频率惩罚类似,但这种惩罚适用于所有已经出现的 tokens,无论它们的频率(出现次数)如何。默认 0,范围 0-1。
  • safetyMode - 安全模式。可选值:CONTEXTUAL, STRICT, NONE。默认 NONE。安全模式暂时不能与文档列表一起配置。
  • documents - 文档列表。一个模型可以引用的相关文档列表,以生成更准确的回复。每个文档都是一个字符串-字符串字典。示例: [ {“title”:“高企鹅”,“text”:“帝企鹅最高。" }, {“title”:“企鹅栖息地”,“text”:“帝企鹅只生活在南极洲。" }, ]

🍧 致谢

  • Koishi - 强大的跨平台机器人框架
  • Cohere - 提供先进 NLP 技术的 Cohere AI

✨ 许可证

MIT License © 2024