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Orenoid

BabelDuck

Beginner-friendly AI conversation practice application

TutorialsAIE roadmapTypeScript
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创建于 2024-09-18 · 更新于 2026-10-07 · 今日第 14910 名
主要开发者

Orenoid/BabelDuck 排名第 14,910,有 693 个星标。

同类别比较

Orenoid/BabelDuck 排名第 14,910,此处有 8 个同类条目;DOsinga/deep_learning_cookbook 排名第 14,906。

同类别比较
名称排名指标
leemengtw/deep-learning-resources14,868
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697
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97
简介:
由淺入深的深度學習資源 Collection of deep learning materials for everyone
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694
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简介:
Test prompts for OpenAI's GPT-3 API and the resulting AI-generated texts.
DOsinga/deep_learning_cookbook14,906
语言:
Jupyter Notebook
星标数:
693
分叉数:
334
简介:
Deep Learning Cookbox
jimmyyhwu/tidybot14,917
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693
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AtsushiSakai/MATLABRobotics14,923
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Matlab
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692
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microsoft/agenticai-design-patterns14,960
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690
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dformoso/sklearn-classification14,968
语言:
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星标数:
689
分叉数:
226
简介:
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关键参数与规格
关键参数与规格
参数值
语言TypeScript
类别Tutorials
子类别AIE roadmap
关键词Education
星标数693
分叉数29
贡献者1
创建日期2024-09-18
更新日期2026-10-07
1 天星标数0
7 天星标数0
排名14,910
上次排名14,745
排名变化-165
7 天星标排名14,715
上次 7 天星标排名14,725
7 天星标排名变化10
总星标排名14,987
上次总星标排名14,970
总星标排名变化-17
国家China
README 摘录

English | 简体中文 BabelDuck Website 📖 Introduction BabelDuck is a highly customizable AI conversation practice application designed for language learners of all levels, with a focus on being beginner-friendly and minimizing the barriers and cognitive load of oral expression practice.

常见问题

记录了多少星标和分叉?

Orenoid/BabelDuck 有 693 个星标和 29 个分叉。

仓库排名是多少?

Orenoid/BabelDuck 排名第 14,910。

记录的语言和类别是什么?

Orenoid/BabelDuck 有 693 个星标,语言为 TypeScript,类别为 Tutorials。

哪个仓库排名最接近?

Orenoid/BabelDuck 与 DOsinga/deep_learning_cookbook 比较,后者排名第 14,906,有 693 个星标。

README

English | 简体中文

BabelDuck

Website

📖 Introduction

BabelDuck is a highly customizable AI conversation practice application designed for language learners of all levels, with a focus on being beginner-friendly and minimizing the barriers and cognitive load of oral expression practice.

✨ Key Features

  • Supports common AI chat features including multiple conversation management, custom system prompts, and streaming responses
  • Seek grammar, translation, or expression refinement suggestions from AI without interrupting the current conversation, with customizable quick commands
  • When you have questions about AI suggestions, you can start a sub-conversation for further discussion and seamlessly return to the original conversation afterward
  • Supports voice input and response
  • Integrates multiple LLM AI services with seamless switching
  • Data stored locally to ensure user data privacy and security
  • Supports individual preference settings for different conversations
  • Provides multilingual interface
  • Built-in tutorials

🛠 Deployment

  1. Install Docker
  2. Clone the repository
git clone https://github.com/Orenoid/BabelDuck
  1. Rename .env.example to .env and fill in the configurations
  2. Run Docker container
docker run -d --name babel-duck --env-file .env -p 9000:9000 orenoid/babel-duck:latest
  1. Visit http://localhost:9000 to see it in action

📄 License

This project is licensed under the LICENSE. See the LICENSE file for details.

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