add repositories (Updated on January 23, 2025)

README.md

@@ -15,28 +15,16 @@ Your contributions are always welcome! Before contributing, please read [the gui
 
 ## The latest additions 🎉
 
-**Chatbots**
- * [Upsonic](https://github.com/upsonic/upsonic) - We do NOT and WILL not have any Crypto Projects, they are a complete SCAM | Task oriented AI agent framework for digital workers and vertical AI agents
-
-
-**Reimplementations**
- * [chatllama](https://github.com/juncongmoo/chatllama) - ChatLLaMA 📢 Open source implementation for LLaMA-based ChatGPT runnable in a single GPU. 15x faster training process than ChatGPT
-
-
-**Tutorials**
- * [e2b-cookbook](https://github.com/e2b-dev/e2b-cookbook) - Examples of using E2B
-
-
-**NLP**
- * [Bob](https://github.com/ripperhe/bob) - Bob 是一款 macOS 平台的翻译和 OCR 软件。
- * [prism](https://github.com/echolabsdev/prism) - A unified interface for working with LLMs in Laravel
+**Prompts**
+ * [LangChain](https://github.com/tryagi/langchain) - C# implementation of LangChain. We try to be as close to the original as possible in terms of abstractions, but are open to new entities.
+ * [Kiln](https://github.com/kiln-ai/kiln) - The easiest tool for fine-tuning LLM models, synthetic data generation, and collaborating on datasets.
 
 
-**Unity**
- * [OpenAI](https://github.com/macpaw/openai) - Swift community driven package for OpenAI public API
+**Langchain**
+ * [openai-quickstart](https://github.com/djangopeng/openai-quickstart) - A comprehensive guide to understanding and implementing large language models with hands-on examples using LangChain for GenAI applications.
 
 
-_Updated on January 20, 2025_ (A total of 1965 repositories listed.)
+_Updated on January 23, 2025_ (A total of 1968 repositories listed.)
 
 ## Table of contents
 
@@ -288,6 +276,8 @@ _Updated on January 20, 2025_ (A total of 1965 repositories listed.)
  * [langwatch](https://github.com/langwatch/langwatch) - The ultimate LLM Ops platform - Monitoring, Analytics, Evaluations, Datasets and Prompt Optimization ✨
  * [phoenix](https://github.com/arize-ai/phoenix) - AI Observability & Evaluation
  * [DataDreamer](https://github.com/datadreamer-dev/datadreamer) - DataDreamer: Prompt. Generate Synthetic Data. Train & Align Models.    🤖💤
+ * [LangChain](https://github.com/tryagi/langchain) - C# implementation of LangChain. We try to be as close to the original as possible in terms of abstractions, but are open to new entities.
+ * [Kiln](https://github.com/kiln-ai/kiln) - The easiest tool for fine-tuning LLM models, synthetic data generation, and collaborating on datasets.
 
 
 ## Chatbots
@@ -1428,6 +1418,7 @@ _Updated on January 20, 2025_ (A total of 1965 repositories listed.)
  * [lsp-ai](https://github.com/silasmarvin/lsp-ai) - LSP-AI is an open-source language server that serves as a backend for AI-powered functionality, designed to assist and empower software engineers, not replace them.
  * [generative-ai](https://github.com/genieincodebottle/generative-ai) - Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation.
  * [paperless-ai](https://github.com/clusterzx/paperless-ai) - An automated document analyzer for Paperless-ngx using OpenAI API and Ollama (Mistral, llama, phi 3, gemma 2) to automatically analyze and tag your documents.
+ * [openai-quickstart](https://github.com/djangopeng/openai-quickstart) - A comprehensive guide to understanding and implementing large language models with hands-on examples using LangChain for GenAI applications.
 
 
 ## Unity

awesome-ChatGPT-repositories.json

@@ -5526,6 +5526,70 @@
                     "zh-hans": "DataDreamer：提示。生成合成数据。训练和对齐模型。🤖💤",
                     "zh-hant": "DataDreamer：提示。生成合成數據。訓練和對齊模型。🤖💤"
                 }
+            },
+            "https://github.com/tryagi/langchain": {
+                "repository_name": "LangChain",
+                "user_name": "tryAGI",
+                "language": "C#",
+                "license": "MIT License",
+                "description": "C# implementation of LangChain. We try to be as close to the original as possible in terms of abstractions, but are open to new entities.",
+                "topics": [
+                    "abstractions",
+                    "agents",
+                    "ai",
+                    "artificial-intelligence",
+                    "chain",
+                    "csharp",
+                    "joi",
+                    "langchain",
+                    "langchain-csharp",
+                    "langchain-dotnet",
+                    "llm",
+                    "llms",
+                    "openai",
+                    "prompt",
+                    "sdk",
+                    "semantic",
+                    "semantic-kernel",
+                    "tryagi"
+                ],
+                "multilingual_descriptions": {
+                    "en": "C# implementation of LangChain. We try to be as close to the original as possible in terms of abstractions, but are open to new entities.",
+                    "ja": "LangChainのC#実装。抽象化に関して可能な限りオリジナルに近づこうと努めていますが、新しいエンティティにもオープンです。",
+                    "zh-hans": "LangChain的C#实现。我们尽量保持与原始版本的抽象接近，但也愿意接受新的实体。",
+                    "zh-hant": "LangChain的C#實現。我們試圖在抽象方面盡可能接近原始版本，但也願意接受新實體。LangChain的C#實現。我們試圖在抽象方面盡可能接近原始版本，但也願意接受新實體。"
+                }
+            },
+            "https://github.com/kiln-ai/kiln": {
+                "repository_name": "Kiln",
+                "user_name": "Kiln-AI",
+                "language": "Python",
+                "license": null,
+                "description": "The easiest tool for fine-tuning LLM models, synthetic data generation, and collaborating on datasets.",
+                "topics": [
+                    "ai",
+                    "chain-of-thought",
+                    "collaboration",
+                    "dataset-generation",
+                    "fine-tuning",
+                    "machine-learning",
+                    "macos",
+                    "ml",
+                    "ollama",
+                    "openai",
+                    "prompt",
+                    "prompt-engineering",
+                    "python",
+                    "rlhf",
+                    "synthetic-data",
+                    "windows"
+                ],
+                "multilingual_descriptions": {
+                    "en": "The easiest tool for fine-tuning LLM models, synthetic data generation, and collaborating on datasets.",
+                    "ja": "LLMモデルの微調整、合成データ生成、およびデータセットの共同作業に最適なツール。",
+                    "zh-hans": "用于微调LLM模型、合成数据生成和数据集协作的最简单工具。",
+                    "zh-hant": "微調LLM模型、合成數據生成和協作數據集的最簡單工具。"
+                }
             }
         },
         "Chatbots": {
@@ -31301,6 +31365,20 @@
                     "zh-hans": "使用OpenAI API和Ollama（Mistral，llama，phi 3，gemma 2）的自动文档分析器，可自动分析和标记您的文件。",
                     "zh-hant": "一個自動文件分析器，使用OpenAI API和Ollama（Mistral，llama，phi 3，gemma 2）來自動分析和標記您的文件。"
                 }
+            },
+            "https://github.com/djangopeng/openai-quickstart": {
+                "repository_name": "openai-quickstart",
+                "user_name": "DjangoPeng",
+                "language": "Jupyter Notebook",
+                "license": "Apache License 2.0",
+                "description": "A comprehensive guide to understanding and implementing large language models with hands-on examples using LangChain for GenAI applications.",
+                "topics": [],
+                "multilingual_descriptions": {
+                    "en": "A comprehensive guide to understanding and implementing large language models with hands-on examples using LangChain for GenAI applications.",
+                    "ja": "LangChainを使用したGenAIアプリケーションのための大規模言語モデルの理解と実装に関する包括的なガイドと、実践的な例を紹介します。",
+                    "zh-hans": "一份全面指南，帮助理解和实施大型语言模型，并使用LangChain进行GenAI应用的实际示例。",
+                    "zh-hant": "一個全面的指南，以實際示例使用LangChain來理解和實施大型語言模型，適用於GenAI應用程式。"
+                }
             }
         },
         "Unity": {

docs/README.en.md

@@ -15,28 +15,16 @@ Your contributions are always welcome! Before contributing, please read [the gui
 
 ## The latest additions 🎉
 
-**Chatbots**
- * [Upsonic](https://github.com/upsonic/upsonic) - We do NOT and WILL not have any Crypto Projects, they are a complete SCAM | Task oriented AI agent framework for digital workers and vertical AI agents
-
-
-**Reimplementations**
- * [chatllama](https://github.com/juncongmoo/chatllama) - ChatLLaMA 📢 Open source implementation for LLaMA-based ChatGPT runnable in a single GPU. 15x faster training process than ChatGPT
-
-
-**Tutorials**
- * [e2b-cookbook](https://github.com/e2b-dev/e2b-cookbook) - Examples of using E2B
-
-
-**NLP**
- * [Bob](https://github.com/ripperhe/bob) - Bob is a translation and OCR software for macOS platform.
- * [prism](https://github.com/echolabsdev/prism) - A unified interface for working with LLMs in Laravel
+**Prompts**
+ * [LangChain](https://github.com/tryagi/langchain) - C# implementation of LangChain. We try to be as close to the original as possible in terms of abstractions, but are open to new entities.
+ * [Kiln](https://github.com/kiln-ai/kiln) - The easiest tool for fine-tuning LLM models, synthetic data generation, and collaborating on datasets.
 
 
-**Unity**
- * [OpenAI](https://github.com/macpaw/openai) - Swift community driven package for OpenAI public API
+**Langchain**
+ * [openai-quickstart](https://github.com/djangopeng/openai-quickstart) - A comprehensive guide to understanding and implementing large language models with hands-on examples using LangChain for GenAI applications.
 
 
-_Updated on January 20, 2025_ (A total of 1965 repositories listed.)
+_Updated on January 23, 2025_ (A total of 1968 repositories listed.)
 
 ## Table of contents
 
@@ -288,6 +276,8 @@ _Updated on January 20, 2025_ (A total of 1965 repositories listed.)
  * [langwatch](https://github.com/langwatch/langwatch) - The ultimate LLM Ops platform - Monitoring, Analytics, Evaluations, Datasets and Prompt Optimization ✨
  * [phoenix](https://github.com/arize-ai/phoenix) - AI Observability & Evaluation
  * [DataDreamer](https://github.com/datadreamer-dev/datadreamer) - DataDreamer: Prompt. Generate Synthetic Data. Train & Align Models.    🤖💤
+ * [LangChain](https://github.com/tryagi/langchain) - C# implementation of LangChain. We try to be as close to the original as possible in terms of abstractions, but are open to new entities.
+ * [Kiln](https://github.com/kiln-ai/kiln) - The easiest tool for fine-tuning LLM models, synthetic data generation, and collaborating on datasets.
 
 
 ## Chatbots
@@ -1428,6 +1418,7 @@ _Updated on January 20, 2025_ (A total of 1965 repositories listed.)
  * [lsp-ai](https://github.com/silasmarvin/lsp-ai) - LSP-AI is an open-source language server that serves as a backend for AI-powered functionality, designed to assist and empower software engineers, not replace them.
  * [generative-ai](https://github.com/genieincodebottle/generative-ai) - Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation.
  * [paperless-ai](https://github.com/clusterzx/paperless-ai) - An automated document analyzer for Paperless-ngx using OpenAI API and Ollama (Mistral, llama, phi 3, gemma 2) to automatically analyze and tag your documents.
+ * [openai-quickstart](https://github.com/djangopeng/openai-quickstart) - A comprehensive guide to understanding and implementing large language models with hands-on examples using LangChain for GenAI applications.
 
 
 ## Unity

docs/README.ja.md

@@ -15,28 +15,16 @@
 
 ## The latest additions 🎉
 
-**Chatbots**
- * [Upsonic](https://github.com/upsonic/upsonic) - 私たちは一切の暗号プロジェクトを持っておらず、持つ予定もありません。それらは完全な詐欺です。| デジタルワーカーや垂直AIエージェント向けのタスク指向型AIエージェントフレームワーク
-
-
-**Reimplementations**
- * [chatllama](https://github.com/juncongmoo/chatllama) - ChatLLaMA 📢 一つのGPUで実行可能なLLaMAベースのChatGPTのオープンソース実装。ChatGPTよりも15倍高速なトレーニングプロセス。
-
-
-**Tutorials**
- * [e2b-cookbook](https://github.com/e2b-dev/e2b-cookbook) - E2Bの使用例
-
-
-**NLP**
- * [Bob](https://github.com/ripperhe/bob) - Bobは、macOSプラットフォーム向けの翻訳およびOCRソフトウェアです。
- * [prism](https://github.com/echolabsdev/prism) - LaravelでLLMを操作するための統一されたインターフェース
+**Prompts**
+ * [LangChain](https://github.com/tryagi/langchain) - LangChainのC#実装。抽象化に関して可能な限りオリジナルに近づこうと努めていますが、新しいエンティティにもオープンです。
+ * [Kiln](https://github.com/kiln-ai/kiln) - LLMモデルの微調整、合成データ生成、およびデータセットの共同作業に最適なツール。
 
 
-**Unity**
- * [OpenAI](https://github.com/macpaw/openai) - OpenAI公開API向けのSwiftコミュニティ駆動パッケージ
+**Langchain**
+ * [openai-quickstart](https://github.com/djangopeng/openai-quickstart) - LangChainを使用したGenAIアプリケーションのための大規模言語モデルの理解と実装に関する包括的なガイドと、実践的な例を紹介します。
 
 
-_Updated on January 20, 2025_ (A total of 1965 repositories listed.)
+_Updated on January 23, 2025_ (A total of 1968 repositories listed.)
 
 ## Table of contents
 
@@ -288,6 +276,8 @@ _Updated on January 20, 2025_ (A total of 1965 repositories listed.)
  * [langwatch](https://github.com/langwatch/langwatch) - 究極のLLM Opsプラットフォーム - モニタリング、分析、評価、データセット、そして迅速な最適化 ✨
  * [phoenix](https://github.com/arize-ai/phoenix) - AI監視と評価
  * [DataDreamer](https://github.com/datadreamer-dev/datadreamer) - Input: DataDreamer: プロンプト。合成データを生成します。モデルをトレーニング＆整列させます。 🤖💤Output: データドリーマー：プロンプト。合成データを生成します。モデルをトレーニング＆整列させます。 🤖💤
+ * [LangChain](https://github.com/tryagi/langchain) - LangChainのC#実装。抽象化に関して可能な限りオリジナルに近づこうと努めていますが、新しいエンティティにもオープンです。
+ * [Kiln](https://github.com/kiln-ai/kiln) - LLMモデルの微調整、合成データ生成、およびデータセットの共同作業に最適なツール。
 
 
 ## Chatbots
@@ -1428,6 +1418,7 @@ _Updated on January 20, 2025_ (A total of 1965 repositories listed.)
  * [lsp-ai](https://github.com/silasmarvin/lsp-ai) - LSP-AIは、AI機能をバックエンドとして提供するオープンソースの言語サーバーであり、ソフトウェアエンジニアを支援し、強化するために設計されており、彼らを置き換えるものではありません。
  * [generative-ai](https://github.com/genieincodebottle/generative-ai) - ジェネレーティブAIに関する包括的なリソース、詳細なロードマップ、プロジェクト、ユースケース、インタビュー準備、コーディング準備などを提供しています。
  * [paperless-ai](https://github.com/clusterzx/paperless-ai) - Paperless-ngxのための自動文書分析ツール。OpenAI APIとOllama（Mistral、llama、phi 3、gemma 2）を使用して、文書を自動的に分析しタグ付けします。
+ * [openai-quickstart](https://github.com/djangopeng/openai-quickstart) - LangChainを使用したGenAIアプリケーションのための大規模言語モデルの理解と実装に関する包括的なガイドと、実践的な例を紹介します。
 
 
 ## Unity

docs/README.zh-hans.md

@@ -15,28 +15,16 @@
 
 ## The latest additions 🎉
 
-**Chatbots**
- * [Upsonic](https://github.com/upsonic/upsonic) - 我们没有任何加密项目，也不会有任何加密项目，它们都是彻头彻尾的骗局 | 面向任务的AI代理框架，用于数字工作者和垂直AI代理
-
-
-**Reimplementations**
- * [chatllama](https://github.com/juncongmoo/chatllama) - ChatLLaMA 📢 是基于 LLaMA 的 ChatGPT 的开源实现，可在单个 GPU 上运行。训练速度比 ChatGPT 快 15 倍。
-
-
-**Tutorials**
- * [e2b-cookbook](https://github.com/e2b-dev/e2b-cookbook) - 使用E2B的示例
-
-
-**NLP**
- * [Bob](https://github.com/ripperhe/bob) - Bob 是一款 macOS 平台的翻译和 OCR 软件。
- * [prism](https://github.com/echolabsdev/prism) - Laravel中用于处理LLMs的统一接口
+**Prompts**
+ * [LangChain](https://github.com/tryagi/langchain) - LangChain的C#实现。我们尽量保持与原始版本的抽象接近，但也愿意接受新的实体。
+ * [Kiln](https://github.com/kiln-ai/kiln) - 用于微调LLM模型、合成数据生成和数据集协作的最简单工具。
 
 
-**Unity**
- * [OpenAI](https://github.com/macpaw/openai) - Swift社区驱动的OpenAI公共API包
+**Langchain**
+ * [openai-quickstart](https://github.com/djangopeng/openai-quickstart) - 一份全面指南，帮助理解和实施大型语言模型，并使用LangChain进行GenAI应用的实际示例。
 
 
-_Updated on January 20, 2025_ (A total of 1965 repositories listed.)
+_Updated on January 23, 2025_ (A total of 1968 repositories listed.)
 
 ## Table of contents
 
@@ -288,6 +276,8 @@ _Updated on January 20, 2025_ (A total of 1965 repositories listed.)
  * [langwatch](https://github.com/langwatch/langwatch) - 终极LLM Ops平台 - 监控，分析，评估，数据集和即时优化 ✨
  * [phoenix](https://github.com/arize-ai/phoenix) - 人工智能可观测性与评估
  * [DataDreamer](https://github.com/datadreamer-dev/datadreamer) - DataDreamer：提示。生成合成数据。训练和对齐模型。🤖💤
+ * [LangChain](https://github.com/tryagi/langchain) - LangChain的C#实现。我们尽量保持与原始版本的抽象接近，但也愿意接受新的实体。
+ * [Kiln](https://github.com/kiln-ai/kiln) - 用于微调LLM模型、合成数据生成和数据集协作的最简单工具。
 
 
 ## Chatbots
@@ -1428,6 +1418,7 @@ _Updated on January 20, 2025_ (A total of 1965 repositories listed.)
  * [lsp-ai](https://github.com/silasmarvin/lsp-ai) - LSP-AI是一个开源的语言服务器，作为AI功能的后端，旨在帮助和赋予软件工程师能力，而不是取代他们。
  * [generative-ai](https://github.com/genieincodebottle/generative-ai) - 生成式人工智能的综合资源，包括详细的路线图、项目、用例、面试准备和编码准备。
  * [paperless-ai](https://github.com/clusterzx/paperless-ai) - 使用OpenAI API和Ollama（Mistral，llama，phi 3，gemma 2）的自动文档分析器，可自动分析和标记您的文件。
+ * [openai-quickstart](https://github.com/djangopeng/openai-quickstart) - 一份全面指南，帮助理解和实施大型语言模型，并使用LangChain进行GenAI应用的实际示例。
 
 
 ## Unity