Report Abuse

Basic Information

LangChain .NET is a C# implementation of the LangChain abstractions intended to help developers build applications that use large language models through composable building blocks. It aims to mirror the original LangChain design while remaining open to new entities and third party libraries. The project provides providers and model wrappers for services such as OpenAI, embedding models, document loaders, vector databases and chain orchestration patterns. The repository includes examples, tests and a wiki to guide usage, and positions itself as a community-driven effort to unite C# developers working on LLM applications. The maintainer highlights quick PR turnaround, invites contributors, and provides support channels and sponsorship information.

Links

Categorization

App Details

Features
Provides LangChain-style abstractions implemented in C# with providers and model wrappers including OpenAiProvider, OpenAiLatestFastChatModel and TextEmbeddingV3SmallModel. Includes document loaders such as PdfPigPdfLoader, text splitting and embedding support, and a SqLiteVectorDatabase for storing and querying vector embeddings. Offers chain orchestration primitives shown in examples like Set, RetrieveSimilarDocuments, CombineDocuments, Template and LLM to build end-to-end pipelines. Ships examples, integration tests and a wiki, a NuGet package, and CI via a dotnet workflow. Tracks model and embedding usage in examples and shows cost estimates. Licensed under MIT and supported by community channels and sponsors.
Use Cases
Helps C# developers prototype and build retrieval augmented generation and other LLM-powered applications by providing ready-made components and clear examples. Developers can create vector databases from documents, compute embeddings, retrieve similar documents and feed combined context to language models using chain primitives. The README demonstrates async usage and chain-based workflows, shows how to measure model and embedding usage and provides cost estimates for sample runs. The project includes tests and example apps to accelerate learning, a wiki for guidance, a NuGet package for easy integration and community support via GitHub discussions, issues and Discord. The MIT license allows reuse and contribution.

Please fill the required fields*