Abraxas-365/langchain-rust

Health v2 · maintenance only

Adoption not part of the score

1344 stars · 176 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

LangChain for Rust is the Rust language implementation of the LangChain framework for building LLM-powered applications through composability. It provides LLM integrations (OpenAI, Azure OpenAI, Ollama, Anthropic), embeddings, vector stores (Qdrant, Postgres, OpenSearch, SQLite, SurrealDB), and chain abstractions.

Use cases

• build LLM applications in Rust
• create conversational chatbots with memory
• implement RAG pipelines with vector stores
• chain multiple LLM calls sequentially
• generate embeddings for documents
• query documents with a Q&A chain
• connect to OpenAI or Claude from Rust

When to choose

• you want LangChain-style abstractions in a Rust codebase
• you need composable LLM chains with Rust performance and safety
• you want built-in integrations for major LLM providers and vector stores

When to avoid

• you need the full breadth of the Python LangChain ecosystem
• your project is in Python, JavaScript, or another language
• you need features not yet ported to the Rust implementation

Facets

library · maturity active

llm-inference rag agent-framework sdk http-client large-language-models artificial-intelligence developer-tools rust langchain openai anthropic ollama embeddings vector-stores chains prompt-templates retrieval-augmented-generation

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