# Abraxas-365/langchain-rust

🦜️🔗LangChain for Rust, the easiest way to write LLM-based programs in Rust

Repository: https://github.com/Abraxas-365/langchain-rust
Canonical: https://ross.abutalabs.com/products/langchain-rust
Language: Rust
License: MIT
License Family: permissive
Topics: langchain, llm, llms, openai, rust
Last push: 2026-08-22T22:16:26+00:00

## Health v2 (maintenance only)
Score: 72/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 40, longevity 67
- inputs: {"age_days": 945, "days_push": 11, "days_rel": 696, "gap_med": 13.0, "n_releases_24m": 3}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1344, forks 176 (observed 2026-08-28T04:04:27.071748+00:00)

## What it is
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
- artifact type: library
- maturity: active
- function: llm-inference, rag, agent-framework, sdk, http-client
- domain: large-language-models, artificial-intelligence, developer-tools
- platform: rust
- tags: langchain, openai, anthropic, ollama, embeddings, vector-stores, chains, prompt-templates, retrieval-augmented-generation

## Member repositories
- Abraxas-365/langchain-rust (main) score 72

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:27.071748+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:42:47.472630+00:00, confidence not recorded.
  - readme: https://github.com/Abraxas-365/langchain-rust (fetched 2026-08-28T04:04:27.071748+00:00, sha 8773ad4d24a3)
  - registry_crates: https://crates.io/api/v1/crates/langchain-rust (fetched 2026-08-29T12:02:00.341046+00:00, sha 08180fc46b1a)
- Data as of 2026-08-30T08:39:29.467469+00:00.