# langchain-rust: Build LLM apps with Ollama + local models in pure Rust — no Python needed > Source: > Published: 2026-08-03 09:24:01+00:00 If you're running local models through Ollama and tired of Python's overhead, check out [langchain-rust](https://github.com/atliliw/langchainrust). It's a full LLM framework in pure Rust that works great with local models: - **Ollama support** — first-class integration with tool calling, vision, and streaming - **9 vector store backends** — InMemory, SQLite, Qdrant, ChromaDB, Redis, PGVector, MongoDB, Pinecone, FileVectorStore - **BM25 keyword search** — with Chinese/English tokenization, no external dependency - **Hybrid retrieval** — BM25 + Vector with RRF fusion for better recall - **GraphRAG** — Knowledge graph construction + community detection, all local - **CorrectiveRAG** — Self-correcting retrieval with hallucination detection - **Code Interpreter** — LocalSandbox (subprocess), E2B cloud, or WASM sandbox - **LocalEmbeddings** — Run embeddings without calling an API Plus: LangGraph workflows, MCP client/server, 7 memory types, guardrails, and 12+ built-in tools. Single binary, no virtualenv, no pip conflicts. Just `cargo add langchainrust` and go. GitHub: [https://github.com/atliliw/langchainrust](https://github.com/atliliw/langchainrust) Docs: [https://docs.rs/langchainrust](https://docs.rs/langchainrust)