Langchain-Rust framework enables LLM apps in pure Rust, bypassing Python

The langchain-rust library offers a comprehensive framework for building LLM applications entirely in Rust, eliminating the need for Python. It provides first-class integration with Ollama for local models, supporting features like tool calling, vision, and streaming. The framework also includes support for nine different vector store backends, BM25 keyword search, hybrid retrieval with RRF fusion, and advanced RAG techniques like GraphRAG and CorrectiveRAG. Additionally, it features a local code interpreter and local embeddings, along with LangGraph workflows and various memory types, all packaged for easy integration via Cargo. AI

IMPACT Enables developers to build LLM applications in Rust, potentially reducing overhead and increasing performance for local model deployments.

RANK_REASON This is a new software library release for building LLM applications, not a frontier model release or significant industry event.

Read on dev.to — LLM tag →

• BM25
• chromadb
• docs.rs
• GitHub
• langchain-rust
• langgraph
• MongoDB
• Ollama
• pgvector
• Pinecone
• Python
• qdrant
• Redis
• Rust

• product
• infra

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