Back to directory

archi

A retrieval-augmented generation framework, first built at MIT for the SubMIT computing project, aimed at research and education teams who need a configurable, private and extensible assistant with a low barrier to entry.

Visit website (opens in a new tab)archi-physics.github.io
archi

archi combines data retrieval with language models through customizable pipelines, and now powers chat, ticketing and course-support workflows across several academic and research organizations. It ingests data from sources such as web links, git repositories, local files and JIRA, and exposes that data through interfaces including a chat application, a ticketing assistant and an email bot.

Its modular design allows custom data sources, LLM backends, including both local and API-based models, and deployment targets to be substituted, and it ships containerized services and CLI utilities for repeatable deployment. Documentation covers configuration through a YAML schema, a REST API, agent and tool specifications with MCP integration, and guides for benchmarking and evaluating retrieval and response quality.

It is written in Python and licensed under MIT.

More in RAG

See all 540
  • ai·rete·rag

    ai-rete-rag.com

    A platform that pairs a Rete rule engine with retrieval-augmented generation, so deterministic rules decide an outcome and grounded retrieval explains the decision in plain language.

  • Xtriever

    github.com

    A hybrid retrieval engine for retrieval-augmented generation, written in Rust to run on-device on a phone or a laptop, combining lexical BM25 search, dense embedding search, reciprocal-rank fusion and cross-encoder re-ranking with no server.

  • FileFlux

    github.com

    A .NET library that turns PDF, DOCX, HWP and other documents into optimized chunks for RAG systems, through a five-stage pipeline built on high-performance Rust FFI readers.