Emerging Architectures for LLM Applications

This page summarizes the projects mentioned and recommended in the original post on news.ycombinator.com

Our great sponsors
  • WorkOS - The modern identity platform for B2B SaaS
  • InfluxDB - Power Real-Time Data Analytics at Scale
  • SaaSHub - Software Alternatives and Reviews
  • Milvus

    A cloud-native vector database, storage for next generation AI applications

  • Bit of self-promotion, but Milvus (https://milvus.io) is another open-source vector database option as well (not sure why it isn't listed here). We also have milvus-lite for folks who don't want to stand up a service.

        pip install milvus-lite

    I think sidecar vector datbases that work with existing dbs will emerge as more prevalent than the pure vector DB. I also think the vector & graph combo on highly interconnected data will have additional benefits for those building a wide range of LLM applications. A good example is the VectorLink architecture with TerminusDB [1] which is based on Hierarchical Navigable Small World graphs written in Rust.

    [1] https://github.com/terminusdb-labs/terminusdb-semantic-index...

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

    WorkOS logo
  • I think sidecar vector datbases that work with existing dbs will emerge as more prevalent than the pure vector DB. I also think the vector & graph combo on highly interconnected data will have additional benefits for those building a wide range of LLM applications. A good example is the VectorLink architecture with TerminusDB [1] which is based on Hierarchical Navigable Small World graphs written in Rust.

    [1] https://github.com/terminusdb-labs/terminusdb-semantic-index...

  • logger

    🐤 A minimal viable logger for Prompt/LLM Engineering. Use your IDE as Logging UI - a fast, simple, extensible, zero dependency Node.js logging tool that starts simple in development and is easily extended for production! (by smol-ai)

  • > You can add instrumentation for observability around that like you would any other code.

    i built my own last weekend. https://github.com/smol-ai/logger

    dumps things to json files, or to a log store. all you need for prompt engineering and monitoring really! no VC needed, no DataDog of AI yet

  • technical-blogs

    Technical blogs around data collaboration, data management, and building collaborative applications.

  • Oh, I should probably mention a blog I wrote describing how it works: https://github.com/terminusdb/technical-blogs/blob/main/blog...

  • langchainrb

    Build LLM-powered applications in Ruby

  • Is the emerging architecture made out to be more complicated than what most of the companies are currently building? Perhaps! But this is most likely the general direction where things will start trending towards as the auxiliary ecosystem matures.

    Shameless plug: For fellow Ruby-ists we're building an orchestration layer for building LLM applications, inspired by the original, Langchain.rb: https://github.com/andreibondarev/langchainrb

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

Suggest a related project

Related posts