LlamaIndex is a very generic framework to ingest data (from anywhere, with no specific context in mind). Developers then build on top of this framework in order to simplify the process of creating LLM-powered on apps. Developers need to handle automatically syncing, building a UI to manage connections, build out the actual features/functionality they desire, etc.
Danswer is:
(1) itself an end-to-end application which allows you to connect to all your workplace tools via a UI, and then ask questions and get answers based on these documents. The goal is to be a permissively licensed, open source solution to the enterprise knowledge retrieval problem.
(2) an ingestion framework specifically targeted for enterprise applications. We provide a UI for admins to manage connections to other common workplace apps, automatically sync them into a vector DB + a keyword search engine, and expose APIs that allow access to these underlying data stores (more to come in this direction). We take care of access control (more in the pipeline here as well), only grabbing updates so we don't have to pull thousands (or millions) of documents every X minutes, etc. TL;DR: we're focused on a specific ingestion use case.
why did you choose not to build on top of something like llama-index or langchain? how easy or difficult would it be to integrate with a library like llama-index?
Danswer is:
(1) itself an end-to-end application which allows you to connect to all your workplace tools via a UI, and then ask questions and get answers based on these documents. The goal is to be a permissively licensed, open source solution to the enterprise knowledge retrieval problem.
(2) an ingestion framework specifically targeted for enterprise applications. We provide a UI for admins to manage connections to other common workplace apps, automatically sync them into a vector DB + a keyword search engine, and expose APIs that allow access to these underlying data stores (more to come in this direction). We take care of access control (more in the pipeline here as well), only grabbing updates so we don't have to pull thousands (or millions) of documents every X minutes, etc. TL;DR: we're focused on a specific ingestion use case.