Re:Show HN: Open-Source DocumentAI with Ollama
by dcreater on Saturday March 08, 2025 @02:25AM
(#43298265)
Why not use an established open source vector db like pg_vector etc? I imagine your implementation is not going to be as performant
Re:Show HN: Open-Source DocumentAI with Ollama
by Xiol32 on Saturday March 08, 2025 @02:59AM
(#43298426)
Defeats the point of the single binary installation if you have to set up dependencies.
Re:Show HN: Open-Source DocumentAI with Ollama
by andai on Saturday March 08, 2025 @08:25AM
(#43300074)
rlama requires a python install (and several dependencies via pip) to extract text.
https://github.com/DonTizi/rlama/blob/main/internal/service/...
Re:Show HN: Open-Source DocumentAI with Ollama
by mentalgear on Saturday March 08, 2025 @04:40AM
(#43298844)
I recommend using this hybrid vector/full text search engine that works across many runtimes: https://github.com/oramasearch/orama
Re:Show HN: Open-Source DocumentAI with Ollama
by PhilippGille on Saturday March 08, 2025 @05:18AM
(#43299005)
Hi, if you want to keep using a Go embedded/in-process vector store, but with some additional features, you can check out my project https://github.com/philippgille/chromem-go
but for now here is the stack used: Core Language: Go (chosen for performance, cross-platform compatibility, and single binary distribution) CLI Framework: Cobra (for command-line interface structure) LLM Integration: Ollama API (for embeddings and completions) Storage: Local filesystem-based storage (JSON files for simplicity and portability) Vector Search: Custom implementation of cosine similarity for embedding retrieval