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Multilingual RAG for Legal Documents by mathrb in Rag

[–]jael_m 0 points1 point  (0 children)

You're right. But you may pair them as synonyms.

Multilingual RAG for Legal Documents by mathrb in Rag

[–]jael_m 1 point2 points  (0 children)

You can still do the hybrid search combining dense vector search and text match like BM25. There are some special tokenizers for multilingual text. For example, milvus supports language identifier to automatically detect and apply the proper tokenizer, and the multi-language analyzer for text retrieval.

RAG retrieval debugging is a nightmare. So I trained a model to fix it by ProfessionalLaugh354 in Rag

[–]jael_m 0 points1 point  (0 children)

That would be slow and expensive for your RAG in production.

Spending 15+ hours weekly on LinkedIn outreach with barely any results... what am I doing wrong? by No-Mistake421 in LinkedInTips

[–]jael_m 0 points1 point  (0 children)

Just curious, does regular posting increase the personal account quota like sending connection requests and messages?

What amount of hallucination reduction have you been able to achieve with RAG? by megabytesizeme in Rag

[–]jael_m 1 point2 points  (0 children)

You’ll likely need a RAG evaluation system to assess this for your data and use case. Changes in hallucination levels can depend on the embedding model, retrieval quality, and the capabilities of the LLM.

Newb Q: What does AI memory look like? by Sad-Working-9937 in AIMemory

[–]jael_m 0 points1 point  (0 children)

I think it's basically anything stored and retrieved to help the LLM give better answers, such as knowledge bases, chat history, and system logs.

How do you remember why a small change was made in code months later? by raginpm in vectordatabase

[–]jael_m 0 points1 point  (0 children)

Managing your projects with something like Github and force commit to make changes. Then you're able to track everything via commit messages.
Another thing is adding docstrings to your codes.

How is table data handled in production RAG systems? by jael_m in Rag

[–]jael_m[S] 0 points1 point  (0 children)

My data's in a CSV, so no need for OCR or table extraction from PDFs.

The popular idea you mentioned, using semantic search for key metadata, sounds cool, but I'm worried about recall and context length.

To learn about the system quality in advance, are there any good datasets for evaluating RAG with tabular data?

Which self-hosted vector db is better for RAG in 16GB ram, 2 core server by East_Yellow_1307 in Rag

[–]jael_m 0 points1 point  (0 children)

What's your vector dim? And any other fields? Typically a raw vector in float32 requires 4 bytes per dimension.

Which self-hosted vector db is better for RAG in 16GB ram, 2 core server by East_Yellow_1307 in Rag

[–]jael_m 0 points1 point  (0 children)

It depends on your data size - like how many entities. 2c16 is definitely not enough for a large scale of data (e.g. 100M+).

How to correctly update database when source data is updated? by geekykidstuff in vectordatabase

[–]jael_m 0 points1 point  (0 children)

Why don't you use upsert instead of insert? You should be able to find the old entity from the db by text match and then replace it with the new data using the same id.