qdrant / qdrant/fastembed

[Feature]: Add custom token corpus for other languages for bm25

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Description

What feature would you like to request?

Hi, I’m exploring how to enable Qdrant/bm25 to properly tokenize and vectorize the Thai language.

I noticed that the model cache directory contains multiple language-specific text files:

(see image below)

I’d like to add a custom Thai corpus based on this word list:
https://github.com/PyThaiNLP/pythainlp/blob/dev/pythainlp/corpus/words_th.txt

However, simply adding a thai.txt file to the model cache directory does not work dynamically (on the fly). Could you clarify the correct way to extend or register a new language corpus for BM25, or whether additional configuration or rebuilding steps are required?

Image
Is there any additional information you would like to provide?

No response

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First steps

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  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by inspecting BM25's language-corpus registration and model-cache loading, then compare the existing language-specific text files with PyThaiNLP's words_th.txt corpus. Determine whether adding Thai requires configuration, a rebuild, or a code change, and define how successful Thai tokenization and vectorization should be verified.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
search
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
30/100

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