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Using Weaviate with Non-English Languages

Blog post from Weaviate

Post Details
Company
Date Published
Author
Leonie Monigatti
Word Count
1,349
Company Posts That Month
2
Language
English
Hacker News Points
-
Post removed?
No
Summary

The use of Weaviate with non-English languages is possible if the embedding models and large language models (LLMs) used support the chosen language. However, there are challenges when working with non-English languages in search or generative AI applications, such as the necessity of capable language models and character encoding issues for languages that cannot be ASCII encoded, like Chinese, Hindi, or Japanese. Weaviate can be used for semantic and generative searches with non-English languages by ensuring support from embedding models and converting escaped Unicode characters to human-readable ones. Currently, there are limitations in using Weaviate with non-English languages, mainly affecting keyword-based search functionality and hybrid search functionality.

Trends Found in this Post
Trend Post Mentions Total Month Mentions Posts Companies MoM
Vector Search 11 1,728 228 84 +63%
LLM 4 2,790 311 123 +34%
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