How it works
Hymalaia relies on two core components that assume English by default:-
Vector Search and Reranking
These components use embedding models to retrieve relevant documents for the LLM. -
LLM Prompts
These are used to guide the LLM in how to respond.
- Swap out English-first embedding/reranking models for multilingual models.
- Apply query expansion to rephrase the user query into target languages.
- Provide LLM instructions to respond in the same language as the user query.
⚠️ Note
The built-in LLM prompts are still in English. For fully non-English use, consider translating all prompts directly into your target language.
Configuration
Hymalaia supports multilingual setup entirely through environment variables. For Docker Compose, create a.env
file inside the hymalaia/deployment/docker_compose
folder.
Here’s an example configuration for English and French:
📝 An up-to-date template for multilingual settings is also available in the codebase under hymalaia/deployment/docker_compose.
Recommendations
- For full translation, localize all prompt templates in your target language.
- Use multilingual embedding models from trusted sources (e.g. Hugging Face).
- Prefer LLMs with multilingual support (e.g. GPT-4, Claude, etc.).