Multilingual-support microservice

community/rfcs/multilingual-support.md

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+# Multilingual-support microservice 
+
+## Author
+
+[Siddhi Velankar](https://github.com/siddhivelankar23)
+
+## Status
+
+Under review
+
+## Objective
+
+The objective of this RFC is to propose the creation of a separate multilingual-support microservice to handle translation that can be seamlessly used with other microservices. Currently, translation exists as a separate megaservice, which makes it difficult to integrate with other standalone microservices or applications. This proposal aims to simplify and standardize the process of multilingual support by creating a dedicated, scalable, and easily integrable microservice that can seamlessly interact with other services within the system architecture. The goal is to provide a flexible, centralized approach to translation and enhancing the user experience across various languages.
+
+## Motivation
+
+In the current system, translation is managed by a monolithic megaservice,  which is challenging to integrate with other microservices. 
+By introducing multilingual support as a standalone microservice, we aim to decouple the translation functionality from other services, making it easier to scale and manage.
+
+
+## Design Proposal
+
+
+![Enterprise RAG Architecture](./assets/enterprise-rag-translation.png)
+
+The proposed architecture involves the creation of a new microservice called multilingual-support. 
+This microservice detects the language of the user's query as well as the response from the first llm microservice. 
+It then configures a translation prompt to convert the answer from the response language to the query language. 
+This prompt is sent to the second llm microservice to generate the final answer. 
+This ensures seamless, accurate communication across different languages in real time.
+
+
+Signature of multilingual-support microservice
+```python
+@traceable(run_type="multilingual-support")
+@register_statistics(names=["opea_service@multilingual_support"])
+def embedding(input: LLMParamsDoc) -> Union[LLMParamsDoc, ChatCompletionRequest, SearchedDoc]:
+```