Data Science Service (LLM service)

• Scrapes the message from the user and records the expense along with merchant.
• Useful to extract the data with permission of user and automatically add it into the database.
• Produces a kafka event with the extracted data to consume by expense service to store it.

Provided API’s

         - POST:  /v1/ds/message

Tech Stack for the DS service-

Python 3, Langchain & Mistral AI

• No need to make the service with low latency, since it works in background mode and has a work to just extract and add the expense. we can use any high level language.
• hence, Python can be used to implement the service. (good library support)
• LangChain (a cost is low for personal projects and can be swapped later with other agent).