This assistant leverages AlloyDB with vector search and Gemini inside and outside the database to fully qualify the user request while giving a conversational experience.
LangChain provides a structured framework for building applications with Large Language Models (LLMs). It addresses prompt engineering through PromptTemplate, enabling dynamic prompt creation.
The Chain abstraction facilitates complex workflows by sequencing LLM calls and other utilities, exemplified by the LLMChain combining an LLM with a prompt.
LangChain also manages conversation memory, integrates with data sources like vector databases, provides a callback system for monitoring, and abstracts LLM interaction for flexibility.
This is an snapshot of the assistant:
