The AI component of the AI Student Advisor is responsible for providing the chat engine with the ability to answer questions based on the data and remember conversation history.
- Data Loading: Ingest data, generate embeddings using LLM model, and store in a hosted vector database
- Context Retrieval: Retieve relevant context from vector database based on user query
- Response Generation: Generate response based on user query, retrieved context and previous conversation history
source: [LangChain - Retrieval](https://python.langchain.com/docs/modules/data_connection/)
- Retrieve & Load Data: Use data loaders to create a retrieval tool for the chat engine
- Embedding Generation: Generate embeddings for the source data using the configured embedding model
- Chat Agent Instantiation: Create a chat agent that can answer questions based on the data & remember conversation history
