Inspiration
Global Hacking Week
What it does
run the RAG application interactively using a simple user interface. You can select and load from several PDF documents, and ask your own question in the prompt. This is the same application with the 7 essential RAG steps as the previous lab but demonstrates use through a user interface.
How we built it
- Using the LangChain framework for developing applications with Large Language Models (LLMs).
- Using Oracle AI Vector Search to store and search vectors in Oracle Database 23ai.
Challenges we ran into
- Time
- Access to docs
What we learned
By using AI Vector Search in Oracle Database 23ai, you can build RAG applications with important context without having to retrain the LLM. The context is stored, searched and retrieved from Oracle Database 23ai and passed to the LLM to generate accurate, up to date, and targeted responses to your prompts. Businesses and enterprises can use RAG with AI Vector Search in Oracle Database 23ai and an LLM to securely respond to important business questions or to generate content for many use cases using private, internal business information.
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