This repository contains the source code for the Retrieval-augmented Generation (RAG) technique, as described in the following articles:
Part 1: Getting started, Chain of Thought
Part 2: Reason-Act, multi-turn conversation
Part 3: PDF ingestion, vector search
Bonus: RAG with SLM (Small Language Model)
First, you need to run the API server of llama.cpp with Phi 2:
./server -m /path/to/phi-2.Q4_K_M.gguf
(For a slower response but with improved accuracy, consider using Mistral 7B OpenOrca).
To launch Pico Jarvis, you need Node.js v18 or later:
npm install npm start
and then open localhost:5000
.
Ask the following questions:
Who wrote the Canon of Medicine?
Is ramen typically eaten in Egypt?
Who directed the Dark Knight movie?
Name Indonesia #1 tourist destination!
What is the native language of Mr. Spock?
Which US state starts with G?
What is the atomic number of Magnesium?
Where do we find kangoroo?
Who is the father of Luke Skywalker?
In which country Mandarin is spoken?
What is the longest river in Latin America?
Who authored the special theory of relativity?
Which fictional metal is infused into Wolverine body?
Who sailed with the flagship Santa Maria?
Name the big desert close to Mongolia
Which is closer to Singapor: Vietnam or Australia?
Who is the fictional spy 007?
Which country is known for IKEA?
Meanwhile, questions related the solar system will be answered by searching the PDF document:
What is a dwarf planet?
Which planet known as the red one?
What materials compose the gas giants?
How about the ice giants?
Explain the heliopause
When did Voyager 2 enter the interstellar space?
How about Voyager 1?
If you get an API key for OpenWeatherMap and supply it as OPENWEATHERMAP_API_KEY
environment variable, try to ask the following:
How is the weather in Jakarta?
What is the current temperature in Palo Alto?
Is it currently cloudy in Seattle?