Getting started LLM for workshop

How to use the LLMs

• Prompt Engineering
• Retrieval Augmented Generation (RAG)
• Fine-tuning
• Training your own Foundation Model(FM) from scratch

Vector databases

• Milvus
• Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain deeplake

Knowledge

• Referred to as “prompts”. Designing a prompt is essentially how you “program” a large language model model
• Plugins can be “eyes and ears” for language models
• Using commands to instruct the model what you want to achieve, such as “Write”, “Classify”, “Summarize”, “Translate”, “Order”
• Foundation model (FM) – An AI model with a large number of parameters and trained on a massive amount of diverse data. A foundation model can generate a variety of responses for a wide range of use cases
• Agent – An application that carry out orchestrations through cyclically interpreting inputs and producing outputs by using a foundation model. An agent can be used to carry out customer requests. For more information
• Retrieval augmented generation (RAG) – The process of querying and retrieving information from a data source in order to augment a generated response to a prompt. For more information

Prompt example

• Give a demonstrations

 1
 2Q: What is prompt engineering?
 3A: It's a laugnauge for LLM to interactive
 4
 5This is awesome! // Positive
 6This is bad! // Negative
 7Wow that movie was rad! // Positive
 8What a horrible show! //
 9
10Classify the text into neutral, negative, or positive
11Text: I think the food was okay.
12Sentiment:
13
14### Instruction ###
15Translate the text below to Spanish:
16Text: "hello!"

AutoGpt getting started

• Fork the offical repo https://github.com/Significant-Gravitas/Auto-GPT.git
• Clone the yourself repo git clone https://github.com/Significant-Gravitas/Auto-GPT.git
• Setting up the project

1cd Auto-GPT
2# create you agent
3./run agent create YOUR_AGENT_NAME
4# start you agent
5./run agent start YOUR_AGENT_NAME
6# to stop agent
7./run agent stop

GPTS Limits

Generative AI application framework

• microsoft semantic kernal
• Build context-aware reasoning applications langchain
• Chroma
• Weaviate open source vector database stores both objects and vectors
• Database for AI. Store Vectors, Images, Texts, Videos

Reference

• A list of open LLMs available for commercial use.
• How to create a GPT
• AutoGPT is the vision of accessible AI for everyone, to use and to build on
• openai assistants
• Prompt Engineering Guide
• Prompt Engineering 101: A Beginner’s Guide to Crafting Powerful Instructions
• Key definitions
• Example project for using chroma to store and query vector embeddings
• the ui and modelfiles

Opensource LLM

• localAI
• ollama
• streamlit apps
• Production Ready Data Framework for LLM-applications