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https://github.com/fullstackwithlawrence/ubc-bsd10-track-b

UBC BSD10 Track B - supplements
https://github.com/fullstackwithlawrence/ubc-bsd10-track-b

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UBC BSD10 Track B - supplements

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# ubc-bsd10-track-b

Supplemental materials for UBC BSD10 Track B

## module 6 labs

I. Getting setup with api access (15 minutes)

- https://platform.openai.com/settings/organization/api-keys
- testing with curl
- setting up Postman
- base url
- required headers
- body
- handling sensitive data
- trouble shooting

II. Understanding LLM out-of-the-box capabilities
Prompt: "Is Lawrence McDaniel a good photographer?" (15 minutes)

- Google
- ChatGPT
- Postman via OpenAI/GoogleAI/MetaAI
- curl via OpenAI
- what's the difference?
- streaming and other UX improvements
- tool calling
- ChatGPT's back door web search

III. Getting setup with Python OpenAI PyPI (10 minutes)

- https://github.com/FullStackWithLawrence/openai-hello-world/
- clone
- make init
- make docker-build
- live demo

## module 7 labs

I. LLM Tool Call live example
Prompt: "What's the weather in Vancouver right now?" (15 minutes)
docs: https://platform.openai.com/docs/guides/function-calling?api-mode=responses
example: https://platform.smarter.sh/docs/developer/weather-function/

- break down a tool call in smarter
- ChatGPT
- Postman
- https://openai.lawrencemcdaniel.com/ -> https://github.com/FullStackWithLawrence/aws-openai
- https://platform.smarter.sh/workbench/example/chat/

II. LLM RAG live example
Prompt: "What analytics and accounting courses does Wharton offer?" (30 minutes)

- Google
- ChatGPT
- LLM Api prompt via Postman
- RAG Prompt: https://github.com/FullStackWithLawrence/openai-embeddings

- setup the project
- build the vector database
- demo template technique
- demo with / without RAG approach
- show a sample human language query to vector database