25.0223 (0214) (Gdrive)

(was 3 Chat (CusSup) (MAQ/LLM/RAG))

(many of the following ideas below are my own non-expert concepts; not sure if they are correct)

I want to get local docs that I create "injected" into ChatGPT. The user can use GPT instead of reading my docs. I was not sure this was possible.

After a few days of searching the internet, I think found what I am looking for: RAG.

• G = Generate a (GPT) response.
• A = Augment the response with my own custom docs.
• R = Retrieve my content (that I put into a custom Supabase DB using my own crawler; demo'd in #299).

The normal method.

With RAG added local context to the response.

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* "scrape" = use AI tools to crawl over info sources (planning docs, docx's, lab notes) to collect info.

About using AI: If you automate too much of dev and writing with AI, then you might end up like someone with an AI driven (battery powered) car:

• You have no control over whats under the hood.
• Only a real expert can fix anything.
• The AI may fail (and leave you stranded or worse).

I want to use only as much AI as currently is reasonable (with eyes on the future).

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Doc #299_(OK)_rag_ai_pydantic_COLE_.docx describes how I did the RAG (retrieval augmented generation) demo from Cole Medin "The Future of RAG is Agentic - Learn this Strategy NOW" Cole Medin @ https://www.youtube.com/watch?v=_R-ff4ZMLC8.

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Note: limited results because vectors only for limited DB entries to avoid costs... but it works.