u/InTheUpstairsCellar

Is this solution dumb?

I'm a novice to intelligent systems integration, so any opinions would be appreciated.

I'm building a system which is designed to ingest a user-written article about a very particular domain, let's say it's the coffee industry. We have a vast repository of quantitative and qualitative (prose) data, and we want to query it for information that the user might find enhances their article.

We're structuring the quantitative data in an SQL db and the prose data within the RAG searchable AWS Knowledge Base.

I plan on mediating LLM -> Data communication via MCP which exposes endpoints for template queries. The parameters for each endpoint fill in the placeholders within the templates. A template query would be something like SQL:'revenue for <company> in <region> in <2025>'

My concern is that every time the data returned from the MCP is reproduced by an LLM we introduce hallucination risk. So how about this: every single Knowledge Base or SQL query launched by the MCP gets put into a Redis instance with a TTL of 30 mins.

This way we can have the LLM reason over the results, summarise them for output (and occasionally hallucinate) but the raw data remains immutable within Redis. The LLM's output can be summaries attached to IDs which we use to pull the raw data from Redis before finally giving it back to the user.

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u/InTheUpstairsCellar — 1 day ago

RAG suitability for problem

I’ve got the following functionality to solve for a client. I’m wondering if RAG search is my best bet here.

Problem: Client writes a press release on this web service. The PR is always about the cafe industry. Some magic AI system the reads it and peruses a huge corpus of prose to present to the author with a little nudge and a suggestion that they might want to consider this interesting data.

The problem is how do we find that data in this corpus of prose?

Is RAG the solution. Would I ask an LLM to read the article and then generate questions for which the answer would field interesting data for the author?

I’d use AWS bedrock knowledge base for this.

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u/InTheUpstairsCellar — 5 days ago

I've been wracking my brain for nearly an hour trying to find a horror game demo I played on steam in December last year. Can anyone help me find it?!

Features I remember:

  • Ultra realistic graphics
  • Play as a woman
  • Set in a modern, white, well lit home
  • On the second floor in the dining room there was a massive oversized head which you had to make a meal for by finding rotten or bloody ingredients around the house
  • A tall shadow figure with a black or white mask frequently jumpsacred and chased you
  • Gameplay involved finding items and reading notes, you have no offensive abilites
  • Has a demo
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u/InTheUpstairsCellar — 18 days ago
▲ 16 r/drawing

I thought I’d write what I sense my biggest weaknesses and strengths are to measure how deluded I am against what you think my biggest weaknesses are

I feel my biggest weakness are:
- composition and character design - wtf is that room? I have no idea why that sofa is in there and nothing else. Why’s the fire exit open? what’s it mean? What’s that boy with the sword wearing? Why’s he bald? Why’s he got a sword? No one knows, not even me.
- Human faces. Especially close up ones, especially detailed ones. Things get better with distance where I can hide behind the skirt of human visual autocomplete and draw little dashes for eyes, but generally it’s awful.
- colouring. That includes theory, selecting the right colours, and the practise of actually layering. Some of my attempts are better than others but only the second picture has achieved ANY success at all with colour. And that’s the only one for which I had a reference

I feel my biggest strengths are:
- I think my intuitions for proportion, scale and perspective is pretty alright. It’s the one thing I haven’t felt the need to look up a tutorial for because I pass my own muster at the moment

u/InTheUpstairsCellar — 21 days ago