MindsDB

MindsDB AI

MindsDB AI

MindsDB AI

MindsDB AI

MindsDB AI

MindsDB AI

MindsDB AI

MindsDB AI

MindsDB AI

MindsDB AI

It knows it f* up

Just posting cause I found funny it admitting it explicitly and cause I didn't fall from my chair when I saw a command executed in a remote DB when I asked it to delete stuff locally. :) Had a long session in plan mode to run a cleanup on that Docker crap that accumulates over the months, ensuring it wouldn't delete anything I actually need/use. Some back and forth with the plan till I figured it was well defined already, so I approved and off it went. After executing the clean up it goes into checking every image, volume etc and instead of checking the actual local DB it decided, out of thin air, to select a count from my PRE production DB instead of the local DB. Before anybody screams, yes, you're absolutely right! It does have access to my PRE Production DB, but it's got read-only credentials set up (it can't insert/update/alter/drop anything, only select), so even on the worst case scenario, if it hallucinates, it won't screw it up big time. And that's the peace of mind I've got since I started to work inside of a Docker container to protect my local machine's filesystem and with specifically generated credentials for AWS, GitHub, databases, external services etc, all very well scoped so the blast radius is as close as possible to 0. Hope these ideas (which are nothing new really, but I believe nobody talks about it enough) help you to keep f* up free long time. submitted by /u/somerussianbear [link] [comments]

Steam Similarity Recommender Find your next favorite game and learn WHY (student project)[P]

I love making recommendation systems that tell the user WHY they got the recommendation. During a steam sale event, I always find myself trying to look for new video games to play. If I wanted to find a new game I would try to whittle it down by using steam tags, but the steam tag system is very broad "action". could apply to many many games. That got me thinking, what aspects do I like about my favorite games? Well I like Persona 4 because of the city vibes and jazz fusion, I like Spore because of the unique character creation and whimsical theme. and I like Balatro for its unique deck building synergies. What if I could capture unique tags that identify a game that aren't just "action" and put them into vectors to show the (focus) of a game For example I could break persona 4 into something like Gameplay Focus vector: - Day cycle 20% - Dungeon crawling 20% - Social sim 20% Tags: - Music: jazz fusion - Vibe: Small rural town I achieved this by pulling 2k reviews for 80k steam games, running them through a 4 stage pipeline that filters out the reviews to find reviews describing a video game's vibes or structure, then asking a llm to generate these reviews into vectors, niche anchor tags and micro tags using non canonical names. to really "capture" niche tags that can't be captured normally. Then I used a 6 stage pipeline to group these non canonical names together (fast combat = speedy action combat) From that I stored it all in PostgreSQL + Chroma db, made an app using React. and Shipped it all within a docker container inside a digital ocean droplet! The result is a cool little steam game recommender that I can use to not just find similar games, but find games that share my favorite aspect of a game I like. A system that explains to me why I got the recommendations I got. I find that this system makes searching for games more "fun" now I can see why I like balatro. I like it because of the card synergies not so much for its rogue-like nature. I also find that this helps find new underrated games, and beats the trap that Collaborative Filtering algorithms that get into where it "feels" like you get recommended the same things. find your next favorite game! : https://nextsteamgame.com/ pull a PR!: https://github.com/BakedSoups/NextSteamGame ( I actually made some git issues myself for problems I can't fix) if anyone has any criticism I would love to hear it! this is probably my favorite passion project. Hope this website helps people find new games! Also I have a advance mode for people that don't mind messing with sliders and weird data terms. submitted by /u/Expensive-Ad8916 [link] [comments]

Help needed (Claude Code + Supabase)

IIn the last couple of weeks and probably months, I was directly asking Claude Code to modify some rows in my db in Supabase and run SQL migrations. However, in the last two days or so, it refuses to do directly. It does not show me the "always allow" button that I usually see. It does not go to my DB and check for my tasks. Keep in mind that I have Supabase as a connector and never removed it. I even tried to give it all the "allow" permissions. No luck. submitted by /u/Throwaway_SQ2 [link] [comments]

Is anyone else terrified of giving Cursor/Claude direct access to their database? I built an open-source solution.

Hey everyone 👋, I absolutely love using Cursor and Claude Desktop for debugging and writing queries, but the idea of hooking them up directly to my database via standard MCP (Model Context Protocol) servers has always given me anxiety. One bad hallucination, and the AI could execute an UPDATE without a WHERE clause, or accidentally read a table full of hashed passwords. I couldn't find a tool that provided enough peace of mind, so I built DB-Whisper. It’s a production-grade, highly secure MCP server designed specifically for AI assistants. Instead of just passing queries through, it acts as a paranoid firewall: Deep AST Validation: It parses the actual AST (not just regex) to ensure ONLY pure SELECT queries are executed. Zero Info Leakage: You can block access to specific tables (like users or payments). Data Masking: It can automatically mask sensitive fields (like emails or phone numbers) before the AI even sees them. Driver-Level Read-Only: Double insurance at the database driver level. I just open-sourced it and I'm looking for some beta testers. If you're building with AI agents or using Cursor for backend work, I’d love for you to try it out. I’d also love some feedback: What other databases should I support next (MySQL, MongoDB)? Can anyone manage to bypass the AST firewall? submitted by /u/Majestic_Common_1669 [link] [comments]

My actual AWS bill running Claude in production for 5 months

So I've been running Claude Haiku 4.5 on AWS Bedrock for about 5 months now across a few different production apps. Thought I'd share what the bill actually looks like because there's a lot of vague "it's cheap" or "it costs a fortune" talk and not enough actual numbers. My setup: a Next.js app on AWS Amplify that uses Bedrock for two things. First, a customer facing AI chat widget (RAG with a knowledge base, about 16 docs). Second, an AI readiness assessment tool that generates personalized reports. Both use Haiku 4.5 because honestly Sonnet is overkill for what I need. The actual numbers (last 3 months average): Chat widget costs about $3.50/month. Most conversations are short. The RAG retrieval from S3 Vectors costs almost nothing, like $0.03/month for the vector store. The trick is keeping the system prompt tight and using the knowledge base to inject context only when needed instead of stuffing everything into the prompt. Assessment reports cost about $4.80/month. Each report is a 150 word personalized analysis. I cap the output at 400 tokens and set a daily cap at 100 reports. Worst case is maybe $8/month but it never hits that. Total Bedrock cost: roughly $8 to $12/month. I set a $20/month AWS budget alarm with alerts at 50%, 80%, and 100%. Haven't hit the 80% alert once. What actually saved me money: Haiku instead of Sonnet. For my use cases the quality difference is negligible but cost difference is like 10x. I tested both extensively before committing. Sonnet gave slightly more polished prose in the reports but nobody noticed or cared. Daily cost caps in DynamoDB. Not just rate limiting per IP (I do that too, 20 requests per 15 min for chat) but a hard atomic counter in DynamoDB that blocks all AI calls after hitting the daily limit. Survives Lambda cold starts unlike in memory counters. Keeping maxOutputTokens low. Assessment prompt uses 400 max. Chat uses 1024. You'd be surprised how much quality you can get in a tight token budget when your prompt is specific about format and length. Bedrock Guardrails for free safety. Content filtering, prompt attack detection, PII blocking. The guardrail evaluation calls are free, you only pay for the model invocation. So I get a full safety layer at $0 extra. The gotcha nobody warns you about: Lambda cold starts can make your in memory rate limiters useless. I had a bug where my daily cost cap was resetting every time a new Lambda instance spun up, so theoretically someone could have burned through way more than intended. Moving the counter to DynamoDB with atomic UpdateItem fixed it permanently. Cost of that DynamoDB table? Like $0.50/month with on demand pricing. What I'd do differently: I probably overengineered the safety stuff early on. The $20/month budget alarm alone would have caught any runaway costs. But the DynamoDB cap gives me peace of mind for the chat widget since it's public facing and I can't control how many people use it. If you're building something similar and debating Bedrock vs the API directly, Bedrock's advantage is the IAM integration. No API keys floating around in env vars, your Lambda just assumes a role and talks to the model. One less secret to manage. Anyone else running Haiku on Bedrock? Curious what your monthly spend looks like for similar workloads. submitted by /u/ecompanda [link] [comments]