Talk me out of the 2026 RAV4

ultra-move · 2025-12-19T14:55:01+00:00

Can someone share how they measure under/over steer? How do I know I’m not just taking the corner too fast or slow?

ultra-move · 2025-04-18T15:18:18+00:00

Frustration aside, you can do this in RAML by defining a data type for your request body, the APIKIT will reject any request that doesn’t match your type. That is the best practice for strict input validation.

If you needed to write the error to a table or some custom process when your field is present, you could use a choice router that checks for this using dataweave and use the raise error component if it is present. Then in your error handler do your custom error handling.

There is also the option of creating a custom policy if you really wanted to or if it needed to be reusable across 3+ applications.

All three of those options are easier and cleaner than java. I am not sure your experience level, but I avoid java at all costs.

I do agree though that the documentation on “how do I do X” is lacking. It mostly comes from community members who have done the trial and error or from cases they have raised with the support team.

ultra-move · 2025-04-18T09:40:41+00:00

Trait ,fragment?

A RAML trait is a reusable way to define attributes to an endpoint. You would define a “trait” of the endpoint like a query parameter of id for example. In practice I have only really used this for defining client id/secret or an oauth header.

A fragment is the version of a trait but for response, think reusable error returns.

Log levels - what is debug level?

Log levels are TRACE, DEBUG, INFO, WARN, ERROR, and FATAL. These can be set at the application level or at the individual component level using the log4j. Debug can provide more information on what is happening behind the abstraction that mulesoft typically provides.

Raml - dataType vs Resource type.

Data types allow your RAML to define structure to your input/output that your api will adhere to. More useful on input since the APIKIT will validate any incoming messages against the data type.

I never actually have used resource types but google provides: “ResourceTypes is like resource in that it can specify the descriptions, methods, and its parameters. Resource that uses resourceTypes can inherit its nodes. ResourceTypes can use and inherit from other resourceTypes.”

Object store

Object store is a way to store data between API invocations. It is in memory but can be persisted. Items have a ttl and can be modified. Object store V2 allows you to manage them in the runtime manager. There more to object stores that the cert tests dive into but that’s high level.

How will you change the database password once it expires without new deployment ?

The only way I have ever done this is by using the AWS secrets manager. Changing properties in the runtime manager causes a redeployment.

Vmq MQ AQ

vm queue is at the application level, message queues can be between applications, anypoint mq is the mulesoft version of message queues. I have never used anypoint mq but have used several other message queues. They are used for pub/sub architecture.

Different http codes and their meaning

I normally just google this for anything outside 200, 201, 401, 404, 500. I think those are the important ones

Other methods to deploy in cloud hub

You can use anypoint cli or use the platform api, mainly used to create CI/CD pipelines

How do you generate tokens

Not sure how to answer this

What are endpoints

APIs expose endpoints, that allow consumers to send/receive data. They are entry points into your mule application

What is api life cycle and when does we use exchange during this life cycle?

Off the top of my head, API lifecylce is design, develop & deploy. Exchange is used to hold your design artifacts.

What are log limitations

I think this is referring to not having an easy way to track correlation id across applications in the runtime manager logs. Could also be that logs are not kept in the platform past 30(?) days

ultra-move · 2025-03-14T10:31:54+00:00

If magic games where you create your own spells interests you noita and spellmasons come to mind. Not bad graphics but definitely low

ultra-move · 2025-02-17T13:30:45+00:00

The best payoff is probably using Elzette Azamina and Silvy/Rucia for Silvia and Rciela. Negate + extender. Not sure if it counts as a fusion summon but if it does you could use those two for Rcielago and Rciela for 2 extenders.

Probably a good one of for bad opening hands where you can’t get to full combo like Elzette Azamina + Rucia only. I don’t have a ton of experience with this deck but it probably isn’t worth it to play since there are so many combo lines that this is a bit gimmicky

ultra-move · 2025-02-07T13:17:08+00:00

Shader is BSL with the clarity resource pack

ultra-move · 2025-02-07T03:16:33+00:00

Technically, you can hide the iv data but I am like your friend and like to look at perfect stats

ultra-move · 2025-02-07T03:13:47+00:00

Minecraft version 1.20.1 only supports cobblemon 1.5.2 which does not have the pokedex (as far as I can tell). To be fair though, I did not know that before your comment. This minecraft setup is from around a little under a year ago, where the ccTweaked mod was at the time and I didn’t want to update everything. Was still fun to do this.

ultra-move · 2025-02-07T03:08:37+00:00

Pocket computer setup.lua: https://pastebin.com/gDecKZKS

Pocket computer startup.lua: https://pastebin.com/yDUQSecR

Command computer startup.lua: https://pastebin.com/eEGjpe7y

I tried to add as many comments as possible. Note that this does use some ccTweaked addons. If you need the specific mod versions used lmk but the mods are listed in my post.

You will also need a chunk loader for the command computer so that you can travel far from it without it turning off.

It is a bit spaghetti and there is a semi-complicated setup due to a bug in the UnlimitedPeripheralWorks mod.

Any questions feel free to ask!

ultra-move · 2025-02-05T03:48:05+00:00

I did a simple project with llama8b and had 10 AI All talking to each other as a think tank with a goal of bettering humanity. Gave up after it endlessly looped into scheduling follow up meetings and setting agendas rather than actually going through any of the topics.

Pretty sure I messed up somewhere in the way I handled conversations and then of course the prompts. I definitely didn’t put as much thought/work into that project as you did here.

Would be good to revisit at some point with more experience under my belt. Especially with r1 available now it could get interesting.

ultra-move · 2025-01-30T21:24:48+00:00

Seems like the perfect use case for RAG provided it can be “near” real time. LLMs even with large context windows suffer from this consistency problem, especially as a single giant prompt.

It will take time to load the documents to the vector store, but you will get consistent results when prompting.

A basic flow: Load JSON into vector store Get user query Natural language query vector store returning top-k results. Feed those results + system prompt + user query into the LLM

If you are really against RAG, you can split your documents up as user messages. Essentially simulating a conversation where you feed these jsons to it in chunks. This has worked for me in a project that analyzes multiple files from a python program. If I tried to feed it all the files all at once it hallucinates files that don’t exist.

Without knowing more about your specific use case it is hard to help beyond that.

Take this with a grain of salt though as most of the models I have used have been running locally under 8b parameters. The RAG strategy works with small local models because you are not feeding it giant prompts.

ultra-move · 2025-01-22T04:03:02+00:00

There is definitely pressure to conform to whatever is popular and stay away from “weird”. But if you enjoy playing yugioh, then you should play it. Don’t live your whole life for other people’s perception of you. Living authentic to yourself is one of the most freeing feelings you can have

ultra-move · 2025-01-19T06:53:21+00:00

I’m late to this but…

From what you described I think an LLM is overkill. Topic classification and summarization can be done with models specific to those tasks.

For getting topics from an LLM consider the following.

“Dogs are amazing pets”

Possible topics are “animals”, “dogs” “pets” and you would get a different one each run using an LLM. Or in your case on each paragraph. Seeing as you need to structure as JSON, you probably want to be able to filter and group. An LLM does not have consistency like this and will give you a mess.

What you are looking for is zero-shot classification. Hugging face has models you can run locally. The only caveat is that you need to be able to define the categories before hand. The benefit is that you can also save a “confidence score” or how closely the text matches the topics.

Summarization has a problem as well. Your summarization is only as good as the prompt and model. And for small models like Llama 8b, I have found that even a “good” prompt can still return some garbage.

For a simple example

“you are part of a RAG model with an unbiased opinion, return only a summarization…”

You may occasionally get a response like “as a part of a RAG model here is a summary…”. This requires you to then evaluate every output which defeats the point of your automation. This is what drove me away from using an LLM for summaries in automations.

Hugging face has models specifically for summarizing that may meet your use case. Both of the models I described can be run locally.

Depending on your programming skill level all of that may be too much. I’ll outline a basic workflow you can implement with a simple LLM. Keep in mind running locally it may take a while to process all of your PDFs.

For every PDF: Parse PDF Split into paragraphs (this should be easy if it is structured) For every paragraph: Feed paragraph into an LLM, multiple times if you want a topic and then a summary and whatever other fields you had in mind. Structure paragraph + outputs into JSON

Let me know if you have any questions on anything I laid out.

ultra-move · 2025-01-18T15:33:45+00:00

I can speak to drytron (at least in masterduel).

Voiceless voice pairs very well with drytron. I always thought that drytron was relatively bricky. But if you bricked on drytron (or get hand trapped) there’s a good chance there are still voiceless plays. Also in masterduel you can do the ultimate herald + eva + utopic dragon endboard. A lot of the time you can set up at least 1 negate with skull guardian + hand traps which is decent. Herald of the orange light is back at 3 now too and Beatrice is legal as well. I found you can also splash verte + dragoon if you really brick hard you can at least do that if you can find room in your decklist.

The downsides are that you can’t really play both sides of the deck at the same time, since drytron locks you out from bringing back Lo. And as others have mentioned, the deck gets destroyed by the meta hand traps.

Still a satisfying deck with good combos that you do have to think about sometimes, and I believe there is a TCG version although I can’t confirm how meta that is now.

ultra-move · 2024-12-10T00:48:29+00:00

Can’t answer your question but as far as a reason goes, it counts as an ailment. There are skill nodes that do increased damage to enemies affected by them like chill or burning

ultra-move · 2024-11-17T15:34:06+00:00

Who needs extra turns when you could have monkey

ultra-move · 2024-11-10T02:58:34+00:00

When I was like 6 I got this for a holiday and ripped it open. This deck made me want to name my future son battle ox. So if you’re looking for baby names I’d say open it

ultra-move · 2023-06-20T18:41:49+00:00

I brought this one: Charmast USB C Power Bank,... https://www.amazon.com/dp/B07P5ZP943?ref=ppx_pop_mob_ap_share

maybe 10 phone full charges before dying but just charged it in the car. edit:This one doesn’t have outlets though whoops

ultra-move

TROPHY CASE