u/Aggressive-Dream5465

Let me be frank: these companies are a fucking cancer.

I would gladly drink my coffee while they all burn down. Honestly. And I am not trying to please anybody. I fucking hate them all, vehemently. And their CEOs are worse than poverty + hunger.

Maybe you disagree, I don't give a fuck.

Apart from that, I have been using GPT Luna and damn! What a great model to use with PI.

Yes!! I know they will do something utterly stupid soon. They will nerf the model, or they will increase the price, or they will just replace it with a dumb alternative and still call it "Luna", but I really think you should try it.

I have been using Claude for over a year, Pro and then Max, and although it has significantly helped me build a couple of personal projects that would have otherwise required considerable time, or even a team, I have noticed that it is virtually impossible to finish anything.

Even though I have tried to be extremely precise and descriptive with my prompts (detailing the bugs, describing the issues, and pointing exactly to where the problem lies when I am able to identify it), the models always fix one thing while breaking another in such a subtle way that I only realise the issue exists later on.

This forces me to return to Claude every day and burn through my quota to fix yet another thing that was previously not a problem. With projects like mine, two issues arise: firstly, almost without noticing, you become so frustrated with the cycle that you lose track of what is going on; secondly, you develop a dependency that keeps you hooked on the subscription.

This latter point is what I have started to realise may be the real business model of these companies, as I assume this is not unique to Claude. The models never truly let you finish something, or they demand significant time and money to reach a point where the output is actually usable.

I acknowledge that bug-free software is, to some extent, a utopia: software always ends up with minor flaws here or there that require refinement or small fixes. However, what I am referring to regarding Claude seems almost deliberate; it feels specifically and meticulously designed to keep you returning every day to use the service, making you believe the work is complete when, in reality, there is yet another hidden issue that was not there yesterday.

I understand this may sound like a conspiracy theory, or suggest some degree of incompetence on my part, but I genuinely have nothing to gain from an anonymous rant on Reddit. This will not fix my issues. I genuinely want to understand if other users have reached the same conclusion, because although at the beginning it feels like you are advancing, you eventually reach a point where you realise you are going nowhere.

The tipping point that made me think this might be a complete waste of time and money was Opus 5. It is genuinely one of the most unreliable models I have ever dealt with. It seems incredibly capable at first, but you soon realise it overcomplicates the code for absolutely no reason. Everything it outputs ends up so brittle and inefficient and labyrinthical that you are just forced to go right back and use it again to clean up its own mess.

I use the free API of Mistral.

The only way to change the temperature of a Mistral model is by creating an agent.

When you do this, you get a agent ID.

Something that looks like this: ag_342oedf203kd34234324

So, my question is this:

Is there a way in auth, settings or models to point at a specific agent from Mistral?

Can anybody please point me to the right plugin to have visibility on this?

How accurate is that calculation?

Thanks.

I can download this model from LM Studio or HuggingFace but Ollama only provides a version by Betiai. I just want the official shit.

I developed a small app to create a RAG index. This app uses an local embedding model I via Ollama. When the index is building (meaning the embedding model is working) I cannot use Gemma4:12b, even though there is plenty of memory free and even though I can see the model is already loaded.

So, I do not understand why is this happening. As mentioned before, I can literally see that Gemma4:12b is there, via "ollama ps" and the OS monitor app.

I live on a remote British island as a foreigner. My wife, who is native to the island, asked for a divorce. Our relationship has deteriorated over the years. No violence or abuse of any form is involved. It is simply over. We have a toddler whom I love very deeply and who has become the cornerstone of my existence.

The court has decided to give my wife the house and, to make things even worse, I have lost my job, as I was on a fixed-term contract. It is financially impossible for me to stay on the island, which means I have little chance of staying close to her. Knowing how difficult it will be for me to stay in contact with my daughter from now on scares me to death. I am going through severe depression in a place where I have no friends or other family.

It is difficult for me to articulate what is going on inside me right now, but it is a darkness and sadness that is devouring me, and deprives me of motivation to do anything. Every second I spend with my daughter feels like a goodbye, and it breaks my heart to know I will not be able to see her grow up. I would like advice from parents who have experienced similar situations.

Gemini is incredibly lazy. Every time I ask it to do something I spend ages writing a thorough prompt but it simply doesn’t bother. I end up wasting my whole day arguing with it almost wishing it were a real person I could punch. This model seems designed to drain your time and make you hate life.

The main reason I started using Pi is its minimalistic philosophy and its organic local model integration. No bloat should mean more efficiency and speed, while local models provide privacy, independence, and autonomy. In fact, I use Pi solely to run local models; if I wanted to use cloud models, Pi would be my last choice.

However, the “Working” status has become so incredibly slow with local models that it is completely ruining the experience. It feels like cloud models are becoming mandatory for this harness to have any value.

To clarify, “Working” is Pi’s status during the interval between a user submitting a message and the model beginning to stream its response. A lengthy delay here is only understandable under two conditions:

• After the first message: When the system loads the initial session context, including agents.md, system prompts, and skills.
• During task execution: When the agent is actively calling tools or processing background operations.

Outside of these scenarios, the current behaviour during standard interactions is entirely unreasonable, making the agent practically useless for local setups.

The issue is not a lack of hardware memory or the size of the model, nor is it caused by agents.md, extensions, or prompts. The bottleneck is Pi itself. Even for basic messages, the “Working” status remains exceptionally slow. Sending a simple “Hi” in the middle of a session triggers a 3-to-5-minute “Working” phase, followed by a prolonged “Thinking” state, before any text is finally generated.

This latency persists despite extensive troubleshooting:

• It occurs even when running pi --no-extensions.
• It happens without an agents.md file present.
• It persists when using highly lightweight local models, such as ministral3:8b via Ollama.
• It occurs after completely uninstalling and fresh-reinstalling Pi.

Something is fundamentally broken in the pipeline. The severe delay has made interacting with the agent so tedious that I am starting to avoid using it altogether.

I need to understand if this is being addressed by the developers, or if it is simply not a priority, so I can decide whether to keep using this harness. This is not a melodramatic threat, but an honest question. I would entirely respect the developers stating, “This is not our priority”; I just need to know the roadmap here to make an informed choice.

Each update is worse than the previous one.

The models dont reply, they get stuck in the pre-thinking for more than 5 minutes. And then they release some bullshit update fixing the issue just to make it worse. I am so fucking fed up with this shit. I should move to LMStudio.

Not sure what is happening, but the “working” is extremely slow after the new update. Is anybody experiencing the same issue with local models?

Every time I am working with any of the models from Google in Antigravity, I face one specific problem: the agents always assume everything. They jump to conclusions. They take for granted contexts which they have not verified.

This leads to two scenarios: waste of time for the user, and destroying settings that were not broken to start with.

This kind of issue seldom happens with basic models of Claude or Codex. Their models at least have the decency to ask the user questions before reaching a conclusion.

Google seems to be breeding a type of agent that is sycophantically eager to act without thinking and fuck up previously done work.

Please, Google engineers, train your models so that they ASK QUESTIONS!

Hey everyone,

Like a lot of you, I have a massive Calibre library (7,000+ DeDRM EPUBs).

Although I read a lot, sometimes I struggle to know what to read next, or what books addresses specific topics, or how are those topics addressed, how can I connect a current read to another one to follow a topic-related path.

So, in other words, I wanted a way to actually interact with that hoard of knowledge using AI—asking questions across hundreds of books at once, finding specific philosophical arguments, or cross-referencing authors—but I absolutely refused to upload my personal library to OpenAI or pay for a cloud subscription.

So, I built Ollama Pi Chat. It’s an open-source, local-first desktop app that acts as a secure wrapper for Ollama, but with a heavily engineered offline RAG (Retrieval-Augmented Generation) engine built specifically for massive EPUB libraries.

I'm going to try to explain how it works:

• Point it at your Calibre Folder You don’t need to move or convert your books. Just point the app’s indexer at your Calibre Library directory, and it will safely parse the raw text from your EPUBs. The app does not edit or touch your ebooks in any way, it only reads them.
• Ultra-Compact Database (No Bloat) Most vector databases explode in size if you feed them thousands of books. I engineered this to use Matryoshka semantic compression (256-dimension vectors) and SQLite external-content tables. The result? You can index the mathematical meaning and text of 7,000+ books into a single database that is less than 10 GB.
• 100% Local & Private It runs entirely on your hardware using Ollama and local embedding models. No internet required, no API keys, and your data never leaves your machine.
• Bulletproof Indexing for "Omnibus" Books If you have massive "Complete Works" EPUBs that usually crash standard parsers, this handles them smoothly using in-memory ZIP streams. Plus, the indexing job is 100% resumable. If you close your laptop halfway through indexing your library, it picks up exactly where it left off.

If you want to give it a try, the repository is here: https://github.com/DuckTapeKiller/ollama-pi-chat

https://reddit.com/link/1tuosil/video/h09ykrqe825h1/player

Hey everyone,

I recently built my own custom AI client—a brutalist GUI wrapper for Ollama that lets local models natively fact-check using Britannica, Wikipedia, and run various other custom skills.

The app runs entirely offline via a local server and exposes the chat interface on localhost, meaning I interact with my models directly in the browser.

My question is: Is there any way or workaround to configure the Brave Browser to replace its built-in "Leo" assistant with my own custom localhost GUI?

Ideally, I'd love to click the native Leo sidebar button and have it open my local Ollama interface instead of pinging Brave's cloud models. Has anyone managed to route Leo's integration to a custom 127.0.0.1 endpoint?

In case none of this makes snese, this is essentially what I built: https://github.com/DuckTapeKiller/ollama-pi-chat