Anyone have experience running local Ollama AI for automation projects? Seeking advice

Willis Rice

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Hey everyone,
I’ve been messing around with local LLMs using Ollama for a while, but I'm hitting the point where I need to take things to the next level and I'm looking for some advice from anyone who has experience here.

I am building a custom AI backend for automated assistant bot Right now, I'm using Ollama to run the models, but I need the agent to have long-term persistent memory and a strict, consistent persona that doesn't break character.

The Problem:
Ollama is great for testing out of the box, but handling dynamic memory (saving past chats) and keeping the bot acting exactly how I want it to over long conversations is getting tricky. I'm moving toward building a custom programmatic architecture (using Python/TypeScript) to handle the prompt stitching and database memory outside of Ollama.

What I’m looking for advice on:

  1. Has anyone successfully built a persistent memory system (like SQLite or vector databases) that feeds context into a local Ollama model?
  2. For those running custom personas—are you just using really good dynamic system prompts, or did you actually bite the bullet and fine-tune (LoRA) your own base model?
  3. Are there better alternatives you'd recommend over Ollama if my main goal is full API control and raw, unfiltered outputs?
Would love to hear from anyone who has built custom stacks around local models. Thanks!
 
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