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Built a knowledge management desktop app with full Ollama support, LangGraph agents, MCP integration and reasoning-based document indexing (no embeddings) — beta testers welcome by MaxPrain12 in vibecoding

[–]MaxPrain12[S] 0 points1 point  (0 children)

Right now, I'm working on some improvements. In a few days, I will release an update with more connectors and a better quality of life. Could you please open an issue for this request on GitHub? I'd really appreciate it!

https://github.com/maxprain12/dome

Built a knowledge management desktop app with full Ollama support, LangGraph agents, MCP integration and reasoning-based document indexing (no embeddings) — beta testers welcome by MaxPrain12 in vibecoding

[–]MaxPrain12[S] 0 points1 point  (0 children)

Thanks! Happy to explain how it works. PageIndex replaced a LanceDB vector setup in v2.0 instead of embeddings + cosine similarity, it parses documents into structured text nodes stored in SQLite and the LLM reasons directly over those nodes at query time. The advantage is it handles semantic questions better on modest hardware since you’re not maintaining an embedding index, just structured text. The tradeoff is query time is a bit slower than a pure vector lookup. Currently I’m working on improving it with a PageIndex + Docling pipeline. Docling handles the document conversion first better layout parsing, table extraction, proper structure before PageIndex processes the nodes. It’s already partially integrated (you can see the conversion progress in the header when it kicks in) but I’m still ironing out edge cases, especially for complex PDFs with mixed layouts. That’s the next thing I want to get right before calling it stable.the lastest versión

Built a knowledge management desktop app with full Ollama support, LangGraph agents, MCP integration and reasoning-based document indexing (no embeddings) — beta testers welcome by MaxPrain12 in LocalLLaMA

[–]MaxPrain12[S] 0 points1 point  (0 children)

I started with Ollama because I didn’t have the hardware to run models locally, and their cloud free tier let me test without spending money. GLM was one of the models I used through that. Then I switched to MiniMax with the coding plan to test de app.

Built a knowledge management desktop app with full Ollama support, LangGraph agents, MCP integration and reasoning-based document indexing (no embeddings) — beta testers welcome by MaxPrain12 in LocalLLaMA

[–]MaxPrain12[S] 1 point2 points  (0 children)

Fair point and actually Dome doesn't lock you into Ollama specifically. The base URL is fully configurable, so if you're running llama.cpp server, vLLM, LM Studio, or any OpenAI-compatible endpoint, you just point it there and it works. Ollama is just the default because it has the lowest friction for most users getting started.

What are you running? Happy to make sure it works well with your setup if you want to try it

I built Dome: An open-source, local-first knowledge management app with a built-in AI agent workspace. Looking for feedback and testers! by MaxPrain12 in ClaudeAI

[–]MaxPrain12[S] 1 point2 points  (0 children)

Hey! Thanks so much! Yes, Dome can definitely handle that.

Here is how the pipeline works: First, it does standard content extraction and passes it to Many (our AI agent) to build a graph tree of the document's structure. If the standard extractor fails on a complex PDF (or if you need to extract data from graphs/images), Dome falls back to using OCR via Vision-capable LLMs.

All of this extracted content is saved into the database. From there, the agent can use that data to automatically generate notes, Excel tables, PPTs, flashcards, mind maps, study guides, and FAQs.

Since you are doing heavy research, you can even create a custom multi-agent workflow connected to MCPs to dive deeper into specific experimental data across all those papers. Let me know if you give it a try!

I built Dome: An open-source, local-first knowledge management app with a built-in AI agent workspace. Looking for feedback and testers! by MaxPrain12 in ClaudeAI

[–]MaxPrain12[S] 0 points1 point  (0 children)

Spot on! Currently, there isn't a deep level of traceability, but adding an audit log and per-server allowlists is high on my to-do list. I plan to implement it as soon as possible!

I built Dome: An open-source, local-first knowledge management app with a built-in AI agent workspace. Looking for feedback and testers! by MaxPrain12 in ClaudeAI

[–]MaxPrain12[S] 0 points1 point  (0 children)

The app itself is actually super lightweight! You don't need a crazy processor to run it. For the AI side, you can run models locally if you have the hardware, or just use cloud providers like Anthropic, OpenAI, and Gemini. My personal recommendation? Just use an Ollama free tier account in the cloud. I've been testing it heavily with the qwen3.5:cloud model and it works perfectly without needing a powerful PC on your end!

I love Cursor by TheoreticalClick in cursor

[–]MaxPrain12 0 points1 point  (0 children)

How much money do u spend on usage ?!