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Show HN: Mnemo – local-first AI memory layer for any LLM (Rust, SQLite,petgraph)
- georgespencer 4mo agoGiven the abundance of vaguely similar local-first AI memory layers, it might be a good idea to add a "Why Mnemo" section right at the top of README.md to explain why folks should consider using it.
- zaydmulani 4mo ago[dead]
- cush 4mo agoOr just wait a week and whatever’s built into your harness de jour will be as good or better than whatever homebrew solutions are out there > Most LLMs forget everything the moment a conversation ends. mnemo fixes that Even the opening line of the README is obviously very out of date. Might be true if you’re raw-dogging a model or using a basic agent SDK
- zaydmulani 4mo ago[dead]
- SwellJoe 4mo agoAfter working with LLMs a bunch, I now want them to forget everything every time I end the conversation. Otherwise they get dumber and more confused over time. LLMs do not have memory and these "memory" systems that everyone makes don't change that fact. They just clutter up context with probably irrelevant noise. I don't want the LLM to remember everything I've ever said and try to make every project align with often contradictory or unrelated facts, rules, guidelines, practices, whatever, because when it tries it gets messier and makes worse software. I don't want the LLM to be my friend and remember my birthday. I have it write plans, developer docs, test suites, and static analysis into every project. That's the "memory". It's compatible with every agent, it's in their native tongue (Markdown and code), and it's focused on the specific project.
- menno-sh 4mo agoYep, the memory in the ChatGPT macOS app is also starting to piss me off. I think developers generally dislike ‘hidden’ state, which is what memory essentially becomes.
- zaydmulani 4mo ago[dead]
- cush 4mo agoI’m not sure how your reply is related to my comment. Harnesses come with capable memory systems. If you want your harness to forget then turn it off.
- zaydmulani 4mo agoDone "Why mnemo" section added to the README with a comparison table. Short version: single Rust binary, zero cloud, petgraph knowledge graph with multi-hop traversal, scored retrieval. Link in case you want to check it: github.com/zaydmulani09/mnemo
- bilbo-b-baggins 4mo agoYou forgot BM25 embeddings. https://github.com/MikeS071/ai-engram https://github.com/MikeS071/ai-engram https://github.com/lamost423/openclaw-hybrid-memory https://github.com/lamost423/openclaw-hybrid-memory https://medium.com/@qdrddr/agentic-memory-framework-hindsight-with-fts-bm25-hybrid-search-and-rabitq-ce8141a0323e https://medium.com/@qdrddr/agentic-memory-framework-hindsigh... https://clawhub.ai/vnesin-sarai/hybrid-retrieval https://clawhub.ai/vnesin-sarai/hybrid-retrieval https://www.josecasanova.com/blog/openclaw-qmd-memory https://www.josecasanova.com/blog/openclaw-qmd-memory https://medium.com/@richardhightower/stop-the-hallucinations-hybrid-retrieval-with-bm25-pgvector-embedding-rerank-llm-rubric-rerank-895d8f7c7242 https://medium.com/@richardhightower/stop-the-hallucinations... https://github.com/oomkapwn/enquire-mcp#-why-its-the-best https://github.com/oomkapwn/enquire-mcp#-why-its-the-best https://github.com/rohitg00/agentmemory#key-capabilities https://github.com/rohitg00/agentmemory#key-capabilities https://github.com/Melody-0321/NE-Memory-Core https://github.com/Melody-0321/NE-Memory-Core https://github.com/ClaudioDrews/memory-os https://github.com/ClaudioDrews/memory-os https://en.wikipedia.org/wiki/Okapi_BM25 https://en.wikipedia.org/wiki/Okapi_BM25 > It is based on the probabilistic retrieval framework developed in the 1970s and 1980s Anyway, good for ya, hope you had fun building it.
- asdev 4mo agoI haven't seen one unique product in AI, everyone is building the same thing
- andai 4mo agoDo any of them work properly yet?
- fjwood69 4mo agosure they do.. but it's painful how to capture, what to capture, when to capture it.. where to put it.. how to make it 'useful'.. how to reinject it or make it accessible the harness makers may well come up with better means than flat files, but there are loads of folks out there working across different harnesses and in teams, and there's very little that works in that respect. why I built mori - https://github.com/fjwood69/mori https://github.com/fjwood69/mori use it solo, use it in your homelab/office, use it in the cloud with a team..
- SwellJoe 4mo agoEverybody builds one. And, then they usually figure out that making the model fill its context with a bunch of memories hurts performance more often than it helps.
- zaydmulani 4mo ago[dead]
- esafak 4mo agoThat's why I always ask: got benchmarks?
- zaydmulani 4mo agoYes — cargo run -p mnemo-bench. Ships with 12 benchmarks. Full retrieval pipeline is ~4ms on debug build. Numbers are in the README performance table.
- SwellJoe 4mo agoI don't care if it's fast, if it makes the model dumber by cluttering up context.
- zaydmulani 4mo ago[flagged]
- kdkdkdjdksksn 4mo ago[dead]
- phantomathkg 4mo agoIs there any relevance with another tool call mnemon?
- zaydmulani 4mo agoDifferent project — mnemon is a Python-based memory tool. mnemo is a Rust binary with a knowledge graph layer and REST API sidecar. Similar name, different approach.
- rayan_ 4mo ago[flagged]
- ksajadi 4mo agoI tend to agree with the rest of the commenters that the most likely outcome is that harnesses will include features like this. I had a slightly different issue and that was 'project-level memory' that i can use across models or harnesses (chat, claude code, etc). for a while i used Obsidian but it was not very good with hosted tools like claude.ai then i moved to a combination of Linear and Notion. Still using Linear but Notion ended up being a royal pain: it is built for humans not agents. It is block based and when multiple agents use it there is a lot of corruption in the process. I wanted a markdown only, notion built for agents that can work with multiple agents so built one: markbase.cloud feel free to try and use it. i think it's useful
- zaydmulani 4mo ago[dead]
- fjwood69 4mo agoYes, the multi-agent governance takes a lot of solving.. thus far I've gotten Hermes writing to the same memory store that Claude code, antigravity, cursor, etc can all contribute, pull from, but it's taken a whole separate layer of governance. Agents that can write to shared memory are powerful. Agents that can write to shared memory without oversight are a liability. Mori has the governance layer - https://github.com/fjwood69/mori https://github.com/fjwood69/mori
- pylotlight 4mo agoBrew installation? Not looking to use pip or load manually. For single bins or otherwise, brew is definitely preferred.
- zaydmulani 4mo agoHomebrew tap is on the roadmap. For now the fastest path on Mac is cargo install --path crates/mnemo-api or the Docker one liner. Will add a brew tap for v0.2.0.
- vichoiglesias 4mo agoI think we are all experiencing more or less the same kind of pain regarding memory+llms, and love to see how different approaches exist this problem. How does mnemo decides when to forget something? So old history wont pollute the new answers?
- zaydmulani 4mo agoCurrently mnemo doesn't have automatic forgetting it's on the v0.2.0 roadmap. The mitigation right now is that retrieval scoring weights recency, so older chunks naturally rank lower than recent ones. A TTL system and explicit memory decay are the right long-term fix. Good callout.
- fjwood69 4mo ago[flagged]
- andywidjaja 4mo agoNice approach, the Rust performance and single-binary deployment are compelling. Question, how do you handle contradictory facts? If John moves from Stripe to Google, does the graph resolve that, or does it store both?
- zaydmulani 4mo ago[flagged]
- Pixel-Labs 4mo ago[flagged]
- xuanlin314 4mo ago[flagged]
- zamalek 4mo ago> and injects relevant context back into future prompts It looks like this is left as an exercise for the student?
- zaydmulani 4mo ago[flagged]
- xuanlin314 4mo ago[flagged]
- jazzen 4mo ago[flagged]
- sikamikanikobg 4mo ago[flagged]