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#vector-database
41 items
Show HN: XTrace – Encrypted vector DB (search embeddings without exposing them) (github.com via hn) how to build a persistent memory layer like recall? (www.reddit.com) I've been testing recall 2.0 and their context layer is exactly what i want. it sits outside the chat, ingests all my github repos and web research, and then feeds the exact right context into claude when i ask a question.
Show HN: Open-source Perplexity clone one file back end, streaming answers (github.com via hn) I built an open-source research agent. You ask a question, it searches the web via Tavily, synthesizes an answer with an LLM, and shows the sources it used.
We built and open-sourced Caliby: An embedded, high-performance vector database for AI Agents (Beats pgvector by 4x, outperforms FAISS on disk) (www.reddit.com) Hi Reddit, we are a team of database researchers (including a PhD from MIT DB Group) and we just open-sourced an embedded vector database for agent/LLM applications. An embedded vector database supporting both text and vectors.
Why your AI agent’s "memory" is a data breach waiting to happen. (www.reddit.com) We are all building AI agents with "memory" right now. It is super easy to get a single-tenant agent working locally.
how do you design an ai agent to handle heavy data processing and large files? (www.reddit.com) looking for architectural patterns on handling data gravity in production agent pipelines. every tutorial I've found assumes light text payloads or short tool-calling loops, but once your agents have to actually interact with massive sourc…
Open-source CLI that turns a folder of docs into a queryable wiki — no vector DB, no chunking (www.reddit.com) Been looking for a self-hostable way to maintain a personal knowledge base from research docs without the complexity of setting up a vector database, writing chunking logic, and babysitting embeddings. Ran into OpenKB this week and it's cl…
MiniVecDb – A 50KB, 1-bit quantized vector database for the browser (github.com via hn) MicroVecDB 50 KB · 0 runtime dependencies · 32× less RAM than pgvector · runs entirely in the browser A vector database compiled from Rust to WebAssembly. It stores embeddings with 1-bit quantisation, indexes them with HNSW, and searches i…
A new evolution of Vector Database, add to your toolkit (github.com via hn) TensorTree TensorTree is a developer-friendly approach to semantic memory built on top of SOP’s KnowledgeBase architecture. Repository layout docs/architecture.md — high-level architecture notes src/examples/clikbdemo/ — the single runnabl…
Lessons We Learned Building a RAG Assistant Without a Separate Vector Database (blog.devgenius.io via hn) How we used StarRocks, Gemini, and tool-based retrieval to power grounded Q&A in a developer community Slack. 9 min read 7 hours ago Author:Billy Chang, Software Engineer at Phoenix AI Press enter or click to view image in full size StarRo…
Open Source Agent, Harness-1, Outperforms GPT-5.4 on Recall (venturebeat.com via hn) A joint research collaboration between researchers at the University of Illinois at Urbana-Champaign (UIUC), UC Berkeley, and the open source AI-native vector database platform Chroma unveiled Harness-1, a 20-billion parameter open-source…
The Self-Healing Vector Database (www.reddit.com) A pattern I keep seeing in agentic RAG systems: The agent is smarter than the retrieval layer. It can notice that context is stale.
How does a Claude Code agent navigate hundreds of skills in a second? (www.reddit.com) I asked my agent: "do an SEO audit on my Shopify store." It searched its skill library, 686 skills sitting in a vector database, in under a second and returned its top candidates. Five of the top seven were exactly what you'd want: seo-con…
Show HN: Vecdb – local-first hybrid vector database in Rust (HNSW and BM25) (github.com via hn) vecdb Open source, production-grade vector database written in Rust. What is vecdb?
AionDB: PostgreSQL-compatible SQL, graph, and vector database in Rust (aiondb.xyz via hn) PostgreSQL wire / ORM-compatible / SQL + graph + vector AionDB PostgreSQL tooling for applications that need relational records, graph relationships, and vector search in one Rust engine. MATCH (u:User {tenant_id: 100})-[:WROTE]->(d:Docume…
Show HN: I built a search engine for llms.txt sites (statespace.com via hn) More and more developer tools are adopting the llms.txt standard to build AI-friendly versions of their docs. The problem is that it's very hard to search across them.
↯ Mistral↯ Function Callingfunction-callingvector-databasemistral+1
FerresDB is now open-source – A high-performance vector database (github.com via hn) FerresDB Core High-performance vector search engine written in Rust, designed for semantic search, RAG (Retrieval-Augmented Generation) and recommendation systems. Overview FerresDB Core is a Rust vector search engine for semantic search,…
RAG isn’t for conversation transcripts (www.reddit.com) Documents are authored, bounded, and self-contained. They carry their own semantic links and can be represented as a wiki or cleanly split into overlapping chunks.
Is anyone else using Cursor to build local VRAM/RAG architectures instead of just wrapper apps? Here is my 8-month deep dive. (www.reddit.com) I'm completely lost in the Agentic Maze. What level to learn. how to organize stydu (www.reddit.com) LogosDB: Fast Semantic Vector Database (github.com via hn) LogosDB is a fast semantic vector database written in C/C++ that provides approximate nearest-neighbor search over embedding vectors with associated text metadata. Authors: Jose (@jose-compu) Features Vectors and metadata are stored as fla…
Forked CozoDB to give agents cognitive primitives (news.ycombinator.com) CozoDB is an embedded relational-graph-vector database created by Ziyang Hu and the Cozo Project authors. It does Datalog, vector search (HNSW), and full-text search in a single embedded engine and was created with the vision to be the “Hi…
Skeg: A vector database that gives the RAM back to your model (github.com via hn) skeg Vector database and context layer for AI agents. Multi-tenant, RAM-frugal.
Agentic Architecture. (www.reddit.com) I am looking to develop an agentic Environment for my company, we use databricks azure for infrastructure and vs code as the editor. My idea is to have a system that will have access to our documentation/business logic, our code and unity…
How I wired a Graph DB on top of my vector store to scale 1K agents for 2 months, because vector search alone fails when user preferences change over time. (www.reddit.com) Most agentic memory patterns are naturally designed around short-lived chat sessions. The focus there is straightforward: track the active thread, keep a basic user profile, and reset the context once the conversation closes.
Simultaneous search by vector database and rating (www.reddit.com) I have a travel AI service. It has a database of 1M+ tourist objects.
Memory and Continuity Solution (www.reddit.com) If you need a simple - low cost solution to keeping your ai consistent and need solutions for memory or continuity here is the offer. The simplest persistent memory system for AI agents and companions.
From Vector Database to Vector Lakebase (zilliz.com via hn) From Vector Database to Vector Lakebase Today, we're launching the public preview of Zilliz Vector Lakebase — the next chapter for Zilliz Cloud. Vector Lakebase is the next step beyond vector databases.
Show HN: Query years of Ask HN and Show HN discussions as a knowledge graph (github.com via hn) I built lightrag-snkv, Basically it uses lightRAG https://github.com/HKUDS/LightRAG ,this requires various storage databases like key value store, graph database, vector database, I built single embedded file based database which covers al…
LangGraph and Cosmos DB: one back end for agents, memory, and RAG (devblogs.microsoft.com via hn) Build AI Agents and RAG Applications with the New LangChain + LangGraph Connector for Azure Cosmos DB Building AI agents and RAG applications today means stitching together half a dozen services, a vector database, a chat history store, a…
I almost shipped OpenAI embeddings until an MTEB rank #130 model beat them by 11% (www.reddit.com) I just interviewed Michael Maximilien, former CTO at IBM and Chairperson of NodeJS Foundation, who spent a year shipping production RAG to multiple customers. His lesson was uncomfortable.
anyone else trying to pipe their own data into claude via mcp? (www.reddit.com) I'm trying to build a reliable local RAG setup for claude and it is just exhausting. I want claude to have access to my github repos and past project docs without me copy-pasting everything into the window every morning.
Five Components of Agent Memory, Implemented in Plain Markdown (www.reddit.com) An agent memory system, to actually be useful, has to do five things: persist information across sessions, give it structure, support retrieval, allow writeback, and handle forgetting. Most current implementations cover two or three of the…
I almost built RAG for my notes, then realized I didn't have a retrieval problem at all (www.reddit.com) My notes live in Obsidian. My reading and highlights live in Readwise.
Show HN: Covalence – Cross-Client Memory for Claude, Cursor, and MCP (macOS) (covalence.app via hn) I use Claude Desktop, Claude Code, and Cursor daily. They all have memory now, but none of them share it.
A clean breakdown of RAG vs MCP architectures for AI Agents (www.reddit.com via reddit) ↯ Model Context Protocolvector-databasemodel-context-protocolrag+1
Cognitor: open-source semantic search engine. Automatically chunks, embeds and indexes the content of a target folder, making it searchable semantically. (www.reddit.com via reddit) https://github.com/tanaos/cognitor Cognitor is an open-source semantic search engine and vector database which automatically chunks, embeds and indexes the entire content of a target folder (and its subfolders), making it easily searchable…
Better to obsess over an Agent Wiki than complex Agent frameworks (www.reddit.com via reddit) It is exhausting to see agent frameworks dropping every week that feels incomplete. you build a custom setup today and someone suggests a better one tomorrow.
I built a RAG system for the first time. Here's what nobody told me would be the hard part (www.reddit.com via reddit) Had been reading about RAG for months before I actually built one. Every explanation made it sound straightforward.
mnemo - a local semantic memory for Claude Code (early stage, looking for testers and contributors) (www.reddit.com) Most "AI memory" tools make the vector database the source of truth. Which means your knowledge is opaque, hard to inspect, and one corruption away from being gone.
Up-to-date docs for Cursor, without the bloat, across the whole web (www.reddit.com) LLMs are trained on a snapshot of the web: APIs change, libraries update, and models confidently generate code that no longer works. The problem gets worse with newer or more niche devtools.