Papr Graph
Upgrade to graph-native vector embeddings
Papr Graph launched on May 19, 2026 with 107 votes, #285 of 20,538 launches that month and more than 95% of that year's launches.
What it does
Papr Graph transforms semantic embeddings into graph-native embeddings with one API call. It encodes temporal, topical, and other dimensions within any embedding, helping agents retrieve answers based on correctness, not just semantic closeness.
Retrieve the right answer, not just semantically similar ones. Encode temporal, topical, and other dimensions into existing embeddings with one APIfrom graph.papr.ai
Does a similar job
all alternatives →
- IMI made a website to semantically search ArXiv papers2024 · papermatch.mitanshu.tech · ▲324
As a grad student (and an ADHDer), I had trouble doing literature review systematically. To combat this, I made a website that finds similar papers using the meaning of the thing I am looking for. I used MixedBread's [^1] embedding model to generate vectors from the abstracts. I store and search similar vectors using Milvus [^2] and finally use Gradio [^3] to serve the frontend. I update the vector database weekly by pulling the metadata dataset from Kaggle [^4]. To speed up the search process on my free oracle instance, I binarise the embeddings and use Hamming distance as a metric. I would…
Graphiti – LLM-Powered Temporal Knowledge Graphs2024 · github.com · ▲142Hey HN! We're Paul, Preston, and Daniel from Zep. We've just open-sourced Graphiti, a Python library for building temporal Knowledge Graphs using LLMs. Graphiti helps you create and query graphs that evolve over time. Knowledge Graphs have been explored extensively for information retrieval. What makes Graphiti unique is its ability to build a knowledge graph while handling changing relationships and maintaining historical context. At Zep, we build a memory layer for LLM applications. Developers use Zep to recall relevant user information from past conversations without including the entire…
Embeddinghub: A vector database built for Machine Learning embeddings2021 · github.com · ▲118The Virtual Feature Store. Turn your existing data infrastructure into a feature store. - featureform/featureform
Python library for embedding large graphs (Written in Rust)2022 · github.com · ▲84Python library for embedding large graphs in 2D space, using force-directed layouts. - H4kor/graph-force
A Parallel Implementation of Graph2Vec2019 · github.com · ▲53A parallel implementation of "graph2vec: Learning Distributed Representations of Graphs" (MLGWorkshop 2017). - benedekrozemberczki/graph2vec
More ai this month
the category →
Paintings by AI models: programs run through a simulation of oil paint.
AI · 20d ago · stillwet.art
PixVerse R2▲381A real-time world model you can explore and change
AI · 28d ago · world.pixverse.video
Source: Product Hunt launch ↗
Launched alongside, May 2026
the whole month →
Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai
Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
Life & fun · May 2026 · github.com
🌱 Private, quiet space for thinking. Simple app for .md files. - zakirullin/files.md
Dev tools · May 2026 · github.com