Open-source inference server and production cluster for all the models your agent needs.
State-of-the-Art Embeddings, Retrieval, and Reranking
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Rust library for generating vector embeddings and reranking locally!
Infinity is a high-throughput, low-latency serving engine for text-embeddings, reranking models, clip, clap and colpali
Nornicdb is a distributed low-latency, Graph+Vector, Temporal MVCC with all sub-ms HNSW search, graph traversal, and writes. Using Neo4j Bolt/Cypher and qdrant's gRPC means you can switch with no changes while adding intelligent features like schemas, managed embeddings, reranking+llm, GPU accel, Auto-TLP, Policy-based Memory Decay, and MCP server.
Open-source infrastructure that turns scattered SKILL.md files into curated, retrieval-ready agent-skill corporaβwith retrieval and evaluation tooling included.
Jev-powered relevance filtering and reranking for RAG in Python.
Agentic RAG for local and self-hosted document search: hybrid retrieval, reranking and multimodal RAG on embedded LanceDB, with Docling parsing and an MCP server
MTEB: State-of-the-art evaluation of embeddings across languages and modalities
Deprecated historical repo. Superlinked now develops SIE, a self-hosted inference engine for embeddings, reranking, OCR, extraction, and document processing.
Reproducible benchmark and reference pipeline for reranked long-term memory retrieval
π₯€ RAGLite is a Python toolkit for Retrieval-Augmented Generation (RAG) with DuckDB or PostgreSQL
RankLLM is a Python toolkit for reproducible information retrieval research using rerankers, with a focus on listwise reranking.
Local document Q&A in your terminal β powered by on-device LLMs.
Local VS Code search across Claude Code, Codex, and OpenCode chats with Laya reranking
Sniff out the right record: Jev-powered search for Rails with index-time labels, query understanding, and streamed reranking on top of your own keyword and embedding search
Typed judgment tools for MCP agents. TypeSafe's Jev model as verify, screen, find, classify, rerank, decide, compare, extract, review, gate, and score: the model judges, policy decides auto, review, or escalate.
Small System One decision models (17Mβ400M) for Yes/No, Choice, Score, and reranking. Training toolkit, Python inference, and ONNX support for Node.js and browsers.
Full-stack multimodal product retrieval and personalized reranking with CLIP, FAISS, Spring Boot, FastAPI, and PostgreSQL.