A zero-embedding approach to video intelligence, using Jev: contact sheets + typed decisions, as MCP tools and a skill for any coding agent.
Inference code for QUAN-Transcribe: fast Vietnamese speech recognition on EmbeddingGemma 2
Offline multi-speaker meeting-speech toolkit: planted-ground-truth synthetic meeting factory, VAD, speaker embeddings, diarization (AHC/spectral/VB-HMM), overlap detection, CTC speaker-attributed ASR, cpWER/DER/JER evaluation, online streaming mode, deterministic reports. NumPy core, CPU-only torch extra.
The #1 AI Harness for Building Resumes, PDFs, Cover Letters & more, locally with 100+ LLMs support.
How Python does AI. Agents, realtime voice, image generation, embeddings. Every model, every interface, typed end to end.
State-of-the-Art Embeddings, Retrieval, and Reranking
Use PEFT or Full-parameter to CPT/SFT/DPO/GRPO 600+ LLMs (Qwen3.8, DeepSeek-V4, GLM-5.1, InternLM3, Llama4, ...) and 300+ MLLMs (Qwen3-VL, Qwen3-Omni, InternVL3.5, Ovis2.5, GLM5.3, Gemma4, Llava, Phi4, ...) (AAAI 2025).
RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.
A very simple framework for state-of-the-art Natural Language Processing (NLP)
Automation foundation model for tiny devices: 2-bit, 8-29 MB, tool calls, ASR, structured extraction and embeddings on phones, wearables, smart homes, robots, cars and microcontrollers.
💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows
🔍大模型应用开发实战一:RAG 技术全栈指南,在线阅读地址:https://datawhalechina.github.io/all-in-rag/
Leveraging BERT and c-TF-IDF to create easily interpretable topics.
Fast and Accurate Code Search for Agents. Uses 99% fewer tokens than grep+read
A Low-Code MCP Framework for Building Complex and Innovative RAG Pipelines
Semantic search over videos using Gemini Embedding 2 or Qwen3-VL.
A python library for self-supervised learning on images.
MTEB: State-of-the-art evaluation of embeddings across languages and modalities
Open-source inference server and production cluster for all the models your agent needs.
Fast, Accurate, Lightweight Python library to make State of the Art Embedding
A persistent, unified memory layer for all your AI agents (e.g. Claude Code, Codex, DSH), backed by Markdown and Milvus.
The collection of pre-trained, state-of-the-art AI models for ailia SDK
Fast State-of-the-Art Static Embeddings
🤖 A Python library for learning and evaluating knowledge graph embeddings
A robust, all-in-one GPT interface for Discord. ChatGPT-style conversations, image generation, AI-moderation, custom indexes/knowledgebase, youtube summarizer, and more!
WeMM-Embedding is a family of universal multimodal embedding models by the WeChat Vision Team at Tencent, supporting multimodal understanding and retrieval.
All-in-one training for vision models (YOLO, ViTs, RT-DETR, DINOv3): pretraining, fine-tuning, distillation.
Extensible, parallel implementations of t-SNE
Solves basic Russian NLP tasks, API for lower level Natasha projects
local-first semantic code search engine
MemeMeow 是一个基于自然语言的表情包检索工具。基于agent自动标注表情包含义,只需描述想要的场景或心情,快速找到合适的表情包。
The OWASP DevSecOps Guideline can help us to embedding security as a part of the development pipeline.
Learnable latent embeddings for joint behavioral and neural analysis - Official implementation of CEBRA
[IEEE T-KDE 2026] Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).
ID-based RAG FastAPI: Integration with Langchain and PostgreSQL/pgvector
Embedding-based discovery of duplicated logic for projects too large or messy to maintain reliably
This repo contains the code for "VLM2Vec / MMEB" [ICLR 2025], "VLM2Vec-V2 / MMEB-V2" [TMLR 2026], and "MMEB-V3" [COLM 2026]
Open-source infrastructure that turns scattered SKILL.md files into curated, retrieval-ready agent-skill corpora—with retrieval and evaluation tooling included.
RAGLight is a modular framework for Retrieval-Augmented Generation (RAG). It makes it easy to plug in different LLMs, embeddings, and vector stores, and now includes seamless MCP integration to connect external tools and data sources.
A flexible, adaptive classification system for dynamic text classification
Inference engine for Intel devices. Serve LLMs, VLMs, Whisper, Kokoro-TTS, Embedding and Rerank models over OpenAI endpoints.
An open-source intelligence (OSINT) analysis tool leveraging GPT-powered embeddings and vector search engines for efficient data processing
RESTai is an AIaaS (AI as a Service) open-source platform. Supports many public and local LLM suported by Ollama/vLLM/etc. Precise embeddings usage, tuning, analytics etc. Built-in image/audio generation with dynamic loading generators. Live chat deployment. Built-in block based graphical language. Prompt versioning and much more...
Established strong JEV based natural language to SQL performance and well-covered semantic operators for PostgreSQL(PG) with optimized cost and latency. Reusable evidence, with native execution, parallel plans and explainable embeddings in development preview.
RAG ReAct Agent - A Retrieval-Augmented Generation system with ReAct (Reasoning+Acting) agent loop for intelligent question answering with multi-hop reasoning
Turn scattered notes, docs and transcripts into a queryable Markdown wiki — an LLM knowledge-base compiler with MCP access, no embeddings, self-hosted.
Pretrained text classifiers you can run and retrain on CPU
Shared memory for AI coding tools: hybrid search, cited Q&A, harness memory discovery and a built-in Web console. Local index, MCP + HTTP.
A local acoustic control system that learns user-defined labels for the surface or location of knocks, such as desk or wall. It also counts threshold-qualified knocks within each captured window. By default, a frozen Microsoft BEATs Iter3+ AS2M encoder creates 768-D audio embeddings and an incremental classifier learns the user's labels.
Meet JevEmbed — turn embeddings into decisions. Choose, score, and judge with your choice of embedding model.
Local-first RAG MCP server in Python: hybrid search (semantic + BM25 keyword boost) over your own documents. 11 MCP tools + CLI, markitdown ingestion for 12 formats, multilingual embeddings, LanceDB. Nothing leaves your machine.
AD-E2E-JEPA: A Joint-Embedding Predictive Architecture For End-to-End Autonomous Driving
Official code for the paper "A New Role for Relevance: Guiding Corpus Interaction in Agentic Search"
A next-gen long-term memory engine for AI apps: self-organizing spatial regions, memory dynamics (Ebbinghaus reinforcement / decay / consolidation), and explainable 8-signal retrieval. Runs offline with zero config; works with any OpenAI-compatible LLM/embedding, cloud or local. Chinese-friendly. Benchmarked head-to-head vs Mem0 and bare RAG
Zero downtime embedding upgrades
EmbeddingGemma2 resources: local search apps, decision models, inference frameworks, tutorials, and datasets. English / 简体中文.
Standalone multi-reference image conditioning for LTX-2.5 in ComfyUI, with MSR LoRA slot embeddings and negative temporal offsets.
Code, datasets, and results for "The Embedder's Dilemma: LLMs Are Better, but at What Cost?" (COLM 2026). MTEB(LLM) benchmarks 10 LLMs and 26 embedding models on 37 tasks with full cost and throughput accounting.
A pure-Python system that automatically discovers, verifies, and applies relevant historical requirements for coding agents — no embeddings, no vector database, no LLM calls. Companion code for the Towards Data Science article on intent continuity.
Meet KaLM-Jev — your local, Jev-style judgment engine, available in Nano, Small, and Large.