#embeddings

Production-ready AI Business OS — 46 autonomous AI Employees, Graph RAG (Neo4j), multi-channel, BYOK across 17 LLM providers plus custom/local endpoints (Ollama), automatic fallback. 8 libs (Python+Java). Self-hosted, MIT licensed, guardrailed autonomy for regulated industries.

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Memory and knowledge service, MCP and TUI for AI agent workflows.

On-device memory layer for AI agents. Claude Code, OpenClaw and Hermes. Hooks + MCP server + hybrid RAG search.

EverAlgo is the algorithm library behind EverMind's memory system — stateless, storage-free, focused on extraction and ranking only. Orchestration, persistence, and routing live upstream in evermem.

OpenCodeRAG is a RAG (Retrieval-Augmented Generation) plugin for semantic code search powered by locally-hosted embedding models. It features a seamless integration with OpenCode and offers a CLI interface for external usage.

A foundation model-agnostic library for accessing generative AI services

Unofficial Python CLI for the Venice.ai API — image, video, audio, TTS, chat, and embeddings from the terminal.

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Semantic code search for coding agents — search by meaning like grep, trace call graphs, find tests & blast radius. 100% local embeddings (ONNX/MLX), MCP server, plugins for Claude Code, OpenCode, Codex & Droid.

Private search and Q&A for your documents. One binary that watches your folders and answers questions with citations, fully local.

A fast, single-binary C database that gives AI agents durable, searchable long-term memory — with a Claude Code integration.

The Voyage AI Provider is a provider for the Vercel AI SDK. It provides a simple interface to the Voyage AI API for embeddings model

Code retrieval for AI agents: one call returns the exact code, verbatim with true line numbers, instead of 20 greps. The whole index is one SQLite file — no vector DB, no daemon. MCP server for Claude Code, Cursor and Codex.

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finished this nest while your build was still going

😈 The zero-bs JavaScript-based search engine. Fulltext & vector search wherever JavaScript runs.

Provide best practices for LMOps, as well as elegant and convenient access to the features of the Qianfan MaaS Platform. (提供大模型工具链最佳实践，以及优雅且便捷地访问千帆大模型平台）

Self-improving context & memory for Claude Code and OpenAI Codex. One canonical knowledge store injected only when relevant — hooks push budgeted context, an MCP server serves depth on demand, and it learns lessons from your sessions. Agent memory + context engineering as a single static Go binary.

Model-agnostic multi-modality generation server with plugin discovery: OpenAI-compatible TTS, embeddings, and image generation. Drop a Python file in ~/.muse/models/ to add a backend.

A verifiable memory layer for language models — facts in a graph, every claim with its source.

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Object-store-native vector database — releases and product home. One static binary, durability from your own bucket.

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