embeddings

Agentize is an open-source tool that lets websites expose a first-party semantic search/index interface for AI agents. It builds a semantic index from owner-selected sources, serves Markdown and canonical URLs from the site’s own domain, and supports local embedding generation.

Deterministic retrieval-only Q&A system for documentation that avoids LLM calls at runtime. It uses Gemini embeddings, local Qdrant storage, and a CLI chatbot to answer questions with low latency and near-zero per-query cost.

An open-source MCP server that returns page-cited, verbatim evidence from embedded and firmware reference docs for coding agents.

Local-first code intelligence for Claude Code that adds structural graph search, semantic memory, cross-project links, MCP integration, and automated hooks for coding workflows.

A cognitive memory engine for AI agents with temporal decay, contradiction detection, autonomous consolidation, knowledge graph support, and ANN recall via HNSW. The repo shows Rust and Python usage, MCP client setup, and a quick-start path for agents and developers.

A Python/Flask code example that shows how to build a retrieval-augmented generation API with Telnyx embeddings and chat completions. The repo includes setup steps, environment variables, endpoint docs, and sample responses.

A GitHub example that audits LangChain’s RAG quickstart with retrieval-quality metrics, flags off-topic and out-of-distribution queries, and surfaces ranking and calibration issues with charts and results files.