Search results for "parsing"
Agentic framework | Self-improving memory | Pluggable tool extensions | Sandbox execution
LLM-powered framework for deep document understanding, semantic retrieval, and context-aware answers using RAG paradigm.
The cognitive database. A new class of data storage. Not a vector store, not a graph DB, not a RAG wrapper. Ebbinghaus decay, Hebbian learning, and Bayesian confidence are engine-native primitives.
The open agent control plane. Govern autonomous AI agents with pre-execution policy enforcement, approval gates, and audit trails. Works with LangChain, CrewAI, MCP, and any framework.
A Slack bot and MCP client acts as a bridge between Slack and Model Context Protocol (MCP) servers. Using Slack as the interface, it enables large language models (LLMs) to connect and interact with v
A universal CLI for Weaviate, Milvus, Chroma, Qdrant, and other vector DBs to help view, list, create, delete, and search collections and documents in collections for development, test, and debugging
Type-safe AI agents for Go. Suricata combines LLM intelligence with Go’s strong typing, declarative YAML specs, and code generation to build safe, maintainable, and production-ready AI agents.
A self-evolving coding agent written in Go. Reads its own source, decides what to improve, writes code, runs tests, and commits — autonomously.
Convert any URL into LLM-friendly formats using a lightweight CLI tool for reading and searching web content efficiently.