{"repo":"redhat-community-ai-tools/UnifAI","free":true,"listed":false,"github":"https://github.com/redhat-community-ai-tools/UnifAI","clone":"git clone https://github.com/redhat-community-ai-tools/UnifAI.git","description":"Production-grade multi-agent orchestration engine. Compose agentic workflows from a pluggable catalog of Agents, LLMs, tools, and retrievers. Execute locally with LangGraph or distributed with Temporal. Built-in RAG pipeline for enterprise knowledge retrieval. A2A and MCP protocol support. Visual drag-and-drop blueprint builder.","language":"Python","stars":44,"topics":["ai-agents","langgraph","qdrant","rag","a2a-protocol","agent-orchestration","flask","kubernetes","llm","mcp"],"license":"Apache-2.0","category":"ai-agents","readme_excerpt":"UnifAI A platform for building and running multi-agent AI workflows over your enterprise knowledge. UnifAI lets you connect internal data sources — Slack, Jira, documents — into a unified vector store, then query them through composable, visual multi-agent pipelines. Define agent graphs as YAML blueprints or build them with a drag-and-drop UI, execute locally or at scale, and stream results in real time. --- What It Does Most teams have knowledge scattered across Slack threads, Jira tickets, PDFs, and internal wikis. Finding answers means manually digging through multiple systems. UnifAI fixes this: 1. Compose — Build multi-agent workflows that reason across sources, route conditionally, and combine results 2. Execute — Run workflows locally or distributed, with real-time streaming 3. Interact — Use the web UI to build blueprints visually, trigger executions, and inspect every node's input/output 4. Ingest — Pull content from Slack, documents (PDF, Markdown), and more into a vector database for agents to search --- Architecture --- Multi-Agent System — The Core The heart of UnifAI is its Multi-Agent System (MAS) : a production-grade orchestration engine for defining, executing, and streaming multi-agent workflows. Blueprint-Driven Workflows Agents are composed into directed graphs called blueprints . Each blueprint declares nodes, edges, conditions, and the tools/LLMs each agent can use — all in a single YAML file: Blueprints can be pre-defined in YAML or built visually throu","default_branch":null,"files":null,"tree":[],"storefront":"/r/redhat-community-ai-tools","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/redhat-community-ai-tools/UnifAI/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}