RAPTOR: Open-Source Multimodal AI Framework & Agent Harness
What it is
RAPTOR is an enterprise AI runtime and framework for building agentic applications over multimodal data (video, audio, images, documents). It provides a suite of composable services including MCP tools, A2A orchestration, persistent memory, hybrid RAG, and GraphRAG, deployed via 27 independent Docker Compose modules.
The problem it solves
The fragmentation of AI infrastructure, where developers must manually integrate separate tools for search, memory, orchestration, and multimodal processing to build a single agentic application.
What you could use it for
- Building enterprise search engines over mixed media types (video, audio, text)
- Creating autonomous agents with persistent memory and tool access via MCP
- Implementing hybrid retrieval (BM25, vector, graph) for complex knowledge bases
- Deploying isolated multi-model databases for per-user data privacy
Read the source ↗Back to the library →
Summary written by an AI model from the source; check the source before you rely on it.