Haohao-end/openagent

What if OpenAI Deep Research and Dify were one platform? OpenAgent — harness architecture for rapidly building vertical AI agents, with deep reasoning loops, visual workflows, RAG, and A2A delegation.

What it solves

OpenAgent provides a comprehensive, full-stack platform for teams to build, orchestrate, and operate AI applications. It moves beyond simple chat demos by offering a professional workspace for managing the entire lifecycle of an AI app, from visual workflow design and dataset integration to publishing and API delivery.

How it works

The platform uses a Flask backend with Celery workers and a Vue 3 frontend. It leverages LangChain and LangGraph for AI orchestration, allowing users to create complex agents that can decompose tasks and coordinate multiple capabilities. The system includes a visual workflow editor where users can drag-and-drop nodes (such as LLMs, tool calls, and HTTP requests) to define logic. For knowledge-enabled behavior, it integrates Weaviate and FAISS for RAG (Retrieval-Augmented Generation) and semantic retrieval.

Who it’s for

It is designed for teams and developers who need to build production-ready AI applications with complex reasoning capabilities, visual orchestration, and the ability to expose their agents as APIs via OpenAPI.

Highlights

  • Visual Workflow Editor: Design complex AI logic using a node-based editor with support for branching, code execution, and parameter extraction.
  • App Workspace: A dedicated area for model and prompt management, version comparison, and live debugging with execution traces.
  • Deep Research Mode: Enables agents to break down complex tasks into multi-step execution chains for deeper reasoning.
  • Deep Knowledge Integration: Full dataset management tools for uploading documents and connecting retrieval nodes to agents.
  • OpenAPI Delivery: Ability to publish apps and expose them via REST and SSE for integration into other services.

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