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Open-source AI agent builder pairing a visual workflow canvas with an Agentic RAG knowledge base, self-hosted or cloud.

Task: Automating WorkflowsUse case: Build and deploy enterprise grade ai agents with visual workflows and rag knowle

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Summarized from 1 community tutorial · July 2026

Access: Free tier
API key: Bring your own
Runs on: Web app · Self-hosted · API
You’ll need: Docker installed (for self-hosting)
API key from a model provider e.g. SiliconFlow
PDF/Word/Markdown docs for the knowledge base
Feishu or DingTalk dev account (optional, for bots)
Skill level: Some setup — keys, settings, or a connected account

Summarized from 1 community tutorial · July 2026

Builds a knowledge-base Q&A appUploads PDF/Word docs, auto-splits into QA pairs or chunks, and answers employee questions with cited source snippets.
Visual workflow builder with branchingDrag-and-drop nodes classify the user's question and route it to different knowledge bases before an AI response node.
Tool-calling / agent-style nodesWorkflow nodes call built-in tools or custom plugins; the LLM decides which tool to invoke and fills required parameters.
Metadata tag filtering on knowledge baseTags documents/collections and filters retrieval by tag for more precise search results.
Self-hosts via Docker with any model providerDeploys locally with Docker and plugs in a third-party model API key (e.g. SiliconFlow) for chat + embedding models.

Summarized from 1 community tutorial · July 2026