Built for developers and builders wanting to explore scalable Agentic AI systems. Provides a modular foundation for building coordinated, human-supervised AI workflows that align with emerging best practices in agentic automation and LLM orchestration. AgentFlow is a production-ready visual orchestration interface for designing, customizing, and executing multi-agent AI workflows. It enables developers and teams to move beyond isolated single-agent prompts and build coordinated, structured AI systems with optional human oversight checkpoints. ⸻ Core Capabilities: ⸻ Visual Workflow Builder: ⸻ • Drag-and-drop canvas for constructing agent flow graphs • Connect agents using structured control logic • Clear execution path visualization ⸻ Specialized Agent Roles: ⸻ Pre-configured agent types for modular orchestration: ⸻ • Researcher – Context gathering and structured analysis • Writer – Structured and engaging content generation • Analyst – Data interpretation and insight extraction • Reviewer – Quality control and validation • Summarizer – Context compression and output refinement • Coder – Code generation, refactoring, and debugging ⸻ Designed for scalable automation, AgentFlow supports research pipelines, content generation systems, data analysis workflows, and code automation sequences, all within a visual, low-friction interface. ⸻ Control Flow Elements: • Start Node • End Node • Human Approval Gate for supervised AI execution Execution Layer: • Workflow execution engine • Real-time logs and output inspection • Structured task sequencing ⸻ Use Cases: • Multi-step AI research pipelines • Automated report generation • AI content production workflows • Code generation and review pipelines • Human-in-the-loop compliance systems • Cross-agent task automation ⸻ This template bridges the latest agentic architecture patterns, allowing multiple specialized AI agents to collaborate within a controlled visual workflow interface. Users drag and drop agents onto the canvas, connect control nodes, and execute end-to-end tasks with visibility into runtime logs and execution flow.
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