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Flowise is an open source low-code tool for developers to build customized LLM orchestration flows & AI agents.
Flowise's Agentflows section provides a platform for building agent-based systems that can interact with external tools and data sources.
Currently, Flowise offers two approaches for designing these systems: Multi-Agents and Sequential Agents.
The Supervisor, as the agent governing the overall workflow and responsible for delegating tasks to the appropriate Worker,
The Worker, as a specialized agent instructed to handle a specific task within the system
It is designed for breaking down a complex task into a sequence of sub-tasks, completed one after another. Supervisor delegates to specialized Workers.
Each node in the graph represents a discrete processing unit, encapsulating its own functionality like language processing, tool execution, or conditional logic.
Edges in the graph represent the flow of data between nodes, where the output of one node becomes the input for the subsequent node, enabling a chain of processing steps.
It is Linear, cyclic and/or branching; nodes connect in a sequence, with conditional logic for branching
LiteLLM Proxy gives you a unified interface to access multiple LLMs
Track LLM Usage automatically
Load-balance across multiple deployments (e.g. Azure/OpenAI)
Prioritizing important requests to ensure they don't fail (i.e. Queueing)
Basic reliability logic - cooldowns, fallbacks, timeouts and retries (fixed + exponential backoff) across multiple deployments/providers.
Built on top of , Flowise's Sequential Agents architecture facilitates the development of conversational agentic systems by structuring the workflow as a directed cyclic graph (DCG), allowing controlled loops and iterative processes.
