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flows-ai

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Multi-Agent Platforms & Frameworks
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Basic Information

Flows AI is a lightweight, type-safe orchestrator library for building and running AI workflows and agent patterns. It is designed for developers using TypeScript and the Vercel AI SDK who want to compose multiple LLM calls into deterministic workflows. The project is inspired by Anthropic's agent patterns and was motivated by the authors' prior work on an agent framework called Fabrice. The library focuses on orchestration of nodes that have flexible input/output contracts, letting users connect often-incompatible components. It provides a simple functional API without classes or mutable state, and supports both explicitly defined workflows and an orchestrator agent that can dynamically decompose complex tasks. The package is published to npm and distributed under the MIT license. Documentation and examples are provided to help developers get started.

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App URL
https://github.com/callstackincubator/flows-ai
Github Repository
https://github.com/callstackincubator/flows-ai/blob/main/README.md

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App Details

Features
The README highlights several practical features: a type-safe agent factory for declaring agents with model and system prompt settings, integration examples using OpenAI models via the Vercel AI SDK, and composable flow primitives such as sequences. It supports explicit control flow including loops and conditionals as well as an orchestrator agent mode for dynamic task decomposition. The API is functional and stateless, avoiding classes, and aims for deterministic orchestration of LLM calls. The package is available on npm and accompanied by documentation and example projects to illustrate agent definitions and execution. The library emphasizes simplicity, reusability of agents, and compatibility with common LLM providers shown in examples.
Use Cases
Flows AI helps developers organize and manage multi-step AI processes by turning individual LLM calls into composable workflow nodes. It reduces integration friction when connecting components with different input/output shapes and enables predictable, deterministic orchestration for tasks like translation then summarization. The library offers both explicit workflow construction and an orchestrator-driven approach to break down complex tasks, making it useful for prototyping and building production pipelines. Its type-safe TypeScript design improves developer confidence and maintainability. Provided docs and examples accelerate onboarding, and the lightweight, stateless API keeps runtime behavior simple. Overall, it streamlines building agent-based applications on top of Vercel AI SDK and common LLM models.

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