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FastAgency

Free plan available

The fastest way to bring multi-agent workflows to production.

Api integration
Open-source framework
Multi-agent workflows
Seamless scaling
Multi-framework support
Unified programming interface
Streamlined deployment

About FastAgency

Launched Sep 18, 2024

Categories

Description

The fastest way to bring multi-agent workflows to production.

FastAgency is an open-source framework designed to accelerate the transition from prototype to production for multi-agent AI workflows. For developers who use the AutoGen framework, FastAgency enables you to seamlessly scale Jupyter notebook prototypes into fully functional, production-ready applications. With multi-framework support, a unified programming interface, and powerful API integration capabilities, FastAgency streamlines the deployment process, saving time and effort while maintaining flexibility and performance.
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FastAgency Key Features

  • Multi-Runtime Support: FastAgency supports AutoGen and plans to add CrewAI giving developers the flexibility to switch between frameworks as needed,
  • Unified Programming Interface: Develop workflows once and reuse them across console (ConsoleUI) and web (MesopUI) interfaces without rewriting code,
  • Seamless API Integration: Import and connect external APIs like OpenAPI with just a couple of lines of code to enhance agent workflows,
  • Command-Line Interface (CLI): Quickly run manage and automate workflows through the CLI supporting DevOps and deployment tasks

FastAgency Use Cases

  • AI Chatbots: Deploy multi-agent conversational AI for customer support or tutoring applications,
  • Data-Driven Decision Making: Build agents that gather real-time data from APIs (e.g. weather finance) to support business decisions,
  • Automated Testing: Use FastAgency's Tester Class to automate testing workflows in CI environments,
  • DevOps Orchestration: Automate complex workflows and integrate AI-driven operations using FastAgency's CLI for efficient DevOps management.

Pros

  • Enables rapid transition from prototype to production, saving time.
  • Supports seamless scaling of Jupyter notebook prototypes into production applications.
  • Offers multi-framework support and a unified programming interface, increasing flexibility.
  • Powerful API integration capabilities streamline the deployment process.
  • Open-source nature allows for community contributions and transparency.

Cons

  • May have a learning curve for developers unfamiliar with AutoGen framework.
  • Being open-source, it might require more self-support and troubleshooting.
  • Possibility of encountering integration issues with certain APIs.

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