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Yet Another Agentic Framework. A Simple implementation of various LLM Agents.

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YAAF - Yet Another Agentic Framework, is an in-house framework designed to create custom AI Agents with ease and zero coupling. YAAF aims to provide a simplified, less bloated alternative to existing AI agent frameworks.

Overview

YAAF was born out of the need for a more reliable and efficient AI agent framework. After experiencing underwhelming results with existing solutions like Crewai in production environments, we decided to create our own low-coupling abstraction on top of OpenAI's assistants and function calling capabilities.

The primary goal of Atlas is to maintain a sequential flow of multiple agents in a pipeline, providing a streamlined approach to AI agent development and deployment.

Features

  • Zero coupling design for flexibility and ease of use
  • Built on top of OpenAI's assistants and function calling
  • Simplified, less bloated framework
  • Sequential flow of multiple agents in a pipeline
  • Four different types of AI Agents to suit various use cases
  • Customizable prompting system

Installation

Coming soon

Agent Types

YAAF supports four different types of AI Agents:

  1. Assistants: Utilizes OpenAI assistants under the hood, combining function calling for fast and efficient operations.

    Assistants Demo

  2. Conversational Persona Bots: Assistants in a loop with the user, designed for interactive conversations.

    Persona Bots Demo

  3. ReAct-based Agents: Implements a Reasoning and Action loop to accomplish tasks effectively.

  4. PAL Agents: Program-Aided Language models built for complex problem-solving scenarios.

Quick Start

Build an agent in just 4 lines of code

from turi_yaaf.assistants.assistants import create_agent, create_task

api_key = "OPENAIAPIKEY"

agent = create_agent(api_key, name, instructions, tools)
create_task(agent, input, prompt)

Roadmap

  • Implement ReAct based agents

  • Implement PAL based agents

  • Implement a new prompting system:

    • Objective
    • Context
    • Instruction
    • Output
    • Examples
  • Develop collaboration workflow:

    • Current focus is on sequential workflows
    • Future plans to implement collaborative agent interactions
  • Integrate feedback mechanism:

    • Initial implementation of a naive feedback system

Why YAAF?

YAAF addresses the reliability issues faced with other frameworks when deploying AI crews to production environments. By creating a custom, low-coupling abstraction, we aim to provide a more dependable and efficient solution for AI agent development and deployment.


Built with ❤️ by Turi Labs

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Yet Another Agentic Framework. A Simple implementation of various LLM Agents.

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