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pilottai

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Basic Information

PilottAI is a Python framework designed to build, orchestrate, and run autonomous multi-agent systems for scalable AI applications. It provides a hierarchical agent model with manager and worker roles, intelligent job routing, context-aware processing, and specialized agent types for common tasks. The project targets production usage by offering asynchronous processing, dynamic scaling, load balancing, fault tolerance, logging, and advanced memory capabilities such as semantic storage and job history tracking. The README includes a quick start showing how to configure an LLM, create agents, start the system, add agents, and execute jobs. Example specialized agent templates cover document processing, customer service, email handling, marketing, research analysis, sales, social media, and web search. The repo includes a project structure for core components, agents, memory, orchestration, tools, and utilities and is installable via pip.

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App URL
https://github.com/pygig/pilottai
Github Repository
https://github.com/pygig/pilottai/blob/main/README.md

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App Details

Features
PilottAI highlights a hierarchical agent system with manager and worker hierarchies, intelligent job routing, context-aware processing, and provision for specialized agent implementations. It is production-oriented with asynchronous processing, dynamic scaling, load balancing, fault tolerance, and comprehensive logging. Memory features include semantic storage, job history tracking, context preservation, and knowledge retrieval. Integrations listed in the README include multiple LLM providers such as OpenAI, Anthropic, and Google, document processing, WebSocket support, and custom tool integration. The quick start demonstrates core APIs like Pilott.start, Pilott.stop, add_agent, and execute_job. Advanced features described include configurable load balancing and fault tolerance settings, and memory management APIs for storing and retrieving semantic contexts. The project structure separates core, agents, memory, orchestration, tools, and utils.
Use Cases
PilottAI helps developers and teams build resilient, scalable multi-agent AI systems by providing orchestration primitives, built-in production concerns, and ready-to-use agent templates. It simplifies job orchestration and workflow composition so complex tasks can be routed and executed across manager and worker agents. The framework"s memory and semantic storage enable context preservation and better knowledge retrieval for long-running or stateful workflows. Built-in load balancing and fault tolerance improve reliability in production deployments while asynchronous processing and dynamic scaling support variable workloads. Prebuilt specialized agents and example use cases, such as document processing, customer support, marketing, research analysis, sales workflows, social media management, and web search, reduce development time. Documentation, contributing guidance, and support channels are provided to help teams adopt and extend the framework.

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