Search Results for "multi agent"

...The system likely integrates with broader agent frameworks, enabling seamless inclusion in multi-agent environments. It emphasizes communication and coordination, ensuring that agents can contribute meaningfully to shared objectives. This makes it particularly useful for complex projects where multiple perspectives or iterative refinement are needed.

Antigravity Awesome Skills is a playful yet practical repository that curates a set of clever, expressive, and sometimes whimsical AI agent skill templates designed to help users bootstrap agent behavior quickly. Rather than focusing on production-grade systems, it provides creative and high-impact skills that demonstrate how agents can be used to automate tasks, generate content, assist with daily operations, or integrate into larger workflows with minimal configuration. ...

...The repository curates reproducible templates that demonstrate how Claude Code agents can participate in end-to-end developer journeys such as building new features, adhering to coding standards, generating documentation, and automating refactor patterns. It also includes example orchestrations that showcase multi-step agent workflows, letting developers see how to compose small, discrete agent capabilities into productive, cohesive sequences. Because it is designed to be modular, individuals and teams can pull in only the skills they need, combine them with custom logic, or share their own extensions with the community.

...DeepPavlov is an open-source framework for chatbots and virtual assistants development. It has comprehensive and flexible tools that let developers and NLP researchers create production-ready conversational skills and complex multi-skill conversational assistants. Use BERT and other state-of-the-art deep learning models to solve classification, NER, Q&A and other NLP tasks. DeepPavlov Agent allows building industrial solutions with multi-skill integration via API services.

...Because it is pattern-driven and optimized for fast matching, it adds minimal runtime overhead to request handling. By abstracting away the complexity of UA sniffing, Mobile-Detect helps teams gracefully support multi-device clients without duplicating detection logic.

...Its central abstraction is the Processor, a unit of work that consumes an asynchronous stream of parts (text, images, audio, JSON) and produces another stream, making it natural to chain operations and keep everything streaming end-to-end. Processors can be composed sequentially (to build multi-step flows) or in parallel (to fan-out work and merge results), which makes sophisticated agent behaviors easy to express with simple operators. The library offers built-in processors for classic turn-based Gemini calls as well as Live API streaming, so you can mix “batch” and real-time interactions in the same graph. It leans on Python’s asyncio to coordinate concurrency, handle network I/O, and juggle background compute threads without blocking.

This is a multi-agent platform utilizing blackboard architecture as the core communication and organization means.