You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Describe how the Dapr community will benefit from this project? Please, describe one or more scenarios.
Floki strengthens Dapr’s position as a leading framework for AI-driven and event-driven systems by introducing a novel use case: Agentic frameworks for orchestrating LLM-based autonomous agents. This benefits the Dapr community in several ways:
Broadens the Use Cases for Dapr: By integrating seamlessly with Dapr's building blocks (e.g., Pub/Sub, State Management, Service Invocation, and Workflows), Floki highlights how Dapr can serve as a robust foundation for developing scalable and collaborative AI systems.
Solidifies Dapr’s Relevance in AI Development: Floki positions Dapr as a go-to solution for researchers and developers exploring autonomous agents, a rapidly growing field within AI. This expands Dapr’s adoption in cutting-edge AI projects.
Enables Experimentation and Innovation: Floki provides a framework for developers to experiment with multi-agent systems, orchestrated workflows, and distributed microservices. For example:
Researchers can design agents that autonomously reason, communicate, and collaborate on tasks such as customer service automation or supply chain optimization.
Developers can use Floki to implement agent-based systems for decentralized problem-solving, such as collaborative robotics or intelligent IoT systems.
Extends the Community’s Reach: By integrating AI-powered workflows with Dapr, Floki brings in AI and ML researchers who may not otherwise have explored Dapr, further enriching the community.
Which programming languages will be used?
Floki will primarily use Python for defining agents, building workflows, and interacting with LLM APIs.
Other languages may be used for future integrations or enhancements based on community needs.
Does the project have any hard dependency on other technologies or cloud vendors? Example: Kubernetes, Azure, AWS, Terraform
Not, it does not.
Enumerate the repositories this project will need to be created.
floki
What is the ETA to have this project reach a stable version and graduate to the main Dapr organization?
6 months
Who are the maintainers of this project and corresponding employers?
Comment period has ended, Floki is approved for Dapr Sandbox! @Cyb3rWard0g I will be creating a repository for this. Be on the lookout for an invitation into the dapr-sandbox org.
Floki strengthens Dapr’s position as a leading framework for AI-driven and event-driven systems by introducing a novel use case: Agentic frameworks for orchestrating LLM-based autonomous agents. This benefits the Dapr community in several ways:
Floki will primarily use Python for defining agents, building workflows, and interacting with LLM APIs.
Other languages may be used for future integrations or enhancements based on community needs.
Not, it does not.
floki
6 months
Roberto Rodriguez @Cyb3rWard0g. This is a personal project that I started here: https://github.com/Cyb3rWard0g/floki. Looking forward to collaborating with others in the Dapr community.
The text was updated successfully, but these errors were encountered: