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Welcome to Kibo AI

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The Universal Distributed Agent Framework

Kibo is a powerful and flexible abstraction framework designed to unify the orchestration of AI Agents. It provides a standardized interface to define, execute, and combine agents from various underlying libraries (like Agno, LangChain, CrewAI, and PydanticAI).

Kibo is not just a wrapper; it transforms standalone agents into distributed, observable, and interconnected components of a larger system.

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🏗️ The Kibo Stack

Kibo covers the entire lifecycle of agentic applications, providing a layered architecture that handles everything from definition to distributed execution.

1. Orchestration Layer (The Core)

At the heart of Kibo is the Unified Agent Blueprint. * AgentConfig: Define your agents using pure Python data structures. No framework-specific boilerplate is locked into your business logic. * Framework Agnostic: Switch the underlying engine (e.g., from agno to langchain) by changing a single string in the config.

2. Execution Layer (The Engine)

Kibo provides a dual-runtime environment to suit your scaling needs: * Local Runtime: Optimized for low-overhead, single-machine execution using thread pools. Perfect for development and simple workflows. * Distributed Runtime (Ray): Built on top of Ray, enabling massive horizontal scaling. Run agents across a cluster of machines with fault tolerance and parallel processing.

3. Integration Layer (The Ecosystem)

Kibo seamlessly integrates with the best-in-class agent frameworks: * Agno (formerly PhiData): For lightweight, specialized agents. * LangChain: For extensive tool support and complex chain logic. * CrewAI: For role-based multi-agent teams. * PydanticAI: For strictly typed, data-driven agents. * LangGraph: For stateful, graph-based workflows.

4. Observability Layer (The Eyes)

Built-in support for Langfuse gives you full visibility into your agentic systems: * Tracing: Track every step of your agent's execution, across frameworks and distributed nodes. * Monitoring: Keep an eye on latency, costs, and error rates. * Prompt Management: Version and manage your prompts centrally.

5. Networking Layer (The Connective Tissue)

Kibo introduces the Agent-to-Agent (A2A) Protocol: * Direct Communication: Agents can discover and message each other directly, enabling complex, emergent behaviors. * Standardized Interface: Common protocol for requests and responses, regardless of the underlying framework.


🚀 Key Features

  • Unified Abstraction: One interface to rule them all.
  • Multi-Framework Interop: Mix LangChain agents with CrewAI teams in the same workflow.
  • Native Tool Integration: Pass standard Python functions or library-specific tools directly.
  • Zero-Dependency Definitions: Your agent definitions remain clean and portable.
  • AI Gateway: Unified access to LLMs via LiteLLM integration.

📦 Quick Install

git clone https://github.com/D10S0VSkY-OSS/kiboai.git
cd kiboai
uv sync

Read the Documentation to start building distributed agents today.