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NeMo Agent Toolkit

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Basic Information

NVIDIA Agent Intelligence (AIQ) toolkit is a lightweight, framework-agnostic library for connecting, composing, and running agentic workflows across enterprise systems. It provides a unified way to wire existing agents, tools, and data sources together without forcing a replatforming to a single agent framework. The repository contains the core aiqtoolkit package, a command-line interface (aiq), example workflows, plugins under a packages directory, and documentation for installing from source. The toolkit supports integration with popular agent frameworks named in the README such as LangChain, LlamaIndex, CrewAI, and Microsoft Semantic Kernel. It also supports Model Context Protocol (MCP) roles as both client and server, a UI chat interface for interacting with agents, and example configurations for running LLM-backed workflows. The project emphasizes composability, reuse, rapid development, and observability for production and experimental agent deployments.

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App URL
https://github.com/NVIDIA/NeMo-Agent-Toolkit
Github Repository
https://github.com/NVIDIA/NeMo-Agent-Toolkit/blob/main/README.md

App Details

Features
The README highlights several concrete features: framework-agnostic integrations so AIQ toolkit can work alongside LangChain, LlamaIndex, CrewAI and Semantic Kernel; a composable API where agents, tools and workflows are callable and reusable; a plugin system with optional packages to add framework-specific adapters; a CLI (aiq) and example workflow files to run demos. Observability includes OpenTelemetry-compatible hooks and example integrations. Profiling tools measure inputs, outputs, token usage and timings. A built-in evaluation system validates agentic workflows. There is a UI chat interface for debugging and visualizing outputs. Full MCP support allows acting as MCP client or server. Installation and development workflows, prerequisites, and example configs are provided in the docs.
Use Cases
AIQ toolkit helps engineering and research teams integrate disparate agent components and third-party tools without rewriting existing stacks. It reduces development overhead by offering reusable agents, tools and workflow templates and by making it easy to install only required plugins. Teams can iterate faster using the example workflows, the aiq CLI, and a UI to inspect and debug agent runs. Profiling and observability features help identify bottlenecks and monitor production workflows. The evaluation subsystem supports validating behavior and maintaining accuracy. MCP support enables publishing or consuming remote tools. The framework-agnostic approach lets organizations adopt the toolkit incrementally alongside LangChain, LlamaIndex, CrewAI or internal frameworks, and the README documents installation, environment prerequisites, and a Hello World example using an LLM configuration.

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