examples

Agent Intelligence Toolkit Examples

Each NVIDIA Agent Intelligence (AIQ) toolkit example demonstrates a particular feature or use case of the NeMo Agent toolkit library. Most of these contain a custom workflow along with a set of custom tools (functions in NeMo Agent toolkit). These examples can be used as a starting off point for creating your own custom workflows and tools. Each example contains a README.md file that explains the use case along with instructions on how to run the example.

Installation and Setup

To run the examples, install the NeMo Agent toolkit from source, if you haven't already done so, by following the instructions in Install From Source.

Example Categories

Getting Started (getting_started)

• scaffolding: Workflow scaffolding and project generation using automated commands and intelligent code generation
• simple_web_query: Basic LangSmith documentation agent that searches the internet to answer questions about LangSmith.
• simple_calculator: Mathematical agent with tools for arithmetic operations, time comparison, and complex calculations
• simple_rag: Simple demonstration of using Retrieval Augmented Generation (RAG) with a vector database and document ingestion.

Custom Functions (custom_functions)

• automated_description_generation: Intelligent system that automatically generates descriptions for vector database collections by sampling and summarizing documents
• plot_charts: Multi-agent chart plotting system that routes requests to create different chart types (line, bar, etc.) from data
• simple_calculator: Mathematical agent with tools for arithmetic operations, time comparison, and complex calculations
• por_to_jiratickets: Project requirements to Jira ticket conversion with human oversight

Frameworks (frameworks)

• agno_personal_finance: Personal finance planning agent built with Agno framework that researches and creates tailored financial plans
• multi_frameworks: Supervisor agent coordinating LangChain, LlamaIndex, and Haystack agents for research, RAG, and chitchat tasks
• semantic_kernel_demo: Multi-agent travel planning system using Microsoft Semantic Kernel with specialized agents for itinerary creation, budget management, and report formatting, including long-term memory for user preferences

Agents (agents)

• react: ReAct (Reasoning and Acting) agent implementation for step-by-step problem-solving
• rewoo: ReWOO (Reasoning WithOut Observation) agent pattern for planning-based workflows
• tool_calling: Tool-calling agent with direct function invocation capabilities
• mixture_of_agents: Multi-agent system with ReAct agent coordinating multiple specialized Tool Calling agents

Front Ends (front_ends)

• simple_calculator_custom_routes: Simple calculator example with custom API routing and endpoint configuration
• simple_auth: Simple example demonstrating authentication and authorization using OAuth 2.0 Authorization Code Flow

Human In The Loop (HITL) (HITL)

• por_to_jiratickets: Project requirements to Jira ticket conversion with human oversight
• simple_calculator_hitl: Human-in-the-loop version of the basic simple calculator that requests approval from the user before allowing the agent to make additional tool calls.

MCP (MCP)

• simple_calculator_mcp: Demonstrates Model Context Protocol support using the basic simple calculator example

Observability (observability)

• redact_pii: Demonstrates how to use Weights & Biases (W&B) Weave with PII redaction
• simple_calculator_observability: Basic simple calculator with integrated monitoring, telemetry, and observability features
• alert_triage_agent: Production-ready intelligent alert triage system using LangGraph that automates system monitoring diagnostics with tools for hardware checks, network connectivity, performance analysis, and generates structured triage reports with root cause categorization
• profiler_agent: Performance profiling agent for analyzing NeMo Agent toolkit workflow performance and bottlenecks using Phoenix observability server with comprehensive metrics collection and analysis
• email_phishing_analyzer: Security-focused email analysis system that detects phishing attempts using multiple LLMs, including its evaluation and profiling configurations
• text_file_ingest: Text file processing and ingestion pipeline for document workflows

Memory (memory)

• redis: Basic long-term memory example using redis
• simple_rag: Complete RAG system with Milvus vector database, document ingestion, and long-term memory using Mem0 platform
• semantic_kernel_demo: Multi-agent travel planning system using Microsoft Semantic Kernel with specialized agents for itinerary creation, budget management, and report formatting, including long-term memory for user preferences

RAG (RAG)

• simple_rag: Complete RAG system with Milvus vector database, document ingestion, and long-term memory using Mem0 platform

Evaluation and Profiling (evaluation_and_profiling)

• swe_bench: Software engineering benchmark system for evaluating AI models on real-world coding tasks
• simple_calculator_eval: Evaluation and profiling configurations based on the basic simple calculator example
• simple_web_query_eval: Evaluation and profiling configurations based on the basic simple web query example
• alert_triage_agent: Evaluation and profiling configurations for the alert triage agent example
• email_phishing_analyzer: Evaluation and profiling configurations for the email phishing analyzer example
• text_file_ingest: Evaluation and profiling configurations for the text file ingestion example

Advanced Agents (advanced_agents)

• alert_triage_agent: Production-ready intelligent alert triage system using LangGraph that automates system monitoring diagnostics with tools for hardware checks, network connectivity, performance analysis, and generates structured triage reports with root cause categorization
• profiler_agent: Performance profiling agent for analyzing NeMo Agent toolkit workflow performance and bottlenecks using Phoenix observability server with comprehensive metrics collection and analysis
• AIQ Blueprint: Blueprint documentation for the official NVIDIA AIQ Blueprint for building an AI agent designed for enterprise research use cases.

Documentation Guides (documentation_guides)

• locally_hosted_llms: Configuration examples for the basic simple LangSmith agent using locally hosted LLM models (NIM and vLLM configurations)
• workflows: Workflow examples for documentation and tutorials:
  • custom_workflow: Extended version of the basic simple example with multiple documentation sources (LangSmith and LangGraph)
  • text_file_ingest: Text file processing and ingestion pipeline for document workflows