LangGraph Integration Overview

Noveum Trace provides powerful integration with LangGraph applications, enabling you to trace complex agent workflows, multi-step reasoning, and state management. This integration gives you complete visibility into your LangGraph applications' execution flow and performance.

What You Get

• Workflow Tracing: Complete visibility into LangGraph execution flows
• State Management: Track state changes and transitions
• Node-level Tracing: Monitor individual nodes and their performance
• Conditional Routing: Trace decision-making and routing logic
• Iterative Processes: Monitor self-loops and iterative refinement
• Performance Analytics: Detailed metrics on workflow execution

Installation

pip install noveum-trace

Note: There's no special noveum-trace[langgraph] package. The base noveum-trace package includes full LangGraph support.

Quick Start

The simplest way to integrate Noveum Trace with LangGraph is using the NoveumTraceCallbackHandler:

import os
import noveum_trace
from noveum_trace import NoveumTraceCallbackHandler
from langgraph.graph import StateGraph
from langchain_openai import ChatOpenAI
 
# Initialize Noveum Trace
noveum_trace.init(
    api_key=os.getenv("NOVEUM_API_KEY"),
    project="customer-support-bot",
    environment="development"
)
 
# Initialize the callback handler
callback_handler = NoveumTraceCallbackHandler()
 
# Add to your LangGraph components
llm = ChatOpenAI(callbacks=[callback_handler])
 
# Use in your graph
graph = StateGraph(YourStateType)
# ... add nodes and edges

Integration Patterns

1. Basic Agents

Trace simple agent workflows with single decision points.

2. Iterative Research

Monitor agents that loop back to refine their work.

3. Conditional Routing

Track complex routing decisions and state transitions.

4. Mixed Tracing

Combine automatic and manual tracing for maximum control.

5. State Management

Monitor state changes and data flow through your graph.

Key Features

• Automatic Node Tracing: Every node execution is automatically traced
• State Visibility: Track state changes and data flow
• Performance Metrics: Monitor execution time and resource usage
• Error Tracking: Comprehensive error handling and debugging
• Workflow Analytics: Understand execution patterns and bottlenecks

LangGraph-Specific Benefits

• Graph Structure: Visualize your entire workflow structure
• Node Dependencies: Understand how nodes connect and depend on each other
• State Transitions: Track how state evolves through your graph
• Loop Detection: Monitor iterative processes and self-loops
• Conditional Logic: Trace routing decisions and branching

Next Steps

• Basic Agent - Start with simple agent workflows
• Iterative Research - Monitor self-looping agents

Need Help?

• Documentation: Browse our comprehensive guides
• Examples: Check out the integration examples directory for real-world implementations
• Community: Join our Discord for support and discussions
• Support: Contact our team for enterprise support