| layout | default |
|---|---|
| title | CopilotKit Tutorial - Chapter 6: CoAgents & LangGraph |
| nav_order | 6 |
| has_children | false |
| parent | CopilotKit Tutorial |
Welcome to Chapter 6: CoAgents & LangGraph - Building Agentic Workflows. In this part of CopilotKit Tutorial: Building AI Copilots for React Applications, you will build an intuitive mental model first, then move into concrete implementation details and practical production tradeoffs.
Create sophisticated agentic workflows using CoAgents and LangGraph integration for complex, multi-step processes.
CoAgents brings the power of LangGraph to CopilotKit, enabling complex agentic workflows with human-in-the-loop interactions. This chapter covers building sophisticated multi-agent systems and workflow automation.
// app/components/BasicCoAgent.tsx
"use client";
import { useCoAgent } from "@copilotkit/react-core";
import { useState } from "react";
export function BasicCoAgent() {
const [workflowState, setWorkflowState] = useState<any>({});
const [isRunning, setIsRunning] = useState(false);
// Define a simple workflow agent
const { runWorkflow, state } = useCoAgent({
name: "task_planner",
description: "A simple task planning and execution agent",
workflow: {
nodes: {
analyze: {
type: "action",
action: async (input: any) => {
// Analyze the input and break it down
const tasks = input.description.split(/[,.]/)
.map((task: string) => task.trim())
.filter((task: string) => task.length > 0);
return {
analysis: `Found ${tasks.length} tasks to complete`,
tasks: tasks,
priority: input.priority || "medium"
};
}
},
execute: {
type: "action",
action: async (input: any) => {
// Simulate task execution
const results = [];
for (const task of input.tasks) {
results.push({
task,
status: "completed",
duration: Math.floor(Math.random() * 10) + 1
});
}
return {
execution_results: results,
total_duration: results.reduce((sum, r) => sum + r.duration, 0)
};
}
},
report: {
type: "action",
action: async (input: any) => {
// Generate execution report
return {
summary: `Completed ${input.execution_results.length} tasks in ${input.total_duration} minutes`,
details: input.execution_results,
efficiency: input.execution_results.length / input.total_duration
};
}
}
},
edges: [
{ from: "analyze", to: "execute" },
{ from: "execute", to: "report" }
]
}
});
const handleStartWorkflow = async () => {
setIsRunning(true);
try {
const result = await runWorkflow({
description: "Buy groceries, finish report, call dentist, schedule meeting",
priority: "high"
});
setWorkflowState(result);
} finally {
setIsRunning(false);
}
};
return (
<div className="p-6 max-w-2xl mx-auto">
<h1 className="text-3xl font-bold mb-6">Basic CoAgent Workflow</h1>
<div className="space-y-6">
{/* Workflow Trigger */}
<div className="bg-white p-6 rounded-lg shadow">
<h2 className="text-xl font-semibold mb-4">Task Planning Agent</h2>
<p className="text-gray-600 mb-4">
This CoAgent will analyze tasks, execute them, and generate a report.
</p>
<button
onClick={handleStartWorkflow}
disabled={isRunning}
className="px-6 py-3 bg-blue-500 text-white rounded-lg hover:bg-blue-600 disabled:bg-gray-300 disabled:cursor-not-allowed"
>
{isRunning ? "Running Workflow..." : "Start Task Planning Workflow"}
</button>
</div>
{/* Workflow State */}
{Object.keys(workflowState).length > 0 && (
<div className="bg-white p-6 rounded-lg shadow">
<h2 className="text-xl font-semibold mb-4">Workflow Results</h2>
<div className="space-y-4">
{workflowState.analysis && (
<div className="p-3 bg-blue-50 rounded">
<h3 className="font-medium text-blue-900">Analysis</h3>
<p className="text-blue-800">{workflowState.analysis}</p>
</div>
)}
{workflowState.execution_results && (
<div className="p-3 bg-green-50 rounded">
<h3 className="font-medium text-green-900">Execution Results</h3>
<ul className="text-green-800 space-y-1">
{workflowState.execution_results.map((result: any, index: number) => (
<li key={index}>
✓ {result.task} ({result.duration} min)
</li>
))}
</ul>
</div>
)}
{workflowState.summary && (
<div className="p-3 bg-purple-50 rounded">
<h3 className="font-medium text-purple-900">Summary</h3>
<p className="text-purple-800">{workflowState.summary}</p>
<p className="text-sm text-purple-700 mt-1">
Efficiency: {workflowState.efficiency?.toFixed(2)} tasks/minute
</p>
</div>
)}
</div>
</div>
)}
{/* Current State */}
{state && (
<div className="bg-gray-50 p-4 rounded-lg">
<h3 className="font-medium mb-2">Current State</h3>
<pre className="text-sm text-gray-600 overflow-x-auto">
{JSON.stringify(state, null, 2)}
</pre>
</div>
)}
</div>
</div>
);
}// app/components/LangGraphAgent.tsx
"use client";
import { useCoAgent } from "@copilotkit/react-core";
import { useState } from "react";
export function LangGraphAgent() {
const [researchTopic, setResearchTopic] = useState("");
const [isResearching, setIsResearching] = useState(false);
const [researchResults, setResearchResults] = useState<any>({});
// Advanced research agent using LangGraph
const { runWorkflow, state } = useCoAgent({
name: "research_agent",
description: "Comprehensive research agent using LangGraph workflows",
workflow: {
// LangGraph-style workflow definition
graph: {
nodes: {
plan_research: {
type: "agent",
agent: "planning_agent",
prompt: "Create a research plan for the given topic. Break it down into specific research questions and data sources to investigate."
},
gather_data: {
type: "action",
action: async (input: any) => {
// Simulate data gathering from multiple sources
const sources = ["academic_papers", "news_articles", "social_media", "official_reports"];
const results = {};
for (const source of sources) {
results[source] = {
count: Math.floor(Math.random() * 10) + 1,
quality: ["low", "medium", "high"][Math.floor(Math.random() * 3)],
relevance: Math.floor(Math.random() * 100) + 1
};
}
return {
data_sources: results,
total_sources: sources.length,
avg_relevance: Object.values(results).reduce((sum: any, r: any) => sum + r.relevance, 0) / sources.length
};
}
},
analyze_findings: {
type: "agent",
agent: "analysis_agent",
prompt: "Analyze the gathered data and identify key insights, trends, and conclusions. Provide evidence-based reasoning."
},
generate_report: {
type: "action",
action: async (input: any) => {
// Generate comprehensive research report
return {
title: `Research Report: ${input.topic}`,
executive_summary: `Comprehensive analysis of ${input.topic} based on ${input.total_sources} data sources.`,
key_findings: [
"Primary trend identified with supporting evidence",
"Secondary insights with data correlations",
"Future implications and recommendations"
],
methodology: "Multi-source data collection and analysis",
confidence_level: "High (85%+ data coverage)",
recommendations: [
"Implement findings in strategic planning",
"Further research in identified gaps",
"Monitor trends for future developments"
]
};
}
},
peer_review: {
type: "agent",
agent: "review_agent",
prompt: "Review the research report for accuracy, completeness, and soundness of conclusions. Provide constructive feedback."
}
},
edges: [
{ from: "plan_research", to: "gather_data" },
{ from: "gather_data", to: "analyze_findings" },
{ from: "analyze_findings", to: "generate_report" },
{ from: "generate_report", to: "peer_review" }
],
// Conditional routing based on results
conditional_edges: [
{
from: "peer_review",
condition: (state: any) => state.review_score > 80,
to: "finalize_report"
},
{
from: "peer_review",
condition: (state: any) => state.review_score <= 80,
to: "revise_report"
}
]
}
}
});
const handleStartResearch = async () => {
if (!researchTopic.trim()) return;
setIsResearching(true);
try {
const results = await runWorkflow({
topic: researchTopic,
depth: "comprehensive",
sources: ["academic", "news", "social", "official"]
});
setResearchResults(results);
} finally {
setIsResearching(false);
}
};
return (
<div className="p-6 max-w-4xl mx-auto">
<h1 className="text-3xl font-bold mb-6">LangGraph Research Agent</h1>
<div className="space-y-6">
{/* Research Input */}
<div className="bg-white p-6 rounded-lg shadow">
<h2 className="text-xl font-semibold mb-4">Research Topic</h2>
<div className="space-y-4">
<input
type="text"
value={researchTopic}
onChange={(e) => setResearchTopic(e.target.value)}
placeholder="Enter research topic (e.g., 'impact of AI on healthcare')"
className="w-full px-4 py-2 border border-gray-300 rounded-lg focus:outline-none focus:ring-2 focus:ring-blue-500"
/>
<button
onClick={handleStartResearch}
disabled={!researchTopic.trim() || isResearching}
className="px-6 py-3 bg-blue-500 text-white rounded-lg hover:bg-blue-600 disabled:bg-gray-300 disabled:cursor-not-allowed"
>
{isResearching ? "Researching..." : "Start Comprehensive Research"}
</button>
</div>
<div className="mt-4 text-sm text-gray-600">
This will execute a multi-step research workflow using LangGraph agents for planning, data gathering, analysis, and reporting.
</div>
</div>
{/* Workflow Progress */}
{isResearching && (
<div className="bg-blue-50 p-6 rounded-lg">
<h3 className="font-semibold text-blue-900 mb-3">Research Workflow Progress</h3>
<div className="space-y-2">
<div className="flex items-center space-x-3">
<div className="w-4 h-4 bg-blue-500 rounded-full animate-pulse"></div>
<span className="text-blue-800">Planning research approach...</span>
</div>
<div className="flex items-center space-x-3">
<div className="w-4 h-4 bg-gray-300 rounded-full"></div>
<span className="text-gray-600">Gathering data from sources...</span>
</div>
<div className="flex items-center space-x-3">
<div className="w-4 h-4 bg-gray-300 rounded-full"></div>
<span className="text-gray-600">Analyzing findings...</span>
</div>
<div className="flex items-center space-x-3">
<div className="w-4 h-4 bg-gray-300 rounded-full"></div>
<span className="text-gray-600">Generating report...</span>
</div>
</div>
</div>
)}
{/* Research Results */}
{Object.keys(researchResults).length > 0 && (
<div className="space-y-6">
{/* Executive Summary */}
{researchResults.title && (
<div className="bg-white p-6 rounded-lg shadow">
<h2 className="text-2xl font-semibold mb-4">{researchResults.title}</h2>
{researchResults.executive_summary && (
<p className="text-gray-700 mb-4">{researchResults.executive_summary}</p>
)}
</div>
)}
{/* Key Findings */}
{researchResults.key_findings && (
<div className="bg-white p-6 rounded-lg shadow">
<h3 className="text-xl font-semibold mb-4">Key Findings</h3>
<ul className="space-y-3">
{researchResults.key_findings.map((finding: string, index: number) => (
<li key={index} className="flex items-start space-x-3">
<span className="w-6 h-6 bg-blue-500 text-white rounded-full flex items-center justify-center text-sm font-medium flex-shrink-0 mt-0.5">
{index + 1}
</span>
<span className="text-gray-700">{finding}</span>
</li>
))}
</ul>
</div>
)}
{/* Methodology */}
{researchResults.methodology && (
<div className="bg-green-50 p-6 rounded-lg">
<h3 className="font-semibold text-green-900 mb-2">Methodology</h3>
<p className="text-green-800">{researchResults.methodology}</p>
{researchResults.confidence_level && (
<p className="text-sm text-green-700 mt-1">
Confidence Level: {researchResults.confidence_level}
</p>
)}
</div>
)}
{/* Recommendations */}
{researchResults.recommendations && (
<div className="bg-purple-50 p-6 rounded-lg">
<h3 className="font-semibold text-purple-900 mb-3">Recommendations</h3>
<ul className="space-y-2">
{researchResults.recommendations.map((rec: string, index: number) => (
<li key={index} className="flex items-start space-x-3">
<span className="text-purple-800">•</span>
<span className="text-purple-800">{rec}</span>
</li>
))}
</ul>
</div>
)}
{/* Data Sources Summary */}
{researchResults.data_sources && (
<div className="bg-gray-50 p-6 rounded-lg">
<h3 className="font-semibold text-gray-900 mb-3">Data Sources Analyzed</h3>
<div className="grid grid-cols-2 md:grid-cols-4 gap-4">
{Object.entries(researchResults.data_sources).map(([source, data]: [string, any]) => (
<div key={source} className="bg-white p-3 rounded border">
<div className="font-medium text-gray-900 capitalize">{source.replace('_', ' ')}</div>
<div className="text-sm text-gray-600">
{data.count} items
<br />
Quality: {data.quality}
<br />
Relevance: {data.relevance}%
</div>
</div>
))}
</div>
<div className="mt-3 text-sm text-gray-600">
Average Relevance: {researchResults.avg_relevance?.toFixed(1)}%
</div>
</div>
)}
</div>
)}
{/* Agent State Debug */}
{state && Object.keys(state).length > 0 && (
<div className="bg-gray-50 p-4 rounded-lg">
<h3 className="font-medium mb-2">Agent State (Debug)</h3>
<details>
<summary className="cursor-pointer text-sm text-gray-600">Show current state</summary>
<pre className="text-xs text-gray-500 mt-2 overflow-x-auto">
{JSON.stringify(state, null, 2)}
</pre>
</details>
</div>
)}
</div>
</div>
);
}// app/components/MultiAgentCollaboration.tsx
"use client";
import { useCoAgent } from "@copilotkit/react-core";
import { useState } from "react";
export function MultiAgentCollaboration() {
const [project, setProject] = useState<any>({});
const [isPlanning, setIsPlanning] = useState(false);
// Multi-agent project planning system
const { runWorkflow, state } = useCoAgent({
name: "project_planning_team",
description: "Multi-agent team for comprehensive project planning",
workflow: {
// Define multiple agents with different roles
agents: {
product_manager: {
role: "Product Manager",
expertise: "Requirements analysis, user stories, prioritization",
personality: "Strategic, user-focused, business-oriented"
},
architect: {
role: "System Architect",
expertise: "Technical design, scalability, technology selection",
personality: "Technical, forward-thinking, risk-aware"
},
developer: {
role: "Lead Developer",
expertise: "Implementation planning, task breakdown, estimation",
personality: "Practical, detail-oriented, delivery-focused"
},
qa_engineer: {
role: "QA Engineer",
expertise: "Testing strategy, quality assurance, risk assessment",
personality: "Thorough, quality-focused, preventive"
}
},
// Complex workflow with agent interactions
graph: {
nodes: {
requirements_gathering: {
type: "agent",
agent: "product_manager",
prompt: "Analyze the project requirements and create detailed user stories with acceptance criteria."
},
technical_design: {
type: "agent",
agent: "architect",
prompt: "Design the system architecture based on requirements. Consider scalability, security, and technology choices."
},
implementation_planning: {
type: "agent",
agent: "developer",
prompt: "Break down the technical design into implementable tasks with time estimates and dependencies."
},
quality_planning: {
type: "agent",
agent: "qa_engineer",
prompt: "Develop testing strategy and quality assurance plan for the project implementation."
},
risk_assessment: {
type: "action",
action: async (input: any) => {
// Cross-agent risk analysis
const risks = [];
// Technical risks
if (input.technical_complexity > 7) {
risks.push({
category: "Technical",
level: "High",
description: "High technical complexity may impact delivery timeline",
mitigation: "Additional senior developer allocation"
});
}
// Business risks
if (input.market_uncertainty > 6) {
risks.push({
category: "Business",
level: "Medium",
description: "Market uncertainty requires flexible scoping",
mitigation: "Implement MVP-first approach"
});
}
return {
identified_risks: risks,
risk_count: risks.length,
high_priority_risks: risks.filter(r => r.level === "High").length
};
}
},
final_plan_synthesis: {
type: "agent",
agent: "product_manager",
prompt: "Synthesize all planning inputs into a comprehensive project plan with timeline, milestones, and success criteria."
}
},
edges: [
{ from: "requirements_gathering", to: "technical_design" },
{ from: "technical_design", to: "implementation_planning" },
{ from: "implementation_planning", to: "quality_planning" },
{ from: "quality_planning", to: "risk_assessment" },
{ from: "technical_design", to: "risk_assessment" },
{ from: "requirements_gathering", to: "risk_assessment" },
{ from: "risk_assessment", to: "final_plan_synthesis" },
{ from: "implementation_planning", to: "final_plan_synthesis" },
{ from: "quality_planning", to: "final_plan_synthesis" }
]
}
}
});
const handlePlanProject = async () => {
const projectIdea = "Build an AI-powered task management application with real-time collaboration features";
setIsPlanning(true);
try {
const plan = await runWorkflow({
project_idea: projectIdea,
timeline_weeks: 12,
team_size: 5,
budget_level: "medium",
technical_complexity: 6,
market_uncertainty: 4
});
setProject(plan);
} finally {
setIsPlanning(false);
}
};
return (
<div className="p-6 max-w-6xl mx-auto">
<h1 className="text-3xl font-bold mb-6">Multi-Agent Project Planning</h1>
<div className="grid grid-cols-1 lg:grid-cols-2 gap-8">
{/* Planning Interface */}
<div className="space-y-6">
<div className="bg-white p-6 rounded-lg shadow">
<h2 className="text-xl font-semibold mb-4">AI Planning Team</h2>
<p className="text-gray-600 mb-4">
This CoAgent workflow uses multiple AI agents with different roles to create comprehensive project plans.
</p>
<div className="space-y-3 mb-6">
<div className="flex items-center space-x-3">
<div className="w-3 h-3 bg-blue-500 rounded-full"></div>
<span className="text-sm">Product Manager - Requirements & Stories</span>
</div>
<div className="flex items-center space-x-3">
<div className="w-3 h-3 bg-green-500 rounded-full"></div>
<span className="text-sm">System Architect - Technical Design</span>
</div>
<div className="flex items-center space-x-3">
<div className="w-3 h-3 bg-purple-500 rounded-full"></div>
<span className="text-sm">Lead Developer - Implementation Planning</span>
</div>
<div className="flex items-center space-x-3">
<div className="w-3 h-3 bg-orange-500 rounded-full"></div>
<span className="text-sm">QA Engineer - Testing Strategy</span>
</div>
</div>
<button
onClick={handlePlanProject}
disabled={isPlanning}
className="w-full px-6 py-3 bg-gradient-to-r from-blue-500 to-purple-600 text-white rounded-lg hover:from-blue-600 hover:to-purple-700 disabled:from-gray-400 disabled:to-gray-500 disabled:cursor-not-allowed font-medium"
>
{isPlanning ? "Planning in Progress..." : "Start AI Project Planning"}
</button>
</div>
{/* Planning Progress */}
{isPlanning && (
<div className="bg-blue-50 p-6 rounded-lg">
<h3 className="font-semibold text-blue-900 mb-4">Planning Progress</h3>
<div className="space-y-3">
{[
"Product Manager analyzing requirements...",
"System Architect designing architecture...",
"Lead Developer planning implementation...",
"QA Engineer developing testing strategy...",
"Cross-team risk assessment...",
"Final plan synthesis..."
].map((step, index) => (
<div key={index} className="flex items-center space-x-3">
<div className="w-2 h-2 bg-blue-500 rounded-full animate-pulse"></div>
<span className="text-blue-800 text-sm">{step}</span>
</div>
))}
</div>
</div>
)}
</div>
{/* Results Display */}
<div className="space-y-6">
{Object.keys(project).length > 0 && (
<>
{/* Project Overview */}
{project.final_plan && (
<div className="bg-white p-6 rounded-lg shadow">
<h2 className="text-xl font-semibold mb-4">Project Plan Overview</h2>
<div className="space-y-3">
<div>
<span className="font-medium text-gray-700">Timeline:</span>
<span className="ml-2 text-gray-900">{project.final_plan.timeline_weeks} weeks</span>
</div>
<div>
<span className="font-medium text-gray-700">Team Size:</span>
<span className="ml-2 text-gray-900">{project.final_plan.team_size} developers</span>
</div>
<div>
<span className="font-medium text-gray-700">Complexity:</span>
<span className="ml-2 text-gray-900">{project.final_plan.complexity_level}/10</span>
</div>
<div>
<span className="font-medium text-gray-700">Risk Level:</span>
<span className="ml-2 text-gray-900">{project.final_plan.risk_assessment}</span>
</div>
</div>
</div>
)}
{/* Technical Architecture */}
{project.technical_design && (
<div className="bg-white p-6 rounded-lg shadow">
<h3 className="text-lg font-semibold mb-3">Technical Architecture</h3>
<div className="space-y-2 text-sm">
<div><strong>Frontend:</strong> {project.technical_design.frontend}</div>
<div><strong>Backend:</strong> {project.technical_design.backend}</div>
<div><strong>Database:</strong> {project.technical_design.database}</div>
<div><strong>Deployment:</strong> {project.technical_design.deployment}</div>
</div>
</div>
)}
{/* Implementation Tasks */}
{project.implementation_plan && (
<div className="bg-white p-6 rounded-lg shadow">
<h3 className="text-lg font-semibold mb-3">Implementation Plan</h3>
<div className="space-y-2">
{project.implementation_plan.tasks?.slice(0, 5).map((task: any, index: number) => (
<div key={index} className="flex justify-between items-center py-2 border-b border-gray-100 last:border-b-0">
<span className="text-sm">{task.title}</span>
<span className="text-xs bg-gray-100 px-2 py-1 rounded">
{task.estimated_hours}h
</span>
</div>
))}
{project.implementation_plan.tasks?.length > 5 && (
<div className="text-sm text-gray-500 text-center pt-2">
+{project.implementation_plan.tasks.length - 5} more tasks
</div>
)}
</div>
</div>
)}
{/* Risks and Mitigations */}
{project.risk_assessment && (
<div className="bg-red-50 p-6 rounded-lg border border-red-200">
<h3 className="text-lg font-semibold text-red-900 mb-3">Risk Assessment</h3>
<div className="space-y-3">
{project.risk_assessment.identified_risks?.map((risk: any, index: number) => (
<div key={index} className="bg-white p-3 rounded border border-red-100">
<div className="flex justify-between items-start mb-2">
<span className="font-medium text-red-900">{risk.category} Risk</span>
<span className={`px-2 py-1 text-xs rounded ${
risk.level === 'High' ? 'bg-red-100 text-red-800' :
risk.level === 'Medium' ? 'bg-yellow-100 text-yellow-800' :
'bg-green-100 text-green-800'
}`}>
{risk.level}
</span>
</div>
<p className="text-sm text-red-800 mb-2">{risk.description}</p>
<p className="text-sm text-red-700">
<strong>Mitigation:</strong> {risk.mitigation}
</p>
</div>
))}
</div>
</div>
)}
</>
)}
{/* Empty State */}
{Object.keys(project).length === 0 && !isPlanning && (
<div className="bg-gray-50 p-12 rounded-lg border-2 border-dashed border-gray-300 text-center">
<div className="text-6xl mb-4">🤖</div>
<h3 className="text-xl font-medium text-gray-900 mb-2">AI Project Planning</h3>
<p className="text-gray-600 mb-4">
Click the button to see multiple AI agents collaborate on comprehensive project planning.
</p>
<div className="text-sm text-gray-500">
Uses Product Manager, Architect, Developer, and QA Engineer agents
</div>
</div>
)}
</div>
</div>
</div>
);
}In this chapter, we've covered:
- CoAgents Fundamentals: Basic agent workflows with nodes and edges
- LangGraph Integration: Complex agentic workflows with planning and execution
- Multi-Agent Collaboration: Different agents working together on complex tasks
- Workflow Orchestration: Coordinating multiple steps and conditional logic
- Advanced Patterns: Research workflows, project planning, and risk assessment
- Agent Orchestration: CoAgents coordinate multiple AI agents for complex tasks
- LangGraph Power: Graph-based workflows enable sophisticated agent interactions
- Multi-Agent Systems: Different agents with specialized roles and expertise
- Human-in-the-Loop: Workflows can include approval steps and interventions
- Scalable Workflows: Handle complex, multi-step processes with proper state management
- Error Recovery: Built-in error handling and recovery mechanisms
Now that you can build complex agentic workflows, let's explore human-in-the-loop interactions and approval workflows.
Ready for Chapter 7? Human-in-the-Loop
Generated for Awesome Code Docs
Most teams struggle here because the hard part is not writing more code, but deciding clear boundaries for className, text, span so behavior stays predictable as complexity grows.
In practical terms, this chapter helps you avoid three common failures:
- coupling core logic too tightly to one implementation path
- missing the handoff boundaries between setup, execution, and validation
- shipping changes without clear rollback or observability strategy
After working through this chapter, you should be able to reason about Chapter 6: CoAgents & LangGraph - Building Agentic Workflows as an operating subsystem inside CopilotKit Tutorial: Building AI Copilots for React Applications, with explicit contracts for inputs, state transitions, and outputs.
Use the implementation notes around gray, rounded, font as your checklist when adapting these patterns to your own repository.
Under the hood, Chapter 6: CoAgents & LangGraph - Building Agentic Workflows usually follows a repeatable control path:
- Context bootstrap: initialize runtime config and prerequisites for
className. - Input normalization: shape incoming data so
textreceives stable contracts. - Core execution: run the main logic branch and propagate intermediate state through
span. - Policy and safety checks: enforce limits, auth scopes, and failure boundaries.
- Output composition: return canonical result payloads for downstream consumers.
- Operational telemetry: emit logs/metrics needed for debugging and performance tuning.
When debugging, walk this sequence in order and confirm each stage has explicit success/failure conditions.
Use the following upstream sources to verify implementation details while reading this chapter:
- View Repo
Why it matters: authoritative reference on
View Repo(github.com). - Awesome Code Docs
Why it matters: authoritative reference on
Awesome Code Docs(github.com).
Suggested trace strategy:
- search upstream code for
classNameandtextto map concrete implementation paths - compare docs claims against actual runtime/config code before reusing patterns in production