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Agentic Flows Developer Guide

Agentic Flows Developer Guide

Overview

Package: @bluefly/agentic-flows Version: Latest License: MIT

Multi-Agent Workflow Orchestration with N8N custom nodes for CrewAI, Langflow integration, MLflow experiment tracking, and vector operations.

Key Features

  • Agent Orchestration: CrewAI integration, multi-agent workflows, role-based agents
  • Langflow Integration: N8N nodes for Langflow, visual flow builder, component deployment
  • MLflow Experiment Tracking: Experiment logging, model registry, metrics tracking
  • Vector Operations: Qdrant, Pinecone, Weaviate, Milvus support
  • LLM Integration: Multi-provider support (OpenAI, Anthropic, Ollama, Bedrock)
  • Observability: Phoenix Arize, MLflow tracking, Prometheus metrics

Installation

For N8N Users

cd ~/.n8n/custom npm install @bluefly/agentic-flows n8n start

For Developers

npm install @bluefly/agentic-flows

Quick Start

N8N Node Examples

CrewAI Agent Node

{ "node": "CrewAI Agent", "parameters": { "operation": "executeAgent", "agentRole": "researcher", "goal": "Research market trends", "backstory": "Expert market analyst", "task": "Analyze Q4 2024 AI market trends", "tools": ["search", "calculator"] } }

Vector Search Node

{ "node": "Vector Search", "parameters": { "operation": "search", "database": "qdrant", "collection": "knowledge-base", "query": "How to implement RAG?", "topK": 5, "scoreThreshold": 0.7 } }

Programmatic API

import { AgenticFlows } from '@bluefly/agentic-flows'; const flows = new AgenticFlows({ n8nUrl: 'http://localhost:5678', crewAiUrl: 'http://localhost:8000' }); const workflow = await flows.createWorkflow({ name: 'Research and Analysis', agents: [ { role: 'researcher', goal: 'Gather information', tools: ['web_search', 'arxiv'] }, { role: 'analyst', goal: 'Analyze findings', tools: ['data_analysis'] } ], flow: 'sequential' }); const result = await workflow.execute({ input: 'Analyze AI impact on healthcare' });

Available N8N Nodes

NodePurposeOperations
CrewAI AgentAgent orchestrationCreate, execute, coordinate
Vector SearchSemantic searchIndex, search, update
LLM GatewayLLM operationsGenerate, embed, moderate
RAG PipelineRetrieval augmentationRetrieve, generate, validate
Agent MemoryState managementStore, retrieve, clear
Tool ExecutorTool invocationExecute, validate, retry

Configuration

Environment Variables

# LLM Configuration OPENAI_API_KEY=sk-... ANTHROPIC_API_KEY=sk-ant-... # Vector Databases QDRANT_URL=http://localhost:6333 PINECONE_API_KEY=... # CrewAI CREWAI_API_URL=http://localhost:8000

Langflow + MLflow Integration

Execute Langflow from N8N

const langflowNode = { node: "Execute Langflow", parameters: { workflowId: "my-ai-workflow", inputs: { query: "Analyze market data" }, trackWithMLflow: true } }

MLflow Experiment Tracking

import { MLflowTracker } from '@bluefly/agentic-flows'; const tracker = new MLflowTracker({ trackingUri: 'http://localhost:5000' }); await tracker.startRun({ experimentName: 'CrewAI Research Team', runName: 'market-analysis-2024' }); await tracker.logMetrics({ accuracy: 0.95, cost: 0.42, duration_seconds: 12.5 }); await tracker.endRun();

Testing

npm test npm run test:coverage npm run lint

Deployment

Kubernetes

kubectl create namespace agentic-flows kubectl apply -f infrastructure/kubernetes/ -n agentic-flows

Documentation