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
| Node | Purpose | Operations |
|---|---|---|
| CrewAI Agent | Agent orchestration | Create, execute, coordinate |
| Vector Search | Semantic search | Index, search, update |
| LLM Gateway | LLM operations | Generate, embed, moderate |
| RAG Pipeline | Retrieval augmentation | Retrieve, generate, validate |
| Agent Memory | State management | Store, retrieve, clear |
| Tool Executor | Tool invocation | Execute, 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
- GitLab: https://gitlab.com/blueflyio/agent-platform/agentic-flows
- OpenAPI Specs: openapi/