Workflows Dashboard Tutorials

// Create a new agent via API
const response = await fetch('/api/agents', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    name: 'Customer Support Agent',
    description: 'Handles customer inquiries',
    systemPrompt: 'You are a helpful customer support agent.',
    model: 'qwen-72b',
    tools: ['web_search', 'ticket_system'],
    knowledgeBase: 'product_docs'
  })
});
const agent = await response.json();

{
  "name": "Content Generation Pipeline",
  "trigger": { "type": "webhook", "path": "/generate-content" },
  "nodes": [
    { "type": "agent", "agentId": "research-agent", "input": "{{trigger.topic}}" },
    { "type": "agent", "agentId": "writer-agent", "input": "{{nodes[0].output}}" },
    { "type": "tool", "toolId": "image-gen", "input": "{{nodes[1].output.title}}" },
    { "type": "webhook", "url": "https://api.example.com/publish", "body": "{{nodes[1].output}}" }
  ]
}

// Create a RAG collection and upload documents
const collection = await fetch('/api/rag/collections', {
  method: 'POST',
  body: JSON.stringify({ name: 'Product Documentation' })
});

// Upload a document
const formData = new FormData();
formData.append('file', pdfFile);
await fetch(`/api/rag/collections/${collection.id}/documents`, {
  method: 'POST',
  body: formData
});

// Semantic search
const results = await fetch(`/api/rag/collections/${collection.id}/search`, {
  method: 'POST',
  body: JSON.stringify({ query: 'How do I reset my password?' })
});

// Send a chat message with streaming
const response = await fetch('/api/chat/stream', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    agentId: 'support-agent',
    message: 'How do I integrate the API?',
    conversationId: 'conv-123',
    attachments: []
  })
});

// Handle streaming response
const reader = response.body.getReader();
while (true) {
  const { done, value } = await reader.read();
  if (done) break;
  const chunk = new TextDecoder().decode(value);
  console.log(chunk); // Stream tokens
}

// Define a custom tool
const tool = {
  name: 'weather_lookup',
  description: 'Get current weather for a location',
  parameters: {
    type: 'object',
    properties: {
      location: { type: 'string', description: 'City name' }
    },
    required: ['location']
  },
  execute: async (params) => {
    const response = await fetch(
      `https://api.weather.com/current?city=${params.location}`
    );
    return response.json();
  }
};

// Register the tool
await fetch('/api/tools', {
  method: 'POST',
  body: JSON.stringify(tool)
});

// Create a research swarm with hierarchical pattern
const swarm = await fetch('/api/swarms', {
  method: 'POST',
  body: JSON.stringify({
    name: 'Research Team',
    pattern: 'hierarchical',
    leadAgent: 'coordinator-agent',
    workers: [
      { agent: 'web-researcher', role: 'web_search' },
      { agent: 'doc-analyzer', role: 'document_analysis' },
      { agent: 'fact-checker', role: 'verification' }
    ],
    aggregation: 'synthesis'
  })
});

// Trigger a workflow execution
const execution = await fetch('/api/executions', {
  method: 'POST',
  body: JSON.stringify({
    workflowId: 'content-pipeline',
    input: { topic: 'AI Trends 2026' },
    priority: 'high'
  })
});

// Check execution status
const status = await fetch(`/api/executions/${execution.id}`);
console.log(status.state, status.progress);

// Get execution logs
const logs = await fetch(`/api/executions/${execution.id}/logs`);

// Store a memory
await fetch('/api/memory/store', {
  method: 'POST',
  body: JSON.stringify({
    agentId: 'support-agent',
    type: 'knowledge',
    content: 'User prefers email contact over phone',
    metadata: { source: 'conversation', confidence: 0.95 }
  })
});

// Retrieve relevant memories
const memories = await fetch('/api/memory/search', {
  method: 'POST',
  body: JSON.stringify({
    agentId: 'support-agent',
    query: 'user communication preferences',
    limit: 5
  })
});