Agent API Reference

The AgenticFlow Agents API provides comprehensive programmatic access to agent creation, management, and execution capabilities. Build, deploy, and orchestrate AI agents at scale with full enterprise-grade API functionality.

🎯 API Overview

The Agents API enables:

🔧 Agent Lifecycle Management - Create, configure, update, and deploy agents
💬 Conversation Management - Handle multi-turn conversations with memory
📊 Execution Control - Monitor, control, and optimize agent performance
🔗 Integration Management - Configure tools, knowledge, and external connections
📈 Analytics & Monitoring - Track usage, performance, and business metrics

Base URL: https://api.agenticflow.ai/v1 Authentication: Bearer token (API key required) Rate Limits: 1000 requests/minute (enterprise limits available)

🔐 Authentication

API Key Setup

# Set your API key as environment variable
export AGENTICFLOW_API_KEY="af_live_your_api_key_here"

# Include in request headers
curl -H "Authorization: Bearer af_live_your_api_key_here" \
     https://api.agenticflow.ai/v1/agents

Authentication Headers

{
  "headers": {
    "Authorization": "Bearer af_live_your_api_key_here",
    "Content-Type": "application/json",
    "User-Agent": "YourApp/1.0.0"
  }
}

API Key Types:

Development Keys (af_test_*) - Sandbox environment, no charges
Production Keys (af_live_*) - Live environment, usage charges apply
Workspace Keys (af_ws_*) - Workspace-specific access and limits

🤖 Agent Management

Create Agent

Create a new AI agent with complete configuration.

Endpoint: POST /agents

const agent = await fetch('https://api.agenticflow.ai/v1/agents', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer af_live_your_api_key',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    name: "Customer Support Specialist",
    description: "AI agent specialized in customer service and support",
    model: "claude-3-5-sonnet-20241022",
    system_prompt: "You are a helpful customer support agent. Always be polite, professional, and solution-focused.",
    configuration: {
      temperature: 0.3,
      max_tokens: 2000,
      response_format: "text"
    },
    knowledge_base_ids: ["kb_customer_policies", "kb_product_docs"],
    tool_ids: ["tool_crm_lookup", "tool_order_status"],
    tags: ["customer_service", "production"],
    is_active: true
  })
});

const response = await agent.json();

Request Body:

{
  "name": "string (required)",
  "description": "string (optional)",
  "model": "string (required)",
  "system_prompt": "string (optional)",
  "configuration": {
    "temperature": "number (0-1)",
    "max_tokens": "number (1-4000)",
    "response_format": "text|json_object",
    "timeout": "number (seconds)"
  },
  "knowledge_base_ids": ["string"],
  "tool_ids": ["string"], 
  "workflow_ids": ["string"],
  "tags": ["string"],
  "is_active": "boolean",
  "metadata": "object"
}

Response:

{
  "id": "agent_clx8k2n4m0001js0h3q5j4k8r",
  "name": "Customer Support Specialist",
  "description": "AI agent specialized in customer service and support",
  "model": "claude-3-5-sonnet-20241022",
  "system_prompt": "You are a helpful customer support agent...",
  "configuration": {
    "temperature": 0.3,
    "max_tokens": 2000,
    "response_format": "text"
  },
  "knowledge_base_ids": ["kb_customer_policies", "kb_product_docs"],
  "tool_ids": ["tool_crm_lookup", "tool_order_status"],
  "tags": ["customer_service", "production"],
  "is_active": true,
  "created_at": "2024-01-15T10:30:00Z",
  "updated_at": "2024-01-15T10:30:00Z",
  "workspace_id": "ws_main_workspace"
}

List Agents

Retrieve all agents with filtering and pagination.

Endpoint: GET /agents

const agents = await fetch('https://api.agenticflow.ai/v1/agents?' + new URLSearchParams({
  limit: '50',
  offset: '0',
  tags: 'customer_service,production',
  is_active: 'true',
  sort: 'created_at_desc'
}), {
  headers: {
    'Authorization': 'Bearer af_live_your_api_key'
  }
});

const response = await agents.json();

Query Parameters:

limit (integer, 1-100): Number of agents to return (default: 50)
offset (integer): Number of agents to skip (default: 0)
tags (string): Comma-separated list of tags to filter by
is_active (boolean): Filter by active status
search (string): Search in agent names and descriptions
model (string): Filter by AI model
sort (string): Sort order (created_at_asc, created_at_desc, name_asc, name_desc)

Response:

{
  "data": [
    {
      "id": "agent_clx8k2n4m0001js0h3q5j4k8r",
      "name": "Customer Support Specialist",
      "description": "AI agent specialized in customer service and support",
      "model": "claude-3-5-sonnet-20241022",
      "is_active": true,
      "created_at": "2024-01-15T10:30:00Z",
      "tags": ["customer_service", "production"]
    }
  ],
  "pagination": {
    "total": 127,
    "limit": 50,
    "offset": 0,
    "has_more": true
  }
}

Get Agent

Retrieve detailed information about a specific agent.

Endpoint: GET /agents/{agent_id}

const agent = await fetch('https://api.agenticflow.ai/v1/agents/agent_clx8k2n4m0001js0h3q5j4k8r', {
  headers: {
    'Authorization': 'Bearer af_live_your_api_key'
  }
});

const response = await agent.json();

Response (full agent object with all configuration details)

Update Agent

Modify an existing agent's configuration.

Endpoint: PUT /agents/{agent_id}

const updatedAgent = await fetch('https://api.agenticflow.ai/v1/agents/agent_clx8k2n4m0001js0h3q5j4k8r', {
  method: 'PUT',
  headers: {
    'Authorization': 'Bearer af_live_your_api_key',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    system_prompt: "Updated system prompt with new instructions...",
    configuration: {
      temperature: 0.5,
      max_tokens: 3000
    },
    tool_ids: ["tool_crm_lookup", "tool_order_status", "tool_knowledge_search"]
  })
});

Request Body: Same as create agent, all fields optional (only provided fields will be updated)

Delete Agent

Permanently delete an agent (irreversible action).

Endpoint: DELETE /agents/{agent_id}

const deletion = await fetch('https://api.agenticflow.ai/v1/agents/agent_clx8k2n4m0001js0h3q5j4k8r', {
  method: 'DELETE',
  headers: {
    'Authorization': 'Bearer af_live_your_api_key'
  }
});

// Returns 204 No Content on success

💬 Conversation Management

Start Conversation

Begin a new conversation with an agent.

Endpoint: POST /agents/{agent_id}/conversations

const conversation = await fetch('https://api.agenticflow.ai/v1/agents/agent_clx8k2n4m0001js0h3q5j4k8r/conversations', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer af_live_your_api_key',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    message: "Hello! I need help with my recent order #12345. It seems to be delayed.",
    context: {
      user_id: "user_12345",
      session_id: "session_abc123",
      metadata: {
        order_id: "12345",
        customer_tier: "premium"
      }
    },
    options: {
      stream: false,
      include_tool_calls: true,
      max_turns: 10
    }
  })
});

const response = await conversation.json();

Request Body:

{
  "message": "string (required)",
  "context": {
    "user_id": "string (optional)",
    "session_id": "string (optional)", 
    "metadata": "object (optional)"
  },
  "options": {
    "stream": "boolean (default: false)",
    "include_tool_calls": "boolean (default: true)",
    "max_turns": "number (default: 100)",
    "temperature_override": "number (optional)"
  }
}

Response:

{
  "conversation_id": "conv_clx8k2n4m0001js0h3q5j4k8r",
  "message": {
    "id": "msg_clx8k2n4m0002js0h3q5j4k8s",
    "role": "assistant",
    "content": "I'd be happy to help you check on your order #12345. Let me look up the current status for you.",
    "tool_calls": [
      {
        "id": "call_order_status_12345",
        "function": "order_status",
        "arguments": {
          "order_id": "12345"
        },
        "result": {
          "status": "in_transit",
          "expected_delivery": "2024-01-18",
          "tracking_number": "1Z999AA123456789"
        }
      }
    ],
    "created_at": "2024-01-15T10:35:22Z"
  },
  "usage": {
    "prompt_tokens": 245,
    "completion_tokens": 87,
    "total_tokens": 332,
    "cost": 0.00234
  }
}

Continue Conversation

Add a message to an existing conversation.

Endpoint: POST /conversations/{conversation_id}/messages

const message = await fetch('https://api.agenticflow.ai/v1/conversations/conv_clx8k2n4m0001js0h3q5j4k8r/messages', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer af_live_your_api_key',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    message: "That's great! Can you also check if I can expedite the shipping?",
    options: {
      include_context: true,
      temperature_override: 0.2
    }
  })
});

Get Conversation History

Retrieve the complete conversation thread.

Endpoint: GET /conversations/{conversation_id}

const conversation = await fetch('https://api.agenticflow.ai/v1/conversations/conv_clx8k2n4m0001js0h3q5j4k8r', {
  headers: {
    'Authorization': 'Bearer af_live_your_api_key'
  }
});

const response = await conversation.json();

Response:

{
  "id": "conv_clx8k2n4m0001js0h3q5j4k8r",
  "agent_id": "agent_clx8k2n4m0001js0h3q5j4k8r",
  "messages": [
    {
      "id": "msg_1",
      "role": "user", 
      "content": "Hello! I need help with my recent order #12345...",
      "created_at": "2024-01-15T10:35:00Z"
    },
    {
      "id": "msg_2",
      "role": "assistant",
      "content": "I'd be happy to help you check on your order...",
      "tool_calls": [...],
      "created_at": "2024-01-15T10:35:22Z"
    }
  ],
  "context": {
    "user_id": "user_12345",
    "session_id": "session_abc123"
  },
  "created_at": "2024-01-15T10:35:00Z",
  "updated_at": "2024-01-15T10:36:45Z"
}

Streaming Conversations

Real-time streaming responses for live conversations.

const response = await fetch('https://api.agenticflow.ai/v1/agents/agent_clx8k2n4m0001js0h3q5j4k8r/conversations', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer af_live_your_api_key',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    message: "Explain quantum computing in simple terms",
    options: {
      stream: true
    }
  })
});

// Handle Server-Sent Events
const reader = response.body.getReader();
const decoder = new TextDecoder();

while (true) {
  const { value, done } = await reader.read();
  if (done) break;
  
  const chunk = decoder.decode(value);
  const lines = chunk.split('\n');
  
  for (const line of lines) {
    if (line.startsWith('data: ')) {
      const data = JSON.parse(line.slice(6));
      
      if (data.type === 'message_delta') {
        process.stdout.write(data.content);
      } else if (data.type === 'tool_call') {
        console.log('\n[Tool Call]', data.function_name);
      } else if (data.type === 'message_complete') {
        console.log('\n[Usage]', data.usage);
      }
    }
  }
}

Streaming Event Types:

message_start - Conversation beginning
message_delta - Incremental content chunks
tool_call_start - Tool execution beginning
tool_call_result - Tool execution result
message_complete - Response finished with metadata

🔧 Agent Configuration

Update Agent Configuration

Modify agent settings without changing core properties.

Endpoint: PATCH /agents/{agent_id}/configuration

const config = await fetch('https://api.agenticflow.ai/v1/agents/agent_clx8k2n4m0001js0h3q5j4k8r/configuration', {
  method: 'PATCH',
  headers: {
    'Authorization': 'Bearer af_live_your_api_key',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    temperature: 0.7,
    max_tokens: 3000,
    response_format: "json_object",
    timeout: 30,
    custom_settings: {
      "persona": "friendly_expert",
      "language_style": "professional_casual",
      "response_length": "detailed"
    }
  })
});

Manage Agent Knowledge Base

Add or remove knowledge bases from an agent.

Endpoint: POST /agents/{agent_id}/knowledge

// Add knowledge bases
const knowledge = await fetch('https://api.agenticflow.ai/v1/agents/agent_clx8k2n4m0001js0h3q5j4k8r/knowledge', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer af_live_your_api_key',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    knowledge_base_ids: ["kb_new_policies", "kb_troubleshooting"],
    operation: "add"
  })
});

// Remove knowledge bases  
const removal = await fetch('https://api.agenticflow.ai/v1/agents/agent_clx8k2n4m0001js0h3q5j4k8r/knowledge', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer af_live_your_api_key',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    knowledge_base_ids: ["kb_old_policies"],
    operation: "remove"
  })
});

Manage Agent Tools

Configure tools and integrations for an agent.

Endpoint: POST /agents/{agent_id}/tools

const tools = await fetch('https://api.agenticflow.ai/v1/agents/agent_clx8k2n4m0001js0h3q5j4k8r/tools', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer af_live_your_api_key',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    tools: [
      {
        id: "tool_slack_notification",
        configuration: {
          channel: "#customer-alerts",
          mention_team: true
        }
      },
      {
        id: "tool_crm_update",
        configuration: {
          auto_create_tickets": true,
          priority_mapping": "customer_tier_based"
        }
      }
    ],
    operation: "replace"
  })
});

📊 Analytics and Monitoring

Agent Performance Metrics

Get detailed performance analytics for an agent.

Endpoint: GET /agents/{agent_id}/analytics

const analytics = await fetch('https://api.agenticflow.ai/v1/agents/agent_clx8k2n4m0001js0h3q5j4k8r/analytics?' + new URLSearchParams({
  start_date: '2024-01-01',
  end_date: '2024-01-31',
  granularity: 'daily',
  metrics: 'conversations,tokens,cost,satisfaction'
}), {
  headers: {
    'Authorization': 'Bearer af_live_your_api_key'
  }
});

const response = await analytics.json();

Query Parameters:

start_date (string): Start date (YYYY-MM-DD)
end_date (string): End date (YYYY-MM-DD)
granularity (string): hourly, daily, weekly, monthly
metrics (string): Comma-separated metrics to include

Response:

{
  "agent_id": "agent_clx8k2n4m0001js0h3q5j4k8r",
  "period": {
    "start_date": "2024-01-01",
    "end_date": "2024-01-31"
  },
  "metrics": {
    "conversations": {
      "total": 1247,
      "successful": 1198,
      "failed": 49,
      "average_length": 4.2,
      "success_rate": 0.961
    },
    "tokens": {
      "total_tokens": 892340,
      "prompt_tokens": 534220,
      "completion_tokens": 358120,
      "average_per_conversation": 715
    },
    "cost": {
      "total_cost": 23.45,
      "average_per_conversation": 0.019,
      "cost_breakdown": {
        "model_usage": 21.30,
        "tool_calls": 1.89,
        "knowledge_base": 0.26
      }
    },
    "satisfaction": {
      "average_rating": 4.6,
      "total_ratings": 892,
      "rating_distribution": {
        "5": 623,
        "4": 189,
        "3": 56,
        "2": 18,
        "1": 6
      }
    }
  },
  "time_series": [
    {
      "date": "2024-01-01",
      "conversations": 42,
      "tokens": 28934,
      "cost": 0.78,
      "average_satisfaction": 4.7
    }
  ]
}

Usage Tracking

Track detailed usage metrics for billing and optimization.

Endpoint: GET /agents/{agent_id}/usage

const usage = await fetch('https://api.agenticflow.ai/v1/agents/agent_clx8k2n4m0001js0h3q5j4k8r/usage?' + new URLSearchParams({
  period: 'last_30_days',
  breakdown: 'by_model,by_tool,by_user'
}), {
  headers: {
    'Authorization': 'Bearer af_live_your_api_key'
  }
});

Real-Time Monitoring

Monitor agent health and performance in real-time.

Endpoint: GET /agents/{agent_id}/status

const status = await fetch('https://api.agenticflow.ai/v1/agents/agent_clx8k2n4m0001js0h3q5j4k8r/status', {
  headers: {
    'Authorization': 'Bearer af_live_your_api_key'
  }
});

const response = await status.json();

Response:

{
  "agent_id": "agent_clx8k2n4m0001js0h3q5j4k8r",
  "status": "active",
  "health": "healthy",
  "current_load": {
    "active_conversations": 23,
    "queued_requests": 2,
    "average_response_time": "1.2s"
  },
  "performance": {
    "success_rate_24h": 0.98,
    "average_rating_24h": 4.7,
    "error_rate_24h": 0.02
  },
  "resource_usage": {
    "credits_used_today": 1247,
    "quota_remaining": 8753,
    "rate_limit_status": "normal"
  },
  "last_activity": "2024-01-15T10:45:23Z"
}

🔗 Batch Operations

Bulk Agent Management

Manage multiple agents in a single API call.

Endpoint: POST /agents/batch

const batchOperation = await fetch('https://api.agenticflow.ai/v1/agents/batch', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer af_live_your_api_key',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    operation: "update",
    agents: [
      {
        id: "agent_1",
        changes: {
          is_active: false,
          tags: ["deprecated"]
        }
      },
      {
        id: "agent_2", 
        changes: {
          system_prompt: "Updated prompt for agent 2",
          configuration: {
            temperature: 0.5
          }
        }
      }
    ],
    options: {
      continue_on_error: true,
      return_details: true
    }
  })
});

const response = await batchOperation.json();

Response:

{
  "batch_id": "batch_clx8k2n4m0001js0h3q5j4k8r",
  "status": "completed",
  "results": [
    {
      "agent_id": "agent_1",
      "status": "success",
      "message": "Agent updated successfully"
    },
    {
      "agent_id": "agent_2",
      "status": "error",
      "message": "Invalid temperature value",
      "error_code": "INVALID_CONFIGURATION"
    }
  ],
  "summary": {
    "total": 2,
    "successful": 1,
    "failed": 1
  }
}

Bulk Conversation Processing

Process multiple conversations simultaneously.

Endpoint: POST /conversations/batch

const batchConversations = await fetch('https://api.agenticflow.ai/v1/conversations/batch', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer af_live_your_api_key',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    conversations: [
      {
        agent_id: "agent_clx8k2n4m0001js0h3q5j4k8r",
        message: "Process this customer feedback: Customer loves the new features!",
        context: { customer_id: "cust_123" }
      },
      {
        agent_id: "agent_clx8k2n4m0001js0h3q5j4k8r", 
        message: "Analyze this support ticket: Website is loading slowly",
        context: { ticket_id: "tick_456" }
      }
    ],
    options: {
      parallel_processing: true,
      max_concurrent: 10
    }
  })
});

⚙️ Advanced Features

Agent Templates

Create and manage reusable agent templates.

Endpoint: POST /agent-templates

const template = await fetch('https://api.agenticflow.ai/v1/agent-templates', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer af_live_your_api_key',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    name: "Customer Support Agent Template",
    description: "Standard template for customer support agents",
    category: "customer_service",
    template: {
      model: "claude-3-5-sonnet-20241022",
      system_prompt: "You are a professional customer support agent...",
      configuration: {
        temperature: 0.3,
        max_tokens: 2000
      },
      required_tools: ["tool_crm_lookup", "tool_order_status"],
      recommended_knowledge: ["kb_customer_policies", "kb_faq"]
    },
    variables: {
      "company_name": {
        "type": "string",
        "required": true,
        "description": "Name of the company"
      },
      "support_email": {
        "type": "string", 
        "required": false,
        "description": "Support team email address"
      }
    }
  })
});

Agent Deployment

Deploy agents to different environments.

Endpoint: POST /agents/{agent_id}/deploy

const deployment = await fetch('https://api.agenticflow.ai/v1/agents/agent_clx8k2n4m0001js0h3q5j4k8r/deploy', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer af_live_your_api_key',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    environment: "production",
    configuration: {
      auto_scaling: true,
      max_concurrent_conversations: 100,
      health_check_interval: 30,
      deployment_strategy: "blue_green"
    },
    notifications: {
      deployment_complete: ["[email protected]"],
      deployment_failed: ["[email protected]"]
    }
  })
});

A/B Testing

Set up A/B tests for agent optimization.

Endpoint: POST /agents/{agent_id}/experiments

const experiment = await fetch('https://api.agenticflow.ai/v1/agents/agent_clx8k2n4m0001js0h3q5j4k8r/experiments', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer af_live_your_api_key',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    name: "Temperature Optimization Test",
    description: "Testing different temperature values for response quality",
    variants: [
      {
        name: "control",
        weight: 50,
        configuration: {
          temperature: 0.3
        }
      },
      {
        name: "warmer",
        weight: 50,
        configuration: {
          temperature: 0.7
        }
      }
    ],
    success_metrics: ["satisfaction_rating", "conversation_completion_rate"],
    duration_days: 14,
    minimum_sample_size: 1000
  })
});

📚 SDK Examples

Python SDK

import agenticflow

# Initialize client
client = agenticflow.Client(api_key="af_live_your_api_key")

# Create agent
agent = client.agents.create(
    name="Support Agent",
    model="claude-3-5-sonnet-20241022",
    system_prompt="You are a helpful support agent.",
    knowledge_base_ids=["kb_support_docs"]
)

# Start conversation
conversation = agent.conversations.create(
    message="How do I reset my password?"
)

print(f"Agent response: {conversation.message.content}")

# Continue conversation
follow_up = conversation.messages.create(
    message="I tried that but it didn't work."
)

print(f"Follow-up response: {follow_up.content}")

Node.js SDK

const AgenticFlow = require('agenticflow');

// Initialize client
const client = new AgenticFlow({
  apiKey: 'af_live_your_api_key'
});

async function main() {
  // Create agent
  const agent = await client.agents.create({
    name: 'Support Agent',
    model: 'claude-3-5-sonnet-20241022',
    systemPrompt: 'You are a helpful support agent.',
    knowledgeBaseIds: ['kb_support_docs']
  });

  // Start conversation with streaming
  const conversation = await client.agents.conversations.create(agent.id, {
    message: 'How do I reset my password?',
    options: { stream: true }
  });

  // Handle streaming response
  for await (const chunk of conversation) {
    if (chunk.type === 'message_delta') {
      process.stdout.write(chunk.content);
    }
  }
}

main().catch(console.error);

❌ Error Handling

Error Response Format

{
  "error": {
    "code": "INVALID_REQUEST",
    "message": "The model 'invalid-model' is not supported",
    "details": {
      "field": "model",
      "supported_models": ["gpt-4", "claude-3-5-sonnet", "gemini-pro"]
    },
    "request_id": "req_clx8k2n4m0001js0h3q5j4k8r"
  }
}

Common Error Codes

INVALID_REQUEST (400) - Malformed request or invalid parameters
UNAUTHORIZED (401) - Invalid or missing API key
FORBIDDEN (403) - Insufficient permissions
NOT_FOUND (404) - Resource not found
RATE_LIMITED (429) - Too many requests
QUOTA_EXCEEDED (429) - Credit or usage limit reached
INTERNAL_ERROR (500) - Server error
SERVICE_UNAVAILABLE (503) - Temporary service issue

Error Handling Best Practices

async function createAgentWithRetry(agentData, maxRetries = 3) {
  for (let attempt = 1; attempt <= maxRetries; attempt++) {
    try {
      const response = await fetch('https://api.agenticflow.ai/v1/agents', {
        method: 'POST',
        headers: {
          'Authorization': 'Bearer af_live_your_api_key',
          'Content-Type': 'application/json'
        },
        body: JSON.stringify(agentData)
      });

      if (!response.ok) {
        const error = await response.json();
        
        // Don't retry client errors (4xx)
        if (response.status >= 400 && response.status < 500) {
          throw new Error(`Client Error: ${error.error.message}`);
        }
        
        // Retry server errors (5xx) and rate limits
        if (attempt === maxRetries) {
          throw new Error(`Max retries exceeded: ${error.error.message}`);
        }
        
        // Exponential backoff
        await new Promise(resolve => setTimeout(resolve, Math.pow(2, attempt) * 1000));
        continue;
      }

      return await response.json();
      
    } catch (error) {
      if (attempt === maxRetries) {
        throw error;
      }
    }
  }
}

🚀 Next Steps & Resources

📚 Continue Learning

Workflows API - Automate complex business processes
Knowledge API - Manage knowledge bases and RAG systems
Integrations API - Connect to external services

🛠️ Development Tools

API Playground - Interactive API testing
Postman Collection - Pre-built API requests
OpenAPI Schema - Complete API specification

💬 Developer Support

Developer Discord - Community support and discussions
API Status Page - Real-time API status and incidents
Developer Support - Technical assistance and guidance

🤖 The Agents API provides complete programmatic control over AgenticFlow's sophisticated AI agent capabilities. From simple chatbots to complex enterprise automation systems, you have the power to build, deploy, and scale AI agents that transform how your business operates.

Build the future of AI automation, one API call at a time.

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Last updated 15 hours ago

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